Silicon最新文献

The production of cement contributes an abundant amount of CO₂ emissions, leading to global warming; therefore, it is necessary to replace cement with alternative cementitious materials. In this research, the materials rich in alumina-silica are mixed with alkali activators in the production of geopolymer concrete. The primary purpose of the study is to develop sustainable high-strength concrete using industrial byproducts in ternary blended geopolymer concrete. The ternary blended mix, which included fly ash, GGBS, and metakaolin in a 60:25:15 ratio, achieved the maximum CS of 62.45 MPa with 1.5% of steel fibres after 28 days of ambient curing. Additionally, a significant improvement in STS & FS was achieved with the increase in fibre content. Durability properties like water absorption, resistance to sulphuric acid, and sodium sulphate solution were evaluated. Test results revealed that GPC has excellent resistance against aggressive environments. The SEM analysis revealed the dense and compact microstructures, with the formation of C-A-S–H and N-A-S–H gels that contributed to the improved hardened properties of the concrete. EDS analysis identified alumina-silicate as the primary component in the geopolymer reaction, and the EDS patterns of all GPC mixes were consistent with the XRD findings. The XRD results showed peaks corresponding to albite and oligoclase minerals, indicating the formation of N-A-S–H and C-A-S–H gels. A strong correlation was obtained from regression analysis between the proposed model equation with experimental results, which can be very useful in predicting CS, STS & FS of concrete.

The SOI MOSFET with an undoped channel offers significant advantages in low-temperature cryogenic electronic circuits compared to Si bulk transistors. These benefits encompass decreased variability, reduced impact of the dopant freeze-out effect, higher mobility, the ability to tune the threshold voltage, and quasi-ideal electrostatic control at cryogenic temperatures. Consequently, silicon-based SOI MOSFET devices have demonstrated considerable promise as a foundational platform for silicon-based spin qubits and quantum information technology. Recognizing the potential of SOI MOSFETs in cryogenic electronic circuits, this paper pioneers the first-time study of the cryogenic behavior of the ultra-scaled 30 nm SOI MOSFET using a fully quantum Non-Equilibrium Green's Function (NEGF) simulation. Through this powerful NEGF simulation, various phenomena of the 30 nm SOI MOSFET are investigated, including improvements in the I_ON/I_OFF ratio, improvements in subthreshold swing (SS) with decreasing temperature, and SS saturation at deep cryogenic temperatures. Additionally, the study delves into various profile variations such as electric field, potential, energy band profiles, transconductance (g_m), and the transconductance-drain current ratio with different temperatures.

The novelity of this work is that the sensitivity of a hetero dielectric Bio Tunnel Field-Effect Transistor (HD-BioTFET) has been successfully predicted using autoregressive integrated moving average (ARIMA) machine learning model with a limited dataset obtained from TCAD simulations. HD-BioTFET is a charge plasma based label-free biosensor where, a high-K dielctric (TiO_2) introduced over source region promotes band-to-band tunneling and hence, a improvement in senstivity of (2times 10^{7} ) in HD-BioTFET than (1.6times 10^{7}) of BioTFET for K=10. Also, the senstivity improved for charged biomolecules is (2.6times 10^{8}) (A/mu m ) in HD-BioTFET than (1.35times 10^{8}) (A/mu m ) in BioTFET and (1.34times 10^{3}) (A/mu m ) in HD-BioTFET than (5times 10^{2}) in BioTFET for ± 1e13 charge values, respectively. A small dataset of 40 rows and 4 coloumns obtained during optimization of HD-BioTFET is then used for training of Machine Learning (ML) models such as convolutional neural nework (CNN), artificial neural network (ANN), and ARIMA that serves the purpose of low computational power. However, due to the limited dataset, CNN and ANN fail, whereas ARIMA excels by handling sequential data and nonlinearities. ARIMA successfully predicted the drain current of the device, achieved 98% accuracy and F1 score = 1 for unknown K =3, 4.1, 4.6, 5, and 7 values and 98% accuracy and F1 score = 0.5 for unknown charged ( range± 4e11, ± 8e12, and ± 3e13) biomolecules. Hence, the sensitivity of HD-BioTFET for ARIMA predicted output and simulated output are closely matched, which justify the integration of ML to the biosensing application that promises a cost-effective, label-free, low-powered, and a higly accurate sensitive prediction solution.

