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Zachary W. Ulissi

Carnegie Mellon University
Chemical Engineering
Ph.D., Massachusetts Institute of Technology, 2015

Zachary W. Ulissi joined Carnegie Mellon University in 2017, after doing his PhD at MIT and post-doc at Stanford. His research at MIT focused on the the applications of systems engineering methods to understanding selective nanoscale carbon nanotube devices and sensors under the supervision of Michael Strano and Richard Braatz. Prof. Ulissi did his postdoctoral work at Stanford with Jens Nørskov where he worked on machine learning techniques to simplify complex catalyst reaction networks, applied to the electrochemical reduction of N2 and CO2 to fuels. The Ulissi group builds on this foundation to model, understand, and design nanoscale interfaces using modern predictive methods to guide detailed molecular simulations.


Our research work is focused on study of chemical, mechanical, electronic, and thermal properties of nano sized materials. At nano scales, entropic fluctuations become more prominent and materials behave differently. Our work is on capturing these effects in real devices and applications requires a range of modeling approaches, from hard theory (DFT and kinetics), to soft theory (continuum, statistical mechanics and molecular dynamics), and up through systems engineering approaches. There are various application to study such effect, including biomedical sensors (nanotube-based optical sensors)  and energy applications (CO2 to fuels, fuel cells, thermal catalysis). Following are our major projects:
Controlling selectivity of nanoscale interfaces with co-adsorbates and soft functionalizations
Machine-learning based approaches to accelerate materials screening
Bayesian methods for complex reaction mechanism reduction and elucidation


Title Position Email
Matt Adams PhD Student
Kirby Broderick PhD Student
Ketong Chen Undergraduate Student
Rui Qi (Richie) Chen Undergraduate Student
Amish Chovatiya
Javier Domingo Postdoctoral Fellow
Sudhees Ethirajan Graduate Student
Jingxuan Li Graduate Student
Arundhati Madabhushi Graduate Student
Pari (Aini) Palizhati Graduate Student
Unnatti Sharma Phd Student
Muhammed Shuaibi Phd Student
Saurabh Sivakumar Graduate Student
Nianhan (Kaylee) Tian Undergraduate Student
Nicholas Tiwari Phd Student
Katsuyuki Tomita
Kevin Tran Graduate Student
Brandon Wood Postdoctoral Fellow
Junwoong Yoon Graduate Student
Zong Qian (Max) Yu MS Student
Wen (Amber) Zhong MS Student
Most Cited Publications

"Molecular recognition using corona phase complexes made of synthetic polymers adsorbed on carbon nanotubes." Jingqing Zhang, Markita P Landry, Paul W Barone, Jong-Ho Kim, Shangchao Lin, Zachary W Ulissi, Dahua Lin, Bin Mu, Ardemis A Boghossian, Andrew J Hilmer, Alina Rwei, Allison C Hinckley, Sebastian Kruss, Mia A Shandell, Nitish Nair, Steven Blake, Fatih Şen, Selda Şen, Robert G Croy, Deyu Li, Kyungsuk Yum, Jin-Ho Ahn, Hong Jin, Daniel A Heller, John M Essigmann, Daniel Blankschtein, Michael S Strano. Nature nanotechnology.
"To address surface reaction network complexity using scaling relations machine learning and DFT calculations." Zachary W Ulissi, Andrew J Medford, Thomas Bligaard, Jens K Nørskov. Nature communications.
"Diameter-dependent ion transport through the interior of isolated single-walled carbon nanotubes." Wonjoon Choi, Zachary W Ulissi, Steven FE Shimizu, Darin O Bellisario, Mark D Ellison, Michael S Strano. Nature communications.
"Machine-Learning Methods Enable Exhaustive Searches for Active Bimetallic Facets and Reveal Active Site Motifs for CO2 Reduction." Zachary W Ulissi, Michael T Tang, Jianping Xiao, Xinyan Liu, Daniel A Torelli, Mohammadreza Karamad, Kyle Cummins, Christopher Hahn, Nathan S Lewis, Thomas F Jaramillo, Karen Chan, Jens K Nørskov. ACS Catalysis.
"Active learning across intermetallics to guide discovery of electrocatalysts for CO 2 reduction and H 2 evolution." Kevin Tran, Zachary W Ulissi. Nature Catalysis.

Recent Publications

"Multi-Task Machine Learning to Predict ORR Catalyst Descriptors and Performance across Surface Composition." Aini Palizhati, Seoin Back, Kevin Tran, Zachary Ulissi. 2019 AIChE Annual Meeting.
"Graph Convolutional Machine Learning Methods for the Predictions of Adsorption and Thermochemistry and Surface Stability." Seoin Back, Aini Palizhati, Wen Zhong, Nianhan Tian, Kevin Tran, Zachary Ulissi. 2019 AIChE Annual Meeting.
"Thermodynamic Techniques to Capture Non-Ideal Surfactant Assembly at Hard Nanoscale Interfaces." Junwoong Yoon, Zachary Ulissi. 2019 AIChE Annual Meeting.
"Towards Predicting Intermetallics Surface Properties with High-Throughput DFT and Convolutional Neural Networks." Aini Palizhati, Wen Zhong, Kevin Tran, Seoin Back, Zachary W Ulissi. Journal of chemical information and modeling.
"Convolutional neural network of atomic surface structures to predict binding energies for high-throughput screening of catalysts." Seoin Back, Junwoong Yoon, Nianhan Tian, Wen Zhong, Kevin Tran, Zachary W Ulissi. The journal of physical chemistry letters.