Short-circuit Research Articles

ДЕЯКІ АСПЕКТИ РОЗРАХУНКУ СТРУМІВ КОРОТКОГО ЗАМКНЕННЯ В ДІЛЬНИЧНИХ ПІДЗЕМНИХ МЕРЕЖАХ

The article considers some aspects of calculating short-circuit currents in mine networks of an underground sec-tion; the shortcomings of traditional methods of calculating short-circuit currents are identified. The article shows that for an accurate calculation, it is necessary to know the actual voltage levels at remote points of the underground section. The influence of the complex resistance of the external power supply network and the ac-tual phase parameter was studied. The article states that the voltage is below the nominal value in the electrically remote connection nodes of the substation's mobile transformers to the underground distribution network and usually no regulating taps are used. The article indicates that according to known methods of calculating short-circuit currents, the voltage on the secondary terminals of the substation transformer is assumed to be equal to the nominal voltage of the network, but in remote areas it is significantly lower and, accordingly, the actual short-circuit currents are 10-12% lower than the calculated ones. It was also investigated that with an increase in the share of the active short-circuit power component, short-circuit currents in district networks increase by 4-5%.

Starch Cross-Linked Glass Fibers for Water Evaporation-Induced Electricity Generation.

Water evaporation-induced electricity devices (WEDs) have become extremely attractive, converting ambient heat into electricity while being environmentally friendly. However, most current WEDs are costly and cumbersome to fabricate, which greatly limits their commercialization process. Here, we present WEDs based on starch cross-linked with glass fiber filter paper (Starch-GF). A single device produced an open-circuit voltage of 0.3 V, a short-circuit current of 1.2 μA, and a maximum power density of 1.8 mW/m2 in a natural environment under 24 h of continuous measurements. Starch-GF devices can drive electronics after charging capacitors and have environmentally friendly properties. This research contributes significantly to the discovery of hydrovoltaic materials and their practical implementation in hydrovoltaic devices.

Evaluation of imidazole blocking layers for perovskite stability

The prevention of AgI formation is critical for ensuring long term stability of perovskite solar cells. While sputtered metal oxide films are known for uniform dense film formation, solution phase nanoparticle coatings of metal oxides are prone to pinholes through which free iodide can migrate leading to AgI formation at the back contact. Iodide migration can be prevented through the addition of passivator or blocking layers at the perovskite/charge transport or charge transport/Ag interfaces. In this paper we evaluated a series of imidazoles as interfacial layers to prevent iodide migration from the perovskite to the Ag back contact through solution phase deposited Y:SnO2. We identified structural features of the imidazoles that contribute to an effective blocking layer. Specifically, it was found that imidazoles with conjugated planer systems and hydrogen bonding heteroatoms were able to prevent ion migration while retaining device performance. Of the materials evaluated 4-(Imidazol-1-yl)phenol had the best performance with a 60 % increase in stability verse the control under illumination at short circuit conditions.

Study on the thermal runaway behavior and mechanism of 18650 lithium-ion battery induced by external short circuit

This study investigated the external short circuit (ESC) characteristics of 18650-type NCM lithium-ion batteries under different states of charge (SOC) and short-circuit currents. The research includes the macroscopic electro-thermal characteristics, microscopic morphology, structural damage, and internal damage evolution mechanism of short-circuited batteries. The tests provided an in-depth study of external short circuit (ESC) failure and thermal runaway (TR) behavioral characteristics. The results indicate that all the temperature changes of the short-circuit batteries were found to be in an upward and then downward trend. The surface temperature rise rate of batteries with low SOC were faster, and the maximum surface temperature rise of batteries with high SOC were higher. And with the increase of short-circuit current rate, the temperature rise gradually increased. In particular, thermal runaway occurred at 25C and the maximum temperature exceeds 500 °C. Different SOC batteries showed different degree of voltage fluctuation. The voltage curve of low SOC batteries showed “falling-rising-falling” trend with a brief platform. High SOC batteries formed a distinct voltage platform near 2.75 V. As the short-circuit current increased, the voltage platform shortened, followed by the rapid drop to zero. X-ray CT and SEM test results showed that the deformation of the battery jelly roll was mainly due to the separator shrinkage and tearing. Major changes occurred in the cathode and separator, including secondary particle rupture and irreversible pore blockage in the separator. The damage mechanism of ESC and its evolution are revealed. The results of this study can provide support for the research work on the thermal safety design of lithium batteries.

