ArticleScientific data2024
Beyond MD17: the reactive xxMD dataset.
Article in Scientific data, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Hierarchical geometric deep learning enables scalable analysis of molecular dynamics.The Journal of chemical physics · 2026Article
- Li-P-S Electrolyte Materials as a Benchmark for Machine-Learned Interatomic Potentials.Journal of chemical theory and computation · 2026Article
- Unprecedented robustness of physics-informed atomic energy models at and beyond room temperature.Communications chemistry · 2026Article
- Introducing Virtual Points in Equivariant Networks by Extending Atom Representation for Effective Prediction.Journal of chemical theory and computation · 2025Article
- DFT-Based Permutationally Invariant Polynomial Potentials Capture the Twists and Turns of CJournal of chemical theory and computation · 2024Article
- Quantum Chemistry Dataset with Ground- and Excited-state Properties of 450 Kilo Molecules.Scientific data · 2024Article
- Beyond MD17: the reactive xxMD dataset.Scientific data · 2024Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
System specific neural force fields (NFFs) have gained popularity in computational chemistry. One of the most popular datasets as a bencharmk to develop NFF models is the MD17 dataset and its subsequent extension. These datasets comprise geometries from the equilibrium region of the ground electronic state potential energy surface, sampled from direct adiabatic dynamics. However, many chemical reactions involve significant molecular geometrical deformations, for example, bond breaking. Therefore, MD17 is inadequate to represent a chemical reaction. To address this limitation in MD17, we introduce a new dataset, called Extended Excited-state Molecular Dynamics (xxMD) dataset. The xxMD dataset involves geometries sampled from direct nonadiabatic dynamics, and the energies are computed at both multireference wavefunction theory and density functional theory. We show that the xxMD dataset involves diverse geometries which represent chemical reactions. Assessment of NFF models on xxMD dataset reveals significantly higher predictive errors than those reported for MD17 and its variants. This work underscores the challenges faced in crafting a generalizable NFF model with extrapolation capability.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.