[Eoas-seminar] [Seminar-announce] Scientific Computing Colloquium with Bin Ouyang

[eoas-seminar at lists.fsu.edu]

"Navigating the Promises of Compositionally Complex Energy Materials with Data-driven Approaches"

Bin Ouyang
Department of Chemistry & Biochemistry,
Florida State University (FSU)

Please feel free to forward/share this invitation with other groups/disciplines that might be interested in this talk/topic. All are welcome to attend.

NOTE: In-person attendance is requested in our 499 Dirac Science Library (DSL) Seminar Room. Zoom access is intended for external (non-departmental) participants only.

https://fsu.zoom.us/j/94273595552
Meeting # 942 7359 5552

🎦 Colloquium recordings will be made available here, https://www.sc.fsu.edu/colloquium<https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.sc.fsu.edu%2Fcolloquium&data=05%7C02%7Csc-seminar-announce%40lists.fsu.edu%7Cef2882cab3b24dd4645208dd7ab90ce4%7Ca36450ebdb0642a78d1b026719f701e3%7C0%7C0%7C638801657391698004%7CUnknown%7CTWFpbGZsb3d8eyJFbXB0eU1hcGkiOnRydWUsIlYiOiIwLjAuMDAwMCIsIlAiOiJXaW4zMiIsIkFOIjoiTWFpbCIsIldUIjoyfQ%3D%3D%7C0%7C%7C%7C&sdata=jviqhIU8gYYYmghN8HmxFK67qAvfQXSG8nCuZ%2BTHfVw%3D&reserved=0>


Wednesday, Apr 16, 2025, Schedule:

* 3:00 to 3:30 PM Eastern Time (US and Canada)
☕ Nespresso & Teatime - 417 DSL Commons

* 3:30 to 4:30 PM Eastern Time (US and Canada)
🕟 Colloquium - 499 DSL Seminar Room

Abstract:
Compositionally complex materials, represented by high-entropy alloys and ceramics, have primarily been used as structural materials since their initial discovery. Recently, interest in their potential for energy storage and conversion has surged. However, this excitement is often accompanied by confusion, as researchers grapple with the need to complicate material composition beyond vague concepts like the "cocktail effect." This talk aims to clarify some fundamental pictures of compositionally complex energy materials (CCEM), illustrated through case studies on high-entropy battery materials and electrocatalysis. Inspired by the ongoing revolution of AI in science, we will also showcase our recent efforts in developing universally adaptable machine learning models for CCEMs. Our findings suggest that, in many cases, machine learning challenges in CCEM stem more from data limitations rather than the need for sophisticated neural network architectures. A well-designed dataset, enriched with the right domain knowledge, can deliver powerful insights even with simple models.
[cid:2d941088-a354-432f-8fea-3c35613738bf]

Additional colloquium details can be found here,
https://www.sc.fsu.edu/news-and-events/colloquium/1869-colloquium-with-bin-ouyang-2025-04-16<https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.sc.fsu.edu%2Fnews-and-events%2Fcolloquium%2F1869-colloquium-with-bin-ouyang-2025-04-16&data=05%7C02%7Csc-seminar-announce%40lists.fsu.edu%7Cef2882cab3b24dd4645208dd7ab90ce4%7Ca36450ebdb0642a78d1b026719f701e3%7C0%7C0%7C638801657391719865%7CUnknown%7CTWFpbGZsb3d8eyJFbXB0eU1hcGkiOnRydWUsIlYiOiIwLjAuMDAwMCIsIlAiOiJXaW4zMiIsIkFOIjoiTWFpbCIsIldUIjoyfQ%3D%3D%7C0%7C%7C%7C&sdata=XtXWXWbNZZjTvIiIf3EI3N0JbghLtCU8WgAnZ0hlntw%3D&reserved=0>
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