Efficient and Accurate Local Equivariant Deep Neural Network Interatomic Potential for Large-Scale Porous Liquids Simulations
<p dir="ltr">Porous materials serve diverse applications like molecular separations and catalysis, offering an energy-efficient method for capturing greenhouse gases (CO<sub>2</sub>, and CH<sub>4</sub>) and valuable noble gases (Xe, Ar, and Kr). Xenon — vital...
محفوظ في:
| المؤلف الرئيسي: | Ouail Zakary (19740229) (author) |
|---|---|
| مؤلفون آخرون: | Perttu Lantto (19740246) (author) |
| منشور في: |
2024
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| الموضوعات: | |
| الوسوم: |
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مواد مشابهة
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Combining Molecular Dynamics with Deep Neural Network Architectures for Realistic Simulations of Porous Liquids
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Efficient and Accurate Local Equivariant Deep Neural Network Interatomic Potential for Large-Scale Porous Liquids Simulations
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Host-Guest Dynamics in Porous Liquids Modeled Using E(3)-Equivariant Neural Networks
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Equivariant Neural Networks Reveal How Host–Guest Interactions Shape Xenon NMR Chemical Shift in Porous Organic Cages
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منشور في: (2025) -
Local E(3)-Equivariant Neural Network Force Field for Modeling Host-Guest Interactions in Xenon-Based Porous Organic Cages
حسب: Ouail Zakary (19740229)
منشور في: (2025)