Method for Cost Effective Molecular Separations and Process Optimization
Princeton Docket #13-2887/2975
Researchers in the Department of Chemical and Biological Engineering at Princeton University have developed a multi-scale computational screening approach for identifying promising materials from databases for industrial separations. The approach is novel in that it selects the most cost-effective materials and optimal process conditions while satisfying important systems-level constraints, such as product purity and recovery. This is in contrast to previous methods which have only considered the material or process in isolation.
Applications of this screening methodology include, but are not limited to, carbon capture, xylene separation, hydrocarbon separation, and natural gas purification. Proof of concept has been demonstrated for the separation of carbon dioxide from power plant flue gases, identifying novel zeolite sorbents as promising materials for cost-effective carbon capture for the first time.
· Cost-effective CO2 capture
· Applicable to other molecular separations of industrial interest:
o Xylene separation
o Hydrogen recovery
o Natural gas purification
o Ethylene and propylene production
· Valuable for high impact chemicals which are difficult to separate by traditional means
· Fully optimized process to combine selection of material with process needs and outcomes
· Results in separations with low cost, high purity and recovery.
Description of the Innovation
This novel computational screening approach starts with ZEOMICS, a three-dimensional pore characterization method, which is applied to each zeolite in a micro-porous materials database. Other databases, such as those for metal-organic frameworks, could also be used. The zeolites are ranked based on the novel metrics of shape selectivity and size selectivity, and the adsorption selectivity is calculated for the top structures. For each high-performing zeolite, a rigorous mathematical model of the pressure swing adsorption (PSA) process is optimized to obtain the best capture and compression cost, purity, and recovery. Zeolites that can capture CO2 with at least 90% purity and 90% recovery are ranked by minimum process cost. By applying this approach to post-combustion carbon capture from a coal-fired power plant, thirteen zeolites with significantly lower costs than 13X, the top zeolite currently available for this application, have been identified.
This computational screening method could be applied to other molecular separations, and it is particularly valuable for high impact chemicals that are difficult to separate through traditional means. Identifying novel materials for these applications can give companies a competitive advantage. Industrial separations of primary interest are air separation, ethylene and propylene production, natural gas purification, hydrogen recovery, and xylene separation.
Christodoulos A. Floudas is Stephen C. Macaleer '63 Professor in Engineering and Applied Science and Professor of Chemical and Biological Engineering at Princeton University. Professor Floudas is a world-renowned authority in mathematical modeling and optimization of complex systems at the macroscopic and microscopic level. His research interests lie at the interface of chemical engineering, applied mathematics, and operations research, with principal areas of focus including chemical process synthesis and design, process control and operations, discrete-continuous nonlinear optimization, local and global optimization, and computational chemistry and molecular biology. Among Prof. Floudas¿ numerous honors and awards are Member of National Academy of Engineering (2011), Princeton University Graduate Mentoring Award (2007), AIChE Computing in Chemical Engineering Award (2006) and AIChE Professional Progress Award for Outstanding Progress in Chemical Engineering (2001), to name a few.
Eric L. First is a fourth-year PhD. Student in the Department of Chemical and Biological Engineering and a National Defense Science and Engineering Graduate (NDSEG) Fellow. He graduated from Cornell University with a B.S. in Chemical Engineering and Computer Science. His thesis work at Princeton focuses on developing algorithms to elucidate physical properties of microporous materials, such as zeolites and metal-organic frameworks, by studying the geometry of their underlying crystal structures. His research is driven by the goal of discovering novel material for applications in separations and catalysis.
M.M. Faruque Hasan is a Postdoctoral Research Associate in the Department of Chemical and Biological Engineering. He earned his B.Sc. in Chemical Engineering at Bangladesh University of Engineering and Technology and completed his Ph.D. in Chemical Engineering at the National University of Singapore (NUS). He is interested in a spectrum of technical challenges that overlap process systems engineering and energy research. His research at Princeton is focused on the computer-aided design and optimization of carbon capture and hybrid energy processes.
Chrysanthos E. Gounaris - Chrysanthos' research involves the development of mathematical optimization-based methodologies to address problems in the areas of process systems engineering, process operations, materials science, and computational chemistry. Before joining the Computer-Aided Systems Laboratory as a Post-Doctoral Research Associate, Chrysanthos worked as an Associate at McKinsey & Co. Chrysanthos received his Ph.D. in Chemical Engineering from Princeton University in 2008. His doctoral thesis was entitled "Advances in Global Optimization and the Rational Design of Shape Selective Separations." Chrysanthos also holds a Diploma in Chemical Engineering and an M.Sc. in Process Control, both from the National Technical University of Athens, Greece.
Industrial collaborators are sought for the further development and commercialization of this opportunity.
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