Search Results (1,271)

Edge-side acoustic monitoring enables animal sound recognition in remote environments, but microcontroller deployment remains constrained by feature extraction, numerical consistency, memory, latency, and energy consumption. This study presents a sensor-based tiny machine learning (TinyML) acoustic monitoring system on an Arduino Nano 33 BLE Sense Rev2 platform, integrating onboard pulse-density modulation (PDM) microphone acquisition, Mel-frequency cepstral coefficient (MFCC) feature extraction, deployment-side standardization, 8-bit integer (INT8) neural-network inference, and edge-side decision output. To reduce training-to-deployment feature drift, consistent frame parameters, mirrored C++ feature operators, and exported standardization parameters are used to align personal-computer-side and microcontroller-side feature representations. A source-isolated seven-class protocol was constructed for six target animal classes and one compound background-noise class. In the single-run baseline comparison, the proposed multilayer perceptron achieved 98.28% test accuracy and 97.21% test macro-F1, while the ten-seed stability analysis yielded 98.64% ± 0.26% test accuracy and 97.87% ± 0.38% test macro-F1. The deployed INT8 model occupied approximately 26.9 KB, with a post-window latency of about 303 ms. System-level input power was 0.783–0.825 W, corresponding to an estimated autonomy of 7.63–8.03 h under the reference battery setting. Full article

Regenerated cellulose is a promising tribopositive material for sustainable triboelectric nanogenerators (TENGs), although its electrical output remains sensitive to surface and interfacial properties. In this study, regenerated cellulose was modified using atomic layer deposition (ALD) of Al₂O₃, TiO₂, and ZnO to investigate how nanoscale oxide coatings influence triboelectric performance against a tribonegative PTFE counter layer. Two deposition regimes were examined: 7 ALD cycles, representing the early stage of ALD growth, and 200 cycles, representing a more developed coating regime. Triboelectric measurements, dielectric spectroscopy, structural characterization and contact angle analysis, were used to evaluate how ALD modification influences the electrical response of regenerated cellulose. All ALD-modified samples exhibited increased surface charge density and power output compared to unmodified cellulose, while also showing improved retention of triboelectric performance at elevated relative humidity. The 7-cycle samples consistently outperformed the corresponding 200-cycle coatings under low-humidity conditions, whereas the 200-cycle ZnO sample exhibited the highest humidity stability. No direct correlation between wettability and triboelectric output was observed. The results suggest that relatively small interfacial modifications introduced by ALD are sufficient to influence both the triboelectric response and humidity-dependent charge dissipation behavior of regenerated cellulose. Full article

The development of low-emission and reliable propulsion systems is essential for extending the operational capability of unmanned aerial vehicles (UAVs). Although aviation decarbonization is widely recognized as an important objective, it must be considered within the broader context of limited renewable-energy availability. Recent system-level analyses of transportation decarbonization have shown that the allocation of renewable electricity and sustainable fuels should prioritize sectors where direct electrification is most efficient, while hard-to-electrify sectors require alternative pathways. Aviation is one of the most difficult transport sectors to electrify because of strict energy-density requirements, especially for long-endurance airborne platforms. Therefore, sustainable liquid fuels and hybrid propulsion systems should not be considered universal replacements for electrification, but rather complementary solutions for applications where batteries alone cannot provide the required endurance, payload capacity or operational flexibility. In this context, the present study focuses on alcohol–kerosene blends for hybrid UAV power systems, where liquid-fuel energy density and partial emission reduction remain relevant engineering requirements. This work provides one of the first systematic experimental evaluations of ethanol–, butanol– and octanol–kerosene blends in a micro-turboprop engine operating as part of a hybrid UAV power-generation architecture. Unlike previous studies focused mainly on micro-turbojet thrust response, the present work evaluates the coupled influence of alcohol chain length and blending ratio on exhaust gas temperature, gaseous emissions, electrical output and operational stability under multi-load conditions representative of UAV operation. Jet-A and nine alcohol–kerosene blends containing 10%, 20% and 30% ethanol, butanol or octanol by volume were tested over four operating regimes, from idle to 2500 W electrical load. The results show that ethanol blends provided the strongest CO reduction, with E30 reducing CO by 24.9% relative to Jet-A under R3, while E10 offered the most balanced behavior across the full operating range. Higher ethanol fractions improved CO suppression but introduced NOx and low-load stability penalties. Octanol blends, particularly O20, exhibited the most kerosene-like and stable response, supporting reliable power delivery with reduced operational variability. Butanol blends showed intermediate behavior without providing a dominant advantage. A multi-criteria evaluation combining emissions, EGT behavior, relative performance, operational stability and cost identified E10 as the best overall compromise for hybrid UAV use. The study demonstrates that alcohol chain length produces nonlinear system-level effects in hybrid micro-turboprop architectures and provides an experimental basis for fuel selection in low-emission UAV power systems. Full article

