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Xue, Yexiang

Publications and source records attributed to Xue, Yexiang.

3 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

In situ study on heavy ion irradiation induced microstructure evolution in single crystal Cu with nanovoids at elevated temperature

Understanding the response of nanovoids to irradiation damage advances our capability to design radiation tolerant materials. Recent in situ studies reveal the shrinkage of hexagon-shaped nanovoids in (110) textured Cu. However, the evolution of voids with irregular geometries under irradiation is less well understood. Here, in situ Kr ion irradiation was performed at 100 °C on single-crystal Cu (112) that possesses nanovoids with high aspect ratio. In situ studies show these elongated voids fragment into smaller voids and shrink gradually with increasing dose. Phase field simulations confirm that fragmentation of the void is governed by the competing kinetics between atoms diffusing toward and away from the elongated nanovoid. In conclusion, cost irradiation analysis reveals the formation of high-density defect clusters.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2018

Phase Mapper: Accelerating Materials Discovery with AI

From the stone age, to the bronze, iron age, and modern silicon age, the discovery and characterization of new materials has always been instrumental to humanity's progress and development. With the current pressing need to address sustainability challenges and find alternatives to fossil fuels, we look for solutions in the development of new materials that will allow for renewable energy. To discover materials with the required properties, materials scientists can perform high-throughput materials discovery, which includes rapid synthesis and characterization via X-ray diffraction (XRD) of thousands of materials. A central problem in materials discovery, the phase map identification problem, involves the determination of the crystal structure of materials from materials composition and structural characterization data. This analysis is traditionally performed mainly by hand, which can take days for a single material system. In this work we present Phase-Mapper, a solution platform that tightly integrates XRD experimentation, AI problem solving, and human intelligence for interpreting XRD patterns and inferring the crystal structures of the underlying materials. Phase-Mapper is compatible with any spectral demixing algorithm, including our novel solver, AgileFD, which is based on convolutive non-negative matrix factorization. AgileFD allows materials scientists to rapidly interpret XRD patterns, and incorporates constraints to capture prior knowledge about the physics of the materials as well as human feedback. With our system, materials scientists have been able to interpret previously unsolvable systems of XRD data at the Department of Energy’s Joint Center for Artificial Photosynthesis, including the Nb-Mn-V oxide system, which led to the discovery of new solar light absorbers and is provided as an illustrative example of AI-enabled high throughput materials discovery

Computer Science↗