arXiv subjects

Yongsoo Yang

Publications and source records attributed to Yongsoo Yang.

At least 19 recordsLinked to original sources

arXiv2025

Correlative 3D Mapping of Structure, Composition, and Valence State Dynamics in Battery Cathodes via Simultaneous ADF-EDS-EELS Tomography

Understanding degradation in battery cathodes and other functional materials requires simultaneous knowledge of structural, chemical, and electronic changes in three dimensions (3D). Here, we present a simultaneous ADF-EDS-EELS tomography method that enables 3D mapping of atomic structure, composition, valence states, and transition metal inhomogeneity within a single, low-dose STEM tilt series acquisition. Applied to LiNi1/3Co1/3Mn1/3O2 (NCM111) particles at different electrochemical cycling stages, this method reveals nanoscale degradation processes with full spatial correlation. We observe that while chemical composition evolves uniformly throughout the entire primary particle, valence state changes and transition metal segregation are strongly depth-dependent and concentrated near the surface. This coexistence of bulk and surface-driven degradation dynamics reveals distinct mechanisms acting at different spatial scales. The evolution of inhomogeneity and valence states deviates from simple phase transition models, highlighting the roles of ion migration and dissolution-driven segregation. Our findings establish valence state gradients and nanoscale inhomogeneity as active contributors to cathode failure. More broadly, this correlative 3D platform opens new opportunities for studying redox-driven transformations in fields such as neuromorphic computing and heterogeneous catalysis, where composition-structure-function coupling is inherently three-dimensional.

cond-mat.mtrl-sci↗

arXiv2025

Advancing atomic electron tomography with neural networks

Accurate determination of three-dimensional (3D) atomic structures is crucial for understanding and controlling the properties of nanomaterials. Atomic electron tomography (AET) offers non-destructive atomic imaging with picometer-level precision, enabling the resolution of defects, interfaces, and strain fields in 3D, as well as the observation of dynamic structural evolution. However, reconstruction artifacts arising from geometric limitations and electron dose constraints can hinder reliable atomic structure determination. Recent progress has integrated deep learning, especially convolutional neural networks, into AET workflows to improve reconstruction fidelity. This review highlights recent advances in neural network-assisted AET, emphasizing its role in overcoming persistent challenges in 3D atomic imaging. By significantly enhancing the accuracy of both surface and bulk structural characterization, these methods are advancing the frontiers of nanoscience and enabling new opportunities in materials research and technology.

cond-mat.mtrl-sci↗

arXiv2025

Spatial correlations of charge density wave order across the transition in 2H-NbSe2

Charge density waves (CDWs) involve coupled amplitude and phase degrees of freedom, but direct access to local amplitude correlations remains experimentally challenging. Here, we report cryogenic four-dimensional scanning transmission electron microscopy (4D-STEM) measurements of CDW ordering in a 2H-NbSe2 flake of 24 nm thickness, enabled by liquid helium-based cooling. By mapping the spatial distribution of CDW superlattice intensities at nanometer-scale resolution and analyzing their autocorrelations, we extract the temperature-dependent correlation length associated with the local amplitude of the CDW order parameter, independent of global phase coherence. Our results reveal that a finite local CDW amplitude is already established well above the transition temperature. When the system is cooled below the transition temperature down to 20 K, the correlation length extends to nearly 110 nm, and the local CDW amplitude is found to strongly anticorrelate with the local strain field.

cond-mat.str-el↗

arXiv2025

Polymorphic spin ordering in a single-crystalline cobalt-doped Fe3GaTe2

A single crystalline system typically stabilizes a unique state for spin ordering below a critical temperature. Certain materials exhibit multiple magnetic states, driven by structural phase transitions under varying thermodynamic conditions. Recently, van der Waals magnets have demonstrated subtle interlayer exchange interactions, offering a promising approach to electrically control spin states without structural transformation. Here, we report the emergence of three distinct magnetic states, ferromagnetic ordering and both collinear and non-collinear antiferromagnetic orderings, in a layered single crystalline magnet, cobalt-doped Fe3GaTe2 ((Co, Fe)3GaTe2). These three magnetic phases occur without structural phase transitions, a phenomenon we designate as polymorphic spin ordering in the material. The introduction of 16% Co-doping in Fe3GaTe2 modulates the interlayer magnetic interaction, enabling multiple spin orderings within the same lattice system with three critical temperatures: a Curie temperature for a ferromagnetic state (Tc=210 K) and two Neel temperatures for the collinear (TN1=110 K) and non-collinear (TN2=30 K) antiferromagnetic states. Our findings are supported by magnetic force microscopy, first-principles calculations, and circular dichroism angular photoemission spectroscopy, which reveals varying spin ordering and changes in the topological band structure and Berry curvature at different temperatures within the single-crystalline (Co, Fe)3GaTe2.

