Doctoral, Ph.D. Thesis : Characterization of Ion Battery Materials by Scanning Electron Microscopy.
Meysam Naghizadeh is a Ph.D. candidate at the McGill Electron Microscopy Research Group (MEMRG) in the Materials Engineering Department at McGill University. He obtained his master’s and undergraduate from the School of Metallurgy and Materials Engineering of the University of Tehran, Iran in 2016 and 2013, respectively. Meysam is now working on the characterization of ion battery materials, including different Li-ion and Na-ion cathodes and graphitic anodes. Today’s global efforts toward renewable energy necessitate improvements in ion batteries. These batteries suffer from degradation during the numerous cycles. For developing new battery materials, understanding microstructural evolution during cycling is essential. High-resolution electron microscopy techniques can be applied to study battery active materials. Moreover, cathode materials are polycrystalline powder materials in which grains’ orientation influences the battery cell’s capabilities and degradation behavior. The Electron Backscatter Diffraction (EBSD) technique is the perfect tool for determining microstructural changes as well as the crystallographic behavior of the cathode materials. For this purpose, he is using state-of-art high-resolution Scanning (Transmission) Electron Microscopes (S(T)EMs) equipped with EBSD/CBED detectors such as the Hitachi SU8000, SU8230, and SU9000.
Doctoral, Ph.D. Thesis : Multiscale Density Functional Theory to Monte Carlo Simulations in Battery Materials.
Ali Jaberi received a B.Sc. in Materials science and Engineering from Shiraz University and started his Ph.D. at the Department of Materials Engineering at McGill University. His Ph.D. research deals with multiscale simulations ranging from Density Functional Theory to Monte Carlo simulations in battery materials. These simulations enabled him to predict the knock-on damages induced during the electron microscopy characterization of Li-ion battery materials. He also identified different diffusion mechanism and their associated barrier energies in layered oxide cathodes and solid electrolyte interphase (SEI) layers. To scale up the simulations, he developed a kinetic Monte Carlo code to determine the diffusion coefficient of Li in these materials. His research contributes to accelerating the study and/or discovery of battery materials to fulfill the fast energy transition shift in the climate change crisis.
Doctoral, Ph.D. Thesis : Improvement of Aluminum Alloys Performances using Automatic Image Acquisition and Deep Learning.
Yinuo Li entered MEMRG as a direct PhD student in September 2022. Prior to this, she did her undergraduate study in the Mining and Materials Engineering Department at McGill University in Montréal. Her research is about the quantification of inclusions in aluminum alloys to improve their performance in collaboration with industrial partners. She mainly works on our Hitachi SU8230 SEM, which she intensively uses to produce high-resolution SE and BSE images of the different microstructures as well generating elemental maps using a high throughput EDS detector. A large part of her research focuses on developing tools to acquire these data remotely and automatically on large scales using the Dragonfly program with the SU8230. In parallel, Yinuo works at developing deep learning models based Monte Carlo simulations to recognize features and analyze the precipitation distribution and properties under a variety of conditions. The statistical data gathered with these techniques will provide unvaluable information that will be used to monitor the effect of minor addition elements to optimize the performance of the alloys after the heat treatment processes for further industrial use.
Doctoral, Ph.D. Thesis : Mechanical and Microstructural Characterization of Battery Materials under Electron Microscopy.
Oluwasogo Adegboyega obtained his bachelor's degree in Physics from the Federal University of Agriculture, Abeokuta, Nigeria, in 2015. Subsequently, in 2019, he completed his master's degree in Theoretical Physics at the University of Ibadan, Nigeria, where his research centred on how pseudopotentials and functionals affect the electronic and optical properties of perovskite solar cell materials, using Density Functional Theory. He later moved to Beihang University (BUAA), Beijing, China, where he pursued another master's degree, this time in Nuclear and Particle Physics. He successfully completed this program in 2022, having researched the microstructural and thermal characteristics of nuclear fusion materials when subjected to intense pulsed ion beam irradiation. His research methodology employed Monte Carlo simulations, finite element method (FEM), and experimental approaches. In 2022, Oluwasogo embarked on his PhD journey with the McGill Electron Microscopy Research Group (MEMRG). His current research revolves around enhancing energy supply, particularly through investigating the mechanical properties and microstructural studies of Li-ion cathodes using in-situ a nano-indentation tool, the Bruker PI-88 nano-indenter, inside the Hitachi SU-3500 and SU-8230 SEMs.
Doctoral, Ph.D. Thesis : Neural network-based MC X-ray for quantitative analysis of elements.
In his PhD project, Dawei is dedicated to enhancing the affordability and efficiency of elemental analysis in materials through Energy Dispersive X-ray Spectroscopy (EDS). Conventional quantitative EDS analysis is prohibitively expensive due to the necessity for extensive databases of standard elements. His innovative approach integrates cutting-edge neural network technology with Monte Carlo simulations, a well-established method for predicting electron-solid interactions. By employing advanced software such as the MC X-Ray program developed in our group, he has validated its accuracy in simulating realistic EDS spectra, and he has made comparative analyses with the Penelope software. Notably, MC X-Ray holds a significant speed advantage, processing simulations 90 times faster than Penelope. This speed promotes the creation of quick and accurate training sets for deep learning models, allowing for the efficient prediction of elemental concentrations from EDS spectra, thereby circumventing the substantial costs associated with standard databases.
