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Opportunity at National Institute of Standards and Technology (NIST)

Data-Driven Technologies for Fluid Property Simulation

Location

Material Measurement Laboratory, Applied Chemicals and Materials Division

RO# Location
50.64.72.B7990 Boulder, CO

Please note: This Agency only participates in the February and August reviews.

Advisers

Name E-mail Phone
Kazakov, Andrei andrei.kazakov@nist.gov 303.497.4898
Kroenlein, Kenneth kenneth.kroenlein@nist.gov 303.497.4852

Description

Molecular modeling (i.e., Monte Carlo and molecular dynamics methods) are becoming computationally-accessible for large-scale simulations of various thermophysical and mechanical properties of substances.

Relatively simple, semiempirical force field-based models appear to provide sufficient framework for quantitative predictions of a range of properties. The key issue with predictive molecular modeling is the parametrization of the force field. There are a large number of force fields in existence and significant efforts are spent on their development and improvement. However, to-date, development of force field models is not performed in a systematic manner. The parameters are usually obtained to reproduce limited experimental observations, often of questionable or unknown quality. Furthermore, the parameter adjustments are usually performed in a brute-force manner, without considerations of nonlinear coupling between multiple parameters. As a result, the models (that reproduce the data that they were calibrated against) often poorly extrapolate to different conditions or different properties. Uncertainties associated with such extrapolations are not easily quantifiable. Our goal is to use the extensive experimental data archives available at NIST/TRC and advanced multidimensional optimization techniques to generate self-consistent, predictive force-filed models applicable over wide range of conditions.

 

Keywords:
Molecular dynamics; Molecular simulation; Monte Carlo; Force field; Thermodynamic properties; Transport properties;

Eligibility

Citizenship:  Open to U.S. citizens
Level:  Open to Postdoctoral applicants
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