publications

2025

1. Frustrated phonon with charge density wave in vanadium Kagome metal

   Seung-Phil Heo, Choongjae Won, Heemin Lee, and 12 more authors

   Nature Communications, 2025

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   The formation of a star-of-David charge density wave superstructure, resulting from the coordinated displacements of vanadium ions on a corner-sharing triangular lattice, has garnered significant attention to comprehend the influence of electron–phonon interaction within geometrically intricate lattice of Kagome metals, specifically AV3Sb5 (where A represents K, Rb, or Cs). However, understanding of the underlying mechanism behind charge density wave formation, coupled with symmetry-protected lattice vibrations, remains elusive. Here, from femtosecond time-resolved X-ray scattering experiments, we reveal that the phonon mode, associated with cesium ions’ out-of-plane motion, becomes frustrated in the charge density wave phase. Furthermore, we observed the photoinduced emergence of a metastable charge density wave phase, facilitated by alleviating the frustration. By not only elucidating the longstanding puzzle surrounding the intervention of phonons but introducing the phononic frustration, this research offers insights into the competition between phonons and periodic lattice distortions, a phenomenon widespread in other correlated quantum materials including layered high-temperature superconductors.

2. Deep-learning real-time phase retrieval of imperfect diffraction patterns from X-ray free-electron lasers

   Sung Yun Lee, Do Hyung Cho, Chulho Jung, and 4 more authors

   npj Computational Materials, 2025

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   Machine learning is attracting surging interest across nearly all scientific areas by enabling the analysis of large datasets and the extraction of scientific information from incomplete data. Data-driven science is rapidly growing, especially in X-ray methodologies, where advanced light sources and detection technologies produce vast amounts of data that exceed meticulous human inspection capabilities. Despite the increasing demands, the full application of machine learning has been hindered by the need for data-specific optimizations. In this study, we introduce a new deep-learning-based phase retrieval method for imperfect diffraction data. This method provides robust phase retrieval for simulated data and performs well on partially damaged and noisy single-pulse diffraction data from X-ray free-electron lasers. Moreover, the method significantly reduces data processing time, facilitating real-time image reconstructions that are crucial for high-repetition-rate data acquisition. This approach offers a reliable solution to the phase problem to be widely adopted across various research areas confronting the inverse problem.

3. Development of the Nanobeam X-ray Experiments instrument at PAL-XFEL

   Jangwoo Kim†, HyoJung Hyun†, Seonghan Kim, and 13 more authors

   Journal of Synchrotron Radiation, 2025

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   A Nanobeam X-ray Experiments (NXE) instrument was developed and installed at the hard X-ray beamline of the Pohang Accelerator Laboratory X-ray Free Electron Laser. This instrument consists of a diagnostic system, focusing optics, an X-ray diffraction endstation and a femtosecond laser delivery system. The NXE instrument enables sophisticated X-ray experiments using nanofocused X-rays. At a 9.5 keV X-ray energy, the beam was successfully focused to 390 nm × 230 nm at the focal plane using Kirkpatrick–Baez mirrors. Following the successful commissioning experiments in December 2021 and April 2022, the instrument became available for regular user experiments in January 2023. The first user experiment was conducted in January 2024. This article provides detailed information on the beamline optics, the NXE instrument, and its performance and capabilities.

2024

1. Off-Axis X-Ray Vortex Beam Ptychography

   Sung Yun Lee, Eunyoung Park, Sinwoo Kim, and 4 more authors

   ACS Photonics, 2024

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   Structured light has sparked interest by introducing a parameter to adjust light–matter interactions in photonics applications. While phase structures applied to their wavefronts enable functional imaging probes, their application in X-ray microscopy has been limited due to their complex configuration. Here, we present X-ray vortex beam ptychography using an off-axis spiral zone plate, showcasing quantitative nanoscale imaging with straightforward manipulation of the phase structure. The simple experimental setup enhances adaptability to most light sources. This coherent X-ray microscopy, capable of resolving nontrivial topological states with additional phase structures of light, is poised to advance photonics research by leveraging topological features.

