Machine learning accelerates the materials discovery
J Fang, M Xie, X He, J Zhang, J Hu, Y Chen… - Materials Today …, 2022 - Elsevier
As the big data generated by the development of modern experiments and computing
technology becomes more and more accessible, the material design method based on …
technology becomes more and more accessible, the material design method based on …
Recent trends in computational tools and data-driven modeling for advanced materials
V Singh, S Patra, NA Murugan, DC Toncu… - Materials …, 2022 - pubs.rsc.org
The paradigm of advanced materials has grown exponentially over the last decade, with
their new dimensions including digital design, dynamics, and functions. Materials modeling …
their new dimensions including digital design, dynamics, and functions. Materials modeling …
Chatgpt research group for optimizing the crystallinity of mofs and cofs
We leveraged the power of ChatGPT and Bayesian optimization in the development of a
multi-AI-driven system, backed by seven large language model-based assistants and …
multi-AI-driven system, backed by seven large language model-based assistants and …
Applying machine learning to design delicate amorphous micro-nano materials for rechargeable batteries
T Zheng, Z Huang, H Ge, P Hu, X Fan, B Jia - Energy Storage Materials, 2024 - Elsevier
As modern society evolves, the global importance of energy requirements has grown
significantly. Thus, exploring new materials for renewable energy storage is urgently …
significantly. Thus, exploring new materials for renewable energy storage is urgently …
Accelerating the prediction of inorganic surfaces with machine learning interatomic potentials
K Noordhoek, C Bartel - Nanoscale, 2024 - pubs.rsc.org
The surface properties of solid-state materials often dictate their functionality, especially for
applications where nanoscale effects become important. The relevant surface (s) and their …
applications where nanoscale effects become important. The relevant surface (s) and their …
Recent progress on surface chemistry II: property and characterization
Surface with well-defined components and structures possesses unique electronic,
magnetic, optical and chemical properties. As a result, surface chemistry research plays a …
magnetic, optical and chemical properties. As a result, surface chemistry research plays a …
Performance evaluation of ZnSnN2 solar cells with Si back surface field using SCAPS-1D: A theoretical study
The earth-abundant semiconductor zinc tin nitride (ZnSnN 2) has garnered significant
attention as a prospective material in photovoltaic and lighting applications, primarily due to …
attention as a prospective material in photovoltaic and lighting applications, primarily due to …
Predicting Molecular Self-Assembly on Metal Surfaces Using Graph Neural Networks Based on Experimental Data Sets
F Zheng, J Lu, Z Zhu, H Jiang, Y Yan, Y He, S Yuan… - ACS …, 2023 - ACS Publications
The application of supramolecular chemistry on solid surfaces has received extensive
attention in the past few decades. To date, combining experiments with quantum mechanical …
attention in the past few decades. To date, combining experiments with quantum mechanical …
[HTML][HTML] Elucidating precipitation in FeCrAl alloys through explainable AI: A case study
A primary challenge of using FeCrAl in high temperature industrial settings is the formation
of α′-precipitates that causes brittleness in the alloy, resulting in failure through fracture …
of α′-precipitates that causes brittleness in the alloy, resulting in failure through fracture …
Comparison of Machine Learning Approaches for Prediction of the Equivalent Alkane Carbon Number for Microemulsions Based on Molecular Properties
The chemical properties of oils are vital in the design of microemulsion systems. The
hydrophilic–lipophilic difference equation used to predict microemulsions' phase behavior …
hydrophilic–lipophilic difference equation used to predict microemulsions' phase behavior …