ArticleJournal of chemical theory and computation2020
Temperature and Phase Transferable Bottom-up Coarse-Grained Models.
Article in Journal of chemical theory and computation, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed.
- Enhanced Sampling for Efficient Learning of Coarse-Grained Machine Learning Potentials.Journal of chemical theory and computation · 2026Article
- The Martini 3 Lipidome: Expanded and Refined Parameters Improve Lipid Phase Behavior.ACS central science · 2025Article
- Microtubules in Martini: Parameterizing a heterogeneous elastic-network towards a mechanically accurate microtubule.PNAS nexus · 2025Article
- Thermodynamic Transferability in Coarse-Grained Force Fields Using Graph Neural Networks.Journal of chemical theory and computation · 2024Article
- Fusion Dynamics and Size-Dependence of Droplet Microstructure in ssDNA-Mediated Protein Phase Separation.JACS Au · 2024Article
- Accessing the electronic structure of liquid crystalline semiconductors with bottom-up electronic coarse-graining.Chemical science · 2024Article
- Transferable Implicit Solvation via Contrastive Learning of Graph Neural Networks.ACS central science · 2023Article
- OpenMSCG: A Software Tool for Bottom-Up Coarse-Graining.The journal of physical chemistry. B · 2023Article
- Transferable Coarse Graining via Contrastive Learning of Graph Neural Networks.bioRxiv : the preprint server for biology · 2023Article
- Utilizing Machine Learning to Greatly Expand the Range and Accuracy of Bottom-Up Coarse-Grained Models through Virtual Particles.Journal of chemical theory and computation · 2023Article
- Statistical Mechanical Design Principles for Coarse-Grained Interactions across Different Conformational Free Energy Surfaces.The journal of physical chemistry letters · 2023Article
- A Core-Shell Approach for Systematically Coarsening Nanoparticle-Membrane Interactions: Application to Silver Nanoparticles.Nanomaterials (Basel, Switzerland) · 2022Article
- Bottom-up Coarse-Graining: Principles and Perspectives.Journal of chemical theory and computation · 2022Review
- Coarse-Grained Water Model Development for Accurate Dynamics and Structure Prediction.ACS omega · 2022Article
- Physical Characterization of Triolein and Implications for Its Role in Lipid Droplet Biogenesis.The journal of physical chemistry. B · 2021Article
- "Dividing and Conquering" and "Caching" in Molecular Modeling.International journal of molecular sciences · 2021Review
- Martini 3: a general purpose force field for coarse-grained molecular dynamics.Nature methods · 2021Article
- A new one-site coarse-grained model for water: Bottom-up many-body projected water (BUMPer). II. Temperature transferability and structural properties at low temperature.The Journal of chemical physics · 2021Article
- Review
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Authors and funding
3 authors.
Funding
Abstract
Despite the high fidelity of bottom-up coarse-grained (CG) approaches to recapitulate the structural correlations in atomistic simulations, the general use of bottom-up CG methods is limited because of the nontransferable nature of these CG models under different thermodynamic conditions. Because bottom-up CG potentials usually correspond to configuration-dependent free energies of the system, recent studies have focused on adjusting enthalpic or entropic contributions to account for issues with transferability. However, these approaches can require a manual adjustment of the CG interaction a priori and are usually limited to constant volume ensembles. To overcome these limitations, we construct temperature and phase transferable CG models under constant pressure by developing the ultra-coarse-graining (UCG) methodology in the mean-field limit. In the mean-field ansatz, an embedded semi-global order parameter recapitulates global changes to the system by automatically adjusting the effective CG interactions, thus bridging free energy decompositions with UCG theory. The method presented is designed to faithfully capture structural correlations under different thermodynamic conditions, using a single UCG model. Specifically, we test the applicability of the developed theory in three distinct cases: (1) different temperatures at constant pressure in liquids, (2) different temperatures across thermodynamic phases, and (3) liquid/vapor interfaces. We demonstrate that the systematic construction of both temperature and phase transferable bottom-up CG models is possible using this generalized UCG theory. Based on our findings, this approach significantly extends the transferability and applicability of the bottom-up CG theory and method.
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Registered trials
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