Kenjiro Fujimoto

The advancement of functional materials requires experimental strategies capable of efficiently exploring high-dimensional spaces defined by composition and processing parameters. This challenge is particularly pronounced in multicomponent inorganic powder materials, such as lithium-ion battery materials, solid electrolytes, and thermoelectric oxides, where even subtle differences in composition, phase assemblage, or crystallographic structure can significantly influence not only electrochemical properties but also reliability and manufacturing stability. In this presentation, I will introduce our high-throughput exploration of multicomponent oxide powder materials based on solution- and slurry-derived processes, and, as a recent topic, discuss our ongoing efforts to achieve rapid acquisition of crystallographic information using synchrotron radiation, with a focus on how these approaches can be connected to materials informatics.

Cu‐Al‐Mn alloys are promising materials for industrial applications because of their excellent workability and low transformation stress. In this work, Cu‐Al‐Mn alloys with compositions in the range of 64.8–78.23 at% Cu, 12.2–31.6 at% Al, and 0–17.87 at% Mn were synthesized via arc melting, and their martensitic transformation temperature and latent heat were investigated. The austenite finish temperature ( A _f ) decreased with increasing Al or Mn composition ratios. The latent heat of the transformation from the martensitic to austenitic phase showed a maximum value of 7.216 J g ⁻¹ for 70.4Cu‐23.8Al‐5.86Mn. A correlation between the latent heat, average martensitic transformation start temperature, and A _f ( T ₀ ) was observed. The latent heat increased with increasing T ₀ , up to 20.55°C, and decreased at higher temperatures. This positive correlation was consistent with the Clausius–Clapeyron equation. The composition containing only the phases involved in the martensitic transformation exhibited a higher latent heat than the composition with unrelated phases at the same transformation temperature. This has led to interesting results that contribute to the study of solid‐state refrigerants using Cu‐Al‐Mn alloys.

Introduction to the International Symposium on Inorganic and Environmental Materials 2023 themed issue.

Cu-based superelastic shape memory alloys are promising for low-stress elastocaloric cooling. We have synthesized bulk alloys of 68Cu–16Al–16Zn under different conditions in order to promote its grain growth and enhance its elastocaloric properties. High-temperature x-ray diffraction of untreated 68Cu–16Al–16Zn alloy showed that the phase boundary between the α + β mixed phases and the high temperature phase (β phase) was between 973 K and 1023 K. Based on this result, the 68Cu–16Al–16Zn alloy was heated and cooled in a furnace repeatedly between 773 K and 1173 K. The maximum grain size after heat treatment of the ingot rolled to 67% reached 11.1 mm. The latent heat of the martensitic transformation after grain growth was 6.3 J g⁻¹, which is higher than the previously reported value for the compound. The stress–strain curve of 68Cu–16Al–16Zn rolled to 67% rolling with cyclical heat treatments showed a maximum stress of 106 MPa at 4.5% strain, with adiabatic temperature change of 5.9 K in heating during stress loading and 5.6 K in cooling in stress removal. Furthermore, no fatigue in the stress–strain behavior was observed up to at least 60 000 mechanical cycles at 2% strain.

