ACKNOWLEDGEMENTS

21 Mar 2024

Submitted by (Bold are A*STAR Staff): Jian Zhang, Haochun Zhang, Jie Xiong, Shuai Chen and Gang Zhang

Research Institute: IHPC

Title of Paper: Theoretical insights into the lattice thermal conductivity and thermal expansion of CoNiFe medium-entropy alloys

Publish in: Materials Advances

Abstract: Medium-entropy alloys (MEAs) have important potential applications in aerospace as well as nuclear energy due to their excellent mechanical and thermodynamic properties. In this paper, we calculate the lattice thermal conductivity of CoNiFe MEA using the equilibrium molecular dynamics method. We investigate the impact of the elemental concentration in MEAs (Co1.5NiFe, CoNi1.5Fe, and CoNiFe1.5) on their lattice thermal conductivity. Increasing the Co and Fe concentration will slightly decrease the lattice thermal conductivity. On the other hand, by increasing the Ni concentration, its lattice thermal conductivity increases up to 17%. Such anomalous lattice thermal conductivity enhancement is explained by an increase in the mode participation rate and acoustic phonon lifetime. Moreover, the impacts of tensile strain and temperature on lattice thermal conductivity are explored. This study contributes to the understanding of the thermal behavior of MEAs and promotes the development of MEAs in the field of thermal science.

URL: https://doi.org/10.1039/D4MA00167B

20 Mar 2024

Submitted by (Bold are A*STAR Staff): Changhong Linghu, Yangchengyi Liu, Xudong Yang, Dong Li, Yee Yuan Tan, Haziq Bin Mohamed Hafiz Mohamed, Fadhli Bin Rohani Mohammad, Zihao Du, Jiangtao Su, Yan Li, Yucheng Huo, Hanyan Xu, Xiufeng Wang, Yifan Wang, Jing Yu, Huajian Gao, K Jimmy Hsia

Research Institute: IHPC

Title of Paper: Fibrillar adhesives with unprecedented adhesion strength, switchability and scalability

Publish in: National Science Review

Abstract: Bio-inspired fibrillar adhesives have received worldwide attention but their potentials have been limited by a trade-off between adhesion strength and adhesion switchability, and a size scale effect that restricts the fibrils to micro/nanoscales. Here, we report a class of adhesive fibrils that achieve unprecedented adhesion strength (∼2 MPa), switchability (∼2000), and scalability (up to millimeter-scale at the single fibril level), by leveraging the rubber-to-glass (R2G) transition in shape memory polymers (SMPs). Moreover, R2G SMP fibrillar adhesive arrays exhibit a switchability of >1000 (with the aid of controlled buckling) and an adhesion efficiency of 57.8%, with apparent contact area scalable to 1000 mm2, outperforming existing fibrillar adhesives. We further demonstrate that the SMP fibrillar adhesives can be used as soft grippers and reusable superglue devices that are capable of holding and releasing heavy objects more than 2000 times of their own weight. These findings represent significant advances in smart fibrillar adhesives for numerous applications, especially those involving high-payload scenarios.

URL: https://doi.org/10.1093/nsr/nwae106

11 Mar 2024

Submitted by (Bold are A*STAR Staff): Jinghan Huang, Qiufeng Chen, Yijun Bian, Pengli Zhu, Nanguang Chen, Moo K. Chung, Anqi Qiu

Research Institute: -- 

Title of Paper: Advancing Graph Neural Networks with HL-HGAT: A Hodge-Laplacian and Attention Mechanism Approach for Heterogeneous Graph-Structured Data

Publish in: arXIV Computer Science

Abstract: Graph neural networks (GNNs) have proven effective in capturing relationships among nodes in a graph. This study introduces a novel perspective by considering a graph as a simplicial complex, encompassing nodes, edges, triangles, and k-simplices, enabling the definition of graph-structured data on any k-simplices. Our contribution is the Hodge-Laplacian heterogeneous graph attention network (HL-HGAT), designed to learn heterogeneous signal representations across k-simplices. The HL-HGAT incorporates three key components: HL convolutional filters (HL-filters), simplicial projection (SP), and simplicial attention pooling (SAP) operators, applied to k-simplices. HL-filters leverage the unique topology of k-simplices encoded by the Hodge-Laplacian (HL) operator, operating within the spectral domain of the k-th HL operator. To address computation challenges, we introduce a polynomial approximation for HL-filters, exhibiting spatial localization properties. Additionally, we propose a pooling operator to coarsen k-simplices, combining features through simplicial attention mechanisms of self-attention and cross-attention via transformers and SP operators, capturing topological interconnections across multiple dimensions of simplices. The HL-HGAT is comprehensively evaluated across diverse graph applications, including NP-hard problems, graph multi-label and classification challenges, and graph regression tasks in logistics, computer vision, biology, chemistry, and neuroscience. The results demonstrate the model's efficacy and versatility in handling a wide range of graph-based scenarios.

URL: https://doi.org/10.48550/arXiv.2403.06687

11 Mar 2024

Submitted by (Bold are A*STAR Staff): Fabio Bussolotti, Hiroyo Kawai, Thathsara D. Maddumapatabandi, Wei Fu, Khoong Hong Khoo, and Kuan Eng Johnson Goh

Research Institute: IHPC, IMRE

Title of Paper: Role of S-Vacancy Concentration in Air Oxidation of WS2 Single Crystals

Publish in: ACS Nano

Abstract: Semiconducting transition metal dichalcogenides (TMDs) are a class of two-dimensional materials with potential applications in optoelectronics, spintronics, valleytronics, and quantum information processing. Understanding their stability under ambient conditions is critical for determining their in-air processability during device fabrication and for predicting their long-term device performance stability. While the effects of environmental conditions (i.e., oxygen, moisture, and light) on TMD degradation are well-acknowledged, the role of defects in driving their oxidation remains unclear. We conducted a systematic X-ray photoelectron spectroscopy study on WS2 single crystals with different surface S-vacancy concentrations formed via controlled argon sputtering. Oxidation primarily occurred at defect concentrations ≥ 10%, resulting in stoichiometric WO3 formation, while a stable surface was observed at lower concentrations. Theoretical calculations informed us that single S-vacancies do not spontaneously oxidize, while defect pairing at high vacancy concentrations facilitates O2 dissociation and subsequent oxide formation. Our XPS results also point to vacancy-related structural and electrostatic disorder as the main origin for the p-type characteristics that persists even after oxidation. Despite the complex interplay between defects and TMD oxidation processes, our work unveils scientifically informed guidance for working effectively with TMDs.

URL: https://doi.org/10.1021/acsnano.3c10389

04 Mar 2024

Submitted by (Bold are A*STAR Staff): Dr. Min Wang, Dr. Zhongbo Zhang, Dr. Jing Lyu, Jian Qiu, Chang Gu, He Zhao, Dr. Tao Wang, Yiwen Ren, Prof. Shuo-Wang Yang, Prof. Guo Qin Xu, Prof. Xiaogang Liu

Research Institute: IHPC

Title of Paper: Overcoming Thermal Quenching in X-ray Scintillators through Multi-Excited State Switching

Publish in: Communication

Abstract: X-ray scintillators have gained significant attention in medical diagnostics and industrial applications. Despite their widespread utility, scintillator development faces a significant hurdle when exposed to elevated temperatures, as it usually results in reduced scintillation efficiency and diminished luminescence output. Here we report a molecular design strategy based on a hybrid perovskite (TpyBiCl5) that overcomes thermal quenching through multi-excited state switching. The structure of perovskite provides a platform to modulate the luminescence centers. The rigid framework constructed by this perovskite structure stabilized its triplet states, resulting in TpyBiCl5 exhibiting an approximately 12 times higher (45 % vs. 3.8 %) photoluminescence quantum yield of room temperature phosphorescence than that of its organic ligand (Tpy). Most importantly, the interactions between the components of this perovskite enable the mixing of different excited states, which has been revealed by experimental and theoretical investigations. The TpyBiCl5 scintillator exhibits a detection limit of 38.92 nGy s−1 at 213 K and a detection limit of 196.31 nGy s−1 at 353 K through scintillation mode switching between thermally activated delayed fluorescence and phosphorescence. This work opens up the possibility of solving the thermal quenching in X-ray scintillators by tuning different excited states.

URL: https://doi.org/10.1002/anie.202401949

26 Feb 2024

Submitted by (Bold are A*STAR Staff): Zicong Marvin Wonga, Gang Wua, Ramanarayan Hariharaputrana

Research Institute: IHPC

Title of Paper: Unravelling the Polarity Preference and Effects of Electrode Layer on Wurtzite Aluminum Nitride for Piezoelectric Applications

Publish in: Materials Advances

Abstract: Aluminum nitride (AlN) is a promising material for electromechanical and optoelectronic applications due to its exceptional properties. The stability and control of the polarity of AlN surfaces, as well as the interactions between AlN and electrode layers, are critical for optimizing device performance. In this study, we investigate the properties of electrode layers on AlN slabs and their impact on the stability and polarity preferences of AlN surfaces. Using first principles simulations, we calculate the formation energies of various electrode layers on AlN slabs and analyze the resulting trends. Additionally, we examine the Bader charges of the electrode layers to gain insights into the nature of the interface interactions. Our findings reveal that the interaction between the electrode layer and AlN slab is thermodynamically favorable and mainly electrostatic or ionic in nature. The preferred stacking sequence of the electrode layer elements on Al-polar AlN slabs aligns with the overall Wurtzite structure of the AlN slabs, minimizing lattice distortion and destabilization. The variation in Bader charge of the interfacial Al atoms on N-polar AlN slabs with electrode layer elements of different electronegativities could impact the interface polarization and piezoelectric properties. By considering electronegativity or Bader charges of the electrodes, the design of AlN slabs with preferred polarity can be achieved. This study provides valuable insights into the design and optimization of AlN-based electronic and piezoelectric devices.

URL: https://doi.org/10.1039/D3MA00842H

23 Feb 2024

Submitted by (Bold are A*STAR Staff): Tong-De Tan, Juan M. I. Serviano, Xiaohua Luo, Peng-Cheng Qian, Patrick L. Holland, Xinglong Zhang, Ming Joo Koh

Research Institute: IHPC

Title of Paper: Congested C(sp3)-rich architectures enabled by iron-catalysed conjunctive alkylation

Publish in: Nature Catalysis

Abstract: Catalytic cross-coupling by transition metals has revolutionized the formation of carbon–carbon bonds in organic synthesis. However, the challenge of forming multiple alkyl–alkyl bonds in crowded environments remains largely unresolved. Here we report the regioselective functionalization of olefins with sp3-hybridized organohalides and organozinc reagents using a simple (terpyridine)iron catalyst. Aliphatic groups of various sizes are successfully installed on either olefinic carbon, furnishing a diverse array of products with congested cores featuring carbon- or heteroatom-substituted stereocentres. The method enables access to valuable but synthetically challenging C(sp3)-rich molecules, including alicyclic compounds bearing multiple contiguous stereocentres, through annulation cascades. Mechanistic and theoretical studies suggest a stepwise iron-mediated radical carbometallation pathway followed by outer-sphere carbon–carbon bond formation, which potentially opens the door to a broader scope of transformations and new chemical space.

URL: https://doi.org/10.1038/s41929-024-01113-8

12 Feb 2024

Submitted by (Bold are A*STAR Staff): Qun Li, Chunyan Deng, Wenyu Zhou, Peng Huang, Chenyang Lu, Haisong Feng, Lichun Dong, Luxi Tan, Yong-Wei Zhang, Cailong Zhou, Yi Qin, and Dong Xia

Research Institute: IHPC

Title of Paper: Ultrathin LayCoOx Nanosheets with High Porosity Featuring Boosted Catalytic Oxidation of Benzene: Mechanism Elucidation via an Experiment–Theory Combined Paradigm

Publish in: Inorganic Chemistry

Abstract: Designing transition-metal oxides for catalytically removing the highly toxic benzene holds significance in addressing indoor/outdoor environmental pollution issues. Herein, we successfully synthesized ultrathin LayCoOx nanosheets (thickness of ∼1.8 nm) with high porosity, using a straightforward coprecipitation method. Comprehensive characterization techniques were employed to analyze the synthesized LayCoOx catalysts, revealing their low crystallinity, high surface area, and abundant porosity. Catalytic benzene oxidation tests demonstrated that the La0.029CoOx-300 nanosheet exhibited the most optimal performance. This catalyst enabled complete benzene degradation at a relatively low temperature of 220 °C, even under a high space velocity (SV) of 20,000 h–1, and displayed remarkable durability throughout various catalytic assessments, including SV variations, exposure to water vapor, recycling, and long time-on-stream tests. Characterization analyses confirmed the enhanced interactions between Co and doped La, the presence of abundant adsorbed oxygen, and the extensive exposure of Co3+ species in La0.029CoOx-300 nanosheets. Theoretical calculations further revealed that La doping was beneficial for the formation of oxygen vacancies and the adsorption of more hydroxyl groups. These features strongly promoted the adsorption and activation of oxygen, thereby accelerating the benzene oxidation processes. This work underscores the advantages of doping rare-earth elements into transition-metal oxides as a cost-effective yet efficient strategy for purifying industrial exhausts.

