We discover, design, and characterize
the advanced materials humanity needs.
At UC San Diego, we leverage our cross-disciplinary expertise to discover, design, and characterize advanced materials needed to address global societal challenges. Our materials work is relevant for developing zero- and low-carbon energy and transportation systems; cost-effective healthcare advances; solutions for natural-resource sustainability; and next-generation information technologies.
This work is grounded in our ability to control materials at the level of atoms and electrons.
Equally important, we are world-leaders in characterizing the structure and function of materials at the nanoscale level using a suite of cutting-edge analytical and theoretical tools, many of which we have developed here at UC San Diego.
Learn more on the "About" page.
Download the IMDD brochure.
About
At the UC San Diego Institute for Materials Discovery and Design (IMDD)
we discover, design, and characterize the advanced materials humanity needs.
Learn more about IMDD here.
In July 2020, we celebrated our first big IMDD win: we landed an $18 million NSR MRSEC grant.
Recent News
IMDD Seminar: The Innovation Ecosystem at UC San Diego
January 25, 2021
Paul Roben, Associate Vice Chancellor for Innovation and Commercialization at UC San Diego, will provide information on how the Office for Innovation and Commercialization can help you translate your reserach from the lab to the marketplace on Friday, February 5. Full Story
IMDD Seminar: Introduction and Materials for Quantum Communication
January 19, 2021
Dr. Bhagawan Sahu from the Department of Chemistry & Biochemistry at UC San Diego will give an IMDD Seminar presentation titled 'Introduction and Materials for Quantum Communication on January 28 at 10 am. Full Story
New Method Makes Better Predictions of Material Properties Using Low Quality Data
January 14, 2021
By combining large amounts of low-fidelity data with smaller quantities of high-fidelity data, nanoengineers at UC San Diego have developed a machine learning method to more accurately predict the properties of new materials including, for the first time, disordered materials. Full Story