cond-mat.mtrl-sci↗

arXiv2025

Crystal nucleation and growth in high-entropy alloys revealed by atomic electron tomography

High-entropy alloys (HEAs) balance mixing entropy and intermetallic phase formation enthalpy, creating a vast compositional space for structural and functional materials (1-6). They exhibit exceptional strength-ductility trade-offs in metallurgy (4-10) and near-continuum adsorbate binding energies in catalysis (11-16). A deep understanding of crystal nucleation and growth in HEAs is essential for controlling their formation and optimizing their structural and functional properties. However, atomic-scale nucleation in HEAs challenges traditional theories based on one or two principal elements (17-23). The intricate interplay of structural and chemical orders among multiple principal elements further obscures our understanding of nucleation pathways (5,24-27). Due to the lack of direct three-dimensional (3D) atomic-scale observations, previous studies have relied on simulations and indirect measurements (28-32), leaving HEA nucleation and growth fundamentally elusive. Here, we advance atomic electron tomography (33,34) to resolve the 3D atomic structure and chemical composition of 7,662 HEA and 498 medium-entropy alloy nuclei at different nucleation stages. We observe local structural order that decreases from core to boundary, correlating with local chemical order. As nuclei grow, structural order improves. At later stages, most nuclei coalesce without misorientation, while some form coherent twin boundaries. To explain these experimental observations, we propose the gradient nucleation pathways model, in which the nucleation energy barrier progressively increases through multiple evolving intermediate states. We expect these findings to not only provide fundamental insights into crystal nucleation and growth in HEAs, but also offer a general framework for understanding nucleation mechanisms in other materials.

cond-mat.mtrl-sci↗

arXiv2024

Atomic-scale 3D structural dynamics and functional degradation of Pt alloy nanocatalysts during the oxygen reduction reaction

Pt-based electrocatalysts are the primary choice for fuel cells due to their superior oxygen reduction reaction (ORR) activity. To enhance ORR performance and durability, extensive studies have investigated transition metal alloying, doping, and shape control to optimize the three key governing factors for ORR: geometry, local chemistry, and strain of their surface and subsurface. However, systematic optimization remains incomplete, as it requires an atomic-scale understanding of these factors and their dynamics over potential cycling, as well as their relationship to ORR activity. Here, we implement neural network-assisted atomic electron tomography to measure the 3D atomic structural dynamics and their effects on the functional degradation of PtNi alloy catalysts. Our results reveal that PtNi catalysts undergo shape changes, surface alloying, and strain relaxation during cycling, which can be effectively mitigated by Ga doping. By combining geometry, local chemistry, and strain analysis, we calculated the changes in ORR activity over thousands of cycles and observed that Ga doping leads to higher initial activity and greater stability. These findings offer a pathway to understanding 3D atomic structural dynamics and their relation to ORR activity during cycling, paving the way for the systematic design of durable, high-efficiency nanocatalysts.

cond-mat.mtrl-sci↗

arXiv2023

Singular Hall response from a correlated ferromagnetic flat nodal-line semimetal

Topological quantum phases have been largely understood in weakly correlated systems, which have identified various quantum phenomena such as spin Hall effect, protected transport of helical fermions, and topological superconductivity. Robust ferromagnetic order in correlated topological materials particularly attracts attention, as it can provide a versatile platform for novel quantum devices. Here, we report singular Hall response arising from a unique band structure of flat topological nodal lines in combination with electron correlation in an itinerant, van der Waals ferromagnetic semimetal, Fe3GaTe2, with a high Curie temperature of Tc=360 K. High anomalous Hall conductivity violating the conventional scaling, resistivity upturn at low temperature, and a large Sommerfeld coefficient are observed in Fe3GaTe2, which implies heavy fermion features in this ferromagnetic topological material. Our circular dichroism in angle-resolved photoemission spectroscopy and theoretical calculations support the original electronic features in the material. Thus, low-dimensional Fe3GaTe2 with electronic correlation, topology, and room-temperature ferromagnetic order appears to be a promising candidate for robust quantum devices.