Harvesting low-grade wind energy from highways using a triboelectric nanogenerator

In an era of growing global energy demands, the exploration of niche energy harvesting methods is becoming increasingly important, and harnessing wind energy from highways presents a promising approach to sustainable infrastructure development given the high traffic of many roads. In this work, we report a cylindrical spinning TENG (CS-TENG) for low-grade wind energy harvesting from highways. Through empirical analysis and theoretical modeling, we investigate the feasibility of integrating CS-TENG devices along highway barriers to capture the wind energy generated by passing vehicles, which could contribute to powering streetlights and other road infrastructure in a more eco-friendly way. Our findings highlight broader societal and environmental benefits including enhancing road safety, traffic management, and energy sustainability. A single 100 mm tall CS-TENG device was tested with approximately 4 m/s wind speed and produced an open circuit voltage of 8 V and a short circuit current of 800 µA. This electrical output can be increased with an elevation in the device number, the device size, and improved material properties. This study contributes to the growing discourse on sustainable infrastructure solutions, inspiring further research and innovation in renewable energy harvesting for carbon neutrality.

Numerical investigation of graphene derivatives as HTL in PBDB-T:NCBDT bulk heterojunction organic solar cell

The damaging effects of the most widely used PEDOT:PSS have led researchers to search for an alternative hole transport layer (HTL) in non-fullerene acceptor (NFA) based bulk heterojunction organic solar cells (BHJOSC’s). This work highlights the numerical simulation study of possible new approach of utilizing graphene, graphene oxide (GO), reduced graphene oxide (rGO), and p type doped graphene (p-graphene), as an alternative to PEDOT:PSS in non-fullerene acceptor based bulk heterojunction organic solar cell (NFABHJOSC) with PBDB-T as donor and NCBDT as acceptor using SCAPS1D. NCBDT is an emerging small-molecule non-fullerene acceptor (SM-NFA) whose bandgap can be tuned and reduced, making it a better option as an acceptor. Validation of the software is done by matching simulation results with experimental results. Diverse electron transport layers (ETL’s), including PDINO, ZnO, IGZO, TiO2, TiO2:gr (20%) composite, and TiO2:gr (10%) composite, are introduced, and device performance of various configurations is analysed. Optimization of the best device configuration ITO (4.8 eV)/rGO/PBDB-T:NCBDT/PDINO/Al gave an improved efficiency of 17.47%, fill factor (FF) of 77.45%, short circuit current density (Jsc) of 25.407 mA/cm2, and an open circuit voltage (Voc) of 0.8878 V.

Controlling Biomedical Devices Using Pneumatic Logic.

Many biomedical devices are powered and controlled by electrical components. These electronics add to the cost of a device (possibly making the device too expensive for use in resource-limited or point-of-care settings) and can also render the device unsuitable for use in some environments (for example, high-humidity areas such as incubators where condensation could cause electrical short circuits, ovens where electronic components may overheat, or explosive or flammable environments where electric sparks could cause serious accidents). In this work, we show that pneumatic logic can be used to power and control biomedical devices without the need for electricity or electric components. Originally developed for controlling microfluidic "lab-on-a-chip" devices, these circuits use microfluidic valves like transistors in air-powered logic "circuits." We show that a modification to the basic valve design-adding additional air channels in parallel through the valve-creates a "high-flow" valve that is suitable for controlling a broad range of bioinstruments, not just microfluidics. As a proof-of-concept, we developed a high-flow pneumatic oscillator that uses five high-flow Boolean NOT gates arranged in a loop. Powered by a single constant vacuum source, the oscillator provides five out-of-phase pneumatic outputs that switch between vacuum and atmospheric pressure every 1.3s. Additionally, a user can adjust the frequency of the oscillator by squeezing a bellows attached to one of the pneumatic outputs. We then used the pneumatic oscillator to power a low-cost 3D-printed laboratory rocker/shaker commonly used to keep blood products, cell cultures, and other heterogeneous samples in suspension. Our air-powered rocker costs around $12 USD to build and performs as well as conventional electronic rockers that cost $1000 USD or more. This is the first of many biomedical devices that can be made cheaper and safer using pneumatic logic.

