ConspectusConcentration-driven processes
in solution,
i.e., phenomena that
are sustained by persistent concentration gradients, such as crystallization
and surface adsorption, are fundamental chemical processes. Understanding
such phenomena is crucial for countless applications, from pharmaceuticals
to biotechnology. Molecular dynamics (MD), both in- and out-of-equilibrium,
plays an essential role in the current understanding of concentration-driven
processes. Computational costs, however, impose drastic limitations
on the accessible scale of simulated systems, hampering the effective
study of such phenomena. In particular, due to these size limitations,
closed system MD of concentration-driven processes is affected by
solution depletion/enrichment that unavoidably impacts the dynamics
of the chemical phenomena under study. As a notable example, in simulations
of crystallization from solution, the transfer of monomers between
the liquid and crystal phases results in a gradual depletion/enrichment
of solution concentration, altering the driving force for phase transition.
In contrast, this effect is negligible in experiments, given the macroscopic
size of the solution volume. Because of these limitations, accurate
MD characterization of concentration-driven phenomena has proven to
be a long-standing simulation challenge. While disparate equilibrium
and nonequilibrium simulation strategies have been proposed to address
the study of such processes, the methodologies are in continuous development.In this context, a novel simulation technique named constant chemical
potential molecular dynamics (CμMD) was recently proposed. CμMD
employs properly designed, concentration-dependent external forces
that regulate the flux of solute species between selected subregions
of the simulation volume. This enables simulations of systems under
a constant chemical drive in an efficient and straightforward way.
The CμMD scheme was originally applied to the case of crystal
growth from solution and then extended to the simulation of various
physicochemical processes, resulting in new variants of the method.
This Account illustrates the CμMD method and the key advances
enabled by it in the framework ofin silicochemistry.
We review results obtained in crystallization studies, where CμMD
allows growth rate calculations and equilibrium shape predictions,
and in adsorption studies, where adsorption thermodynamics on porous
or solid surfaces was correctly characterized via CμMD. Furthermore,
we will discuss the application of CμMD variants to simulate
permeation through porous materials, solution separation, and nucleation
upon fixed concentration gradients. While presenting the numerous
applications of the method, we provide an original and comprehensive
assessment of concentration-driven simulations using CμMD. To
this end, we also shed light on the theoretical and technical foundations
of CμMD, underlining the novelty and specificity of the method
with respect to existing techniques while stressing its current limitations.
Overall, the application of CμMD to a diverse range of fields
provides new insight into many physicochemical processes, thein silicostudy of which has been hitherto limited by finite-size
effects. In this context, CμMD stands out as a general-purpose
method that promises to be an invaluable simulation tool for studying
molecular-scale concentration-driven phenomena.