ArticleNature communications2021
Dynamical strengthening of covalent and non-covalent molecular interactions by nuclear quantum effects at finite temperature.
Article in Nature communications, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
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Who cites it
23 citing papers in PubMed.
- aims-PAX: Parallel Active Exploration Enables Expedited Construction of Machine Learning Force Fields for Molecules and Materials.Journal of chemical information and modeling · 2026Article
- Computational approaches to enzymatic reaction assignment: a review of methods, validations, and future directions.Briefings in bioinformatics · 2025Review
- Molecular Simulations with a Pretrained Neural Network and Universal Pairwise Force Fields.Journal of the American Chemical Society · 2025Article
- Nuclear quantum effects in molecular liquids across chemical space.Nature communications · 2025Article
- Recent Development in Molecular Dynamics Simulations of Gas Hydrates in Flow Assurance.Energy & fuels : an American Chemical Society journal · 2025Review
- Molecular Interactions Governing the Rat Aryl Hydrocarbon Receptor Activities of Polycyclic Aromatic Compounds and Predictive Model Development.Molecules (Basel, Switzerland) · 2024Article
- Revisiting the Most Stable Structures of the Benzene Dimer.International journal of molecular sciences · 2024Article
- Electronic and Nuclear Quantum Effects on Proton Transfer Reactions of Guanine-Thymine (G-T) Mispairs Using Combined Quantum Mechanical/Molecular Mechanical and Machine Learning Potentials.Molecules (Basel, Switzerland) · 2024Article
- Biomolecular dynamics with machine-learned quantum-mechanical force fields trained on diverse chemical fragments.Science advances · 2024Article
- Neural Network Corrections to Intermolecular Interaction Terms of a Molecular Force Field Capture Nuclear Quantum Effects in Calculations of Liquid Thermodynamic Properties.Journal of chemical theory and computation · 2024Article
- Challenges in modelling dynamic processes in realistic nanostructured materials at operating conditions.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2023Review
- Efficient interatomic descriptors for accurate machine learning force fields of extended molecules.Nature communications · 2023Article
- A molecular descriptor of intramolecular noncovalent interaction for regulating optoelectronic properties of organic semiconductors.Nature communications · 2023Article
- Nuclear quantum effects on zeolite proton hopping kinetics explored with machine learning potentials and path integral molecular dynamics.Nature communications · 2023Article
- How Robust Is the Reversible Steric Shielding Strategy for Photoswitchable Organocatalysts?The Journal of organic chemistry · 2022Article
- BIGDML-Towards accurate quantum machine learning force fields for materials.Nature communications · 2022Article
- Article
- Learning neural network potentials from experimental data via Differentiable Trajectory Reweighting.Nature communications · 2021Article
- Machine learning of solvent effects on molecular spectra and reactions.Chemical science · 2021Article
- Combining Machine Learning and Computational Chemistry for Predictive Insights Into Chemical Systems.Chemical reviews · 2021Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Nuclear quantum effects (NQE) tend to generate delocalized molecular dynamics due to the inclusion of the zero point energy and its coupling with the anharmonicities in interatomic interactions. Here, we present evidence that NQE often enhance electronic interactions and, in turn, can result in dynamical molecular stabilization at finite temperature. The underlying physical mechanism promoted by NQE depends on the particular interaction under consideration. First, the effective reduction of interatomic distances between functional groups within a molecule can enhance the n → π
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