URL: https://doi.org/10.1021/acs.inorgchem.3c04621

1 Feb 2024

Submitted by (Bold are A*STAR Staff): Juan Manuel Arce-Ramos, Wen-Qing Li, San Hua Lim, Jie Chang, Takuya Hashimoto, Hiroyuki Kamata, Michael B. Sullivan, Armando Borgna, Luwei Chen, Chee Kok Poh, Jia Zhang

Research Institute: IHPC,ISCE2

Title of Paper: Investigating the deactivation and regeneration mechanism of Fe-based catalysts during CO2 reduction to chemicals

Publish in: Applied Catalysis B: Environment and Energy

Abstract: The Modified Fischer-Tropsch process converts CO2 to chemicals using a dual-function Fe-based catalyst composed typically of magnetite and iron carbides. However, catalyst deactivation limits its industrial application. In this study, we combined Density Functional Theory (DFT) calculations and experiments to provide insights into the underlying catalyst deactivation and regeneration mechanisms. The dynamic state of the catalyst was observed with time on stream, revealing the impact of the evolving reaction mixture along the reactor. Rapid CO2 and H2O dissociation on the carbide phase creates persistent *O, causing Fe5C2 deactivation through oxidation. On the other hand, the direct carburization of Fe3O4 proves challenging due to significant energy barriers, underscoring the need for metallic Fe or a highly reduced surface as a precursor to effective catalyst activation. These insights into iron catalyst evolution during CO2 reduction can guide the development of strategies for achieving efficient catalyst performance.

URL: https://doi.org/10.1016/j.apcatb.2024.123794

31 Jan 2024

Submitted by (Bold are A*STAR Staff): Jim Shaw, Jean-Sebastien Gounot, Hanrong Chen, Niranjan Nagarajan, and Yun William Yu

Research Institute: GIS

Title of Paper: Floria: Fast and accurate strain haplotyping in metagenomes

Preprint in: bioRxiv

Abstract: Shotgun metagenomics allows for direct analysis of microbial community genetics, but scalable computational methods for the recovery of bacterial strain genomes from microbiomes remains a key challenge. We introduce Floria, a novel method designed for rapid and accurate recovery of strain haplotypes from short and long-read metagenome sequencing data, based on minimum error correction (MEC) read clustering and a strain-preserving network flow model. Floria can function as a standalone haplotyping method, outputting alleles and reads that co-occur on the same strain, as well as an end-to-end read-to-assembly pipeline (Floria-PL) for strain-level assembly. Benchmarking evaluations on synthetic metagenomes showed that Floria is > 3× faster and recovers 21% more strain content than base-level assembly methods (Strainberry), while being over an order of magnitude faster when only phasing is required. Applying Floria to a set of 109 deeply sequenced nanopore metagenomes took <20 minutes on average per sample, and identified several species that have consistent strain heterogeneity. Applying Floria’s short-read haplotyping to a longitudinal gut metagenomics dataset revealed a dynamic multi-strain Anaerostipes hadrus community with frequent strain loss and emergence events over 636 days. With Floria, accurate haplotyping of metagenomic datasets takes mere minutes on standard workstations, paving the way for extensive strain-level metagenomic analyses.

URL: https://doi.org/10.1101/2024.01.28.577669

18 Jan 2024

Submitted by (Bold are A*STAR Staff): V Vijendran, Aritra Das, Dax Enshan Koh, Syed Assad and Ping Koy Lam

Research Institute: IHPC

Title of Paper: An Expressive Ansatz for Low-Depth Quantum Approximate Optimisation

Accepted in: Quantum Science and Technology

Abstract: The Quantum Approximate Optimisation Algorithm (QAOA) is a hybrid quantum-classical algorithm used to approximately solve combinatorial optimisation problems. It involves multiple iterations of a parameterised ansatz that consists of a problem and mixer Hamiltonian, with the parameters being classically optimised. While QAOA can be implemented on near-term quantum hardware, physical limitations such as gate noise, restricted qubit connectivity, and state-preparation-and-measurement errors can limit circuit depth and decrease performance. To address these limitations, this work introduces the eXpressive QAOA (XQAOA), an overparameterised variant of QAOA that assigns more classical parameters to the ansatz to improve its performance at low depths. XQAOA also introduces an additional Pauli-Y component in the mixer Hamiltonian, allowing the mixer to implement arbitrary unitary transformations on each qubit. To benchmark the performance of XQAOA at unit depth, we derive its closed-form expression for the MaxCut problem and compare it to QAOA, Multi-Angle QAOA(MA-QAOA), a Classical-Relaxed algorithm, and the state-of-the-art Goemans-Williamson algorithm on a set of unweighted regular graphs with 128 and 256 nodes for degrees ranging from 3 to 10. Our results indicate that at unit depth, XQAOA has benign loss landscapes with local minima concentrated near the global optimum, allowing it to consistently outperform QAOA, MA-QAOA, and the Classical-Relaxed algorithm on all graph instances and the Goemans-Williamson algorithm on graph instances with degrees greater than 4. Small-scale simulations also reveal that unit-depth XQAOA invariably surpasses both QAOA and MA-QAOA on all tested depths up to five. Additionally, we find an infinite family of graphs for which XQAOA solves MaxCut exactly and analytically show that for some graphs in this family, special cases of XQAOA are capable of achieving a much larger approximation ratio than QAOA. Overall, XQAOA is a more viable choice for variational quantum optimisation on near-term quantum devices, offering competitive performance at low depths.

URL: https://doi.org/10.1088/2058-9565/ad200a

17 Jan 2024

Submitted by (Bold are A*STAR Staff): Kai Xiang Kuah , Man-Fai Ng , Teck Leong Tan , Daniel John Blackwood 

Research Institute: IHPC

Title of Paper: Mg/MgO interfaces as efficient hydrogen evolution cathodes causing accelerated corrosion of additive manufactured Mg alloys: A DFT analysis

Published in: Journal of Magnesium and Alloys

Abstract: The corrosion rates of additive-manufactured Mg alloys are higher than their as-cast counterparts, possibly due to increased kinetics for the hydrogen evolution reaction on secondary phases, which may include oxide inclusions. Scanning Kelvin Probe Force Microscopy demonstrated that MgO inclusions could act as cathodes for Mg corrosion, but their low conductivity likely precludes this. However, the density of state calculations through density functional theory using hybrid HSE06 functional revealed overlapping electronic states at the Mg/MgO interface, which facilitates electron transfers and participates in redox reactions. Subsequent determination of the hydrogen absorption energy at the Mg/MgO interface reveals it to be an excellent catalytic site, with HER being found to be a factor of 23x more efficient at the interface than on metallic Mg. The results not only support the plausibility of the Mg/MgO interface being an effective cathode to the adjacent anodic Mg matrix during corrosion but also contribute to the understanding of the enhanced cathodic activities observed during the anodic dissolution of magnesium.

URL: https://doi.org/10.1016/j.jma.2023.12.002

06 Jan 2024

Submitted by (Bold are A*STAR Staff): Dillon W. P. Tay, Lee Ling Tan, Elena Heng, Nadiah Zulkarnain, Kuan Chieh Ching, Mario Wibowo, Elaine Jinfeng Chin, Zann Yi Qi Tan, Chung Yan Leong, Veronica Wee Pin Ng, Lay Kien Yang, Deborah C. S. Seow, Yi Wee Lim, Winston Koh, Lokanand Koduru, Yoganathan Kanagasundaram, Siew Bee Ng, Yee Hwee Lim & Fong Tian Wong 

Research Institute: ISCE2, IMCB, SIFBI, BII

Title of Paper: Exploring a general multi-pronged activation strategy for natural product discovery in Actinomycetes

Published in: Communications Biology

Abstract: Natural products possess significant therapeutic potential but remain underutilized despite advances in genomics and bioinformatics. While there are approaches to activate and upregulate natural product biosynthesis in both native and heterologous microbial strains, a comprehensive strategy to elicit production of natural products as well as a generalizable and efficient method to interrogate diverse native strains collection, remains lacking. Here, we explore a flexible and robust integrase-mediated multi-pronged activation approach to reliably perturb and globally trigger antibiotics production in actinobacteria. Across 54 actinobacterial strains, our approach yielded 124 distinct activator-strain combinations which consistently outperform wild type. Our approach expands accessible metabolite space by nearly two-fold and increases selected metabolite yields by up to >200-fold, enabling discovery of Gram-negative bioactivity in tetramic acid analogs. We envision these findings as a gateway towards a more streamlined, accelerated, and scalable strategy to unlock the full potential of Nature’s chemical repertoire.

URL: https://doi.org/10.1038/s42003-023-05648-7

05 Jan 2024

Submitted by (Bold are A*STAR Staff): Jian Zhang, Hao-Chun Zhang, Weifeng Li and Gang Zhang

Research Institute: IHPC

Title of Paper: Thermal Conductivity of GeTe Crystals Based on Machine Learning Potentials

Accepted in: Chinese Physics B

Abstract: GeTe has attracted extensive research interest in thermoelectric application. In this paper, we first train a neuro-evolution potential (NEP) based on the dataset constructed by ab initio molecular dynamics (AIMD) with the Gaussian approximation potential (GAP) as a reference. The phonon density of states is then calculated by two machine learning potentials and compared with density functional theory (DFT) results, with the GAP potential having higher accuracy. Next, the thermal conductivity of GeTe crystal at 300 K is calculated by equilibrium molecular dynamics (EMD) method using both machine learning potentials, and both are in good agreement with the experimental result, however, the calculations using the NEP potential are about 500 times faster than using GAP potential. Finally, the lattice thermal conductivity in the range of 300-600 K is calculated using the NEP potential. The lattice thermal conductivity decreases as temperature increases due to the phonon anharmonic effect. This study provides a theoretical tool for the study of thermal conductivity of GeTe.

URL: https://doi.org/10.1088/1674-1056/ad1b42

04 Jan 2024

Submitted by (Bold are A*STAR Staff): Shengnan Sun, Chencheng Dai, Peng Zhao, Shibo Xi, Yi Ren, Hui Ru Tan, Poh Chong Lim, Ming Lin, Caozheng Diao, Danwei Zhang, Chao Wu, Anke Yu, Jie Cheng Jackson Koh, Wei Ying Lieu, Debbie Hwee Leng Seng, Libo Sun, Yuke Li, Teck Leong Tan, Jia Zhang, Zhichuan J. Xu & Zhi Wei Seh 

Research Institute: IHPC, IMRE, ISCE2

Title of Paper: Spin-related Cu-Co pair to increase electrochemical ammonia generation on high-entropy oxides

Published in: Nature communications

Abstract: The electrochemical conversion of nitrate to ammonia is a way to eliminate nitrate pollutant in water. Cu-Co synergistic effect was found to produce excellent performance in ammonia generation. However, few studies have focused on this effect in high-entropy oxides. Here, we report the spin-related Cu-Co synergistic effect on electrochemical nitrate-to-ammonia conversion using high-entropy oxide Mg0.2Co0.2Ni0.2Cu0.2Zn0.2O. In contrast, the Li-incorporated MgCoNiCuZnO exhibits inferior performance. By correlating the electronic structure, we found that the Co spin states are crucial for the Cu-Co synergistic effect for ammonia generation. The Cu-Co pair with a high spin Co in Mg0.2Co0.2Ni0.2Cu0.2Zn0.2O can facilitate ammonia generation, while a low spin Co in Li-incorporated MgCoNiCuZnO decreases the Cu-Co synergistic effect on ammonia generation. These findings offer important insights in employing the synergistic effect and spin states inside for selective catalysis. It also indicates the generality of the magnetic effect in ammonia synthesis between electrocatalysis and thermal catalysis.

URL: https://doi.org/10.1038/s41467-023-44587-z

31 Dec 2023

Submitted by (Bold are A*STAR Staff): Mingchang Zhang, Weidong Xu, Xuefei Han, Huiqing Fan, Tao Chen, YaXiong Yang, Yong Gao, Chao Zheng, Yi Yang, Ting Xiong, Yong-Wei Zhang, Wee Siang Vincent Lee, Weijia Wang, Hongge Pan, Zhi Gen Yu, Junmin Xue

Research Institute: IHPC

Title of Paper: Unveiling The Mechanism of The Dendrite Nucleation and Growth in Aqueous Zinc Ion Batteries

Published in: Advanced Energy Materials

Abstract: Aqueous zinc ion batteries (ZIBs) exhibit great potential for next-generation energy storage devices. However, significant challenges exist, including the uncontrollable formation of Zn dendrite and side reactions during zinc stripping and plating. The mechanism of Zn dendrite nucleation has yet to be fully understood. In this work, the first principles simulations are used to investigate the Zn dendrite formation process. The unintentionally adsorbed O2− and OH− ions are the inducing factors for Zn dendrite nucleation and growth on the Zn (0001) plane due to significantly increased Zn diffusion barriers. A top-down method is demonstrated to suppress the dendrite using delaminated V2CTx to capture O2− and OH− ions thanks to reduced Zn diffusion barriers. The experimental results revealed significantly suppressed Zn dendrite nucleation and growth, resulting in a layer-by-layer deposit/stripping of Zn. Based on the electrochemical evaluations, the V2CTx-coated Zn composite delivers a high coulombic efficiency of 99.3 % at 1.0 mAh cm−2. Furthermore, the full cell achieves excellent cyclic performance of 93.6 % capacity retention after 2000 cycles at 1 A g−1. This strategy has broad scalability and can be widely applied in designing metallic anodes for rechargeable batteries.

