Comments on “Monte Carlo simulations for water adsorption in porous materials: Best practices and new insights”

Siderius, Daniel W.; Hatch, Harold W.; Errington, Jeffrey R.; Shen, Vincent K.

doi:10.1002/aic.17686

Cited by 5 publications

(10 citation statements)

References 17 publications

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“…The entire isotherm for TIP4P in ZIF-8 is, however, at lower relative pressure compared to the isotherm for SPC/E water; the LOS are at p / p 0 ≈ 35 and p / p 0 ≈ 5600. This important difference is due primarily to the longer-range pair interaction between TIP4P molecules and the MOF and secondarily due to differences in phase behavior of the two water models (i.e., TIP4P water has a higher saturation pressure than SPC/E water). The longer-range potential (both LJ and electrostatic terms) strengthens the interaction with the MOF and consequently shifts the hysteresis loop to lower pressure.…”

Section: Resultsmentioning

confidence: 99%

“…We also ran FHMC simulations of bulk SPC/E water at 300 K, using the same cutoff and Ewald strategies as for the adsorption simulations, and the resultant ln Π( N ;μ) is used to convert μ to bulk-fluid pressure and identify the bulk-fluid saturation pressure ( p 0 ). For SPC/E water at 300 K as simulated here, p 0 = 1313 ± 6 Pa; we note that this is about 30% larger than the saturation pressure of SPC/E water at 300 K using long-range corrections. , Finally, for reasons that are explained in Section , we will present some simulation results in terms of the fugacity ( f ) of the SPC/E adsorbate. Here, we use the conventional definition of the fugacity: f = k B T exp false( β μ false) Λ 3 where Λ is the thermal de Broglie wavelength.…”

Section: Resultsmentioning

confidence: 99%

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Flat-Histogram Monte Carlo Simulation of Water Adsorption in Metal–Organic Frameworks

Siderius,

Hatch,

Shen

2024

J. Phys. Chem. B

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Molecular simulations of water adsorption in porous materials often converge slowly due to sampling bottlenecks that follow from hydrogen bonding and, in many cases, the formation of water clusters. These effects may be exacerbated in metal–organic framework (MOF) adsorbents, due to the presence of pore spaces (cages) that promote the formation of discrete-size clusters and hydrophobic effects (if present), among other reasons. In Grand Canonical Monte Carlo (MC) simulations, these sampling challenges are typically manifested by low MC acceptance ratios, a tendency for the simulation to become stuck in a particular loading state (i.e., macrostates), and the persistence of specific clusters for long periods of the simulation. We present simulation strategies to address these sampling challenges, by applying flat-histogram MC (FHMC) methods and specialized MC move types to simulations of water adsorption. FHMC, in both Transition-matrix and Wang–Landau forms, drives the simulation to sample relevant macrostates by incorporating weights that are self-consistently adjusted throughout the simulation and generate the macrostate probability distribution (MPD). Specialized MC moves, based on aggregation-volume bias and configurational bias methods, separately address low acceptance ratios for basic MC trial moves and specifically target water molecules in clusters; in turn, the specialized MC moves improve the efficiency of generating new configurations which is ultimately reflected in improved statistics collected by FHMC. The combined strategies are applied to study the adsorption of water in CuBTC and ZIF-8 at 300 K, through examination of the MPD and the adsorption isotherm generated by histogram reweighting. A key result is the appearance of nontrivial oscillations in the MPD, which we show to be associated with water clusters in the adsorption system. Additionally, we show that the probabilities of certain clusters become similar in value near the boundaries of the isotherm hysteresis loop, indicating a strong connection between cluster formation/destruction and the thermodynamic limits of stability. For a hydrophobic MOF, the FHMC results show that the phase transition from low density to high density is suppressed to water pressure far above the bulk-fluid saturation pressure; this is consistent with results presented elsewhere. We also compare our FHMC simulation isotherm to one measured by a different technique but with ostensibly the same molecular interactions and comment on observed differences and the need for follow-up work. The simulation strategies presented here can be applied to the simulation of water in other MOFs using heuristic guidelines laid out in our text, which should facilitate the more consistent and efficient simulation of water adsorption in porous materials in future applications.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Flat-Histogram Monte Carlo Simulation of Water Adsorption in Metal–Organic Frameworks

Siderius,

Hatch,

Shen

2024

J. Phys. Chem. B

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“…For example, in the study of liquid–vapor phase equilibrium, the pressure, density and free energy of the vapor and liquid phases may be calculated directly . In addition to equilibrium states, metastable states and the critical point as well as other thermodynamic or structural properties of interest at a given temperature can also be obtained with these approaches. TMMC has also been successfully applied toward the study of adsorption on surfaces − and inside porous materials. − TMMC may also be used in studies of self-assembly to calculate critical micelle concentrations, critical micelle temperatures and other structural transitions. , Temperature extrapolation methods further improve the efficiency of TMMC by reducing the number of required simulations, − and initialization with Wang–Landau can reduce convergence times. , …”