Doctoral, Ph.D. Thesis : Quantitative X-ray microanalysis of oxygen using scanning electron microscope.
With the increasing demand for advanced materials like high-temperature materials, wear-resistant materials, and ceramics among others, which usually contain light elements like oxygen, nitrogen and boron, precise quantification of light elements is becoming more and more necessary. His Ph.D. work focuses on the development of a technique for the quantification of oxygen (using φ(ρz) and f-ratio method) by calculating an accurate mass absorption coefficient for this element and considering the effect of bonding on its value. He uses the SU-8000, SU-8230 and SU-9000 SEM/EDS instruments for studying the x-ray emission of the materials of interest as well as the NX-5000 Triple-Beam FIB to make the samples necessary to his project. His work also involves using Monte Carlo modeling to deduce the mass absorption coefficients from experimental data.
Doctoral, Ph.D. Thesis : Controlling the FIB-SEM with Deep Learning for Automated Acquisitions and Image Quality Improvement.
Sabrina's research aims to automate workflows for SEMs and FIB SEMs, incorporating image processing tasks during acquisitions to produce appropriate image quality for quantitative microscopy. More precisely, she developed an optimization method for image acquisition and segmentation on the SU-8230 based on a deep learning model trained with experimental and simulated data.
Doctoral, Ph.D. Thesis : Low-voltage STEM-EELS elemental quantification for lithium material characterization.
After a B.Sc. in chemistry and a M.Sc.A in chemical engineering in Sherbrooke University. Nicolas joined Pr. Gauvin's research group as a PhD student in January 2019. He works on the development of methods using low voltage (30 keV) CRYO-STEM-EELS. The goal in using low-voltage STEM is to reduce the knock-on damage induced in beam sensitive materials in lithium ion’s batteries. For his project he mostly works with the Hitachi SU9000 STEM/EELS and the TS Talos F200X TEM/STEM/EELS.
Maibelin Rosales earned her Ph.D. in Materials Science Engineering from the University of Chile in 2020 and currently works as a researcher at the Advanced Mining Technology Center (AMTC) at the University of Chile. With expertise in materials science, her research is focused on the design, synthesis, and characterization of tunable multifunctional nanomaterials, highlighting the precise control over the morphology, optoelectronic properties, and surface chemistry of function-tailored low-dimensional semiconductors. Morphology engineering of metal-oxide nanomaterials is a key aspect of her work, conferring them high-performance photo-thermal and photo-active behavior for heavy metals and persistent pollutants removal from water, as well as the selective recovery of dissolved metals through photo-oxidation and adsorption processes. Additionally, she is exploring these advanced nanomaterials in green hydrogen production. Currently, she is conducting research as a Visiting Postdoctoral Researcher in the Electron Microscopy Research Group at McGill University, under the supervision of Prof. Gauvin. Here, the focus of her research is to characterize the microstructure, morphology, and chemical composition of various nanostructured semiconductors using the high-resolution SU-8230 and SU-9000 scanning electron microscopes as well as low voltage electron energy loss spectroscopy (LV-EELS). This characterization will allow to elucidate changes in electronic structures, including the tuning of band-gap energy and band-edge potentials, through tailored morphological modifications of these nanomaterials.
Hendrix Demers Ph.D. (2008)
Samantha Rudinsky Ph.D. (2019)
Chaoyi Teng, Ph.D. (2019)
Shirin Kaboli, Ph.D. (2015)
Muhammad Atarian Shandiz, Ph.D. (2015)
Ivonne Carjaval, Ph.D. candidate ()
Frédéric Voisard, Ph.D. candidate (2017)
Stéphanie Bessette, M.Sc. (2018)
Maryam Gozolar, Ph.D. (2018)
Yu Yuan, Ph.D. (2020)
Wei Bin, Ph.D. (2016)
Seyedmahmoud Bayazid, Ph.D. (2023)
Camille Probst, Jean-François Leberre, Philippe Pinnard, Hendrix Demers, Prof. Raynald Gauvin, Dominique Poirier, Jennifer Cocle and Paula Horny at the 2006 Microscopy and Microanalysis Conference held in Chicago.
Quentin Stoyel, M.Sc. (2020)
Camille Probst, Ph.D., (2011) Post Doctoral student.
Philippe Pinnard, M. Ing. (2010) Ph.D. Student Aachen University, Germany.
Dominique Poirier Ph.D. (2009), Researcher, Institute of Industrial Materials, Boucherville, QC.
Jennifer Cocle, M. Ing. (2008), Researcher, IREQ, Varennes, QC.
Jean-Francois Leberre Ph.D. (2007), Researcher, Paprican, Montreal, QC.
Paula Horny, Ph.D. (2005), Professor, CEGEP de Limoilou, QC.
Dominique Drouin, Ph.D. (1998), Professor, University of Sherbrooke, QC.
Pierre Hovington Ph.D. (1997), Researcher, Svante Inc., Vancouver, BC.