URL: https://doi.org/10.1002/aenm.202303737

18 Dec 2023

Submitted by (Bold are A*STAR Staff): Jianguo Sun, Hao Yuan, Jing Yang, Tuo Wang, Yulin Gao, Qi Zhao , Ximeng Liu, Haimei Wang, Yong-Wei Zhang, John Wang

Research Institute: IHPC, IMRE

Title of Paper: Frameworked electrolytes: Ionic transport behavior and high mobility for solid state batteries

Published in: InfoMat

Abstract: All solid-state batteries (ASSBs) are the holy grails of rechargeable batteries, where extensive searches are ongoing in the pursuit of ideal solid-state electrolytes. Nevertheless, there is still a long way off to the satisfactorily high (enough) ionic conductivity, long-term stability and especially being able to form compatible interfaces with the solid electrodes. Herein, we have explored ionic transport behavior and high mobility in the sub-nano pore networks in the framework structures. Macroscopically, the frameworked electrolyte behaves as a solid, and however in the (sub)-nano scales, the very limited number of solvent molecules in confinement makes them completely different from that in liquid electrolyte. Differentiated from a liquid-electrolyte counterpart, the interactions between the mobile ions and surrounding molecules are subject to dramatic changes, leading to a high ionic conductivity at room temperature with a low activation energy. Li+ ions in the sub-nano cages of the network structure are highly mobile and diffuse rather independently, where the rate-limiting step of ions crossing cages is driven by the local concentration gradient and the electrostatic interactions between Li+ ions. This new class of frameworked electrolytes (FEs) with both high ionic conductivity and desirable interface with solid electrodes are demonstrated to work with Li-ion batteries, where the ASSB with LiFePO4 shows a highly stable electrochemical performance of over 450 cycles at 2°C at room temperature, with an almost negligible capacity fade of 0.03‰ each cycle. In addition, the FE shows outstanding flexibility and anti-flammability, which are among the key requirements of large-scale applications.

URL: https://doi.org/10.1002/inf2.12487

18 Dec 2023

Submitted by (Bold are A*STAR Staff): Albert Ong, Zi Cheng Wong, Kang Le Osmund Chin, Wei Wei Loh, Ming Hui Chua, Shi Jun Ang and Jason Y. C. Lim

Research Institute: IMRE, IHPC, ISCE2

Title of Paper: Enhancing the photocatalytic upcycling of polystyrene to benzoic acid: a combined computational-experimental approach for acridinium catalyst design

Published in: Royal Society of Chemistry

Abstract: Converting polystyrene into value-added oxygenated aromatic compounds is an attractive end-of-life upcycling strategy. However, identification of appropriate catalysts often involves laborious and time-consuming empirical screening. Herein, after demonstrating the feasibility of using acridinium salts for upcycling polystyrene into benzoic acid by photoredox catalysis for the first time, we applied low-cost descriptor-based combinatorial in silico screening to predict the photocatalytic performance of a family of potential candidates. Through this approach, we identified a non-intuitive fluorinated acridinium catalyst that outperforms other candidates for converting polystyrene to benzoic acid in useful yields at low catalyst loadings (≤5 mol%). In addition, this catalyst also proved effective with real-life polystyrene waste containing dyes and additives. Our study underscores the potential of computer-aided catalyst design for valorizing polymeric waste into essential chemical feedstock for a more sustainable future.

URL: https://doi.org/10.1039/D3SC06388G

09 Dec 2023

Submitted by (Bold are A*STAR Staff): Qing-Xiang Pei, Wanghui Li, Zachary H. Aitken, Ping Liu & Yong-Wei Zhang

Research Institute: IHPC

Title of Paper: Enhancing the impact property of high-entropy alloys with graphene layers: a molecular dynamics study

Published in: Composites & nanocomposites

Abstract: High-entropy alloy (HEA) and graphene have high strength, and both have been explored as shielding materials for impact protection. Very recently, HEA/graphene composites with HEA as the matrix and graphene as reinforcing phase have attracted great interests. Herein, the deformation behavior and penetration resistance of AlCoCuFeNi HEA/graphene composites are studied under ballistic impact loadings using molecular dynamics simulations. It is found that graphene can enhance the impact property of the HEA with graphene on the top surface or inside HEA. The amount of enhancement is proportional to the number of graphene layers from monolayer to trilayer. This enhancement is mainly attributed to the strong load carrying ability of graphene, which significantly increases the penetration resistance when a projectile passes through the graphene layers. However, graphene could also lead to some reduction in the impact force of HEA when it is inside the HEA. This negative effect is because graphene sheets break the structure continuity of HEA, reducing the load carrying ability of the local HEA. Overall, the positive effect of graphene outweighs the negative effect, leading to improved impact performance of the HEA/graphene composites. Besides, graphene considerably affects the magnitude and distribution of stress at the HEA/graphene interface during the impact process, which greatly influences the dislocation nucleation and propagation in the HEA/graphene composites. The present work not only provides insights into the dual role that graphene plays in the impact performance of the HEA/graphene composites, but also is useful for the design of HEA/graphene composites for impact protection.

URL: https://doi.org/10.1007/s10853-023-09173-0

08 Dec 2023

Submitted by (Bold are A*STAR Staff): Ingrid Guilvout, Firdaus Samsudin, Roland G. Huber, Peter J. Bond, Benjamin Bardiaux, Olivera Francetic 

Research Institute: BII

Title of Paper: Membrane platform protein PulF of the Klebsiella type II secretion system forms a trimeric ion channel essential for endopilus assembly and protein secretion

Published in: Molecular and Cellular Biology

Abstract: Type IV pili and type II secretion systems (T2SS) are crucial for bacterial adaptation, virulence, and environmental impact. A common mechanism underlying their multiple functions involves assembly of dynamic plasma membrane-anchored filaments—the (endo)pili. The cytoplasmic ATPase motor GspE/PilB is thought to energize pilus assembly via the membrane assembly platform protein GspF/PilC, but platform protein structure and its molecular role remain elusive. Here, to dissect the GspF/PilC architecture and mechanism, we generated all-atom models of the Klebsiella T2SS platform protein PulF in different oligomeric states. Comprehensive modeling, molecular dynamics (MD) simulations, cysteine crosslinking, and biochemical analyses support the trimeric state of PulF. In the trimer, the transmembrane segment TMS2 and the nonessential cytoplasmic N-domain are peripherally located, while TMS1 and TMS3 form a 6-helix bundle delineating a central transmembrane channel. Polar and proline residue pairs in these segments, conserved in all GspF/PilC homologs, define the channel constriction that can accommodate sodium ions or protons. Remarkably, obstructing this channel via Cys crosslinking abolished endopilus assembly and protein secretion, shedding light on previous findings showing that dissipating the membrane potential with ionophores reversibly abolished T2SS function. The trimeric PulF shows an excellent fit with the PulE ATPase hexamer, building a complex with structural similarities to the V-ATPase. MD simulations of PulF inserted in an Escherichia coli membrane model reveal strong binding and enrichment in cardiolipin, the phospholipid known to stimulate ATPase activity of GspE/PilB. We propose that GspF/PilC cooperates with the ATPase to energize (endo)pilus assembly using the ion motive force.

URL: https://doi.org/10.1128/mbio.01423-23

04 Dec 2023

Submitted by (Bold are A*STAR Staff): C. Tang, D.T. Wu, S.S. Quek

Research Institute: IHPC

Title of Paper: Isotropic discretization methods of Laplacian and generalized divergence operators in phase field models

Published in: Computational Materials Science

Abstract: Phase field models have been extensively used to address various physical phenomena. However, discretization-induced anisotropy remains a longstanding challenge for phase field models. By using a hexagonal mesh in 2D, we describe isotropic discretization methods for the computation of Laplacian and generalized divergence operators. Quantitative analyses derived from discrete Fourier analysis prove that our methods are more isotropic than commonly used approaches, including isotropic methods for square mesh. To compare the performance of conventional and our discretization methods, a specific phase field model of alloy solidification was selected to perform benchmark simulations. Various 2D simulations using different discretization methods were carried out to verify the accuracy and efficiency of the improved numerical methods in a hexagonal mesh. We emphasize that the improved numerical methods using a hexagonal mesh are general and may be equally applied to other physical models that include the same operators.

URL: https://doi.org/10.1016/j.commatsci.2023.112688

23 Nov 2023

Submitted by (Bold are A*STAR Staff): Haisong Feng, Meng Zhang, Zhen Ge, Yuan Deng, Pengxin Pu, Wenyu Zhou, Hao Yuan, Jing Yang, Feng Li, Xin Zhang, and Yong-Wei Zhang

Research Institute: IHPC

Title of Paper: Designing Efficient Single-Atom Alloy Catalysts for Selective C═O Hydrogenation: A First-Principles, Active Learning and Microkinetic Study

Published in: ACS Applied Materials & Interfaces

Abstract: Selective hydrogenation of α,β-unsaturated aldehydes into unsaturated alcohols is a process in high demand in organic synthesis, pharmaceuticals, and food production. This process requires the precise hydrogenation of C═O bonds, a challenge that requires a tailored catalyst. Single-atom alloys (SAAs), where individual atoms of one metal are distributed in a host metal matrix, offer a potential solution to this challenge. Nevertheless, identifying the appropriate SAA capable of targeted adsorption and the efficient activation of C═O bonds remains a substantial hurdle. In this work, we synergistically combine density functional theory (DFT) calculations, active learning, and microkinetic simulations to design SAAs for the efficient and selective hydrogenation of α,β-unsaturated aldehydes. We first comprehensively assessed the potential of 66 SAAs across 264 surfaces (including (100), (110), (111), and (320) crystal planes), to gauge their potential in activating C═C and C═O bonds. Our assessment unveiled the excellent selectivity of the Ti1Au SAA in activating C═O bonds. Moreover, our detailed DFT calculations further demonstrated the high catalytic activity of Ti1Au(320) and Ti1Au(111) surfaces with a low activation energy barrier of only 0.60 eV. Subsequently, we conducted microkinetic simulations on the selective hydrogenation process of crotonaldehyde, by selecting Ti1Au (320) and (111) surfaces as the catalysts and demonstrated that they exhibited a remarkable selectivity and nearly 100% conversion toward crotyl alcohol in the temperature range from 373 to 553 K. The present study not only reveals novel SAAs for targeted hydrogenation of α,β-unsaturated aldehydes but also establishes a promising path toward efficient design of selective hydrogenation catalysts more broadly.

URL: https://doi.org/10.1021/acsami.3c15108

18 Nov 2023

Submitted by (Bold are A*STAR Staff): Yue Hu, Jiawei Liu, Carmen Lee, Wenyu Luo, Jinfeng Dong, Zhishan Liang, Mengxin Chen, Erhai Hu, Mingsheng Zhang, Xiang Yun Debbie Soo, Qiang Zhu, Fengkun Li, Rajdeep Singh Rawat, Man-Fai Ng, Lixiang Zhong, Bo Han, Dongsheng Geng, and Qingyu Yan

Research Institute: IMRE, IHPC

Title of Paper: Balanced NOx– and Proton Adsorption for Efficient Electrocatalytic NOx– to NH3 Conversion

Published in: ACS Nano

Abstract: Electrocatalytic nitrate (NO3–)/nitrite (NO2–) reduction reaction (eNOx–RR) to ammonia under ambient conditions presents a green and promising alternative to the Haber–Bosch process. Practically available NOx– sources, such as wastewater or plasma-enabled nitrogen oxidation reaction (p-NOR), typically have low NOx– concentrations. Hence, electrocatalyst engineering is important for practical eNOx–RR to obtain both high NH3 Faradaic efficiency (FE) and high yield rate. Herein, we designed balanced NOx– and proton adsorption by properly introducing Cu sites into the Fe/Fe2O3 electrocatalyst. During the eNOx–RR process, the H adsorption is balanced, and the good NOx– affinity is maintained. As a consequence, the designed Cu–Fe/Fe2O3 catalyst exhibits promising performance, with an average NH3 FE of ∼98% and an average NH3 yield rate of 15.66 mg h–1 cm–2 under the low NO3– concentration (32.3 mM) of typical industrial wastewater at an applied potential of −0.6 V versus reversible hydrogen electrode (RHE). With low-power direct current p-NOR generated NOx– (23.5 mM) in KOH electrolyte, the Cu–Fe/Fe2O3 catalyst achieves an FE of ∼99% and a yield rate of 15.1 mg h–1 cm–2 for NH3 production at −0.5 V (vs RHE). The performance achieved in this study exceeds industrialization targets for NH3 production by exploiting two available low-concentration NOx– sources.

