arXiv subjects

Daniel W. Siderius

Publications and source records attributed to Daniel W. Siderius.

5 recordsLinked to original sources

arXiv2026

A reaction volume bias Monte Carlo trial for sampling chemisorption in confinement

Molecular modeling of chemisorption with Monte Carlo requires the development of new trial moves to efficiently sample complex fluids such as water in Bronsted acid zeolites. Here, we develop a reaction volume bias (RxVB) Monte Carlo trial for modeling chemisorption by combining identity-switch and aggregation-volume-bias (AVB) moves. This method aims to promote the sampling of reactions by choosing reactive pairs that are within an arbitrarily specified reaction volume. The RxVB move achieves up to a 90-fold increase in accepted reaction events over unbiased moves in a single-site slit-pore model, corresponding to a 70-fold gain in statistical efficiency after accounting for computational overhead. But when the same move is applied to water in a Bronsted acid zeolite without orientational bias, there is no measurable speedup for a single MFI unit cell. We demonstrate a simple expression that predicts the maximum efficiency increase in the simplest case where selecting reactants that are near each other is the major sampling bottleneck. Dense water systems may require additional configuration-bias or orientational bias to improve sampling of the hydrogen bond network in order to increase acceptance. This new RxVB trial was made available with examples in the open-source Free Energy and Advanced Sampling Simulation Toolkit (FEASST) simulation package.

physics.chem-ph↗

arXiv2025

Intrinsic Direct Air Capture

We present new metrics to evaluate solid sorbent materials for Direct Air Capture (DAC). These new metrics provide a theoretical upper bound on CO2 captured per energy as well as a theoretical upper limit on the purity of the captured CO2. These new metrics are based entirely on intrinsic material properties and are therefore agnostic to the design of the DAC system. These metrics apply to any adsorption-refresh cycle design. In this work we demonstrate the use of these metrics with the example of temperature-pressure swing refresh cycles. The main requirement for applying these metrics is to describe the equilibrium uptake (along with a few other materials properties) of each species in terms of the thermodynamic variables (e.g. temperature, pressure). We derive these metrics from thermodynamic energy balances. To apply these metrics on a set of examples, we first generated approximations of the necessary materials properties for 11 660 metal-organic framework materials (MOFs). We find that the performance of the sorbents is highly dependent on the path through thermodynamic parameter space. These metrics allow for: 1) finding the optimum materials given a particular refresh cycle, and 2) finding the optimum refresh cycles given a particular sorbent. Applying these metrics to the database of MOFs lead to the following insights: 1) start cold - the equilibrium uptake of CO2 diverges from that of N2 at lower temperatures, and 2) selectivity of CO2 vs other gases at any one point in the cycle does not matter - what matters is the relative change in uptake along the cycle.

cond-mat.mtrl-sci↗

arXiv2022

Reproducible Sorbent Materials Foundry for Carbon Capture at Scale

We envision an autonomous sorbent materials foundry (SMF) for rapidly evaluating materials for direct air capture of carbon dioxide (CO2), specifically targeting novel metal organic framework materials. Our proposed SMF is hierarchical, simultaneously addressing the most critical gaps in the inter-related space of sorbent material synthesis, processing, properties, and performance. The ability to collect these critical data streams in an agile, coordinated, and automated fashion will enable efficient end-to-end sorbent materials design through machine learning driven research framework.

cond-mat.mtrl-sci↗

arXiv2016

Modulus-Pressure Equation for Confined Fluids

Ultrasonic experiments allow one to measure the elastic modulus of bulk solid or fluid samples. Recently such experiments have been carried out on fluid-saturated nanoporous glass to probe the modulus of a confined fluid. In our previous work [J. Chem. Phys., (2015) 143, 194506], using Monte Carlo simulations we showed that the elastic modulus $K$ of a fluid confined in a mesopore is a function of the pore size. Here we focus on modulus-pressure dependence $K(P)$, which is linear for bulk materials, a relation known as the Tait-Murnaghan equation. Using transition-matrix Monte Carlo simulations we calculated the elastic modulus of bulk argon as a function of pressure and argon confined in silica mesopores as a function of Laplace pressure. Our calculations show that while the elastic modulus is strongly affected by confinement and temperature, the slope of the modulus versus pressure is not. Moreover, the calculated slope is in a good agreement with the reference data for bulk argon and experimental data for confined argon derived from ultrasonic experiments. We propose to use the value of the slope of $K(P)$ to estimate the elastic moduli of an unknown porous medium.

physics.chem-ph↗

arXiv2015

Relation Between Pore Size and the Compressibility of a Confined Fluid

When a fluid is confined to a nanopore, its thermodynamic properties differ from the properties of a bulk fluid, so measuring such properties of the confined fluid can provide information about the pore sizes. Here we report a simple relation between the pore size and isothermal compressibility of argon confined in these pores. Compressibility is calculated from the fluctuations of the number of particles in the grand canonical ensemble using two different simulation techniques: conventional grand-canonical Monte Carlo and grand-canonical ensemble transition-matrix Monte Carlo. Our results provide a theoretical framework for extracting the information on the pore sizes of fluid-saturated samples by measuring the compressibility from ultrasonic experiments.

physics.chem-ph↗