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UID:31b49c40-183c-4dac-9e5e-1da415800c7c@nexttoyou
DTSTAMP:20261106T174023Z
DTSTART:20261119T194500Z
DTEND:20261119T204500Z
SUMMARY:MSE Seminar - Siamak Farhad
LOCATION:Institute for Advanced Materials & Manufacturing 147\, 2641 Ospre
 y Vista Way\, Knoxville\, TN 37996
DESCRIPTION:“Physics-Guided and AI-Assisted Sustainable Manufacturing: Fro
 m Experimental Discovery to Process Scale-Up”\n\nAbstract: Sustainable ma
 nufacturing is increasingly shaped by advances in AI\, computational mode
 ling\, experimental methods\, and process automation. Integrating these c
 apabilities provides new opportunities to improve material utilization\, 
 energy efficiency\, process performance\, and resource recovery. In parti
 cular\, physics-guided and AI-assisted approaches can combine fundamental
  scientific understanding with experimental data to accelerate materials 
 discovery\, identify relationships among processing parameters and materi
 al behavior\, and support process optimization and scale-up. This seminar
  will provide an overview of ongoing research in the Sustainable Manufact
 uring\, Advanced Recycling\, and Energy Technologies (SMART) Laboratory\,
  including AI-enabled manufacturing\, polymer processing\, manufacturing 
 energy optimization\, and advanced materials recycling.\n\nThe seminar wi
 ll then examine how physics-guided and AI-assisted methods can be integra
 ted with experimental research to address complex materials-processing ch
 allenges. Using direct recycling of lithium-ion battery cathode manufactu
 ring scrap as a case study\, the presentation will discuss the developmen
 t of a framework combining systematic experimental investigation\, fundam
 ental understanding of material interactions\, data-driven analysis\, and
  interpretable predictive modeling. Particular emphasis will be placed on
  \n\nhttp://next-to-u.app/events/31b49c40-183c-4dac-9e5e-1da415800c7c
URL:http://next-to-u.app/events/31b49c40-183c-4dac-9e5e-1da415800c7c
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