Graduate Student Seminar
November 17, 2023
12:00 p.m. ET
Scaife Hall 105
November 17, 2023
12:00 p.m. ET
Scaife Hall 105
Precise control over and understanding of point defect concentrations and atomic geometries has become a critically important goal for materials in semiconductor electronics and quantum information applications. In this talk, I will present electronic-structure simulations towards accurate fabrication and characterization by exploiting excited electronic states. Information about atomic geometries and defects is encoded in the electronic and optical properties of a material and I will use recent results for optical spectra of MnF2 to better understand the band gap of this prototypical antiferromagnet. I will also explain the influence of dielectric screening as a factor that can limit the accuracy of such simulations. Using bulk Al2O3 as an example, I will discuss challenges of the standard density functional theory simulation approach when identifying lowest-energy defect geometries that act as starting point for defect diffusion studies. By incorporating light, we envision to facilitate defect diffusion through photo-ionic increases of the defect mobility. Finally, to mitigate the high computational cost of such first-principles techniques, I will discuss benefits of data-intensive machine learning techniques with the goal of expanding towards a much more complex materials space.
Schleife is a Blue Waters Associate Professor in Materials Science and Engineering at the University of Illinois at Urbana-Champaign. He obtained his Diploma and Ph.D. at Friedrich-Schiller-University in Jena. He then was a Postdoctoral Researcher at Lawrence Livermore National Laboratory before starting at Illinois in 2013. He received the NSF CAREER award, the ONR YIP award, and was an ACS PRF doctoral new investigator. André actively organizes national and international schools, workshops, and tutorials to advance the community around cutting-edge first-principles simulations of materials. His research is on efficient, fast, and scalable quantum-mechanical simulations and their applications. He develops and uses predictive computational materials science techniques at the nexus of solid-state physics and modern data-driven approaches to study electronic materials, metals, and defects in materials with quantum information applications.
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12:45 PM ET
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Wean Hall 7500