Silicon (Si) plays a pivotal role in improving soil functionality and mitigating abiotic stress, particularly in regions where poor soil fertility and extreme climatic conditions constrain agricultural productivity. In the São Francisco Valley, northeastern Brazil, sandy soils with low organic matter content present significant challenges for onion (Allium cepa L.) cultivation. Thus, we hypothesize that higher doses of silicon fertilization could adversely impact microbial biomass and activity, potentially disrupting nutrient cycling and affecting agricultural sustainability. This study investigated the effects of silicate fertilization at rates of 0, 75, 125, 175, and 225 kg ha⁻¹ on microbial biomass carbon (C-mic), basal respiration (C-CO₂), metabolic quotient (qCO₂), microbial quotient (qMic), enzymatic activity, and organic carbon content. Low silicon application rates (75 and 125 kg ha⁻¹) markedly enhanced C-mic by 53% and 44%, respectively, relative to the control, along with substantial increases in the activities of β-glucosidase (73%), alkaline phosphatase (115%), and arylsulfatase (68%). Conversely, excessive Si input (225 kg ha⁻¹) triggered a pronounced rise in C-CO₂ emissions, up to eightfold higher than the control, indicating intensified microbial metabolism and accelerated organic matter decomposition. Concurrently, qCO₂ values increased by 110%, reflecting greater microbial stress and reduced carbon-use efficiency. These results highlight the complex interplay between Si fertilization and soil microbial dynamics, guiding the optimization of nutrient management in dryland agroecosystems. Proper Si supplementation can enhance soil fertility and microbial efficiency, supporting sustainable crop production in tropical environments.

This work investigates the synthesis, characterization, and device integration of CoAl₀.₂Fe₁.₈O₄ thin films fabricated via the sol–gel auto-combustion method. Structural analysis using X-ray diffraction confirms the formation of a cubic spinel phase with successful incorporation of Al³⁺ ions, preserving crystallographic integrity while inducing slight modifications in lattice parameters. Morphological studies using SEM and TEM reveal quasi-spherical nanoparticles with mean sizes ranging between 25–40 nm, exhibiting controlled agglomeration favorable for electromagnetic applications. UV–Vis-NIR spectroscopic measurements highlight strong absorbance in the UV–visible region and high diffuse reflectance in the near-infrared, with optical band gaps estimated at 1.98 eV (direct) and 2.59 eV (indirect), supporting potential for optoelectronic uses. Current–voltage (I-V) characterization of Ag/CoAl₀.₂Fe₁.₈O₄/p-Si/Al heterojunctions reveals excellent rectifying behavior with temperature-dependent diode parameters and barrier heights, modeled via thermionic emission and Norde's methods. Findings demonstrate that Al-substituted CoFe₂O₄ thin films possess tunable structural and electronic features, making them promising candidates for optoelectronics applications.

This study investigated the use of biomass ash as an additive for reducing the boron (B) content in industrial silicon (Si). Coffee shell, a biomass rich in alkali earth metals, was selected for its potential to effectively remove non-metallic impurities from industrial silicon. A series of single-factor experiments was designed to systematically examine the effects of biomass ash content, smelting temperature, and refining time on B removal. The experimental results indicated that under optimized process conditions, the ideal biomass ash addition was 5 wt.%, the suitable smelting temperature was 1500℃, and the optimal refining time was 240 min. Under these conditions, the B content in industrial Si was significantly reduced from 100.46 ppmw to 12.08 ppmw, thereby achieving a removal rate of 87.98%. This method offered a novel approach for purifying industrial Si and facilitating the effective utilization of biomass resources. It has significant implications for advancing the sustainable development of the Si materials industry.

The present study investigates the efficiency of Cyclic Olefin Copolymer (COC) combined with Magnesium Fluoride (MgF₂) as an antireflective sheet for boosting the power conversion efficiency (PCE) of solar photovoltaic cells. The anti-reflective sheets were prepared by incorporating MgF₂ at varying weight percentages of 1–4 wt% with COC and labelled as COCM1, COCM2, COCM3, and COCM4 respectively. The anti-reflective sheets were fabricated using fused deposition modelling (3D printing) technique to ensure precise and uniform layer deposition. Optical, electrical, and structural characteristics of the sheets were systematically evaluated. The photovoltaic sample covered with COCM3 sheet showed minimum reflection of 5.27% respectively. Among the samples, COCM3 (3wt% of MgF₂) demonstrated the lowest resistivity of 5.38 × 10^–3 Ω-cm, highest hall mobility of 12.66 cm² V⁻¹ s⁻¹, and maximum carrier concentration of 35.53 × 10²⁰ cm⁻³ respectively. Correspondingly, COCM3 exhibited the highest PCE of 16.41% in sunlight exposure and 18.02% in controlled atmosphere, indicating superior antireflective performance. The results highlight that the addition of an optimum MgF₂ concentration prominently increases the electrical and optical behaviour of the anti-reflective sheets, establishing 3wt% as the ideal loading for enhancing solar cell performance. This research confirms the potential of COCM antireflective sheets as an effective and optimal anti-reflective material for photovoltaic applications.