Real-Time Detection of Internal Short Circuits in Lithium-Ion Batteries using an Extend Kalman Filter

Concerns over fuel scarcity and environmental degradation largely drive the increasing popularity of electric vehicles (EVs). Lithium-ion batteries (LIBs), known for their high energy and power densities, are the favored power source for EVs. Over the past few decades, research has been concentrated on ensuring these batteries operate efficiently, safely, and reliably. A key issue impacting the safety of Li-ion batteries is thermal runaway (TR), which can lead to hazardous battery fires. Internal short circuits (ISCs) are often the primary cause of these TR incidents, making the early detection of spontaneous ISC formation a pivotal diagnostic task. This research introduces an innovative ISC detection technique for cylindrical Li-ion battery cells. This technique is based on the augmentation of the model state vector in an extended Kalman filter (EKF), combining both classical voltage measurements to surface temperature observations. This framework enables real-time estimation of the internal ISC state while maintaining computational efficiency. The proposed method is tested numerically considering a high-fidelity numerical plant cycled using charge-depleting tests that mimic a practical battery cell working cycle at various C rates and at different ambient temperatures to account for both load and environmental uncertainties. The results demonstrate the robustness and effectiveness of the method. In addition, the method has been proven to be computationally efficient, demonstrating the feasibility of its real-time implementation.

Simulation of Dendrite Growth with a Diffusion-Limited Aggregation Model Validated by MRI of a Lithium Symmetric Cell during Charging

Lithium metal batteries offer high energy density but are challenged by dendrite growth, which can lead to short circuits and battery failure. Multiple models with varying degrees of accuracy and computational cost have been developed to understand and predict dendrite growth. This study presents a simple model to simulate macroscale dendrite growth on lithium metal electrodes. The model uses a 3D single-particle Diffusion-Limited Aggregation (DLA) algorithm with an electric field bias to simulate dendrite growth. The electric field bias was introduced into the model with an important parameter, namely the biasing factor c, which determines the balance between diffusion and electric field effects. Before performing the simulation with the proposed model, the dendrite growth in a lithium symmetric cell during charging was measured by sequential 3D magnetic resonance imaging (MRI). These data were then used to validate the simulation, as the dendrite structure in each measured MRI time frame was used a starting point for a new simulation, the results of which were then validated with the measured dendrite structure of the next time frame. The best agreement between the simulated and measured dendrite structures using the overlap and displacement of deposition sites metrics was obtained at the biasing factor c = 0.7. This agreement was also good in terms with the fractal dimension of the dendrite structures. The proposed method offers a simple, accurate, and scalable framework for predicting dendrite growth over long deposition periods, making it a valuable tool for studying dendrite suppression under real-world battery charging conditions.

Non-fused nonfullerene acceptors withasymmetric benzo[1,2-b:3,4-b', 6,5-b"]trithiophene (BTT) central donor core and different acceptor terminal units for organic solar cells.

Here in, we have designed two new unfused non-fullerene small molecules based on asymmetric benzo[1,2-b:3.4-b', 6,5-b"]trithiophene (BTT) central donor core and different terminal units, i.e. 2-(3-oxo-2,3-dihydro-1H-inden-1-ylidene)malononitrile (NFA-4) and 1,3-diethyl-2-thioxodi hydropyrimidine-4,6(1H,5H)-dione (NFA-5) and their optical and electrochemical properties were investigated. Employing a wide band-gap copolymer D18, the binary D18: NFA-4 and D18:NFA-5 bulk heterojunction-based organic solar cells realized an overall power conversion efficiency of about 17.07% and 11.27 %, respectively. The higher value of power conversion efficiency for the NFA-4-based organic solar cells, as compared to the NFA-5 counterpart, is attributed to the enhanced values of short circuit current, open circuit voltage, and fill factor. After the incorporation of NFA-5 into the binary bulk heterojunction D18:NFA-4, the ternary organic solar cells attained a power conversion efficiency of 18.05 %, which is higher than that for the binary counterparts and attributed to the increased values of short circuit current, fill factor, and open circuit voltage. The increased value of short circuit current is associated with the effective utilization of excitons through the energy transfer from the NFA-5 to NFA-4 as the NFA-4 exhibits a more significant dipole moment than the NFA-5 and is effectively dissociated into a free charge carrier.

