High-speed data acquisition is essential for pushbroom imaging sensors on Low Earth Orbit (LEO) satellites, where timing accuracy, word reconstruction, and frame-boundary identification affect image fidelity and real-time operation. Previous FPGA-based LVDS, SERDES, and SoC studies have mainly emphasized throughput or individual interface functions, while hardware-validated integration of independent dual-bank timing, serialized boundary detection, word reconstruction, and mission-representative line timing remains limited. This work presents and experimentally evaluates a dual-bank FPGA acquisition architecture for the NEO-1 Medium Resolution Imager. The design combines independent PLL-derived 4× retiming clocks, serialized synchronization-pattern detection, and Serial-In-Parallel-Out reconstruction of 14-bit pixel words. Ground-based tests used the physical sensor with clock, trigger, pixel, and line-period parameters representative of the nominal 500 km imaging scenario. At a nominal 66 MHz sensor clock, the implemented acquisition period is 149,857 cycles, or approximately 2.271 ms, and the calculated aggregate payload rate is 178.282 Mbps. The non-instrumented design uses 543 logic elements, 413 registers, and two PLLs, with an estimated FPGA thermal power dissipation of 234.18 mW and positive setup and hold slack for all constrained intra-domain paths. Across five Signal Tap sessions, 138 pixel intervals yielded a mean period of 151.520 ns, with no variation resolved beyond the 3.788 ns sampling interval. One mismatch among 29,904 captured bit observations gave a capture-based bit-mismatch fraction of 3.344×10−5. These results demonstrate timing-consistent and resource-efficient dual-bank acquisition under the evaluated ground conditions. Formal physical-link BER, complete-frame FER, long-duration stability, and environmental qualification remain future work.
Hydrogen (H2) is recognized as a clean energy carrier with potential applications in various sectors; however, its colorless and high flammability necessitate sensitive and reliable monitoring under ambient conditions. Chemiresistive semiconducting metal oxide sensors are attractive for their simple architecture and high sensitivity, but their performance often drops at room temperature and they still face selectivity challenges, which limit their practical deployment. Here, we address the challenge of room-temperature operation in chemiresistive semiconducting metal oxides-based sensors by engineering magnesium (Mg)-doped porous ZnFe2O4 microspheres (ZFM) and integrating them with platinum-decorated carbon nanotubes (CP). This composite design is expected to enhance room-temperature H2 sensing by increasing defect-mediated adsorption on the ZFM surface, facilitating efficient charge transport through the CNT network and accelerating reaction kinetics via Pt-assisted H2 dissociation. A two-step optimization strategy was adopted to establish composition–microstructure–property correlations: CP loading (0.1, 0.25, 0.5, 0.75 and 1 wt%) was first varied at an intermediate Mg (10 wt%) to investigate the effect of CNT/Pt network evolution, and then the optimal CP level (0.5 wt%) was kept constant while the Mg content (5–15 wt%) was varied. All the prepared composites were comprehensively characterized using XRD, FESEM, EDX, TEM, FTIR, UV–Vis, BET, and XPS to identify their phase composition, morphology, porosity, and surface chemical states. The sensing layers were fabricated by drop-casting onto epoxy-glass electrodes and tested under ambient conditions toward different H2 concentrations. The optimized ZFM10-CP0.5 sensing layer showed the best performance with a response of 2.2 at 10000 ppm H2 with fast response/recovery (11/90.9 s) and preferential response toward H2 relative to the tested organic interferents methanol, ethanol, ethylene glycol, and DMF, while maintaining approximately 90% of its H2 response at 70% relative humidity. XPS, BET, and FESEM collectively suggest that Mg doping increases the contribution of defect-related surface oxygen species, while 0.5 wt% CP provides a more continuous conductive network and accessible porous interface, consistent with the improved H2 response of ZFM10–CP0.5. These results identify an optimized ZFM–CP composition for heater-free room-temperature H2 sensing under the investigated conditions and highlight concurrent tuning of Mg content and CP loading as an effective strategy within this composite.
A hybrid composite based on Urushibara nickel-A and reduced graphene oxide (U-Ni-A/rGO) was developed for nonenzymatic glucose sensing in alkaline media. The composite combines skeletal nickel with a conductive rGO framework, giving an rGO-supported Ni interface with improved dispersion and lower interfacial resistance than U-Ni-A under identical conditions. The electrochemical response was examined by cyclic voltammetry (CV) and chronoamperometry (CA). CV was used to probe concentration-dependent behavior across 0.01–6000 μM, yielding a concentration-specific CV-derived slope of 5,666,475 μA mM−1 cm−2 in the 0.01–0.1 μM window. Quantitative sensing performance was evaluated by CA at 480 mV vs SCE, giving a linear response from 1 to 6000 μM with a sensitivity of 1000 μA mM−1 cm−2 and a response time of less than 2 s. The hybrid sensor also exhibited cycling durability and short-term shelf stability under the tested protocol, and strong selectivity toward glucose, with minimal interference from uric acid, ascorbic acid, dopamine, major cations, and various structurally related sugars under the tested 10:1 glucose-to-interferent screening conditions. These results support U-Ni-A/rGO as a potential platform for nonenzymatic glucose sensing.
Glucose-6-phosphate dehydrogenase (G6PD) is vital for maintaining cellular redox balance through the generation of NADPH in the pentose phosphate pathway. Given the global prevalence of G6PD deficiency and its association with hemolytic anemia, neonatal jaundice, and drug-induced oxidative complications, rapid and reliable assessment of enzyme activity is clinically important. Because NADPH production directly reflects G6PD function, sensitive quantification of NADPH provides an effective strategy for deficiency screening. To address this clinical need, a deployable electrochemical biosensor was developed using a screen-printed graphene electrode modified with a graphene nanoplatelet–WS2 (GNPl–WS2) nanocomposite. The synergistic nanohybrid interface enhances conductivity, increases electroactive surface area, and accelerates electron-transfer kinetics, leading to amplified anodic signals for NADPH oxidation. The platform was systematically optimized and thoroughly characterized to ensure robust analytical performance. Under optimal conditions, the sensor demonstrated a wide linear range from 5 μM to 3.5 mM and a low limit of detection of 1.01 μM. Importantly, the device offers rapid analysis (time-to-result <2 min), portability, and operational simplicity without complex fabrication or electrode regeneration. These features make the proposed deployable sensor a practical and promising tool for point-of-care and field-based evaluation of G6PD activity in biological samples, particularly in blood samples.
Graphene-based hydrogels are promising candidates for motion-sensing applications in assistive technologies. However, conventional systems rely on expensive, non-renewable precursors, which limits scalability and sustainability. In this study, palm kernel shell waste was used as a renewable carbon source to synthesize reduced graphene oxide (RGO), which was subsequently functionalized with silica (RGS) to enhance hydrogel performance. The synthesis of RGO and RGS was optimized to achieve high yield, facile processing, and cost-effectiveness. Incorporation of silica-functionalized RGO improved dispersion, interfacial bonding, and the structural integrity of PVA hydrogels, enhancing mechanical durability and stability. Density Functional Theory (DFT) calculations were performed to elucidate the electronic properties and molecular interactions between PVA and filler supporting the experimental findings. The resulting strain sensor exhibited a high gauge factor (GF ≈ 9.5), fast response, and reliable detection of assistive motions. Furthermore, the device successfully recognized Indonesian Sign System (SIBI) gestures, demonstrating its potential as a sustainable, low-cost, and high-performance platform for assistive communication technologies.
