{"688038":{"#nid":"688038","#data":{"type":"event","title":"PhD Defense by  Shivank Shukla","body":[{"value":"\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EShivank Shukla\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003EAdvisor: Prof. Rampi Ramprasad\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u003Cem\u003Ewill defend a doctoral thesis entitled,\u003C\/em\u003E\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EADVANCED POLYMER DESIGN FOR EXTREME ENVIRONMENTS:\u0026nbsp;\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EHIGH-ENERGY DENSITY CAPACITORS AND AI-DRIVEN PROPERTY OPTIMIZATION\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u003Cem\u003EOn\u003C\/em\u003E\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003ETuesday, Feb. 17, 2026\u003C\/p\u003E\u003Cp\u003E11: 30 am - 1:30 pm\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003EMRDC Room 3515\u003C\/p\u003E\u003Cp\u003Eor virtually via Teams:\u003C\/p\u003E\u003Cp\u003E\u003Ca href=\u0022https:\/\/teams.microsoft.com\/l\/meetup-join\/19%3ameeting_Y2E5YzJmNDItZDY1Zi00Y2U4LTkyY2QtMjJiOWRjYmFhM2Fi%40thread.v2\/0?context=%7b%22Tid%22%3a%22482198bb-ae7b-4b25-8b7a-6d7f32faa083%22%2c%22Oid%22%3a%22201ed8c1-9680-448e-ac11-1fb2468b01c8%22%7d\u0022 title=\u0022https:\/\/teams.microsoft.com\/l\/meetup-join\/19%3ameeting_Y2E5YzJmNDItZDY1Zi00Y2U4LTkyY2QtMjJiOWRjYmFhM2Fi%40thread.v2\/0?context=%7b%22Tid%22%3a%22482198bb-ae7b-4b25-8b7a-6d7f32faa083%22%2c%22Oid%22%3a%22201ed8c1-9680-448e-ac11-1fb2468b01c8%22%7d\u0022\u003ETeams link\u003C\/a\u003E\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ECommittee:\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EProf. Rampi Ramprasad- School of Materials Science and Engineering (advisor)\u003C\/p\u003E\u003Cp\u003EProf. Naresh Thadani- School of Materials Science and Engineering (co-advisor)\u003C\/p\u003E\u003Cp\u003EProf. Chaitanya Deo- School of Materials Science and Engineering\u003C\/p\u003E\u003Cp\u003EProf. Roshan Joseph- School of Industrial and Systems Engineering\u003C\/p\u003E\u003Cp\u003EProf. Guoxiang (Emma) Hu- School of Materials Science and Engineering\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003EDesigning functional polymers for targeted applications remains a highly complex and non-trivial challenge due to the vastness of chemical design space and the strong coupling between molecular structure and macroscopic properties. This challenge is further amplified when engineering polymers for extreme operating conditions, where few or no existing materials satisfy performance requirements. This thesis addresses one such regime: polymer dielectric membranes for high-energy-density capacitors operating at elevated temperatures, where most commercially available polymer dielectrics exhibit a pronounced decline in energy density.\u003C\/p\u003E\u003Cp\u003EIn this work, a comprehensive and scalable polymer design framework is developed that integrates data-driven modeling, machine learning, synthesis aware polymer generation, and high-throughput molecular simulations, followed by experimental validation. The proposed pipeline enables the rapid exploration and screening of millions of chemically feasible polymer candidates, reducing the materials discovery timeline from years to months. Machine learning models are trained across multiple polymer classes to enable fast and accurate prediction of dielectric and thermomechanical properties. In parallel, a robust molecular dynamics\u2013based simulation protocol is established to predict the glass transition temperature of polymers, serving both as a validation tool and as a secondary data source to augment model training.\u003C\/p\u003E\u003Cp\u003ECollectively, this integrated approach demonstrates an efficient pathway for the discovery and design of polymer dielectrics with improved high-temperature performance and establishes a generalizable framework for polymer materials design under extreme operating conditions.\u003Cbr\u003E\u003Cbr\u003E\u0026nbsp;\u003C\/p\u003E","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003E\u003Cstrong\u003EADVANCED POLYMER DESIGN FOR EXTREME ENVIRONMENTS:\u0026nbsp;\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EHIGH-ENERGY DENSITY CAPACITORS AND AI-DRIVEN PROPERTY OPTIMIZATION\u003C\/strong\u003E\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"ADVANCED POLYMER DESIGN FOR EXTREME ENVIRONMENTS:  HIGH-ENERGY DENSITY CAPACITORS AND AI-DRIVEN PROPERTY OPTIMIZATION"}],"uid":"27707","created_gmt":"2026-02-05 13:51:43","changed_gmt":"2026-02-05 13:52:18","author":"Tatianna Richardson","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2026-02-17T11:30:00-05:00","event_time_end":"2026-02-17T13:30:00-05:00","event_time_end_last":"2026-02-17T13:30:00-05:00","gmt_time_start":"2026-02-17 16:30:00","gmt_time_end":"2026-02-17 18:30:00","gmt_time_end_last":"2026-02-17 18:30:00","rrule":null,"timezone":"America\/New_York"},"location":"MRDC Room 3515","extras":[],"groups":[{"id":"221981","name":"Graduate Studies"}],"categories":[],"keywords":[{"id":"100811","name":"Phd Defense"}],"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":""}}}