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Richard A. Messerly

los alamos national laboratory, theoretical division, los alamos, new mexico, usa

16H指数
71论文数
1.4K被引数
收录论文 21
发表时间
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Multi-fidelity learning for interatomic potentials: low-level forces and high-level energies are all you need*多 fidelity 学习用于原子间势能：低级力和高级能量就是你所需要的*
errMachine Learning: Science and Technology
IF0
err2025-09-29
err0
errOAAI
errMitchell Messerly; Sakib Matin; Alice E A Allen; Benjamin Nebgen; Kipton Barros; Justin S Smith; Nicholas Lubbers; Richard Messerly
err分享
err收藏
Toward machine learning interatomic potentials for modeling uranium mononitride面向机器学习型原子间势能用于模拟一氮化铀
errMachine Learning: Science and Technology
IF0
err2025-09-24
err0
errOAAI
errLorena Alzate-Vargas; Kashi N Subedi; Nicholas Lubbers; Michael W D Cooper; Roxanne M Tutchton; Tammie Gibson; Richard A Messerly
err分享
err收藏
Teacher-student training improves the accuracy and efficiency of machine learning interatomic potentials师生训练提高了机器学习原子间势能的准确性和效率。
errDigital Discovery
IF5.6
err2025-08-07
err0
errOAAI
errSakib Matin; Alice E. A. Allen; Emily Shinkle; Aleksandra Pachalieva; Galen T. Craven; Benjamin Nebgen; Justin S. Smith; Richard Messerly; Ying Wai Li; Sergei Tretiak; Kipton Barros; Nicholas Lubbers
err分享
err收藏
Improving Bond Dissociations of Reactive Machine Learning Potentials through Physics-Constrained Data Augmentation
errJOURNAL OF CHEMICAL INFORMATION AND MODELING
IF5.3
err2025-01-28
err0
PREAI
errdos Santos, Luan G. F.; Nebgen, Benjamin T.; Allen, Alice E. A.; Hamilton, Brenden W.; Matin, Sakib; Smith, Justin S.; Messerly, Richard A.
err分享
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Learning together: Towards foundation models for machine learning interatomic potentials with meta-learning共同学习: 通过元学习建立机器学习的原子间势的基础模型
errNPJ COMPUTATIONAL MATERIALS
IF11.9
err2024-07-17
err3
errOAAI
errAllen, Alice E. A.; Lubbers, Nicholas; Matin, Sakib; Smith, Justin; Messerly, Richard; Tretiak, Sergei; Barros, Kipton
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err收藏
Exploring the frontiers of condensed-phase chemistry with a general reactive machine learning potential探索具有一般反应性机器学习潜力的凝聚相化学的前沿
errNATURE CHEMISTRY
IF20.2
err2024-03-07
err22
errOAAI
errZhang, Shuhao; Makos, Malgorzata Z.; Jadrich, Ryan B.; Kraka, Elfi; Barros, Kipton; Nebgen, Benjamin T.; Tretiak, Sergei; Isayev, Olexandr; Lubbers, Nicholas; Messerly, Richard A.; Smith, Justin S.
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Machine Learning Potentials with the Iterative Boltzmann Inversion: Training to Experiment
errJOURNAL OF CHEMICAL THEORY AND COMPUTATION
IF5.5
err2024-02-02
err10
errOAAI
errMatin, Sakib; Allen, Alice E. A.; Smith, Justin; Lubbers, Nicholas; Jadrich, Ryan B.; Messerly, Richard; Nebgen, Benjamin; Li, Ying Wai; Tretiak, Sergei; Barros, Kipton
err分享
err收藏
Synergy of semiempirical models and machine learning in computational chemistry计算化学中半经验模型和机器学习的协同作用
errJOURNAL OF CHEMICAL PHYSICS
IF3.1
err2023-09-15
err8
errOAAI
errFedik, Nikita; Nebgen, Benjamin; Lubbers, Nicholas; Barros, Kipton; Kulichenko, Maksim; Li, Ying Wai; Zubatyuk, Roman; Messerly, Richard; Isayev, Olexandr; Tretiak, Sergei
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err收藏
NEXMD v2.0 Software Package for Nonadiabatic Excited State Molecular Dynamics Simulations
errJOURNAL OF CHEMICAL THEORY AND COMPUTATION
IF5.5
err2023-07-28
err13
PREAI
errFreixas, Victor M.; Malone, Walter; Li, Xinyang; Song, Huajing; Negrin-Yuvero, Hassiel; Perez-Castillo, Royle; White, Alexander; Gibson, Tammie R.; Makhov, Dmitry V.; Shalashilin, Dmitrii V.; Zhang, Yu; Fedik, Nikita; Kulichenko, Maksim; Messerly, Richard; Mohanam, Luke Nambi; Sharifzadeh, Sahar; Bastida, Adolfo; Mukamel, Shaul; Fernandez-Alberti, Sebastian; Tretiak, Sergei
err分享
err收藏
Uncertainty-driven dynamics for active learning of interatomic potentials用于主动学习原子间势的不确定性驱动动力学
