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The DOE Carbon Management funding opportunity (DE-FOA-0002614) supports research and development of advanced tools and capabilities for carbon capture, utilization, and storage (CCUS) including substantial AI/ML-enabled topic areas.
Funded scope includes AI/ML-accelerated discovery of carbon capture sorbents and materials, machine learning for direct air capture process optimization, AI-driven monitoring of geologic storage and leak detection, digital twins for CO2 pipeline networks, ML-based emissions accounting and verification, and AI for techno-economic and life-cycle analysis of negative emissions technologies.
The opportunity aligns with U.S. climate commitments and supports the Bipartisan Infrastructure Law and Inflation Reduction Act carbon management investments. Strong fit for AI/ML teams partnered with carbon capture, materials science, geosciences, and chemical engineering researchers, including national laboratories, universities, startups, and energy industry partners.
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Or search similar grants →According to the current listing, eligibility includes: Domestic entities including universities, nonprofits, national laboratories, state and local governments, and for-profit organizations. International partners allowed under DOE standard terms. Cost share required for industry applicants per DOE policy. Confirm the full requirements in the official notice before applying.
The current listing shows individual awards range from $400,000 to $5,000,000, with a total program funding of up to $54.4 million across multiple topic areas. Verify award ceilings, matching requirements, and allowable costs in the official notice.
Applications for DOE Carbon Management DE-FOA-0002614 for AI and Machine Learning in Carbon Capture and Storage are due October 1, 2026. Build your timeline backwards from this date to cover registrations, approvals, and final submission checks.
DOE Carbon Management DE-FOA-0002614 for AI and Machine Learning in Carbon Capture and Storage is funded by U.S. Department of Energy (Office of Fossil Energy and Carbon Management). Verify program details on the funder's official page before applying.
Start from the official opportunity page linked in this listing — it carries the sponsor's submission instructions.
The NEH Humanities Research Centers on Artificial Intelligence program funds the creation of university-based humanities research centers focused on the ethical, legal, and societal implications of artificial intelligence. Funded centers undertake interdisciplinary humanities-led research that brings ethics, law, history, philosophy, anthropology, religious studies, literature, linguistics, and cultural studies to bear on questions raised by AI systems. Topics include responsible AI governance frameworks, AI and civil rights, AI and labor, cultural impact of generative AI, AI and creative authorship, philosophical foundations of machine reasoning, history of AI thought, and humanistic evaluation of AI safety and alignment. Centers are expected to convene researchers, train new humanities scholars in AI, host public-facing programming, and produce publications and translational tools that inform policy and public understanding. Strong fit for universities seeking to launch sustained interdisciplinary AI humanities research programs in partnership with computer science and other STEM departments.
SaTC 2.0 is NSF's flagship cybersecurity, privacy, and trust research program reorganized to address emerging threats including generative AI security, open-source software security, quantum computing security, and supply chain security. Funded scope covers the bidirectional role of AI as both a cybersecurity threat (adversarial attacks on AI systems, AI-enabled cyberattacks, data poisoning) and a defensive tool (AI for intrusion detection, automated vulnerability discovery, secure-by-design AI). The program supports interdisciplinary collaboration across computer science, mathematics, social and behavioral sciences, and STEM education to build trust in global cyber ecosystems.
NSF SaTC 2.0 (Security Privacy and Trust in Cyberspace) is the largest open solicitation for university-led cybersecurity research in the federal portfolio now expanded with AI security as an explicit priority area. The 2.0 reboot added generative AI security open-source software security quantum computing security and supply chain security as topics of interest addressing the bidirectional role of AI as both a cybersecurity threat and a defensive tool. Research awards support adversarial machine learning and attacks on AI systems AI weaponization against people information and systems privacy-preserving machine learning and responsible AI use for detecting and responding to cyber threats. The program funds three award types: Research awards up to $1.2M for four years Education awards up to $500K for three years and Seedling awards up to $300K for two years through Dear Colleague Letters. Proposals are accepted on a recurring annual basis with two windows per year. This is distinct from NSF CyberAICorps which focuses on scholarship and workforce development and from NSF AIMing which focuses on AI formal methods and mathematical reasoning.
On August 24, 2026, DOE and SBA signed a memorandum of agreement creating the Small Business Investment Company-Energy Initiative, pointing a $58 billion SBA-leveraged investment program at DOE's technology priorities. No application, no NOFO, no deadline. Here is how SBIC capital actually works, why a January 2026 rule change made this possible, and what a company sitting on a DOE Phase II award should do about it.
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