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David Beyer

Publications and source records attributed to David Beyer.

6 recordsLinked to original sources

Optimal Intermediate Hamiltonians for Non-Equilibrium Free Energy Calculations: A Numerical Study of Markov Models

The Jarzynski relation enables the estimation of equilibrium free energy differences from non-equilibrium, finite-time switching simulations. These estimates usually converge poorly because rare trajectories dominate the exponential work average. Here, we numerically determined and explored the sequence of intermediate Hamiltonians connecting initial and final states that minimize the mean squared error (MSE) of the Jarzynski estimator and thereby enhance convergence. For discrete-time Markov models, an exact tilted-master-equation representation of the MSE in the large-sample limit, combined with automatic differentiation, enables efficient gradient-based minimization over all intermediate energies. We applied our approach to three model systems of increasing complexity: a two-state model, a double-well potential, and a shifted potential well. In all three systems, the optimal intermediate Hamiltonians jump at the initial and final times. Extensive Monte Carlo simulations show that optimal intermediates can reduce the MSE by more than an order of magnitude compared with linear and logarithmic interpolation, most strongly for large changes in the energy landscape. Remarkably, they need not dissipate less work than intermediates yielding larger errors. Our results suggest heuristics for more efficient non-equilibrium free energy calculations of realistic molecular systems: optimal intermediate Hamiltonians jump at the initial and final times; for barrier-crossing problems, the barrier should be lowered rapidly and raised again later; and minimizing dissipation does not guarantee faster convergence.

cond-mat.stat-mech

How Topology Shapes the Phase Behavior of Polyelectrolytes

We develop a topology-specific theory of polyelectrolyte coacervation using the random phase approximation and apply it to both simple and complex coacervation. Our results for stars and dendrimers show that more compact chain topologies display a greater propensity for liquid-liquid phase separation, as a function of both Bjerrum length and salt concentration. For mixtures of different topologies, we demonstrate that differences in polymer topology alone are sufficient to drive multiphase coacervation of polyelectrolytes, which we rationalize in terms of an effective $\chi$ parameter. Analysis of a simplified global phase diagram reveals that the propensity for such topology-driven phase separation is largest at a finite molecular weight. Overall, our results establish polymer topology as a powerful design lever for tuning the phase diagram of charged macromolecules independently of molecular weight, net charge, and monomer chemistry, since changes in topology enable fine-tuning of the effective charge density without altering these molecular characteristics.

cond-mat.soft

CO2-induced Drastic Decharging of Dielectric Surfaces in Aqueous Suspensions

We study the influence of airborne CO2 on the charge state of carboxylate stabilized polymer latex particles suspended in aqueous electrolytes. We combine conductometric experiments interpreted in terms of Hessinger's conductivity model with Poisson-Boltzmann cell (PBC) model calculations with charge regulation boundary conditions. Without CO2, a minority of the weakly acidic surface groups are dissociated and only a fraction of the total number of counter-ions actually contribute to conductivity. The remaining counter-ions exchange freely with added other ions like Na+, K+ or Cs+. From the PBC-calculations we infer a corresponding pKa of 4.26 as well as a renormalized charge in reasonably good agreement with the number of freely mobile counter-ions. Equilibration of salt- and CO2-free suspensions against ambient air leads to a drastic de-charging, which exceeds by far the expected effects of to dissolved CO2 and its dissociation products. Further, no counter-ion-exchange is observed. To reproduce the experimental findings, we have to assume an effective pKa of 6.48. This direct influence of CO2 on the state of surface group dissociation explains our recent finding of a CO2-induced decrease of the {\zeta}-potential and supports the suggestion of an additional charge regulation caused by molecular CO2. Given the importance of charged surfaces in contact with aqueous electrolytes, we anticipate that our observations bear substantial theoretical challenges and important implications for applications ranging from desalination to bio-membranes.

cond-mat.soft

pyMBE: the Python-based Molecule Builder for ESPResSo

We present the Python-based Molecule Builder for ESPResSo (pyMBE), an open source software to design custom Coarse-Grained (CG) models, as well as pre-defined models of polyelectrolytes, peptides and globular proteins in the Extensible Simulation Package for Research on Soft Matter (ESPResSo). The Python interface of \espresso offers a flexible framework, capable of building custom CG models from scratch. As a downside, building CG models from scratch is error-prone, especially for newcomers in the field of CG modeling, or for molecules with complex architectures. The pyMBE module builds CG models in \espresso using a hierarchical bottom-up approach, providing a robust tool to automate the setup of CG models and helping new users prevent common mistakes. ESPResSo features the constant pH (cpH) and grand-reaction (G-RxMC) methods, which have been designed to study chemical reaction equilibria in macromolecular systems with many reactive species. However, setting up these methods for systems which contain several types of reactive groups is an error-prone task, especially for beginners. The pyMBE module enables the automatic setup of cpH and G-RxMC simulations in \espresso, lowering the barrier for newcomers and opening the door to investigate complex systems not studied with these methods yet. To demonstrate some of the applications of pyMBE, we showcase several case studies where we successfully reproduce previously published simulations of charge-regulating peptides and globular proteins in bulk solution and weak polyelectrolytes in dialysis. The pyMBE module is publicly available as a GitHub repository (https://github.com/pyMBE-dev/pyMBE) which includes its source code and various sample and test scripts, including the ones that we used to generate the data presented in this article.

cond-mat.soft

A Generalized Grand-Reaction Method for Modelling the Exchange of Weak (Polyprotic) Acids between a Solution and a Weak Polyelectrolyte Phase

We introduce a Monte-Carlo method that allows for the simulation of a polymeric phase containing a weak polyelectrolyte, which is coupled to a reservoir at a fixed pH, salt concentration and total concentration of a weak polyprotic acid. The method generalizes the established Grand-Reaction Method by Landsgesell et al. [Macromolecules 53, 3007-3020 (2020)] and thus allows for the simulation of polyelectrolyte systems coupled to reservoirs with a more complex chemical composition. In order to set the required input parameters that correspond to a desired reservoir composition, we propose a generalization of the recently published chemical potential tuning algorithm of Miles et al. [Phys. Rev. E 105, 045311 (2022)]. To test the proposed tuning procedure, we perform extensive numerical tests for both ideal and interacting systems. Finally, as a showcase, we apply the method to a simple test system which consists of a weak polybase solution that is coupled to a reservoir containing a small diprotic acid. The complex interplay of the ionization various species, the electrostatic interactions and the partitioning of small ions leads to a non-monotonous, stepwise swelling behaviour of the weak polybase chains.

cond-mat.soft

Explaining Giant Apparent $\mathrm{p}K_\mathrm{A}$ Shifts in Weak Polyelectrolyte Brushes

Recent experiments on weak polyelectrolyte brushes found marked shifts in the effective p$K_\mathrm{A}$ that are linear in the logarithm of the salt concentration. Comparing explicit-particle simulations with mean-field calculations we show that for high grafting densities the salt concentration effect can be explained using the ideal Donnan theory, but for low grafting densities the full shift is due to a combination of the Donnan effect and the polyelectrolyte effect. The latter originates from electrostatic correlations which are neglected in the Donnan picture and which are only approximately included in the mean-field theory. Moreover, we demonstrate that the magnitude of the polyelectrolyte effect is almost invariant with respect to salt concentration but depends on the grafting density of the brush. This invariance is due to a complex cancellation of multiple effects. Based on our results, we show how the experimentally determined p$K_\mathrm{A}$ shifts may be used to infer the grafting density of brushes, a parameter that is difficult to measure directly.

cond-mat.soft