A5056737807- X-ray Diffraction in Crystallography
- Crystallization and Solubility Studies
- Lanthanide and Transition Metal Complexes
- Magnetism in coordination complexes
- Spectroscopy and Chemometric Analyses
- Metal-Organic Frameworks: Synthesis and Applications
- Spectroscopy Techniques in Biomedical and Chemical Research
- Water Quality Monitoring and Analysis
- Metal complexes synthesis and properties
- Organic and Molecular Conductors Research
- Crystallography and molecular interactions
- Machine Learning in Materials Science
- Advanced Chemical Sensor Technologies
- Luminescence and Fluorescent Materials
- Magnetic Properties of Alloys
- Molecular Junctions and Nanostructures
- Magnetic properties of thin films
- Photochromic and Fluorescence Chemistry
- Computational Drug Discovery Methods
- Molecular Sensors and Ion Detection
- Covalent Organic Framework Applications
- Advanced NMR Techniques and Applications
- Magnetic Properties and Applications
- Advancements in Battery Materials
- Conducting polymers and applications
Tokyo University of Science
2024-2025
Tohoku University
2020-2023
Graduate School USA
2020
Sendai University
2020
Redox-active metal–organic frameworks (MOFs) have great potential for use as cathode materials in lithium-ion batteries (LIBs) with large capacities because the organic ligands can undergo multiple-electron redox processes. However, most MOFs are electrical insulators, limiting their application electrode materials. Here, we report an electron-conductive MOF a 2,5-dihydroxy-1,4-benzoquinone (dhbq) ligand, Fe(dhbq). This compound had conductivity of 5 × 10–6 S cm–1 at room temperature due to...
Recent advances in artificial intelligence have significantly improved spectral data analysis. In this study, we used unsupervised machine learning to classify chemical compounds based on infrared (IR) images, without relying prior knowledge. The potential of for classification was demonstrated by extracting IR images from the Spectral Database Organic Compounds and converting them into 208620-dimensional vector data. Hierarchical clustering 230 revealed distinct main clusters (A–G), each...
Recent advances in artificial intelligence have significantly improved spectral data analysis. In this study, we used unsupervised machine learning to classify chemical compounds based on infrared (IR) images, without relying prior knowledge. The potential of for classification was demonstrated by extracting IR images from the Spectral Database Organic Compounds and converting them into 208,620-dimensional vector data. Hierarchical clustering 230 revealed distinct main clusters (A-G), each...
A flexible coordination polymer with a naphthalenediimide core exhibited reversible desorption-adsorption of solvent molecules and an enhancement electrical conductivity (∼10-7 S cm-1) upon chemical reduction using hydrazine.
We report the synthesis, characterization, and electronic properties of quinoid-based three-dimensional metal-organic framework [Fe2(dhbq)3]. The MOF was synthesized without using cations as a template, unlike other reported X2dhbq3-based coordination polymers, crystal structure determined by single-crystal X-ray diffraction. entirely different from [Fe2(X2dhbq3)]2-; three independent 3D polymers were interpenetrated to give overall structure. absence led microporous structure, investigated...
The recent advancements in artificial intelligence have greatly improved spectral data analysis. Here, we explored using unsupervised machine learning to classify chemical compounds based on IR spectrum images without relying prior knowledge. research demonstrated the potential of classification by extracting from SDBS database and converting them into 218196-dimensional vector data. hierarchical clustering 227 revealed distinct main clusters (A-G), each with specific subclusters showing...
Recent advances in artificial intelligence have significantly improved spectral data analysis. In this study, we used unsupervised machine learning to classify chemical compounds based on infrared (IR) images, without relying prior knowledge. The potential of for classification was demonstrated by extracting IR images from the Spectral Database Organic Compounds and converting them into 194300-dimensional vector data. Hierarchical clustering 227 revealed distinct main clusters (A–G), each...