Section: Introductionmentioning

confidence: 99%

“…A recent study of water adsorption utilized single-macrostate TMMC simulations and reported large efficiency gains compared to conventional GCE Monte Carlo (MC) simulations. ,, However, no efficiency comparison was made to multiple-macrostate TMMC simulations in the GCE. To our knowledge, such a comparison remains lacking.…”

Section: Introductionmentioning

confidence: 99%

“…For example, in the study of liquid−vapor phase equilibrium, the pressure, density and free energy of the vapor and liquid phases may be calculated directly. 1 In addition to equilibrium states, metastable states 2 and the critical point 3 as well as other thermodynamic or structural properties of interest at a given temperature can also be obtained with these approaches. TMMC has also been successfully applied toward the study of adsorption on surfaces 4−7 and inside porous materials.…”

Section: Introductionmentioning

confidence: 99%

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Efficiency Comparison of Single- and Multiple-Macrostate Grand Canonical Ensemble Transition-Matrix Monte Carlo Simulations

et al. 2023

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Recent interest in parallelizing flat-histogram transition-matrix Monte Carlo simulations in the grand canonical ensemble, due to its demonstrated effectiveness in studying phase behavior, self-assembly and adsorption, has led to the most extreme case of single-macrostate simulations, where each macrostate is simulated independently with ghost particle insertions and deletions. Despite their use in several studies, no efficiency comparisons of these single-macrostate simulations have been made with multiple-macrostate simulations. We show that multiple-macrostate simulations are up to 3 orders of magnitude more efficient than single-macrostate simulations, which demonstrates the remarkable efficiency of flat-histogram biased insertions and deletions, even with low acceptance probabilities. Efficiency comparisons were made for supercritical fluids and vapor–liquid equilibrium of bulk Lennard-Jones and a three-site water model, self-assembling patchy trimer particles and adsorption of a Lennard-Jones fluid confined in a purely repulsive porous network, using the open source simulation toolkit FEASST. By directly comparing with a variety of Monte Carlo trial move sets, this efficiency loss in single-macrostate simulations is attributed to three related reasons. First, ghost particle insertions and deletions in single-macrostate simulations incur the same computational expense as grand canonical ensemble trials in multiple-macrostate simulations, yet ghost trials do not reap the sampling benefit from propagating the Markov chain to a new microstate. Second, single-macrostate simulations lack macrostate change trials that are biased by the self-consistently converging relative macrostate probability, which is a major component of flat histogram simulations. Third, limiting a Markov chain to a single macrostate reduces sampling possibilities. Existing parallelization methods for multiple-macrostate flat-histogram simulations are shown to be more efficient than parallel single-macrostate simulations by approximately an order of magnitude or more in all systems investigated.

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Efficient Modeling of Water Adsorption in MOFs Using Interpolated Transition Matrix Monte Carlo

Mazur,

Firlej,

Kuchta

2024

ACS Appl. Mater. Interfaces

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With the specter of accelerating climate change, securing access to potable water has become a critical global challenge. Atmospheric water harvesting (AWH) through metal−organic frameworks (MOFs) emerges as one of the promising solutions. The standard numerical methods applied for rapid and efficient screening for optimal sorbents face significant limitations in the case of water adsorption (slow convergence and inability to overcome high energy barriers). To address these challenges, we employed grand canonical transition matrix Monte Carlo (GC-TMMC) methodology and proposed an efficient interpolation scheme that significantly reduces the number of required simulations while maintaining accuracy of the results. Through the example of water adsorption in three MOFs: MOF-303, MOF-LA2−1, and NU-1000, we show that the extrapolation of the free energy landscape allows for prediction of the adsorption properties over a continuous range of pressure and temperature. This innovative and versatile method provides rich thermodynamic information, enabling rapid, large-scale computational screening of sorbents for adsorption, applicable for a variety of sorbents and gases. As the presented methodology holds strong applicative potential, we provide alongside this paper a modified version of the RASPA2 code with a ghost swap move implementation and a Python library designed to minimize the user's input for analyzing data derived from the TMMC simulations.

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Comments on “Monte Carlo simulations for water adsorption in porous materials: Best practices and new insights”

Cited by 5 publications

References 17 publications

Flat-Histogram Monte Carlo Simulation of Water Adsorption in Metal–Organic Frameworks

Flat-Histogram Monte Carlo Simulation of Water Adsorption in Metal–Organic Frameworks

Efficiency Comparison of Single- and Multiple-Macrostate Grand Canonical Ensemble Transition-Matrix Monte Carlo Simulations

Efficient Modeling of Water Adsorption in MOFs Using Interpolated Transition Matrix Monte Carlo

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