URL: https://doi.org/10.1021/acsnano.3c06798

9 Nov 2023

Submitted by (Bold are A*STAR Staff): Ziqi Yanga, Chaoran Xua, Xianxian Zhoua, Choon Boon Cheong, Choon Wee Kee and Choon-Hong

Research Institute: ICES2

Title of Paper: A chiral pentanidium and pyridinyl-sulphonamide ion pair as an enantioselective organocatalyst for Steglich rearrangement

Published in: Chemical Science

Abstract: Enantioselective ion pair catalysis has gained significant attention due to its ability to exert selectivity control in various reactions. Achiral counterions have been found to play crucial roles in modulating reactivity and selectivity. The modular nature of an ion pair catalyst allows rapid alterations of the achiral counterion to achieve optimal outcomes, without the need to modify the more onerous chiral component. In this study, we report the successful development of a stable chiral pentanidium pyridinyl-sulphonamide ion pair as a nucleophilic organocatalyst for asymmetric Steglich rearrangement. The ion pair catalyst demonstrated excellent performance, leading to enantioenriched products with up to 99% ee through simple alterations of the achiral anions. We conducted extensive ROESY experiments and concluded that the reactivity and enantioselectivity were correlated to the formation of a tight ion pair in solution. Further computational analyses provided greater clarity to the structure of the ion pair catalyst in solution. Our findings reveal the critical roles of NMR experiments and computational analyses in the design and optimisation of ion pair catalysts.

URL: https://doi.org/10.1039/D3SC04397E

31 Oct 2023

Submitted by (Bold are A*STAR Staff): Lujain Alrais, Sandeep Suryabhan Gholap, Indranil Dutta, Edy Abou-Hamad, Benjamin W.J. Chen, Jia Zhang, Mohamed Nejib Hedhili, Jean-Marie Basset, Kuo-Wei Huang

Research Institute: IHPC,IMRE

Title of Paper: Highly efficient immobilized PN3P-pincer iridium catalyst for dehydrogenation of neat formic acid

Published in: Applied Catalysis B: Environmental

Abstract: Formic acid (FA) has been well recognized as one of the most promising hydrogen carriers. The dehydrogenation of the FA could offer an efficient process to on-demand hydrogen generation with a suitable catalyst. Homogeneous catalysts have demonstrated superior activity and selectivity compared to traditional heterogeneous catalysis. However, the latter is preferred for large-scale applications. By incorporating the homogeneous organometallic complex onto an appropriate support, the unique features of both types of catalysts can be combined and utilized effectively. Herein, we synthesized an immobilized PN3P-Ir pincer catalyst (2) supported onto KCC-1, a 3D fibrous silica nanosphere that exhibits a high surface area and contains a tetracoordinate aluminum site. To reduce the use of volatile additives, the choice of cesium formate (CsO2CH) was found to be crucial as at 80–90 °C, CsO2CH could act as a reaction medium and serve as basic additive. Remarkable reactivities under neat conditions were achieved with a TOF of 13,290 h-1 and a TON of up to 540,000. The comparative study indicates a significant improvement of 2 from its homogenous counterpart, PN3P-IrH3 (1).

URL: https://doi.org/10.1016/j.apcatb.2023.123439

13 Oct 2023

Submitted by (Bold are A*STAR Staff): Shuai Chen, Ping Liu, Qingxiang Pei, Zhi Gen Yu, Zachary H. Aitken, Wanghui Li, Zhaoxuan Wu, Rajarshi Banerjee, David J. Srolovitz, Peter K. Liaw, Yong-Wei Zhang

Research Institute: IHPC

Title of Paper: Ideal plasticity and shape memory of nanolamellar high-entropy alloys

Published in: Science Advances

Abstract: Understanding the relationship among elemental compositions, nanolamellar microstructures, and mechanical properties enables the rational design of high-entropy alloys (HEAs). Here, we construct nanolamellar AlxCoCuFeNi HEAs with alternating high– and low–Al concentration layers and explore their mechanical properties using a combination of molecular dynamic simulation and density functional theory calculation. Our results show that the HEAs with nanolamellar structures exhibit ideal plastic behavior during uniaxial tensile loading, a feature not observed in homogeneous HEAs. This remarkable ideal plasticity is attributed to the unique deformation mechanisms of phase transformation coupled with dislocation nucleation and propagation in the high–Al concentration layers and the confinement and slip-blocking effect of the low–Al concentration layers. Unexpectedly, this ideal plasticity is fully reversible upon unloading, leading to a remarkable shape memory effect. Our work highlights the importance of nanolamellar structures in controlling the mechanical and functional properties of HEAs and presents a fascinating route for the design of HEAs for both functional and structural applications.

URL: https://doi.org/10.1126/sciadv.adi5817

13 Oct 2023

Submitted by (Bold are A*STAR Staff): Ganna Petruk, Manoj Puthia, Firdaus Samsudin, Jitka Petrlova, Franziska Olm, Margareta Mittendorfer, Snejana Hyllén, Dag Edström, Ann-Charlotte Strömdahl, Carl Diehl, Simon Ekström, Björn Walse, Sven Kjellström, Peter J. Bond, Sandra Lindstedt & Artur Schmidtchen 

Research Institute: BII

Title of Paper: Targeting Toll-like receptor-driven systemic inflammation by engineering an innate structural fold into drugs.

Published in: Nature Communications

Abstract: There is a clinical need for conceptually new treatments that target the excessive activation of inflammatory pathways during systemic infection. Thrombin-derived C-terminal peptides (TCPs) are endogenous anti-infective immunomodulators interfering with CD14-mediated TLR-dependent immune responses. Here we describe the development of a peptide-based compound for systemic use, sHVF18, expressing the evolutionarily conserved innate structural fold of natural TCPs. Using a combination of structure- and in silico-based design, nuclear magnetic resonance spectroscopy, biophysics, mass spectrometry, cellular, and in vivo studies, we here elucidate the structure, CD14 interactions, protease stability, transcriptome profiling, and therapeutic efficacy of sHVF18. The designed peptide displays a conformationally stabilized, protease resistant active innate fold and targets the LPS-binding groove of CD14. In vivo, it shows therapeutic efficacy in experimental models of endotoxin shock in mice and pigs and increases survival in mouse models of systemic polymicrobial infection. The results provide a drug class based on Nature´s own anti-infective principles.

URL: https://doi.org/10.1038/s41467-023-41702-y

11 Oct 2023

Submitted by (Bold are A*STAR Staff): Ping Liu, Shuai Chen, Qing-Xiang Pei,  Zachary H. Aitken, Wanghui Li, Yong-Wei Zhang

Research Institute: IHPC

Title of Paper: Simultaneously enhancing the tensile strength and ductility of high entropy alloys by nanoscale precipitates/fillers

Published in: APL Materials

Abstract: High entropy alloys (HEAs) in the solid solution (SS) phase have attracted much attention due to their novel strengthening mechanisms. Recent studies have shown that introducing nanoscale precipitates/fillers can further strengthen the SS HEAs. In this work, we performed large-scale molecular dynamics simulations of AlxCoCuFeNi HEAs filled with randomly distributed AlNi3 nanoparticles. The effects of AlNi3 particle size and volume fraction, the chemical composition of the HEA matrix, and temperature on the mechanical properties, deformation, and failure behavior of the composite are systematically investigated. Our simulations show that, remarkably, the AlNi3 nanoparticles can simultaneously enhance the ultimate tensile strength and ultimate tensile strain of the composite. The underlying mechanism is that the AlNi3 nanoparticles greatly suppressed the phase change and dislocation appearance in the HEA matrix, resulting in a delayed material failure during the deformation. We also find that Young’s modulus, ultimate tensile strength, and ultimate tensile strain follow the lower-bound of the rule of mixtures and further present the underlying reason for this lower-bound relation. The present work not only provides insights into the mechanical properties, deformation, and failure behavior of AlNi3 nanoparticle-reinforced AlxCoCuFeNi HEAs but is also useful for guiding the rational design of HEAs for engineering applications.

URL: https://doi.org/10.1063/5.0168668

19 Sept 2023

Submitted by (Bold are A*STAR Staff):  Jingwen Zhu,  Daniel Margulies,  Anqi Qiu

Research Institute:

Title of Paper: White matter functional gradients and their formation in adolescence

Published in: Cerebral Cortex

Abstract: It is well known that functional magnetic resonance imaging (fMRI) is a widely used tool for studying brain activity. Recent research has shown that fluctuations in fMRI data can reflect functionally meaningful patterns of brain activity within the white matter. We leveraged resting-state fMRI from an adolescent population to characterize large-scale white matter functional gradients and their formation during adolescence. The white matter showed gray-matter-like unimodal-to-transmodal and sensorimotor-to-visual gradients with specific cognitive associations and a unique superficial-to-deep gradient with nonspecific cognitive associations. We propose two mechanisms for their formation in adolescence. One is a “function-molded” mechanism that may mediate the maturation of the transmodal white matter via the transmodal gray matter. The other is a “structure-root” mechanism that may support the mutual mediation roles of the unimodal and transmodal white matter maturation during adolescence. Thus, the spatial layout of the white matter functional gradients is in concert with the gray matter functional organization. The formation of the white matter functional gradients may be driven by brain anatomical wiring and functional needs.

URL: https://doi.org/10.1093/cercor/bhad319

15 Sept 2023

Submitted by (Bold are A*STAR Staff): Shuai Chen, Zachary H. Aitken, Subrahmanyam Pattamatta, Zhaoxuan Wu, Zhi Gen Yu, David J. Srolovitz, Peter K. Liaw, Yong-Wei Zhang

Research Institute: IHPC

Title of Paper: Crack Tip Dislocation Activity in Refractory High-Entropy Alloys

Published in: International Journal of Mechanical Sciences

Abstract: Dislocation activities play an important role in the deformation and failure of refractory high-entropy alloys (RHEAs). However, the impact of chemical short-range ordering (SRO) on dislocation activities at a crack tip in RHEAs remains unclear. Here, we investigate the effect of SRO on the dislocation nucleation, propagation, and reaction at a crack tip in a body-centered-cubic (BCC) MoTaTiWZr RHEA, using a combination of molecular dynamic simulations and Monte Carlo methods. Our results indicate that this RHEA is energetically favorable to form SRO, developing a pseudo-composite microstructure with low-energy clusters (LECs), medium-energy clusters (MECs), and high-energy clusters (HECs). The HECs at the crack tip are favorable sites for dislocation nucleation whereas the MECs surrounding the HECs function as a strong matrix to stabilize the weak HECs. At elevated temperatures, the HECs near the crack tip transform to severely distorted BCC and disordered structures, which can cause the breakup, absorption, and annihilation of emitted dislocations and nucleation of new dislocations. Our work reveals the interesting role of SRO in altering the dislocation activities at the crack tip of RHEAs and suggests alternative routes for designing superior RHEAs at both room and elevated temperatures.

URL: https://doi.org/10.1016/j.ijmecsci.2023.108753

14 Sept 2023

Submitted by (Bold are A*STAR Staff): Krishna M. Gupta, Srinivasulu Aitipamula, Pui Shan Chow

Research Institute: ICES2

Title of Paper: In-silico design of covalent organic framework membranes for efficient water/ethanol separation

Published in: Journal of Membrane Science

Abstract: Covalent organic frameworks (COFs) have recently emerged as a promising class of nanoporous materials for membrane separation. At present, COF membranes are not efficient for separation of water from ethanol (ethanol dehydration) owing to pervasive challenge to separate small-sized molecular mixture. In this proof-of-concept study, we have computationally designed a series of novel COFs as pervaporation (PV) membranes for efficient ethanol dehydration. We utilized TpPa-1 as a model COF and its framework was rationally modified by attaching several hydrophobic and hydrophilic functional groups, resulting in new COF membranes namely TpPa-1-C5H8, TpPa-1-COOC2H5, TpPa-1-OC3H6OH, TpPa-1-C2Ph, TpPa-1-OC4H8OH and TpPa-1-OC2H4NHOCH3. These membranes possess different functionality and aperture size. Molecular dynamics (MD) simulations demonstrated that the permeation flux of water and ethanol is mostly governed by pore aperture size. The COF with the largest pore aperture holds the highest flux. In contrast, polarity of the pore functional groups governs the separation factor. COF membranes with hydrophobic pore functionalities display a lower separation factor than the membranes with hydrophilic pore functionalities. Among the designed COF membranes, TpPa-1-OC4H8OH has shown superior performance compared to the state-of-art membranes. Also, activation energies for permeation of water and ethanol through the two promising TpPa-1-OC3H6OH and TpPa-1-OC4H8OH membranes are lower than the reported PV membranes. Interestingly, water and ethanol molecules indicate backward movement before leaving the membrane surface at permeate side. The potential of mean force (PMF) shows that free energy barrier for water to enter the pore of highly selective COF membrane is ∼18.84 kJ/mol and the driving force for the water transfer from feed side to permeate side is ∼ −10.5 kJ/mol at PV condition. The current study not only reveals the underlying mechanism for solvent permeation and separation, but also suggests a highly selective COF membrane for water/ethanol separation. We envisage potential applications of the designed COFs as novel materials for sustainable solvent recovery.