cond-mat.str-el↗

arXiv2023

Revealing the Three-Dimensional Arrangement of Polar Topology in Nanoparticles

In the early 2000s, low dimensional systems were predicted to have topologically nontrivial polar structures, such as vortices or skyrmions, depending on mechanical or electrical boundary conditions. A few variants of these structures have been experimentally observed in thin film model systems, where they are engineered by balancing electrostatic charge and elastic distortion energies. However, the measurement and classification of topological textures for general ferroelectric nanostructures have remained elusive, as it requires mapping the local polarization at the atomic scale in three dimensions. Here we unveil topological polar structures in ferroelectric BaTiO3 nanoparticles via atomic electron tomography, which enables us to reconstruct the full three-dimensional arrangement of cation atoms at an individual atom level. Our three-dimensional polarization maps reveal clear topological orderings, along with evidence of size-dependent topological transitions from a single vortex structure to multiple vortices, consistent with theoretical predictions. The discovery of the predicted topological polar ordering in nanoscale ferroelectrics, independent of epitaxial strain, widens the research perspective and offers potential for practical applications utilizing contact-free switchable toroidal moments.

cond-mat.mtrl-sci↗

arXiv2023

Optical detection of bond-dependent and frustrated spin in the two-dimensional cobalt-based honeycomb antiferromagnet Cu3Co2SbO6

Two-dimensional honeycomb antiferromagnet becomes an important class of materials as it can provide a route to Kitaev quantum spin liquid, characterized by massive quantum entanglement and fractional excitations. The signatures of its proximity to Kitaev quantum spin liquid in the honeycomb antiferromagnet includes anisotropic bond-dependent magnetic responses and persistent fluctuation by frustration in paramagnetic regime. Here, we propose Cu3Co2SbO6 heterostructures as an intriguing honeycomb antiferromagnet for quantum spin liquid, wherein bond-dependent and frustrated spins interact with optical excitons. This system exhibits antiferromagnetism at 16 K with different spin-flip magnetic fields between a bond-parallel and bond-perpendicular directions, aligning more closely with the generalized Heisenberg-Kitaev than the XXZ model. Optical spectroscopy reveals a strong excitonic transition coupled to the antiferromagnetism, enabling optical detection of its spin states. Particularly, such spin-exciton coupling presents anisotropic responses between bond-parallel and bond-perpendicular magnetic field as well as a finite spin-spin correlation function around 40 K, higher than twice its N\'eel temperature. The characteristic temperature that remains barely changed even under strong magnetic fields highlights the robustness of the spin-fluctuation region. Our results demonstrate Cu3Co2SbO6 as a unique candidate for the quantum spin liquid phase, where the spin Hamiltonian and quasiparticle excitations can be probed and potentially controlled by light.

cond-mat.str-el↗

arXiv2022

Multislice Electron Tomography using 4D-STEM

Electron tomography offers important three-dimensional (3D) structural information which cannot be observed by two-dimensional imaging. By combining annular dark field scanning transmission electron microscopy (ADF-STEM) with aberration correction, the resolution of electron tomography has reached atomic resolution. However, tomography based on ADF-STEM inherently suffers from several issues, including a high electron dose requirement, poor contrast for light elements, and artifacts from image contrast nonlinearity. Here, we developed a new method called MultiSlice Electron Tomography (MSET) based on 4D-STEM tilt series. Our simulations show that multislice-based 3D reconstruction can effectively reduce undesirable reconstruction artifacts from the nonlinear contrast, allowing precise determination of atomic structures with improved sensitivity for low-Z elements, at considerably low electron dose conditions. We expect that the MSET method can be applied to a wide variety of materials, including radiation-sensitive samples and materials containing light elements whose 3D atomic structures have never been fully elucidated due to electron dose limitations or nonlinear imaging contrast.