To address the issues of low light absorption efficiency and limited temperature gradient distribution in conventional planar Ag₂Se-based photothermoelectric (PTE) detectors, this paper proposes a structured design strategy for the surface functional layer. Ag₂Se-based PTE detectors with periodic surface microstructure arrays were fabricated using photolithography, and the influence of surface structure on the device’s PTE response performance was systematically investigated. The results indicate that surface microstructures can enhance light absorption and localized photothermal conversion efficiency, thereby increasing the PTE output voltage. However, they also lengthen the thermal diffusion path and reduce the dynamic response speed. When the structural pitch is 6.7 um, the device exhibits optimal overall detection performance within the measured spectral range of 405–950 nm. Under irradiation at a wavelength of 950 nm and a laser power density of 120 mW/cm², the device achieved a voltage sensitivity of 0.14 mV/W. This study reveals the trade-off between enhancing the response performance and response speed of Ag₂Se-based PTE detectors through surface structural design, providing experimental evidence and design guidance for rationally optimizing device structural parameters and realizing room-temperature PTE detection. Full article

The increasing demand for sustainable energy and efficient wastewater treatment has driven interest in single-chamber microbial fuel cells (SCMFCs) as integrated systems for bioelectricity generation and waste remediation. This study evaluates untreated agro-industrial byproduct olive mill wastewater (OMW) as a substrate in SCMFCs. It investigates the performance of activated biochar derived from olive pomace coated on stainless-steel mesh (ACB/SSM) as a low-cost cathode material. A synthetic media was used as a control. Electrochemical performance was assessed using voltage profiles, polarization analysis, power density, chemical oxygen demand (COD%) removal, and coulombic efficiency (CE%). The synthetic media achieved higher peak voltage (0.647 ± 0.026 V) and power density (46.05 mW m⁻²), whereas OMW showed more stable voltage output and lower internal resistance. OMW exhibited superior initial COD removal (74%) and a gradual increase in CE% up to 63% over successive cycles. In contrast, synthetic media exhibited a consistent COD% of 64%; its CE% removal improved to 61%. These results demonstrate that, despite lower peak power, OMW provides a more stable and sustainable substrate for long-term SCMFC operation. The use of waste-derived biochar cathodes further enhances system feasibility by reducing cost and supporting circular economy principles. This study highlights the potential of OMW-based SCMFCs as a practical approach for simultaneous wastewater treatment and renewable energy recovery. Full article