2. Inverted nucleation for photoinduced nonequilibrium melting

   Junha Hwang†, Yungok Ihm†, Daewoong Nam, and 12 more authors

   Science Advances, 2024

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   Ultrafast photoinduced melting provides an essential platform for studying nonequilibrium phase transitions by linking the kinetics of electron dynamics to ionic motions. Knowledge of dynamic balance in their energetics is essential to understanding how the ionic reaction is influenced by femtosecond photoexcited electrons with notable time lag depending on reaction mechanisms. Here, by directly imaging fluctuating density distributions and evaluating the ionic pressure and Gibbs free energy from two-temperature molecular dynamics that verified experimental results, we uncovered that transient ionic pressure, triggered by photoexcited electrons, controls the overall melting kinetics. In particular, ultrafast nonequilibrium melting can be described by the reverse nucleation process with voids as nucleation seeds. The strongly driven solid-to-liquid transition of metallic gold is successfully explained by void nucleation facilitated by photoexcited electron–initiated ionic pressure, establishing a solid knowledge base for understanding ultrafast nonequilibrium kinetics.

3. Development of the multiplex imaging chamber at PAL-XFEL

   Junha Hwang, Sejin Kim, Sung Yun Lee, and 12 more authors

   Journal of Synchrotron Radiation, 2024

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   Various X-ray techniques are employed to investigate specimens in diverse fields. Generally, scattering and absorption/emission processes occur due to the interaction of X-rays with matter. The output signals from these processes contain structural information and the electronic structure of specimens, respectively. The combination of complementary X-ray techniques improves the understanding of complex systems holistically. In this context, we introduce a multiplex imaging instrument that can collect small-/wide-angle X-ray diffraction and X-ray emission spectra simultaneously to investigate morphological information with nanoscale resolution, crystal arrangement at the atomic scale and the electronic structure of specimens.

2023

1. Nanoscale Three-Dimensional Network Structure of a Mesoporous Particle Unveiled via Adaptive Multidistance Coherent X-ray Tomography

   Sung Yun Lee†, Do Hyung Cho†, Sung Chan Song†, and 7 more authors

   ACS Nano, 2023

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   Mesoporous nanoparticles provide rich platforms to devise functional materials by customizing the three-dimensional (3D) structures of nanopores. With the pore network as a key tuning parameter, the noninvasive and quantitative characterization of these 3D structures is crucial for the rational design of functional materials. This has prompted researchers to develop versatile nanoprobes with a high penetration power to inspect various specimens sized a few micrometers at nanoscale 3D resolutions. Here, with adaptive phase retrievals on independent data sets with different sampling frequencies, we introduce multidistance coherent X-ray tomography as a noninvasive and quantitative nanoprobe to realize high-resolution 3D imaging of micrometer-sized specimens. The 3D density distribution of an entire mesoporous silica nanoparticle was obtained at 13 nm 3D resolution for quantitative physical and morphological analyses of its 3D pore structure. The morphological features of the whole 3D pore network and pore connectivity were examined to gain insight into the potential functions of the particles. The proposed multidistance tomographic imaging scheme with quantitative structural analyses is expected to advance studies of functional materials by facilitating their structure-based rational design.

2021

1. Denoising low-intensity diffraction signals using k-space deep learning: Applications to phase recovery

   Sung Yun Lee, Do Hyung Cho, Chulho Jung, and 4 more authors

   Physical Review Research, 2021

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   Phase recovery is a well-known inverse problem prevalent across science disciplines and attracts active research interests to develop a number of theoretical and experimental methods. Recent developments in artificial intelligence have further prompted research activities in processing the experimentally collected imperfect data, but applications have been limited to slow-varying data such as real images. Experimental noise present in largely fluctuating diffraction data, in particular, adds practical challenges to hamper consistent phase recovery. Here, we introduce a convolutional neural-network assisted k-space denoising method that can directly manage noisy diffraction signals. It showed superior performance on denoising the diffraction data, which promote improved phase recovery from noise-buried single-pulse diffraction signals obtained by the x-ray free-electron laser. Adapting our method to general diffraction data can expand boundaries of interpretable data and enhance observability of faint objects with weak signals.