URL: https://doi.org/10.1016/j.memsci.2023.122083

2 Sept 2023

Submitted by (Bold are A*STAR Staff): C. Tang, D.T. Wu, S.S. Quek

Research Institute: IHPC

Title of Paper: An Isotropic Discretization with Semi-implicit Approach for Phase Field Model of Alloy Solidification

Published in: arXiv Materials Science

Abstract: Quantitative phase field models have been extensively used to study the solidification behavior of alloys under different conditions. However, a longstanding challenge of phase field models is the directional bias caused by the discretization-induced lattice effects. In particular, widely used discretization methods may introduce significant spurious anisotropy for simulations of polycrystalline solidification. In this paper, we demonstrate a feasible 2D discretization strategy utilizing a hexagonal mesh to reduce the lattice-induced anisotropy of the phase field model. The leading differential terms of the 2D discretization methods are analyzed by using known methods in Fourier space. Using Taylor expansion of discrete Fourier Transform up to sixth order, we found that the proposed discretization strategy is more accurate and isotropic than other methods, including the isotropic discretization recently proposed by Ji et al.[1]. Additionally, the proposed 2D discretization method can be easily incorporated into a semi-implicit algorithm to solve phase field equations, thereby greatly reducing time step constraints and improving computational efficiency compared to explicit approaches. To prove the accuracy and efficiency of the proposed isotropic discretization with semi-implicit algorithm, 2D simulations of alloy solidification with different discretization schemes were performed and compared. We show that the proposed discretization using a hexagonal mesh can drastically reduce grid-induced anisotropy compared to conventional methods.

URL: https://doi.org/10.48550/arXiv.2309.00836

21 Aug 2023

Submitted by (Bold are A*STAR Staff): Jing Xia, Nanguang Chen, Anqi Qiu

Research Institute:

Title of Paper: Multi-level and joint attention networks on brain functional connectivity for cross-cognitive prediction

Published in: Medical Image Analysis

Abstract: Deep learning on resting-state functional MRI (rs-fMRI) has shown great success in predicting a single cognition or mental disease. Nevertheless, cognitive functions or mental diseases may share neural mechanisms that can benefit their prediction/classification. We propose a multi-level and joint attention (ML-Joint-Att) network to learn high-order representations of brain functional connectivities that are specific and shared across multiple tasks. We design the ML-Joint-Att network with edge and node convolutional operators, an adaptive inception module, and three attention modules, including network-wise, region-wise, and region-wise joint attention modules. The adaptive inception learns brain functional connectivity at multiple spatial scales. The network-wise and region-wise attention modules take the multi-scale functional connectivities as input and learn features at the network and regional levels for individual tasks. Moreover, the joint attention module is designed as region-wise joint attention to learn shared brain features that contribute to and compensate for the prediction of multiple tasks. We employed the Adolescent Brain Cognitive Development (ABCD) dataset (n=9092) to evaluate the ML-Joint-Att network for the prediction of cognitive flexibility and inhibition. Our experiments demonstrated the usefulness of the three attention modules and identified brain functional connectivities and regions specific and common between cognitive flexibility and inhibition. In particular, the joint attention module can significantly improve the prediction of both cognitive functions. Moreover, leave-one-site cross-validation showed that the ML-Joint-Att network is robust to independent samples obtained from different sites of the ABCD study. Our network outperformed existing machine learning techniques, including Brain Bias Set (BBS), spatio-temporal graph convolution network (ST-GCN), and BrainNetCNN. We demonstrated the generalization of our method to other applications, such as the prediction of fluid intelligence and crystallized intelligence, which also outperformed the ST-GCN and BrainNetCNN.

URL: https://doi.org/10.1016/j.media.2023.102921

14 Aug 2023

Submitted by (Bold are A*STAR Staff): Chenfei Li, Xin Ying Kong, Maoping Lyu, Xiu Ting Tay, Miloš Đokić, Kek Foo Chin, Crystal Ting Yang, Erin Ke Xin Lee, Jinfan Zhang, Chun Yuan Tham, Wei Xin Chan, Wen Jie Lee, Teik Thye Lim, Atsushi Goto, Michael B. Sullivan, Han Sen Soo

Research Institute: IHPC

Title of Paper: Upcycling of non-biodegradable plastics by base metal photocatalysis

Published in: Chem

Abstract: Globally, only around 9% of plastic waste is currently recycled, leaving a staggering 91% in landfills, incinerators, or discarded into the environment. The majority of the unrecycled plastics consist of non-biodegradable polyolefins, such as polyethylene and polypropylene commonly used in packaging materials due to their long lifespans, which pose significant challenges to their waste management. Traditional methods like high-temperature pyrolysis require heating to at least 200°C, which unnecessarily emits considerable amounts of greenhouse gases. Herein, we report a photocatalytic reaction that can upcycle plastics into platform chemicals at ambient temperature and pressure. The products include carboxylic acids that are versatile precursors and can be used for energy storage as liquid organic hydrogen carriers. This work establishes the viability of “mining” plastic waste as a sustainable alternative to fossil fuels for energy generation and the production of chemical feedstocks.

URL: https://doi.org/10.1016/j.chempr.2023.07.008

14 Aug 2023

Submitted by (Bold are A*STAR Staff): Albert Ong, Jerald Y. Q. Teo, Zixuan Feng, Tristan T. Y. Tan, and Jason Y. C. Lim

Research Institute: IMRE

Title of Paper: Organocatalytic Aerobic Oxidative Degradation of Polystyrene to Aromatic Acids

Published in: ACS Sustainable Chemistry & Engineering

Abstract: Polystyrenes are among the most prevalent commercial plastics produced worldwide, but their end-of-life treatment remains highly suboptimal today. Although currently only in their infancy, chemical upcycling of polystyrenes into functional chemicals have emerged as a potential solution to the growing waste plastic problem. Herein, we describe the first thermal organocatalytic method to oxidatively degrade commercial waste polystyrenes to benzoic acid and 4-nitrobenzoic acid, both of which are important chemicals in demand across multiple industries. Using N-hydroxyl catalysts such as N,N′,N″-trihydroxyisocyanuric acid and N-hydroxyphthalimide derivatives, our operationally simple method affords substantial yields of these aromatic acids in the presence of a suitable nitrate source in air at atmospheric pressure. Furthermore, our method can degrade commercial polystyrene products containing additives such as dyes on gram-scales as well as different polystyrene derivatives (e.g., polystyrene sulfonic acid) into other industrially relevant aromatic acids. Our findings not only redefine the currently overlooked potential of organocatalysis in chemical upcycling of recalcitrant plastics containing inert, non-cleavable polymer backbone structures but also complement other emerging catalytic methods for chemical degradation of plastic waste.

URL: https://doi.org/10.1021/acssuschemeng.3c01387

10 Aug 2023

Submitted by (Bold are A*STAR Staff): Tian Li, Quyang Liu, Jing Cao, Soo Wah Gan, Xinyu Dong, Ching Chiuan Yen, Chengtie Wu, and Wei Zhai

Research Institute: IMRE

Title of Paper: A Universal Chelation-Induced Selective Demetallization Strategy for Bioceramic Nanosheets (BCene)

Published in: Nano Letters

Abstract: The emergence of nanosheet materials like graphene and phosphorene, which are created by breaking the interlayer van der Waals force, has revolutionized multiple fields. Layered inorganic materials are ubiquitous in materials like bioceramics, semiconductors, superconductors, etc. However, the strong interlayer covalent or ionic bonding in these crystals makes it difficult to fabricate nanosheets from them. In this study, we present a simple technique to produce nanosheets from layered crystals by selectively exfoliating their interlayer metal atoms using the metal-chelation reaction. As a proof of concept, we successfully produced bioceramic nanosheets (BCene) by extracting Ca layers from Akermanite (AKT). The 3D-printed BCene scaffolds exhibited superior mechanical strength and in vitro bioactivity compared to the scaffolds made from AKT nanopowders. Our findings demonstrate the outstanding potential of BCene nanosheets in tissue engineering. Additionally, the selective demetallization technique for nanosheet production could be applied to other inorganic layered crystals to optimize their performance.

URL: https://doi.org/10.1021/acs.nanolett.3c02459

7 Aug 2023

Submitted by (Bold are A*STAR Staff): Yun Liu, Bartomeu Monserrat, and Julia Wiktor

Research Institute: IHPC

Title of Paper: Strong electron-phonon coupling and bipolarons in Sb2 S3

Published in: PHYSICAL REVIEW MATERIALS

Abstract: Antimony sulfide (Sb2S3) is an Earth-abundant and nontoxic material that is under investigation for solar energy conversion applications. However, it still suffers from poor power conversion efficiency and a large open circuit voltage loss that have usually been attributed to point or interfacial defects. More recently, there has been some discussion in the literature about the role of carrier trapping in the optical properties of Sb2S3, with some reporting self-trapped excitons as the microscopic origin for the performance loss, while others have found no evidence of carrier trapping with only large polarons existing in Sb2S3. By using first-principles methods, we demonstrate that Sb2S3 exhibits strong electron-phonon coupling, a prerequisite for carrier self-trapping in semiconductors, which results in a large renormalization of 200meV of the absorption edge when temperature increases from 10 to 300K. When two electrons or holes are added to the system, corresponding to a carrier density of 1.6×1020cm−3, we find wave function localization consistent with the presence of bipolarons accompanying a significant lattice distortion with the formation of Sb and S dimers. The formation energies of the electron and hole bipolarons are −330 and −280 meV per carrier, respectively. Our results reconcile some of the controversy in the literature regarding carrier trapping in Sb2S3 and demonstrate the existence of large electron-phonon coupling and carrier self-trapping that might place a fundamental limit on the open circuit voltage and, consequently, the maximum efficiency of the photovoltaic cells.

URL: https://doi.org/10.1103/PhysRevMaterials.7.085401

24 Jul 2023

Submitted by (Bold are A*STAR Staff): Mengshuang Zhang, Yun Liu, Yajing Du, and Hongzhi Liu

Research Institute: IHPC

Title of Paper: Tuning Topology and Scaffolding Units in Nanoporous Polymeric Materials for Efficient Iodine Adsorption and Detection

Published in: ACS Applied Nano Materials

Abstract: The precise control of scaffold elements and topologies of nanoporous materials shows great prospects in the application of adsorption and separation. In this work, two kinds of porous polymers, silsesquioxane-based porous polymers (PCSs) and triazine-based covalent–organic polymers (covalent triazine-based frameworks, CTFs), were prepared by the Heck reaction and Suzuki reaction of triazine monomers with octavinylsilsesquioxane and p-phenylboronic acid, respectively. A series of experimental results showed that the specific surface areas (SBET) and the morphological structures of the target materials can be controlled by regulating the building modules. The PCSs are irregular nanoporous aggregates with SBET values of 360∼560 m2 g–1, while the CTFs are regular hollow tubular polymers with SBET values of about 30∼70 m2 g–1. Different SBET values result in different adsorption capabilities of iodine in the volatile or solution phase. For volatile iodine, the adsorption capacity of CTFs is up to 2.5 g g–1, larger than that of PCSs, while in iodine–cyclohexane solution, the adsorption capacity of PCSs is larger than that of CTFs. Due to the fluorescence quenching caused by charge transfer between the polymers and I2, two polymers can be used to detect I2 with good selectivity and sensitivity. In this work, the porosity, fluorescence properties, and adsorption capacity of the target materials were successfully regulated by adjusting the scaffold units and topological structures of starting materials, thus realizing the sensitive detection and efficient adsorption of iodine.


URL: https://doi.org/10.1021/acsanm.3c00723

21 Jul 2023

Submitted by (Bold are A*STAR Staff): Jeremy H. M. Wong, Huayun Zhang, Nancy F. Chen

Research Institute: I2R

Title of Paper: Modelling Inter-rater Uncertainty in Spoken Language Assessment

Published in: IEEE/ACM Transactions on Audio, Speech, and Language Processing

Abstract: In a subjective task, such as Spoken Language Assessment (SLA), the reference scores provided by different human raters may vary. A collection of annotated scores from multiple raters can be interpreted as an expression of data uncertainty. Previous studies often treat SLA as classification or regression tasks, and train and evaluate models against scalar reference scores that were computed from the multiple rater scores, for example by majority voting. However, a scalar representation may not adequately capture information about uncertainty that is expressed by the multiple rater scores. This paper proposes to reformulate this subjective task as a distribution fitting problem, where the model should aim to emulate the uncertainty expressed by the multiple raters. Toward this aim, the model is trained and evaluated by computing a distance between the model's output posterior and the distribution of reference scores from the multiple raters. Different methods to infer a scalar score from the model's output posterior are also considered. This paper also proposes to improve the match between the model and the SLA task, by interpreting the model's outputs as parameters of a beta density function, to capture both uncertainty and score monotonicity. Finally, ensemble combination is investigated and a novel combination method is proposed, to marginalise out model uncertainty from the combined output distribution. These approaches are evaluated on the speechocean762 dataset and an in-house Tamil dataset.


