Research

Scanning Transmission Electron Microscope

: A shuttle guiding us to atomic world

▷ A machine learning solution for electrode characterization

A machine learning-driven electron spectroscopic imaging (ESI) approach enables nanoscale visualization and statistical analysis of structural degradation in PEMFC electrodes. This method simultaneously maps Pt catalysts, ionomer, and carbon support, revealing cycling-induced morphological changes and offering critical insight into degradation mechanisms for MEA optimization (Applied Catalysis B: Environment and Energy 382, 125911, 2025).

▷ Sparse section imaging-based deep learning electron tomography

Deep learning-empowered electron tomography visualizes 3D structure of porous carbon supports in PEMFC with a few image data, which reduces the data requirement by > 95% while maintaining a high reliability (Journal of Energy Chemistry 104, 795-806, 2025).

▷ Revealing the role of oxygen vacancy in an oxide solid electrolyte

This study unveiled the hidden role of oxygen vacancy (VO) in facilitating Li-ion transport in lithium lanthanum titanate solid electrolytes. The VO is directionally interconnected to form a 2D network parallel to the c-plane and widens the directional Li-ion passages, which lowers the energy barrier of Li-ion migration (ACS Energy Letters 9 (11), 5606-5615, 2024).

▷ 4D STEM-based domain mapping for perovskite solar cells

Our 4D STEM-based crystallographic domain mapping unfolded the mystery of aging-induced efficiency improvement of perovskite solar cells. It revealed that aging can induce partial lattice strain relaxation, a core agent for enhancing power conversion efficiency (ACS Energy Letters 9(7), 3618-3627, 2024).

▷ The interplay of structure-cation defect-oxygen vacancy in doped HfO2 film

Our multimodal 4D-STEM (PA)CBED/EDX/EELS at multiple length scales revealed the complicated interplay of structure-cation defect-oxygen vacancy in La-doped HfO2 films. The results show that the spatial distribution of oxygen vacancies coupled with La defects plays a significant role in stabilizing orthorhombic ferroelectrics (ACS Nano 17(19), 19076-19086, 2023).

▷ Unveiling self-oxidation resistance mechanism of a curved Cu surface

Our pico-scale precision electron microscopy revealed that the porous copper nanostructures self-regulate the giant oxidation resistance by constructing a curved surface that generates a series of monoatomic steps, followed by shrinkage of the lattice spacing of one or two surface layers (Advanced Materials 35(42), 2210564, 2023).

▷ Deep learning catalyst particle analysis with Attention U-Net

We propose a rapid, automated, and reliable analytical method for the morphological distribution of Pt-based electrocatalyst nanoparticles (NPs) with deep learning processing for a massive image dataset, providing valuable information required for engineering electrocatalyst NPs and understanding their structural evolution in response to an electrochemical reaction (Materials Today Energy 36, 101348, 2023).

Source code available at: https://github.com/SKKU-STEM/PMA-Net

▷ Elucidating the growth mechanism of a single crystal Cu thin film

Our electron microscopy describes in detail the initial growth of copper thin films required for mono-atom step-level flat surfaces (MSFSs). Deposition using atomic sputtering epitaxy leads to the coherent merging of trillions of islands into a coplanar layer, eventually forming an MSFS, for which the key factor is suggested to be the individual deposition of single atoms (Nature Communications 14, 685, 2023).

▷ Single particle-level spectroscopic mapping for defect distributions

Computation-aided STEM-EELS showed that the distributions of the surface oxygen vacancies and the reduced Ti valencies enclosing the stoichiometric core were responsible for the enhanced photocatalytic activity (Applied Catalysis B-Environmental 322, 122140, 2023).

▷ Segmented electron tomography for PEM-fuel cell analysis

Our advanced segmented electron tomography visualizes 3D structure of carbon support in proton exchange membrane fuel cells (PEM-FCs) and explains the structural degradation phenomenon of the carbon support as the cycling of the PEM-FC proceeds (Journal of Energy Chemistry 74, 359-367, 2022).

▷ Mechanism for ion enhanced polarization in doped HfO2

Hafnium oxide is an exciting material because it has ferroelectric behavior that makes it attractive for various device applications. The multimodal investigation based on microscopy and spectroscopy showed that the ferroelectric properties improve by bombarding films of hafnium oxide with a beam of helium ions. The ion bombardment creates oxygen vacancies and strain changes from helium implantation that push more of the polycrystalline samples into the ferroelectric orthorhombic phase (Science 376(6594), 731-738, 2022).

▷ Hybrid deep learning crystallography with 4D-STEM

Deep learning crystallographic analysis unequivocally addresses structure problems for sub-10 nm polycrystalline hafnium zirconium oxide thin films. A hybrid deep learning-based methodology for mapping crystal phases was developed in combination with 4D-STEM (PA)CBED (Small 18(18), 2107620, 2022).

▷ Superb oxidation resistance of Cu uncovered by electron microscopy

Comprehensive atomic-resolution microscopy revealed that wafer-scale Cu(111) single-crystal thin films free of multilayer step edges show a semi-permanent oxidation resistance. Our study not only provides decisive insight into the oxidation mechanism of copper but also suggests a pragmatic nonoxidative approach towards the mass production of pure metal thin films as a breakthrough for industrial applications (Nature 603(7901), 434-438, 2022).

▣ 2022년 10대 나노기술 우수연구개발성과 선정 (나노기술연구협의회)

▷ Unveiled doping mechanisms in oxide catalysts

Electron microscopy and spectroscopy combined with theoretical modeling can directly resolve the site-specific doping phenomena of transition metals in SnO2 nanoparticles. Our approach, including picoscale-precision strain and oxygen vacancy mapping, provides a clear view of the roles of site-selective dopants, thus improving the understanding of the resulting physical properties (Applied Catalysis B-Environmental 305, 121083, 2022).