cond-mat.mtrl-sci↗

arXiv2022

Revealing 3-dimensional core-shell interface structures at the single-atom level

Nanomaterials with core-shell architectures are prominent examples of strain-engineered materials, where material properties can be designed by fine-tuning the misfit strain at the interface. Here, we elucidate the full 3D atomic structure of Pd@Pt core-shell nanoparticles at the single-atom level via atomic electron tomography. Full 3D displacement fields and strain profiles of core-shell nanoparticles were obtained, which revealed a direct correlation between the surface and interface strain. It also showed clear Poisson effects at the scale of the full nanoparticle as well as the local atomic bonds. The strain distributions show a strong shape-dependent anisotropy, whose nature was further corroborated by molecular statics simulations. From the observed surface strains, the surface oxygen reduction reaction activities were predicted. These findings give a deep understanding of structure-property relationships in strain-engineerable core-shell systems, which could pave a new way toward direct control over the resulting catalytic properties.

cond-mat.mtrl-sci↗

arXiv2022

Atomic-scale identification of the active sites of nanocatalysts

Alloy nanocatalysts have found broad applications ranging from fuel cells to catalytic converters and hydrogenation reactions. Despite extensive studies, identifying the active sites of nanocatalysts remains a major challenge due to the heterogeneity of the local atomic environment. Here, we advance atomic electron tomography to determine the 3D local atomic structure, surface morphology and chemical composition of PtNi and Mo-doped PtNi nanocatalysts. Using machine learning trained by density functional theory calculations, we identify the catalytic active sites for the oxygen reduction reaction from experimental 3D atomic coordinates, which are corroborated by electrochemical measurements. By quantifying the structure-activity relationship, we discover a local environment descriptor to explain and predict the catalytic active sites at the atomic level. The ability to determine the 3D atomic structure and chemical species coupled with machine learning is expected to expand our fundamental understanding of a wide range of nanocatalysts.

physics.chem-ph↗

arXiv2021

Direct observation of three-dimensional atomic structure of twinned metallic nanoparticles and their catalytic properties

We determined a full 3D atomic structure of a dumbbell-shaped Pt nanoparticle formed by a coalescence of two nanoclusters using deep learning assisted atomic electron tomography. Formation of double twin boundary was clearly observed at the interface, while substantial anisotropy and disorder were also found throughout the nanodumbbell. This suggests that the diffusion of interfacial atoms mainly governed the coalescence process, but other dynamic processes such as surface restructuring and plastic deformation were also involved. A full 3D strain tensor was clearly mapped, which allows direct calculation of the oxygen reduction reaction activity at the surface. Strong tensile strain was found at the protruded region of the nanodumbbell, which results in an improved catalytic activity on {100} facets. This work provides important clues regarding the coalescence mechanism and the relation between the atomic structure and catalytic property at the single-atom level.

cond-mat.mtrl-sci↗

arXiv2020

Single-atom level determination of 3-dimensional surface atomic structure via neural network-assisted atomic electron tomography

Functional properties of nanomaterials strongly depend on their surface atomic structure, but they often become largely different from their bulk structure, exhibiting surface reconstructions and relaxations. However, most of the surface characterization methods are either limited to 2-dimensional measurements or not reaching to true 3D atomic-scale resolution, and single-atom level determination of the 3D surface atomic structure for general 3D nanomaterials still remains elusive. Here we show the measurement of 3D atomic structure of a Pt nanoparticle at 15 pm precision, aided by a deep learning-based missing data retrieval. The surface atomic structure was reliably measured, and we find that <100> and <111> facets contribute differently to the surface strain, resulting in anisotropic strain distribution as well as compressive support boundary effect. The capability of single-atom level surface characterization will not only deepen our understanding of the functional properties of nanomaterials but also open a new door for fine tailoring of their performance.

cond-mat.mtrl-sci↗

arXiv2019

Correlating 3D atomic defects and electronic properties of 2D materials with picometer precision

