High-throughput ensemble characterization of individual core-shell nanoparticles with quantitative 3D density from XFEL single-particle imaging
Do Hyung Cho, Zhou Shen, Yungok Ihm, Dae Han Wi, Chulho Jung, Daewoong Nam, Sangsoo Kim, Sang-Youn Park, Kyung Sook Kim, Daeho Sung, Heemin Lee, Jae-Yong Shin, … 展开作者
Do Hyung Cho, Zhou Shen, Yungok Ihm, Dae Han Wi, Chulho Jung, Daewoong Nam, Sangsoo Kim, Sang-Youn Park, Kyung Sook Kim, Daeho Sung, Heemin Lee, Jae-Yong Shin, Junha Hwang, Sung-Yun Lee, Su Yong Lee, Sang Woo Han, Do Young Noh, N. Duane Loh, Changyong Song
The structures, as building-blocks for designing functional nanomaterials, have fueled the development of versatile nanoprobes to understand local structures of noncrystalline specimens. Progresses in analyzing structures of individual specimens with atomic scale accuracy have 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 new algorithm 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 strains. The 3D elastic energy distribution is further corroborated by molecular dynamics simulations to gain mechanical insight at atomic level. This work establishes a new route to high-throughput characterization of individual specimens in large ensembles, hence overcoming statistical deficiency while providing quantitative information at the nanoscale.
The emerging optical multiplexing within nanoscale shows super-capacity in encoding information by using the time-domain fingerprints from uniform nanoparticles. However, the optical diffraction limit compromises the decoding throughput and accuracy of the nanoparticles during wide-field imaging. This, in turn, challenges the quality of nanoparticles to afford the modulated excitation condition, and further to retain the multiplexed optical fingerprints for super-resolution multiplexing. Here we report a tailor-made time-domain super-resolution method with the lifetime-engineered upconversion …
Bubbles have a rich history as transducers in particle-physics experiments. In a solid-state analogue, we use bubble domains in nanomagnetic films to measure magnetic nanoparticles. This technique can determine the magnetic orientation of a single nanoparticle in a fraction of a second, and generate a full hysteresis loop in a few seconds, which is much faster than any other reported technique. We achieve this unprecedented speed by tuning the nanomagnetic properties of the films, including the Dzyaloshinskii-Moriya interaction, in the first application of topological protection from the skyrm…
In this work, we present an open access database for surface and vacancy-formation energies using classical force-fields (FFs). These quantities are essential in understanding diffusion behavior, nanoparticle formation and catalytic activities. FFs are often designed for a specific application, hence, this database allows the user to understand whether a FF is suitable for investigating particular defect and surface-related material properties. The FF results are compared to density functional theory and experimental data whenever applicable for validation. At present, we have 17,506 surface e…
High-index dielectric metasurfaces featuring Mie-type electric and magnetic resonances have been of a great interest in a variety of applications such as imaging, sensing, photovoltaics and others, which led to the necessity of an efficient large-scale fabrication technique. To address this, here we demonstrate the use of single-pulse laser interference for direct patterning of an amorphous silicon film into an array of Mie resonators. The proposed technique is based on laser-interference-induced dewetting. A precise control of the laser pulse energy enables the fabrication of ordered dielectr…
Controlled integration of metallic nanoparticles (NPs) onto photonic nanostructures enables realization of complex devices for extreme light confinement and enhanced light-matter interaction. This can be achieved combining Nanoparticle-on-Mirror (NPoM) nanocavities with the light manipulation capabilities of micron-scale metallic antennas and/or photonic integrated waveguides. However, metallic nanoparticles are usually deposited via drop-casting, which prevents their accurate positioning. Here we present a methodology for precise transfer and positioning of individual NPs onto different photo…
