Silicon最新文献

This study investigates the impact of corona aging on the morphology, thermal stability, and electrical performance of silicone rubber–boron nitride (BN) nanocomposites used in high-voltage insulation applications. Nanocomposites containing varying BN loadings were prepared and subjected to controlled corona discharge to assess degradation behavior. Atomic Force Microscopy (AFM) revealed that BN incorporation mitigates surface degradation and reduces roughness, while phase imaging confirmed enhanced nanoscale mechanical stability and partial recovery after aging. Thermogravimetric Analysis (TGA) showed that S0 silicone rubber undergoes significant reductions in onset and peak degradation temperatures and activation energy after corona exposure, whereas BN-filled samples retain higher thermal stability, indicating improved heat dissipation and structural integrity. Electrical characterization using Schottky emission analysis demonstrated that corona aging lowers the barrier height and promotes charge injection in S0 samples, while nanocomposites exhibit minimal change, confirming their superior dielectric resilience. Overall, the results highlight that BN nanofillers effectively enhance the corona aging resistance of silicone rubber by improving its morphological, thermal, and electrical stability, thereby extending its reliability in long-term insulation applications.

This study focuses on the optimization of acid activation of Sabga clay, a locally available natural resource from Cameroon, for the removal of nickel (Ni²⁺) ions from aqueous solutions. Sulfuric acid (H₂SO₄) was employed as the activating agent to enhance the clay’s porosity and surface functionality. A Central Composite Design (CCD) was applied to evaluate and optimize the effects of three key parameters: contact time, acid concentration, and activation temperature on the textural and adsorption properties of the material. The optimization results yielded a quadratic model with a high predictive accuracy for the methylene blue and iodine indices. Optimal activation conditions were determined to be a contact time of 52 min, an acid concentration of 3 M H₂SO₄, and an activation temperature of 70 °C, leading to methylene blue and iodine indices of 8.4 and 248.25 mg/g, respectively. The raw and activated clays were characterized using Fourier Transform Infrared Spectroscopy (FTIR), Scanning Electron Microscopy (SEM), and Brunauer–Emmett–Teller (BET) surface area analysis. Acid activation increased the specific surface area from 16.88 m²/g to 17.89 m²/g (≈ 6% increase) and improved porosity, confirming successful structural modification. Batch adsorption experiments revealed that the adsorption of Ni²⁺ ions was strongly influenced by pH, initial concentration, and contact time, with maximum removal occurring at pH 8. Kinetic analysis showed that the process followed a pseudo-second-order model, indicating chemisorption as the dominant mechanism. The equilibrium data were best described by the Langmuir isotherm, suggesting monolayer adsorption with a maximum adsorption capacity (q_m) of 13.87 mg/g. These results demonstrate that acid-activated Sabga clay is an efficient, low-cost, and eco-friendly adsorbent for the removal of nickel ions from contaminated water. The study provides a statistically optimized activation procedure that can be extended to other heavy metal pollutants and scaled up for sustainable wastewater treatment applications.

This research aims to enhance the structural and optical properties of porous silicon (PSi) for advanced sensing applications through a novel multilayer surface modification. A new modification approach was successfully applied to PSi layers by incorporating a multilayer structure composed of silver (Ag) and gold (Au) nanoparticles along with multi-walled carbon nanotubes (MWCNTs). The modification was achieved via a simple room-temperature immersion process in ionic solutions. The original porous structure was fabricated using a laser-assisted electrochemical etching technique on a high-resistivity silicon substrate (100 Ω·cm), utilizing a 635 nm diode laser with a power density of 150 mW. Comprehensive characterization revealed significant improvements after modification. Increased nanoparticle surface density due to MWCNT integration, enhanced specific surface area up to 339.6 m²/g. Reduced grain size to approximately 1.8 nm. A photoluminescence blue shift of 79 nm. An improvement factor of 9.23 compared to the unmodified PSi. The proposed multilayer modification presents a simple, effective, and low-cost strategy for improving PSi, making it a promising platform for various sensing applications. Also,the increase in surface area after adding MWCNTS from 182.16 g/ m² to 333.96 g/m2, is considered one of the most important enhancements contributed by adding MWCNTS.

In recent years, the rapid development of the photovoltaic industry has led to an increased demand for raw materials used in metallurgical-grade silicon (MG-Si) production, resulting in a large amount of silicon slag. MG-Si refining slag contains large amounts of underutilized silicon resources. Therefore, developing an effective method for silicon recovery is crucial. In this study, a depressant sodium hexametaphosphate (SHMP) was introduced for the flotation separation of silicon from metallurgical-grade silicon (MG-Si) refining slag using 2^# oil as a collector and a frother. The impeller speed was set to 2000 rpm, and the slurry pH was adjusted to 8, followed by 4 min of conditioning during the flotation process. Flotation results revealed that with the increasing concentration of SHMP, the recovery rate of Si increased from 42.47% ± 1.77% to 77.45% ± 4.01%. Additionally, by controlling particle size, it was found that as particle size decreases, the recovery rate continues to increase. This study seeks to provide a more feasible and effective technical route for the large-scale recovery of silicon from MG-Si refined slag. The development of such a route is highly significant for reducing the loss of silicon resources and the clean and sustainable development of silicon industry.

