Search Results (667)

This study presents an electrothermal coating approach for synthesizing cell-imprinted polymers (CIPs) on metallic microwires through localized resistive heating-induced polymerization. Imprinted polymers (IPs) are robust, cost-effective synthetic affinity materials widely used in sensing applications. However, conventional fabrication methods, including bulk and suspension polymerization, often lack spatial control, producing non-specific polymerization, heterogeneous coatings, and reduced sensor reproducibility. Electrochemical polymerization provides improved spatial control but requires specialized instrumentation and restricts monomer selection. Here, applying direct current (DC) to metallic microwires immersed in a prepolymer solution generated localized Joule heating, enabling controlled in situ polymerization and uniform coatings while minimizing undesired bulk polymerization. By optimizing the applied current and polymerization time, CIP coatings with tunable thicknesses were fabricated on gold-coated microwires. Under optimized conditions, ~6 µm thick coatings were imprinted using Salmonella templates. Scanning electron microscopy revealed bacteria-shaped cavities consistent with template removal and the formation of imprinted cavities. Rebinding experiments demonstrated enhanced bacterial capture, with CIP-coated microwires achieving ~70% capture efficiency, compared to 22% for bare microwires and 33% for non-imprinted polymer (NIP) controls. These results support the effectiveness of the proposed method for localized polymerization and demonstrate the enhanced capture of the template species by CIP-coated microwires relative to bare microwires and NIP-coated controls. Full article

High-purity SiC powder is an important feedstock for SiC crystal growth, but thermal-field regulation becomes difficult during large-batch synthesis. This study examined an α-SiC powder-synthesis furnace with upper and lower induction-coil groups through numerical simulations and 70 kg synthesis experiments. A representative two-dimensional axisymmetric model was used to compare eight cases with different coil-turn or numerical power allocations. Redistributing the coil turns changed $E_1$, $E_2$, volumetric Joule heat density, $Q$, and the resulting temperature and calculated gas-phase velocity-magnitude fields. From C01 to C04, the maximum calculated temperature decreased from 2501.10 to 2359.13 K, while $\Delta T$ decreased from 242.57 to 76.20 K. Increasing the upper-coil numerical power raised the temperature level while reducing $\Delta T$ to 152.41 K. Increasing the lower-coil numerical power also raised the temperature level, but increased $\Delta T$ to 292.26 K. Equal-total-power comparisons showed that axial power allocation affected $T_{\mathrm{m}\mathrm{a}\mathrm{x}}$ and $\Delta T$. XRD identified 6H-SiC as the detected crystalline phase in both analyzed middle-region specimens, although X-ray-amorphous carbon could not be excluded. The specimens also differed in macroscopic appearance, measured impurity concentrations, and local nitrogen concentration profiles. Because the experimental conditions were maintained nominally unchanged except for the upper-coil current, these specimen-level differences may be associated with altered internal thermal conditions. Such changes may affect local equilibrium, supersaturation, and species transport, providing a possible link to the observed material differences. The numerical results identify coil-turn allocation and axial power allocation as variables for regulating the calculated furnace fields. Full article

This study presents a numerical model of electromagnetic and thermal processes characteristic of a submerged arc furnace. Because direct modeling of a full-scale industrial furnace is complex and difficult to validate experimentally, a laboratory system without an electric arc is considered at this stage. The system reproduces the main features of current supply and energy distribution in the conductive region of the furnace bath. The model is implemented in ANSYS Fluent 2020 R1 using user-defined scalar equations for the electric potential, the components of the magnetic vector potential, and their time derivatives. The implementation was assessed in terms of mesh independence, time-step sensitivity, current and energy balances. The calculations yielded consistent distributions of electric potential, current density, magnetic flux density, Joule heat generation, and temperature. Heating was described using a two-stage scheme: the transient electromagnetic problem is first solved to obtain period-averaged Joule heat generation, which is then used as a source term in the energy equation. The model represents the first stage of a computational framework for submerged arc furnace modeling: at this stage, it is developed and assessed using a simplified laboratory configuration without an electric arc, while in future work it can be supplemented with an arc-channel description and extended to industrial furnace conditions. Full article