Facing global problems such as the energy crisis and climate change, in recent years, the bioelectrochemical system represented by plant microbial fuel cell (PMFC) has been widely studied. It is a frontier bioelectrochemical technology that combines plant photosynthesis, rhizosphere microbial metabolism, and electrochemical energy conversion. This paper focuses on the linkage application of PMFC and intelligent sensing technology in the paddy-field environment, systematically expounds the basic composition, working principle, and integration mode of this technology with paddy field ecology, and emphatically analyzes its realization path and application potential in self-powered external sensor deployment, rhizosphere biosensor, and multi-node sensor network integration. The analysis shows that PMFC has the unique advantage of in situ and continuous micro-power generation in flooded rice fields. Its output not only supports the intermittent operation of low-power sensors, but the output electrical signals can also reflect plant stress and environmental conditions, thereby possessing biosensing potential. However, the current system still faces key bottlenecks, such as low power density, easily disturbed electrical signals, and high cost of high-performance electrode materials, which restrict the actual deployment of rice fields. Through the collaborative optimization of electrode interface engineering, microbial community directional control, and low-power sensing fusion strategy, it is expected to promote the transformation of PMFC from principle verification to field intelligent monitoring application. Full article

Compact urban form can reduce road transportation GHG emissions and mitigate resource supply bottlenecks associated with mass EV adoption. Global databases from Climate TRACE and the Global Human Settlement Layer are utilized to develop the Compact Urban Form Estimation Tool or CUFET for calculating the reduction in VKT and road transportation GHGs from shifting toward CUF. The CUFET does not explicitly account for mechanistic changes in driving (e.g., modal shift) but rather uses settlement density as a coarse proxy for walking and transit urban fabrics. VKT was modeled using weighted least squares regression from the independent variables settlement population, settlement population density, and country fixed effects. Population size banding was introduced to the model to improve explanatory power. The model was developed using 10,495 settlements in the 2021 Climate TRACE dataset. The CUFET VKT model was able to explain 78% (p < 0.001) of the variation in the VKT of test settlements and improved with the addition of a country fixed effect. The CUFET on average gave estimates of VKT within 24% of Climate TRACE-calculated VKT for countries with a GDP per capita between $20,000 and $45,000 and average estimates within 20% for countries with a GDP per capita above $45,000. Increased settlement density was associated with more substantial reductions in VKT in small (50,000 to 88,335) and medium (88,335 to 329,480) sized settlements relative to large (>329,480) settlements. Higher variability was observed in VKT estimates of small settlements. The CUFET VKT was validated by backcasting historical VKT data from 1960 to 2000. The backcasting exercise used historical administrative boundaries and only included high economic output nations (GDP per capita above $20,000 in 2021 USD). Despite these limitations, backcasting achieved a % difference of ~20% for settlements after 1990, suggesting the model can make useful estimates within 30 years of the model calibration year for high economic output nations. The VKT model was used to calculate emissions using a settlement-specific emissions factor. Settlements with annual road transportation emissions per capita greater than 2 t CO₂eq have the lowest population densities relative to their populations and are mostly located in the United States, Japan, Canada, and Australia. The nations with the highest transportation emissions are also nations where the CUFET provides the most accurate VKT estimates. The CUFET aims to bridge the gap between academic consensus and local decision-making practice by reducing the barriers to estimate VKT and transportation GHG reduction from shifting to compact urban form. Full article

Hydrogen peroxide fuel cells have emerged as a promising class of electrochemical energy conversion device owing to the dual redox character of H₂O₂, its liquid-phase storage, and its ability to operate in air-free environments. In this work, a dual-compartment direct H₂O₂ fuel cell using a Prussian Blue cathode and a tantalum anode, separated by a Nafion 115 proton exchange membrane, was systematically characterized and optimized with respect to electrolyte pH and ionic composition. The influence of pH on OCV was investigated independently in each compartment across the range of pH 2 to 12. In the tantalum compartment, OCV increased non-linearly with pH from 573 mV to 808 mV, driven by the enhanced electrochemical reactivity of the system under alkaline conditions. In the Prussian Blue compartment, OCV decreased from 676 mV to 199 mV with increasing pH, reflecting the instability of the material in alkaline conditions. The effect of the electrolyte ionic composition on average current density was subsequently investigated by varying the concentrations of NaCl and Dy(NO₃)₃. Increasing NaCl from 0 to 2.5 M produced an increase in current density from 0.414 mA/cm² to 0.973 mA/cm², consistent with ohmic resistance reduction through improved ionic conductivity. The addition of Dy(NO₃)₃ produced a positive response with an optimal concentration of $0.05$ M, at which current density reached 1.08 mA/cm², before declining sharply. Under the fully optimized conditions, pH 12 in the tantalum compartment, pH 2 in the Prussian Blue compartment, 0.3 M H₂O₂, 2.0 M NaCl, and 0.05 M Dy(NO₃)₃, the cell produced an OCV of 724 mV and a peak power density of 0.283 mW/cm² at a current density of 0.8 mA/cm². These results demonstrate that meaningful electrochemical performance can be achieved in a dual-compartment H₂O₂ fuel cell without the use of precious metal catalysts and highlight electrolyte engineering as an effective strategy for improving cell output in this class of device. Full article

