Maria Chan is a scientist with the Center for Nanoscale Materials who studies nanomaterials and renewable energy materials, including solar cells and batteries and other energy storage, as well as photo- and electro-catalysts, thermal transport, and thermoelectrics. Particular focus is on using machine learning for efficient computational approaches and for interfacing computational models with materials characterization (x-ray, electron, and scanning probe). She is a senior fellow at the Northwestern Argonne Institute for Science and Engineering, and a fellow of the University of Chicago Consortium for Advanced Science and Engineering. She is also an associate editor at the ACS Journal Chemistry of Materials, and serves on the advisory boards for the journal APL-Machine Learning, Duke’s aiM-NRT AI training project, and CEDARS EFRC.

Winter 2023: We are hiring postdocs and students! Please email me at mchan@​anl.​gov for details.

Education

• BSc, Physics and Applied Mathematics, University of California at Los Angeles
• PhD, Physics, Massachusetts Institute of Technology

Research topics

• First principles and atomistic modeling of nanomaterials and renewable energy materials, including photovoltaics, energy storage, photo- and electro-catalysts, thermal transport, and thermoelectrics
• Development of first principles and machine learning approaches for materials property prediction
• Methodology and software development for integrating atomistic modeling and experimental measurements
• First principles computation in conjunction with synchrotron x-ray characterization to determine the structure of solid-water interfaces

Current/previous projects

• Center for Nanoscale Materials, Theory and Modeling group: structural and electronic properties of semiconductor nanoparticles, transition-metal dichalcogenides for catalysis, hybrid perovskite photovoltaics, connecting modeling to synchrotron characterization and microscopy techniques
• DOE Early Career Award: development of FANTASTX (Fully Automated Nanoscale To Atomistic Structures from Theory and eXperiments) for determination of structures from x-ray, electron, and scanning probe characterization
• Midwest Integrated Center for Computational Materials: inter-operable computational modeling codes to model transport at interfaces
• AI/ML at Scientific User Facilities: use of artificial intelligence and machine learning for information extraction from x-ray, electron microscopy, and neutron data
• DOE SBIR/STTR for data management framework, computer vision, and natural language processing towards labeled microscopy data
• Center for Electrochemical Energy Science: high capacity lithium-ion, lithium-oxygen, and hybrid lithium-ion/lithium-oxygen battery materials, solid-electrolyte interphase, surface and interfacial interactions
• DOE EERE Solar Energy Technology Office: grain boundaries and dopants in CdTe photovoltaics, degradation in Si photovoltaics
• DOE ARPA-E SHIELD: nanostructured thermal barrier coatings
• Integrated Imaging to Understand Photocatalysis: photocatalysis on transition oxide metal surfaces, integrated imaging with computational modeling
• Argonne internal projects: computer-vision guided retrieval of microscopy images, intermediate band hybrid perovskite photovoltaics, non-equilibrium thermal transport, non-PGM catalysts
• Industrial sponsors: electronic and lattice thermal transport modeling

Publications

Google Scholar profile

Codes

• https://​github​.com/​M​a​t​e​r​i​a​lEyes
• https://​github​.com/​j​o​s​h​-​m​u​t​i​a​n​/​g​r​a​i​n​-​b​o​u​n​d​a​r​y​-​genie

Data

Published datasets at the Materials Data Facility

Lectures and seminars

• Argonne Outloud presentation ​“From Atoms to Clean Energy Technologies” 
• Cell Press Webinar ​“Machine learning impurity levels in semiconductors”
• Tutorial on machine learning of impurity levels by former postdoc Arun Mannodi Kannakithodi
• Modeling and Machine Learning of X-ray Absorption Spectra for Energy Materials: XAS Journal Club

Awards

• 2022 Sam Bader Award
• 2021 Physical Science & Engineering Directorate Excellence Award
• 2020 DOE Early Career Award
• 2017 Argonne Outstanding Postdoctoral Supervisor Award

Research News

• 2022 Staff Spotlight
• 2022 Boundaries in NMC battery materials
• 2022 Perovskite design
• 2021 CdTe solar cell
• 2021 Borophane
• 2021 Validating first principles molecular dynamics simulations
• 2019 Ultrafast dynamics in perovskite halides
• 2018 Low Pt catalyst for fuel cells
• 2016 Machine learned interatomic potential for IrO2
• 2013 Hybrid Li-ion/Li-O2 batteries

