Search Results - "Messerly, Richard A"

Configuration-Sampling-Based Surrogate Models for Rapid Parameterization of Non-Bonded Interactions by Messerly, Richard A, Razavi, S. Mostafa, Shirts, Michael R

“…In this study, we present an approach for rapid force field parameterization and uncertainty quantification of the non-bonded interaction parameters for…”
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Exploring the frontiers of condensed-phase chemistry with a general reactive machine learning potential by Zhang, Shuhao, Makoś, Małgorzata Z., Jadrich, Ryan B., Kraka, Elfi, Barros, Kipton, Nebgen, Benjamin T., Tretiak, Sergei, Isayev, Olexandr, Lubbers, Nicholas, Messerly, Richard A., Smith, Justin S.

“…Atomistic simulation has a broad range of applications from drug design to materials discovery. Machine learning interatomic potentials (MLIPs) have become an…”
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Data Generation for Machine Learning Interatomic Potentials and Beyond by Kulichenko, Maksim, Nebgen, Benjamin, Lubbers, Nicholas, Smith, Justin S., Barros, Kipton, Allen, Alice E. A., Habib, Adela, Shinkle, Emily, Fedik, Nikita, Li, Ying Wai, Messerly, Richard A., Tretiak, Sergei

“…The field of data-driven chemistry is undergoing an evolution, driven by innovations in machine learning models for predicting molecular properties and…”
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Bayesian-Inference-Driven Model Parametrization and Model Selection for 2CLJQ Fluid Models by Madin, Owen C, Boothroyd, Simon, Messerly, Richard A, Fass, Josh, Chodera, John D, Shirts, Michael R

“…A high level of physical detail in a molecular model improves its ability to perform high accuracy simulations but can also significantly affect its complexity…”
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Mie 16–6 force field predicts viscosity with faster-than-exponential pressure dependence for 2,2,4-trimethylhexane by Messerly, Richard A., Anderson, Michelle C., Razavi, S. Mostafa, Elliott, J. Richard

“…In response to the 10th Industrial Fluid Properties Simulation Challenge, we report viscosity (η) estimates obtained with equilibrium molecular dynamics for…”
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Predicting phosphorescence energies and inferring wavefunction localization with machine learning by Sifain, Andrew E, Lystrom, Levi, Messerly, Richard A, Smith, Justin S, Nebgen, Benjamin, Barros, Kipton, Tretiak, Sergei, Lubbers, Nicholas, Gifford, Brendan J

“…Phosphorescence is commonly utilized for applications including light-emitting diodes and photovoltaics. Machine learning (ML) approaches trained on ab initio…”
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Coexistence calculation using the isothermal-isochoric integration method by Razavi, S. Mostafa, Messerly, Richard A., Elliott, J. Richard

“…In this work, the isothermal-isochoric integration (ITIC) method is demonstrated as a viable method for vapor-liquid coexistence calculation by molecular…”
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Molecular Calculation of the Critical Parameters of Classical Helium by Messerly, Richard A, Gokul, Navneeth, Schultz, Andrew J, Kofke, David A, Harvey, Allan H

“…We compute the vapor–liquid critical coordinates of a model of helium in which nuclear quantum effects are absent. We employ highly accurate ab initio pair and…”
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Histogram-Free Reweighting with Grand Canonical Monte Carlo: Post-simulation Optimization of Non-bonded Potentials for Phase Equilibria by Messerly, Richard A, Soroush Barhaghi, Mohammad, Potoff, Jeffrey J, Shirts, Michael R

“…Histogram reweighting (HR) is a standard approach for converting grand canonical Monte Carlo (GCMC) simulation output into vapor–liquid coexistence properties…”
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Understanding how chemical structure affects ignition-delay-time ϕ-sensitivity by Messerly, Richard A., Luecke, Jon H., St. John, Peter C., Etz, Brian D., Kim, Yeonjoon, Zigler, Bradley T., McCormick, Robert L., Kim, Seonah