errNATURE COMPUTATIONAL SCIENCE
IF18.3
err2023-03-06
err39
errOAAI
errKulichenko, Maksim; Barros, Kipton; Lubbers, Nicholas; Li, Ying Wai; Messerly, Richard; Tretiak, Sergei; Smith, Justin S.; Nebgen, Benjamin
err分享
err收藏
Extending machine learning beyond interatomic potentials for predicting molecular properties (vol 6, pg 653, 2022)
errNATURE REVIEWS CHEMISTRY
IF51.7
err2022-11-16
err0
errOAAI
errFedik, Nikita; Zubatyuk, Roman; Kulichenko, Maksim; Lubbers, Nicholas; Smith, Justin S.; Nebgen, Benjamin; Messerly, Richard; Li, Ying Wai; Boldyrev, Alexander I.; Barros, Kipton; Isayev, Olexandr; Tretiak, Sergei
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err收藏
Extending machine learning beyond interatomic potentials for predicting molecular properties将机器学习扩展到原子间势之外，以预测分子特性
errNATURE REVIEWS CHEMISTRY
IF51.7
err2022-08-25
err65
PREAI
errFedik, Nikita; Zubatyuk, Roman; Kulichenko, Maksim; Lubbers, Nicholas; Smith, Justin S.; Nebgen, Benjamin; Messerly, Richard; Li, Ying Wai; Boldyrev, Alexander, I; Barros, Kipton; Isayev, Olexandr; Tretiak, Sergei
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err收藏
Elucidating the temperature and density dependence of silver chloride hydration numbers in high-temperature water vapor: A first-principles molecular simulation study
errCHEMICAL GEOLOGY
IF3.6
err2022-04-01
err2
errOAAI
errMesserly, Richard A.; Yoon, Tae Jun; Jadrich, Ryan B.; Currier, Robert P.; Maerzke, Katie A.
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Bayesian-Inference-Driven Model Parametrization and Model Selection for 2CLJQ Fluid Models
errJOURNAL OF CHEMICAL INFORMATION AND MODELING
IF5.3
err2022-02-07
err10
errOAAI
errMadin, Owen C.; Boothroyd, Simon; Messerly, Richard A.; Fass, Josh; Chodera, John D.; Shirts, Michael R.
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Understanding how chemical structure affects ignition-delay-time φ-sensitivity
errCOMBUSTION AND FLAME
IF6.2
err2021-03-01
err6
errOAAI
errMesserly, Richard A.; Luecke, Jon H.; St John, Peter C.; Etz, Brian D.; Kim, Yeonjoon; Zigler, Bradley T.; McCormick, Robert L.; Kim, Seonah
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Predicting phosphorescence energies and inferring wavefunction localization with machine learning
errCHEMICAL SCIENCE
IF7.4
err2021-01-01
err17
errOAAI
errSifain, Andrew E.; Lystrom, Levi; Messerly, Richard A.; Smith, Justin S.; Nebgen, Benjamin; Barros, Kipton; Tretiak, Sergei; Lubbers, Nicholas; Gifford, Brendan J.
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Towards quantitative prediction of ignition-delay-time sensitivity on fuel-to-air equivalence ratio
errCOMBUSTION AND FLAME
IF6.2
err2020-04-01
err17
errOAAI
errMesserly, Richard A.; Rahimi, Mohammad J.; St John, Peter C.; Luecke, Jon H.; Park, Ji-Woong; Huq, Nabila A.; Foust, Thomas D.; Lu, Tianfeng; Zigler, Bradley T.; McCormick, Robert L.; Kim, Seonah
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Uncertainty quantification confirms unreliable extrapolation toward high pressures for united-atom Mie λ-6 force field不确定性量化证实了联合原子Mie λ-6力场对高压的不可靠外推
errJOURNAL OF CHEMICAL PHYSICS
IF3.1
err2018-09-21
err10
PREAI
errMesserly, Richard A.; Shirts, Michael R.; Kazakov, Andrei F.
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Configuration-Sampling-Based Surrogate Models for Rapid Parameterization of Non-Bonded Interactions基于配置采样的代理模型，用于非结合相互作用的快速参数化
errJOURNAL OF CHEMICAL THEORY AND COMPUTATION
IF5.5
err2018-05-04
err32
PREAI
errMesserly, Richard A.; Razavi, S. Mostafa; Shirts, Michael R.
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err收藏
Uncertainty quantification and propagation of errors of the Lennard-Jones 12-6 parameters for n-alkanes
errJOURNAL OF CHEMICAL PHYSICS
IF3.1
err2017-05-19
err29
errOAAI
errMesserly, Richard A.; Knotts, Thomas A.; Wilding, W. Vincent
err分享
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研究方向

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