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

Including Physics-Informed Atomization Constraints in Neural Networks for Reactive Chemistry

将物理信息原子化约束纳入反应化学神经网络

Zhang, Shuhao; Chigaev, Michael; Isayev, Olexandr; Messerly, Richard A; Lubbers, Nicholas

Data Generation for Machine Learning Interatomic Potentials and Beyond

用于机器学习的数据生成:原子间势及其他

Kulichenko, Maksim; Nebgen, Benjamin; Lubbers, Nicholas; Smith, Justin S; Barros, Kipton; Allen, Alice E A; Habib, Adela; Shinkle, Emily; Fedik, Nikita; Li, Ying Wai; Messerly, Richard A; Tretiak, Sergei

Exploring the frontiers of condensed-phase chemistry with a general reactive machine learning potential

利用通用反应机器学习潜力探索凝聚相化学的前沿领域

Zhang, Shuhao; Makoś, Małgorzata Z; Jadrich, Ryan B; Kraka, Elfi; Barros, Kipton; Nebgen, Benjamin T; Tretiak, Sergei; Isayev, Olexandr; Lubbers, Nicholas; Messerly, Richard A; Smith, Justin S

Measurement of the axial vector form factor from antineutrino-proton scattering

利用反中微子-质子散射测量轴矢量形状因子

Cai, T; Moore, M L; Olivier, A; Akhter, S; Dar, Z Ahmad; Ansari, V; Ascencio, M V; Bashyal, A; Bercellie, A; Betancourt, M; Bodek, A; Bonilla, J L; Bravar, A; Budd, H; Caceres, G; Carneiro, M F; Díaz, G A; da Motta, H; Felix, J; Fields, L; Filkins, A; Fine, R; Gago, A M; Gallagher, H; Gilligan, S M; Gran, R; Granados, E; Harris, D A; Henry, S; Jena, D; Jena, S; Kleykamp, J; Klustová, A; Kordosky, M; Last, D; Le, T; Lozano, A; Lu, X-G; Maher, E; Manly, S; Mann, W A; Mauger, C; McFarland, K S; Messerly, B; Miller, J; Moreno, O; Morfín, J G; Naples, D; Nelson, J K; Nguyen, C; Paolone, V; Perdue, G N; Plows, K-J; Ramírez, M A; Ransome, R D; Ray, H; Ruterbories, D; Schellman, H; Salinas, C J Solano; Su, H; Sultana, M; Syrotenko, V S; Valencia, E; Vaughan, N H; Waldron, A V; Wascko, M O; Wret, C; Yaeggy, B; Zazueta, L

Uncertainty-driven dynamics for active learning of interatomic potentials

基于不确定性的动力学方法用于主动学习原子间势

Kulichenko, Maksim; Barros, Kipton; Lubbers, Nicholas; Li, Ying Wai; Messerly, Richard; Tretiak, Sergei; Smith, Justin S; Nebgen, Benjamin

Bayesian-Inference-Driven Model Parametrization and Model Selection for 2CLJQ Fluid Models

基于贝叶斯推断的2CLJQ流体模型参数化和模型选择

Madin, Owen C; Boothroyd, Simon; Messerly, Richard A; Fass, Josh; Chodera, John D; Shirts, Michael R

Predicting phosphorescence energies and inferring wavefunction localization with machine learning

利用机器学习预测磷光能量并推断波函数局域化

Sifain, Andrew E; Lystrom, Levi; Messerly, Richard A; Smith, Justin S; Nebgen, Benjamin; Barros, Kipton; Tretiak, Sergei; Lubbers, Nicholas; Gifford, Brendan J

Modified Entropy Scaling of the Transport Properties of the Lennard-Jones Fluid

Lennard-Jones流体输运性质的修正熵标度

Bell, Ian H; Messerly, Richard; Thol, Monika; Costigliola, Lorenzo; Dyre, Jeppe C

Uncertainty quantification and propagation of errors of the Lennard-Jones 12-6 parameters for n-alkanes

正构烷烃 Lennard-Jones 12-6 参数的不确定性量化和误差传递

Messerly, Richard A; Knotts, Thomas A 4th; Wilding, W Vincent

Telemedicine Provides Noninferior Research Informed Consent for Remote Study Enrollment: A Randomized Controlled Trial

远程医疗为远程研究招募提供非劣效的研究知情同意:一项随机对照试验

Bobb, Morgan R; Van Heukelom, Paul G; Faine, Brett A; Ahmed, Azeemuddin; Messerly, Jeffrey T; Bell, Gregory; Harland, Karisa K; Simon, Christian; Mohr, Nicholas M