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DTSTAMP:20260413T101909
DTSTART;TZID=America/Detroit:20260416T113000
DTEND;TZID=America/Detroit:20260416T123000
SUMMARY:Workshop / Seminar:ChE SEMINAR: Carl Laird\, Carnegie Mellon University
DESCRIPTION:Systems\, Surrogates\, Solutions: Optimization and Machine Learning for Decision-Making at Scale\n\nEmerging global challenges are pushing the limits of today's scientific computing tools. To overcome these barriers\, our group develops open-source solutions for large-scale optimization problems. At the intersection of data science and mathematical programming\, new capabilities support optimization-based decision-making with embedded machine-learning and data-driven models. Leveraging high-level languages like Python\, we are democratizing these capabilities\, placing powerful tools in the hands of a broader research community. Two vignettes illustrate the effectiveness of these capabilities to tackle challenging science and engineering problems at scale.\n   The first vignette highlights our rapid-response work during COVID-19. The pandemic exposed significant challenges in mitigating emerging infectious diseases. I will discuss our work to efficiently estimate county-level transmission parameter dynamics using a fully-coupled\, national-scale model. With full spatio-temporal transmission parameter profiles\, we were able to estimate the impact of non-pharmaceutical interventions on the spread of COVID-19. Our current work focuses on developing accessible\, advanced optimization capabilities that enable inference on very large-scale\, nonlinear dynamic systems.\n   Machine learning (ML) models are increasingly used as surrogates for complex processes within engineering. Here\, I will discuss the need for surrogates in large-scale decision-making and introduce the Optimization and Machine Learning Toolkit (OMLT)\, a Python framework developed in collaboration with Imperial College London and Sandia National Laboratories. This package supports solution of mathematical programming problems with embedded ML models. I will showcase several applications that illustrate the use of machine learning surrogates\, including for example\, process design and operations\, bioprocess modeling\, and process family design.\n\nCarl D. Laird\nJohn E. Swearingen Professor and Department Head\n\nProf. Carl Laird is the John E. Swearingen Professor and Department\n			   Head in the Chemical Engineering Department at Carnegie Mellon University. His international reputation centers on pioneering high-performance computing strategies for large-scale nonlinear and discrete optimization problems\, parallel scientific computing strategies\, and the development of open-source optimization capabilities\, including both modeling and solvers. He has worked in several application areas\, including process and energy systems\, product manufacturing\, biopharmaceutical processes\, homeland security\, and large-scale infectious disease spread. He is the recipient of several research awards\, including the Steven J. Fenves Award for Systems Research\, Carnegie Mellon College of Engineering\, the INFORMS Computing Society Prize\, CAST Division Outstanding Young Researcher Award\, National Science Foundation Faculty Early Development (CAREER) Award\, and the prestigious Wilkinson Prize for Numerical Software for his work on IPOPT\, a software library for solving nonlinear\, nonconvex\, large-scale continuous optimization problems.
UID:143399-21892981@events.umich.edu
URL:https://events.umich.edu/event/143399
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:chemical engineering,Chemistry
LOCATION:North Campus Research Complex Building 10 - B10 Auditorium
CONTACT:
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DTSTAMP:20260414T140036
DTSTART;TZID=America/Detroit:20260423T113000
DTEND;TZID=America/Detroit:20260423T123000
SUMMARY:Workshop / Seminar:ChE SEMINAR: Bryan McCloskey\, University of California\, Berkeley
DESCRIPTION:Abstract:\nConventional Li-ion battery electrolytes have been designed to optimize numerous desirable properties\, including interfacial and thermal stability\, conductivity\, and low flammability. However\, all conventional liquid Li + -bearing electrolytes still possess low Li + transference (t + ) numbers\, where current passed through them is primarily carried by the counteranion\, resulting in large concentration gradients that limit battery performance\, particularly at high discharge and charging rates.\n\nThe development of high t + electrolytes—those in which most (or all) current is carried by the Li + ion—could enable safer battery cycling\, faster charging rates\, and thicker\, more energy-dense cathode designs in Li-ion batteries. This presentation will outline our attempts to develop high t + electrolytes using two strategies. In the first\, Li-neutralized polyanions are used as a salt in nonaqueous liquid electrolytes (so-called nonaqueous polyelectrolyte solutions). In this configuration\, Li ions\, when appropriately solvated\, have hydrodynamic radii much smaller than the polymer chain’s size\, ostensibly allowing them to diffuse or migrate faster than their appended counteranions\, and hence enable high t + electrolytes. Ultimately\, I show this picture to be oversimplified\, and that anion-anion and cation-anion correlations severely limit the t + of high conductivity polyelectrolyte solutions. In the second\, we suspend Li-ion conducting inorganic particles\, which have both high conductivity and unity Li + transference numbers\, in organic electrolytes.\n\nThe development of these organic-inorganic composite electrolytes could enable solid state batteries\, an important emerging energy storage technology that has been hindered by the poor processability of thin-film pure inorganic ion conductors. Although the composite electrolyte field is highly active due to the processability advantages composite electrolytes possess\, researchers are still puzzled about why\, in most cases\, no significant improvement in the electrolyte conductivity is observed after incorporating inorganic particles\, whose conductivity is orders of magnitude larger than that of polymer electrolytes at room temperature.\n\nI will present our efforts to quantify phase contributions to ion transport in model inorganic-organic systems\, ultimately showing that three critical factors govern the conductivity of composite electrolytes: Li + -desolvation dynamics\, Li + -transference number in the organic phase\, and the ceramic particle size. Using this knowledge\, we show that certain composite configurations have enhanced conductivity and substantially higher transference numbers than the pure model organic electrolyte alone.\n\nSpeaker Bio:\nBryan McCloskey is the Department Chair and Warren &amp\; Katharine Schlinger Distinguished Professor in Chemical Engineering in the Department of Chemical and Biomolecular Engineering at the University of California\, Berkeley. He also holds a joint appointment as a Faculty Chemical Engineer in the Energy Storage and Distributed Resources Division at Lawrence Berkeley National Laboratory. His laboratory explores numerous applications of electrochemistry to energy sustainability\, conversion\, and storage. Current projects focus on elucidating the fundamental electrochemistry of metal-air batteries and understanding a variety of challenges facing Li-ion and Na-ion batteries\, including high voltage cathode-electrolyte interfacial stability and organic-inorganic composites for solid-state batteries. He has co-authored more than 175 articles and has won numerous awards for his research\, including The Electrochemical Society Charles Tobias Award\, The International Society of Electrochemistry Tajima Prize\, and the VW/BASF Science Award- Electrochemistry. More information about the McCloskey Lab can be found at the Lab’s website: www.mccloskeylab.com.
