{"679047":{"#nid":"679047","#data":{"type":"news","title":"Ravikumar Wins Best Paper Award for Next-Generation Computing Memory Research","body":[{"value":"\u003Cp\u003EArtificial intelligence (AI) and machine learning (ML) model parameters have been growing exponentially in the past decade, driving the need for advanced hardware to keep pace with rising demands in energy consumption, speed, and efficiency.\u003C\/p\u003E\u003Cp\u003EFerroelectric field effect transistors (FEFET) have emerged as a promising solution for logic and memory applications in next-generation edge computing, artificial intelligence, and enterprise cloud applications. The non-volatile memory technology harnesses electric polarization to store data in binary, and has been renowned for its speed, density, and ultra-low energy consumption.\u003C\/p\u003E\u003Cp\u003ETheir widespread adoption, however, hinges on addressing critical reliability challenges.\u003C\/p\u003E\u003Cp\u003E\u003Ca href=\u0022https:\/\/ece.gatech.edu\/\u0022\u003EGeorgia Tech School of Electrical and Computer Engineering\u003C\/a\u003E (ECE) third-year Ph.D. candidate Priyankka Ravikumar undertook the challenge of bringing clarity to one major reliability concerns in her paper, \u201cFirst write pulse-induced interface damage in ferroelectric field-effect transistors.\u201d\u003C\/p\u003E\u003Cp\u003EThe research, completed in ECE associated professor \u003Ca href=\u0022https:\/\/ece.gatech.edu\/directory\/asif-islam-khan\u0022\u003EAsif Khan\u2019s\u003C\/a\u003E \u003Ca href=\u0022https:\/\/electrons.ece.gatech.edu\/\u0022\u003Elab\u003C\/a\u003E, recently won the Best Student Paper Award at the 2024 IEEE International Integrated Reliability Workshop.\u003C\/p\u003E\u003Cp\u003EThe research reported on a new phenomenon in FEFET, known as the first switch effect and explains the phenomenon\u2019s origin. The findings reveal that the very first write operation on a FEFET contributes to nearly 50% of the total degradation seen over the device\u0027s lifetime.\u003C\/p\u003E\u003Cp\u003EThe work is an important step towards understanding the fundamental drivers of degradation in FEFETs, laying the groundwork for developing innovative strategies to mitigate degradation, improve device performance, and facilitate the widespread adoption of the technology.\u003C\/p\u003E\u003Cp\u003ERavikumar will be presenting this work at an invited talk next year at the \u003Ca href=\u0022https:\/\/www.irps.org\/\u0022\u003E2025 IEEE International Reliability Physics Symposium\u003C\/a\u003E.\u003C\/p\u003E","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EThe third-year Ph.D. candidate pioneering work on the \u201cfirst switch effect\u201d will help researchers understand the reliability of ferroelectric field effect transistors.\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"The third-year Ph.D. candidate pioneering work on the \u201cfirst switch effect\u201d will help researchers understand the reliability of ferroelectric field effect transistors."}],"uid":"36558","created_gmt":"2024-12-30 18:58:26","changed_gmt":"2024-12-30 18:58:57","author":"zwiniecki3","boilerplate_text":"","field_publication":"","field_article_url":"","location":"Atlanta, GA","dateline":{"date":"2024-12-30T00:00:00-05:00","iso_date":"2024-12-30T00:00:00-05:00","tz":"America\/New_York"},"extras":[],"hg_media":{"675915":{"id":"675915","type":"image","title":"Ravikumar.jpg","body":null,"created":"1735585121","gmt_created":"2024-12-30 18:58:41","changed":"1735585121","gmt_changed":"2024-12-30 18:58:41","alt":"Ravikumar","file":{"fid":"259594","name":"Ravikumar.jpg","image_path":"\/sites\/default\/files\/2024\/12\/30\/Ravikumar.jpg","image_full_path":"http:\/\/hg.gatech.edu\/\/sites\/default\/files\/2024\/12\/30\/Ravikumar.jpg","mime":"image\/jpeg","size":871916,"path_740":"http:\/\/hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/2024\/12\/30\/Ravikumar.jpg?itok=rU9g_Gi8"}}},"media_ids":["675915"],"groups":[{"id":"1255","name":"School of Electrical and Computer Engineering"}],"categories":[{"id":"145","name":"Engineering"}],"keywords":[{"id":"187812","name":"artificial intelligence (AI)"},{"id":"9167","name":"machine learning"},{"id":"191774","name":"Asif Khan ferroelectric field effect transistors"},{"id":"103141","name":"Best Paper Award"}],"core_research_areas":[{"id":"39451","name":"Electronics and Nanotechnology"}],"news_room_topics":[],"event_categories":[],"invited_audience":[],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003EZachary Winiecki\u003C\/p\u003E","format":"limited_html"}],"email":["zwiniecki3@gatech.edu"],"slides":[],"orientation":[],"userdata":""}}}