Interior permanent magnet synchronous motor (IPMSM) has advantages with high power density, wide speed range, small size, and high efficiency, and is widely used in the drive system of electric vehicles. Compared to other types of motors, permanent magnet synchronous motors (PMSMs) have some irreplaceable advantages, but there are also some disadvantages. As a type of PMSM, IPMSMs have problems with large fluctuations in permanent magnet (PM) magnetic field and demagnetization. At present, irreversible demagnetization of PMs is the most serious problem faced by IPMSMs. Once irreversible demagnetization of PMs occurs, it can cause a decrease in the performance of IPMSMs and can even damage the entire drive system. This paper takes an IPMSM with 48 slots, 8 poles, and 66 kW as the research object. Based on the reasons for PM demagnetization, a PM demagnetization model is established to obtain the demagnetization law of PMs. Firstly, the magnetic properties of PM materials were described based on their characteristic curves. The demagnetization mechanism of PMs was analyzed, and the demagnetization process of PMs was studied in combination with the reasons for demagnetization. Secondly, the basic parameters and torque performance of IPMSMs were calculated and analyzed. We analyzed the demagnetization curves of PM materials at different temperatures, calculated the operating points of PMs under various working conditions, and analyzed whether PMs undergo irreversible demagnetization based on the relationship between the operating points of PMs and the knee points of demagnetization curves. A high-fidelity electromagnetic–thermal coupling simulation model has been established, combined with the characteristics of electric vehicle driving conditions, to accurately characterize the temperature rise distribution and electromagnetic parameter changes of IPMSMs under different operating conditions and achieve multi-physics field collaborative analysis. Finally, a finite element model is adopted to simulate uniform and local demagnetization of PMs, and the changing characteristics of motor performance parameters under demagnetization are summarized. Different magnitudes of d-axis reverse current are applied as demagnetization excitation to analyze PM behaviors under various demagnetization degrees. The variations in magnetic flux density, output torque, and no-load back electromotive force (EMF) before and after demagnetization are simulated and analyzed. For the investigated motor and specific magnet grade, this work summarizes the irreversible demagnetization characteristics and corresponding practical judgment references. Full article

