Jun Ohta

This study presents a sustainable waste-to-resource approach for water treatment through the development of an immobilized adsorption–photocatalytic system based on Fe-doped TiO₂ and biomass-derived hard carbon. Hard carbon was synthesized from durian peel via a hydrothermal–carbonization process, transforming agricultural waste into a high-value adsorbent with a high specific surface area (279 m² g⁻¹) and hierarchical pore structure. Fe-doped TiO₂ nanoparticles were prepared using a solution combustion method with titanium isopropoxide (TTIP) and glycine, resulting in porous anatase-dominant structures. The Fe-doped TiO₂/hard carbon composite was subsequently coated onto 3D-printed polylactic acid (PLA) scaffolds to form an immobilized catalytic system. Structural and physicochemical characterization (X-ray diffraction (XRD), Rietveld refinement, scanning electron microscopy/transmission electron microscopy (SEM/TEM), Brunauer–Emmett–Teller (BET), ultraviolet–visible diffuse reflectance spectroscopy (UV–Vis DRS), and photoluminescence (PL)) confirmed that Fe doping effectively reduced the bandgap (from 3.02 to 2.89 eV) and introduced defect states that enhance charge separation. The 3 mol% Fe-doped TiO₂ exhibited the most optimal structural and textural properties, including the highest surface area (123 m² g⁻¹) among TiO₂-based samples. Photocatalytic performance was evaluated using methylene blue (MB) as a model organic pollutant. The Fe-doped TiO₂/hard carbon-coated PLA structures demonstrated enhanced removal efficiency compared to pristine TiO₂, attributed to a synergistic mechanism combining pollutant adsorption and photocatalytic degradation. The hard carbon component facilitates pollutant pre-concentration, while Fe doping improves light absorption and suppresses charge carrier recombination. The 3 mol% Fe-doped TiO₂/hard carbon system exhibited the best performance, consistent with its optimized structural, optical, and surface properties. Importantly, the use of biomass-derived carbon and 3D-printed biodegradable PLA substrates highlights the environmental and practical advantages of the developed system, including resource recovery, catalyst stability, and ease of reuse. This work demonstrates a promising pathway for integrating waste valorization with advanced water treatment technologies, contributing to sustainable and circular approaches for environmental remediation.

More than one fifth of American adults lives with chronic pain. As pain chronifies, the underlying neuronal circuitry undergoes maladaptive spatial and temporal changes. We previously developed and used an advanced CMOS sensor to record video of ventral tegmental area (VTA) activity in response to acute pain and pain chronification. Here we use both discriminative and generative AI approaches to spatiotemporally characterize the VTA's complex response to pain and quantify changes in its circuit dynamics murine chronic pain models. We trained a time-attention convolutional neural network (TA-CNN) and used its gradient-weighted class activation maps (Grad CAMs) to spatially isolate activity which differentiates pre- and post-surgical responses to stimulation. Next, we implemented an unsupervised vector quantized variational autoencoder (VQ-VAE) to learn a dense, discrete representation of the VTA's response in terms of a codebook of spatiotemporal motifs. The TA-CNN's (test set accuracy 0.787) CAMs help isolate post-surgery activity differences to the inferior segments of the VTA for partial sciatic nerve ligation (PNL) subjects but not sham subjects. The VQ-VAE (validation mean squared error 0.00732) identifies distinct spatiotemporal motifs which spatially correspond to observed VTA sub-regions. Furthermore, these motifs show changes in both spatial organization and time-response to pain after PNL but not after sham operation. These motifs also exhibit intensified spatiotemporal responses to varying intensities of mechanical stimulation in post-PNL recordings. The use of AI to fit complex space-time dynamics to an ordered latent representation or code paves the way for nuanced analysis of previously difficult-to-approach problems.

In this paper, we demonstrated a high-sensitivity polarization image sensor for millimeter-wave electric field imaging using electro-optic crystals. We developed a three-layer on-pixel polarizer structure fabricated with a 0.35-µm standard CMOS process, achieving an extinction ratio of 5.7, which corresponds to a 73% improvement over previous two-layer structure. Crosstalk reduction was implemented by applying a bias voltage to the n-well pixel separation, and extinction ratio was further improved. By using an improved sensor, it demonstrated a 7.6 dB SNR improvement in 30 GHz electric field imaging compared to previous sensors, despite 30% transmittance reduction. Angular dependence analysis confirmed adequate performance within the optical system’s constraints. These results enable high-speed and high-sensitivity millimeter-wave imaging applications.

