The Condensed Matter and Materials Theory Program supports theoretical and computational materials research in the topical areas represented by other Materials Research Programs, which include:Condensed Matter PhysicsBio...
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DeadlineFixedLocationAlabamaTypegrantLevelFederalOpenposted Aug 19, 2026
✦ AI Summary
Who can apply: Federal-level applicants (see eligibility for details).
Issued by: National Science Foundation.
About: The Condensed Matter and Materials Theory Program supports theoretical and computational materials research in the topical areas represented by other Materials Research Programs, which include:Condensed Matter…
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Who can apply — at a glance
Eligible applicants:
see the Eligibility tab for the criteria from the official announcement.
Where:
Alabama, Alaska, Arizona, Arkansas, California, Colorado, Connecticut, Delaware, Florida, Georgia, Hawaii, Idaho, Illinois, Indiana, Iowa, Kansas, Kentucky, Louisiana, Maine, Maryland, Massachusetts, Michigan, Minnesota, Mississippi, Missouri, Montana, Nebraska, Nevada, New Hampshire, New Jersey, New Mexico, New York, North Carolina, North Dakota, Ohio, Oklahoma, Oregon, Pennsylvania, Rhode Island, South Carolina, South Dakota, Tennessee, Texas, Utah, Vermont, Virginia, Washington, West Virginia, Wisconsin, Wyoming, District of Columbia.
Award:
amount not specified by the source.
Matching funds:
not required.
Deadline type: Fixed.
Compiled from the official listing's structured fields — always verify with the funder before applying.
The Condensed Matter and Materials Theory Program supports theoretical and computational materials research in the topical areas represented by other Materials Research Programs, which include:Condensed Matter PhysicsBiomaterialsCeramicsElectronic and Photonic MaterialsMetals and Metallic NanostructuresPolymersSolid State and Materials Chemistry.The program supports foundational research that includes but is not limited to:Advancements to our conceptual understanding of hard and soft materials along with materials-related phenomena.The development of associated data-centric techniques.Predictive materials-specific modeling for materials research.First-principles electronic structure.Quantum many-body and field theories.Statistical mechanics.Classical and quantum Monte Carlo and molecular dynamics are among the methods used in the broad spectrum of research supported in the program. Research may encompass advancing new paradigms in materials research, including emerging data-centric approaches using data analytics or machine learning. Computational efforts may span from the workstation level to advanced and high-performance scientific computing.The program emphasizes approaches that begin at the smallest appropriate length scale, such as mesoscale, required to yield foundational insight into material behavior, to predict new materials and states of matter, and to reveal new materials phenomena. Advancing fundamental understanding of materials properties and phenomena, particularly for polymeric materials and soft matter, may require approaches that span multiple length and time scales.Areas of recent interest include, but are not limited to: strongly correlated electron systems; topological phases; low-dimensional materials and systems; quantum and classical nonequilibrium phenomena, the latter including pattern formation, materials growth, microstructure the jamming transition; gels; glasses; disordered materials, hard and soft; defects; high-temperature superconductivity; creation and manipulation of coherent quantum states; nanostructured materials and mesoscale phenomena; sustainable materials; polymeric materials and soft condensed matter; active matter and related collective behavior; biologically inspired materials; and foundational research at the interfaces of materials with biological systems.The program encourages potentially transformative proposals at the frontiers of data-intensive materials research, which include but are not limited to:Advancing the understanding of emergent properties and phenomena of materials and condensed matter systems.Developing materials-specific prediction and advancing understanding of emergent states of matter associated with either hard or soft materials.Developing and exploring new paradigms including computational and data-enabled approaches to advance foundational understanding of materials and materials-related phenomena.Fostering research at interfaces among subdisciplines in materials research.Harnessing machine learning or developing explainable machine learning to advance understanding of materials and materials-related phenomena.Developing new theoretical frameworks in areas of materials research, such as active matter, nonequilibrium materials or matter, the synthesis of solid-state materials, or reformulating quantum many-body theory for conceptual insight or greater tractability.
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Who can apply
The Condensed Matter and Materials Theory Program supports theoretical and computational materials research in the topical areas represented by other Materials Research Programs, which include:Condensed Matter PhysicsBiomaterialsCeramicsElectronic and Photonic MaterialsMetals and Metallic NanostructuresPolymersSolid State and Materials Chemistry.The program supports foundational research that includes but is not limited to:Advancements to our conceptual understanding of hard and soft materials along with materials-related phenomena.The development of associated data-centric techniques.Predictive materials-specific modeling for materials research.First-principles electronic structure.Quantum many-body and field theories.Statistical mechanics.Classical and quantum Monte Carlo and molecular dynamics are among the methods used in the broad spectrum of research supported in the program. Research may encompass advancing new paradigms in materials research, including emerging data-centric approaches using data analytics or machine learning. Computational efforts may span from the workstation level to advanced and high-performance scientific computing.The program emphasizes approaches that begin at the smallest appropriate length scale, such as mesoscale, required to yield foundational insight into material behavior, to predict new materials and states o
Geographic eligibility
Alabama
Alaska
Arizona
Arkansas
California
Colorado
Connecticut
Delaware
Florida
Georgia
Hawaii
Idaho
Illinois
Indiana
Iowa
Kansas
Kentucky
Louisiana
Maine
Maryland
Massachusetts
Michigan
Minnesota
Mississippi
Missouri
Montana
Nebraska
Nevada
New Hampshire
New Jersey
New Mexico
New York
North Carolina
North Dakota
Ohio
Oklahoma
Oregon
Pennsylvania
Rhode Island
South Carolina
South Dakota
Tennessee
Texas
Utah
Vermont
Virginia
Washington
West Virginia
Wisconsin
Wyoming
District of Columbia
How to apply
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