Shun Muroga

We propose tabular two-dimensional correlation spectroscopy analysis for extracting features from multifaceted characterization data, essential for understanding material properties. This method visualizes similarities and phase lags in structural parameter changes through heatmaps, combining hierarchical clustering and asynchronous correlations. W...

To meet the need for more adaptable and expedient approaches in research and manufacturing, we present a continuous autonomous system that leverages real-time, in situ characterization and an active-learning-based decision-making processor.

A multimodal deep‐learning (MDL) framework is presented for predicting physical properties of a ten‐dimensional acrylic polymer composite material by merging physical attributes and chemical data. The MDL model comprises four modules, including three generative deep‐learning models for material structure characterization and a fourth model for prop...

We present a multimodal deep learning (MDL) framework for predicting physical properties of a 10-dimensional acrylic polymer composite material by merging physical attributes and chemical data. Our MDL model comprises four modules, including three generative deep learning models for material structure characterization and a fourth model for propert...

While the functionalization of carbon nanotubes (CNTs) has attracted extensive interest for a wide range of applications, a facial and versatile strategy remains in demand. Here, we report a microwave-assisted, solvent-free approach to directly functionalize CNTs both in raw form and in arbitrary macroscopic assemblies. Rapid microwave irradiation...

We investigate the liquid crystal (LC) phase behaviors of the sodium cholate stabilized single-walled carbon nanotube (SWCNT) aqueous dispersions with different SWCNT aspect ratios. The isotropic-to-nematic phase transition occurs at a lower concentration for the SWCNT dispersion with larger aspect ratio, which is expected by the Onsager theory. Th...

Controlling the alignment of single-walled carbon nanotubes (SWCNTs) on the macroscopic scale is critical for practical applications because SWCNTs are extremely anisotropic materials. One efficient technique is to create an effective SWCNT dispersion, which shows a liquid crystal (LC) phase. A strong acid treatment can realize SWCNT liquid crystal...

A comprehensive characterization of various carbon nanotube (CNT) yarns provides insight for producing high-performance CNT yarns as well as a useful guide to select the proper yarn for a specific application. Herein we systematically investigate the correlations between the physical properties of six CNT yarns produced by three spinning methods, a...

Virtual experiment of carbon nanotube (CNT) film based on artificial intelligence is examined. As reported in many previous papers, artificial intelligence can create many kinds of images and data and using those technics many researchers have tried to develop the high functional materials using AI. In this study, one of the deep learning technics,...

Artificial intelligence relying on structure-property databases is an emerging powerful tool to discover new materials with targeted properties. However, this approach cannot be easily applied to tangible structures, such as plastic composites and fabrics, because of their high structural complexity. Here, we propose a deep learning computational f...

Here, we propose a novel attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy method for simultaneously monitoring the curing reaction and the diffusion behavior of curing agents at the surface of rubber in real-time. The proposed scheme was demonstrated by fluorine rubber (FKM) and FKM/carbon nanotube (CNT) nanocomposites...

Artificial intelligence is an emerging frontier in material science to discover new materials with targeted properties by an artificial neural network (ANN) constructed from existing structure-property databases. This approach has not been applicable to tangible materials, such as plastic composites, fabrics, and rubbers, because the complexities o...

A nondestructive method of evaluating the curing degree (crosslinking density) of cured rubbers and their nanocomposites based on attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy was proposed and applied to fluorine-based rubber (FKM), in which triallyl-isocyanurate (TAIC) was employed as a curing agent. ATR-FTIR spect...

To fully utilize intrinsic properties of carbon nanotubes (CNT) for the industrial application, preservation of the quality is of importance through dispersion processes in matrices. We demonstrated a 10⁴-fold enhanced electrical conductivity of CNT rubber composite keeping the CNT quality by the predispersion of CNT powder in the viscous rubber ba...

Preserving the quality of carbon nanotubes (CNT) is essential to fully utilize the characteristics in the dispersions and other forms. To fabricate CNT dispersions retaining the quality, we propose to reduce CNT aggregate size distributions by viscous liquids at the initial stage from as-grown CNT powders originally possessing a wide aggregate size...

This paper proposes a nondestructive method of evaluating polymer composites using near-infrared (NIR) diffuse reflection spectroscopy with multiple ground plates. Wavelength-dependent absorption and reduced scattering coefficients were acquired to evaluate the chemical structure and the concentration of the substances from absorption and to determ...

We propose an analytical method to evaluate the dispersion of additives in polymers using FT-IR spectroscopic imaging. Averaging filters with various window sizes were intentionally applied to imaging data measured with high resolution. The window size dependent coefficients of variance (CV) were calculated to evaluate the dispersion state in each...

The hydrolysis of polylactide (PLA) occurs during melt processing, leading to product defects in, for example, appearance and mechanical properties. Hydrolyzed PLA products, whose mechanical properties were deteriorated, must be detected during processing to ensure the quality control of PLA products. In this study, near-infrared (NIR) hyperspectra...

During melt processing, the moisture inside polylactide (PLA) easily induces hydrolysis, which deteriorates the mechanical and thermal properties of the product. The state of dryness of resin pellets must be monitored to prevent PLA hydrolysis. In this study, near-infrared (NIR) spectroscopy was applied to measure water content in PLA. In addition,...