Predicting Pair Correlation Functions of Glasses using Machine Learning

Glasses offer a broad range of tunable thermophysical properties that are linked to their compositions. However, it is challenging to establish a universal composition-property relation of glasses due to their enormous composition and chemical space. Here, we address this problem and develop a metamodel of composition-atomistic structure relation of a class of glassy material via a machine learning (ML) approach. Within this ML framework, an unsupervised deep learning technique, viz. convolutional neural network (CNN) autoencoder, and a regression algorithm, viz. random forest (RF), are integrated into a fully automated pipeline to predict the spatial distribution of atoms in a glass. The RF regression model predicts the pair correlation function of a glass in a latent space. Subsequently, the decoder of the CNN converts the latent space representation to the actual pair correlation function of the given glass. The atomistic structures of silicate (SiO2) and sodium borosilicate (NBS) based glasses with varying compositions and dopants are collected from molecular dynamics (MD) simulations to establish and validate this ML pipeline. The model is found to predict the atom pair correlation function for many unknown glasses very accurately. This method is very generic and can accelerate the design, discovery, and fundamental understanding of composition-atomistic structure relations of glasses and other materials

New universal scaling laws of diffusion and Kolmogorov-Sinai entropy in simple liquids

A new universal scaling law relating the self-diffusivities of the components of a binary fluid mixture to their excess entropies is derived using mode coupling theory. These scaling laws yield numerical results, for a hard sphere as well as Lennard-Jones fluid mixtures, in excellent agreement with simulation results even at a low density region, where the empirical scaling laws of Dzugutov [Nature (London) 381, 137 (1996)] and Hoyt, Asta, and Sadigh [Phys. Rev. Lett. 85, 594 (2001)] fail completely. A new scaling law relating the Kolmogorov-Sinai entropy to the excess entropy is also obtained

Universal scaling laws of diffusion in a binary fluid mixture

A new universal scaling law relating the self-diffusivities of a binary fluid mixture and the excess entropies of its components is derived using mode coupling theory, reproducing the empirical scaling laws of Dzugutov [Nature (London) 381, 137 (1996)] and Hoyt et al. [Phys. Rev. Lett. 85, 594 (2000)] as special cases. The derived scaling laws are tested through numerical calculations for binary Lennard-Jones fluid mixtures for a wide range of physical parameters, and a very good correlation is observed. We have also arrived at a new universal scaling relationship between the cross-diffusivity and entropy for the first time

A microscopic theory of tracer diffusivity: crossover to the hydrodynamic limit

A microscopic approach is developed for the tracer diffusivity in fluids based on the concepts of mode coupling theory. The calculated numerical results for the tracer diffusivity in a Lennard-Jones (LJ) fluid are shown to be in good agreement with the corresponding simulation results. The hydrodynamic limit is found to be reached at higher mass and larger size of the solute particle which is consistent with the results of simulation studies

Curious Characteristics of Polar and Nonpolar Molecules Confined within Carbon Nanotubes (CNT) of Varied Diameter: Insights from Molecular Dynamics Simulation

Carbon nanotube (CNT) has emerged as a potential candidate for desalination of salty water as well as for purification of various kinds of gaseous and liquid mixtures which is controlled by the interaction of the fluid molecules within the nanocavity of CNT. It is, therefore, worthwhile to investigate the behavior of both the polar and nonpolar fluid molecules within the nanoconfinement of CNT at the molecular level. In the present study, molecular dynamics simulations have been performed to investigate the structure and dynamics of polar and nonpolar molecules within CNTs. Results show the enhancement of confined density with increase in nanotube diameter. Single file flow of water, methanol, and methane inside CNT­(6,6) was diminished with increase in nanotube diameter and converted to layered flow for larger CNTs. Surprisingly, results showed controversial effects of nanotube dimension for dynamics of polar and nonpolar fluids, which has been explained in terms of interaction forces acting between fluid particles and fluid–nanotube wall. The density of states (DOS) results have been found in line with the corresponding velocity autocorrelation function (VACF). Interestingly, the altered H bonding of methanol in the axial and radial direction of CNT­(6,6) and CNT­(7,7) conceded the reversal effects on rotation degree of freedom (DOF) and translation DOF respectively. However, all such effects were observed to be vanished for the larger diameter of CNTs. Overall, the present study provides an insightful view of flow transition from sub continuum to bulk fluid properties, while moving from small to large diameter CNTs, established with both the polar and nonpolar fluids, which is supposed to be very supportive for understanding of equivalent fluid channels in living cells, and the CNTs would serve as good prototypes for narrow biological channels

Molecular Dynamics Simulation for the Calibration of the OPLS Force Field Using DFT Derived Partial Charges for the Screening of Alkyl Phosphate Ligands by Studying Structure, Dynamics, and Thermodynamics

Molecular dynamics (MD) simulations were performed to calibrate the all-atom optimized potential for liquid simulations (OPLS-AA) force field using partial quantum charges calculated from four different population analysis methods: Mulliken, Löwdin, NPA, and ChelpG for predicting the thermophysical properties of pure liquids like tri-<i>n</i>-butylphosphate (TBP), tri-isoamylphosphate (TiAP), triethylphosphate (TEP), and dodecane to determine a potential solvent for the nuclear fuel cycle. The structural, dynamic, and thermodynamic properties were calculated in NVT ensembles by introducing the partial charges on each atom calculated from density functional theory (DFT). The calculated structural and dynamic properties were affected by the different partial charges on TBP, TiAP, and TEP. The estimated liquid density employing partial charges obtained from Mulliken population analysis with OPLS force field leads to an excellent agreement with the experimental data (within 0.36–1.41%). The diffusivity and the pair correlation function (PCF) for all of the ligands have been calculated and validated wherever literature data is available. The free energies of hydration and solvation for all of the ligands were evaluated using thermodynamic integration technique and the hydration free energy for TEP is within 8.3% of the experimental value, and for other properties they are not available in the literature for comparison. Furthermore, the partition coefficient of the ligands calculated using MD derived free energy difference between the water–dodecane system resembles the trend predicted by DFT/COSMO-RS calculations which is in qualitative agreement with the experimental results. Among the four-charge model, the computed dipole moment of TBP and TEP using the Mulliken charge is found to be in good agreement with the experimental results. Finally, the superiority of TiAP over TBP as an extracting agent for the UO₂²⁺ ion has been demonstrated by a higher calculated free energy of extraction, Δ<i>G</i>_ext, over TBP using DFT. Overall the Mulliken charge embedded calibrated OPLS-AA force field is perhaps the most reliable one as it does not incorporate any arbitrary scaling in the force field or Lennard–Jones parameters and thus can be used indubitably to evaluate the liquid state properties of alkyl phosphates and <i>n</i>-alkanes which eventually assist in the invent of future generation extractants