This National Science Foundation (NSF) Engineering program grant, awarded to Trustees of the Colorado School of Mines (Colorado School of Mines) under CFDA 47.041, provides $386,077 to support a project to develop molecular imprinting atomic layer deposition techniques for creating microporous silica structures near active sites in mesoporous aluminosilicate catalysts. The goal is to induce confinement effects to enhance catalytic activity and selectivity for C-C coupling reactions, particularly...
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...
The National Science Foundation (NSF) Division of Chemistry (CHE) and Division of Chemical, Bioengineering, Environmental and Transport Systems (CBET) have awarded a $250,000 Project Grant to the Colorado School of Mines under the NSF's Mathematical and Physical Sciences (CFDA 47.049) program. This grant, with a period of performance from April 1, 2025 to March 31, 2027, aims to produce sustainable liquid fuels using CO2 as a starting material. The project will develop and demonstrate an...
The National Science Foundation Division of Chemical, Bioengineering, Environmental, and Transport Systems awarded $323,986 to the Trustees of the Colorado School of Mines under Project Grant CFDA 47.041, the Engineering program, to support the research project "Understanding the Interaction of 2D Particles with Phospholipid Membranes" from September 1, 2021 through August 31, 2024. This project aims to improve understanding of how two-dimensional particles interact with phospholipid...
This $311,985 Project Grant award from the National Science Foundation's Engineering (CFDA 47.041) program supports research on the scalable manufacturing of large-area thin films of metal-organic frameworks (MOFs) for separation applications. The University of Illinois, as the prime awardee, is using a combination of in-situ experimentation, modeling, and separation measurements to develop fundamental manufacturing knowledge on MOF thin film formation through scalable coating techniques like...
This $578,793 federal Project Grant award from the National Science Foundation's Engineering program (CFDA 47.041) aims to revolutionize chemical synthesis and composite material discovery through an innovative physics-informed machine learning approach. The primary objective is to develop an autonomous chemical synthesis framework that integrates first-principles modeling, machine learning, and process optimization to enhance the quality and efficiency of synthesizing perovskite oxides, which...
This National Science Foundation (NSF) Engineering program (CFDA 47.041) Project Grant award provides $300,000 in funding to the Colorado School of Mines to conduct collaborative research on the relationship between the structure of two-dimensional particle films at fluid-fluid interfaces and mass transport across those films. The research aims to understand how the organization and heterogeneity of sheet-like particles on liquid surfaces impact the movement of molecules between different...
The National Science Foundation (NSF) Division of Chemistry awarded a $449,440 Project Grant to Colorado State University for the purpose of "DESIGNING CHEMICAL PROCESSES WITH MULTICOMPONENT SOLVENTS THROUGH SELF-EVOLVING SOLUBILITY DATABASES AND NEURAL NETWORKS". This award is funded through the NSF's Mathematical and Physical Sciences program (CFDA 47.049). Under this grant, the research team led by Dr. Seonah Kim will develop innovative machine learning (ML) models for predicting...
This National Science Foundation (NSF) Project Grant award, funded through the Mathematical and Physical Sciences program (CFDA 47.049), provides $424,350 to Duquesne University from September 1, 2023 to August 31, 2026. The project aims to design and discover energy-efficient, environmentally friendly, and cost-effective metal-free catalysts for the activation and conversion of small molecules, such as converting carbon dioxide to useful chemicals and fuels. The research approach combines...