“…ϕ-sensitivity is the change in ignition delay time (IDT) with respect to the fuel-to-air equivalence ratio (ϕ). High ϕ-sensitivity is a desirable fuel property…”
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Towards quantitative prediction of ignition-delay-time sensitivity on fuel-to-air equivalence ratio by Messerly, Richard A., Rahimi, Mohammad J., St. John, Peter C., Luecke, Jon H., Park, Ji-Woong, Huq, Nabila A., Foust, Thomas D., Lu, Tianfeng, Zigler, Bradley T., McCormick, Robert L., Kim, Seonah

“…Several compression-ignition and low-temperature combustion strategies require a fuel where the ignition-delay-time (IDT) is highly sensitive to the…”
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Molecular Calculation of the Critical Parameters of Classical Helium by Messerly, Richard A, Gokul, Navneeth, Schultz, Andrew J, Kofke, David A, Harvey, Allan H

“…We compute the vapor-liquid critical coordinates of a model of helium in which nuclear quantum effects are absent. We employ highly accurate pair and…”
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Developing an internally consistent set of theoretically based prediction models for the critical constants and normal boiling point of large n-alkanes by Messerly, Richard A., Knotts, Thomas A., Giles, Neil F., Wilding, W. Vincent

“…The normal boiling point (Tb), critical temperature (Tc), critical pressure (Pc), critical density (ρc), and critical compressibility factor (Zc) are essential…”
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Improved Estimates of the Critical Point Constants for Large n‑Alkanes Using Gibbs Ensemble Monte Carlo Simulations by Messerly, Richard A, Rowley, Richard L, Wilding, W. Vincent

“…In this work, we present improved estimates of the critical temperature (T c), critical density (ρc), critical pressure (P c), and critical compressibility…”
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Building a DFT+U machine learning interatomic potential for uranium dioxide by Stippell, Elizabeth, Alzate-Vargas, Lorena, Subedi, Kashi N., Tutchton, Roxanne M., Cooper, Michael W.D., Tretiak, Sergei, Gibson, Tammie, Messerly, Richard A.

“…Despite uranium dioxide (UO2) being a widely used nuclear fuel, fuel performance models rely extensively on empirical correlations of material behavior,…”
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An improved approach for predicting the critical constants of large molecules with Gibbs Ensemble Monte Carlo simulation by Messerly, Richard A., Knotts, Thomas A., Rowley, Richard L., Wilding, W. Vincent

“…In this work we focus on predicting the critical temperature (Tc), critical density (ρc), and critical pressure (Pc) from Gibbs Ensemble Monte Carlo (GEMC)…”
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Ternary Liquid–Liquid Equilibrium of Biodiesel Compounds for Systems Consisting of a Methyl Ester + Glycerin + Water by Bell, Joseph C, Messerly, Richard A, Gee, Ryan, Harrison, Aaron, Rowley, Richard L, Wilding, W. Vincent

“…Ternary LLE data have been experimentally measured for several systems consisting of biodiesel compounds. Systems measured include mixtures with the methyl…”
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Improvements and limitations of Mie λ-6 potential for prediction of saturated and compressed liquid viscosity by Messerly, Richard A., Anderson, Michelle C., Razavi, S. Mostafa, Elliott, J. Richard

“…Over the past decade, the Mie λ-6 (generalized Lennard-Jones) potential has grown in popularity due to its improved accuracy for predicting vapor-liquid…”
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Bayesian inference-driven model parameterization and model selection for 2CLJQ fluid models by Madin, Owen C., Boothroyd, Simon, Messerly, Richard A., Fass, Josh, Chodera, John D., Shirts, Michael R.

“…A high level of physical detail in a molecular model improves its ability to perform high accuracy simulations, but can also significantly affect its…”
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Elucidating the temperature and density dependence of silver chloride hydration numbers in high-temperature water vapor: A first-principles molecular simulation study by Messerly, Richard A., Yoon, Tae Jun, Jadrich, Ryan B., Currier, Robert P., Maerzke, Katie A.

“…Hydration numbers of metal complexes in low-density aqueous solutions are required for developing geochemical models for ore-forming metals and for designing…”
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