Flat-Histogram Monte Carlo as an Efficient Tool To Evaluate Adsorption Processes Involving Rigid and Deformable Molecules

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.