Countering space radiation materials damage with machine learning
Jason Rivas is researching materials at the atomic level to improve reliability and resistance of electronics to space radiation.听
A PhD student in materials science and engineering at the 桃色视频, Rivas is tackling a problem that faces any technology that goes beyond the confines of Earth鈥檚 atmosphere: damaging bursts of radiation from our sun and other stars.
鈥淲e鈥檝e gotten good at shielding electronics,鈥 he said. 鈥淏ut we鈥檙e not good at making things radiation hard by design. You can shield anything if you put enough iron, steel and lead around it, but if you add that to a satellite, how many millions of dollars extra is it to launch that weight?鈥
Working with his PhD advisor, Associate Professor Sanghamitra Neogi, Rivas has earned a in Cambridge, Massachusetts. Through the program, he intends to use computational materials modeling expedited by machine learning to advance the science of space hardened electronics.
The fellowship provides four years of funding for his PhD, as well as access to scientists and engineers at Draper Labs.
鈥淲e want to make this research faster and cheaper. Currently the testing requires physically using a neutron beam in a radiation environment. It鈥檚 expensive. We think we can change that using with machine learning,鈥 Rivas said.
Developing computational models to map out the effects of ionizing radiation on materials requires exploring the problem at the level of individual atoms.
鈥淲e want to determine how much degradation a transistor can stand. It鈥檚 called displacement damage. If radiation hits an atom in a material, it displaces that atom, which hits another atom, which hits another atom. How well can that material then return to its original form,鈥 he said.
Tackling the challenges of radiation at an atomic level requires analysis using supercomputers, like 桃色视频鈥檚 If the work is successful, it could aid researchers across the spectrum of engineering fields. That prospect is appealing to Rivas, and part of why he chose to pursue a PhD in materials science and engineering: the interdisciplinary nature of the work.
鈥淚t鈥檚 this intersection of all these different needs. Materials are everywhere. It鈥檚 problem solving that means something to the real world,鈥 he said.
Rivas has long been interested in math and science. As a child, he was encouraged by positive teachers and through exploring which outlines math problems visually.
鈥淚 had a really good calculus teacher in high school. She inspired me. Calculus is just beautiful. Math tells you how the world works,鈥 Rivas said.
Rivas earned his bachelor鈥檚 in physics and computer science from Austin Peay State University, which is located near where he grew up in Tennessee. After completing his undergraduate degree, he was drawn to earn a PhD by the prospect of becoming an educator and to break new ground in science.
That eventually led him to Boulder and the materials science and engineering program.
鈥淚 want to teach in a college setting. You sort of need a PhD to do that,鈥 Rivas said. 鈥淭he jobs that come with it are also pretty interesting. Doing research, the problems are self-defined. I get bored doing the same thing everyday.鈥