UID:143400-21892983@events.umich.edu
URL:https://events.umich.edu/event/143400
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:chemical engineering,Chemistry
LOCATION:North Campus Research Complex Building 32 - B32 Auditorium
CONTACT:
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DTSTAMP:20260407T171647
DTSTART;TZID=America/Detroit:20260521T153000
DTEND;TZID=America/Detroit:20260521T163000
SUMMARY:Other:James and Judith Street Professor of Chemical Engineering - Delia Milliron
DESCRIPTION:Delia Milliron received her AB from Princeton University (1999) and her PhD from the University of California\, Berkeley (2004)\, both in Chemistry. While at Princeton\, she also completed a Certificate in Materials Science and Engineering. She initially worked for IBM’s research division\, first as a postdoc at the T.J. Watson Research Center and then as a Research Staff Member at the Almaden Research Center. In 2008\, she joined the research staff at the Molecular Foundry\, Lawrence Berkeley National Lab\, where she led the Inorganic Nanostructures Facility and later served as the Deputy Director. In 2013\, she began her academic career as an Associate Professor of Chemical Engineering at the University of Texas at Austin\, where she ultimately served as Department Chair and was appointed as the Ernest Cockrell\, Sr. Chair #1 in Engineering before moving to the University of Michigan in 2025 to become the Anthony C. Lembke Department Chair of Chemical Engineering. She is jointly appointed as a Professor of Chemistry.\n\nMilliron develops materials based on metal oxide nanocrystals\, tuning their composition and structure to control visible and infrared light and to guide electrochemical reactions. The nanocrystals' size-dependent properties offer new opportunities for optoelectronics and clean energy technologies. Her work has resulted in over 200 peer-reviewed publications and 20 issued US patents and led to her co-founding two venture-backed spin-off companies.\n\nMilliron's research has been recognized with awards including the DOE Early Career Research Program\, the Sloan Research Fellowship\, the American Chemical Society's (ACS) Inorganic Nanoscience Award\, Senior Membership in the National Academy of Inventors\, the Norman Hackerman Award from the Welch Foundation\, the O’Donnell Award in Engineering from the Texas Academy of Medicine\, Engineering\, Science & Technology\, the Nanoscale Science and Engineering Forum Award from the American Institute of Chemical Engineers (AIChE)\, and the Materials Research Society's MRS Medal.\n\n\n\nTHE JAMES AND JUDITH STREET PROFESSORSHIP\n\nThis Endowed professorship was made possible through the generosity of James R. and Judith W. Street. Dr. Street is a retired executive of the Shell Oil Company and the Royal Dutch Group. In 1987\, he was elected president of Shell Development Company with responsibility for Shell's entire research and development portfolio. He also served as president of Shell Chemical Company\, leading a successful turnaround effort. In 1991\, he served as chief technology officer of the Royal Dutch/Shell Group of companies located in London\, England. He earned three \nchemical engineering degrees and a math degree from the University of Michigan. In 2007\, Dr. Street was awarded the Department of Chemical Engineering Alumni Society Merit Award.\n\nThe James and Judith Street Professorship in Chemical Engineering was established in 2008 by a gift of $1.5M to establish and support an endowed professorship. The holder will be a professor in the department of Chemical Engineering who will be appointed to the professorship for five-year\, renewable terms. \n\nENDOWED PROFESSORSHIPS\nEndowed professorships at Michigan Engineering are essential to the University of Michigan. They provide resources to attract\, reward and retain outstanding faculty in all areas of engineering. Appointment to an endowed professorship is reserved for a scholar of national and often international stature who has earned a highly distinguished record of teaching\, research and publishing.\n\nThese professorships\, funded and named by donors\, bring prestige and recognition to leading members of our faculty and reward their contributions to the institution and to the field. Equally important\, endowed professorships attract new teaching and research talent from outside the University and continue in perpetuity to enrich the community of scholars at Michigan.
UID:147512-21901166@events.umich.edu
URL:https://events.umich.edu/event/147512
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:chemical engineering,Professorship
LOCATION:Lurie Robert H. Engin. Ctr - Johnson Rooms
CONTACT:
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