Publications
Showing 22 results for Author: Dilip N. Asthagiri
May, 2026
Journal
Rotational memory function of SPC/E water
Memory effects are essential for the dynamics of condensed materials and are responsible for non-exponential relaxation of correlation functions of dynamic variables through the memory function. Memory functions of dipole rotations for water have never been calculated directly from molecular dynamics simulations. We present here calculations of memory functions for single-…
Mar, 2026
Conference Paper
Ensemble Simulations on Leadership Computing Systems
Scientific productivity can be enhanced through workflow management tools, relieving large High Performance Computing (HPC) system users from the tedious tasks of scheduling and designing the complex computational execution of scientific applications. This paper presents a study on the usage of ensemble workflow tools to accelerate science using the Summit and Frontier sup…
Jan, 2026
Journal
Equipartition and the Temperature of Maximum Density of TIP4P/2005 Water
We simulate TIP4P/2005 water in the temperature range of 257 to 318 K with time-steps δ = 0.25, 0.50, 1.00, 2.00, and 4.00 fs. The density–temperature behavior obtained using 0.25 or 0.50 fs is in excellent agreement with each other but differs from those obtained using time steps that have been shown earlier to lead to a breakdown of equipartition. For δt = 0.25 or 0.50 f…
Nov, 2025
Journal
Extended molecular eigenmodes treatment of dipole–dipole NMR relaxation in real fluids
Traditional models of NMR relaxation fail to account for the complex, multi-exponential behavior of the autocorrelation function in realistic systems characterized by soft-interactions and molecules that are chemically and physically complex. Here, we describe the relative diffusion of the spin dipoles by means of a Fokker–Planck equation that includes an interaction poten…
Aug, 2025
ORNL Report
Workflows for Science: A comprehensive guide for ensemble workflow tools usage with applications on OLCF systems
The growing demand for robust computational and workflow environments for scientific applications and user communities at the Oak Ridge Leadership Computing Facility (OLCF) has prompted collaboration with ensemble tools development teams and facility users to produce this technical paper. We connect science applications to the RADICAL-Pilot (RP) workflow tool to execute en…
Jun, 2025
Journal
Characterization of kerogen nanopores using 2D NMR relaxation and MD simulations
The characterization of kerogen nanopores is crucial for predicting the geostorage capacity and recoverability of natural gas in unconventional gas shale reservoirs. Towards this end, a powerful technique is presented which integrates 2D NMR T1-T2 relaxation measurements with molecular dynamics (MD) simulations of hydrocarbons confined in the nanopores of kerogen. The inte…
Apr, 2025
Journal
Molecular-Level Insights into the NMR Relaxivity of Gadobutrol Using Quantum and Classical Molecular Simulations
MRI is an indispensable diagnostic tool in modern medicine; however, understanding the molecular-level processes governing NMR relaxation of water in the presence of MRI contrast agents remains a challenge, hindering the molecular-guided development of more effective contrast agents. By using quantum-based polarizable force fields, the first-of-its-kind molecular dynamics…
Mar, 2025
Journal
Consequences of the failure of equipartition for the p–V behavior of liquid water and the hydration free energy components of a small protein
Earlier we showed that in the molecular dynamics simulation of a rigid model of water it is necessary to use an integration time-step δt ≤ 0.5 fs to ensure equipartition between translational and rotational modes. Here we extend that study in the NVT ensemble to NpT conditions and to an aqueous protein. We study neat liquid water with the rigid, SPC/E model and the protein…
Mar, 2025
Journal
Multi-level Monte Carlo methods in chemical applications with Lennard-Jones potentials and other landscapes with isolated singularities
We describe and compare outcomes of various Multi-Level Monte Carlo (MLMC) method variants, motivated by the potential of improved computational efficiency over rejection based Monte Carlo, which scales poorly with problem dimension. With an eye toward its application to computational chemical physics, we test MLMC's ability to sample trajectories on two problems — a famil…