URL: https://doi.org/10.1109/TASLP.2023.3297958

29 Jun 2023

Submitted by (Bold are A*STAR Staff): Chenye Shen, Chaoqiang Liu, Anqi Qiu

Research Institute: -

Title of Paper: Metabolism-related brain morphology accelerates aging and predicts neurodegenerative diseases and stroke: a UK Biobank study

Published in: Translational Psychiatry

Abstract: Metabolic syndrome (MetS) is characterized by a constellation of metabolic risk factors, including obesity, hypertriglyceridemia, low high-density lipoprotein (HDL) levels, hypertension, and hyperglycemia, and is associated with stroke and neurodegenerative diseases. This study capitalized on brain structural images and clinical data from the UK Biobank and explored the associations of brain morphology with MetS and brain aging due to MetS. Cortical surface area, thickness, and subcortical volumes were assessed using FreeSurfer. Linear regression was used to examine associations of brain morphology with five MetS components and the MetS severity in a metabolic aging group (N = 23,676, age 62.8 ± 7.5 years). Partial least squares (PLS) were employed to predict brain age using MetS-associated brain morphology. The five MetS components and MetS severity were associated with increased cortical surface area and decreased thickness, particularly in the frontal, temporal, and sensorimotor cortex, and reduced volumes in the basal ganglia. Obesity best explained the variation of brain morphology. Moreover, participants with the most severe MetS had brain age 1-year older than those without MetS. Brain age in patients with stroke (N = 1042), dementia (N = 83), Parkinson’s (N = 107), and multiple sclerosis (N = 235) was greater than that in the metabolic aging group. The obesity-related brain morphology had the leading discriminative power. Therefore, the MetS-related brain morphological model can be used for risk assessment of stroke and neurodegenerative diseases. Our findings suggested that prioritizing adjusting obesity among the five metabolic components may be more helpful for improving brain health in aging populations.


URL: https://doi.org/10.1038/s41398-023-02515-1

28 Jun 2023

Submitted by (Bold are A*STAR Staff): Man-Fai Ng, Daniel John Blackwood, Hongmei Jin, Teck Leon Tan

Research Institute: IHPC

Title of Paper: First-Principles Investigation into the Contributions of ORR and HER in Magnesium Corrosion

Published in: Electrochemical Society

Abstract: Recent experiments have demonstrated that oxygen reduction reaction (ORR) can contribute significantly to Mg corrosion in addition to hydrogen reduction reaction (HER). However, its contributions at various stages of Mg corrosion remains unclear. Using density functional theory calculations, we investigate ORR and HER on both pristine and Fe/Mn-alloyed Mg, MgO and Mg(OH)2 during Mg corrosion. We found that both HER and ORR on pristine and alloyed Mg contribute to the overall cathodic current density: HER contributes much more significantly than ORR, while the ORR contribution is up to the mass transport limit and would diminish over time. In addition, we found that ORR activities on Fe/Mn alloyed MgO are high, suggesting an alternate source of cathodic ORR contribution during the whole course of Mg corrosion. Excellent agreements are found between our findings and a recent experiment.

URL: https://doi.org/10.1149/1945-7111/ace243

16 Jun 2023

Submitted by (Bold are A*STAR Staff): Peh Joo Ho, Elaine Hsuen Lim, Mikael Hartman, Fuh Yong Wong , Jingmei Li

Research Institute: GIS

Title of Paper: Breast cancer risk stratification using genetic and non-genetic risk assessment tools for 246,142 women in the UK Biobank.

Published in: Genetics in Medicine

Abstract: 

Purpose
The benefit of using individual risk prediction tools to identify high-risk individuals for breast cancer (BC) screening is uncertain, despite the personalized approach of risk-based screening.

Methods
We studied the overlap of predicted high-risk individuals among 246,142 women enrolled in the UK Biobank. Risk predictors assessed include the Gail model (Gail), BC family history (FH, binary), BC polygenic risk score (PRS), and presence of LoF in BC predisposition genes. Youden J-index was used to select optimal thresholds for defining high-risk.

Results
In total, 147,399 were considered at high risk for developing BC within the next two years by at least one of the four risk prediction tools examined (Gail2-year>0.5%: 47%, PRS2-year>0.7%: 30%, FH: 6%, and LoF: 1%); 92,851 (38%) were flagged by only one risk predictor. The overlap between individuals flagged as high-risk due to genetic (PRS) and Gail model risk factors was 30%. The best-performing combinatorial model comprises a union of high-risk women identified by PRS, FH, and, LoF (AUC2-year [95% CI]: 62.2 [60.8 to 63.6]). Assigning individual weights to each risk prediction tool increased discriminatory ability.

Conclusion
Risk-based BC screening may require a multi-pronged approach that includes PRS, predisposition genes, FH, and other recognised risk factors.

URL: https://doi.org/10.1016/j.gim.2023.100917

19 May 2023

Submitted by (Bold are A*STAR Staff): Dillon W. P. Tay, Naythan Z. X. Yeo, Krishnan Adaikkappan, Yee Hwee Lim & Shi Jun Ang 

Research Institute: ISCE2, IHPC

Title of Paper: 67 million natural product-like compound database generated via molecular language processing

Published in: Data Descriptors

Abstract: Natural products are a rich resource of bioactive compounds for valuable applications across multiple fields such as food, agriculture, and medicine. For natural product discovery, high throughput in silico screening offers a cost-effective alternative to traditional resource-heavy assay-guided exploration of structurally novel chemical space. In this data descriptor, we report a characterized database of 67,064,204 natural product-like molecules generated using a recurrent neural network trained on known natural products, demonstrating a significant 165-fold expansion in library size over the approximately 400,000 known natural products. This study highlights the potential of using deep generative models to explore novel natural product chemical space for high throughput in silico discovery.

URL: https://doi.org/10.1038/s41597-023-02207-x

12 May 2023

Submitted by (Bold are A*STAR Staff): Shengwei Ma, Keni Chih-Hua Wu, Stephen Wan, Cary Turangan, Kai Liang Tan, Wei Shin Cheng, Jun Ming Tan, Bud Fox

Research Institute: IHPC, ARTC

Title of Paper: Numerical simulation and experimental study of normal force and particle speed in the robotic stream finishing process

Published in: Manufacturing Processes

Abstract: Normal force and particle speed are the two most important parameters in determining the mass removal rate on the workpiece in the stream finishing process. However, quantifying them is still a big challenge due to the complexity of the interaction between media flow and the workpiece. In this study, a continuum-based (μ(I) rheology) numerical model was developed to simulate the granular media flow in a robotic stream finishing (RSF) system and validated with in-house experimental data. A novel frictional wall-slip model was developed to describe the media flow speed on the surface of a rectangular workpiece. The impact of three key process variables: (i) immersion depth (D), (ii) angle of attack (θ), and (iii) radial distance (r) on the resulting normal force and media flow speed was analyzed. The resulting normal force on the workpiece strongly depends on the immersion depth. A small increase in the hydrostatic pressure is amplified through elevated effective viscosity near the workpiece, resulting in a significant increase in the normal force. A critical θ for the dependency of normal force was identified. Below the critical θ, the normal force varies slightly with the increase in θ. Above the critical θ, the normal force decreases rapidly with the increase in θ. The normal force also increases linearly with the increase in radial distance. In general, the media flow speed increases rapidly with θ. However, the increase peaks at θ = 75° due to the wake effect behind the leading edge. As D increases, the media flow speed only changes marginally, given the same θ. The media flow speed increases with radial distance, and the relationship is quadratic. We have validated – through experiments – that the numerical model can reliably predict both normal force and media flow speed on the rectangular workpiece. As the local material removal rate has a direct correlation to the normal force and the media flow speed, this numerical model is capable of predicting material removal distribution on an actual polished component and, therefore, will be an indispensable tool for conducting in-process optimization and toolpath planning.

URL: https://doi.org/10.1016/j.jmapro.2023.04.081

02 May 2023

Submitted by (Bold are A*STAR Staff): Wenwen Liu, Jian Liang Cheong, Man-Fai Ng, Jackie Y. Ying

Research Institute: IMRE, IHPC, ID Labs

Title of Paper: Carbon nitride mediated synthesis of titanium-based electrodes for high-performance asymmetric supercapacitors

Published in: Nano Energy

Abstract: Rational design of electrode materials with specific compositions and unique morphological and structural features to achieve supercapacitors (SCs) with high energy densities without compromising their inherent electrochemical merits remains a great challenge. Herein, a carbon nitride (C3N4) mediated “one-for-two” strategy was proposed to synthesize titanium nitride/carbon nanosheets (TiN/C) and titanium carbide/carbon nanosheets (TiC/C) with three-dimensional morphology and hierarchical structure, respectively. The derived TiN/C and TiC/C were used as cathode and anode materials, respectively, with excellent capacitor behavior in aqueous electrolyte. Specifically, asymmetric SCs constructed with the TiN/C cathode and the TiC/C anode delivered a large operation voltage of 0.3–1.8 V, a high specific capacitance of 103 F·g−1, and a remarkable energy density of 45.2 Wh·kg−1, outperforming most of the previously reported TiN- and TiC-based SCs. Ex situ XRD and TEM characterizations as well as DFT simulation indicated that the excellent performance could be attributed to reversible pseudocapacitive redox reaction and electro-adsorbed anions at the TiN/C cathode, and fast adsorption/desorption of cations at the TiC/C anode, as well as unique surface morphology and heterostructure. The strategy presented in this work also provides new design concepts for the synthesis of other transition metal nitrides (or carbides)/carbon composites for other advanced energy applications.

URL: https://doi.org/10.1016/j.nanoen.2023.108489

29 Apr 2023

Submitted by (Bold are A*STAR Staff): Guodong Liu, Chenye Shen and Anqi Qiu

Research Institute:

Title of Paper: Amyloid-β Accumulation in Relation to Functional Connectivity in Aging: a Longitudinal Study

Published in: NeuroImage

Abstract: The brain undergoes many changes at pathological and functional levels in healthy aging. This study employed a longitudinal and multimodal imaging dataset from the OASIS-3 study (n=300) and explored possible relationships between amyloid beta (Aβ) accumulation and functional brain organization over time in healthy aging. We used positron emission tomography (PET) with Pittsburgh compound-B (PIB) to quantify the Aβ accumulation in the brain and resting-state functional MRI (rs-fMRI) to measure functional connectivity (FC) among brain regions. Each participant had at least 2 to 3 follow-up visits. A linear mixed-effect model was used to examine longitudinal changes of Aβ accumulation and FC throughout the whole brain. We found that the limbic and frontoparietal networks had a greater annual Aβ accumulation and a slower decline in FC in aging. Additionally, the amount of the Aβ deposition in the amygdala network at baseline slowed down the decline in its FC in aging. Furthermore, the functional connectivity of the limbic, default mode network (DMN), and frontoparietal networks accelerated the Aβ propagation across their functionally highly connected regions. The functional connectivity of the somatomotor and visual networks accelerated the Aβ propagation across the brain regions in the limbic, frontoparietal, and DMN networks. These findings suggested that the slower decline in the functional connectivity of the functional hubs may compensate for their greater Aβ accumulation in aging. The Aβ propagation from one brain region to the other may depend on their functional connectivity strength.

URL: https://doi.org/10.1016/j.neuroimage.2023.120146

17 Apr 2023

Submitted by (Bold are A*STAR Staff): Qingwei Meng, Jiaxuan Zang, Wenli Zhang, Chengwu Qiu, Peng Zhao, Jia Zhang and Tiejun Wang

Research Institute: IHPC

Title of Paper: Selective furanyl ring hydrogenation of 5-hydroxymethylfurfural at sub-ambient temperature via steric effect on decorated Pd surfaces

Published in: International Journal of Hydrogen Energy

Abstract: It is a great challenge to synthesize the medical intermediate 5-hydroxymethyltetrahydrofurfural (HMTHF) from selective hydrogenation of 5-hydroxymethylfurfural (HMF), as the branched Cdouble bondO group is usually preferentially hydrogenated over active metal, e.g. Pd sites. Herein, we designed a surface-decorated Pd@NSi@Al2O3 catalyst and achieved selective hydrogenation of HMF, yielding 83.5% HMTHF at sub-ambient temperature (5 °C). Combination of experiments and DFT calculations verify the steric effect caused by the decoration of Pd surfaces led to larger bond lengths between O or C in –CHO ligand of HMF and the closest surface Pd sites. The total activation barrier for the hydrogenation reactions on the –CHO group of HMF becomes larger from 0.60 eV on Pd(111) to 0.83 eV on the cramped Pd(111). As a result, Cdouble bondC groups in the furanyl ring was preferentially hydrogenated over the branched Cdouble bondO of HMF. Furthermore, hydrogen bonds between the hydroxymethyl of the adsorbed HMF and the amine groups on Pd surfaces promote the adsorption of HMF and significantly increase the catalytic activity. Notably, this catalyst is robust and readily applicable in the furanyl ring hydrogenation of furfural and 5-methylfurfural. Overall, a controllable surface decoration strategy has been delivered that tailoring an efficient catalyst for selective hydrogenation of aromatic aldehyde.

