Thermodynamics and the potential energy landscape: case study of small water clusters

Surface phase diagrams from nested sampling

Studies in atomic-scale modeling of surface phase equilibria often focus on temperatures near zero Kelvin due to the challenges in calculating the free energy of surfaces at finite temperatures. The Bayesian-inference-based nested sampling (NS) algorithm allows for modeling phase equilibria at arbitrary temperatures by directly and efficiently calculating the partition function, whose relationship with free energy is well known. This work extends NS to calculate adsorbate phase diagrams, incorporating all relevant configurational contributions to the free energy. We apply NS to the adsorption of Lennard-Jones (LJ) gas particles on low-index and vicinal LJ solid surfaces and construct the canonical partition function from these recorded energies to calculate ensemble averages of thermodynamic properties, such as the constant-volume heat capacity and order parameters that characterize the structure of adsorbate phases. Key results include determining the nature of phase transitions of adsorbed LJ particles on flat and stepped LJ surfaces, which typically feature an enthalpy-driven condensation at higher temperatures and an entropy-driven reordering process at lower temperatures, and the effect of surface geometry on the presence of triple points in the phase diagrams. Overall, we demonstrate the ability and potential of NS for surface modeling.

Stability of the high-density Jagla liquid in 2D: sensitivity to parameterisation

We computed the pressure-temperature phase diagram of the hard-core two-scale ramp potential in two-dimensions, with the parameterisation originally suggested by Jagla [E. A. Jagla, Phys. Rev. E, 63, 061501 (2001)], as well as with a series of systematically modified variants of the model to reveal the sensitivity of the stability of phases. The nested sampling method was used to explore the potential energy landscape, allowing the identification of thermodynamically relevant phases, such as low- and high-density liquids and various crystalline forms, some of which have not been reported before. We also proposed a smooth version of the potential, which is differentiable beyond the hard-core. This potential reproduces the density anomaly, but forms a dodecahedral quasi-crystal structure at high pressure. Our results allow to hypothesise on the necessary modifications of the original model in order to improve the stability of the metastable high-density liquid phase in 3D.

Finite Element Analysis for Predicting Skin Pharmacokinetics of Nano Transdermal Drug Delivery System Based on the Multilayer Geometry Model

Background

Skin pharmacokinetics is an indispensable indication for studying the drug fate after administration of transdermal drug delivery systems (TDDS). However, the heterogeneity and complex skin structured with stratum corneum, viable epidermis, dermis, and subcutaneous tissue inevitably leads the drug diffusion coefficient (Kp) to vary depending on the skin depth, which seriously limits the development of TDDS pharmacokinetics in full thickness skin.

Methods

A multilayer geometry skin model was established and the Kp of drug in SC, viable epidermis, and dermis was obtained using the technologies of molecular dynamics simulation, in vitro permeation experiments, and in vivo microdialysis, respectively. Besides, finite element analysis (FEA) based on drug Kps in different skin layers was applied to simulate the paeonol nanoemulsion (PAE-NEs) percutaneous dynamic penetration process in two and three dimensions. In addition, PAE-NEs skin pharmacokinetics profile obtained by the simulation was verified by in vivo experiment.

Results

Coarse-grained modeling of molecular dynamic simulation was successfully established and the Kp of PAE in SC was 2.00×10⁻⁶ cm²/h. The Kp of PAE-NE in viable epidermis and in dermis detected using penetration test and microdialysis probe technology, was 1.58×10⁻⁵ cm²/h and 3.20×10⁻⁵ cm²/h, respectively. In addition, the results of verification indicated that PAE-NEs skin pharmacokinetics profile obtained by the simulation was consistent with that by in vivo experiment.

Discussion

This study demonstrated that the FEA combined with the established multilayer geometry skin model could accurately predict the skin pharmacokinetics of TDDS.

Pressure-Temperature Phase Diagram of Lithium, Predicted by Embedded Atom Model Potentials

In order to study the performance of interatomic potentials and their reliability at higher pressures, the phase diagrams of two different embedded-atom-type potential models (EAMs) and a modified embedded-atom model (MEAM) of lithium are compared. The calculations were performed by using the nested sampling technique in the pressure range 0.01-20 GPa, in order to determine the liquid-vapor critical point, the melting curve, and the different stable solid phases of the compared models. The low-pressure stable structure below the melting line is found to be the body-centered-cubic (bcc) structure in all cases, but the higher pressure phases and the ground-state structures show a great variation, being face-centered cubic (fcc), hexagonal close-packed (hcp), a range of different close-packed stacking variants, and highly symmetric open structures are observed as well. A notable behavior of the EAM of Nichol and Ackland (Phys. Rev. B: Condens. Matter Mater. Phys. 2016, 93, 184101) is observed, that the model displays a maximum temperature in the melting line, similarly to experimental results.

Finite Systems under Pressure: Assessing Volume Definition Models from Parallel-Tempering Monte Carlo Simulations

We have investigated different approaches to handling parallel-tempering Monte Carlo (PTMC) simulations in the isothermal-isobaric ensemble of molecular cluster/nanoparticle systems for predicting structural phase diagram transitions. We have implemented various methodologies that consist of treating pressure implicitly through its effect on the volume. Thus, the main problem in the simulations under nonzero pressure becomes the volume definition of the finite nonperiodic system, and we considered approaches based on the particles' coordinates. Various volume models, namely container-volume, particle-volume, average-volume, ellipsoids-volume, and convex hull-volume, were employed, and the required corrections for each of them in the Monte Carlo computations were introduced. Finally, we explored the effects of volume/pressure changes for all models on structural phase transitions of a test system, such as the small "icelike" (H₂O)₁₂ water cluster. The temperature and pressure dependence of the cluster's heat capacity and energy-volume Pearson correlation coefficient were studied, phase diagrams were constructed using a multiple-histogram method, and attempts were made to identify phase transitions to particular cluster structures. Our results show significant differences between the employed volume models, and we discuss all pressure-induced, such as solid-solid-, solid-liquid-, and liquid-gas-like, phase transformations in the present study.