The increase in atmospheric carbon dioxide（CO₂）concentration is likely to be related to global warming and climate change. Photosynthesis can convert atmospheric CO₂ using light and water to produce many kinds of organic molecules. The lack of crystal structures of the enzymes involved in photosynthetic carbon assimilation has hindered the understanding of the detailed mechanisms. Crystallographic studies of the enzymes involved in photosynthetic carbon assimilation provide new insights into the molecular mechanisms.

Driven by improvement of the computer speed and tremendous efforts of crystallographers and equipment manufacturers, X-ray structure analysis has recently become relatively easy and requires no specialized knowledge. On the other hand, synchrotron radiation diffraction experiments have mainly aimed at advanced structural analysis, including electron density analysis, taking advantage of stable and intense X-rays. In recent years, demand for the use of the facility in the materials field has increased, but researchers unfamiliar with synchrotron radiation experiments have felt difficulty in use. Based on my experience in developing conventional diffractometers and software at the equipment manufacturer where I worked after obtaining my degree, I have promoted the development of advanced synchrotron radiation X-ray diffraction systems at SPring-8, a large synchrotron radiation facility. In particular, I have been responsible for the single crystal structure analysis beamline（BL02B1）and the powder diffraction beamline（BL02B2）, which have a wide range of user groups and diverse requirements for instrumental performance, and engaged in instrument development. In addition, I have also worked on structural analysis of functional materials and clarified their structure-function relationships. Among them, I introduce fruitful results on generation process of magnesia cement and design of spin crossover Fe（II）complexes. I believe that such upgrading of synchrotron radiation diffraction systems and development research of functional materials could not be performed without hardware and software knowledge which I learned at the equipment manufacturer.

A technique for the structural analysis of crystalline and amorphous phase mixtures using X-ray total scattering measurement is developed. The technique extracts the pair distribution function of the amorphous phase by subtracting of that of the crystalline phase from the observed scattering. Li₂VO₂F, a high-capacity cathode material in lithium-ion batteries, partially forms an amorphous phase upon charging. Applying the technique to the Li₂VO₂F material, the contribution of the hidden amorphous phase is obtained. Analysis of the pair distribution function of the amorphous phase allows the three-dimensional atomic configurations associated with the material function to be visualized. The structural analysis technique is expected to provide an understanding of the material properties from the viewpoint of the microscopic structure in the amorphous phase, not only of the battery materials but also of any mixtures of crystalline and amorphous phases.

The circadian clock, an internal timekeeping system created and utilized by organisms adapting to the Earth’s Rotation, is driven by the rhythmic chemical reaction cycles of biomolecules such as clock proteins and clock genes. The cyanobacterial clock system is composed of three clock proteins, KaiA, KaiB, and KaiC, which concert the circadian rhythms even in the test tube in the presence of adenosine-tri-phosphate（ATP）. KaiC orchestrates the rhythm through an ATP hydrolysis（ATPase cycle）and auto-phosphorylation/dephosphorylation（Phospho-cycle）. The N-terminal ring of functional KaiC hexamer determines the clock speed during the ATPase cycle, while another C-terminal ring changes phosphorylation status like time stamps during Phospho-cycle. Structural biology has been investigating the origin of the circadian rhythm in the KaiC double-ring structure for a quarter century. We conducted the comprehensive structural analyses on KaiC and finally identified structural factors that ensure the smooth and tight communication between those distant two catalytic sites, which is critical for the rhythmicity. We also revealed that the time information is propagated to the entire cell through the rearrangement of the KaiC double ring and the assembly/disassembly of KaiA and KaiB.

Three cases in our recent activities are presented, each of those is motivated through collaborations with experimental groups and industry. The topics include the implementation of a modern algorithm that efficiently generates crystal structure models of solid solutions, a method that identifies systematic changes reflected in XRD patterns and tells us which peaks to look out for, and the search for new crystal phases using genetic algorithms.

In this review article, the authors present their recent work on efficiently synthesizing new metal-organic frameworks （MOFs） and optimizing their functionality by utilizing machine learning techniques. We successfully synthesized a series of new anionic Ln-BDC-MOFs by focusing on the unexplored chemical reaction space. We also adopted the Bayesian optimization technique to optimize the stoichiometric ratio of metal-salts in Ln-MOF, and successfully synthesized MIL-103 （Ln（BTB）（H₂O）, H₃BTB＝1,3,5-tris（4-carboxyphenyl）benzene）, which emits white light. These synthetic exploration approach can significantly reduce the experimental effort required to discover new materials.

Reliable evaluation of single crystal specimens before time-consuming diffraction data collection is essential to improve throughput of crystallographic work. A quantitative evaluation was proposed that uses the averaged isotropic temperature factor derived from Wilson plot. However, this technique has limited capability to distinguish minor structural differences, e.g., difference between before and after guest-exchange in host-guest crystal. Here I review our newly proposed technology for analyzing the factor more precisely than the conventional way. In this technology, by implementing Bayesian inference, we were able to sensitively distinguish isomorphic crystals containing different guest molecules just using preliminary-collected small diffraction data.

Organic crystals have presented flexible features in contrast with inorganic crystals, and are expected for the future applications of optoelectronics and active matters. Pharmaceuticals are also the utilization of the organic crystal family. This article presents the basis of the data science in organic crystals, and a few examples of application of my research. An attempt is to screen the structural phase transition of organic crystals, and another topic is to compare structural representation of molecular and crystal structures regressed by graph neural network.