This Project Grant award, totaling $320,117, was provided by the National Science Foundation's (NSF) Engineering program (CFDA 47.041) to the Trustees of the Colorado School of Mines (CSM). The project aims to develop machine learning tools to rapidly predict the attractive forces between desired molecules and candidate adsorbent materials, which will enable the computational screening of vast libraries of adsorbents to identify optimal materials for industrially important separation...
The National Science Foundation Division of Chemical, Bioengineering, Environmental, and Transport Systems awarded a $597,273 Project Grant to the Rector & Visitors of the University of Virginia to develop computational molecular models and theory predicting the dynamics of agglomeration and redispersion of metals supported by zeolites. This project, funded under the NSF Engineering program (CFDA 47.041), will provide guidance on engineering deactivation resistant zeolites used widely in the...
This National Science Foundation (NSF) Project Grant under the Engineering program (CFDA 47.041) supports a $337,663 research project at the University of Oklahoma from August 1, 2024 to July 31, 2027. The project aims to develop a revolutionary approach to synthesizing materials and chemicals under high-pressure conditions using porous materials. It proposes leveraging the high pressures observed within adsorbed fluid or solid films on solid substrates as an alternative to traditional,...
This National Science Foundation Project Grant of $408,234 will fund research at the University of Notre Dame to develop predictive models for gas adsorption in porous materials. Under the Engineering (47.041) program, the principal investigator will implement and validate an active learning framework to navigate adsorption landscapes using molecular modeling and machine learning. By representing absorbent and gaseous properties as features, the models aim to efficiently predict adsorption...
This $425,000 Project Grant award from the National Science Foundation (NSF) Engineering program (CFDA 47.041) will fund a collaborative research project between Johns Hopkins University in the U.S. and École Polytechnique Fédérale de Lausanne in Switzerland. The goal is to develop a new type of zeolite membrane capable of efficiently separating complex gas mixtures, which could significantly reduce the energy demands and costs of chemical production processes. The researchers will synthesize...
This Project Grant from the National Science Foundation's Division of Chemical, Bioengineering, Environmental, and Transport Systems supports $422,695 in research at the University of Virginia from January 1, 2023 through December 31, 2025. The award aims to characterize and predict changes in catalytic active sites in metal-containing zeolites under dynamic reaction conditions through the Engineering program (CFDA 47.041). Specifically, the university will develop methodologies to quantify...
The National Science Foundation (NSF) awarded a $638,566 Project Grant under the Engineering program (CFDA 47.041) to the University of Delaware. The grant supports a collaborative research effort to develop a computational-experimental methodology using machine learning to design stable, active, and selective single-atom catalysts for industrial applications. The project aims to uncover physics-inspired descriptors to predict how the support material properties influence the stability,...
The National Science Foundation awarded a $431,091 Project Grant to the University of Massachusetts under the Engineering federal grant program (CFDA 47.041) to develop computational tools for rational design of nanoporous catalysts for carbonylation reactions. The award period is from September 1, 2022 through August 31, 2027. The project aims to discover effective porous solid-acid catalysts as a technologically and environmentally appealing alternative to rare metal catalysts and corrosive...
This Project Grant award from the National Science Foundation (NSF) Integrative Activities program (CFDA 47.083) provides $300,000 to the University of Alaska Fairbanks (UAF) to collaborate with NASA Ames Research Center on developing new porous sorbents for low-pressure carbon dioxide (CO2) capture. The goal is to engineer defects in metal-organic frameworks (MOFs) to increase their CO2 adsorption capacity at low pressures, which will enable more effective CO2 capture and storage...
The National Science Foundation (NSF) awarded a $291,349 Project Grant to the University of Alabama under the Engineering program (CFDA 47.041) to develop and apply advanced machine learning force fields to simulate nanoparticle catalysts under realistic reaction conditions. The goal is to elucidate the catalytic active sites and how nanoparticle shapes evolve during catalytic processes. This research will help enable more sustainable chemical manufacturing by improving the computational...