Zachary W. Ulissi

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

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

Pari (Aini) Palizhati

Graduate Student

apalizha@andrew.cmu.edu
Doherty Hall A207A, Carnegie Mellon University, Pittsburgh PA, 15213

Affiliation:

Chemical Engineering
Carnegie Mellon University

Nianhan (Kaylee) Tian

Undergraduate Student

nianhant@andrew.cmu.edu
Doherty Hall A207A, Carnegie Mellon University, Pittsburgh PA, 15213

Affiliation:

Chemical Engineering
Carnegie Mellon University

Kevin Tran

Graduate Student

ktran@andrew.cmu.edu
Doherty Hall A207A, Carnegie Mellon University, Pittsburgh PA, 15213

Affiliation:

Chemical Engineering
Carnegie Mellon University

Junwoong Yoon

Graduate Student

junwoony@andrew.cmu.edu
Doherty Hall A207A, Carnegie Mellon University, Pittsburgh OR, 15213

Affiliation:

Chemical Engineering
Carnegie Mellon University

Zong Qian (Max) Yu

MS Student

zongqiay@andrew.cmu.edu
Doherty Hall A207A, Carnegie Mellon University, Pittsburgh PA, 15213

Affiliation:

Chemical Engineering
Carnegie Mellon University
Most Cited Publications
  1. "Molecular recognition using corona phase complexes made of synthetic polymers adsorbed on carbon nanotubes," J. Zhang, M. P. Landry, P. W. Barone, J-H Kim, S. Lin, Z. W. Ulissi, D. Lin, B. Mu, A. A. Boghossian, A. J Hilmer, A. Rwei, A. C. Hinckley, S. Kruss, M. A Shandell, N. Nair, S. Blake, F. Şen, S. Şen, R. G. Croy, D. Li, K. Yum, J-H Ahn, H. Jin, D. A. Heller, J. M. Essigmann, D. Blankschtein, M. S. Strano, Nature Nanotechnology 8, 959 (2013)
  2. "Diameter-dependent ion transport through the interior of isolated single-walled carbon nanotubes," W. Choi, Z. W. Ulissi, S. FE Shimizu, D. O Bellisario, M. D. Ellison, M. S. Strano, Nature Communications 4, 2397 (2013)
  3. "To address surface reaction network complexity using scaling relations machine learning and DFT calculations," Z. W. Ulissi, A.J Medford, T. Bligaard, J. K Nørskov, Nature Communications 8,14621 (2017)
  4. "Modelling and development of photoelectrochemical reactor for H2 production'" C. Carver, Z. W. Ulissi, C. K. Ong, S. Dennison, G. H. Kelsall, K. Hellgardt, International Journal of Hydrogen Energy 37, 2911 (2012)
  5. "Low dimensional carbon materials for applications in mass and energy transport," Q.Hua Wang, D. O. Bellisario, L. W. Drahushuk, R. M. Jain, S. Kruss, M. P. Landry, S. G. Mahajan, S. FE Shimizu, Z. W. Ulissi, M.S. Strano, Chem. Mater., 26, 72 (2014)
Recent Publications
  1. "Convolutional Neural Network of Atomic Surface Structures To Predict Binding Energies for High-Throughput Screening of Catalysts," S Back, J Yoon, N Tian, W Zhong, K Tran, and ZW UlissiJournal of Physical Chemistry Letters (2019)
  2. "Towards a design of active oxygen evolution catalysts: Insights from automated density functional theory calculations and machine learning,"  S Back, K Tran, and ZW UlissiACS Catalysis (2019)
  3. "Predicting Intermetallic Surface Energies with High-Throughput DFT and Convolutional Neural Networks,"  A Palizhati, W Zhong, K Tran, and ZW UlissiChemrXiv (2019)
  4. "Dynamic Workflows for Routine Materials Discovery in Surface Science,"  K Tran, A Palizhati, S Back, and ZW UlissiJournal of Chemical Information and Modeling (2018)
  5. "Active learning across intermetallics to guide discovery of electrocatalysts for CO2 reduction and H2 evolution,"  K Tran and ZW UlissiNature Catalysis (2018)

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