The neurobiology of chronic pain is complex and multifaceted, intertwining with the mesocorticolimbic system to regulate the behavioral and perceptional response to adverse stimuli. Specifically, the ventral tegmental area (VTA), the dopaminergic hub of the reward pathways located deep within the midbrain, is crucial for regulating the release of dopamine (DA) throughout the central nervous system (CNS). To better understand the nuances among chronic pain, VTA response, and therapeutics, implementing progressive approaches for mapping and visualizing the deep brain in real time during nociceptive stimulation is crucial. In this study, we utilize a fluorescence imaging platform with a genetically encoded calcium indicator (GCaMP6s) to directly visualize activity in the VTA during acute nociceptive stimulation in both healthy adult mice and adult mice with partial nerve ligation (PNL)-induced neuropathic pain. We also investigate the visualization of the analgesic properties of morphine. Deep brain imaging using our self-fabricated µ-complementary metal–oxide–semiconductor (CMOS) imaging device allows the tracking of the VTA’s response to adverse stimuli. Our findings show that nociceptive stimulation is associated with a reduction in VTA fluorescence activity, supporting the potential of this platform for visualizing pain-related responses in the central nervous system. Additionally, treatment with morphine significantly reduces the neuronal response caused by mechanical stimuli and is observable using the CMOS imaging platform, demonstrating a novel way to potentially assess and treat neuropathic pain.

Artificial retinal devices require a high-density electrode array and mechanical flexibility to effectively stimulate retinal cells. However, designing such devices presents significant challenges, including the need to conform to the curvature of the eyeball and cover a large area using a single platform. To address these issues, we developed a parylene-based multi-module retinal device (MMRD) integrating a complementary metal-oxide semiconductor (CMOS) system. The proposed device is designed for suprachoroidal transretinal stimulation, with each module comprising a parylene-C thin-film substrate, a CMOS chip, and a ceramic substrate housing seven platinum electrodes. The smart CMOS system significantly reduces wiring complexity, enhancing the device’s practicality. To improve fabrication reliability, we optimized the encapsulation process, introduced multiple silane coupling modifications, and utilized polyvinyl alcohol (PVA) for easier detachment in flip-chip bonding. This study demonstrates the fabrication and evaluation of the MMRD through in vitro and in vivo experiments. The device successfully generated the expected current stimulation waveforms in both settings, highlighting its potential as a promising candidate for future artificial vision applications.

In this study, we developed a high-frequency electric field imaging system based on the first-order electro-optic effect for the detection of time-varying frequency wave sources. The proposed system utilizes the optical heterodyne technique. The process begins with an antenna that detects the frequency of the electric field of interest, which is then fed into the optical local oscillator (LO) signal generation system. This optical LO signal tracks the frequency of the electric field being observed while maintaining a constant intermediate frequency. This configuration enables the visualization of dynamic electric fields, including asynchronous wave sources and frequency-modulated signals, without requiring a direct physical connection to the wave source. In this study, we present the development of a high-frequency electric field imaging system based on the first-order electro-optic effect for the detection of time-varying frequency wave sources. The proposed system utilizes the optical heterodyne technique. The process begins with an antenna that detects the frequency of the electric field of interest, which is then fed into the optical local oscillator (LO) signal generation system. This optical LO signal is designed to follow the frequency of the electric field being observed while maintaining a constant intermediate frequency. This configuration facilitates accurate electric field imaging and enables the visualization of dynamic electric fields, including asynchronous wave sources and frequency-modulated signals, without requiring a direct physical connection to the wave source.

This paper introduces an image processing method, used to achieve uniform sensitivity across the imaging plane in a high-frequency electric field imaging system, that employs an electro-optical crystal and a polarization image sensor. The polarization pixels have two polarization directions, 0° and 90°, in pairs, and, conventionally, their difference is computed first. In contrast, this study proposes a method to separate each polarization image, perform pixel completion, and subsequently perform intensity correction. The proposed method was demonstrated to improve field distribution images acquired using 36 GHz and 30 GHz input signals for a microstrip line and patch antenna, respectively. From the measurement results of the microstrip line, the application of the proposed method reduced the electric field fluctuations on the line from 3.1 dB to 1.5 dB. This image-processing method can be applied sequentially during image acquisition, making it suitable for the real-time imaging of electric fields.

Unlike traditional methods that implant passive optical components like fibers and rod lenses, optoelectronic semiconductor-based devices directly implant active optoelectronic semiconductors into the...