The helical-channel magnetohydrodynamic (MHD) thruster is a silent underwater propulsion device free of rotating mechanical components, which fundamentally eliminates the inherent mechanical noise induced by blades and shaft systems in conventional propeller-driven thrusters. Taking a 10 T-class superconducting helical-channel MHD thruster as the research object, this work establishes a three-dimensional numerical simulation model with bidirectional electromagnetic-fluid coupling via Maxwell–Fluent, filling the research gap of systematic optimization of helical pitch angles in existing low-magnetic-field numerical investigations. A composite magnetic circuit configuration consisting of main coils and compensation coils is adopted, achieving a magnetic field uniformity of 90.13% within the effective working section and markedly alleviating magnetic field attenuation at both ends of the flow channel. Three schemes with helical pitch angles of 23.00°, 17.66°, and 14.29° are quantitatively compared to analyze the effects of helical pitch angle on current density, static pressure, total pressure, radial/axial flow velocities and three-dimensional helical streamlines. Under the rated design mass flow rate of 15.5 kg/s, the scheme with the small pitch angle of 14.29° delivers a thrust of 262.56 N and an electromagnetic efficiency of 7.23%; compared with the large pitch angle scheme of 23.00°, its thrust is improved by 28% and electromagnetic efficiency rises by 53%. Reducing the helical pitch angle extends the effective coupling distance between seawater and the electromagnetic field, optimizes the uniformity of radial current distribution, suppresses eddy currents and Joule heat loss, converts more electromagnetic energy into fluid pressure energy, and thus greatly improves the energy utilization efficiency of the propulsion system. This study provides quantitative design references for the structural optimization and engineering prototype development of low-noise superconducting underwater propulsion equipment, and supports the engineering application of helical-channel magnetohydrodynamic thrusters. Full article

The development of lightweight multifunctional materials integrating electromagnetic interference (EMI) shielding, Joule heating and flame retardancy is highly demanded for advanced electronics and aerospace systems. Herein, we fabricate graphene/Fe₃O₄@hollow glass microsphere (G/Fe₃O₄@HGM) composite foam with an ultralow density of 0.36 g/cm⁻³. The porous structure synergizes graphene’s conductivity, Fe₃O₄’s magnetism and HGM’s low thermal conductivity to optimize impedance matching. The foam delivers absorption-dominated EMI shielding with a maximum X-band shielding effectiveness (SE) of 60.1 dB and an average absorption coefficient of 0.56, which effectively suppresses secondary electromagnetic reflection pollution. The composite exhibits stable voltage-controllable Joule heating: the 25 wt% Fe₃O₄@HGM sample reaches 91.3 °C at 16 V, enabling rapid de-icing within 200 s and stable thermal maintenance at −20 °C. Flame tests confirm no combustion or structural collapse under open flame. This work provides a simple fabrication strategy for lightweight multifunctional materials applicable to aerospace stealth, electronic thermal management and anti-icing systems. Full article

The temperature field of a high-voltage direct-current (HVDC) cable governs its current rating and insulation lifetime and must therefore be predicted accurately across diverse operating conditions. Finite-element (FE) simulation is accurate but too costly for repeated evaluation, whereas data-driven reduced-order models (ROMs) often extrapolate poorly beyond the training-current range. This paper proposes a physics-structured POD–neural ROM to address this limitation. Specially, proper orthogonal decomposition (POD) compresses the three-dimensional temperature-rise field into a few modal coefficients, which are predicted from the operating conditions by a neural network. The key innovation is to embed the Joule-heating law directly into the architecture: the leading coefficient is represented as a current-squared factor multiplied by a learned current-independent shape. This construction guarantees the correct current scaling of the dominant mode, including its zero-current limit and extrapolation beyond the training range. On FE data for an eight-layer cross-linked polyethylene cable, the model achieves 2.4% mean relative error under current extrapolation and remains below 5% at twice the maximum training current, outperforming Gaussian-process, dynamic-mode-decomposition, autoregressive, and black-box baselines. The full field is evaluated in approximately one millisecond per condition, with a cost independent of the training-set size. Controlled ablations show that the improvement arises from structurally enforcing the scaling law rather than merely supplying $I^2$ as an input feature. Embedding known physical scaling into a surrogate architecture therefore provides a principled route to reliable extrapolation. Full article

