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At least 487 records · Page 27

High-throughput screening of tribological properties of monolayer films using molecular dynamics and machine learning

Monolayer films have shown promise as a lubricating layer to reduce friction and wear of mechanical devices with separations on the nanoscale. These films have a vast design space with many tunable properties that can affect their tribological effectiveness. For example, terminal group chemistry, film composition, and backbone chemistry can all lead to films with significantly different tribological properties. This design space, however, is very difficult to explore without a combinatorial approach and an automatable, reproducible, and extensible workflow to screen for promising candidate films. Here, using the Molecular Simulation Design Framework (MoSDeF), a combinatorial screening study was performed to explore 9747 unique monolayer films (116 964 total simulations) and a machine learning (ML) model using a random forest regressor, an ensemble learning technique, to explore the role of terminal group chemistry and its effect on tribological effectiveness. The most promising films were found to contain small terminal groups such as cyano and ethylene. The ML model was subsequently applied to screen terminal group candidates identified from the ChEMBL small molecule library. Approximately 193 131 unique film candidates were screened with approximately a five order of magnitude speed-up in analysis compared to simulation alone. The ML model was thus able to be used as a predictive tool to greatly speed up the initial screening of promising candidate films for future simulation studies, suggesting that computational screening in combination with ML can greatly increase the throughput in combinatorial approaches to generate in silico data and then train ML models in a controlled, self-consistent fashion.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Molecular dynamics simulations of the dielectric constants of salt-free and salt-doped polar solvents

Here, we develop a Stockmayer fluid model that accounts for the dielectric responses of polar solvents (water, MeOH, EtOH, acetone, 1-propanol, DMSO, and DMF) and NaCl solutions. These solvent molecules are represented by Lennard-Jones (LJ) spheres with permanent dipole moments and the ions by charged LJ spheres. The simulated dielectric constants of these liquids are comparable to experimental values, including the substantial decrease in the dielectric constant of water upon the addition of NaCl. Moreover, the simulations predict an increase in the dielectric constant when considering the influence of ion translations in addition to the orientation of permanent dipoles.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Quasiclassical sampling and Wigner sampling of initial vibrational coordinates and momenta for polyatomic molecules in Monte Carlo molecular dynamics simulations

In a quasiclassical trajectory simulation, the vibrational modes are initialised with quantised vibrational energies, but vibrational phases are sampled by Monte Carlo. This requires an algorithm to assign coordinates and momenta to the various atoms. In this work, we present two methods for implementing this for nonrotating polyatomic molecules, namely, fixed-energy vibrational-state-selected initial conditions and thermal initial conditions. We also present a method for initiating classical trajectories with a ground-state Wigner distribution. These vibrational treatments are sufficient to initialise trajectories for unimolecular processes, and we also show how they can be applied to simulate bimolecular collision processes. The treatments of unimolecular and bimolecular collision processes are available in two Python codes called wigner_state_selected.py and bimolecular_collision.py, respectively, which will generate initial condition files that are recognisable by the SHARC and SHARC-MN computer programs for dynamics calculations. Both codes are available as standalone programs, as well as being included in SHARC-MN, and they will be included in future versions of SHARC. Here, the methods implemented in these codes are mostly also available in the ANT computer program, and those that are not available in ANT will be incorporated in future versions of ANT.

Wigner distribution↗

Multiscale Molecular Dynamics Simulations: Accelerating Conformational Sampling of Biomolecular Systems by Iterating All-Atom and Coarse-Grained Simulations

We developed the atomistic-coarse-grained multiscale MD simulation method in the OpenMM simulation package by iterating between the all-atom (AA) and coarse-grained (CG) MD simulations to enhance the sampling of biomolecular conformations. As the free energy surfaces are flattened during CG MD simulations, we can accelerate the transitions between different low-energy conformations. The AA-CG-AA cycles are repeated, facilitating the accelerated sampling of biomolecular conformations at a CG level, while the finer atomistic interactions are refined with AA simulators.

Do, Hung Nguyen↗

Predicting thermodynamic and thermophysical properties of molten chloride salts from ab-initio and classical molecular dynamics simulations

Molten salt reactors (MSRs) are among the advanced concepts pursued under the generation IV nuclear energy technology umbrella. However, the basic concept is not new and was first developed as part of the effort to power aircrafts with nuclear energy in the 1950’s. Later in the 1960’s, Oak Ridge National Laboratory (ORNL) built and operated the Molten-Salt Reactor Experiment (MSRE). This reactor used a fluoride salt with uranium as fuel. Fluorides salts are still highly relevant and proposed in several designs. In addition, chloride salts are being considered for MSRs operating in the fast neutron spectrum. This report focuses on chloride salts.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

The Reactivity and Structural Dynamics of Supported Metal Nanoclusters Using Electron Microscopy, in-situ X-Ray Spectroscopy, Electronic Structure Theories, and Molecular Dynamics Simulations

This research will provide new methods to determine the structures and compositions of heterogeneous catalysts as they exist in reaction conditions. The new tools will make it possible to understand how extremely small material structures—ones in a size range spanning from single atoms to larger polyatomic clusters—make it possible to carry out highly selective chemical transformations required to synthesize useful materials as well as for efficient energy production and utilization. The tools will make it possible to see how the atomic structures of catalytic materials evolve over time under the conditions of their use, and in this way provide understandings to guide the design of new energy-efficient catalysts. The work will make it possible to answer long standing questions that include the following. How does catalyst structure help guide molecules along specific reaction pathways? What are the important intermediates involved in these transformations? How do the structures and reactivity of catalytic materials, as well as the chemistry of their interfaces, vary with reaction conditions? Is it possible to develop new catalytic materials using new knowledge of the active structures and reaction mechanisms? The work will provide heretofore unavailable experimental tools that can be applied in advanced programs of research addressing such questions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