FUNDING RESOURCES
Advances in artificial intelligence and data-driven methods are rapidly transforming materials research, from autonomous experimentation and computational design to advanced manufacturing. This resource is designed to help researchers identify funding opportunities relevant to AI for Materials Research. These opportunities span internal funding mechanisms, individual or multi-PI programs, center-level competitions, and broader federal investments in AI, computation, and materials innovation.
Individual or Multi-PI Programs
NSF-CBET-Process Systems, Reaction Engineering, and Molecular Thermodynamics
Supports process modeling, design, control, and optimization theory and algorithms. High-priority areas include smart manufacturing, computational tools (including quantum computing methods), real-time optimization of large-scale chemical systems, and machine learning for process intensification.
Submission Window: Anytime
NSF-CMMI-Advanced Manufacturing
Includes cybermanufacturing systems, materials processing, nanomanufacturing, and cross-domain work that uses AI, robotics, or data-driven methodologies to advance manufacturing. Encourages interdisciplinary proposals incorporating computational tools and intelligent systems.
Submission Window: Anytime
NSF-CMMI-Engineering Design and Systems Engineering (EDSE)
Supports research in design science and systems science, including AI in design, robotics and intelligent system design, engineered materials systems, optimization, immersive design, and extreme-scale systems.
Submission Window: Anytime
NSF-DMR-Topical Materials Research Programs (TMRP)
Supports data-intensive materials research, including materials research driven by AI and machine learning within specific material classes (Metals, Ceramics, Polymers, Electronic/Photonic Materials).
Submission Window: Anytime (Suggested: Avoid Apr 15–Jun 15)
NSF-DMR-Condensed Matter and Materials Theory (CMMT)
Harnessing machine learning or developing explainable ML to advance understanding of materials and materials-related phenomena.
Submission Window: Anytime
NSF-CISE-Cyber-Physical Systems (CPS)
Supports hybrid intelligent systems combining computation with physical processes—relevant to autonomous labs, robotics-enhanced experimentation, and AI-driven materials systems.
Submission Window: Anytime (for Small & Medium proposals)
NSF-CISE-Cyberinfrastructure for Sustained Scientific Innovation (CSSI)
Funds small groups creating robust cyberinfrastructure services supporting data-driven and computationally intensive areas of science and engineering, including AI workflows.
Submission Window: December 1, 2026 (Annual)
NSF-Cross-Directorate (MPS/ENG/CISE)-Designing Materials to Revolutionize and Engineer our Future (DMREF)
Accelerates materials discovery using machine learning, data science, closed-loop workflows, and MGI-aligned autonomous research frameworks.
Submission Window: January 21, 2025 – February 4, 2025 (Every 2 years)
DOD-ONR-Computer-Aided Materials Design
Supports the “Computer-Aided Materials Design” portfolio. Focuses on inverse design methodologies: defining extreme environmental constraints (corrosion, high heat, blast) and utilizing AI to identify or design materials capable of surviving these conditions.
Submission Window: Anytime (Long Range BAA)
DOD-ONR-Machine Learning, Reasoning and Intelligence
Supports fundamental research in machine learning and artificial intelligence. Focuses on robust, explainable AI approaches that function effectively with sparse data, highly relevant for pure algorithmic development applied to materials science problems.
Submission Window: Anytime (Long Range BAA)
DOD-DARPA-AI for Plasma & Materials (DSO)
Focuses on AI for plasma state measurement, physics-based modeling, and materials for high-power propulsion. Includes research into rapid qualification tools, self-learning models for complex physical systems, and interpretable AI for physics.
Submission Window: Anytime (Submit Executive Summary to DSO Office-wide BAA)
DOE-BES-Computational Chemical Sciences (CCS)
Supports the development of open-source codes and algorithms for predictive chemistry and materials modeling. Focuses on creating the computational tools (e.g., hybrid DFT-ML workflows) rather than just the application of existing tools.
Submission Window: Annual (Typically Q1/Q2)
DOE-Fusion Energy Sciences (FES)-AI/ML for Fusion Energy
Supports AI/ML platforms for fusion energy materials, specifically for structural materials and plasma-facing components. Focuses on predicting material degradation and utilizing real-time control systems to prevent material damage in extreme environments.
Submission Window: Annual (Usually September/October)
NSF–Industrial Innovation and Partnerships (IIP)-SBIR / STTR Fast-Track Pilot Programs
Supports large, multi-institutional centers integrating synthesis, characterization, and theory. Prioritizes “co-design” frameworks where AI experts and experimentalists collaborate deeply to solve mission-critical clean energy challenges (storage, catalysis, quantum).
Submission Window: Anticipated 2026 (Every 4 years)
Broader Funding Opportunities
DOE-CET-Frontiers in AI for Science, Security and Technology (FASST) – DOE-GENESIS Mission
Funds the development of large-scale foundation models for scientific discovery. Key Initiative: The “Genesis Mission,” which focuses specifically on deploying autonomous laboratories and AI-driven workflows for advanced nuclear, grid, and energy materials discovery.
Submission Window: Not yet released (Expected 2026)
DOE-FES-Fusion Science and Technology (FS&T) Roadmap
Outlines the strategic vision for “Closing the Fusion Materials Gap.” Supports broader initiatives for AI-driven discovery and qualification of fusion materials (structural, plasma-facing components, and blankets) and integrated engineering designs for pilot plants.
Submission Window: Varies by specific solicitation (Strategic Roadmap)
DOE-BES-Energy Frontier Research Centers (EFRC)
Supports large, multi-institutional centers integrating synthesis, characterization, and theory. Prioritizes “co-design” frameworks where AI experts and experimentalists collaborate deeply to solve mission-critical clean energy challenges (storage, catalysis, quantum).
Submission Window: Currently open
UW–Madison Internal
UW-Madison Igniting Interdisciplinary Innovation
Supports bold, cross-disciplinary research teams at UW–Madison working on high-impact problems across areas such as AI, materials, health, energy, environment, and societal resilience. Provides seed funding (up to $250k) and structured cohort support to help teams launch transformative research directions with strong potential for major external funding.
Submission Window: April 1, 2026 (Incubation session attendance required in Jan-Feb)
GIE-WIN-AIM Seed
Supports early-stage, collaborative research at the intersection of AI and materials science within the WIN-AIM community. A limited number of seed awards will be offered to catalyze new partnerships and pilot studies that can grow into competitive external proposals.
Details: Full program scope and application information will be introduced at the WIN-AIM Connect and Create Workshop on Jan. 13. 2026.
Submission Window: To be announced