This study evaluates the effect of decorative ceramic screen printing on the optical and photovoltaic performance of glass covers intended for building-integrated photovoltaics (BIPV). Nine ceramic-printed glass samples with different colors and optical densities were compared with a 4 mm Optiwhite reference glass and a bare silicon solar cell. The samples were characterized by UV-VIS-NIR spectrophotometry, energy-dispersive X-ray spectroscopy (EDS), and electrical measurements under simulated AM 1.5G irradiation at 1000 W/m². The optical results showed that the Optiwhite reference provided the highest transmittance, whereas the printed samples exhibited lower transmission, typically in the range of 60–80% in the visible region, depending on the coating type. Among the decorative variants, sample 1 showed the highest transparency, while sample 6 exhibited the lowest transmittance. The spectral behavior of the coated glasses indicates that the ceramic layers modify the photon flux reaching the solar cell through wavelength-dependent absorption and scattering effects. The photovoltaic measurements confirmed a clear relationship between decorative coating and electrical performance. Relative to the Optiwhite-covered reference cell, the printed samples showed power losses ranging from approximately 17% to 32%, with sample 1 achieving the highest maximum power among the decorative variants at 1.41 W, and sample 4 the lowest at 1.16 W. The main electrical effect of the ceramic coatings was a reduction in short-circuit current, whereas the open-circuit voltage remained nearly constant across the tested samples. EDS analysis identified the presence of ceramic-layer constituents associated with silica-, zinc-, titanium-, iron-, cobalt-, aluminum-, and fluorine-containing compounds, supporting the interpretation of vitrified decorative coatings formed during high-temperature processing. Overall, the results demonstrate that decorative ceramic printing can provide a practical compromise between architectural appearance and photovoltaic output when the optical density of the coating is appropriately controlled. Full article

Microbial fuel cells (MFCs) are promising bioelectrochemical systems for simultaneous wastewater treatment and energy recovery. However, their practical application is still limited by insufficient power output and weak transient energy-supply capability under fluctuating operational conditions. Herein, a bifunctional CF/MXene/FeS composite anode was fabricated through a one-step hydrothermal strategy to simultaneously enhance electricity generation and capacitive charge storage in MFCs. Unlike conventional bioanode modifications that primarily target conductivity enhancement alone, the constructed hierarchical composite integrates conductive MXene nanosheets and electroactive FeS phases to synergistically improve extracellular electron transfer and interfacial charge-storage behavior. The modified electrode exhibited enhanced surface roughness, abundant electroactive sites, and improved biofilm-supporting interfaces. Benefiting from the integrated conductive and electroactive composite framework, the CF/MXene/FeS anode achieved a maximum power density of 1.69 W/m², which was 70.7% higher than that of pristine CF, together with an increased open-circuit voltage of 0.711 V. In addition, the composite electrode delivered a high total charge density of 13,192.09 C/m² under the C900/D900 condition. Microbial community analysis further revealed substantial enrichment of electroactive bacteria, with the relative abundance of Geobacter increasing from 0.0058% to 22.84%. This work provides a promising strategy for integrating electricity generation and transient energy storage in bioelectrochemical systems, offering potential applications for energy-buffered MFCs under fluctuating power-demand conditions. Full article

This paper presents an application-oriented evaluation of a 130 kW interior permanent magnet synchronous motor (IPMSM) for C-segment electric vehicle (EV) traction by linking sequentially coupled multiphysics analysis with WLTP-based vehicle system-level simulation. Conventional motor performance evaluation is based on single-physics analysis at a limited number of operating points. This approach is insufficient to capture nonlinear characteristic variations under changing operating conditions or to reflect realistic driving environments. To overcome this limitation, sequentially coupled multiphysics analysis incorporating electromagnetic, thermal, and structural characteristics was performed, and the resulting loss data were incorporated into a vehicle system-level simulation model. The WLTP Class 3b driving cycle was applied to quantitatively evaluate energy performance under realistic driving conditions. The results show that the designed IPMSM satisfies the target output power of 130 kW, while its electromagnetic, thermal, and structural characteristics, including torque ripple, back-EMF, winding temperature, permanent magnet temperature, and rotor stress, remain within acceptable limits. The system-level analysis further indicates that the motor operating points during driving are predominantly distributed in the high-efficiency region, and that the final energy economy considering regenerative braking reaches 5.59 km/kWh, with an estimated maximum driving range of 352.58 km on a single charge. These results indicate that the combined motor-level and vehicle-level numerical evaluation can provide useful design-stage information for assessing high-power-density EV traction motors. Full article

