Polysilicon Research Articles

Ultraviolet Laser Activation of Phosphorus‐Doped Polysilicon Layers for Crystalline Silicon Solar Cells

AbstractIn crystalline silicon photovoltaics (c‐Si PV), a pulsed laser can be used as a substitute for a high‐temperature furnace dopant diffusion/activation step. In contrast to furnace‐based activation, lasers can be used to achieve highly localized doping with controlled dopant concentrations, useful in advanced architectures such as the interdigitated back contact (IBC) solar cell. In this study, a pulsed ultraviolet (UV) laser is utilized for phosphorus dopant activation within a low‐pressure chemical vapor deposited (LPCVD) polycrystalline silicon (poly‐Si) passivated contact layer. The highest implied open‐circuit voltage iVoc values achieved using this approach reach 726 mV. However, this comes at the expense of high specific contact resistivities ρc, which is attributed to a lower dopant concentration across the poly‐Si(n+)/SiOx/c‐Si interface. Regardless, the optimum iVoc, ρc combination is measured at a laser fluence of 0.78 J cm−2 producing values of 712 mV and 89 mΩ‐cm2, respectively. These values are still compatible with high‐efficiency solar cell designs, underscoring the feasibility and effectiveness of this approach.

Enhancement of the quality of mc-Si ingot grown by vacuum directional solidification furnace with growth rate increase reducing the cost of the wafer for PV application: Carbon and oxygen analysis

In this paper, we propose a numerical model to investigate the dissolution of oxygen atoms from the porous silica crucible, SiO gas formation, back diffusion of CO gas and segregation of carbon and oxygen during the growth of multi-crystalline silicon (mc-Si) by vacuum directional solidification (VDS) at different growth rates (3, 6 and 9 mm/h) by silt valve opening rate. The dissolution of oxygen decreases during the rapid growth of ingot because the reaction between the molten silicon and the porous silica crucible is constrained. This limitation on oxygen dissolution from the porous silica crucible further diminishes chemical reaction inside the VDS furnace. Consequently, the segregation pattern of the carbon and oxygen is affected at higher growth rate. During the VDS mc-Si growth, a growth rate of 9mm/h yields better quality of the VDS grown mc-Si ingots compared to other growth rates, this rate reduces SiC precipitation and SiO2 cluster formation due to lower concentration of carbon and oxygen. The obtained carbon concentration minimizes the wire saw defects. Based on these numerical results (9 mm/h), we have implemented experimental work. Prepared samples are analyzed using FTIR spectra and minority carrier lifetime measurements. The effect of oxygen concentration in the samples is analyzed in the minority carrier lifetime measurements. The oxygen and carbon concentrations are calculated by FTIR spectra and their results are compared with the numerical simulation.

Image quality enhancement in variable refresh rate LTPO-based AMOLED displays using a gate in panel voltage compensation scheme

This study investigated novel driving scheme for low-temperature polycrystalline silicon and oxide (LTPO) active-matrix organic light-emitting diode (AMOLED) displays under variable refresh rate (VRR) driving conditions with aim of reducing the brightness instability (i.e., flicker and luminance variation) for seamless performance. The mechanisms underlying brightness fluctuations in displays were examined, focusing on frequency-dependent differences in gate-inpanel (GIP) operations. Notably, our study revealed additional factors within the GIP operation that cause LTPO flicker and VRR performance, in addition to previously identified factors of thin-film transistor hysteresis and OLED charging. Consequently, variable GIP voltage driving method that reduced these issues and enhanced display performance was proposed. The proposed method could minimize brightness fluctuations to levels imperceptible to users and facilitate performance improvement through driving options in peripheral circuits without modifying panel design and is applicable across various applications utilizing LTPO OLED technology. Its driving scheme was validated through simulation and measurement of luminance variation during frequency transition using 6.0-inch LTPO-applied AMOLED displays. The experimental results indicated a decrease in luminance difference from 14.2% to 1.5%, particularly at extremely low brightness level of 0.2 nit. The luminance distortion decreased from 7 to less than 1, which is a just noticeable color difference (JNCD).

