Project Grant 2414050
Award Date
3/1/25
Completion Date
2/29/28
Dollars Obligated
$280K
Federal Agency
Division of Civil, Mechanical, and Manufacturing Innovation
Federal Grant Program
47.041
Assistance Type
Project Grant
Place of Performance
Pittsburgh, PA 15260, USA
Similar Awards
This National Science Foundation (NSF) Project Grant award under the Engineering program (CFDA 47.041) provides $269,542 to Rutgers, The State University in New Brunswick, NJ to develop a combined numerical-experimental approach to model the synthesis of large populations of advanced materials at the nanoscale. The key products include: (1) in-situ environmental transmission electron microscopy measurements of metal oxide nanoparticle formation, evolution, and catalytic activation; (2) automated...
This $450,000 Project Grant award from the National Science Foundation (NSF) Engineering program (CFDA 47.041) aims to understand and control the interfacial dynamics governing the formation of discrete tiles of nanoparticle assemblies on functionalized fluid interfaces. The research combines experimental and computational methods to investigate and manipulate the thermodynamic and kinetic factors influencing nanoparticle assembly at fluid interfaces. The goal is to achieve precise control...
This National Science Foundation (NSF) Project Grant award under the Engineering (CFDA 47.041) program totaling $165,437 is funding research to visualize and characterize the motion and interaction of individual nanoparticles near surfaces. The awardee, Georgia Tech Research Corporation, will develop a workflow combining nanoscale microscopy with data-driven modeling to study how nanoparticles move and interact in heterogeneous environments, with applications in areas such as nanomedicine,...
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...
The $148,060 Project Grant from the National Science Foundation's Division of Civil, Mechanical, and Manufacturing Innovation under the Engineering program (CFDA 47.041) will fund research at Carnegie Mellon University investigating machine learning approaches to support engineering designers in digital manufacturing. The university will mine part designs from open online repositories and curated datasets developed through in-class challenges. A machine learning pipeline will extract design...
This $154,577 federal Project Grant award from the National Science Foundation's (NSF) Engineering program (CFDA 47.041) supports research at Duke University to develop machine learning models for predicting protein-nanoparticle interactions. The research aims to characterize the protein "corona" that forms on nanoparticle surfaces and utilize machine learning to forecast how nanoparticle properties influence protein adsorption. This work will advance the understanding of nano-bio...
The National Science Foundation awarded a $526,334 Project Grant to the University of Pittsburgh through the Engineering program (CFDA 47.041) to support research titled "CAREER: UNRAVELING FUNDAMENTAL MECHANISMS GOVERNING GRAIN REFINEMENT IN COMPLEX CONCENTRATED ALLOYS MADE BY ADDITIVE MANUFACTURING TOWARDS STRONG AND DUCTILE STRUCTURES." The five-year award, effective April 15, 2021 through March 31, 2026, will fund research investigating fundamental mechanisms governing...
This National Science Foundation (NSF) Project Grant award under the Mathematical and Physical Sciences (MPS) program provides $306,369 in funding to the University of Delaware to conduct computational modeling and education research on the multiscale simulation of nanofluid assembly for the design of smart materials. The research aims to gain a fundamental understanding of how microscale self-assembly processes in particle-stabilized multiphase fluids can be used to control the mesoscale...
This National Science Foundation (NSF) Project Grant award for $362,000 under the NSF Engineering program (CFDA 47.041) supports research by The Johns Hopkins University to develop models for predicting and controlling the behavior of colloidal particle assemblies on curved surfaces. The key objectives are to: 1) obtain high-dimensional particle scale dynamic simulations to match experiments, 2) develop coarse-grained models for stochastic microstructure evolution and topological defect...
This $371,708 Project Grant awarded by the National Science Foundation (NSF) under the Engineering program (CFDA 47.041) supports fundamental research at Cornell University to develop heuristic rules for enhancing the stability and kinetic accessibility of nanoparticle superlattices. The research aims to formulate and test molecular-simulation based heuristics to predict the correlation between nanoparticle interactions and their self-assembly into target superlattice structures, including for...