▷ Deep learning algorithm for automated defect quantification in 2D TMDs

Our deep learning-assisted quantification algorithm reduces heavy load of data processing for researchers, which has hindered the pace of design and development of two-dimensional transition metal dichalcogenides (2D TMDs). Furthermore, an integrated understanding of the atomic-scale behavior of point defects in 2D TMDs under environmental stimuli is now available without data reduction or sampling (Advanced Science 8, 2101099, 2021).

Source code available at: https://github.com/SKKU-STEM/2D_TMD_Quantification_with_Deeplearning

▷ Picoscale precision lattice strain analysis for multidomain 2D TMDs

Our work with STEM-based statistical lattice strain analysis provided the first demonstration of successful control of lattice structure of anisotropic ReS2, resulting in isotropic responses in optical scattering and electrical transport by the electron doping of Li ions (ACS Nano 15, 13770-13780, 2021).

▷ Atomic-scale chemical mapping of Cu dopants (0.2 at.%) in a thermoelectric alloy by STEM-EDX

We have successfully mapped copper dopants added by 0.2 at% into a multi-component thermoelectric alloy (Bi2Te2.7Se0.3) system, where the role of dopants is decisive in determining the properties of the material, using our advanced energy dispersive X-ray spectroscopy (EDX) spectrum imaging (SI) in STEM with a 1-Å level drift stability. This unprecedented stability is central to achieving a clear atomic-level chemical mapping of dopants under the concentration below one atomic percentage (Materials Today Physics 17, 100347, 2021).

▷ High-resolution STEM-EELS analysis of doped ZnO nanoparticles

Our atomic-scale STEM observations combined with site-specific electron energy loss spectroscopy revealed that the two transition metal ions substitute for Zn, in different valence states (Cr3+ and Co2+, respectively), without inducing a phase change of the host ZnO matrix (wurtzite structure) (Journal of Materials Chemistry A 8, 25345-25354, 2020).

▷ Cation vacancy mapping by STEM-EDX

Our STEM-EDX chemical mapping can provide an atomic-level picture of what truly occurs with cation vacancies at an oxide interface. Cation vacancies of Sr and Ti in SrTiO3 film and Nb ions diffused from a Nb:SrTiO3 substrate are revealed to collaboratively participate in the formation of a nonstoichiometric interface layer for charge compensation, resulting in the tetragonal phase transition (Materials Today Physics 16, 100302, 2021).

▷ Atomic resolution analysis of nanoparticles by STEM-EELS/EDX

Our STEM-EELS/EDX-based work revealed that surface oxygen vacancies in anatase-type Fe@TiO2 nanoparticles for superior photocatalytic activities can be readily controlled by simple pH treatment. A comprehensive analysis at the atomic to mesoscopic scale shows that the point defects are maximized and predominantly formed on the surface of the anatase NPs, resulting in electronically different core-shell nanostructures (Applied Surface Science 507, 144916, 2020).

▷ 3D electron tomography for Li ion batteries

Our work demonstrates how the geometrical parameters of active cathode materials are inextricably linked to their battery performance, based on multimodal/multiscale characterizations (ACS Applied Materials & Interfaces 11, 4017, 2019).

▷ Atom counting analysis for 2D materials

Our work investigates the hitherto unsolved conundrum of how organic chemicals can heal chalcogen vacancies in MoS2 monolayer at the atomic scale. We observed chalcogen vacancy healing by an organic molecule at the atomic-level for the first time and revealed that this healing phenomenon is highly unusual but energetically favorable, involving the dissociation and reconstruction of reactive chemical species at the vacancy sites (Nano Letters 18(7), 4523, 2018).

▷ Oxygen octahedral tilt mapping for complex oxide thin films

Our work provides the first demonstration of octahedra-derived multiferroic properties that can be stabilized in a thin film form without the help of complex chemical modifications. The complex interplay between octahedral tilts and polar/magnetic orders is examined by advanced STEM and magnetic measurements, revealing that the tilt symmetry is critical to tailoring the multiferroicity (Advanced Functional Materials 19, 1800839, 2018).

▷ Valence state mapping for Li ion batteries

Using atom-resolved STEM-EDX/EELS, this study reveals that the electrochemical properties of Li(NixCoyMnz)O2 (NCM) materials are decisively determined by the interplay of combined disordering of cations and the relevant chemical/electronic changes (Journal of Materials Chemistry A 6, 16111, 2018).

▷ Atomic-resolution chemical mapping for energy materials

Our atomic-resolution STEM-EDX chemical mapping was conducted for the direct visualization of atomic-scale interstitial and antisite defects in complete single phase Ti1–xHfxNiSn1–ySby half-Heusler (HH) TE alloys with the highest zT value in n-type HH alloys (Advanced Materials 29, 1702091, 2017) .

▷ Polarization mapping for ferroelectric materials

By a combination of microscopy and spectroscopy techniques, we directly observed for the first time the field effect in ferroelectric material that exhibits switchable electrical polarization at the ferroelectric-electrode interface on the atomic scale (Nature Materials 13, 1019, 2014).

▷ Oxygen vacancy mapping for solid oxide fuel cell cathode materials

Local oxygen stoichiometry in functional oxides has been a long-standing challenge that needs to be addressed in order to elucidate the physics of strongly correlated oxides and improve materials performance for applications ranging from fuel cells and sensors to memristive data storage. The method developed in this work quantifies oxygen vacancy distribution and homogeneity, which directly control the operation of solid-oxide fuel cells and are intrinsically coupled with magnetic, electronic, and transport properties of oxides (Nature Materials 11, 888, 2012).

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