Metallization of Hydrogen-Rich Materials: Predicting Novel Superconductors

NONTECHNICAL SUMMARY This award supports theoretical and computational research and education whose ultimate goal is the rational design via computational modeling of new superconductors, materials through which electric currents can flow without losing energy. Replacing copper wires with superconducting power lines would have a tremendously beneficial impact on the electrical power infrastructure of the USA, but unfortunately all of the superconductors that are technologically useful must be cooled to very low temperatures. Research suggests that hydrogen-rich solids could potentially behave as superconductors at high temperatures and are the focus of this project. Just like diamonds can be synthesized at high pressures deep within the Earth, researchers can use pressure as a variable to create new materials with unusual properties. A number of superconductors have been synthesized in this way. Recent exciting experiments in certain hydrogen- and lanthanum-containing compounds under pressure bring tantalizing promise of room-temperature superconductivity, exhibiting superconductivity onset temperatures of as high as 44 degrees Fahrenheit. These types of experiments are very difficult to carry out, and accurate computational predictions can accelerate new materials discovery. The PI will carry out calculations based upon quantum mechanics to predict promising new targets for synthesis, and will collaborate with leading experimental groups in high-pressure research that will attempt to create these materials. To advance this goal the PI will further develop relevant software that can be used to computationally predict the structure of a solid without any experimental information. The software is freely available to the materials science, physics, and chemistry communities, facilitating the advance of rational materials design as well as of current and future discoveries in science and engineering. Graduate and undergraduate students will be trained in computational materials discovery as part of this project. Aiming to broaden their participation, undergraduate students from underrepresented groups will be trained in computational modelling and materials prediction via personnel exchange, paving the way for future career opportunities in STEM fields. TECHNICAL SUMMARY This award supports theoretical and computational research and education that will lead towards rational design of novel superconductors. The PI will computationally predict the crystal structures of materials with unique stoichiometries and structures that can be synthesized under pressure, and study their electronic structure and properties via first-principles calculations. The phase diagrams under pressure of most binary hydrides have already been explored computationally, and a number of phases with very high superconducting critical temperatures have been predicted, in particular for alkaline and rare-earth polyhydrides. The focus of this project will be on ternary hydrides, whose structures and properties are still unknown. The PI will also study novel hydrides containing expanded metal compounds, which are known to exhibit fascinating quantum behavior. New, perhaps completely unexpected, chemistry and totally new types of materials will be discovered theoretically, and the predictions will be confirmed by leading experimental groups in high-pressure research. The XtalOpt evolutionary algorithm that can be used to predict the structure of an extended system given only its stoichiometry, will be further developed. Key developments will increase the size and complexity of the unit cells that can be predicted without any experimental information, and accelerate the progress of a priori structure prediction for extended systems. The crystallography suite within the highly popular chemical builder, editor, and visualizer Avogadro, will be further advanced. XtalOpt and Avogadro are open-source software, which contributes to the creation of cyberinfrastructure as well as to facilitating current and future discoveries in science and engineering. Graduate and undergraduate students will be trained in rational computational materials design and programming, thereby preparing them for future careers where synergy between theory, computation, and experiment leads to innovation. Collaboration with primarily undergraduate, minority-serving institutions that involves student and faculty exchange will expose students from underrepresented groups to research and future career opportunities in STEM fields and train them in first-principles modelling techniques. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.