SBIR/STTR Research Award

Accessible Open-Source Software Framework for Multi-Scale Modeling

Award identifier b0b17881ca745741e294cb2dedaffa0b788a4bf6faf4903ffb534f3da3395b36Awarding agency Department of Energy

Award amount

$196,024

Program and phase

SBIR · Phase I

Award year

2022

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Award details

Awarding agency
Department of Energy
Branch
Not reported
Recipient company
EXABYTE INC.
Proposal award date
2022-02-14
Contract end date
2022-11-13
UEI
F5GSDMC5N3C3
Solicitation number
Not reported
Topic code
C53-14a

Research abstract

As new multi-modal nanoscale capabilities accelerated the discovery of new fundamental concepts and phenomena in materials science across multiple length and time scales, there is a significant amount of complex multidimensional new data being generated as these tools are developed. This increasingly complex data requires new comprehensive digital approaches combining AI/ML and physics-based modeling to analyze multi-dimensional correlations and enable new scientific discoveries as well as improved capabilities for autonomous experiments. Exabyte.io proposes to develop a new capability in our current open-source, cross-platform software framework to bridge digital approaches across multiple lengths and timescales for selected materials systems. We deploy scalable, python-based workflows that employ first-principles and/or atomistic-MD simulation packages that scale well on DOE supercomputers (e.g., VASP, Quantum Espresso, GROMACS, etc.) and provide atomistic calculations of 2d or 3d structural models to develop data-driven AI/ML models. Our approach enables an accessible (‘black box’) usage pattern so that the codes are easily accessible even with a rudimentary understanding of the different methods underlying the software. We will build an open-source, python-based workflow design engine to make it accessible to the community at large. We will focus on NWChem(Ex) and LAMMPS because of their ability to study vdW and molecular solids, as well as heterostructures formed from - a major unique addition to our existing platform. Our aim is to focus on the workflow engine as the key component and reuse other parts of our existing infrastructure to demonstrate the proof-of-concept. The integration of this open-source multi-scale modeling with our platform improves the accessibility, speed, and efficiency of materials research and development (R&D) and enables the development of new kinds of products in industrial sectors. Computational materials design drives the transformation of industrial materials R&D and will become a multi-billion market by 2025.

Technology keywords

Not reported

Other awards by this recipient

Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.

Awards with the same topic code

Verified by an exact topic code match. This is not a text-similarity match.

Research funding history

8 SBIR/STTR records share this UEI (2020–2024). Reported award amounts total $3,889,819. Reported amounts are not federal obligations.

Phases: Phase I, Phase II – Direct to Phase II, Phase II

Agencies: Department of Defense, Department of Energy, Department of Commerce

Agency intelligence

Department of Energy

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