A New Back-End-Of-Line Ferroelectric Field-Effect Transistor Platform via Laser Processing.

The discovery of ferroelectricity in hafnia-based materials has revitalized interest in realizing ferroelectric field-effect transistors (FeFETs) due to its compatibility with modern microelectronics. Furthermore, low-temperature processing by atomic layer deposition offers promise for realizing monolithic three-dimensional (M3D) integration toward energy- and area-efficient computing paradigms. However, integrating ferroelectrics with channel materials in FeFETs for M3D integration remains challenging due to the dual requirement of a high-quality ferroelectric-channel interface and low-power operation, all while maintaining back-end-of-line (BEOL)-compatible fabrication temperatures. Recent studies on 2D semiconductors and metal oxide channels highlight these challenges. Polycrystalline silicon (poly-Si), a channel material long integrated into the semiconductor industry, presents a promising alternative; however, its high fabrication temperature has hindered its applications to M3D integration. To overcome this challenge, wedemonstrates a BEOL-compatible FeFET platform using poly-Si channels fabricated via locally-confined laser thermal processing and hafnia-based ferroelectrics by low-temperature atomic layer deposition with wafer-scale uniformity. The local nature of the laser processing mitigates the trade-off between the high-temperature crystallization for the quality of the interface and BEOL thermal budget constraints. The laser-processed FeFETs boast the largest effective memory widow for all BEOL-compatible FeFETs. Moreover, the fabricated FeFETs are integrated into wafer-scale synaptic arrays for neuromorphic computing, achieving record-high energy efficiency. Therefore, this work establishes a promising BEOL-compatible FeFET materials platform toward M3D integration.

Sustainable management of end of life crystalline silicon solar panels in Australia: Advancing circular economy practices

The worldwide adaptation of Photovoltaic (PV) technology as a sustainable alternative to fossil fuels, has experienced exponential growth in recent years. However, the lack of effective waste management policies has hindered efficient PV panel disposal and recycling practices. In the absence of effective policies, the worldwide End-of-Life (EoL) PV module accumulation is predicted to reach a critical stage in the early 2030s. This study examines the environmental impacts of different EoL management practices using Life Cycle Assessment (LCA), based on a comprehensive database generated from both literature and industrial data. Five different EoL scenarios were considered for 1000 kg of Crystalline Silicon (c-Si) PV modules with a focus on Australia as a case study, while considering the energy recovery options and emphasizing the economic benefits. From a comprehensive LCA study, it is found that upcycling options reduce the environmental impacts significantly compared to downcycling, while chemical treatment emerges as a preferred option, demonstrating a reduced environmental burden. Nevertheless, the utilization of toxic chemicals during chemical treatment-based PV recycling needs to be reconsidered. Additionally, the usage of chemicals during the metal recovery process of PV module recycling caused the highest environmental burden, necessitating the importance of moving to greener treatment practices. This research study will enable the identification of optimum EoL c-Si module recycling options, contributing to sustainable waste management.

Electric-field assisted silicon nanowire field effect transistor for the ultra-low concentration nucleic acid detection

