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Computational and Data driven Materials Research (CDMR)

Status: Archived

Archived funding opportunity

This document has been archived.

Important information about NSF’s implementation of the revised 2 CFR

NSF Financial Assistance awards (grants and cooperative agreements) made on or after October 1, 2024, will be subject to the applicable set of award conditions, dated October 1, 2024, available on the NSF website. These terms and conditions are consistent with the revised guidance specified in the OMB Guidance for Federal Financial Assistance published in the Federal Register on April 22, 2024.

Important information for proposers

All proposals must be submitted in accordance with the requirements specified in this funding opportunity and in the NSF Proposal & Award Policies & Procedures Guide (PAPPG) that is in effect for the relevant due date to which the proposal is being submitted. It is the responsibility of the proposer to ensure that the proposal meets these requirements. Submitting a proposal prior to a specified deadline does not negate this requirement.

Synopsis

The Division of Materials Research recognizes the scientific opportunities enabled by advances in theory and computation and the application of data-enabled and data-centric approaches in conjunction with experimental activities to advance materials research. This program supports materials research driven by computation, data, or theory. Areas of interest include but are not limited to new materials design and preparation, structure development, evolution and control, nanoscale materials, multi-scale properties and optimization in all the topical, disciplinary, and interdisciplinary areas represented in DMR programs. Research and education activities supported in this program are distinct from those supported in other programs in DMR by approach: successful projects may be more simulations and less algorithm development and theory than in CMMT and may also incorporate experiments and/or a heavy emphasis on data mining. Supported projects will advance fundamental understanding of materials or materials-related phenomena through transformative research in which a computational, data-centric, or theoretical activity drives a well-integrated experimental activity or vice versa. Successful projects may involve the creation of software or databases validated by associated synthesis or experiments to address imperfect or incomplete theoretical understanding or computational intractability to forge innovative methods to advance the frontiers of materials research. Projects that explore the combination of dedicated computation or data-centric activities with innovative instrumentation leading to transformative tools to advance materials research will also be considered. Of particular interest are projects that create new paradigms for materials research through the innovative use of digital data in ways that complement or dramatically enhance traditional computational, experimental, and theoretical methods to discover new materials or new materials-related phenomena, and advance the fundamental understanding of materials more generally. This program will also support efforts to develop materials research knowledge portals that integrate experimental data with data of simulation or theoretical origin with the aim to organize, enhance, and make broadly accessible the digital products of materials research.

Program contacts

Program Director:  Dr. Diana Farkas
Name Email Phone Organization
Diana Farkas
dfarkas@nsf.gov (703) 292-2335
Daryl Hess
dhess@nsf.gov 703-292-4942

Awards made through this program

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Map of recent awards made through this program