Amide A band is a fingerprint for water dynamics in reverse osmosis polyamide membranes

Toward Molecular Simulation Guided Design of Next-Generation Membranes: Challenges and Opportunities

Membranes provide energy-efficient solutions for separating ions from water, ion-ion separation, neutral or charged molecules, and mixed gases. Understanding the fundamental mechanisms and design principles for these separation challenges has significant applications in the food and agriculture, energy, pharmaceutical, and electronics industries and environmental remediation. In situ experimental probes to explore Angstrom-nanometer length-scale and pico-nanosecond time-scale phenomena remain limited. Currently, molecular simulations such as density functional theory, ab initio molecular dynamics (MD), all-atom MD, and coarse-grained MD provide physics-based predictive models to study these phenomena. The status of molecular simulations to study transport mechanisms and state-of-the-art membrane separation is discussed. Furthermore, limitations and open challenges in molecular simulations are discussed. Finally, the importance of molecular simulations in generating data sets for machine learning and exploration of membrane design space is addressed.

Molecular Dynamics Insights into Water Transport Mechanisms in Polyamide Membranes: Influence of Cross-Linking Degree

Polyamide (PA) membranes are widely utilized in desalination and water treatment applications, yet the mechanisms underlying water transport within these amorphous polymer materials remain insufficiently understood. To gain more insight into these problems on a microscopic scale, we employ molecular dynamics (MD) simulations to analyze the relationship between the structural properties and the water permeation behavior of PA membranes. Two distinct atomistic models of PA membranes are developed by controlling their degrees of cross-linking (DC). We then conducted a comparative analysis on their microscopic structural properties and configurations of water inside the membranes and investigated how these differences lead to different water diffusion coefficients. Our results reveal that the membrane with a lower DC exhibits higher polymer mobility and a more orderly microscopic structure, allowing the formation of pores that can hold larger water clusters as well as more transient passages between pores, both contributing to an increased water diffusion coefficient. From these observations, we can conclude that water permeability within PA membranes is governed by both the morphology of semirigid pores and the oscillatory movements of the polymer chains. Overall, these findings contribute to a deeper understanding of the intricate mechanisms governing water permeation in PA membranes and may inform the design of more efficient membranes for reverse osmosis and other water treatment technologies.

Momentum removal to obtain the position-dependent diffusion constant in constrained molecular dynamics simulation

The position-dependent diffusion coefficient along with free energy profile are important parameters needed to study mass transport in heterogeneous systems such as biological and polymer membranes, and molecular dynamics (MD) calculation is a popular tool to obtain them. Among many methodologies, the Marrink-Berendsen (MB) method is often employed to calculate the position-dependent diffusion coefficient, in which the autocorrelation function of the force on a fixed molecule is related to the friction on the molecule. However, the diffusion coefficient is shown to be affected by the period of the removal of the center-of-mass velocity, τ v 0 , which is necessary when performing MD calculations using the Ewald method for Coulombic interaction. We have clarified theoretically in this study how this operation affects the diffusion coefficient calculated by the MB method, and the theoretical predictions are proven by MD calculations. Therefore, we succeeded in providing guidance on how to select an appropriate τ v 0 value in estimating the position-dependent diffusion coefficient by the MB method. This guideline is applicable also to the Woolf-Roux method.

Weight average approaches for predicting dynamical properties of biomolecules

Recent advances in atomistic molecular dynamics (MD) simulations of biomolecules allow us to explore their conformational spaces widely, observing large-scale conformational fluctuations or transitions between distinct structures. To reproduce or refine experimental data using MD simulations, structure ensembles, which are characterized by multiple structures and their statistical weights on the rugged free-energy landscapes, are often used. Here, we summarize weight average approaches for various experimental measurements. Weight average approaches are now applied to hybrid quantum mechanics/molecular mechanics MD simulations to predict fast vibrational motions in a protein with a high accuracy for better understanding of molecular functions from atomic structures.