Bottom-up production of semiconductor nanomaterials is often accompanied by inhomogeneity resulting in a spread in electronic properties which may be influenced by the nanoparticle geometry, crystal quality, stoichiometry or doping. Using photoluminescence spectroscopy of a population of more than 20,000 individual Zn-doped GaAs nanowires, we reveal inhomogeneity in, and correlation between doping and nanowire diameter by use of a Bayesian statistical approach. Recombination of hot-carriers is shown to be responsible for the photoluminescence lineshape; by exploiting lifetime variation across …
College of Chemical Engineering, Zhejiang University of Technology（浙江工业大学化学工程学院）；School of Physical Science and Technology, Ningbo University（宁波大学物理科学与技术学院）；Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences（中国科学院宁波材料技术与工程研究所）；Institute of Vegetables, Ningbo Academy of Agricultural Sciences（宁波市农业科学院蔬菜研究所）
Antisolvent crystallization methods are frequently used to fabricate high-quality perovskite thin films, to produce sizable single crystals, and to synthesize nanoparticles at room temperature. However, a systematic exploration of the effect of specific antisolvents on the intrinsic stability of multicomponent metal halide perovskites has yet to be demonstrated. Here, we develop a high-throughput experimental workflow that incorporates chemical robotic synthesis, automated characterization, and machine learning techniques to explore how the choice of antisolvent affects the intrinsic stability…
Catalysis informatics is constantly developing, and significant advances in data mining, molecular simulation, and automation for computational design and high-throughput experimentation have been achieved. However, efforts to reveal the mechanisms of complex supported nanoparticle catalysts in cyberspace have proven to be unsuccessful thus far. This study fills this gap by exploring N$_2$ dissociation on a supported Ru nanoparticle as an example using a universal neural network potential. We calculated 200 catalyst configurations considering the reduction of the support and strong metal-suppo…
A new approach is presented to obtain candidate structures from atomic pair distribution function (PDF) data in a highly automated way. It fetches, from web-based structural databases, all the structures meeting the experimenter's search criteria and performs structure refinements on them without human intervention. It supports both x-ray and neutron PDFs. Tests on various material systems show the effectiveness and robustness of the algorithm in finding the correct atomic crystal structure. It works on crystalline and nanocrystalline materials including complex oxide nanoparticles and nanowir…
Electron tomography has achieved higher resolution and quality at reduced doses with recent advances in compressed sensing. Compressed sensing (CS) theory exploits the inherent sparse signal structure to efficiently reconstruct three-dimensional (3D) volumes at the nanoscale from undersampled measurements. However, the process bottlenecks 3D reconstruction with computation times that run from hours to days. Here we demonstrate a framework for dynamic compressed sensing that produces a 3D specimen structure that updates in real-time as new specimen projections are collected. Researchers can beg…
Despite the recent surge in interest in Cu$_{3-x}$P for catalysis, batteries, and plasmonics, the electronic nature of Cu$_{3-x}$P remains unclear. Some studies have shown evidence of semiconducting behavior, whereas others have argued that Cu$_{3-x}$P is a metallic compound. Here, we attempt to resolve this dilemma on the basis of combinatorial thin-film experiments, electronic structure calculations, and semiclassical Boltzmann transport theory. We find strong evidence that stoichiometric, defect-free Cu$_3$P is an intrinsic semimetal, i.e., a material with a small overlap between the valenc…
Quantifying the Distribution of Biexciton Emission Efficiencies in Colloidal Quantum Shells
Debye Institute for Nanomaterials Science, Utrecht University（乌得勒支大学德拜纳米科学研究所）；The Center for Photochemical Sciences, Bowling Green State University（鲍灵格林州立大学光化学科学中心）；Department of Physics, Bowling Green State University（鲍灵格林州立大学物理系）
Physics-aware neural networks enable robust and full atomic structure determination via low-dose atomic electron tomography
Beijing National Laboratory for Molecular Sciences, Center for Integrated Spectroscopy, College of Chemistry and Molecular Engineering, Peking University（北京大学化学与分子工程学院，集成光谱中心，北京分子科学国家实验室）
Real-Time Atomic-Resolution Electron Phase Imaging without Probe Calibration via Ptychography-Supervised Learning
Fudan University（复旦大学）；National Tsing Hua University（国立清华大学）；National Center for Instrumentation Research, National Institutes of Applied Research（国家应用研究院国家仪器研究中心）；Institute for Infocomm Research, A*STAR（新加坡科技研究局资讯通信研究院）；The University of Sydney（悉尼大学）
