NSF invests in designing materials for the future

The U.S. National Science Foundation Designing Materials to Revolutionize and Engineer our Future (NSF DMREF) program is the primary means by which NSF actively contributes to the Materials Genome Initiative (MGI) for Global Competitiveness. Since MGI's inception in 2011, NSF and numerous other federal agencies have worked together through the National Science and Technology Council (NSTC) Subcommittee for MGI to galvanize and support the diverse relevant research communities toward the goal of building a national capability for "deploying advanced materials at least twice as fast as possible today, at a fraction of the cost." Since 2012, the NSF DMREF program has helped the involved research communities nurture and foster the requisite culture shift in materials research, which relies on encouraging and facilitating an integrated team approach that embraces the tools of data science and machine learning.

On this 10th anniversary of MGI, NSF announces a $65.3 million investment in 37 new DMREF awards supported by nine divisions across the NSF directorates for Mathematical and Physical Sciences, Engineering, and Computer and Information Science and Engineering. Among this cohort, 13 awards include Air Force Research Laboratory (AFRL) collaborators through the NSF-Air Force Partnership in Advanced Material Sciences.

"The DMREF program unifies the materials enterprise across NSF and other federal agencies offering a multidisciplinary funding opportunity that enables research teams to harness the power of data and machine learning and train the next generation workforce," notes Linda Sapochak, division director for the NSF Division of Materials Research and subcommittee co-chair for MGI. John Schlueter, DMREF program lead, is "excited by the diversity of this year's cohort and the wide range of research topics that hold significant potential for societal impact." 

Below are the DMREF class of 2021 awards:

• Machine Learning-aided Discovery of Synthesizable, Active and Stable Heterogeneous Catalysts: University of Michigan and Wayne State University.
• Microstructure by Design: Integrating Grain Growth Experiments, Data Analytics, Simulation and Theory: Columbia University, University of Utah, Illinois Institute of Technology and Lehigh University.
• Designing Plasmonic Nanoparticle Assemblies for Active Nanoscale Temperature Control by Exploiting Near- and Far-Field Coupling: University of Washington, Temple University and Rice University.
• Physics-informed Meta-learning for Design of Complex Materials: University of Iowa and AFRL. 
• Grain Interface Functional Design to Create Damage Resistance in Polycrystalline Metallic Materials: University of Wisconsin-Madison, University of New Hampshire, Iowa State University and AFRL.
• Symmetry-Guided Machine Learning for the Discovery of Topological Phononic Materials:  University of California-Santa Barbara, MIT and AFRL.
• Computational Chemistry to Accelerate Development of Long Wave Infrared Polymers:University of Arizona and AFRL.
• GOALI: Salt Separation Membranes Based on Modifiable Two-Dimensional Covalent Organic Frameworks: University of Wyoming and Wyonano LLC.
• Designer 3D Mesoscale Materials Synthesized in the Self-Assembly Foundry:  MIT and University of Chicago. 
• AI-Accelerated Design of Synthesis Routes for Metastable Materials: University of Florida. 
• Accelerated Discovery of Artificial Multiferroics with Enhanced Magnetoelectric Coupling:  Washington University, The University of Texas at Austin and the University of Nebraska.
• Transforming Photonics and Electronics with Digital Alloy Materials: University of Massachusetts-Lowell, University of Virginia, Purdue University, The University of Texas at Austin and AFRL.
• A Computationally-Driven Predictive Framework For Stabilizing Viral Therapies:  University of Massachusetts-Amhurst, Michigan Technological University and Clemson University.
• III-nitride Monolayers and Extreme Quantum Dots: University of Michigan, and AFRL.
• Accelerated Data-Driven Discovery of Ion-Conducting Materials: University of Maryland, Northwestern University and Lehigh University. 
• Design of Stabilized Protein-Polymer Hybrids by Combinatorial Experimentation, Molecular Modeling, and Machine Learning: Rutgers University, Princeton University and AFRL.
• Uncovering Mechanisms of Grain Boundary Migration in Polycrystals for Predictive Simulations of Grain Growth: Carnegie Mellon University and University of Florida.
• Rheostructurally-informed Neural Networks for Geopolymer Material Design: Northeastern University, Georgetown University, University of Delaware and AFRL.
• Design and Optimization of Granular Metamaterials using Artificial Evolution:  Yale University and University of Vermont.
• Materials Architected by Adaptive Processing: Johns Hopkins University, Georgetown University, University of Massachusetts-Lowell and AFRL.
• AI-Guided Accelerated Discovery of Multi-Principal Element Multi-Functional Alloys:  Texas A&M University.
• Switchable Underwater Adhesion through Dynamic Chemistry and Geometry: Virginia Tech., Michigan Tech., University of Colorado and University of California, Berkley. 
• Engineering the On-The-Fly Control of 3-D Printed Block Bottlebrush Assemblies via Dynamic Bonds and Materials Processing: University of Illinois and AFRL.
• Design of Superionic Conductors by Tuning Lattice Dynamics: Duke University, Harvard University, North Carolina State University and Michigan State University.
• Machine Learning Algorithm Prediction and Synthesis of Next Generation Superhard Functional Materials: University of Illinois-Chicago, SUNY-Buffalo and AFRL.
• Developing Damage Resistant Materials for Hydrogen Storage and Large-scale Transport:  SUNY-Stony Brook, MIT and Stanford University.
• Machine Learning Accelerated Design and Discovery of Rare-earth Phosphates as Next Generation Environmental Barrier Coatings: Rensselaer Polytechnic Institute.
• GOALI: Discovering Materials for CO2 Capture in the Presence of Water via Integrated Experiment, Modeling, and Theory: Northwestern University, Numat and University of Southern Alabama.
• Computational Discovery of Polymeric Membranes for Dehydration of Polar Solvents:  Vanderbilt University.
• Quasi-Direct Semiconductors: Arizona State University and The University of Texas at Austin.
• GOALI: Physics-Informed Artificial Intelligence for Parallel Design of Metal Matrix Composites and their Additive Manufacturing: Georgia Tech, Sinter Print, University of Utah and AFRL.
• Creation of Architected Materials with Prescribed Fingerprints via Graph Based Machine Learning and Additive Manufacturing: UCLA and Penn State.  
• GOALI: High-Affinity Supramolecular Peptide Materials for Selective Capture and Recovery of Proteins: Johns Hopkins University, Bristol Myers Squibb, University of Chicago and Northwestern University. 
• Living Biotic-abiotic Materials with Temporally Programmable Actuation:  University of San Diego, University of California-Santa Barbara, Rochester Institute of Technology, Syracuse University and University of Chicago.
• Accelerated Design of Redox-Active Polymers for Metal-Free Batteries: Texas A&M University and University of Chicago.
• Computationally Driven Design of Tissue-Inspired Multifunctional Materials: The University of Texas at Austin, Penn State and University of Tennessee.
• Accelerating Adoption of Sintering-Assisted Additive Manufacturing Using Integrated Experiments, Theory, Simulation and Data Science: San Diego State University, Clemson University and AFRL.