Hideaki Iwasawa

Development of spin- and angle-resolved photoemission spectromicroscopy under magnetic field

Researcher

Hideaki Iwasawa

Outline

In this work, we will develop a novel spin- and angle-resolved photoemission spectromicroscopy apparatus, enabling us to apply a magnetic field based on our expertise in microscopic and spin measurements, as well as measurement informatics. We will elucidate the relationships among band structure, spin texture, and magnetic structure in novel topological materials by visualizing local electronic and spin states along with their magnetic responses. Our goal is to gain insights into the high functionality of these novel materials, establish fundamental principles, and provide guidance for exploring and designing new functional materials.

Kenichi Umeda

AI-driven automation of high-speed AFM measurement and analysis

Researcher

Kenichi Umeda

Outline

I automate high-speed AFM measurement and analysis technology, and measure intrinsically disordered proteins (IDPs) as a model case to benchmark the developed automated system. Because IDPs are the cause of various diseases, and by establishing basic technology to elucidate their structures and mechanisms of action, we can provide solutions to SDG3 (health and welfare).

Yuta Kimura

Establishment of an Informatics-Integrated Measurement Framework for Exploring the Spatiotemporal Dynamics of Chemical Reactions in Particle Ensembles

Researcher

Yuta Kimura

Outline

Chemical/electrochemical devices such as rechargeable batteries employ composite components comprising numerous constituent particles. Within these particle ensembles, unique chemical reactions, unanticipated from the individual particle behavior, emerge. This research directly observes such chemical reaction dynamics inherent to these particle ensembles and analyzes the measurement data using a data-driven approach, aiming to establish a methodology for understanding the mechanisms underlying the collective behavior and exploiting them for device design.

Ayaka Sakata

Comprehensive optimization of data acquisition and analysis based on probabilistic inference

Researcher

Ayaka Sakata

Outline

In this project, we will study the optimization of advanced measurement systems using statistical methods, mutual optimization of data acquisition and data analysis, and decision support systems that link measurement and statistical science researchers. We focus on the similarities between the exploration of measurement conditions, decision making and statistical modeling based on prediction. Further, by introducing graphical representations that visually represent measurement conditions and possible scenarios, we will overcome the barriers between measurement science and statistical science and bring them closer together.

Takakazu Seki

Visualization of interfacial molecular environment in real-space using super-resolution interface-specific spectroscopy

Researcher

Takakazu Seki

Outline

The electronic and optical properties of the devices are critically affected by molecular structure and orientation at materials’ interfaces. In this study, by extending the super-resolution optical scheme to interface-specific vibrational spectroscopy, I aim to develop a novel all-optical interface-specific spectroscopic tool with an extreme resolution in three-dimensional space. This technique will provide ~100 times improvement of spatial resolution in the horizontal direction compared to the conventional interface-specific vibrational spectroscopy, thereby allowing us to access real-space molecular information with the orientational and depth analysis of chemical moieties of the interfacial molecules.

Terumasa Tadano

Advancing first-principles prediction of physical properties through the introduction of finite-temperature effects

Researcher

Terumasa Tadano

Outline

Highly functional metastable phases and emergent properties are expected to be hidden within the finite-temperature range of the phase space. However, computational exploration of these materials from first principles is a challenge due to the lack of accurate and efficient methods that can take into account the finite-temperature effects. This research aims to develop a simulation method that can accurately and efficiently predict temperature-induced structural and property modulations by modeling elementary excitations, such as phonons and magnons, from first principles. To demonstrate the effectiveness of this method, we will apply it to the exploration of functional materials that emerge at finite temperatures.

Yasunari Tamai

Challenge to overcome the “Gap time window” in the transient absorption spectroscopy

Researcher

Yasunari Tamai

Outline

Transient absorption spectroscopy enables us to quantitatively measure the dynamics of short-lived transient species, making it one of the most powerful spectroscopic techniques in the field of photophysics, photochemistry, and photobiology. However, it has been difficult to accurately measure the “Gap time window” near nanosecond by using conventional transient absorption spectroscopies. This study aims to realize accurate measurement of the “Gap time window” through fusion of transient absorption spectroscopy and informatics.

