{"683043":{"#nid":"683043","#data":{"type":"event","title":"PhD Proposal by Xueyu Hu","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003EXueyu Hu\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EAdvisor: Prof. Meilin Liu (MSE) and Prof. Xiaoming Huo (ISyE)\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u003Cem\u003Ewill propose a doctoral thesis entitled,\u003C\/em\u003E\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EAccelerated Discovery of Oxygen Electrodes for Protonic Solid Oxide Cells via Data-driven\u003C\/strong\u003E \u003Cstrong\u003EApproach\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003E\u003Cem\u003EOn\u003C\/em\u003E\u003C\/p\u003E\u003Cp\u003EFriday, July 25 at 11:30 a.m.\u003C\/p\u003E\u003Cp\u003ELOVE Room 183\u003C\/p\u003E\u003Cp\u003EOr\u003C\/p\u003E\u003Cp\u003EVirtually via Zoom Link\u003C\/p\u003E\u003Cp\u003E\u003Ca href=\u0022https:\/\/gatech.zoom.us\/j\/97575653573?pwd=cvzVrlmh4f9qjduZERmeKYEiOb93Y0.1\u0022\u003Ehttps:\/\/gatech.zoom.us\/j\/97575653573?pwd=cvzVrlmh4f9qjduZERmeKYEiOb93Y0.1\u003C\/a\u003E\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ECommittee\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp; Prof. Xiaoming Huo\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp; Prof. Angus P. Wilkinson\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp; Prof. Hamid Garmestani\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp; Prof. Matthew T. McDowell\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp; Prof. Preet Singh\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EAbstract\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EProtonic solid oxide cells (P-SOCs) offer high-efficient power generation and green hydrogen production, fostering a sustainable cycle of chemical-electrical energy conversion and paving the way toward a zero-emission future. However, the commercialization of P-SOCs is hindered by the absence of oxygen electrode materials that combine high electrocatalytic activity with long-term durability. To accelerate the discovery of such material \u2013 capable of operating under real-world conditions \u2013 including high humidity, exposed to contaminants, and reduced activity at lower temperatures \u2013 we conducted high-throughput density functional theory (DFT) calculations to systematically evaluate key descriptors relevant to oxygen electrode performance. These include the energy above hull (\u003Cem\u003EE\u003C\/em\u003Ehull), vacancy formation energy (\u003Cem\u003EE\u003C\/em\u003Ev), \u003Cem\u003Ep-\u003C\/em\u003Eband center, \u003Cem\u003Ed-\u003C\/em\u003Eband center, \u003Cem\u003Ed-\u003C\/em\u003E\u00ad\u003Cem\u003Ep\u003C\/em\u003E hybridization, and oxygen non-stoichiometry (\u03b4), enabling rapid screening of candidate materials.\u003C\/p\u003E\u003Cp\u003EBuilding upon this foundation, we developed a supervised learning model to identify the dominant physical descriptors governing performance and to ensure transferability across diverse chemistries. These computational insights were integrated into an active learning-guided experimental loop, where the learned descriptors served as inputs to predict polarization resistance (\u003Cem\u003ER\u003C\/em\u003Ep) \u2013 a critical multiphysics property indicative of electrocatalytic activity. By maximizing the expected information gain, the active learning framework strategically guided standardized experiments toward the most informative candidates. This approach enabled direct \u003Cem\u003ER\u003C\/em\u003Ep prediction, and further analysis revealed that \u003Cem\u003Ed-p\u00ad\u003C\/em\u003E hybridization and calcination resistance are key factors driving performance. Through large-scale screening of 6,940,032 compositions, we identified top-performing oxygen electrodes materials that achieved a peak power density of 2.68 W cm-2 at 600\u0026nbsp;\u00b0C exceeding benchmark materials by 35% and demonstrated stable operation for over 500 hours in a P-SOC configuration.\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003E\u003Cstrong\u003EAccelerated Discovery of Oxygen Electrodes for Protonic Solid Oxide Cells via Data-driven\u003C\/strong\u003E \u003Cstrong\u003EApproach\u003C\/strong\u003E\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"Accelerated Discovery of Oxygen Electrodes for Protonic Solid Oxide Cells via Data-driven Approach"}],"uid":"27707","created_gmt":"2025-07-08 16:53:39","changed_gmt":"2025-07-08 16:54:25","author":"Tatianna Richardson","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2025-07-25T11:30:00-04:00","event_time_end":"2025-07-25T13:30:00-04:00","event_time_end_last":"2025-07-25T13:30:00-04:00","gmt_time_start":"2025-07-25 15:30:00","gmt_time_end":"2025-07-25 17:30:00","gmt_time_end_last":"2025-07-25 17:30:00","rrule":null,"timezone":"America\/New_York"},"location":"LOVE Room 183 Or Virtually via Zoom Link","extras":[],"groups":[{"id":"221981","name":"Graduate Studies"}],"categories":[],"keywords":[{"id":"102851","name":"Phd proposal"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1788","name":"Other\/Miscellaneous"}],"invited_audience":[{"id":"78771","name":"Public"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}}}