Todd J. Martinez
Stanford University
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Primary Section: 14, Chemistry Secondary Section: 13, Physics Membership Type:
Member
(elected 2019)
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Biosketch
Todd Martínez is a theoretical chemist recognized for his work on light-induced and mechanically-induced chemistry, computational reaction discovery, and development of new algorithms to solve the Schrodinger equation for both electrons and nuclei. Martínez was born in Amityville, New York and grew up in Central America and the Caribbean. He received his B. S. in Chemistry from Calvin College in 1989 and his Ph.D. in Chemistry from the University of California at Los Angeles in 1994. From 1994 to 1996, he was a Fulbright Junior Postdoctoral Researcher at Hebrew University in Jerusalem and a University of California President’s Postdoctoral Fellow at UCLA. In 1996, he joined the faculty in the Department of Chemistry at the University of Illinois. He rose through the ranks to become the Gutgsell Chair in Chemistry. In 2009, he joined the faculty at Stanford University and SLAC National Accelerator Laboratory, where he is currently David Mulvane Ehrsam and Edward Curtis Franklin Professor.
Research Interests
Professor Martínez’ research lies in the area of theoretical chemistry, emphasizing the development and application of new methods which accurately and efficiently capture quantum mechanical effects of both electrons and nuclei. He developed the ab initio multiple spawning (AIMS) method to describe chemical reaction dynamics on multiple electronic states, simultaneously solving the electronic Schrodinger equation to obtain potential energy surfaces and couplings. AIMS describes bond rearrangement, electronic excitation, and electron/proton transfer seamlessly, without preconceptions. His applications of AIMS to photoisomerization revealed the role of multiple coordinates, charge transfer, and conical intersections and revised the textbook picture of this fundamental photochemical reaction. Femtosecond time-resolved photoelectron spectra for isomerization processes predicted by Martínez in 2011 were subsequently measured in 2015, with nearly quantitative agreement. Motivated by the computational difficulties of modeling large molecules and/or complex environments with ab initio methods, Martínez developed new electronic structure algorithms that focused on the strengths of graphical processing units (GPUs) and led to as much as three orders of magnitude improvement in computational efficiency. He also developed the tensor hypercontraction (THC) formalism that exposes hidden structure in operators and electronic wavefunctions. Exploiting this factorization reduces the scaling of all correlated methods, while maintaining arbitrary accuracy.
