New Framework for Computing a General Local Self-Diffusion Coefficient Using Statistical Mechanics

Molecular Dynamics Computational Study of Sustainable Green Surfactant for Application in Chemical Enhanced Oil Recovery

Green surfactant (GS) flooding, an environmentally friendly chemical Enhanced Oil Recovery (cEOR) method, is explored in this molecular dynamics (MD) simulation study. This study evaluates the ability of (S)-2-dodecanamido-aminobutanedioic as a GS for cEOR, assessing its performance with hexane (C6), dodecane (C12), and eicosane (C20) as representative oils. In the case of the bulk system, a comprehensive molecular-level investigation provides structural details such as the radial distribution function, solvent-accessible surface area, GS adsorption dynamics, diffusivity, and emulsion stability of the GS, oil, and water systems. Also the impact of the three distinct oils on interfacial tension was examined in the existence of GS molecules. The findings reveal rapid GS molecule aggregation and adsorption on oil droplets, with various impacts on emulsion stability depending on the oil type. Additionally, GS enhances the aggregation of heavy C20 oil molecules in a water medium. The study demonstrates GS's role as an effective emulsifier, facilitating oil droplet recovery, with electrostatic interactions governing micelle formation and van der Waals interactions influencing oil droplet emulsification. These results align with prior experimental data, affirming GS's promising application potential in cEOR while prioritizing environmental sustainability.

Estimating Position-Dependent and Anisotropic Diffusivity Tensors from Molecular Dynamics Trajectories: Existing Methods and Future Outlook

Confinement can substantially alter the physicochemical properties of materials by breaking translational isotropy and rendering all physical properties position-dependent. Molecular dynamics (MD) simulations have proven instrumental in characterizing such spatial heterogeneities and probing the impact of confinement on materials' properties. For static properties, this is a straightforward task and can be achieved via simple spatial binning. Such an approach, however, cannot be readily applied to transport coefficients due to lack of natural extensions of autocorrelations used for their calculation in the bulk. The prime example of this challenge is diffusivity, which, in the bulk, can be readily estimated from the particles' mobility statistics, which satisfy the Fokker-Planck equation. Under confinement, however, such statistics will follow the Smoluchowski equation, which lacks a closed-form analytical solution. This brief review explores the rich history of estimating profiles of the diffusivity tensor from MD simulations and discusses various approximate methods and algorithms developed for this purpose. Besides discussing heuristic extensions of bulk methods, we overview more rigorous algorithms, including kernel-based methods, Bayesian approaches, and operator discretization techniques. Additionally, we outline methods based on applying biasing potentials or imposing constraints on tracer particles. Finally, we discuss approaches that estimate diffusivity from mean first passage time or committor probability profiles, a conceptual framework originally developed in the context of collective variable spaces describing rare events in computational chemistry and biology. In summary, this paper offers a concise survey of diverse approaches for estimating diffusivity from MD trajectories, highlighting challenges and opportunities in this area.

Surface functionalization of graphene nanosheet with poly (L-histidine) and its application in drug delivery: covalent vs non-covalent approaches

Nowadays, nanomaterials are increasingly being used as drug carriers in the treatment of different types of cancers. As a result, these applications make them attractive to researchers dealing with diagnosis and biomarkers discovery of the disease. In this study, the adsorption behavior of gemcitabine (GMC) on graphene nanosheet (GNS), in the presence and absence of Poly (L-histidine) (PLH) polymer is discussed using molecular dynamics (MD) simulation. The MD results revealed an increase in the efficiency and targeting of the drug when the polymer is covalently attached to the graphene substrate. In addition, the metadynamics simulation to investigate the effects of PLH on the adsorption capacity of the GNS, and explore the adsorption/desorption process of GMC on pristine and PLH- grafted GNS is performed. The metadynamics calculations showed that the amount of free energy of the drug in acidic conditions is higher (- 281.26 kJ/mol) than the free energy in neutral conditions (- 346.24 kJ/mol). Consequently, the PLH polymer may not only help drug adsorption but can also help in drug desorption in lower pH environments. Based on these findings, it can be said that covalent polymer bonding not only can help in the formation of a targeted drug delivery system but also can increase the adsorption capacity of the substrate.