Ultra-low concentration nucleic acid detection is crucial for disease diagnosis and prognosis. Silicon nanowire field-effect transistors (SiNW FETs) are promising due to their sensitivity, real-time capabilities, and compact design. A critical consideration for FETs is the reaction time required for nucleic acid diffusion to the detection surface, especially at low concentrations. This study utilizes polycrystalline silicon nanowire FETs (poly-SiNW FETs) as biosensors, employing a negative voltage on the liquid gate used for detection to create an electric field. This field accelerates nucleic acid diffusion towards the sensor surface to interact with immobilized probes. We adjusted the gate voltages and target solution injection flow rates to identify optimal parameters for nucleic acid detection and how the electrical field accelerates hybridization kinetics. We varied the probe immobilization times to show that higher ligand density accelerates the interaction with the immobilized probe. The study demonstrated stable diffusion of target DNA by combining FET with an electric field of −1 V and a slow injection flow rate, reducing the equilibrium time from 60 to 20 min. Additional improvement was achieved by enhancing probe immobilization density and applying an electric field, resulting in a faster probe-target hybridization reaction rate. These efforts significantly improved the signal to maintain superior performance and reduced the time required to reach equilibrium. This research pioneers using an external electric field to expedite detection time in field-effect transistors, demonstrating the potential for accelerated nucleic acid detection in nanowire FETs.

Enhanced Photovoltaic Efficiency through 3D-Printed COC/Al₂O₃ Anti-Reflective Coversheets

In the past few years, there has been a considerable growth in the utilization of solar cells to produce electrical power to fulfil the growing worldwide energy demands. An optical loss is a crucial factor that impacts the performance of the photovoltaic conversion process. This loss occurs when incoming sunlight is reflected back on the outer layer of the photovoltaic cells. The application of antireflective materials on the photovoltaic substrates can enhance the absorption of sunlight and minimize the reflection. Currently, there is no ideal anti-reflective coating for solar cells that can allow the transmission of sunlight without any reflection. In this research, a transparent cyclic-olefin-copolymer (COC) was used to fabricate anti-reflection (AR) coversheet by fused deposition modelling process (3D printing). Further, the aluminium oxide Al2O3 powder was added at the proportions of 1wt%, 2wt%, 3wt%, and 4wt% to the COC polymer to increase the anti-reflection characteristics. The structural, morphological, mechanical (tear strength), electrical and temperature characteristics were studied. The performance of COC with aluminium oxide (COCA) coversheets was evaluated, and the findings revealed a considerable increment in power conversion efficiency (PCE) of 17.21% (sunlight exposure) and 18.34% (neodymium light) for COCA3 coversheets. As seen, the COCA3 sample exhibit lower electrical resistance of 3.88 ×10-3 Ω cm, carrier concentration (36.91×1020 cm-3) and higher hall mobility (13.67 cm2/Vs). The findings from the investigations demonstrated that the utilization of COC with Al2O3 powder (COCA) can be a suitable antireflective coversheet material for boosting the performance of polycrystalline silicon photovoltaic cells.

Analysis of degradation mechanism in polycrystalline silicon thin-film transistors under dynamic off-state stress with fast transition time

Abstract This study represents the investigation into the degradation of polycrystalline silicon (poly-Si) thin-film transistors (TFTs) under dynamic off-state stress, with a focus on transition times as rapid as 1 nanosecond (ns). The study found that dynamic off-state stress with larger amplitude leads to more severe device degradation. Unlike previous studies, both the rising time (t r ) and falling time (t f ) of the pulse significantly influence the hot carrier (HC) degradation in the poly-Si TFTs. The on-state current degradation rate (ΔI on ) after 104 s stress dramatically increases from 11.8% to 80.8% when t r decreases from 500 ns to 1 ns. When t f decreases from 500 ns to 1 ns, ΔI on also dramatically increases from 22.9% to 69.2%. Combined with transient simulations, the source of the carrier for HC degradation is clarified and consequently, a non-equilibrium PN junction degradation model modulated by accumulated electrons is developed.