URL: https://doi.org/10.1016/j.ijhydene.2023.03.227

10 Apr 2023

Submitted by (Bold are A*STAR Staff): Andrew Jun Yao Wong, Wei Ying Lieu, Deviprasath Chinnadurai, Man-Fai Ng, and Zhi Wei She

Research Institute: IMRE, IHPC

Title of Paper: Uncovering the Binder Interactions with S-PAN and MXene for Room Temperature Na–S Batteries

Published in: Nano Letters

Abstract: MXenes and sulfurized polyacrylonitrile (S-PAN) are emerging as possible contenders to resolve the polysulfide dissolution and volumetric expansion issues in sodium–sulfur batteries. Herein, we explore the interactions between Ti3C2Tx MXenes and S-PAN with traditional binders such as polyvinylidene difluoride (PVDF), poly(acrylic acid) (PAA), and carboxymethyl cellulose (CMC) in Na–S batteries for the first time. We hypothesize that the linearity and polarity of the binder significantly influence the dispersion of S-PAN over Ti3C2Tx. The three-dimensional polar CMC binder resulted in better contact surface area with both S-PAN and Ti3C2Tx. Moreover, the improved binding of the discharge products with the CMC binder effectively traps them and prevents unwanted shuttling. Consequently, the Na–S battery using the CMC binder displayed a high initial capacity of 1282 mAh/g(s) at 0.2 C and a low capacity fading of 0.092% per cycle over 300 cycles. This work highlights the importance of understanding MXene-binder interactions in sulfur cathodes.

URL: https://pubs.acs.org/doi/10.1021/acs.nanolett.3c00778

06 Apr 2023

Submitted by (Bold are A*STAR Staff): Krishna M. Gupta, Xavier Chin, Parijat Kanaujia 

Research Institute: ISCE2

Title of Paper: Molecular Interactions between APIs and Enteric Polymeric Excipients in Solid Dispersion: Insights from Molecular Simulations and Experiments

Published in: Pharmaceutics

Abstract: Solid dispersion of poorly soluble APIs is known to be a promising strategy to improve dissolution and oral bioavailability. To facilitate the development and commercialization of a successful solid dispersion formulation, understanding of intermolecular interactions between APIs and polymeric carriers is essential. In this work, first, we assessed the molecular interactions between various delayed-release APIs and polymeric excipients using molecular dynamics (MD) simulations, and then we formulated API solid dispersions using a hot melt extrusion (HME) technique. To assess the potential API–polymer pairs, three quantities were evaluated: (a) interaction energy between API and polymer [electrostatic (Ecoul), Lenard-Jones (ELJ), and total (Etotal)], (b) energy ratio (API–polymer/API–API), and (c) hydrogen bonding between API and polymer. The Etotal quantities corresponding to the best pairs: NPX-Eudragit L100, NaDLO–HPMC(P), DMF–HPMC(AS) and OPZ–HPMC(AS) were −143.38, −348.04, −110.42, and −269.43 kJ/mol, respectively. Using a HME experimental technique, few API–polymer pairs were successfully extruded. These extruded solid forms did not release APIs in a simulated gastric fluid (SGF) pH 1.2 environment but released them in a simulated intestinal fluid (SIF) pH 6.8 environment. The study demonstrates the compatibility between APIs and excipients, and finally suggests a potential polymeric excipient for each delayed-release API, which could facilitate the development of the solid dispersion of poorly soluble APIs for dissolution and bioavailability enhancement.

URL: https://doi.org/10.3390/pharmaceutics15041164

28 Mar 2023

Submitted by (Bold are A*STAR Staff): Naythan Z. X. Yeo, Dillon W. P. Tay, Shi Jun Ang

Research Institute: ISCE2,IHPC

Title of Paper: Benchmarking tandem mass spectra of small natural product molecules via ab initio molecular dynamics

Published in: ChemRxiv

Abstract: Natural products have proven to be valuable, particularly in the fields of drug discovery and chemogenomics. Tandem mass spectrometry, along with reference mass spectral libraries, has been frequently used to assist the characterization of natural products present in unknown complex mixtures. As current spectral libraries only contain a small percentage of known natural products, their continual expansion is crucial for accurate molecular identification. However, doing so through experimental means is often expensive and time-consuming. This study explores the use of ab initio molecular dynamics simulations (AIMD) based on the lightweight GFN2-xTB semiempirical Hamiltonian, to generate mass spectra for small natural products molecules. Through this approach, more than 2,700 unique mass spectra were generated and analysed in relation to the Global Natural Products Social Molecular Networking (GNPS) database. This study found that AIMD performs relative well (mean cosine similarity score of 0.68), with improved performance observed in aromatic molecules but limitations found when applied to molecules with carboxylic acid groups. Other key findings relating to experimental and simulated conditions also led to several recommendations for future work in this area. Overall, AIMD proved to have huge potential to be used to develop a putative natural product mass spectral library.

URL: https://doi.org/10.26434/chemrxiv-2023-7k5x8

27 Mar 2023

Submitted by (Bold are A*STAR Staff): Shuai Chen, Zachary H. Aitken, Subrahmanyam Pattamatta, Zhaoxuan Wu, Zhi Gen Yu,David J. Srolovitz, Peter K. Liaw, Yong-Wei Zhang

Research Institute: IHPC

Title of Paper: Short-range ordering alters the dislocation nucleation and propagation in refractory high-entropy alloys

Published in: Materials Today

Abstract: The role of short-range ordering (SRO) in the dislocation kinetics in refractory high-entropy alloys (RHEAs) remains controversial. On one hand, it was shown by simulations that the mobility of edge dislocations was enhanced while that of screw dislocations was reduced, leading to the conclusion that screw dislocations should be dominant. On the other hand, experiments exclusively showed the dominance of edge dislocations. Here, we investigate the impact of SRO in the grain interior and grain boundary on dislocation nucleation and propagation in a BCC MoTaTiWZr RHEA, using a combination of the density-functional theory calculations, Monte Carlo method, and molecular dynamic simulation. Our results show that this RHEA is energetically favorable to undergo SRO, thus forming a pseudo-composite microstructure. This microstructure consists of three categories of clusters: high energy clusters (HECs), medium energy clusters (MECs), and low energy clusters (LECs), with the HECs in grain boundaries acting as weak fillers to induce dislocation nucleation while the MECs/LECs serving as a strong matrix to stabilize the weak HECs. Importantly, SRO is found to enhance the energy barriers for both edge and screw dislocation motion and make the mobility of edge dislocations comparable to or even lower than screw dislocations, contributing to the dominance of edge dislocations in the BCC RHEA. Our work highlights the importance of SRO in influencing the dislocation activity of RHEAs and presents a fascinating route for designing RHEAs to achieve superior mechanical properties.

URL: https://doi.org/10.1016/j.mattod.2023.03.009

20 Mar 2023

Submitted by (Bold are A*STAR Staff): Changhong LINGHU, Yangchengyi Liu, Yee Yuan Tan, Jun Heng Marcus Sing, Yuxuan Tang, Aiwu Zhou, Xiufeng Wang, Dong Li, Huajian Gao, K. Jimmy Hsia

Research Institute: IHPC

Title of Paper: Overcoming the adhesion paradox and switchability conflict on rough
surfaces with shape-memory polymers

Published in: Applied Physical Sciences

Abstract: Smart adhesives that can be applied and removed on demand play an important role in modern life and manufacturing. However, current smart adhesives made of elastomers suffer from the long-standing challenges of the adhesion paradox (rapid decrease in adhesion strength on rough surfaces despite adhesive molecular interactions) and the switchability conflict (trade-off between adhesion strength and easy detachment). Here, we report the use of shape-memory polymers (SMPs) to overcome the adhesion paradox and switchability conflict on rough surfaces. Utilizing the rubbery–glassy phase transition in SMPs, we demonstrate, through mechanical testing and mechanics modeling, that the conformal contact in the rubbery state followed by the shape-locking effect in the glassy state results in the so-called rubber-to-glass (R2G) adhesion (defined as making contact in the rubbery state to a certain indentation depth followed by detachment in the glassy state), with extraordinary adhesion strength (>1 MPa) proportional to the true surface area of a rough surface, overcoming the classic adhesion paradox. Furthermore, upon transitioning back to the rubbery state, the SMP adhesives can detach easily due to the shape-memory effect, leading to a simultaneous improvement in adhesion switchability (up to 103, defined as the ratio of the SMP R2G adhesion to its rubbery-state adhesion) as the surface roughness increases. The working principle and the mechanics model of R2G adhesion provide guidelines for developing stronger and more switchable adhesives adaptable to rough surfaces, thereby enhancing the capabilities of smart adhesives, and impacting various fields such as adhesive grippers and climbing robots.

URL: https://doi.org/10.1073/pnas.2221049120

17 Mar 2023

Submitted by (Bold are A*STAR Staff): Anqi Qiu, Chaoqiang Liu

Research Institute:

Title of Paper: Pathways link environmental and genetic factors with structural brain networks and psychopathology in youth

Published in: Neuropsychopharmacology

Abstract: Adolescence is a period of significant brain development and maturation, and it is a time when many mental health problems first emerge. This study aimed to explore a comprehensive map that describes possible pathways from genetic and environmental risks to structural brain organization and psychopathology in adolescents. We included 32 environmental items on developmental adversity, maternal substance use, parental psychopathology, socioeconomic status (SES), school and family environment; 10 child psychopathological scales; polygenic risk scores (PRS) for 10 psychiatric disorders, total problems, and cognitive ability; and structural brain networks in the Adolescent Brain Cognitive Development study (ABCD, n = 9168). Structural equation modeling found two pathways linking SES, brain, and psychopathology. Lower SES was found to be associated with lower structural connectivity in the posterior default mode network and greater salience structural connectivity, and with more severe psychosis and internalizing in youth (p < 0.001). Prematurity and birth weight were associated with early-developed sensorimotor and subcortical networks (p < 0.001). Increased parental psychopathology, decreased SES and school engagement was related to elevated family conflict, psychosis, and externalizing behaviors in youth (p < 0.001). Increased maternal substance use predicted increased developmental adversity, internalizing, and psychosis (p < 0.001). But, polygenic risks for psychiatric disorders had moderate effects on brain structural connectivity and psychopathology in youth. These findings suggest that a range of genetic and environmental factors can influence brain structural organization and psychopathology during adolescence, and that addressing these risk factors may be important for promoting positive mental health outcomes in young people.

URL: https://doi.org/10.1038/s41386-023-01559-7

13 Mar 2023

Submitted by (Bold are A*STAR Staff): Cihan Acar, Kuluhan Binici, Alp Tekirdağ, Wu Yan

Research Institute: I2R

Title of Paper: Visual-Policy Learning through Multi-Camera View to Single-Camera View Knowledge Distillation for Robot Manipulation Tasks

Published in: arXIV [cs.CV]

Abstract: The use of multi-camera views simultaneously has been shown to improve the generalization capabilities and performance of visual policies. However, the hardware cost and design constraints in real-world scenarios can potentially make it challenging to use multiple cameras. In this study, we present a novel approach to enhance the generalization performance of vision-based Reinforcement Learning (RL) algorithms for robotic manipulation tasks. Our proposed method involves utilizing a technique known as knowledge distillation, in which a pre-trained ``teacher'' policy trained with multiple camera viewpoints guides a ``student'' policy in learning from a single camera viewpoint. To enhance the student policy's robustness against camera location perturbations, it is trained using data augmentation and extreme viewpoint changes. As a result, the student policy learns robust visual features that allow it to locate the object of interest accurately and consistently, regardless of the camera viewpoint. The efficacy and efficiency of the proposed method were evaluated both in simulation and real-world environments. The results demonstrate that the single-view visual student policy can successfully learn to grasp and lift a challenging object, which was not possible with a single-view policy alone. Furthermore, the student policy demonstrates zero-shot transfer capability, where it can successfully grasp and lift objects in real-world scenarios for unseen visual configurations.

URL: https://doi.org/10.48550/arXiv.2303.07026

9 Mar 2023

Submitted by (Bold are A*STAR Staff): Wen-Qing Li, Juan Manuel Arce-Ramos, Michael B. Sullivan, Chee Kok Poh, Luwei Chen, Armando Borgna, Jia Zhang

Research Institute: IHPC, ISCE2

Title of Paper: Mechanistic insights into selective ethylene formation on the χ-Fe5C2 (510) surface

Published in: Journal of Catalysis

Abstract: While iron carbide catalysts are widely used to produce diverse hydrocarbons during Fisher-Tropsch synthesis, the complexity of the catalyst and reaction makes it very challenging to obtain a deep understanding of the chemical process and to further improve the performance. In this work, we propose a novel mechanism through density functional theory simulations for CO-derived surface C hydrogenation to C2H4 involving previously unexplored surface diffusion of partially hydrogenated intermediates (CH, CHCH), which significantly reduces the effective energy barrier (Ea-eff) of CH2CH2 from 2.89 eV to 2.10 eV. The hydrogenation of CH2CH to C2H4 is the key step of the entire process. Studies on the correlation between the average Bader charge of surface Fe and the Ea-eff of CH4 and CH2CH2 formation indicate that an increase in the positive charge of iron can enhance the activity and selectivity (with reference to CH4) of ethylene formation.

