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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Oct8
EVENT DETAILS
lessThe Department of Chemical and Biological Engineering is pleased to welcome Zhen-Gang Wang from the California Institute of Technology for a seminar titled:
Self-Assembly of End-Charged Block Copolymers and Blends: Effects of Ion Clustering
ABSTRACT: Adding ionic groups to polymer chain ends—whether within a single diblock copolymer or across two different homopolymers in a blend—offers a promising route to direct self-assembly for applications ranging from compatibilizing immiscible polymer blends to templating functional and ion-conducting nanostructures. Using self-consistent field theory that accounts for strong ion correlations, we show that under low-dielectric conditions typical for polymers, charged ends aggregate into multi-ion clusters that fundamentally alter assembly behavior. In end-charged diblock copolymers, these clusters act as compact, curvature-favoring foci, enabling complex network phases such as single primitive and single gyroid—structures that are absent in neutral diblocks. In binary blends with oppositely charged ends, electrostatic attraction suppresses macroscopic phase separation and induces microphase separation. However, the resulting phase diagram is simpler (dominated by lamellar and cylindrical phases) than the effective diblock picture would predict. This difference arises because ion clusters reside at the interface in blends, where they resist curvature, unlike in diblocks where they organize the surrounding chains. Notably, both systems form ordered microstructures at significantly lower segregation strengths than the corresponding uncharged diblock copolymers.
Zhen-Gang Wang received his B.Sc. in Chemistry in 1982 from Beijing (Peking) University, and his Ph.D. in Chemistry in 1987 from the University of Chicago. He did postdoctoral research first in Exxon Research and Engineering Company and then at UCLA. Since 1991 he has been on the Chemical Engineering faculty at the California Institute of Technology, where he is currently the Dick and Barbara Dickinson Professor. He has also served as Executive Officer (department chair) for Chemical Engineering for 6 years.
Wang’s research is the theoretical and computational study of structure, phase behavior, interfacial properties and dynamics of polymers, soft materials, and biophysical systems. His current activities revolve around three main themes: charged systems, including polyelectrolytes, salt-doped polymers, and electric double layers; nucleation or more generally barrier crossing in polymers and soft matter; and nonlinear rheology of polymer gels and entangled polymers.
Wang is a fellow of the American Physical Society and a member of the U. S. National Academy of Engineering. He is recipient of several significant awards and honors, including the Camille Dreyfus Teacher–Scholar Award (1995), the Alfred P. Sloan Award (1996), the Braskem Award from the American Institute of Chemical Engineers (AIChE) (2018), the AIChE Alpha Chi Sigma Award (2023), and the American Physical Society Polymer Physics Prize (2024). In addition, he was awarded the Richard P. Feynman Prize for Excellence in Teaching (2008), Caltech’s highest teaching honor.
Wang has served on the editorial advisory boards of Journal of Theoretical and Computational Chemistry, Macromolecules, ACS Macro Letters, Giant, Acta Physicochimica Sinica, and Science in China B (Chemistry). He is currently an associate editor for the ACS Journal Macromolecules.
Dr. Wang's seminar will be hosted by Northwestern faculty, Krishna Shrinivas.
TIME Thursday, October 8, 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)