Comparative Study of Indium Oxide Films for High‐Mobility TFTs: ALD, PLD and Solution Process

AbstractDeposition of indium oxide base films for high‐mobility thin film transistors (TFTs) has been an important part in the implementation of high‐resolution and high‐frequency display back panels. In this study, three types of In2O3 (InO) films have been fabricated for TFTs using atomic layer deposition (ALD), pulsed laser deposition (PLD), and solution process, respectively. ALD‐derived InO films show controllable grain formation and optimized TFTs show the field effect mobility of ≈100 cm2 V−1s−1 in both the conventional transistor measurements and critical four‐probe measurements, reaching the level of low‐temperature polycrystalline silicon (LTPS). Combined spectroscopy investigations show that the ALD‐derived InO film features advantages as compared to those of the PLD‐deposited and solution‐processed InO film in providing a smoother surface morphology, good crystallinity, and more orderly atomic growth mode. Moreover, the bias‐stress stability of ALD‐derived TFTs can be improved with further passivation.

Research on the reliability of wire web in diamond multi-wire saw slicing photovoltaic monocrystalline silicon wafer

Diamond multi-wire slicing technology is the main method for producing the solar cell substrate based on monocrystalline silicon. To reduce the production cost and increase the production efficiency during the sawing process, the diameter of the diamond saw wire is becoming thinner, and the sawing speed is getting faster, which leads to an increasingly prominent problem of saw wire breakage during the slicing process. To understand the breaking characteristics of diamond saw wire and evaluate the reliability of the saw wire during the sawing process, the tensile testing of saw wires was carried out in this paper. And based on the Weibull function, the breaking force was analyzed statistically. A maximum tension force model for the saw wire during the sawing process was established. And based on the maximum tension force model and Weibull reliability function, the influence of various process parameters on the reliability of the wire web was analyzed. The results indicated that as the usage time of the saw wire increases, the breaking force gradually decreases and stabilizes. Compared to the fresh saw wire, the reliability of the used saw wires is significantly reduced. As the abrasive distribution density and the wire speed increases, the reliability of the wire web gradually increases. Conversely, as the feed speed and the pretension of the saw wire increase, the reliability of the wire web gradually decrease. The results of this paper provide a theoretical approach for assessing the reliability of diamond saw wire web during the sawing process. It also provides guidance for optimizing process parameters to enhance the reliability of the wire web.

Degradation of crystalline silicon solar cells caused by lightning induced impulse surge

Abstract Crystalline silicon (c-Si) solar cells are connected in series to form photovoltaic modules, which are installed in wide-open areas. They are exposed to lightning electromagnetic (EM) interference at high risk. The lightning EM field can induce an impulse surge in the loop of the solar-cell string, and c-Si solar cells are prone to damage. To study the effect of lightning surge on monocrystalline silicon cells and polycrystalline silicon cells, impulse voltage tests are conducted. Semiconductor structures of c-Si solar cells after testing are observed using scanning electron microscopy. The results indicate that the lightning surge will generate some cracks and defects in the P–N junction. Under a strong electric field, the N-type emitter layer and the grain boundary can be destroyed, which contributes to the degradation of the c-Si solar cell. Compared to monocrystalline silicon cells, polycrystalline silicon cells can withstand greater forward lightning surge; however, their maximum reverse lightning surge is relatively low.

Enhancing performance of microbolometers by utilizing low-temperature polycrystalline silicon

In response to the urgent need for advanced noncontact temperature sensing technologies to mitigate pandemic transmission, there has been a notable surge in global demand. Thermal cameras, combined with infrared sensors, are critical not only for high-resolution imaging but also for cost-effective commercialization. Amorphous silicon-based microbolometers offer advantages in terms of integration and cost compatibility with conventional silicon processes. However, they suffer from limitations in their electrical properties, particularly in the noise-equivalent temperature difference. This study examines the effectiveness of low-temperature polycrystalline silicon (poly-Si) as an active material for microbolometer cells compared to amorphous silicon, focusing on improving the temperature coefficient of resistance (TCR) and lowering the noise density. Our investigation reveals that various parameters, such as dehydrogenation temperatures ranging from 350 to 550 °C, diverse laser annealing techniques (including single, step and multishot methods), and laser power density levels ranging from 150 to 300 mJ/cm2, influence the grain size trends of poly-Si. Using these methods, we produced poly-Si films with grain sizes ranging from 15 to 40 nm, which were used as the active layer in bolometer cells. The final part of our study assessed the TCR and noise density in devices with different poly-Si grain sizes. The TCR/noise density ratio was 3.5 times better in poly-Si devices compared to amorphous silicon devices. This study evaluates poly-Si as an active material for microbolometers, paving the way for future research and development in next-generation infrared sensor technology.

