Condensed Matter and Materials Theory — U.S. National Science Foundation funding opportunity
U.S. National Science Foundation · Federal agency

Condensed Matter and Materials Theory

CMMT supports theoretical and computational materials research in the topical areas represented in DMR's other Topical Materials Research Programs (these are also variously known as Individual Investigator Award (IIA) Pr...

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Deadline Fixed Location Alabama Type grant Level Federal Open posted Jun 6, 2025
✦ AI Summary
  • Who can apply: Federal-level applicants (see eligibility for details).
  • Funding amount: total funding pool ~$15,000,000.
  • Issued by: U.S. National Science Foundation.
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The “key facts” mode pulls structured fields directly from the official source posting (amount, deadline, eligibility tags). The AI mode adds a short plain-English narrative on top, generated from the same source. Always verify with the agency before applying.

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Deadline
Fixed
Total pool
$15M

About this opportunity

CMMT supports theoretical and computational materials research in the topical areas represented in DMR's other Topical Materials Research Programs (these are also variously known as Individual Investigator Award (IIA) Programs, or Core Programs, or Disciplinary Programs), which are: Condensed Matter Physics (CMP), Biomaterials (BMAT), Ceramics (CER), Electronic and Photonic Materials (EPM), Metals and Metallic Nanostructures (MMN), Polymers (POL), and Solid State and Materials Chemistry (SSMC). The CMMT program supports fundamental research that advances conceptual understanding of hard and soft materials, and materials-related phenomena; the development of associated data-centric techniques; and 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 CMMT. Research may encompass the advance of new paradigms in materials research, including emerging data-centric approaches utilizing data-analytics or machine learning. Computational efforts span from the level of workstations to advanced and high-performance scientific computing. Emphasis is on approaches that begin at the smallest appropriate length scale, such as mesoscale, required to yield fundamental insight into material behavior, to predict new materials and states of matter, and to reveal new materials phenomena. Approaches that span multiple scales of length and time may be required to advance fundamental understanding of materials properties and phenomena, particularly for polymeric materials and soft matter. 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 research at the interfaces of materials with biological systems. CMMT encourages potentially transformative submissions at the frontiers of data-intensive materials research, which includes but is not limited to: i) advancing the understanding of emergent properties and phenomena of materials and condensed matter systems, ii) developing materials-specific prediction and advancing understanding of emergent states of matter associated with either hard or soft materials, iii) developing and exploring new paradigms including computational and data-enabled approaches to advance fundamental understanding of materials and materials related phenomena, iv) fostering research at interfaces among subdisciplines represented in the Division of Materials Research, v) harnessing machine learning or developing explainable machine learning to advance understanding of materials and materials-related phenomena, or vi) 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. Research involving significant materials research cyberinfrastructure development, for example, software development with an aim to share software with the broader materials community, should be submitted to CMMT through Computational and Data-Enabled Science and Engineering (CDS&E) in accordance with its submission instructions for DMR. Additional Information Eligibility rules apply for submissions; please see Section II.

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Geographic eligibility

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  • District of Columbia

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Citation details

Source systemgrants.gov
Source ID359626
PostedJun 6, 2025

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