Zisheng Zhang
Assistant Professor
Chemical Engineering
"Real chemical systems are messy. Catalysts restructure inside the reactor, materials break down under high voltage, solvents reorganize drastically around a dissociating molecule. I believe that, instead of making a growing list of exceptions or averaging the messiness out of our models, we should appreciate chemical complexity as a new handle for engineering.
My approach stems from my personal trajectory in science. As a kid I was fascinated by the variety and diversity of life and wanted to be a naturalist. When I embarked on my academic journey, I was initially trained in experimental materials chemistry and became aware of the intricacies and tricks that common models neglect. This gap inspired me to pivot to theory and computation to investigate at an atomic level. I have since been developing evolution-inspired sampling algorithms to identify the minority yet reactive species in various operating catalysts, and to inverse-design functional molecules and materials.
At Stanford, the ZZ Lab will empower modern computational workflows with AI to keep up with the growing degrees of freedom that we try to capture in our models. The simulation tools we develop will be applied to understand the outliers and non-ideal behaviors in molecular, solid-state, and surface and interface systems, ultimately aiming to leverage them to tackle energy and environmental challenges. We believe that including more complexity in our models lets us not only predict the behavior of chemical systems more accurately, but also open up new mechanisms to manipulate novel reactivity, break design tradeoffs, and make disruptive discoveries.
As a "Gen Z professor", I enjoy communicating scientific concepts and findings with the help of pop culture references, in the form of memes and comics. To foster AI and scientific literacy in the next generation, we need to use the media they love to engage with, in an approachable and intellectually enjoyable way."
