research in energy and the environment
The Andlinger Center for Energy and the Environment is a nexus at Princeton University for research that spans the technology-policy spectrum and aims to address today’s global energy and environmental challenges to ensure a sustainable future. Through a variety of programs, including grants and fellowships, the center supports collaborative, interdisciplinary research and sustains a community of scholars focused on developing technologies and solutions that will pave the way for a world less reliant on fossil fuels.
research areas
Research at the Andlinger Center is advancing fundamental and applied sciences in several critical areas related to energy systems, infrastructure, and practices that can help mitigate human impacts on climate and the environment. These include developing renewable energy and energy storage technologies, optimizing energy systems transitions and process systems efficiencies, investigating novel approaches for sustainable manufacturing in various sectors, applying behavioral and decision sciences for environmental policy and technology adoption, solving critical problems at the water-energy nexus and developing resilient infrastructure in the face of a changing climate.
A constellation of six interacting research areas forms the heart of the center’s focus: Built Environment, Transportation, and Infrastructure; Electricity Production, Transmission, and Storage; Fuels and Chemicals; Environmental Sensing and Remediation; Decision and Behavioral Science, Policy, and Economics; and Environmental and Climate Science.
quick links
featured research news
- Read Andlinger Center’s Monthly Newsletter
- Engineers use moisture to pull carbon dioxide out of the air
- Andlinger Center supports research to separate critical minerals for the energy transition
- Engineers use AI to wrangle fusion power for the grid
- Flexible geothermal power approach combines clean energy with a built-in ‘battery’
- Buyer beware: Most clean power purchasing strategies do little to cut emissions
- Leveraging language models for fusion energy research