Technological Features of Filler Wire Melting for Arc Welding and Surfacing with the Introduction of SF6 into Protective Gas Atmosphere

On the basis of the results of experimental studies the paper establishes important patterns of dependence of the frequency of short circuits of the arc gap and the coefficient of loss of electrode metal due to spatter from the voltage on the arc and the feed rate of the filler wire during welding and surfacing with the introduction of gaseous SF6 into the Ar + CO2 protective mixture. It is proposed to introduce fluorine-containing components of SF6 directly into the protective gas mixture of 82 % Ar + 18 % CO2 in quantities not exceeding 2 %. The technology makes it possible to reduce the amount of diffusion hydrogen in the deposited metal, which is an urgent task when welding high-strength steels and materials sensitive to hydrogen embrittlement. Previously, we resolved a number of issues related to the obstacle to increasing the concentration of S in the deposited metal, which made it possible to determine the most effective concentrations of SF6 in the protective gas environment, limited to 1.5 % by volume of the total composition (Ar + CO2) + SF6. At the same time, modification of the protective gas atmosphere with the halide compound SF6 has a significant effect on the melting characteristics of the electrode wire and temperature indicators in the arc combustion zone. This is due to the high ionization potential of fluorine as a product of the high-temperature dissociation reaction of SF6. The results obtained have made it possible to determine the most effective relationships between the values of the mode parameters, as well as to study the specifics of melting the filler wire in a protective atmosphere modified with SF6. Important regularities have been established that reveal the technological features of welding and surfacing with modification of the protective atmosphere with halide compounds.

Fabricating complex parts through optimizing weld bead geometry in WAAM: A comparative study of surface tension transfer and cold metal transfer

Wire arc additive manufacturing (WAAM) technology is being employed in industries such as aerospace, maritime and automotive to produce high-valued metallic parts. With a growing demand for products with complex structures, it is crucial to develop an effective and reliable method for fabricating such parts to meet the demand. Currently, cold metal transfer (CMT), is one of the waveform-controlled short circuit transfer processes, commonly adopted in the WAAM process to fabricate medium to large-scale parts due to its perceived low heat input. However, the approach of using synergic control of wire feed speed and torch travel speed to control weld bead geometry in CMT may not be applicable for fabricating parts with complex structures. In these circumstances, surface tension transfer (STT), a waveform controlled short circuit transfer process, or one of the alternative variants of controlled short circuit transfer with low heat input, may provide more options to control weld bead geometry. There appear to have been few systematic investigations of alternative controlled short circuiting variants for use in WAAM. This paper provides a comparative study to explore the potential of the STT process for fabricating parts with complex geometries in WAAM. Firstly, the working principles of the STT and CMT processes are reviewed. Then, the impacts of welding parameters in the STT and CMT on weld bead geometry are analysed based on experiment results. Finally, a comparison between these two welding processes with regard to flexibility in welding parameter adjustment, heat input and overlapping performance is conducted. Finally, a comparison between these two welding processes is conducted from three critical aspects: (i) Flexibility in parameter adjustment: STT has 333 % and 174 % larger average width and height variation ranges than CMT; (ii) Heat input: STT's heat input is 74.66 % higher than CMT's at TS = 300 mm/min; (iii) Overlapping performance: the average surface roughness of the tested CMT and STT groups is 0.1312 and 0.1823, respectively. Suggestions for using STT and CMT to fabricate parts with complex geometries are provided accordingly.

Effect of SF6 circuit breaker parameters on switching overvoltages evaluated based on nominal modes of converter transformers

In this work, we set out to investigate the influence of operating currents of SF6 circuit breakers on the magnitude of overvoltages during switching of converter transformers. The experience of electrical equipment operation is analyzed with a focus on the problems associated with the natural aging of insulation, overloads, and switching overvoltages. The methods of equipment diagnostics were used. According to statistical data, at present, about 37% of short circuits between phases and 42% of single-phase earth faults in electrical networks of industrial enterprises occur due to switching overvoltages. The conducted tests showed that the overvoltages emerging during switching by SF6 circuit breakers of converter transformers, which are used in aluminum smelters, may reach a three-fold rated voltage of the network. This threatens the insulation of transformer windings, cable line, and the switch itself. It was established that an increase in operating currents of an LF2 circuit breaker, not exceeding 27.8% of the rated current of the switch, leads to an increase in overvoltages during switching of converter transformers. At a further increase in the operating currents of the circuit breaker by more than 27.8% of the rated current of the circuit breaker, a sharp decrease in the value of switching overvoltages is observed. Therefore, the operating currents of SF6 circuit breakers were established to affect the level of switching overvoltages of converter transformers. The underlying mechanism of this phenomenon was determined, which should be taken into account when improving the reliability of power supply of converter transformers and, consequently, the reliability of aluminum production. The feasibly of resistive-capacitive dampers as the most effective means for limiting overvoltages during switching of converter transformers was confirmed.