In recent years, "Materials Genome Initiative (MGI)", "Materials Informatics (MI)", and "Process Informatics (PI)" research have attracted much attention as keywords for high-throughput materials discovery. Much of the MI and PI research that has been published so far emphasizes data mining, statistics, machine learning, and predictive analytics. The MGI proposed by the US government in 2011 indicated that material innovation requires "experimental tools" in addition to "computational tools" and "digital data. "Experimental tools" means the creation of big data using automated high-throughput synthesis, evaluation and analysis systems, but there are not many examples of this development. In order to promote highly accurate materials discovery, a three-way relationship is important. And in order to improve the overall speed of exploration, all processes need to be accelerated. In the production of ceramic powder, which is also the synthesis process of dielectrics, the crystalline phase and grain size vary depending on the raw material manufacturer, purity, sintering atmosphere, sintering temperature, and other conditions. These have a great impact on the physical properties. It is important to create a data set that includes not only composition, phase identification results, lattice parameters, and physical property data, but also detailed experimental process conditions. If the data can be collected in a unified high-throughput experimental environment, it will greatly contribute to data interpolation in MI and PI research. We expect that combining the data obtained from high-throughput automated experiments with the data-driven research found in MI and PI will accelerate more accurate research. To achieve this goal, we are continuing to work on the development of combinatorial technology, a high-throughput synthesis, evaluation, and analysis technique for multi-component ceramic powders. For the preparation of powder samples consisting of a vast number of combinations, we have developed two methods based on wet processes.¹⁾²⁾ These devices allow us to synthesize 100 samples per day, reducing the amount of raw material used per sample to about 1/1000. This has the advantage of not only increasing the high-throughput but also reducing the excessive use of raw materials. After the library is created, the crystal structure needs to be evaluated. In recent years, the high-speed detectors of experimental X-ray diffractometers have made it possible to obtain X-ray diffraction patterns in a short time. In 2014, Gregoire et al. developed a technique to simultaneously collect synchrotron XRD and XRF data for a group of multi-component thin film samples. They developed a technique to collect the data and showed that they could collect at least 5000 patterns per day in less than 18 seconds per sample³⁾. Furthermore, Kusune et al. matched the synchrotron thin-film XRD patterns with the Inorganic Crystal Structure Database (ICSD) using an on-the-fly method, and greatly improved the classification accuracy of structural phases overlapping in the three-component reaction diagram.⁴⁾ The use of XRD patterns for informatics is often discussed between phase information, lattice constants and physical properties, but crystallographic information such as fractional coordinates should be added to the data set if genomic machine learning is to be promoted. In order to obtain the diffraction intensities for high-throughput synthesized samples, which are necessary for structural refinement, collaboration with synchrotron radiation is required. We propose a high-throughput crystallographic information collection process combined with efficient measurement tools and an automated structure refinement program.^5,6) 1) K. Fujimoto et al., Measurement Science and Technology 16 41-45 (2005). 2) K. Fujimoto et al., Solid State Ionics 177 2639-2642 (2006). 3) J. M. Gregoire et al., Journal of Synchrotron Radiation, 21(6), 1262-1268 (2014). 4) Aaron Gilad Kusne et al., Scientific Report, 4: 6367 (2014). 5) A. Aimi et al., ACS Combinatorial Science 22(1) 35-41 (2020). 6) K. Fujimoto et al., ACS Combinatorial Science 22(12) 734-737 (2020).

Hydrogen gas is a promising, clean, and highly efficient energy source. However, to use combustible H₂ gas safety, high-performance and safe gas leakage sensors are required. In this study, transparent and flexible platinum-catalyst-loaded tungsten trioxide (Pt/WO₃) nanoparticle-dispersed membranes were prepared as H₂ gas leakage sensors. The nanoparticle-dispersed membrane with a Pt:W compositional ratio of 1:13 was transparent and exhibited a sufficient color change in response to H₂ gas. The membrane containing 0.75 wt.% of Pt/WO₃ nanoparticles exhibited high transparency over a wide wavelength range and the largest transmittance change in response to H₂ gas among the others. The heat treatment of the particles at 573 K provided sufficient crystallinity and an accessible area for a gasochromic reaction, resulting in a rapid and sensitive response to the presence of H₂ gas. The lower limit of detection of the optimized Pt/WO₃ nanoparticle-dispersed membrane by naked eye was 0.4%, which was one-tenth of the minimum explosive concentration. This novel membrane was transparent as well as flexible and exhibited a clear and rapid color response to H₂. Therefore, it is an ideal candidate sensor for the safe and easy detection of H₂ gas leakage.

Layered rock-salt LiNi_(1−x)/2Co_(1−x)/2Ti_xO₂ (0 ≤ x ≤ 0.1) and LiNi_(1−x)/2Co_{(1−x)/2–0.05}Fe_0.05Ti_xO₂ (0 ≤ x ≤ 0.1) were prepared by the electrostatic spray deposition method, which is one of the solution processes, to investigate the correlation between these crystal structures and electrode properties of the multinary oxides with solid solution of Fe and Ti ions. Even with only 5 % solid solution of Fe, the cycle retention rate after 50 cycles decreased by 5–8 %. Regardless of Fe-substitution/non-substitution, the crystallite size of the powder calcined at 973 K under oxygen atmosphere became finer as the amount of Ti substitution increased. Although Ti ions do not contribute to redox, Ti-substituted materials are improved Li diffusion due to finer crystallite size, and show better discharge capacity and cycle performance as Ti content increased. Not only in the Li–Ni–Co system, but also in the Li–Ni–Co–Fe system, crystallite size refinement and improvement in initial discharge capacity and cycle performance were observed depending on the amount of Ti substitution, indicating that Ti ions contribute to lattice stabilization.