The conductor temperature of cross-linked polyethylene (XLPE) high-voltage direct-current (HVDC) cables governs ampacity assessment and insulation life management, yet it cannot be measured in service, and finite-element simulation is too expensive for real-time use. This paper presents a physics-informed neural network (PINN) that embeds the transient heat-conduction equation, a temperature-dependent Joule source, and the boundary and initial conditions into the training loss of a neural surrogate. Three ingredients adapt the framework to power cables: a layer-aware material mapping over the eight heterogeneous cable layers; an electro-thermal coupling through the temperature dependence of the conductor conductivity, handled during training by a convergent Picard-type evaluation of the Joule source; and a condition-embedding input treating the load current and ambient temperature as continuous parameters so that a single network covers the admissible current–ambient envelope of the studied cable configuration. Validated against finite-element references under fifteen operating conditions, the model attains a root-mean-square error of $0.0024$ K (mean over five training seeds) on a held-out condition relative to a finite-element reference whose mesh-discretization error a refinement study bounds at about $0.04$ K while reducing the governing-equation residual by approximately 28-fold relative to an identically sized data-driven network at statistically indistinguishable pointwise accuracy. The physics prior also renders degradation under training-data reduction more graceful and improves extrapolation to unseen ambient temperatures, whereas current extrapolation remains the most challenging transfer. The differentiable surrogate identifies the load current and the unmeasurable conductor hotspot from ten surface sensors within seconds, at below 9 ms per ${10}^5$ queries. A loss-weight sensitivity study and a three-dimensional cable-end-effect case on a second material configuration are also reported. All reference data are numerical; experimental cable-loop validation remains for future work. Full article

This study presents a comparative analysis of the energy and thermal behavior of a Peltier module operating in hot environments (28 °C to 40 °C) using Python and MATLAB/Simulink. A theoretical block model was developed to define governing equations, while an empirical Python-based framework was implemented to capture real-world non-linearities. Results demonstrate that heat absorption is fundamentally dependent on efficient heat dissipation; a maximum coefficient of performance (COP) of 3.1 was achieved at 1 A. However, operation in hot environments necessitates increased current to maintain low absorption temperatures, leading to a critical “thermal runaway” threshold beyond 5 A where internal Joule heating (scaling quadratically) outweighs the Peltier cooling effect (scaling linearly). While both platforms effectively evaluate heat transfer, the Python-based empirical model provided a more realistic description of cold-side absorption with prediction errors as low as 0.14%. These findings offer a robust pathway for optimizing Peltier cooling with potential industrial applications. Full article

Electrified steam methane reforming (eSMR) is emerging as a promising technology for the decarbonization of the chemical industry and low-carbon hydrogen production by coupling renewable electricity with renewable gaseous feedstocks such as biomethane. In this work, structured Ni-based catalysts washcoated on highly thermally conductive SiC open-cell foams (OCFs) were developed and evaluated for biomethane steam-reforming operating conditions. Two catalyst formulations, 30 wt.% Al₂O₃_30 wt.% CeO₂_20 wt.%Ni and SiC_30 wt.% Al₂O₃_30 wt.%Ce_0.25Zr0.75 O₂_20 wt.%Ni, were tested in a laboratory-scale indirectly electrically heated reformer. The high thermal conductivity of the SiC-structured support ensured efficient heat transfer throughout the reactor, limiting radial temperature gradients to below 10 °C. Both catalyst formulations exhibited excellent catalytic performance; however, the Ce_0.25Zr0.75O₂-promoted catalyst achieved the best results, maintaining equilibrium methane conversion at a gas hourly space velocity above 7000 h⁻¹ while reaching a specific electrical energy consumption of 2.06 kWh/Nm³ of produced H₂ projected for industrial-scale efficiency. Notably, these performances were obtained with a catalyst loading approximately 20–50% lower than that of conventional commercial alumina pellet catalysts. XRD characterization did not reveal the formation of crystalline graphitic carbon after catalytic operation. Furthermore, the structural evolution of the Ce–Zr–O highlights the active role of the mixed oxide in promoting redox processes and maintaining catalytic activity under reaction conditions. Overall, these results demonstrate that the combination of highly conductive SiC-structured supports and Ce–Zr-promoted Ni catalysts significantly enhances both the thermal and catalytic efficiency of eSMR. The proposed catalyst provides a promising route toward compact, energy-efficient, and decentralized hydrogen production from biomethane, supporting the electrification and decarbonization of future hydrogen generation technologies. Full article