Experimental investigation of a nano coating efficiency for dust mitigation on photovoltaic panels in harsh climatic conditions

Dust accumulation on photovoltaic (PV) panels in arid regions diminishes solar energy absorption and panel efficiency. In this study, the effectiveness of a self-cleaning nano-coating thin film is evaluated in reducing dust accumulation and improving PV Panel efficiency. Surface morphology and elemental analysis of the nano-coating and dust are conducted. Continuous measurements of solar irradiances and ambient temperature have been recorded. SEM analysis of dust revealed irregularly shaped micron-sized particles with potential adhesive properties, causing shading effects on the PV panel surface. Conversely, the coating particles exhibited a uniform, spherical shape, suggesting effective prevention of dust adhesion. Solar irradiance ranged from 120 W/m² to a peak of 720 W/m² at noon. Application of the self-cleaning nano-coating thin film consistently increased short circuit current (Isc), with the coated panel averaging 2.8 A, which is 64.7% higher than the uncoated panel’s 1.7 A. The power output of the coated panel ranged from 7 W to 38 W, with an average of approximately 24.75 W, whereas the uncoated panel exhibited a power output between 3 W and 23 W, averaging around 14 W. These findings highlight the substantial potential of nano-coating for effective dust mitigation, particularly in dusty environments, thus enhancing PV system reliability.

Extending Dynamic Blind Interaction: Microgap Discharge-Induced Flexible Virtual Electrotactile Braille.

Braille is an essential implement for the blind to communicate with outside, but traditional Braille is limited to a paper-based format that cannot directly provide real-time word information. In this work, a flexible virtual electrotactile Braille is proposed that can benefit the blind from blocked interaction. The Braille interface, S-shaped wires and a sphere electrode with a textile fingerstall integrated by silicone, offers flexibility and simultaneously generates the microgap through textile cracks, which achieves virtual electrotactile sensation by electrostatic discharge. Powered by a high-voltage triboelectric generator of 10.2 kV designed through the charge accumulation and induction strategy, the electrotactile stimulation is realized with a microgap discharge of only 40 μA current induced on the finger. A dynamic electrotactile Braille is finally assembled, controlled by a programmable relay array. The strategies of short circuit and voice reminder are employed, so that the recognition of dynamic Braille letters is realized with spatiotemporal electrotactile stimulation and high recognition accuracy. This virtual electrotactile Braille brings convenience for the blind to access the information world and illustrates its applications to promote virtual electrotactility in this special community.

Enhance the Performance of CZTSSe Solar Cells Through Inhibiting the Cu2+, Tu, and (─COOH) Association Reaction.

The Sol-gel precursor solution reaction mechanism has a significant impact on the Cu2ZnSn(S, Se)4 (CZTSSe) solar cells. It is discovered that in the Cu2ZnSnS4 (CZTS) precursor solution (CZTS-PS) in the preparation, there is an association reaction among Cu2+, thiourea (Tu), and carboxyl (-COOH), which is an important reason for the undesirable CZTSSe solar cells. The strong association reaction generates excessive Cu2+ ions, forming the CuxSe secondary phase on the surface of the CZTSSe absorber. The secondary phase causes a short circuit and deterioration of gadget performance. Following a 6-h aging period for the CZTS-PS, the average photoelectric conversion efficiency (PCE) of the device is enhanced to 8.02%, and there is also an improvement in device uniformity, as evidenced by a decrease in the standard deviation to less than 1. To inhibit the association reaction and eliminate the aging time phenomenon, a strategy is developed using hydrochloric acid to regulate the CZTS-PS environment. This strategy shifts the REDOX reaction in Cu2++Sn2+ toward the formation of Cu1++Sn4+, leading to a decrease in the defect concentrations of VSn(-/0) and CuSn(-/0), which increases the carrier concentration and reduces the impact of band tailing. The average power conversion efficiency (PCE) of the devices improved from 7.45% to 9.26%, the PCE of the best-performing CZTSSe solar cells increased from 9.25% to 9.83%, and the consistency among the devices is further enhanced, as indicated by a reduction in the standard deviation from 0.98 to 0.44. Ultimately, the device performance of the Cu2++Sn2+-DMF system improved by 11.01% (without the MgF2 layer) after optimization. This study serves as a reference for regulating the environment of the CZTS-PS to further enhance the CZTSSe devices' performance, and the photoelectric conversion efficiency is improved by ≈30%.