2. High-Throughput 3D Ensemble Characterization of Individual Core–Shell Nanoparticles with X-ray Free Electron Laser Single-Particle Imaging

   Do Hyung Cho†, Zhou Shen†, Yungok Ihm, and 16 more authors

   ACS Nano, 2021

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   The structures as building blocks for designing functional nanomaterials have fueled the development of versatile nanoprobes to understand local structures of noncrystalline specimens. Progress in analyzing structures of individual specimens with atomic scale accuracy has been notable recently. In most cases, however, only a limited number of specimens are inspected lacking statistics to represent the systems with structural inhomogeneity. Here, by employing single-particle imaging with X-ray free electron lasers and algorithms for multiple-model 3D imaging, we succeeded in investigating several thousand specimens in a couple of hours and identified intrinsic heterogeneities with 3D structures. Quantitative analysis has unveiled 3D morphology, facet indices, and elastic strain. The 3D elastic energy distribution is further corroborated by molecular dynamics simulations to gain mechanical insight at the atomic level. This work establishes a route to high-throughput characterization of individual specimens in large ensembles, hence overcoming statistical deficiency while providing quantitative information at the nanoscale.

2020

1. A Comprehensive Evaluation of the Process of Copying a Complex Figure in Early- and Late-Onset Alzheimer Disease: A Quantitative Analysis of Digital Pen Data

   Ko Woon Kim†, Sung Yun Lee†, Jongdoo Choi, and 4 more authors

   Journal of Medical Internet Research, 2020

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   Background: The Rey-Osterrieth Complex Figure Test (RCFT) is a neuropsychological test that is widely used to assess visual memory and visuoconstructional deficits in patients with cognitive impairment, including Alzheimer disease (AD). Patients with AD have an increased tendency for exhibiting extraordinary behaviors in the RCFT for selecting the drawing area, organizing the figure, and deciding the order of images, among other activities. However, the conventional scoring system based on pen and paper has a limited ability to reflect these detailed behaviors. Objective: This study aims to establish a scoring system that addresses not only the spatial arrangement of the finished drawing but also the drawing process of patients with AD by using digital pen data. Methods: A digital pen and tablet were used to copy complex figures. The stroke patterns and kinetics of normal controls (NCs) and patients with early-onset AD (EOAD) and late-onset AD (LOAD) were analyzed by comparing the pen tip trajectory, spatial arrangement, and similarity of the finished drawings. Results: Patients with AD copied the figure in a more fragmented way with a longer pause than NCs (EOAD: P=.045; LOAD: P=.01). Patients with AD showed an increased tendency to draw the figures closer toward the target image in comparison with the NCs (EOAD: P=.005; LOAD: P=.01) Patients with AD showed the lower accuracy than NCs (EOAD: P=.004; LOAD: P=.002). Patients with EOAD and LOAD showed similar but slightly different drawing behaviors, especially in space use and in the initial stage of drawing. Conclusions: The digitalized complex figure test evaluated copying performance quantitatively and further elucidated the patients’ ongoing process during copying. We believe that this novel approach can be used as a digital biomarker of AD. In addition, the repeatability of the test will delineate the process of executive functions and constructional organization abilities with disease progression.

2019

1. Detecting Abuser Group in MMORPG by using Ranking System based on Game Transaction Network

   Sungyun Lee*, Sunghun Kim, Inhae Seok, and 1 more author

   Proceedings of the Korea Software Congress 2019 (KSC2019), 2019

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   본 논문에서는 게임 내 거래 네트워크를 분석하는 방법론으로 community ecology 분야에서 ranking system 측정을 위해 사용되는 알고리즘인 David’s score를 활용하였다. 이를 게임 데이터에 맞추어 변형한 selective David’s score를 개발하였으며, 실제 MMORPG 거래소 데이터에 적용하였다. 아이템별 평균가 대비 거래 가격 구간을 나누어 적용해 목표하는 이상 거래를 효과적으로 탐지했으며, label이 존재하지 않기 때문에 해당 게임의 행동 로그 및 상태 정보를 이용하여 패턴 확인 및 검증까지 진행하였다.