The world can be mapped in a variety of ways, from physical representations to the genetics of the nearby organisms. It makes sense that National Renewable Energy Laboratory (NREL) Scientist Kandler Smith would use these ideas in his research given that he enjoys the outdoors and is an active hiker, mountain biker, and mountain biker. Smith oversees NREL’s computational modeling of batteries for electrochemical energy storage, where he creates maps and models to deepen our comprehension of batteries.
One little way I can contribute to the preservation of the natural world is by working in renewable energy, Smith remarked. I like the challenge of hastening the development of secure, dependable, and effective batteries for grid and transportation decarbonization.
A FUTURE MODEL FOR BETTER BATTERIES Although Smith has spent 15 years at NREL, electrochemical energy storage has not always been his area of expertise. Smith is a specialist in predicting and increasing the lifetime of lithium-ion batteries. Prior to focusing on renewable energy, Smith began his career in mechanical engineering, developing jet engines for military projects. He joined NREL after receiving a Ph.D. in mechanical engineering from Pennsylvania State University.
Smith stated, “I used to be interested in creating machinery, like helicopters. However, my interest in energy and later electrochemistry was inspired by the study of thermodynamics and heat transport. I started creating computer models instead of engines to create better batteries for a sustainable future.
Smith’s concern for the environment is a perfect fit for NREL, which is tucked away in the pleasant foothills of Colorado. Smith has worked at NREL on a number of battery model development projects, including the ambitious Computer-Aided Engineering of Batteries (CAEBAT) project. Numerous engineers throughout the world now use software programs developed with the help of the CAEBAT project to better understand how battery electrochemical physics interacts with the complexity of large-scale systems. Smith recently received the distinction of “Distinguished Member of Research Staff” from NREL in honor of his outstanding contributions to battery lifespan modeling, prediction, optimization, and design.
BATTERY DATA GENOME MAPPING The foundations of a decarbonized future, electrified transportation and a quickly changing power grid, depend on energy storage. The achievement of energy targets depends on an open exchange of battery data. Smith is leading a developing partnership between NREL and business partners to develop a robust battery genome to standardize data formats and encourage open sharing of data and software within the battery community as part of this initiative. This project would aid future initiatives to accelerate battery research and development using machine learning and artificial intelligence.
According to Smith, computational modeling enables researchers to automate and speed up invention. Where battery mechanics are not fully understood or the size of the data set is too enormous for humans to handle, physics-informed artificial intelligence fills in the gaps. Together, we can hasten the pace of cutting-edge testing and boost the adoption of fresh, environmentally friendly technology.
Research on all energy storage projects will go more quickly if the battery genome is better understood. Smith doesn’t directly work on the discovery of novel battery materials, but his modeling work facilitates quick scale-up for next-generation discoveries by offering a rough assessment of how a battery might function with new materials. The battery genome research would also examine batteries as an entire system, from manufacture to health forecasting, improving all-encompassing energy storage technologies.
Find out more about the sustainable transportation and energy storage research at NREL.
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courtesy of the U.S. Department of Energys (DOEs) National Renewable Energy Laboratory (NREL) for the article.
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