Current postdoctoral associates

• Dr Luqing Wang (Google Scholar)
• Dr Joshua Paul (Google Scholar)
• Dr Arun Baskaran (Google Scholar)
• Dr Chaitanya Kolluru (Google Scholar)(former PhD student co-supervised with Professor Richard Hennig)
• Dr Davis Unruh (Google Scholar)
• Dr Nina Andrejevic (Maria Geoppart Mayer Fellow) (LinkedIn)(Google Scholar)

Current doctoral student

• Ms Yiming Chen (University of California, San Diego, co supervised with Professor Shyue Ping Ong)
• Ms Sam Tetef (University of Washington, co supervised with Gerald Seidler)
• Mr Shinjan Dutta (Northwestern University)

Current research assistants

• Mr Justin Pothoof (University of Washington)
• Ms Haili Jia (Johns Hopkins University)
• Ms Bipasha Ferdaushi (UIUC)

Former postdoctoral associates

• Dr Alper Kinaci (Google Scholar)(LinkedIn)(Now Senior Computational Specialist at Northwestern University)
• Dr Fatih Sen (Google Scholar)(LinkedIn)(Now Senior Scientist, Metallurgy and Modeling at Novelis)
• Dr Liang Li (Google Scholar)(LinkedIn) (Now Founding Engineer @ Novel)
• Dr Yi Xia (Google Scholar)(Now postdoctoral fellow at Northwestern University)
• Dr Kendra Letchworth-Weaver (Rahman Named Fellow)(Google Scholar)(LinkedIn)(Now Assistant Professor at James Madison University)
• Dr Denise Ford (Duke University)
• Dr Ji-Sang Park (Website)(Now an Assistant Professor at Kyungpook National University)
• Dr Arun Mannodi Kanakkithodi (Google Scholar)(LinkedIn)(Website)(Now Assistant Professor at Purdue University)
• Dr Joydeep Munshi (Google Scholar)(Now Research Scientist at Sony AI)

Former doctoral students

• Dr Chris Buurma (Now Modeling and Simulation Scientist at Battelle)
• Dr Joseph Kubal (visiting from Purdue University)(Now Assistant Chemical Engineer at Argonne National Lab)
• Dr Lynza Sprawl (visiting from Oregon State University)(Now Senior R&D Engineer at Honeywell)
• Dr Mingren Shen (University of Wisconsin Madison, co supervised with Professor Dane Morgan)(Now Software Development Engineer at Amazon)
• Dr Eric Schwenker (Northwestern University, co supervised with Professor Chris Wolverton)(Now Computer Vision Engineer at Path Robotics, Inc.)
• Dr Weixin Jiang (Northwestern University, co supervised with Professor Ollie Coissart)(Now Machine Learning Engineer at Uber)

Former research assistants

• Ms Karen Zheng (UIUC) (Now a Food Scientist)
• Ms Jessi Hartman (UCDavis) (Now PhD student at UIUC)
• Ms Amy Wey (Cornell University) (Now Software Engineer at Galaxy Digital)
• Mr Mutian (Josh) Liu (University of Chicago)(Now Senior Software Engineer at Meta)
• Mr Ryan Pencak (Bucknell University) (Now Software Engineer at NYDIG)
• Mr Michael Toriyama (UIUC) (2018 Barry Goldwater Scholar)(Now PhD student at Northwestern)
• Mr Thierry Wambo (University of Texas San Antonio) (Now Data Scientist at Lockheed Martin)
• Mr Ryan Pederson (Virgnia Tech) (Now PhD student at UC Irvine)
• Ms Grace Lu (Northwestern University) (Now PhD student at UIUC)
• Mr Jackson O’Donnell (LinkedIn)(University of Chicago) (Now PhD student at UC Santa Cruz)
• Mr Spencer Hills (LinkedIn)(Wheaton College) (Now medical student)
• Mr Isaac Malsky (University of Chicago) (Now PhD student at University of Michigan)
• Ms Sarah O’Brien (Northwestern University) (Now Cloud Engineer at Sonos)
• Mr Viraaj Jayaram (University of Chicago) (Now PhD student at Yale)
• Ms Sankhya Hirani (UIUC) (Now PhD student at U Washington)
• Mr Rahim Raja (University of Chicago)
• Mr Marcel Chlupsa (Kansas State University)(Now PhD student at University of Michigan)
• Mr Trevor Spreadbury (MIT)(Now Software Engineer at Data Science Institute (DSI) at the University of Chicago)
• Mr Buduka Ogonor (University of Chicago)
• Ms Victoria Adebayo (Howard University)