ChemE researchers are developing the materials, devices, and systems necessary for meeting pressing energy challenges like climate change and rapidly increasing demand. As such, our work is vital in the transition to a decarbonized economy. Our faculty have a long track record of excellence in electrochemical systems, and are driving innovation in photovoltaics, batteries, fuel cells, and electronic polymers.
Image: An array of photoluminescence predictions of a perovskite solar cell, based on a machine learning algorithm that learned on a set of atomic force microscopy data. Created by Wesley Beckner for the 2016 Science & Engineering as Art Competition
- Fuel cells
- Electronic polymers
- Electrochemical systems
- Energy systems integration
Clean Energy Institute
CEI supports the advancement of next-generation solar energy and battery materials and devices. The institute offers a graduate fellows program and the Clean Energy Bridge to Research REU, among other training opportunities.
Washington Clean Energy Testbeds
The Testbeds are a 15,000 square foot laboratory and collaborative workspace that enables start-ups and established businesses open access to state-of-the art R&D facilities. The Testbeds provide access to the instrumentation, training, and expertise necessary to scale next-generation clean energy devices and systems.
DIRECT: Data Intensive Research Enabling Clean Technologies
A training program of ChemE and the Clean Energy Institute for UW graduate students interested in data-enabled discovery and design of materials for clean energy
Undergraduates can compete in the American Institute of Chemical Engineers' annual Chem-E-Car Competition. Students design and construct a car powered by a chemical energy source, that will safely carry a specified load over a given distance and stop.
Lilo Pozzo led a collaborative effort to bring low cost and resilient energy systems to health clinics and residents in rural Puerto Rico in the aftermath of Hurricane Maria
With a grant from the DOE's Solar Energy Technologies Office, the Hillhouse Group is using advanced machine-learning algorithms to generate a predictive model of degradation for perovskite solar cells
For an award-winning senior capstone design project, a group of undergraduates developed ElectroSolar Oxygen: a solar-powered electrolyzer cell that produces medical-grade oxygen