Satoru Tokuda

Innovation in a guiding principle for modeling based on observed data

Researcher

Satoru Tokuda

Outline

Mathematical modeling has promoted our understanding of natural phenomena since the 17th century. However, recent developments in data science reveal some practical problems. This project focuses on three issues: model un-identifiability, measurement noise, and model discrepancy. The researcher develops a methodology that deals with them all at once and the foundation of Bayesian inference that supports the methodology. Based on these, the researcher proposes a guiding principle for modeling based on observed data, enabling understanding of every phenomenon without ambiguity.

Kei Nakayama

Atomic-resolution and in-situ observation of charge and discharge reactions of rechargeable batteries

Researcher

Kei Nakayama

Outline

This project aims to achieve atomic-resolution and in-situ observation of charge and discharge reactions of rechargeable batteries. By constructing a microscope system capable of regulating the reaction region, controlling the sample orientation, and reducing electron exposure while maintaining image quality, I aim to dynamically visualize changes in ion distribution and accompanying local structural alterations in electrode materials at the atomic level. With the obtained dynamic imaging data, I aim to contribute to the establishment of a theoretical framework in nanoelectrochemistry from a nonequilibrium and microscopic perspective.

Koji Hashiguchi

High-resolution trace measurement system using high-finesse cavity

Researcher

Koji Hashiguchi

Outline

In technology-intensive industries, there is an increasing demand for accurate measurement of trace components in gases. The goal of this project is to develop a technology for the direct measurement of trace components in gases with high sensitivity and high accuracy using a high-finesse cavity. Through the acquisition of data with high temporal and spatial resolution and the use of informatics (machine learning), a new measurement system will make it possible to measure what was previously invisible, contributing to the development of materials.

Bin Feng

Development of electron beam irradiation-based atomic resolution dynamic STEM imaging and its application to materials science

Researcher

Bin Feng

Outline

In this project, we aim to establish an atomic-resolution dynamic observation method using a scanning transmission electron microscope (STEM) with sub-angstrom spatial resolution. This will be achieved by utilizing electron beam irradiation and integrating it with in-situ TEM holders capable of applying various external fields. Furthermore, by applying this method to various materials, we aim to elucidate dynamic processes of lattice defects inside materials at the atomic level, which have been extremely challenging to analyze so far.

Kazuki Miyata

Innovative subnanoscale analysis of solid-liquid interfacial structures by localization three dimensional atomic force microscopy

Researcher

Kazuki Miyata

Outline

Atomic Force Microscopy (AFM) is capable of atomic-resolution imaging of the surface in liquid environment. Recent progress in the AFM technique has enabled high-speed and three-dimensional imaging at solid-liquid interfaces with subnanometer-scale resolution. However, its data analysis methods are limited to extensions of conventional image processing, hindering the effective extraction of valuable subnanoscale information. In this PRESTO project, I aim to develop a “localization 3D-AFM” technique based on statistical analysis using a large number of in-liquid 3D-AFM, enabling the novel subnanoscale analysis of solid-liquid interfacial structures.

Tomokazu Yamamoto

The development of next-generation electron tomography techniques with deep learning

Researcher

Tomokazu Yamamoto

Outline

In this project, a new multimodal electron tomography technique, capable of high-accuracy 3D reconstruction, will be developed by combining 4D-STEM diffraction imaging, elemental and chemical state mapping using STEM-EDX/EELS, and image reconstruction techniques using deep learning. The goal of this project is to achieve high-precision 3D atomic arrangement analysis of lattice defects, surfaces and interfaces in polycrystalline materials, and other non-periodic atomic arrangements.