ArticleJournal of chemical theory and computation2018
Flat-Histogram Monte Carlo as an Efficient Tool To Evaluate Adsorption Processes Involving Rigid and Deformable Molecules.
Article in Journal of chemical theory and computation, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- A Review of Ammonia (NH3) Adsorption in Porous Solids.Chemical reviews · 2026Article
- Effects of Pore Connectivity on Water Adsorption in Metal-Organic Frameworks.Langmuir : the ACS journal of surfaces and colloids · 2026Article
- Queryable Gaseous Adsorption Properties of Pure Components and Mixtures in Metal-Organic Frameworks.Langmuir : the ACS journal of surfaces and colloids · 2025Article
- Computational Modeling of Reticular Materials: The Past, the Present, and the Future.Advanced materials (Deerfield Beach, Fla.) · 2025Review
- Water Adsorption in Metal-Organic Frameworks: Characteristics, Mechanisms, and Structure-Property Relationships.Journal of the American Chemical Society · 2025Article
- Small Rotations, Big Effects: Lessons from Water Adsorption in NU-1000.The journal of physical chemistry. C, Nanomaterials and interfaces · 2025Article
- Ab Initio Predictions of Adsorption in Flexible Metal-Organic Frameworks for Water Harvesting Applications.Journal of the American Chemical Society · 2025Article
- Water motifs in zirconium metal-organic frameworks induced by nanoconfinement and hydrophilic adsorption sites.Nature communications · 2024Article
- Flat-Histogram Monte Carlo Simulation of Water Adsorption in Metal-Organic Frameworks.The journal of physical chemistry. B · 2024Article
- Efficient Modeling of Water Adsorption in MOFs Using Interpolated Transition Matrix Monte Carlo.ACS applied materials & interfaces · 2024Article
- Identifying pathways to metal-organic framework collapse during solvent activation with molecular simulations.Journal of materials chemistry. A · 2023Article
- Quasicontinuous Cooperative Adsorption Mechanism in Crystalline Nanoporous Materials.The journal of physical chemistry letters · 2022Article
- Extrapolation and interpolation strategies for efficiently estimating structural observables as a function of temperature and density.The Journal of chemical physics · 2020Article
- Parallel Prefetching for Canonical Ensemble Monte Carlo Simulations.The journal of physical chemistry. A · 2020Article
- Deep neural network learning of complex binary sorption equilibria from molecular simulation data.Chemical science · 2019Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Monte Carlo simulations are the foundational technique for predicting thermodynamic properties of open systems where the process of interest involves the exchange of particles. Thus, they have been used extensively to computationally evaluate the adsorption properties of nanoporous materials and are critical for the in silico identification of promising materials for a variety of gas storage and chemical separation applications. In this work we demonstrate that a well-known biasing technique, known as "flat-histogram" sampling, can be combined with temperature extrapolation of the free energy landscape to efficiently provide significantly more useful thermodynamic information than standard open ensemble MC simulations. Namely, we can accurately compute the isosteric heat of adsorption and number of particles adsorbed for various adsorbates over an extremely wide range of temperatures and pressures from a set of simulations at just one temperature. We extend this derivation of the temperature extrapolation to adsorbates with intramolecular degrees of freedom when Rosenbluth sampling is employed. Consequently, the working capacity and isosteric heat can be computed for any given combined temperature/pressure swing adsorption process for a large range of operating conditions with both rigid and deformable adsorbates. Continuous thermodynamic properties can be computed with this technique at very moderate computational cost, thereby providing a strong case for its application to the in silico identification of promising nanoporous adsorbents.
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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.