This article investigates the design and optimization of a high-speed surface-mounted permanent magnet synchronous motor with an amorphous stator core for hydrogen compressor applications, where high efficiency and high power density are critical. Amorphous materials offer significant potential for reducing excessive core losses at high electrical frequencies—a key requirement for high-speed hydrogen compression systems. However, manufacturing processes such as annealing and cutting degrade their magnetic properties, making raw ribbon data insufficient for accurate loss calculation. To address this, the magnetic performance degradation of the processed amorphous core is characterized by introducing a loss modification factor, improving core loss prediction accuracy. Based on a conventional silicon steel baseline motor operating at 60,000 rpm, a finite element model incorporating the corrected amorphous loss data is developed by replacing the stator core with amorphous material. The Dowell analytical model for AC windings is employed to accelerate computation. A multi-objective evolutionary algorithm is then applied to optimize the motor geometry, maximizing efficiency while maintaining output power to meet the demanding requirements of hydrogen compressors. Finally, a prototype is manufactured and tested. The experimental results validate the efficiency improvement of the amorphous material-based motor and confirm the effectiveness of the proposed optimization methodology for hydrogen compressor applications. Full article

For enhancing the level of refinement of short-horizon wind-storage power prediction, this paper introduces an advanced BiLSTM prediction model integrating data preprocessing based on the density-based clustering technique known as DBSCAN, partial least squares regression (PLSR), and particle swarm optimization (PSO). In this paper, “wind-storage power” refers to the net power output of a wind farm integrated with a battery energy storage system (BESS), where the measured data already embed the effects of charge/discharge operations. First, outage and missing data are removed from the historical dataset. DBSCAN is then employed to identify abnormal samples in wind-storage power and meteorological variables, such as wind speed, wind direction, atmospheric pressure, temperature, and humidity, and linear regression is used to correct the detected noise points. Correlation analysis is further conducted to identify the most relevant meteorological inputs, namely wind speed, wind direction, and atmospheric pressure. Next, the PLSR model is applied to generate the preliminary prediction of wind-storage output. On this basis, the BiLSTM network is employed to predict the residual error, which mainly reflects the nonlinear characteristics not captured by the preliminary prediction. Meanwhile, PSO is implemented to determine the most suitable core hyperparameters for the BiLSTM architecture. Ultimately, the preliminary PLSR result is corrected by the predicted residual to obtain the final wind-storage power prediction. The DBSCAN parameters are systematically selected via a k-distance plot (ε = 0.9, MinPts = 2.5), and the PLSR number of components is set to A = 3 based on five-fold cross-validation. Case studies show that, for the 24 h prediction horizon, the proposed method improves prediction accuracy by 2.29%, 11.47%, and 5.54% compared with the BP, Wavelet-LSTM, and standard LSTM models, respectively. Furthermore, statistical significance is confirmed by Diebold–Mariano tests and 10-run confidence intervals. Full article

This paper presents a 140 GHz two-channel transmitter in 40 nm bulk CMOS technology for D-band wireless communication systems. The transmitter employs a direct upconversion architecture with IQ Gilbert cell mixers and a shared ×9 frequency multiplier for local oscillator (LO) generation. The Lange coupler generates quadrature LO signals for I and Q paths, while the two-way four-stage differential power amplifier with cascade topology provides high output power. On-wafer measurement at 140 GHz LO frequency demonstrates a 9.9 dB conversion gain with a 5.5–6.1 GHz 3 dB bandwidth. The measured saturated output power is 10.1 dBm with an output 1 dB compression point of 6.5 dBm. The IQ imbalance remains within 2 dB across the 3 dB bandwidth. The fabricated transmitter occupies a chip area of 1.68 mm² and consumes 435 mW from a 1 V supply. The power density of 6.09 mW/mm² is the highest among reported CMOS-based D-band transmitters. The dual-channel architecture with shared LO generation enables MIMO transmission, spatial multiplexing, and diversity techniques while maintaining compact size and competitive power efficiency for high data rate wireless applications in the D-band frequency range. Full article