Nanoemulsions have been employed as one of the methods for nano-dispersing poorly water-soluble drugs in mucus. However, most liquid suspension such as the emulsions is washed by the clearance effect on the mucus surface. This study examined the spontaneous emulsification formulation using porous polymer microparticles with mucosal adhesion as the technology for drug permeation enhancement. The nanoemulsion formation expected in this technology could be realized using medium-chain fatty acid triglyceride as the oil component. Moreover, the spontaneous emulsification and the diffusion of the nanoemulsion in mucus proceeded smoothly by using porous particles composed of anionic polymers that have little interaction with mucus components, because mucus is composed of anionic polymer, mucin. It was anticipated that the fine emulsions prepared by this method would enhance drug transport in mucus.

Heat generation characteristics by oxidation and water adsorption of dry coal were estimated at low temperatures (40–80°C) by using a highly sensitive thermogravimetric analysis and differential scanning calorimetry (TG-DSC) apparatus for three types of coal. Oxidation heat could be adequately estimated even at the low temperature of 40°C, where had not been accurately measured in the past. The relationship between the amount of water adsorption and the water adsorption heat was approximated by a convex upward curve with intercept of 0, which didn’t depend on coal type and ambient temperature. Comparison of the oxidation and water adsorption heat of dry coal showed that the water adsorption heat had a significant influence on the self-heating, especially in the temperature range around 40°C, which was the initial stage of self-heating. In addition, under conditions where dry O₂ or wet N₂ was supplied to dry coal, the total amount of oxidation and water adsorption heat was the largest at the low temperature of 40°C.

In the manufacturing industry, there is a growing focus on the application of AI-driven material informatics (MI) and process informatics (PI). However, issues remain in the handling of information that is difficult to convert into data, particularly with regard to image data. While images contain critical information related to material performance, conventional methods have difficulty in accurately analysis. To address these issues, this paper introduces AI technology capable of quantifying images and presents examples that immediately quantify parameters related to particle size, shape, and color. Furthermore, we report on the optimization of manufacturing conditions through the utilization of this quantifiable image information, a capability that was previously unattainable.

Aluminum nitride (AlN) ceramics containing large-sized AlN whiskers were fabricated to investigate their effects on thermal conductivity and mechanical properties. As the whisker content increased, both the relative density and thermal conductivity exhibited a decreasing trend. Microstructural observations of the sintered and green bodies revealed the presence of voids around the whiskers, which contributed to the reduction in relative density.

The jamming transition of soft particles has well been studied by physicists and the critical behavior of the pressure, elastic moduli, and excess coordination number has been examined by numerous experiments and simulations. In numerical studies of the jamming transition, molecular dynamics simulations play an important role in extracting critical exponents and analyzing normal modes. In most numerical simulations, however, the particles are not allowed to deform though real soft particles can be deformed by contacts with neighboring particles. Here, we theoretically and numerically investigate the jamming transition of deformable particles. Employing the Morse-Witten model, we derive the (extended) Hessian of soft deformable particles. We also use the Morse-Witten model for the force law in molecular dynamics simulations and numerically demonstrate mechanically stable packings of deformable particles. We find that the shear modulus and density of states of deformable particles are quantitatively different from those of artificially undeformed particles.

Before being used for coating in an industrial process, powders are typically converted to a homogeneous slurry by mixing them with the dispersion medium. In contrast, replacing slurries with wet granules (i.e., wet agglomerates), which contain a lower amount of dispersion medium than a slurry, reduces the cost and energy consumption of the drying process in the manufacturing process. We have been investigating the structure and physical properties of wet granules for application in the manufacturing process of lithium-ion battery electrodes. This article describes our previous studies on wet granules for lithium-ion battery.