News & EventsDepartment Events
Events
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Oct1
EVENT DETAILS
lessMore details to come.
TIME Thursday, October 1, 2026 at 9:30 AM - 10:45 AM
LOCATION LR4, Technological Institute map it
CONTACT Olivia Wise olivia.wise@northwestern.edu EMAIL
CALENDAR McCormick-Chemical and Biological Engineering (ChBE)
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Oct2
EVENT DETAILSmore info
lessManufacturing with Embodied AI
Celebrating manufacturing-related R&D achievements and their business impacts on National Manufacturing Day!
Leadership Remarks
-Northwestern University President Mung Chiang
-National Center for Manufacturing Sciences President and CEO Lisa Strama
-Northwestern University Provost Erik LuijtenCorporate Panel, Stan Rendon, 3M VP of R&D, Yu Cao, Applied Materials Chief AI Officer and Amey Deosthali, AMD Head of Robotics, Industrial & Healthcare (Physical AI)
NU Faculty Panel, Prof. Jian Cao, Prof. Ed Colgate, Prof. Mark Hersam, Prof. John Rogers
Founders/SME Panel, Jason Sebastian, Executive VP QuesTek Innovation, Demeng Che, co-Founder & CEO Converge Lab, Gino Domel, CEO HiDeNN-AI, Joe Mullenbach, co-founder Fluid Reality
Ecosystems Panel, Tom Kurfess, CTO, NCMS & Executive Director of Mfg Institute at Georgia Tech, Berardino Baratta, CEO MxD, Allison Fisher, Chief of Staff mHUB
TIME Friday, October 2, 2026 at 8:15 AM - 5:00 PM
LOCATION 2001 Sheridan Road map it
CONTACT Maegen Gregory maegen.gregory@northwestern.edu EMAIL
CALENDAR Northwestern Initiative for Manufacturing Science and Innovation
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Oct15
EVENT DETAILS
lessThe Department of Chemical and Biological Engineering is pleased to present a seminar with department faculty member, John Torkelson.
"Upcycling Virgin and Waste Thermoplastic Polyethylene, Polypropylene, and Related Copolymers into Covalent Adaptable Networks that Recover Crosslink Density upon Recycling"
ABSTRACT: Approximately one trillion pounds of synthetic polymers/plastics are produced worldwide each year. However, less than 10% of spent polymers and plastics are effectively recycled. Polyethylene (PE) and polypropylene (PP) account for more than half of global polymer production; thus, approaches to address this recycling crisis should consider PE, PP, and their copolymers. We will describe how thermoplastic PE, PP, and associated copolymers, composed of linear or branched chains, can be upcycled into covalent adaptable networks (CANs) using a one-step, radical-based reactive processing method that is a simple “drop-in” modification of the commercial process used to make non-recyclable, permanently crosslinked PE (PEX) networks or thermosets from thermoplastic PE. The commercial process for making PEX thermosets, which have enhanced properties relative to thermoplastic PE and are produced at ~20 billion pounds annually, involves melt-processing PE with a low level of radical initiator, resulting in the transfer of a hydrogen atom from PE to the initiated radical. This transfer leaves a radical on the PE backbone that can react with another PE backbone radical, leading to a permanent crosslink. We developed dynamic covalent cross-linkers that can be “dropped into” the reactive process at several weight percent relative to PE or ethylene-based copolymer. This yields CANs with crosslinks that are robust under use conditions but dynamic during melt reprocessing, enabling recyclability. Our dynamic covalent crosslinkers yield PE CANs that recover the original crosslink density and properties after multiple recycling steps and exhibit markedly reduced elevated-temperature creep compared with thermoplastic PE. We will also show that direct free-radical copolymerization of ethylene with low levels of dynamic covalent crosslinkers can produce fully recyclable PE CANs. Our approach also enables us to overcome the challenge of forming networks by reactive melt-state processing of PP and propylene-based copolymers. No commercial crosslinked PP thermoset is produced by radical-based reactive processing because of chain scission. We overcame this problem by developing methods that stabilize radicals via resonance, yielding recyclable PP CANs that recover cross-link density upon recycling. Finally, we will discuss using CANs to mitigate the formation of microplastics.
John Torkelson is a Walter P. Murphy Professor in the Dept. of Chemical and Biological Engineering and the Dept. of Materials Science and Engineering at Northwestern University. He previously served as Associate Dean for Graduate Studies and Research in the Engineering School and Director of the Materials Research Center at Northwestern. He also held leadership roles in the Division of Polymer Physics of the American Physical Society and the Materials Engineering and Sciences Division of the American Institute of Chemical Engineers. John received the Tau Beta Pi Outstanding Teaching Award, the Lilly Foundation Teaching Award, the Northwestern University Alumni Association Excellence in Teaching Award, and both the McCormick School of Engineering Teacher of the Year Award and Advisor of the Year Award. In 2004, John’s research excellence was recognized with both the Wiley Polymer Physics Award and the Charles M. Stine Award from the Materials Division of AIChE. In 2025, he was named a “highly ranked scholar”by ScholarGPS in several categories based on lifetime achievement, including #1 in “Transition Temperature,” #1 in “Gradient Copolymer,” and #3 in “Glass Transition.” John was the 2026 Turner Alfrey Visiting Professor at Michigan State University-St. Andrews, and he and his research team were just named winners of the 2027 ACS PMSE Division Cooperative Research Award for the research he will discuss in his seminar at Northwestern University.
