A5103137196- Machine Learning in Materials Science
- Metal-Organic Frameworks: Synthesis and Applications
- Advanced battery technologies research
- Advanced Photocatalysis Techniques
- Transition Metal Oxide Nanomaterials
- Carbon dioxide utilization in catalysis
- Advanced Optical Network Technologies
- Catalysis and Oxidation Reactions
- Satellite Communication Systems
- Opinion Dynamics and Social Influence
- Traffic control and management
- Advanced Battery Materials and Technologies
- Advanced Photonic Communication Systems
- Computational Drug Discovery Methods
- Transportation Planning and Optimization
- TiO2 Photocatalysis and Solar Cells
- Advanced Battery Technologies Research
- Traffic Prediction and Management Techniques
- Gas Sensing Nanomaterials and Sensors
- Liquid Crystal Research Advancements
- Advancements in Battery Materials
- Advanced Materials and Mechanics
- Software-Defined Networks and 5G
- Energy Efficiency and Management
- Advanced Thermoelectric Materials and Devices
Northwestern University
2023-2025
Argonne National Laboratory
2023-2024
Zhengzhou University
2021-2024
Hokkaido University
2022-2024
University of Chicago
2024
University of Science and Technology Beijing
2024
Chinese Academy of Sciences
2023
Dalian Institute of Chemical Physics
2023
University of Chinese Academy of Sciences
2023
Dalian National Laboratory for Clean Energy
2023
Abstract Metal-organic frameworks (MOFs) exhibit great promise for CO 2 capture. However, finding the best performing materials poses computational and experimental grand challenges in view of vast chemical space potential building blocks. Here, we introduce GHP-MOFassemble, a generative artificial intelligence (AI), high performance framework rational accelerated design MOFs with adsorption capacity synthesizable linkers. GHP-MOFassemble generates novel linkers, assembled one three...
Abstract In data-driven materials design where the target have limited data, transfer machine learning from large known source materials, becomes a demanding strategy especially across different crystal structures. this work, we proposed deep approach to predict thermodynamically stable perovskite oxides based on computational dataset of spinel oxides. The neural network (DNN) domain model with “Center-Environment” (CE) features was first developed using formation energy 5329 oxide...
Caution is essential when using SS coin cells in aqueous battery research due to the negative impact. We show that commonly used cell provokes a severe hydrogen evolution reaction causing disruptive interference Zn plating/stripping processes, which can be mitigated with Ti spacer.
The computational search for new stable inorganic compounds is faster than ever, thanks to high-throughput density functional theory (DFT). However, compound searches remain highly expensive because of the enormous space and cost DFT calculations. To aid these searches, recommendation engines have been developed. We conduct a systematic comparison performance previously developed engines, specifically ones based on elemental substitution, data mining, neural network prediction formation...
Abstract We introduce an end-to-end computational framework that allows for hyperparameter optimization using the DeepHyper library, accelerated model training, and interpretable AI inference. The is based on state-of-the-art models including CGCNN , PhysNet SchNet MPNN MPNN-transformer TorchMD-NET . employ these along with benchmark QM9 hMOF MD17 datasets to showcase how can predict user-specified material properties within modern computing environments. demonstrate transferable...
Machine learning (ML) is gaining popularity as a tool for materials scientists to accelerate computation, automate data analysis, and predict properties. The representation of input material features critical the accuracy, interpretability, generalizability data-driven models scientific research. In this Perspective, we discuss few central challenges faced by ML practitioners in developing meaningful representations, including handling complexity real-world industry-relevant materials,...
The homo anion–cation coupling of cyclic diaryl λ 3 -bromanes/diarylbrominiums has been disclosed for the first time. Moreover, metal-free cross-coupling diarylbrominiums with alcohols, phenols, and water developed.
Pure Magneli phase Ti 4 O 7 nanoparticles with diameters of 200–500 nm were successfully synthesised under hydrogen atmospheres. In this reported work, the influences reduction temperature and time on reduced phases investigated, it is shown that pure can be obtained by heating at 850°C for 5 h. The as‐prepared materials are characterised X‐ray diffraction (XRD), scanning electron microscopy, transmission corresponding selected area indicates single‐crystal structure, which also consistent...
Abstract: Catalytic oxidation is a commonly employed technology in the industry for removing volatile organic compounds (VOCs) due to its exceptional efficiency under mild operating conditions. Although supported Pt-based nano-catalysts are recognized widely as one of most promising and extensively used industrial catalysts VOC abatement, their practical application, development restricted by exorbitant cost. Single-atom catalyst (SAC) with maximized metal utilization exclusive electronic...
The carrier-borne aircraft dispatch rate is an important indicator to measure the combat performance of carrier. key factor affecting efficiency carrier support operation scheduling. Shipboard scheduling refers a rational arrangement order operations required by as well efficient completion for under constraints limited time, space, and resources. existing solution strategies based on optimization methods (dynamic programming, linear etc.) heuristic (genetic algorithm, particle swarm...
The advancement of deep learning in chemistry has resulted state-of-the-art models that incorporate an increasing number concepts from standard quantum chemistry, such as orbitals and Hamiltonians. With eye towards the future development these approaches, we present here what believe to be first work focused on assigning labels orbitals, namely energies characterizations, given real-space descriptions electronic structure theories Hartree-Fock. In addition providing a foundation for...
Abstract The trend of miniaturization and intgration the electronic device has put forward higher requirements on efficiency heat radiating, which can hardly be satisfied by traditional forced convection dissipation method. In this paper, strategy topology optimization technique is adopted to greatly improve a semiconductor ignition device. penalization method used implement process. Three kinds objective functions thermal compliance, temperature variance geometric average were separately...
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Comprehensive Summary Stimulus‐sensitive surfaces with tunable morphologies exhibit a wide range of applications in the fields surface science and engineering. Herein, cost‐effective yet practical strategy is proposed to fabricate photo‐sensitive patterning on film/substrate wrinkle system based an azo‐containing polyblend. By manipulating stress field bilayer globally and/or locally upon relaxation triggered by reversible cis ‐ trans isomerization azobenzene, heating/cooling wrinkles...