日期 影响因子
日期:
2020 年 — 2026 年
2020
2021
2022
2023
2024
2025
2026
影响因子:
–

Crash testing machine learning force fields for molecules, materials, and interfaces: molecular dynamics in the TEA challenge 2023

碰撞测试机器学习力场在分子、材料和界面中的应用：TEA 2023挑战赛中的分子动力学

期刊:Chemical Science
影响因子:7.4
doi:10.1039/d4sc06530a
Poltavsky, Igor; Puleva, Mirela; Charkin-Gorbulin, Anton; Fonseca, Grégory; Batatia, Ilyes; Browning, Nicholas J; Chmiela, Stefan; Cui, Mengnan; Frank, J Thorben; Heinen, Stefan; Huang, Bing; Käser, Silvan; Kabylda, Adil; Khan, Danish; Müller, Carolin; Price, Alastair J A; Riedmiller, Kai; Töpfer, Kai; Ko, Tsz Wai; Meuwly, Markus; Rupp, Matthias; Csányi, Gábor; Anatole von Lilienfeld, O; Margraf, Johannes T; Müller, Klaus-Robert; Tkatchenko, Alexandre
发表日期：2025
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Crash testing machine learning force fields for molecules, materials, and interfaces: model analysis in the TEA Challenge 2023

分子、材料和界面的碰撞测试机器学习力场：TEA Challenge 2023 中的模型分析

期刊:Chemical Science
影响因子:7.4
doi:10.1039/d4sc06529h
Poltavsky, Igor; Charkin-Gorbulin, Anton; Puleva, Mirela; Fonseca, Grégory; Batatia, Ilyes; Browning, Nicholas J; Chmiela, Stefan; Cui, Mengnan; Frank, J Thorben; Heinen, Stefan; Huang, Bing; Käser, Silvan; Kabylda, Adil; Khan, Danish; Müller, Carolin; Price, Alastair J A; Riedmiller, Kai; Töpfer, Kai; Ko, Tsz Wai; Meuwly, Markus; Rupp, Matthias; Csányi, Gábor; von Lilienfeld, O Anatole; Margraf, Johannes T; Müller, Klaus-Robert; Tkatchenko, Alexandre
发表日期：2025
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Explainable chemical artificial intelligence from accurate machine learning of real-space chemical descriptors

基于真实空间化学描述符的精确机器学习的可解释化学人工智能

期刊:Nature Communications
影响因子:15.7
doi:10.1038/s41467-024-48567-9
Gallegos, Miguel; Vassilev-Galindo, Valentin; Poltavsky, Igor; Martín Pendás, Ángel; Tkatchenko, Alexandre
发表日期：2024
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Accurate Quantum Monte Carlo Forces for Machine-Learned Force Fields: Ethanol as a Benchmark

用于机器学习力场的精确量子蒙特卡罗力：以乙醇为基准

期刊:Journal of Chemical Theory and Computation
影响因子:5.5
doi:10.1021/acs.jctc.4c00498
Slootman, E; Poltavsky, I; Shinde, R; Cocomello, J; Moroni, S; Tkatchenko, A; Filippi, C
发表日期：2024
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Efficient interatomic descriptors for accurate machine learning force fields of extended molecules

用于扩展分子精确机器学习力场的高效原子间描述符

期刊:Nature Communications
影响因子:15.7
doi:10.1038/s41467-023-39214-w
Kabylda, Adil; Vassilev-Galindo, Valentin; Chmiela, Stefan; Poltavsky, Igor; Tkatchenko, Alexandre
发表日期：2023
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Author Correction: Efficient interatomic descriptors for accurate machine learning force fields of extended molecules

作者更正：用于扩展分子精确机器学习力场的高效原子间描述符

期刊:Nature Communications
影响因子:15.7
doi:10.1038/s41467-023-39798-3
Kabylda, Adil; Vassilev-Galindo, Valentin; Chmiela, Stefan; Poltavsky, Igor; Tkatchenko, Alexandre
发表日期：2023
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Force Field Analysis Software and Tools (FFAST): Assessing Machine Learning Force Fields under the Microscope

力场分析软件和工具（FFAST）：显微镜下评估机器学习力场

期刊:Journal of Chemical Theory and Computation
影响因子:5.5
doi:10.1021/acs.jctc.3c00985
Fonseca, Gregory; Poltavsky, Igor; Tkatchenko, Alexandre
FAS
发表日期：2023
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Machine Learning Force Fields

机器学习力场

期刊:Chemical Reviews
影响因子:55.8
doi:10.1021/acs.chemrev.0c01111
Unke, Oliver T; Chmiela, Stefan; Sauceda, Huziel E; Gastegger, Michael; Poltavsky, Igor; Schütt, Kristof T; Tkatchenko, Alexandre; Müller, Klaus-Robert
发表日期：2021
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Machine learning of accurate energy-conserving molecular force fields

机器学习实现精确的能量守恒分子力场

期刊:Science Advances
影响因子:12.5
doi:10.1126/sciadv.1603015
Chmiela, Stefan; Tkatchenko, Alexandre; Sauceda, Huziel E; Poltavsky, Igor; Schütt, Kristof T; Müller, Klaus-Robert
发表日期：2017
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Modeling quantum nuclei with perturbed path integral molecular dynamics

利用扰动路径积分分子动力学模拟量子核

期刊:Chemical Science
影响因子:7.4
doi:10.1039/c5sc03443d
Poltavsky, Igor; Tkatchenko, Alexandre
发表日期：2016
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