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SUMMARY:Design Principles for Sustainable Chemistry: from Biomass to Renewa
 ble Biofuel and Biomaterial
LOCATION:Chemistry A101
TZID:America/Denver
DTSTART:20191101T000000
UID:2026-05-05-04-26-50@natsci.colostate.edu
DTSTAMP:20260505T042650
Description:About the Seminar:\n\nThe overarching goal of our group is to d
 evelop new methods to extract sustainable fuels and chemicals from plants.
  Our approach has been to develop and apply computational tools to both bi
 ological and chemical conversion processes as part of an iterative ‘mode
 l-validate-predict’ design process for de novo catalysts.\n\nWith its hi
 gh carbon and hydrogen content\, lignocellulosic biomass presents an alter
 native to petroleum as a nearly carbon-neutral precursor to upgraded liqui
 d fuels. I will present some  representative results in designing new cat
 alysts for biological and chemocatalytic processes of biomass.\n\nOur grou
 p has introduced a “Fuel property first” design approach to reduce emi
 ssions and increase performance. Traditional approaches for developing the
 se mechanistic models require many years for each new molecule\, a pace th
 at is poorly suited to the large-scale search for new bioderived blendstoc
 ks. We have developed a quantitative structure-property relationship (QSPR
 ) model for sooting tendency based on the experimental yield sooting index
  (YSI)\, developed by collaborators at Yale (Prof. L. Pfefferle and Dr. C.
  McEnally). This is the first fuel property predictive tool using ML (Mach
 ine Learning) approaches in combustion research. We have started to build 
 kinetic mechanisms of soot precursor formation during combustion using DFT
  and flow reactor experiments (collaboration with Dr. R. McCormick\, NREL)
  to show how the fundamental chemistry affects this practical engineering 
 problem.\nAbout the Speaker:\nSeonah Kim is a senior scientist at NREL sin
 ce 2011.\nHer research background combines extensive experience in both cl
 assical molecular dynamics simulations and quantum mechanical modeling (DF
 T) of transition states. She has been working on understanding and designi
 ng catalysts for the decomposition of both lignin and cellulose. Her resea
 rch areas contribute on both biochemical and thermochemical conversion pro
 jects based on a variety of biocatalysts and inorganic catalysts experienc
 es. She expand her research by combining DFT and machine learning to predi
 ct fuel/chemical properties.\nSeonah leads projects for autoignition prope
 rties determination project (DFT/machine learning)\, computational thermoc
 hemical conversion catalysts and also enzymatic engineering for biochemica
 l conversion. She serves as a Chair (2020) for computational chemistry div
 ision (COMP) of American Chemical Society (ACS). Seonah receive a M. Sc. i
 n Computer Science from University of Houston and a Ph. D. in Computationa
 l Chemistry from University of Florida. 4:00 pm
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