URL: https://doi.org/10.1016/j.jcat.2023.03.014

8 Mar 2023

Submitted by (Bold are A*STAR Staff): Fabio Bussolotti, Hiroyo Kawai, Ivan Verzhbitskiy, Wei Tao, Duc-Quan Ho, Anirban Das, Junxiang Jia, Shantanu Mukherjee, Bent Weber, and Kuan Eng Johnson Goh

Research Institute: IMRE, IHPC

Title of Paper: Interlayer hybridization in a van der Waals quantum spin-Hall insulator/superconductor heterostructure

Published in: AIP Advances

Abstract: In this work, we present an angle-resolved photoemission spectroscopy study of a 1T′-WTe2 monolayer epitaxially grown on NbSe2 substrates, a prototypical quantum spin Hall insulator (QSHI)/superconductor heterojunction. Angle-resolved photoemission spectroscopy data indicate the formation of electronic states in the bulk bandgap of WTe2, which are absent in the nearly free-standing WTe2 grown on the highly oriented pyrolytic graphite substrate, where an energy gap of ∼100 meV is reported. The results are explained in terms of hybridization effects promoted by the QSHI–superconductor interaction at WTe2/NbSe2 interfaces, in line with recent scanning probe microscopy investigation and theoretical band structure calculations. Our findings highlight the important role of interlayer interaction on the electronic properties and ultimately on the engineering of topological properties of the QSHI/superconducting heterostructure.

URL: https://doi.org/10.1063/5.0130393

18 Feb 2023

Submitted by (Bold are A*STAR Staff): Jinghan Huang, Moo K. Chung, Anqi Qiu

Research Institute:

Title of Paper: Heterogeneous Graph Convolutional Neural Network via Hodge-Laplacian for Brain Functional Data

Published in: arXIV [cs.CV]

Abstract: This study proposes a novel heterogeneous graph convolutional neural network (HGCNN) to handle complex brain fMRI data at regional and across-region levels. We introduce a generic formulation of spectral filters on heterogeneous graphs by introducing the k−th Hodge-Laplacian (HL) operator. In particular, we propose Laguerre polynomial approximations of HL spectral filters and prove that their spatial localization on graphs is related to the polynomial order. Furthermore, based on the bijection property of boundary operators on simplex graphs, we introduce a generic topological graph pooling (TGPool) method that can be used at any dimensional simplices. This study designs HL-node, HL-edge, and HL-HGCNN neural networks to learn signal representation at a graph node, edge levels, and both, respectively. Our experiments employ fMRI from the Adolescent Brain Cognitive Development (ABCD; n=7693) to predict general intelligence. Our results demonstrate the advantage of the HL-edge network over the HL-node network when functional brain connectivity is considered as features. The HL-HGCNN outperforms the state-of-the-art graph neural networks (GNNs) approaches, such as GAT, BrainGNN, dGCN, BrainNetCNN, and Hypergraph NN. The functional connectivity features learned from the HL-HGCNN are meaningful in interpreting neural circuits related to general intelligence.

URL: https://doi.org/10.48550/arXiv.2302.09323

14 Feb 2023

Submitted by (Bold are A*STAR Staff): Zi S. D. Toa, Maria V. Chekhova, Leonid A. Krivitsky, Anna V. Paterova

Research Institute: IMRE

Title of Paper: Crystal superlattices for versatile and sensitive quantum spectroscopy

Published in: Optics Express

Abstract: Nonlinear interferometers with quantum correlated photons have been demonstrated to improve optical characterization and metrology. These interferometers can be used in gas spectroscopy, which is of particular interest for monitoring greenhouse gas emissions, breath analysis and industrial applications. Here, we show that gas spectroscopy can be further enhanced via the deployment of crystal superlattices. This is a cascaded arrangement of nonlinear crystals forming interferometers, allowing the sensitivity to scale with the number of nonlinear elements.
In particular, the enhanced sensitivity is observed via the maximum intensity of interference fringes that scales with low concentration of infrared absorbers, while for high concentration the sensitivity is better in interferometric visibility measurements. Thus, a superlattice acts as a versatile gas sensor since it can operate by measuring different observables, which are relevant to practical applications. We believe that our approach offers a compelling path towards further enhancements for quantum metrology and imaging using nonlinear interferometers with correlated photons.

URL: https://doi.org/10.1364/OE.477019

10 Feb 2023

Submitted by (Bold are A*STAR Staff): Choon Wee Kee

Research Institute: ISCE2

Title of Paper: Molecular Understanding and Practical In Silico Catalyst Design in Computational Organocatalysis and Phase Transfer Catalysis—Challenges and Opportunities

Published in: Molecules 2023

Abstract: Through the lens of organocatalysis and phase transfer catalysis, we will examine the key components to calculate or predict catalysis-performance metrics, such as turnover frequency and measurement of stereoselectivity, via computational chemistry. The state-of-the-art tools available to calculate potential energy and, consequently, free energy, together with their caveats, will be discussed via examples from the literature. Through various examples from organocatalysis and phase transfer catalysis, we will highlight the challenges related to the mechanism, transition state theory, and solvation involved in translating calculated barriers to the turnover frequency or a metric of stereoselectivity. Examples in the literature that validated their theoretical models will be showcased. Lastly, the relevance and opportunity afforded by machine learning will be discussed.

URL: https://doi.org/10.3390/molecules28041715

9 Feb 2023

Submitted by (Bold are A*STAR Staff): V. Vijendran, Aritra Das, Dax Enshan Koh, Syed M. Assad, Ping Koy Lam

Research Institute: IMRE, IHPC

Title of Paper: An Expressive Ansatz for Low-Depth Quantum Optimisation

Published in: arXIV [quant-ph]

Abstract: The Quantum Approximate Optimisation Algorithm (QAOA) is a hybrid quantum-classical algorithm used to approximately solve combinatorial optimisation problems. It involves multiple iterations of a parameterised ansatz that consists of a problem and mixer Hamiltonian, with the parameters being classically optimised. While QAOA can be implemented on near-term quantum hardware, physical limitations such as gate noise, restricted qubit connectivity, and state-preparation-and-measurement (SPAM) errors can limit circuit depth and decrease performance. To address these limitations, this work introduces the eXpressive QAOA (XQAOA), a modified version of QAOA that assigns more classical parameters to the ansatz to improve the performance of low-depth quantum circuits. XQAOA includes an additional Pauli-Y component in the mixer Hamiltonian, thereby allowing the mixer to implement arbitrary unitary transformations on each qubit. To benchmark the performance of the XQAOA ansatz at low depth, we derive its closed-form expression for the MaxCut problem and compare it to QAOA, Multi-Angle QAOA (MA-QAOA), a Classical-Relaxed (CR) algorithm, and the state-of-the-art Goemans-Williamson (GW) algorithm on a set of unweighted regular graphs with 128 and 256 nodes and degrees ranging from 3 to 10. Our results show that XQAOA performs better than QAOA, MA-QAOA, and the CR algorithm on all graphs and outperforms the GW algorithm on graphs with degrees greater than 4. Additionally, we find an infinite family of graphs for which XQAOA solves MaxCut exactly and show analytically that for some graphs in this family, special cases of XQAOA can achieve a larger approximation ratio than QAOA. Overall, XQAOA is a more viable choice for implementing quantum combinatorial optimisation on near-term quantum devices, as it can achieve better results with a single iteration, despite requiring additional classical resources.

URL: https://doi.org/10.48550/arXiv.2302.04479

23 Jan 2023

Submitted by (Bold are A*STAR Staff): Nikhil Tulsian, Palur Raghuvamsi, Xinlei Qian, Yue Gu, Bhuvaneshwari D/O Shunmuganathan, Firdaus Samsudin, Yee Hwa Wong, Jianqing Lin, Kiren Purushotorman, Mary Kozma, BEI WANG, Julien Lescar, Cheng-I Wang, Ravindra Gupta, Peter Bond, Paul MacAry

Research Institute: BII, SIgN

Title of Paper: Defining neutralization and allostery by antibodies against COVID-19 variants

Published in: Nature Communications

Abstract: The changing landscape of mutations in the SARS-CoV-2 Spike protein is linked to the emergence of variants, immune-escape and reduced efficacy of the existing repertoire of anti-viral antibodies. A major factor that contributes to the functional activity of the neutralizing antibodies are the intrinsic quaternary changes that occur as a result of antibody-Spike trimer interactions. In this study, we reveal the conformational dynamics and allosteric perturbations linked to binding of human monoclonal antibodies and the viral Spike protein. We identify epitope hotspots of known and novel antibodies, and associated changes in Spike dynamics that define weak, moderate and strong neutralizing antibodies. We show the impact of mutations in Wuhan, Delta, and Omicron variants of concern (VoCs) and differences observed in the antibody-induced conformational changes and illustrate how these render certain antibodies ineffective. Our comparative analyses of the antibody-footprints on Spike variants reveal how antibodies with similar binding affinities may induce destabilizing and stabilizing allosteric effects. These differences have important implications for neutralization efficacy and for developing new antibodies targeting emerging variants. Our results provide mechanistic insights into the functional modes and synergistic behavior of human antibodies against COVID-19, and provide a rationale to design effective antiviral strategies.

URL: https://doi.org/10.21203/rs.3.rs-2465199/v1

20 Jan 2023

Submitted by (Bold are A*STAR Staff): Carina Yi Jing Lim, Meltem Yilmaz, Juan Manuel Arce-Ramos, Albertus D. Handoko, Wei Jie Teh, Yuangang Zheng, Zi Hui Jonathan Khoo, Ming Lin, Mark Isaacs, Teck Lip Dexter Tam, Yang Bai, Chee Koon Ng, Boon Siang Yeo, Gopinathan Sankar, Ivan P. Parkin, Kedar Hippalgaonkar, Michael B. Sullivan, Jia Zhang & Yee-Fun Lim  

Research Institute: IHPC, IMRE

Title of Paper: Surface charge as activity descriptors for electrochemical CO2 reduction to multi-carbon products on organic-functionalised Cu

Published in: Nature Communications

Abstract: Intensive research in electrochemical CO2 reduction reaction has resulted in the discovery of numerous high-performance catalysts selective to multi-carbon products, with most of these catalysts still being purely transition metal based. Herein, we present high and stable multi-carbon products selectivity of up to 76.6% across a wide potential range of 1 V on histidine-functionalised Cu. In-situ Raman and density functional theory calculations revealed alternative reaction pathways that involve direct interactions between adsorbed histidine and CO2 reduction intermediates at more cathodic potentials. Strikingly, we found that the yield of multi-carbon products is closely correlated to the surface charge on the catalyst surface, quantified by a pulsed voltammetry-based technique which proved reliable even at very cathodic potentials. We ascribe the surface charge to the population density of adsorbed species on the catalyst surface, which may be exploited as a powerful tool to explain CO2 reduction activity and as a proxy for future catalyst discovery, including organic-inorganic hybrids.

URL: https://doi.org/10.1038/s41467-023-35912-7

10 Jan 2023

Submitted by (Bold are A*STAR Staff): Sabrina L. Slimani, Roman Kostecki, Ahmed Nuri Kursunlu, Tak W. Kee, Patrick C. Tapping, Adrian M. Mak and James Q. Quach  

Research Institute: IHPC

Title of Paper: Experimental and computational characterisation of an artificial light harvesting complex

Published in: Royal Society of Chemistry

Abstract: Photosynthesis has been shown to be a highly efficient process for energy transfer in plants and bacteria. Like natural photosynthetic systems, the artificial light harvesting complex (LHC) BODIPY pillar[5]arene exhibits Förster resonance energy transfer (FRET). However, extensive characterisation of the BODIPY pillar[5]arene LHC to determine its suitability as an artificial LHC has yet to occur. In this paper we experimentally and computationally investigate the photophysical properties of the LHC by comparing the light absorption of the BODIPY LHC to individual BODIPY chromophores. Our results show evidence for quantum coherence, with oscillation frequencies of 100 cm−1 and 600 cm−1, which are attributable to vibronic, or exciton–phonon type coupling. Computational analysis suggests strong couplings of the molecular orbitals of the LHC resulting from the stacking of neighbouring BODIPY chromophore units. Interestingly, we find a 40% reduction in the absorbance of light for the BODIPY LHC compared to the individual chromophores which we attribute to electronic interactions between the conjugated π-systems of the BODIPY chromophores and the pillar[5]arene backbone.

URL: https://doi.org/10.1039/D2CP03858G

06 Jan 2023

Submitted by (Bold are A*STAR Staff): Yingying Jiang, Martial Duchamp, Shi Jun Ang, Hongwei Yan, Teck Leong Tan & Utkur Mirsaidov

Research Institute: IHPC

Title of Paper: Dynamics of the fcc-to-bcc phase transition in single-crystalline PdCu alloy nanoparticles

Published in: Nature Communications

Abstract: Two most common crystal structures in metals and metal alloys are body-centered cubic (bcc) and face-centered cubic (fcc) structures. The phase transitions between these structures play an important role in the production of durable and functional metal alloys. Despite their technological significance, the details of such phase transitions are largely unknown because of the challenges associated with probing these processes. Here, we describe the nanoscopic details of an fcc-to-bcc phase transition in PdCu alloy nanoparticles (NPs) using in situ heating transmission electron microscopy. Our observations reveal that the bcc phase always nucleates from the edge of the fcc NP, and then propagates across the NP by forming a distinct few-atoms-wide coherent bcc–fcc interface. Notably, this interface acts as an intermediate precursor phase for the nucleation of a bcc phase. These insights into the fcc-to-bcc phase transition are important for understanding solid − solid phase transitions in general and can help to tailor the functional properties of metals and their alloys.

URL: https://doi.org/10.1038/s41467-022-35325-y