Penn State University has awarded seed funding to 14 interdisciplinary research teams tackling climate and energy challenges, with artificial intelligence playing a central role in nearly half the projects. The Institute of Energy and the Environment (IEE) distributed the 2026 Seed Grant Program awards to more than 40 researchers across 10 colleges and campuses, supporting early-stage work designed to attract larger external funding and accelerate solutions to environmental problems.

The funding represents a strategic bet on combining AI with real-world climate adaptation. Over the past 12 years, the IEE Seed Grant Program has generated a 19-to-1 return on investment, with previous seed-funded projects attracting more than $100 million in external funding from government agencies, nonprofits, and industry. This year's cohort includes projects ranging from using AI to predict harmful algal blooms in the Chesapeake Bay to developing fiber-optic sensors that monitor river flow continuously.

How Are Researchers Using AI to Solve Climate Problems?

• Algal Bloom Prediction: Researchers are using AI to forecast harmful algal blooms in Chesapeake Bay rivers, especially during extreme weather events, to improve early warning systems and emergency response times.
• X-ray Imaging for Energy Systems: A team combining ultrafast X-ray imaging with AI aims to observe rapid phase-change processes inside energy systems that are currently impossible to see directly, potentially improving energy efficiency.
• PFAS Contamination Detection: Two separate projects use AI to understand how harmful PFAS chemicals interact with plants, advancing plant-based cleanup of contaminated soils and water, and developing soft electrodes that allow plants to act as living sensors for environmental contaminants.

What Climate Challenges Are These Projects Addressing?

The 14 projects span multiple environmental domains. Beyond AI-powered applications, the research teams are tackling water management, air quality, mineral recovery, and aviation emissions. One project examines how networks of urban stormwater systems reduce flooding and pollution during extreme storms, while another investigates whether short-term exposure to wildfire smoke combined with high radon levels increases long-term lung cancer risk in affected communities.

A particularly innovative approach involves using distributed acoustic sensing, where fiber-optic cables function as large-scale sensors to continuously measure river flow and improve water monitoring. This technology, called HydroDAS, could revolutionize how scientists track watershed health in real time.

Aviation emissions also feature prominently. Researchers are developing affordable laboratory experiments and models to better understand how airplane exhaust forms contrail clouds and how cleaner fuels might reduce them, addressing a climate impact often overlooked in broader decarbonization discussions.

Why Does Interdisciplinary Collaboration Matter for Climate Research?

The IEE Seed Grant Program deliberately funds teams that span multiple disciplines and career stages. This approach creates mentorship opportunities and knowledge-sharing networks while preparing the next generation of interdisciplinary research leaders. The 14 projects bring together researchers from engineering, earth sciences, agriculture, medicine, and liberal arts, reflecting the reality that climate and energy challenges rarely fit neatly into a single academic silo.

For example, the project on thermal resilience during extreme heat combines engineering expertise in cooling textiles with human physiology knowledge from the College of Health and Human Development. Similarly, research on rare-earth element recovery pairs engineering design with economics and regulatory policy analysis.

The seed funding model also serves a practical purpose: it helps researchers build proof-of-concept results that attract larger grants from federal agencies, foundations, and industry partners. With a 19-to-1 return on investment, the IEE's approach demonstrates that early-stage, high-risk research can generate substantial downstream funding and real-world impact.

Steps to Support Climate-Focused AI Research

• Seek Interdisciplinary Partnerships: Researchers looking to advance climate solutions should actively collaborate across departments and disciplines, combining domain expertise with emerging technologies like AI to address complex environmental problems.
• Build Proof-of-Concept Results: Early-stage projects should focus on generating preliminary data and results that demonstrate feasibility, making it easier to attract larger external funding from government agencies and private foundations.
• Connect with University Research Institutes: Academic institutions often offer seed grant programs designed to fund high-risk, early-stage research; applying for these programs can provide the initial resources needed to launch interdisciplinary climate and energy projects.

These projects represent a shift in how universities approach climate solutions. Rather than treating AI as a standalone technology, researchers are embedding it into domain-specific problems where it can meaningfully improve prediction, monitoring, and decision-making. The next phase will be watching which of these seed-funded ideas attract external funding and scale into operational tools that communities and industries can actually use.