Method for Cost Effective Molecular Separations and Process Optimization for Carbon Dioxide/Methane Separation

Web Published:

10/18/2013

Description:

Method for Cost Effective Molecular Separations and Process Optimization for Carbon Dioxide/Methane Separation

Docket # 14-2975

Researchers in the Department of Chemical and Biological Engineering, Princeton University, have developed a multi-scale computational screening approach for identifying promising materials from databases for the purification of natural gas. 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, CO₂/methane separation (including natural gas, shale gas, coal bed methane, EOR gas, biogas and landfill gas). Proof of concept has been demonstrated identifying novel materials for cost-effective processing of natural gas with various CO₂ contents from 5 to 50%. Using the proposed methods, methane is obtained with at most 2-3% CO₂ suitable for pipeline transport.

Applications:

· Cost- effective CO₂/Methane separation

· Applicable over a wide range of feed compositions, pressures, temperatures and flow rates

· Suitable to other processes in addition to PSA (pressure swing adsorption).

Advantages:

· Fully optimized process to combine selection of material with process needs and outcomes

· Results in separations with low cost, high purity and recovery.

Advantages:

· Fully optimized process to combine selection of material with process needs and outcomes

· Results in separations with low cost, high purity and recovery.

Advantages:

· 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

Our computational screening approach starts with ZEOMICS, a three-dimensional pore characterization method, which is applied to each zeolite in a microporous materials database (other databases, such as those for metal-organic frameworks, could also be used). We rank the zeolites based on our novel metrics of shape selectivity and size selectivity, and we calculate adsorption selectivity for the top structures. For each high-performing zeolite, we optimize a rigorous mathematical model of the pressure swing adsorption (PSA) process to obtain the best separation and compression cost, purity, and recovery. Novel zeolites have been identified that are not only feasible (meaning that the purity of the methane product is at least 97% and at least 95% of the methane is recovered) but also cost effective for most feed conditions.

Alternatively our 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, carbon capture, hydrogen recovery, and xylene separation.

Inventors:

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

Eric is a fifth-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

Faruque 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.

Intellectual Property and Technology Status:

Patent pending

Industrial collaborators are sought for the further development and commercialization of this opportunity.

Contacts:

Laurie Tzodikov

Princeton University Office of Technology Licensing • (609) 258-7256• tzodikov@princeton.edu