This study investigates the fabrication of sustainable hybrid composites by incorporating Miscanthus fiber (M. fiber) and various weight proportions (1.5, 3, and 4.5 wt.%) of nano-silicon dioxide (SiO₂ NPs) into an epoxy matrix, aiming to optimize mechanical, thermal, and flame-retardant characteristics. Tensile evaluation revealed that the composite containing 3 wt.% SiO₂ NPs achieved the highest tensile strength of 54.6 MPa, representing a 28.6% enhancement compared to the pure Miscanthus–epoxy composites. Similarly, flexural and impact strengths increased by 24.5% and 21.7%, respectively, due to enhanced fiber–matrix adhesion and uniform nanoparticle distribution. Thermogravimetric analysis indicated that thermal stability improved with increasing SiO₂ content. The composite with 4.5 wt.% SiO₂ shows a thermal stability of 427 °C, compared to 392 °C for the neat epoxy system. Cone calorimetry confirmed the enhanced flame-retardant effect; Time to Ignition (TTI) increased from 28 s (for neat epoxy) to 43 s (for the 4.5 wt.% composite); Peak Heat Release Rate (PHRR) reduced from 495 kW/m² to 312 kW/m², and Total Heat Release (THR) was reduced by 35.2%. The residual mass loss (RML) for the 4.5 wt.% hybrid reached 32.6%, indicating a greater yield of thermally stable char. The SEM analysis of the fracture surfaces revealed a noticeable decrease in fiber pull-out for Miscanthus/SiO₂ NPs hybrid composites. These observations underscore the promise of integrating M. fibers with SiO₂ NPs for producing green composites that boast enhanced mechanical properties, improved thermal stability, and stronger fire resistance, suitable for both automotive and load-bearing structural components.

The work aim is to establish the mechanism of influence of silica glass-based optical fiber drawing temperature on its strength. The object of research was silica fiber of 125 μm diameter with a polymer coating of 60 μm thickness. The fiber preform, fabricated by the MCVD method, contained a core doped with 3 mol % GeO₂ and a cladding containing small additions of P₂O₅ and fluorine. Fiber strength was measured by the two-point bending method. When fiber drawing temperature was decreased from 2150 to 1900 °C, its strength degraded from 5.9 to 5.6 GPa. For each fiber drawing temperature, 20 samples were used to evaluate the mean strength value and its standard error (≈ 0.016 GPa). For the first time the nature responsible for the decrease in strength of silica fiber with lower drawing temperatures has been identified. This phenomenon is characterized by a radial viscosity gradient forming in the fiber during drawing. This results in a competition between the elastic deformation of the outer silica glass fiber cladding and the plastic deformation of its inner low-viscosity regions under the influence of the fiber drawing force. A simple mathematical model for estimating the fiber surface stress layer thickness and the magnitude of tensile stresses in it is proposed. Based on the etching rate measurement of the fiber in HF solution, the stressed outer layer thickness of the fiber drawn at 1900 and 1970 °C was measured. The calculated and experimental results for the stressed layer thickness agree well.

Graphical Abstract

Amid the quest for ultra-low power nano scaled devices to mimic the biological neuronal functionalities, this article presents a reconfigurable L-shaped double gate (RL-DG) MOSFET for the realization of spiking neural network (SNN). Using well-calibrated 2D TCAD simulations, both the synaptic and neuronal functionalities of the device have been explored by reconfiguring the front and the back gate respectively. The front gate and the oxide/nitride/oxide (O/N/O) stack is used to imitate the synaptic dynamics while the back gate with unique feature of L-shape offers high rate of impact ionization to emulate the leaky integration behavior. Biological synapse realization of the present device is investigated in terms of paired-pulse facilitation/depression (PPF/PPD). The proposed RL-DG MOSFET when configured as leaky–integrate and fire (LIF) neuron consumes 619.5 fJ energy per spike which is much lower as compared to PD SOI LIF neuron and some of the recently published BTBT, FinFET and FB based neurons. In addition, it also exhibits a higher spiking frequency (in the range of gigahertz) ∼8 order greater than the biological neuron, low threshold voltage of 0.086 V and reduced breakdown voltage of 0.48 V, due to crowding of the electric field lines near the gate edges. The results obtained presume that the proposed L-shaped DG MOSFET with reconfigurable functionality of synapse and neuronal behavior will be a potential candidate for hardware implementation of SNN owing to its ultra-low power energy efficiency and CMOS compatibility.