A novel all-optical U-shaped 4 × 2 encoder based on two-dimensional silicon photonic crystals is designed to achieve ultra-fast operation, compact size, and a high contrast ratio, targeting applications in computing and all-optical logic systems. The silicon encoder structure, composed of a U-shaped power splitter, a nanocavity, and biperiodic waveguides, significantly enhances performance by increasing the contrast ratio while minimizing power loss and return loss. The photonic crystal is formed by a periodic array of high-refractive-index silicon rods embedded in a low-index dielectric medium, providing strong light confinement and guiding capabilities. The photonic band structure is analyzed using the Plane Wave Expansion (PWE) method to ensure bandgap suitability for the targeted wavelength. Functional parameters such as response time, delay time, steady-state time, insertion loss, bit rate, contrast ratio, and extinction ratio are numerically estimated using the two-dimensional Finite-Difference Time-Domain (2D-FDTD) technique at an operational wavelength of 1550 nm. To assess material impact, the proposed U-shaped silicon encoder is analyzed using different core materials, including Indium Phosphide (InP) and Gallium Arsenide (GaAs), in addition to silicon. The comparison reveals that the silicon-based encoder outperforms the others by achieving the maximum contrast ratio of 29.2 dB, minimal crosstalk of -29.2 dB, and an ultra-compact footprint of 246µm². The silicon encoder also demonstrates a high data rate of 2.083Tbps. These promising results indicate that the optimized silicon photonic crystal encoder is well-suited for compact, high-speed, and scalable integration in photonic logic and computing circuits.

Silica nanoparticles (SiNPs) have been reported to alleviate the negative impacts of different environmental stresses. However, studies concerning the mitigation of salinity stress in soybeans are limited. Keeping this in consideration, the present study aimed to evaluate the efficacy of SiNPs in ameliorating the impact of salinity stress in Glycine max (soybean). In this regard, 0, 1, 5, and 10 g/L of SiNPs were used in tandem with NaCl concentrations of 0, 100, 200, and 300 mM. The results indicated that all applied concentrations of SiNPs under salinity improved seed germination attributes, along with growth, photosynthesis, ionic and osmotic balance, membrane integrity, and managed oxidative stress in both seedling and vegetative stages. Amongst all the concentrations, 10 g/L SiNPs showed the best results. The positive results of SiNPs could be correlated to the better availability of Si in the roots, which improved the uptake and translocation of Si in plants, ultimately reducing Na⁺ and improving K⁺ accumulation. 10 g/L SiNPs improved Si accumulation by 1.62 and 1.55 folds; reduced Na⁺ accumulation by 3.53 and 8.26 folds; and improved K⁺ accumulation by 1.55 and 1.59 folds, respectively, in soybean seedlings and vegetative plants under 300 mM NaCl stress. Therefore, it can be concluded that the SiNPs have great potential to be developed as a fertilizer to improve plant health even in the presence of salinity stress. However, further studies need to be conducted to address the efficacy of SiNPs-based nanofertilizers for field applications, their optimal dosage, and environmental safety concerns.

Silicon heterojunction (SHJ) solar cells, which combine crystalline silicon wafers with thin amorphous silicon layers, have rapidly advanced as a leading photovoltaic technology due to their high efficiency, excellent passivation, and low temperature coefficients. However, their performance is challenged by high optical reflection and increased series resistance, particularly in the absence of anti-reflection coatings (ARCs) and transparent conductive oxide (TCO) layers. ARCs, especially advanced multilayer structures like SiO₂/TiO₂ and Al₂O₃/ITO, are crucial for minimizing reflection and maximizing light absorption across a broad spectrum, while TCO layers enhance lateral carrier transport and reduce resistive losses, though they can introduce parasitic absorption that must be carefully managed. TCO-free designs can improve transparency and short-circuit current density but are limited by higher resistive losses. Recent advancements focus on optimizing ARC and TCO configurations to balance optical and electrical performance, reducing reliance on scarce elements such as indium, and developing novel passivation and contact architectures, with efficiencies now exceeding 26% and fill factors above 86%. Future research is directed toward indium-free TCOs and innovative ARC designs to further improve the efficiency, sustainability, and scalability of SHJ solar cells, supporting continued progress in photovoltaic technology.