Abstract: Modern scientific progress is being driven by larger data sets and more comprehensive analyses. In the Thermodynamics Research Center at the National Institute of Standards and Technology (NIST) in the US, we specialize in the curation of high quality thermophysical and thermochemical property data for well-defined chemical systems and their validation using domain expertise and information technology. Given the many fundamental interrelationships between thermodynamic properties, a strong foundation in physical modeling, and the heuristics that industrial practice has developed, this generates the need to synthesize a range of heterogenous information channels into coherent recommendations. This is made all the more challenging in that for any particular chemical system, the particular models and data availability will vary wildly. Every data scenario becomes unique. In this presentation, we will discuss a range of tools that TRC is developing for this challenge. Particular areas to be discussed include: the general development of algorithms for empowering domain experts to quickly and comprehensively evaluate new data in a historical context, a quantum chemical tool chain for large-scale prediction of ideal gas enthalpies of formation with uncertainties on par with experimental calorimetry, and application of machine learning techniques to the very limited data sets available in the chemical literature. In all this, it is important to consider that while the entirety of relevant data reported in the open literature is small on the scale of Big Data, high-quality data points are costly in both time and money, and thus researchers must take maximal advantage of every piece of information available.
Bio: Dr. Kenneth Kroenlein is the Director of the Thermodynamics Research Center (TRC) at the U.S. National Institute of Standards and Technology (NIST) in Boulder, Colorado, USA. After graduation from Princeton University with a PhD in Mechanical Engineering in 2007, he joined the TRC group to continue pursuing his interests in optimal recommended values for thermophysical and thermochemical properties for well characterized systems. His research interests cover a broad range of the scientific areas such as phenomenological thermodynamics, computational physics and numerical methods, information management and communication, and machine learning techniques. Dr. Kroenlein serves on board of the International Association of Chemical Thermodynamics (IACT) as treasurer, on the organizing committee for the Symposium on Thermophysical Properties, and on the editorial boards of the Journal of Physical and Chemical Reference Data and the International Journal of Thermophysics.