Kyoto Institute of Technology

Abstract Polyhedral oligomeric silsesquioxane (POSS) has been extensively studied as an essential building block into polymer matrices to improve their thermal and mechanical properties. Although aggregation and dispersion state of POSS segments influence these properties, a deep understanding of POSS aggregation behavior is lacking. In this study, the aggregation behavior of heptaisobutyl-mono-substituted-POSS (7B1R-POSS) was investigated in chloroform (CHCl3), using a simplified model that eliminates various factors within polymer matrices, to understand the mechanism of POSS molecules aggregation. The UV-VIS spectra of 7B1R-POSS solutions with varying concentrations revealed a critical aggregation concentration (CAC), indicating that 7B1R-POSS formed aggregates in CHCl3. Dynamic light scattering (DLS) measurements of 7B1R-POSS solutions above the CAC suggested that the most of aggregation particles were on the order of nanometers, and very few aggregates of a few hundred nanometers were formed. It was found that all 7B1R-POSS exhibited temperature-responsive reversible aggregation behavior, aggregating upon heating, and dispersing upon cooling. This behavior was similar to the entropy-driven behavior observed in polymer micelles, which is known as hydrophobic behavior. In this work, the entropy-driven dominant aggregation behavior in the aggregates of 7B1R-POSS was clarified.

This study proposes a framework to assess the seismic risk by integrating city‐scale numerical simulations with sensor data prediction. The study begins with advanced numerical simulations using two primary methods: the integrated earthquake simulator (IES) and the stochastic Green's function method. The stochastic Green function method is used to generate the motion from the fault model to the outcropped engineering bedrock. The IES is used to simulate the ground motion on the surface, considering different scenarios, and the sumulation results are seperated into training and validation datasets. In this study, all scenarios are generated from a single fault model, and variability is introduced by changing the rupture initiation point, representing a limited dataset but practically relevant setting. Proper orthogonal decomposition (POD) is then applied to the training datasets to extract spatial modes, and those modes are used for identifying the most suitable distributions for sensors. In this study, the sensors are strategically placed to maximize data collection efficiency while minimizing the overall number of sensors used. Optimizing sensor distribution is crucial owing to the challenges associated with deploying numerous sensors in actual situations. The distribution of sensors obtained by this method is validated using a test set generated from IES simualation. The case study focusing on Sendai city (Japan), for scenarios associated with the Nagamachi–Rifu fault, finds an optimal solution for the distribution of sensors and allows for an overall prediction of the expected accuracy. The results show that seismic risk prediction and assessment on a city scale can be achieved by this method while maintaining accuracy and the number of sensors. The present work therefore demonstrates the feasibility of the proposed rapid prediction framework under limited dataset conditions for a specific, high impact seismic source, while the extension to multiple faults and magnitudes is left for future work.

In this study, carbon-doped Y2Ti2O7 and TiO2 22% - 1/2 (Y2O3) 78% (TiO2 22%-YTO) thin films were fabricated using mist CVD method under atmospheric pressure, and their structural analysis and electrical characteristics were evaluated. These films were formed using a low-temperature process with maximum heat treatment at 430°C and exhibited memory switching properties based on metal-insulator transition (MIT). The fabricated devices showed an initial low-resistance metallic state (Born-on characteristic) and demonstrated non-polar switching behavior, transitioning to a high-resistance insulating state when a voltage of approximately 0.7 V was applied. Furthermore, TiO2 22%-YTO maintained similar switching performance at 200°C as at room temperature, confirming operation over a wide temperature range. SIMS analysis confirmed approximately 0.4% carbon doping in the films, which is believed to create impurity levels that enable metal-insulator transitions in Mott-Hubbard insulators. The material system developed in this research is promising for applications in correlated electron random access memory (CeRAM) that operates at low voltages over a broad temperature range.

Abstract Research in human–robot Interaction (HRI) has increasingly demonstrated how Augmented Reality (AR) enables better interactions between humans and robots. However, the design of HRI remains less understood. Through a systematic literature review of 53 related papers, this research provides an overview of the emerging applications and trends for AR and identifies three types of AR interfaces as follows: 1) remote modular interface, 2) proximal modular interface, and 3) proximal integral interface. The review indicates potential future directions of construction-oriented and human-centric interaction design studies, leading to four pairs of subsystems, which are frequently modularised or integrated, and three conceptual frameworks for HRI interfaces are proposed. Moreover, this research contributes to the theoretical exploration of interaction design. Future applications can adapt to various tasks by using the proposed three conceptual frameworks for interfaces, as well as combining the four proposed subsystem pairs to suit specific task requirements in the construction sector.

The phase-field (PF) model based on a double-obstacle (DO) potential has been extensively used to simulate free boundary problems in material science similarly to the model based on the double-well (DW) potential. The nonlinear preconditioning method, which transforms the PF variable into a linear interfacial distance function, enables stable computations even with coarse interface resolution in DW model. However, when applied to the DO model, this approach leads to numerical instability, rendering the simulations practically infeasible. To address the issue, we propose a novel hybrid nonlinear preconditioning approach for the PF model with the DO potential. In this approach, the nonlinear preconditioning DO model is applied inside the interface region, while the nonlinear preconditioning DW model is used in the outer region where the DO model becomes numerically unstable. We first derive a single-phase-field equation based on this approach and subsequently extend it to a multi-phase-field equation. The proposed method is validated through two-dimensional simulations of single-grain growth and the triple junction migration. Our results show that the proposed model provides improved numerical accuracy compared to the conventional DO model under low interface resolution conditions and effectively reduces the influence of grid anisotropy. These results demonstrate that the proposed strategy offers a computationally accurate and efficient approach for DO potential PF simulations under coarse grid resolution.

Poly(ethylene terephthalate) (PET) is a widely used commodity polymer owing to its low cost, excellent mechanical properties, and high processability. Chemical modification of PET surfaces to impart specific functionalities represents an effective strategy for transforming PET into high-value-added materials without altering its bulk properties. In this study, we investigated the surface functionalization of PET substrates using surface-initiated atom transfer radical polymerization (SI-ATRP). ATRP initiation sites were introduced onto PET surfaces through mild surface hydrolysis followed by polyethyleneimine coating. To further enhance the grafting density, an inimer-based strategy was employed, in which a bifunctional monomer containing both a polymerizable group and a latent initiation site was used to form hyperbranched polymer structures on the PET surface, thereby amplifying the number of active initiation sites. Using these modified PET substrates, SI-ATRP of functional methacrylate monomers was successfully carried out. Grafting of poly(2,2,2-trifluoroethyl methacrylate) imparted highly hydrophobic surface properties, yielding water contact angles above 120°, whereas grafting of poly([2-(methacryloyloxy)ethyl]trimethylammonium chloride) produced hydrophilic surfaces with contact angles below 20°. Surface characterization by X-ray photoelectron spectroscopy confirmed successful graft polymerization and effective surface coverage. While the macroscopic wettability was primarily governed by the chemical nature of the grafted polymers, the inimer-based initiation-site amplification significantly enhanced the surface electrostatic properties of the polycationic polymer–grafted surfaces, increasing the ζ-potential from approximately +20 mV to over +100 mV. Antibacterial tests using Escherichia coli K-12 as a model bacterium demonstrated that PET substrates grafted with poly([2-(methacryloyloxy)ethyl]trimethylammonium chloride) exhibited clear contact-active antibacterial activity, achieving up to 2-log reduction in viable bacterial counts after 3 h of contact incubation. These results highlight the importance of molecular-level control of grafting architecture and surface electrostatic properties in the design of functional antibacterial PET surfaces.