Research · NIST AI
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By using machine learning approaches, they seek to elucidate underlying universal characteristics of fluids and fluid mixtures that enable property prediction.
Key facts
- NIST provided a $500,000 Advanced Manufacturing Technology Consortia (AMTech) Program Planning Award to initiate a collaborate effort with the American Chemical Society Green Chemistry Institute (ACS
- R., "Regional, temporal, and species patterns of mercury in Alaskan seabird eggs: Mercury sources and cycling or food web effects?," Environmental Pollution, 166, 226-232 (2012)
- K., "Predicting low-temperature free energy landscapes with flat-histogram Monte Carlo methods," Journal of Chemical Physics, 146, (2017)
- K., " Multivariable extrapolation of grand canonical free energy landscapes," Journal of Chemical Physics, 147, (2017)
Summary
Official websites use.gov A.gov website belongs to an official government organization in the United States. Secure.gov websites use HTTPS A lock or https:// means you’ve safely connected to the.gov website. Machine learning approaches are being studied by NIST for enable property prediction of fluids and fluid mixtures. Understanding the thermodynamic properties of fluids and fluid mixtures is of central importance in many fields of science and engineering ranging from medicine to consumer products.