On the absorption coefficient of GaP1-xNx layers and its potential application for silicon photovoltaics

The absorption coefficient and the energy gap of GaP1-xNx layers has been obtained by spectroscopic ellipsometry for samples grown on Si(001) substrates by chemical beam epitaxy with N mole fractions in the range 0 ≤ x ≤ 0.081. The resulting absorption spectra exhibit a direct band-like behavior near the absorption edge. The absorption coefficient values increase with the N content, reaching values in the range α ∼ 1-2x104 cm−1 in the vicinity of the absorption edge below the original GaP direct bandgap, which are comparable to those obtained for high efficiency solar cell materials. Furthermore, dependence of the absorption coefficient with increasing N content points to a strong GaP Γ-like character of the conduction-band wave function of GaP1-xNx alloys near the Brillouin zone center at k = 0, as predicted by the band anticrossing model. Bandgap energy values obtained by spectroscopic ellipsometry are compared with previous values obtained by photoluminescence measurements on the same samples, observing a shift of about 50–100 meV. Finally, the value of the band anticrossing parameter coupling the N level and the host GaP conduction band has been obtained from the dependence of both, the bandgap and the absorption coefficient, with the N content (2.1 and 3.3 eV respectively).

Sintering polycrystalline silicon carbide composite ceramics with ultra-high hardness under high pressure

Silicon carbide (SiC) is an important structural ceramic material, exhibiting exceptional comprehensive properties that are unmatched by metals and other structural materials. In this study, a combination of α-SiC micron powder and β-SiC nanopowder was utilized as precursor materials for high pressure and high temperature (HPHT) sintering. Under a pressure of 5.0 GPa, polycrystalline SiC samples with mixed grain size were sintered within a temperature range from 1000 to 1700 °C, and compared with SiC samples sintered from single micron powder under identical temperature and pressure conditions. The microstructures of the two sets of SiC samples were observed using scanning electron microscopy. Additionally, the stress states and strengthening mechanisms among SiC grains with mixed grain size under HPHT were further analyzed in conjunction with X-ray diffraction results. The polycrystalline SiC composite ceramics sintered at 1700 °C exhibited superior mechanical and thermal properties, achieving a Vickers hardness of 35.2 GPa that is 23.5 % higher than that obtained by conventional spark plasma sintering and even surpassing the hardness of single crystal SiC, demonstrating thermal stability up to 1405 °C in air environment. Transmission electron microscopy was employed to analyze defects and plastic deformation in these samples. The study suggests that the primary strengthening mechanisms of the sintered polycrystalline SiC composite ceramics under HPHT include the increase in micro defects induced by in-situ plastic deformation at elevated temperatures and the effects of high-temperature creep. This study provides new insights into the HPHT sintering of hard materials.

Polycrystalline silicon photovoltaic cell defects detection based on global context information and multi-scale feature fusion in electroluminescence images

In photovoltaic (PV) cell inspection, electroluminescence (EL) imaging provides high spatial resolution for detecting various types of defects. The recent integration of EL imaging with deep learning models has enhanced the recognition of defects in PV cells. However, the high surface impurity content in polycrystalline silicon PV cells presents a challenge. Defect features can be similar to complex background textures, making highlighting features for small target defects difficult and leading to potential misclassification as background or other classes. To address these challenges, we propose a novel deep convolutional neural network (CNN) model for effectively identifying small target defects in polycrystalline PV cells. We first utilize a global context information (GCI) block to improve CNN’s modeling of global information, aiding in distinguishing PV cell defects with similar local details. Moreover, we design a channel weight feature pyramid (CWFP) that dynamically adjusts the channel weights of extracted features. We further achieve multi-scale feature fusion through the pyramid structure to enhance the resolution capability for small targets. The proposed model was evaluated on a publicly available dataset of 8 defect classes in polycrystalline PV cells, achieving an accuracy of 96.36 %. The experimental results show that the proposed model outperforms existing deep learning models in detecting small target defects with higher precision.