TIME Thursday, October 15, 2026 at 9:30 AM - 10:45 AM
LOCATION LR4, Technological Institute map it
CONTACT Olivia Wise olivia.wise@northwestern.edu EMAIL
CALENDAR McCormick-Chemical and Biological Engineering (ChBE)
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Oct22
EVENT DETAILS
lessThe Department of Chemical and Biological Engineering is proud to present our 20th annual Richard S.H. Mah Lecture with speaker Jim Rawlings from the University of California, Santa Barbara.
Process Engineering at the Dawn of (Generative) AI
Maintaining high standards of living while decreasing our impact on the planet requires both new manufacturing technologies as well as increasingly efficient operation of these technologies at large scale. Process systems engineering will play a critical role in addressing these challenges.
We start with a review of some of the advances that have taken place in the field of process systems engineering during the last 50 years. We focus specifically on process control because it is currently faced with several new challenges: increasingly stringent product quality requirements, tighter environmental regulations, and increasingly transient operating conditions, e.g., large fluctuations in electricity prices and supply chains. We present the central ideas of model predictive control, which has become during this period the leading advanced feedback control method, both in industrial practice as well as a topic of control theory research. We discuss the fundamental reasons for this success, which builds upon the foundations of optimal control and dynamic modeling, supplemented with measurement feedback to make the resulting system robust against model inaccuracies and disturbances.
At the dawn of generative AI, we anticipate using machine learning and deep neural networks trained on large datasets to provide improved modeling capability. But when we create models for process optimization or process control, the basic issue to be understood is how much information are we able to extract from available measurements, and how much domain-specific structural information must we provide, e.g., conservation laws and thermodynamic principles, before the optimization of such composite models is reliable and useful. We currently lack systematic guidelines for how best to combine these two sources of information.
Finally we discuss the education of chemical engineers to understand, operate and improve these new technologies. Adding to our educational challenge, universities are now seeing the first generation of engineering students who first ask a large language model (LLM) agent to solve their homework exercises or write their software code. Meanwhile most of these exercises were designed to be solved solely by the students, to start building up their engineering understanding and intuition through simple examples. This mismatch in current educational materials and widely-available LLM technology is a pressing challenge that educators must now address.
James B. Rawlings received the B.S. from the University of Texas and the Ph.D. from the University of Wisconsin, both in Chemical Engineering. He spent one year at the University of Stuttgart as a NATO postdoctoral fellow and then joined the faculty at the University of Texas. He moved to the University of Wisconsin in 1995, and then to the University of California, Santa Barbara in 2018, and is currently the Mellichamp Process Control Chair in the Department of Chemical Engineering, and the co-director of the Texas-Wisconsin-California Control Consortium (TWCCC).
Professor Rawlings's research interests are in the areas of chemical process modeling, monitoring and control, nonlinear model predictive control, moving horizon state estimation, and molecular-scale chemical reaction engineering. He has written numerous research articles and coauthored three textbooks: "Modeling and Analysis Principles for Chemical and Biological Engineers," 2nd ed. (2022), with Mike Graham, "Model Predictive Control: Theory Computation, and Design," 2nd ed. (2020), with David Mayne and Moritz Diehl, and "Chemical Reactor Analysis and Design Fundamentals," 2nd ed. (2020), with John Ekerdt.
In recognition of his research and teaching, Professor Rawlings has
received several awards including:- Election to the National Academy of Engineering;
- John M. Prausnitz Institute Lecturer, AIChE
- Richard E. Bellman Control Heritage Award, American Automatic Control Council
- William H. Walker Award for Excellence in Contributions to Chemical
- Engineering Literature from the AIChE;
- Warren K. Lewis Award for Chemical Engineering Education from the AIChE;
- Inaugural High Impact Paper Award from the International Federation of Automatic Control (IFAC);
- Ragazzini Education Award, American Automatic Control Council;
He is a fellow of IFAC, IEEE, and AIChE.
Dr. Rawlings' Mah Lecture will be hosted by department chair Danielle Tullman-Ercek.
TIME Thursday, October 22, 2026 at 9:30 AM - 10:45 AM
LOCATION LR4, Technological Institute map it
CONTACT Olivia Wise olivia.wise@northwestern.edu EMAIL
CALENDAR McCormick-Chemical and Biological Engineering (ChBE)
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Oct29
EVENT DETAILS
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TIME Thursday, October 29, 2026 at 9:30 AM - 10:45 AM
LOCATION LR4, Technological Institute map it
CONTACT Olivia Wise olivia.wise@northwestern.edu EMAIL
CALENDAR McCormick-Chemical and Biological Engineering (ChBE)
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Nov5
EVENT DETAILS
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TIME Thursday, November 5, 2026 at 9:30 AM - 10:45 AM
LOCATION LR4, Technological Institute map it
CONTACT Olivia Wise olivia.wise@northwestern.edu EMAIL
CALENDAR McCormick-Chemical and Biological Engineering (ChBE)
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Nov12
EVENT DETAILS
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TIME Thursday, November 12, 2026 at 9:30 AM - 10:45 AM
LOCATION LR4, Technological Institute map it
CONTACT Olivia Wise olivia.wise@northwestern.edu EMAIL
CALENDAR McCormick-Chemical and Biological Engineering (ChBE)
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Nov19
EVENT DETAILS
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TIME Thursday, November 19, 2026 at 9:30 AM - 10:45 AM
LOCATION LR4, Technological Institute map it
CONTACT Olivia Wise olivia.wise@northwestern.edu EMAIL
CALENDAR McCormick-Chemical and Biological Engineering (ChBE)
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Dec3
EVENT DETAILS
lessMore details to come.
TIME Thursday, December 3, 2026 at 9:30 AM - 10:45 AM
LOCATION LR4, Technological Institute map it
CONTACT Olivia Wise olivia.wise@northwestern.edu EMAIL
CALENDAR McCormick-Chemical and Biological Engineering (ChBE)