The exceptional electronic, optical and chemical properties of two-dimensional materials strongly depend on the 3D atomic structure and crystal defects. Using Re-doped MoS2 as a model, here we develop scanning atomic electron tomography (sAET) to determine the 3D atomic positions and crystal defects such as dopants, vacancies and ripples with a precision down to 4 picometers. We measure the 3D bond distortion and local strain tensor induced by single dopants for the first time. By directly providing experimental 3D atomic coordinates to density functional theory (DFT), we obtain more truthful electronic band structures than those derived from conventional DFT calculations relying on relaxed 3D atomic models, which is confirmed by photoluminescence measurements. We anticipate that sAET is not only generally applicable to the determination of the 3D atomic coordinates of 2D materials, heterostructures and thin films, but also could transform ab initio calculations by using experimental 3D atomic coordinates as direct input to better predict and discover new physical, chemical and electronic properties.

cond-mat.mtrl-sci↗

arXiv2019

Capturing Nucleation at 4D Atomic Resolution

Nucleation plays a critical role in many physical and biological phenomena ranging from crystallization, melting and evaporation to the formation of clouds and the initiation of neurodegenerative diseases. However, nucleation is a challenging process to study in experiments especially in the early stage when several atoms/molecules start to form a new phase from its parent phase. Here, we advance atomic electron tomography to study early stage nucleation at 4D atomic resolution. Using FePt nanoparticles as a model system, we reveal that early stage nuclei are irregularly shaped, each has a core of one to few atoms with the maximum order parameter, and the order parameter gradient points from the core to the boundary of the nucleus. We capture the structure and dynamics of the same nuclei undergoing growth, fluctuation, dissolution, merging and/or division, which are regulated by the order parameter distribution and its gradient. These experimental observations differ from classical nucleation theory (CNT) and to explain them we propose the order parameter gradient (OPG) model. We show the OPG model generalizes CNT and energetically favours diffuse interfaces for small nuclei and sharp interfaces for large nuclei. We further corroborate this model using molecular dynamics simulations of heterogeneous and homogeneous nucleation in liquid-solid phase transitions of Pt. We anticipate that the OPG model is applicable to different nucleation processes and our experimental method opens the door to study the structure and dynamics of materials with 4D atomic resolution.

cond-mat.mtrl-sci↗

arXiv2017

GENFIRE: A generalized Fourier iterative reconstruction algorithm for high-resolution 3D imaging

Tomography has made a radical impact on diverse fields ranging from the study of 3D atomic arrangements in matter to the study of human health in medicine. Despite its very diverse applications, the core of tomography remains the same, that is, a mathematical method must be implemented to reconstruct the 3D structure of an object from a number of 2D projections. In many scientific applications, however, the number of projections that can be measured is limited due to geometric constraints, tolerable radiation dose and/or acquisition speed. Thus it becomes an important problem to obtain the best-possible reconstruction from a limited number of projections. Here, we present the mathematical implementation of a tomographic algorithm, termed GENeralized Fourier Iterative REconstruction (GENFIRE). By iterating between real and reciprocal space, GENFIRE searches for a global solution that is concurrently consistent with the measured data and general physical constraints. The algorithm requires minimal human intervention and also incorporates angular refinement to reduce the tilt angle error. We demonstrate that GENFIRE can produce superior results relative to several other popular tomographic reconstruction techniques by numerical simulations, and by experimentally by reconstructing the 3D structure of a porous material and a frozen-hydrated marine cyanobacterium. Equipped with a graphical user interface, GENFIRE is freely available from our website and is expected to find broad applications across different disciplines.

physics.comp-ph↗

arXiv2017

Single-Shot 3D Diffractive Imaging of Core-Shell Nanoparticles with Elemental Specificity

We report 3D coherent diffractive imaging of Au/Pd core-shell nanoparticles with 6 nm resolution on 5-6 femtosecond timescales. We measured single-shot diffraction patterns of core-shell nanoparticles using very intense and short x-ray free electron laser pulses. By taking advantage of the curvature of the Ewald sphere and the symmetry of the nanoparticle, we reconstructed the 3D electron density of 34 core-shell structures from single-shot diffraction patterns. We determined the size of the Au core and the thickness of the Pd shell to be 65.0 +/- 1.0 nm and 4.0 +/- 0.5 nm, respectively, and identified the 3D elemental distribution inside the nanoparticles with an accuracy better than 2%. We anticipate this method can be used for quantitative 3D imaging of symmetrical nanostructures and virus particles.

physics.ins-det↗