Reliable Prediction of Solar Photovoltaic Power and Module Efficiency using Bayesian Surrogate Assisted Explainable Data-Driven Model

This study proposes a Bayesian surrogate-driven explainable deep neural network model to predict and interpret the module efficiency and maximum output power of three commercially available photovoltaic modules: monocrystalline silicon, polycrystalline silicon, and amorphous silicon during the winter season. In addition, the influence of the photovoltaic material and ambient conditions on the predicted power and module efficiency is investigated. The model inputs include solar irradiance, module material (monocrystalline, polycrystalline, and amorphous silicon), season of the year (months), and time of day (morning to evening). Experiments were conducted on these three modules during the winter using data from Rawalpindi, Pakistan. These data were then fed into the deep neural network model to train and yield predictions. Several preprocessing techniques such as logarithmic transformation, square root, cube root, reciprocal, and exponential transformations are employed to improve the linearity of distributed data. For hyper-parameters optimization, Gaussian process, gradient boost regression trees, and random forest are used. The results show that the optimal deep neural network using random forest surrogate model along with square root and exponential transformation is able to predict the maximum power output and module efficiency of the considered photovoltaic modules for the entire investigated period with a correlation coefficient, R2 = 0.998. The least accurate model (R2=0.991) is a Gaussian process using simple data distribution. These results hold valuable insights for predicting and optimizing the performance of other solar photovoltaic modules in various climates and different seasons of the year.

Electrical Performance and Degradation Analysis of Field-Aged PV Modules in Tropical Climates: A Comparative Experimental Study

Performance degradation is a prevalent phenomenon in solar photovoltaic systems globally, with varying aging profiles and effects depending on environmental and climatic conditions. This paper presents an extensive investigation of the electrical performance, aging mechanisms, and degradation analysis of field-aged PV modules under the tropical climate of Malaysia. Utilizing a combination of visual inspection, I-V curve measurement, and thermal imaging techniques, this research provides a comprehensive assessment of the electrical and thermal properties of field-aged PV modules from two locations in Malaysia over extended periods (8 years at UMPSA and 10 years at Pasir Mas). The multi-faceted approach of the study allows for a deeper understanding of the degradation process, offering insights into the causes and effects of higher current and lower voltage in aged modules. The study found the average annual degradation rates at UMPSA were 0.3% for open circuit voltage (Voc), 0.23% for short circuit current (Isc), 0.81% for maximum power (Pmax), and 0.35% for fill factor (FF) and at Pasir Mas, the average annual degradation rates were 1.124% for Voc, −0.166% for Isc, 1.276% for Pmax, and 0.43% for FF. The study also found that monocrystalline silicon (m-Si) panels experienced an average power degradation of 6.48%, while polycrystalline silicon (p-Si) panels showed a higher degradation of 12.76%. However, Thermal imaging revealed significant temperature variations across the modules, with hotspots reaching up to 11.2 °C above cooler areas in UMPSA panels and an even more pronounced 26.1 °C difference in Pasir Mas modules. These temperature disparities highlight the uneven heat distribution and potential performance issues in the panels. This research contributes to the understanding of PV module degradation in tropical climates and aligns with sustainable development, climate change mitigation efforts, and SDG 7 by promoting sustainable energy solutions.