Shape Memory Alloy Hybrid Composites (SMAHCs) are promising for morphing structures. However, their transition from laboratory laminates to reliable actuators is hindered by interfacial delamination and the complexity of running real-time control modelling. We address both challenges with a single device and model. We manufactured an elastomer-interfaced SMAHC (E-SMAHC) in a two-step autoclave process that co-cures a rubber-like interface to relieve interfacial shear and embeds a Pt100 sensor adjacent to the wire. We modelled the laminate with a single Timoshenko bimetallic formulation combined with Turner’s effective coefficient of thermal expansion, which lumps the wire’s transformation into a single temperature-dependent coefficient, and added a Euler–Bernoulli contribution for the tip load. We actuated the cantilever by localised Joule heating at three power levels, both unloaded and under a tip load. We calibrated the model coefficients using the unloaded tests. With only the Euler–Bernoulli contribution for the tip load added, the model predicted the loaded tip position with an NRMSE of 6.2–11.7%. An a posteriori refit of the temperature shift using the loaded test data reduced the error to 5.8–6.4%. A preliminary diagnostic further indicates that the wire resistance contains an actuation-related signal, motivating its future evaluation as a possible feedback coordinate. The results provide a proof-of-concept demonstration of an elastomer-interfaced SMAHC actuator and a compact modelling approach under the investigated loading and heating conditions. Full article

The overhead ground wire (OGW) may fracture at the suspension clamp under short-circuit faults, posing a serious threat to the safe operation of transmission lines. However, the dominant damage mechanism—whether Joule heating or arc discharge—remains unclear. This study investigates a 110 kV OGW breakage accident through combined experimental and numerical approaches. Fracture analysis using scanning electron microscopy (SEM) and energy-dispersive spectroscopy (EDS) revealed composite damage featuring both melting and tensile necking, with no fatigue characteristics. A real-scale short-circuit test platform was constructed, which, for the first time, directly captured intense arc discharge phenomena inside the suspension clamp during current flow. A multi-physics finite element model was then developed to decouple and quantify the thermal contributions of Joule heating and arc heating. Results show that Joule heating alone raises the local temperature to only 49.27 °C—far below the melting points of aluminum (660 °C) and steel (1450 °C). In contrast, arc heating elevates the temperature to over 26,000 °C locally, causing rapid melting of aluminum strands and heating of the steel core above 1450 °C within milliseconds. This extreme heat reduces the effective load-bearing cross-section and tensile strength, ultimately leading to fracture under normal operating tension. The findings demonstrate that arc discharge, rather than Joule heating, is the decisive factor in such failures. This study provides a quantitative theoretical basis for fault protection and hardware design optimization of overhead transmission lines. Full article

Flexible thermoelectric textiles have emerged as promising materials for wearable energy harvesting and electrothermal applications because they combine mechanical flexibility with the ability to convert low-grade heat into electrical energy. In this study, reduced graphene oxide/zinc oxide/copper oxide (rGO/ZnO/CuO) hybrid nanocomposites were synthesized and deposited onto Cotton–Nylon–Spandex (80:15:05) stretch fabrics using a silicone elastomer-assisted coating process to develop flexible conductive textiles. The influence of nanocomposite loading (2–8 g/100 mL elastomer) on the structural, electrical, thermal, and thermoelectric properties of the coated fabrics was systematically investigated. SEM, EDX, XRD, and Raman analyses confirmed the successful formation and uniform distribution of the rGO/ZnO/CuO hybrid coating on the textile substrate. Increasing the nanocomposite loading progressively reduced the electrical resistance from approximately 42 to 18 MΩ, indicating the formation of an interconnected conductive network, while the Seebeck coefficient increased from 0.049 to 0.056 mV K⁻¹ (49–56 μV K⁻¹). The measured effective thermal conductivity of the coated textile decreased from approximately 12 to 2.68 W m⁻¹ K⁻¹, reflecting changes in the thermal transport behavior of the composite coating. The coated fabrics also exhibited stable electrical performance under repeated bending, stretching (up to 80% strain), and washing, together with improved thermal stability and uniform Joule-heating behavior. These results demonstrate that the rGO/ZnO/CuO hybrid coating provides an effective strategy for developing flexible, mechanically durable, and multifunctional conductive textiles with potential applications in wearable thermoelectric energy harvesting and smart heating systems. Full article

Joule-heated electric glass melters are highly energy-intensive and operate under stringent throughput, quality, and refractory-protection constraints, yet existing optimization approaches either rely on offline high-fidelity CFD—which is too slow for day-to-day operating decisions—or on purely data-driven energy models that do not enforce physics-based glass-quality constraints. This work presents a simulation-informed supervisory optimization framework that closes this gap by integrating (i) a high-fidelity CFD design of experiments on a cold-top electric glass melter, (ii) interpretable linear reduced-order models (ROMs) for furnace temperatures and glass-process indices (residence time, sand dissolution, mixing, and melting indices), and (iii) a convex linear-program supervisory optimizer that minimizes electrical power subject to throughput, glass-quality, and refractory-protection constraints. Sixteen CFD operating points spanning power inputs of 900–1671 kW, pull rates of 0.12–0.36 kg/s, and cullet fractions of 0–30% are used to fit and cross-validate the ROMs. The novelty of this contribution is the unification of CFD-derived multi-KPI quality constraints with a fast, interpretable supervisory optimizer suitable for advisory deployment on industrial electric melters. For a representative 1350 kW baseline, the optimizer recommends a reduced operating power of 1256 kW (~7% reduction) while satisfying all quality, throughput, and refractory constraints—demonstrating a practical ROM-enabled digital-twin pathway for energy-efficient electric glass melting. Full article

