{"686358":{"#nid":"686358","#data":{"type":"event","title":"PhD Defense by Janhavi Nistane","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003EJanhavi Nistane\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\u0026nbsp;defend\u0026nbsp;a doctoral thesis entitled\u003C\/em\u003E,\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EInformatics-driven sustainable polymer membrane design for solvent separations\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003E\u003Cem\u003EOn\u003C\/em\u003E\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003EMonday, November. 24, 2025\u003C\/p\u003E\u003Cp\u003E11am - 1pm\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003EMRDC Room 3515\u003C\/p\u003E\u003Cp\u003Eor virtually via Teams:\u0026nbsp;\u003Ca href=\u0022https:\/\/teams.microsoft.com\/l\/meetup-join\/19%3ameeting_ZjM4ZWQ1YTAtMTNhMC00ZGQ4LWI5NzEtYzVkMWU3MWEyYTNi%40thread.v2\/0?context=%7b%22Tid%22%3a%22482198bb-ae7b-4b25-8b7a-6d7f32faa083%22%2c%22Oid%22%3a%22ee851d30-ec0e-4bee-a9d0-275c7bf14595%22%7d\u0022\u003ELink\u003C\/a\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003EMeeting ID:\u0026nbsp;248 927 409 443 1\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. Seung Soon Jang- School of Materials Science and Engineering (co-advisor)\u003C\/p\u003E\u003Cp\u003EProf. Ryan Lively- School of Chemical and Biomolecular Engineering\u0026nbsp;\u003C\/p\u003E\u003Cp\u003EProf. Aaron Stebner- School of Mechanical Engineering\u0026nbsp;and Materials Science and 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\u003EAbstract: Separating organic solvents is vital for producing fuels and chemicals. Traditional thermal distillation-based separation methods are highly energy-intensive, whereas polymer membranes can achieve comparable separations using one-tenth of the energy. However, designing such membranes is challenging, requiring a balance of conflicting properties\u2014high permeability, ideal permselectivity, and environmental friendliness. Moreover, membrane discovery is hindered by the lack of benchmarks and the resource-intensive trial-and-error discovery. My research addresses this challenge by introducing an end-to-end machine learning (ML) pipeline for discovering environmentally friendly membranes for solvent separation. Screening criteria are first established, and relevant polymer\u2013solvent machine learning models are trained. A key outcome is the development of multi-task solvent diffusivity models that combine experimental and high-throughput simulation data, enabling robust predictions in unseen chemical spaces and overcoming the limitations of conventional models trained only on experimental data. Focusing on the industrially relevant toluene\u2013heptane separation, these solvent-transport ML models were applied to identify polymers with high permeability and ideal permselectivity. For known polymers, the framework correctly identified polyvinyl chloride (PVC) as a high-performing benchmark, consistent with the literature, validating our approach. The pipeline was then extended to screen hypothetical 7 million chemically recyclable, non-halogenated greener alternatives. Further screening based on recyclability, solubility, and synthetic accessibility narrowed the candidate space. Four polymers were synthesized, and two showed satisfactory performance as PVC replacements in preliminary tests; further testing is currently underway. Another major contribution is the development of an ML pipeline to assess solvent sustainability and identify greener solvent substitutes, accelerating the discovery of green solvents for membrane fabrication. This work guides the discovery of greener polymers for solvent separation and promotes environmentally friendly membrane fabrication.\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EInformatics-driven sustainable polymer membrane design for solvent separations\u003C\/strong\u003E\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"  Informatics-driven sustainable polymer membrane design for solvent separations"}],"uid":"27707","created_gmt":"2025-11-11 17:13:21","changed_gmt":"2025-11-11 17:13:53","author":"Tatianna Richardson","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2025-11-24T11:00:00-05:00","event_time_end":"2025-11-24T13:00:00-05:00","event_time_end_last":"2025-11-24T13:00:00-05:00","gmt_time_start":"2025-11-24 16:00:00","gmt_time_end":"2025-11-24 18:00:00","gmt_time_end_last":"2025-11-24 18:00:00","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":""}}}