Formation of n-type polycrystalline silicon with controlled doping concentration by flash lamp annealing of catalytic CVD amorphous silicon films

We investigated the properties of polycrystalline silicon (poly-Si) films formed by the flash lamp annealing (FLA) of hydrogenated amorphous Si (a-Si:H) films. Phosphorus- (P-) doped a-Si:H films with a thickness of several micrometers deposited by catalytic chemical vapor deposition (Cat-CVD) on a silicon nitride- (SiN x -) coated textured glass substrate are crystallized by FLA. P doping was achieved by flowing phosphine (PH3) during Cat-CVD, and the P concentration was controlled within a range of 1016–1021 cm−3, which was measured by secondary ion mass spectrometry. We also fabricated simple back-contact Si heterojunction solar cells to estimate a potential of flash-lamp-crystallized poly-Si as an absorption layer. The current-density–voltage (J–V) characteristics of the cells measured under 1 Sun light irradiation show an open-circuit voltage (V OC) of >0.4 V.

Numerical analysis on performance evaluation of photovoltaic thermal systems using ternary hybrid nanofluids and forced convection around copper cylinders

This study evaluates the performance of a photovoltaic thermal (PV/T) system using forced convection and ternary hybrid nanofluids, comprising water with cobalt, zinc, and silver. The PV/T system includes a glass absorber, polycrystalline silicon, and a flow channel with eight copper cylinders, positioned at 20 %, 40 %, 60 %, and 80 % along the channel, both above and below the flow path for optimal thermal conductivity. The working fluid is modeled under turbulent, steady-state conditions using the κ−ε turbulence model.Numerical simulations via COMSOL Multiphysics 6.0 evaluate the system's thermal and fluid dynamics, focusing on local Nusselt numbers and photovoltaic cell thermal efficiency compared to a baseline. The investigation spans Reynolds numbers from 10,000 to 100,000, nanoparticle volume fractions of 1 %–20 %, and aspect ratios of 0.1–0.3. The aspect ratio in this study is defined as the ratio of the height of a square obstacle within the flow channel to the total height of the flow channel. A supervised machine learning framework develops predictive regression models for system analysis. Results show fluid force at the outlet increases by about 1200 % and 1300 % for aspect ratios of 0.1 and 0.3 as the Reynolds number rises. The Nusselt number enhances by 420 % and 466 % at a 20 % nanoparticle volume fraction for aspect ratios of 0.1 and 0.3, respectively, with a 9 % improvement in photovoltaic cell efficiency. This work uniquely applies machine learning to derive regression equations for fluid force, Nusselt number, and electrical efficiency, an approach not previously explored in laminar flow studies.

Manufacturing lithium-ion anodes from silicon recovered from end-of-life solar panels

With the rapid growth of solar energy, the recycling or re-use of used solar panels has become a key issue. Recycling high-value photovoltaic silicon from solar cells is an important step towards achieving “carbon neutrality.” In this paper, an efficient and high-value recycling strategy is employed to convert recycled silicon from discarded solar cells into lithium-ion anode materials. In this case, the recycled PV silicon is etched with hydrofluoric acid (HF) to create a porous silicon structure. This structure is designed to withstand the expansion stress of the electrodes. After surface modification with citric acid and carbon nanotubes to enhance the electrical conductivity of the recycled silicon and buffer the electrode from stress expansion during lithium storage and release, lithium difluorooxalate borate was added to pre-treat the surface of the recycled photovoltaic silicon through heat treatment. This process creates a robust and fast lithium-ion conductive interface enriched with LiF, Li2C2O4, LiBO2, and Li2B4O7. Density Functional Theory (DFT) calculations were performed to investigate the electronic structure of the synthesized materials, revealing their remarkable electronic conductivity and atomic bonding characteristics. When used as an anode for Li-ion batteries, W-pSi@C/CNTs exhibited high initial coulombic efficiency with stable cycling, demonstrating a capacity of 2040 mAh/g at 0.2 A/g for 200 cycles. In addition, this high-value recycling will help promote the development of renewable energy in an economically and environmentally sustainable manner.