This work presents the design evolution, fabrication, and characterisation of an additively manufactured ring-type thermal airflow sensor for in-pipe flow monitoring, developed employing exclusively Fused Deposition Modelling (FDM) additive manufacturing technology and a commercially available Carbon Nanotube (CNT)-enriched Biopolymer Polylactic Acid (PLA) composite filament. The design evolution proceeds through three progressive stages. In the first stage, a flat heater element is characterised through Constant-Current (CC) Joule heating experiments in order to derive the corresponding Temperature Coefficient of Resistance (TCR) and Thermal Resistance from the obtained experimental data. Consequently, a Finite Element Method (FEM) model implemented in COMSOL Multiphysics^® and calibrated with the extracted material parameters validates the experimental temperature–power relationship and predicts the convective cooling behaviour at various airflow velocities. In the second stage, the geometry is optimised by introducing a conductive trace with a reduced-cross-section central region; as a result, an equivalent thermal localisation is achieved at approximately 26% lower supplied power with respect to the initial heating element, enabled by the design freedom inherent in the FDM process. We should note that the specific sensing geometry can also be directly embedded into any 3D-printed structural component (e.g., a bracket or housing), enabling simultaneous local thermal heating and/or thermal monitoring together with structural functionality within a single printed part. In the third and final stage—the target device—a fully monolithic ring-type airflow sensor is directly integrated into a 3D-printed pipe segment during the printing process. Under constant-current excitation at 40 mA, the device exhibits a monotonically decreasing resistance with increasing airflow (ΔR ≈ 117 Ω over 0–4 m/s) due to convective cooling, while in a single flow-interruption cycle, approximately 79% of the flow-induced resistance change was recovered upon flow removal, with a residual offset of approximately 3% of the heated baseline. A coupled electrothermal FEM model of the device further supports the experimental response by comparing the simulated temperature rise with the values inferred from resistance measurements, while also clarifying the role of the effective internal convective cooling conditions imposed by the pipe geometry. Key features of the proposed device are low raw-consumables cost, fast on-site manufacturing employing a commercially available desktop 3D printer, monolithic construction free of wire-bonded interconnections, and simplicity, indicating its potential for flow monitoring and condition-based maintenance systems aboard vessels as well as in a wide range of industrial sectors. We should note that the present characterisation was performed under laboratory conditions employing a single prototype per design stage; the effects of humidity, salt exposure, vibration, temperature cycling, and material-batch variability remain to be assessed prior to shipboard deployment. Full article

Graphene and its derivatives have attracted sustained research interest as adsorbent materials for environmental applications, driven by their large surface area, chemically tunable surface, and compatibility with a wide range of functional modifications. This review covers recent developments in the use of graphene-based materials for water, air, and soil remediation, focusing primarily on work published over the last five years. A concise overview of graphene, its derivatives, and other carbon nanostructures, such as carbon nanotubes and fullerenes, is also provided. The main graphene derivatives are briefly described (graphene oxide, reduced graphene oxide, graphene nanoribbons, and graphene quantum dots) together with a comparative overview of the principal synthesis methods, from mechanical exfoliation and chemical vapor deposition to liquid-phase exfoliation, oxidation/reduction, and flash Joule heating. The discussion then turns to how surface functionalization and composite formation affect adsorption performance in practice. In water treatment, the results are most developed: functionalized composites have reached adsorption capacities of 484.3 mg g⁻¹ for organic dyes and 157.23 mg g⁻¹ for Cr(VI). Air purification is a smaller but growing area, with plasma-treated graphene aerogels achieving CO₂ capture capacities of 3.3 mmol g⁻¹ and retaining performance over 40 cycles. Soil remediation remains the least explored compartment, though arsenic immobilization efficiencies of up to 99.3% have been reported. Remaining challenges around scalability, behavior in real environmental matrices, and long-term ecotoxicological impact are identified and discussed. Full article