Abstract N , N’ ‐dihydroxy‐1,4,5,8‐naphthalenetetracarboxdiimide (NDI−(OH) 2 ) has attracted much attention in recent years, because its doubly deprotonated state, (O−NDI−O) 2− metal‐coordination ability and characteristic electronic transition useful for designing optical functions. In contrast, a molecular crystal with the mono‐deprotonated (HO−NDI−O) − ion remains unknown. We herein report an organic containing non‐disproportionated ions, which are connected by very strong O−H−O hydrogen...
Lanthanide (Ln) compounds are common research targets in the field of magnetism and optics. Their properties arise from electrons localized f-orbital. Moreover, effect covalency between lanthanide ligands on has attracted significant attention. We have provided insight into Gd–Pt bond (of heterometallic Ln-Pt complexes: {[Pt(PhSAc)4]Ln[(PhSAc)4Pt]} NEt4·2DMF (Ln = Y(0), La(1), Gd(2); PhSAc thiobenzoate, NEt4 tetraethylammonium)); single-crystal polarized X-ray absorption near edge structure...
Naphthalenediimide (NDI) is generally a yellowish to reddish chromophore, which shows vapochromism by the alternation of charge-transfer (CT) interactions at NDI core. On contrary, we discovered that deprotonation N,N′-dihydroxy-1,4,5,8-naphthalenetetracarboxdiimide (NDI-(OH)2) gave bluish organic salt with hydrochromic property, has been rare in conventional derivatives. basis structural analyses and calculation, origin hydrochromism can be explained change hydrogen-bond interaction between...
Recent advances in artificial intelligence have significantly improved the spectral data analysis. In this study, we used unsupervised machine learning to classify chemical compounds based on infrared (IR) images, without relying prior knowledge. This study demonstrated potential of for classification by extracting IR images from Spectral Database Organic Compounds (SDBS) database and converting them into 218196-dimensional vector data. Hierarchical clustering 227 revealed distinct main...
Recent advances in artificial intelligence have significantly improved spectral data analysis. In this study, we used unsupervised machine learning to classify chemical compounds based on infrared (IR) images, without relying prior knowledge. The potential of for classification was demonstrated by extracting IR images from the Spectral Database Organic Compounds and converting them into 194300-dimensional vector data. Hierarchical clustering 227 revealed distinct main clusters (A–G), each...
Estimating the coordination environment of non-crystalline metal complexes has been an important issue. In this study, we applied machine learning methods to extract features number and elements from X-ray absorption near edge structure (XANES) spectra 44 Ni complexes. The were clearly classified according elements. similarity between was visualized as a 2D map by dimensionality reduction using multidimensional scaling (MDS). structural in
Theoretical calculations are typically utilized for examining intermetallic interactions. However, to validate the theory, experimental confirmation of existence these interactions is necessary. We synthesized new heterometallic Ln–Pt complexes, NEt4{[Pt(PhSAc)4]Ln[(PhSAc)4Pt]}·2DMF (Ln: lanthanoid = Gd (1), Tb (2), Dy (3), PhSAc benzothioacetate, NEt4 tetraethylammonium), in which both diamagnetic Pt(II) ions interact with central Ln(III) ion. Typically, not detected because distance...
The first interdigitated MX-type chain complex with infinite π-stacked arrays was synthesized. synchronization between a Pt-Br⋯ and π-stacking periodicities led to the longest M-X-M distance (6.6978(15) Å) nil or negligible intervalence charge transfer, which is essential realize Robin-Day class I mixed valence state in MX chains.
Theoretical calculations are typically utilized for examining intermetallic interactions. However, to validate theory, experimental confirmation of the existence these interactions is necessary. We synthesized new heterometallic Ln–Pt complexes, NEt4{[Pt(PhSAc)4]Ln[(PhSAc)4Pt]}·2DMF (Ln: lanthanoid = Gd (1), Tb (2), Dy (3), PhSAc benzothioacetate, NEt4 tetraethylammonium), in which both diamagnetic Pt(II) ions interact with central Ln(III) ion. Typically, not detected, because distance...