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Benjamin Nebgen

united states department of energy (doe)

24H指数
132论文数
4.2K被引数
收录论文 36
发表时间
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Mott vs Kondo: Influence of various density functional based methods on the Ce isostructural phase transition mechanism莫特与库柏：基于不同密度泛函方法的铈同构相变机制的影响
errJournal of Applied Physics
IF2.5
err2026-02-07
err0
PREAI
errHamilton, Brenden W.; Munoz, Alexander R.; Jones, Travis E.; Nebgen, Benjamin T.
err分享
err收藏
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
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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
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Shadow Molecular Dynamics with a Machine Learned Flexible Charge Potential
errJOURNAL OF CHEMICAL THEORY AND COMPUTATION
IF5.5
err2025-03-01
err0
PREAI
errLi, Cheng-Han; Kaymak, Mehmet Cagri; Kulichenko, Maksim; Lubbers, Nicholas; Nebgen, Benjamin T.; Tretiak, Sergei; Finkelstein, Joshua; Tabor, Daniel P.; Niklasson, Anders M. N.
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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.
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Challenges and opportunities for machine learning potentials in transition path sampling: alanine dipeptide and azobenzene studies机器学习势在过渡路径采样中的挑战与机遇：丙氨酸二肽和偶氮苯研究
errDIGITAL DISCOVERY
IF5.6
err2025-01-01
err0
errOAAI
errFedik, Nikita; Li, Wei; Lubbers, Nicholas; Nebgen, Benjamin; Tretiak, Sergei; Li, Ying Wai
err分享
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
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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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Distributed non-negative RESCAL with automatic model selection for exascale data
errJOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING
IF4
err2023-09-01
err4
errOAAI
errBhattarai, Manish; Kharat, Namita; Boureima, Ismael; Skau, Erik; Nebgen, Benjamin; Djidjev, Hristo; Rajopadhye, Sanjay; Smith, James P.; Alexandrov, Boian
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Semi-Empirical Shadow Molecular Dynamics: A PyTorch Implementation
errJOURNAL OF CHEMICAL THEORY AND COMPUTATION
IF5.5
err2023-05-10
err1
errOAAI
errKulichenko, Maksim; Barros, Kipton; Lubbers, Nicholas; Fedik, Nikita; Zhou, Guoqing; Tretiak, Sergei; Nebgen, Benjamin; Niklasson, Anders M. N.
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Lightweight and effective tensor sensitivity for atomistic neural networks
errJOURNAL OF CHEMICAL PHYSICS
IF3.1
err2023-05-09
err9
errOAAI
errChigaev, Michael; Smith, Justin S. S.; Anaya, Steven; Nebgen, Benjamin; Bettencourt, Matthew; Barros, Kipton; Lubbers, Nicholas
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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
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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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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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Deep learning of dynamically responsive chemical Hamiltonians with semiempirical quantum mechanics具有半经验量子力学的动态响应化学哈密顿量的深度学习
errPROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
IF9.1
err2022-07-01
err29
errOAAI
errZhou, Guoqing; Lubbers, Nicholas; Barros, Kipton; Tretiak, Sergei; Nebgen, Benjamin
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Teaching a neural network to attach and detach electrons from molecules教导神经网络将电子与分子连接和分离
errNATURE COMMUNICATIONS
IF15.7
err2021-08-11
err55
errOAAI
errZubatyuk, Roman; Smith, Justin S.; Nebgen, Benjamin T.; Tretiak, Sergei; Isayev, Olexandr
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Machine learned Huckel theory: Interfacing physics and deep neural networks
errJOURNAL OF CHEMICAL PHYSICS
IF3.1
err2021-06-25
err30
errOAAI
errZubatiuk, Tetiana; Nebgen, Benjamin; Lubbers, Nicholas; Smith, Justin S.; Zubatyuk, Roman; Zhou, Guoqing; Koh, Christopher; Barros, Kipton; Isayev, Olexandr; Tretiak, Sergei
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Automated discovery of a robust interatomic potential for aluminum自动发现铝的强大原子间潜力
errNATURE COMMUNICATIONS
IF15.7
err2021-02-23
err62
errOAAI
errSmith, Justin S.; Nebgen, Benjamin; Mathew, Nithin; Chen, Jie; Lubbers, Nicholas; Burakovsky, Leonid; Tretiak, Sergei; Nam, Hai Ah; Germann, Timothy; Fensin, Saryu; Barros, Kipton
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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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研究方向

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合作学者
合作期刊
T
Thomas Frauenheim
H 指数: 100 · 论文数: 939
O
Oleg V. Prezhdo
H 指数: 98 · 论文数: 805
M
M. D. Fayer
H 指数: 92 · 论文数: 654
S
Sergei Tretiak
H 指数: 88 · 论文数: 738
A
Alexander I. Boldyrev
H 指数: 87 · 论文数: 558
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