Charudatta M Phatak


  • Materials Science Division, Argonne National Laboratory

Research Interests

  • Understanding domain behavior and interactions in ferromagnetic heterostructures at the mesoscale using in-situ Lorentz transmission electron microscopy.
  • Phase retrieval and 3D tomographic reconstructions of scalar and vector fields for TEM.
  • Image simulation for TEM as well as development of integrated imaging approach for TEM and X-ray microscopy.


  • D – 2009, Materials Science Engineering,
    Carnegie Mellon University, Pittsburgh, PA, USA
  • Tech – 2005 (Ceramics and Composites),
    Metallurgical and Materials Science Engineering,
    Indian Institute of Technology, Bombay, India
  • Tech – 2004,
    Metallurgical and Materials Science Engineering,
    Indian Institute of Technology, Bombay, India


  • Awarded the Early Career Award from joint Institute of Sustainability and Energy at Northwestern-Argonne to perform research on electrostatic potential mapping using electron microscopy, June 2015.
  • Awarded equipment grant from Materials Science Division (ANL) to upgrade Lorentz TEM for achieving excellent scientific goals, June 2014.
  • Awarded fellowship on international cooperation by Univ. of Paul Sabatier, Toulouse on “Combining Vector Field Tomography using off-axis and in-line holography”, September 2012.
  • Awarded the Presidential Student award for outstanding research work by the Microscopy Society of America, August 2008.

Selected Publications

  • Yang, F. De Carlo, C. Phatak, and D. Gürsoy, “A convolutional neural network approach to calibrating the rotation axis for X-ray computed tomography,”J. Synchrotron Radiat.24 (2), 469–475 (2017).
  • Zhang, A. K. Petford-Long, and C. Phatak, “Creation of artificial skyrmions and antiskyrmions by anisotropy engineering,”Sci. Rep.6, 31248 (2016).
  • Brajuskovic, F. Barrows, C. Phatak, and A. K. Petford-Long, “Real-space observation of magnetic excitations and avalanche behavior in artificial quasicrystal lattices,”Sci. Rep.6, 34384 (2016).
  • Phatak, O. Heinonen, M. De Graef, and A. Petford-Long, “Nanoscale skyrmions in a non-chiral metallic multiferroic: Ni2MnGa,”Nano Lett.16(7), 4141–4148 (2016).
  • Phatak, A. K. Petford-Long, and M. De Graef, “Recent advances in Lorentz microscopy,”Curr. Opin. Solid State Mater. Sci.20 (2), 107–114 (2016).
  • Phatak, L. de Knoop, F. Houdellier, C. Gatel, M. J. Hÿtch, A. Masseboeuf, “Quantitative 3D electromagnetic field determination of 1D nanostructures from single projection.”Ultramicroscopy164, 24–30 (2016).
  • Phatak and D. Gürsoy, “Iterative reconstruction of magnetic induction using Lorentz transmission electron tomography.,”Ultramicroscopy,150, 54–64 (2015).
  • Choiet al., “Enhancement of Local Piezoresponse in Polymer Ferroelectrics via Nanoscale Control of Microstructure,” ACS Nano9 (2), 1809–1819 (2015).
  • Phatak, A. K. Petford-Long, H. Zheng, J. F. Mitchell, S. Rosenkranz, and M. R. Norman, “Ferromagnetic domain behavior and phase transition in bilayer manganites investigated at the nanoscale,”Phys. Rev. B92, 224418 (2015).
  • Hong, S. H. Chang, C. Phatak, B. Magyari-Kope, Y. Nishi, S. Chattopadhyay, J. H. Kim, “Mechanism Study of Reversible Resistivity Change in Oxide Thin Film,”ECS Trans., 69 (3), 51–55 (2015).

Professional Activities

  • Programming committee member for 21st International Conference on Magnetism, San Francisco, 2018
  • Programming committee member for Annual Magnetism and Magnetic Materials Conference, New Orleans, LA, October 2016.
  • Co-organizer of a symposium on “Driving Discovery: Integration of multi-modal imaging and data analysis” at the Annual TMS conference, Feb 2016.
  • IEEE Chicago Section, Students Activities Chair, 2015 – present.


Current Projects

  • Materials Science Division, Emergent Behavior of Functional Nanostructures:studying patterned nanomagnetic lattices to study geometric frustration in periodic and aperiodic lattices, controlling interfacial interactions in ferromagnetic heterostructures to create novel and non-trivial magnetic spin textures such as merons, and skyrmions, studying structural and chemical changes in resistive switching oxides
  • Smart Acquisition and Sampling for Simulation and Imaging:to employ machine-learning and training algorithms to develop data acquisition strategies that maximize the knowledge gain from imaging experiments, and minimize radiation exposure.
  • Multimodal Imaging of Materials for Energy Storage:development of integrated computational framework for tomographic data analysis from electron and X-ray tomography using machine learning algorithms, studying NMC (Li-Ni-Mn-Co oxide) cathode materials
  • Institute for Sustainability and Energy at Northwestern University award: visualizing electrostatic potential at interfaces and grain boundaries in CeO2using medium resolution off-axis electron holography


Charudatta M Phatak