Sandia Labs FY21 LDRD Annual Report
FY21 ANNUAL REPORT
Realizing high temperature superconductivity near ambient conditions in metal hydrides. Sandia is working to realize materials that exhibit superconductivity near ambient conditions. Superconducting materials exhibit zero electrical resistance, a property that would enable low-loss power transmission and revolutionize any electrical technology. Existing superconductors exhibit zero resistance only at very low temperatures, or at high temperatures but very high pressures. These limitations eliminate any benefit of zero resistance, so very few applications of superconductors have been realized. To solve this problem, researchers are developing ways to reduce the pressure required to realize high temperature superconductivity in the metal hydrides. Metal hydrides that contain large amounts of hydrogen, such as LaH 10 , exhibit superconductivity near 270 K, the freezing point of water, at high pressures. The LDRD team sought ways to lower the formation pressure for LaH 10 by modifying the lanthanum metal precursor to accept more hydrogen at lower pressures. Sandia’s superconducting hydride team discovered that ball milling improves the reactivity of lanthanum, likely by promoting damage sites that improve hydrogen absorption. The goal is to reach sufficiently high hydrogen content that will promote superconductivity near room temperature. This project has stimulated collaboration between Lawrence Livermore National Laboratory, Argonne National Laboratory, and academic partners at California State University Northridge. (PI: Peter Sharma)
Developing methods for modeling and making predictions about individual differences in human cognition. Understanding individual cognitive differences is important for maximizing human and human-system performance. To predict how specific individuals will perform or process information, researchers asked, “Can we train a model to make predictions about which people understand which languages?” Language processing was selected because of the well-characterized differences in neural processing that occur when people are presented with linguistic stimuli they either do or do not understand. Sandia researchers and academic partners at the University of Illinois at Urbana-Champaign conducted a series of experiments to collect participants’ behavioral and neural responses to words in many languages. In one experiment, participants viewed words in English and Spanish and were asked to press one button if a word contained five letters or fewer and another button if the word contained six letters or more. Another experiment used electroencephalography (EEG) to record participants’ brain activity while reading words in English, Spanish, French, and German. Researchers used machine learning methods to model the resulting data in both experiments. Both models achieved high accuracy in predicting which participants understood which languages, with the best performance achieved by the EEG-based model. The new methods developed for this project can be applied in several research areas to better understand individual differences in cognitive processing. The project also laid the groundwork to develop new methods for characterizing cognitive performance in applied settings and developing individualized approaches to improving human performance. (PI: Laura Matzen)
These scalp maps show the electrical activity of a monolingual English speaker’s brain from 350-450 milliseconds after reading a word. The EEG shows a different pattern of brain activity in response to pairs of English words than for word pairs in other languages. Modeling this response across many individuals can be used to make predictions about the language proficiency of new participants.
LABORATORY DIRECTED RESEARCH & DEVELOPMENT
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