The environmental and economic issues of conventional silica mining necessitate sustainable alternatives. This study investigates silica nanoparticle extraction from sugarcane bagasse and groundnut shell using an eco-friendly extraction-precipitation method. Comprehensive characterization via SEM, EDX, FTIR, and XRD confirmed amorphous silica synthesis with particle sizes of 25–49 nm and high surface area. Functionalization with trichlorodocecylsilane produced hydrophobic nanocoatings exhibiting water contact angles exceeding 140°, demonstrating excellent protective properties. Response Surface Methodology (RSM) employing central composite design optimized extraction parameters, identifying optimal conditions at 1.68 M NaOH, 77.5 °C, and 92 min, yielding 89% silica with 96% purity (R² > 0.95). A supervised machine learning model based on linear regression successfully predicted silica yield with R² = 0.97 and MAE = 1.26%, validating the integration of data-driven approaches with experimental frameworks. This integrated methodology combining sustainable extraction, statistical optimization, and predictive modeling establishes a robust framework for bio-derived nanomaterial synthesis, aligning with reducing environmental impact.

The fate of nanomaterials in living organisms is significantly influenced by their molecular corona, which dictates their interactions with cells. For instance, silica nanoparticles (SiO₂NP) form biomolecular coronas when exposed to biological fluids, thereby affecting their uptake and cytotoxicity. Understanding these dynamic interactions is crucial to optimize their use in biomedical applications. In this work, the interaction of 18 nm SiO₂NP with DMEM supplemented with FBS varying the molar concentration and time incubation in order to clarify the binding mechanism between biomolecules and nanoparticle surface. In addition, cytotoxic effects have been evaluated using the HUV-EC-C cell lineage, which plays a pivotal role during tissue repair. Biomolecular corona is formed on SiO₂NP upon contact with biomolecules, generating agglomerates by association with other particles, forming colloidally stable, prolate-shaped SiO₂NP@biomolecule structures, whose sizes are modified by the SiO₂NP/bioprotein ratio and incubation time. Polar interactions and partial hydrophobic contributions, driven by enthalpy and entropy, controlled the formation of the dynamic SiO₂NP@biomolecule agglomerates, as confirmed by isothermal titration calorimetry. These interactions alter the fluorescence quenching mechanism of tryptophan residues in the biomolecular corona as well as the cellular uptake efficiency. Cells actively interact with SiO₂NP@biomolecule agglomerates leading to morphological changes and reduced viability/proliferation, depending on nanoparticle concentration. Uptake is modulated by the size of the SiO₂NP@biomolecule agglomerates determined by the SiO₂NP/biomolecule ratio and incubation time. Significant cytotoxicity was observed and cell population was halved after 24 h and 48 h when incubated respectively with 9.8 mM and 4.6 mM of SiO₂NP. However, sublethal doses allowed cellular recovery upon nanoparticle removal. Concluding, our findings suggest that SiO₂NP bioactivity can be modulated by the SiO₂NP/biomolecule ratio and incubation time under the tested conditions, enabling control on cytotoxicity to inhibit cellular expansion, showing the importance of surface chemistry and functionalization in the development of nanomaterials for biomedical applications.

In recent times, wide bandgap semiconductor p-n heterostructure based ultraviolet photodetectors (UV PDs) engrossed the researchers to fabricate in cost-effective routes to utilize in the next generation optoelectronics field. In this work, we have demonstrated the UV photo detection using In/n-TiO₂ nano belts (NBs)/p-Si architecture. GIXRD scan confirmed the formation of TiO₂ NBs film in the anatase phase. FESEM images confirmed the typical surface morphology of TiO₂ that comprises plenty of NBs with an average length of 157.4 nm and width of 80.5 nm. XPS results confirmed the composition of the expected elements as well as BE states of Ti 2p, O1s, Si 2p and C1s states. The UV PD parameters were interpreted with the help of J-V under dark/UV light illumination, EQE, D^*, responsivity and temporal (I-t) data. At 7 V of 375 nm illumination, the constructed In/n-TiO₂ NBs/p-Si UV PD device exhibited reasonable responsivity of 1.06 AW⁻¹, EQE of 351% and D^* of 4.4 × 10¹² Jones, respectively. At 5 V of 370 nm, the I-t data is extracted from In/n-TiO₂ NBs/p-Si PD device displayed faster rise times and fall times of 400 ms and 260 ms. On the other hand, at 7 V of 380 nm UV light illumination, the rise and fall times of 630 ms and 130 ms were calculated. Thus, the fabricated In/n-TiO₂NBs/p-Si PD heterojunction showed reasonable photo detection parameters by means of cost-effective spin coating and conventional electron beam evaporation techniques validates that the TiO₂ NBs based PDs have pronounced prospective in UV sensing applications of the near future.