Standout Papers

Less is more: Sampling chemical space with active learning 2018 2026 2020 2023 522
  1. Less is more: Sampling chemical space with active learning (2018)
    Justin S. Smith, Benjamin Nebgen et al. The Journal of Chemical Physics
  2. Approaching coupled cluster accuracy with a general-purpose neural network potential through transfer learning (2019)
    Justin S. Smith, Benjamin Nebgen et al. Nature Communications
  3. Non-adiabatic Excited-State Molecular Dynamics: Theory and Applications for Modeling Photophysics in Extended Molecular Materials (2020)
    Tammie Nelson, Alexander White et al. Chemical Reviews
  4. Exploring the frontiers of condensed-phase chemistry with a general reactive machine learning potential (2024)
    Shuhao Zhang, Ryan B. Jadrich et al. Nature Chemistry

Immediate Impact

3 by Nobel laureates 18 from Science/Nature 69 standout
Sub-graph 1 of 17

Citing Papers

MACE-OFF: Short-Range Transferable Machine Learning Force Fields for Organic Molecules
2025 Standout
Empowering biomedical discovery with AI agents
2024 Standout
1 intermediate paper

Works of Benjamin Nebgen being referenced

Teaching a neural network to attach and detach electrons from molecules
2021
Less is more: Sampling chemical space with active learning
2018 Standout
and 2 more

Author Peers

Author Last Decade Papers Cites
Benjamin Nebgen 1773 792 940 44 2.5k
Raghunathan Ramakrishnan 2398 518 1573 33 2.9k
Kipton Barros 1623 646 864 86 2.8k
Nicholas Lubbers 1763 454 953 59 2.7k
Huziel E. Sauceda 2433 445 1165 24 2.8k
Stefan Chmiela 2330 391 1266 21 2.9k
Fang Liu 1041 585 376 64 2.3k
Pavlo O. Dral 2950 1095 1692 79 4.0k
Michael Gastegger 1604 354 836 24 2.0k
Katja Hansen 1674 400 1175 15 2.2k
David M. Wilkins 1076 672 460 24 1.8k

All Works

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Rankless by CCL
2026