Short-Circuit Detection in Lithium-Ion Batteries Using Machine Learning: Analysis and Comparison with Physics-Based Method

Early detection of short circuits in battery-powered systems is critical in preventing potential catastrophic failures. However, nascent short-circuit signatures are extremely weak and challenging to detect using existing algorithms without compromising on prediction accuracy. Traditional physics-based approaches rely on hand-crafted models to establish relationships between battery operating parameters and short resistance, which limits their ability to capture all relevant details, resulting in sub-optimal accuracies. In this study, we present a machine learning-based approach that leverages rest period voltage data to detect short circuits. Our method employs a 1D convolutional neural network (CNN) classifier/estimator that extracts temporal dynamic features relevant to the short circuit prediction problem from both the long and short tails of the rest period voltage profile. The approach is validated using commercial battery data, generated at different conditions including temperatures, and short circuits of varying severities; with prediction accuracies greater than 90% even for soft shorts of 500Ω. The key performance parameters of the 1D CNN model are compared against a physics-based short detection approach, demonstrating its superior performance and cost-effectiveness. Overall, our work represents a significant advancement in the field of short circuit detection in battery-powered systems, offering improved accuracy, efficiency, and cost-effectiveness.

Design of an FPGA-based short-circuit fault diagnosis algorithm for DC current-limiting fuses

Abstract In recent years, DC current-limiting fuses have played a crucial role in the comprehensive power systems of ships, rail transport, and new energy sectors, ensuring the safe and reliable operation of DC power systems. However, with the increase in the capacity of DC power systems, short-circuit faults can lead to a rise in short-circuit current at rates of up to 40 A/μs, with peak short-circuit currents reaching up to 105KA. This poses higher demands on the accuracy and speed of fuse diagnostics to interrupt short-circuit currents. To address this issue, this paper introduces a fault diagnostic algorithm based on FPGA that can calculate the rise rate of short-circuit currents in real-time: employing FPGA with its high integration, abundant logic resources, and parallel data processing capabilities as the core of the measurement and control system to enhance the speed of short-circuit fault diagnosis from a hardware perspective; replacing the common large current trip protection and DDL protection algorithms with the Newton interpolation algorithm. This improvement calculates the rise rate of each current data point instead of the average rise rate over a period, thus enhancing the speed and accuracy of short-circuit fault diagnosis from a software perspective. The paper also discusses the design of the system’s hardware and software and the construction of the experimental platform. Simulation and experimental results show that the fault diagnosis time of the algorithm has been reduced from 98μs to 36μs, with the numerical error in the short-circuit current rise rate within 2%, and a significant reduction in the peak value of short-circuit current, meeting performance requirements and effectively ensuring the safe and reliable operation of DC power systems.

Machine learning-assisted SCAPS device simulation for photovoltaic parameters prediction of [formula omitted] perovskite solar cells

Perovskite solar cells (PSCs) have garnered significant research attention because of their remarkable surge in power conversion efficiency (PCE) surpassing 26% within a short timeframe. However, the widespread adoption of these highly efficient PSCs is hampered by the inherent toxicity associated with lead (Pb)-based perovskites, which currently dominate the field. Researchers have explored alternative cations like Ge2+ and Sn2+ Owing to their identical oxidation states to Pb2+, paving the way for lead-free PSC development. By examining the critical factors influencing CsSnI3 thin film solar cells’ performance as well as their interdependencies, this work seeks to improve the efficiency of these devices. To do so, machine learning algorithms (ML) are employed to figure out the critical factors influencing the completion of CsSnI3 solar cells. A new dataset of 7870 data points is generated through simulations with SCAPS-1D to effectively depict the perovskite solar cell. Five ML regression algorithms are thereafter utilized to predict the photovoltaic parameters of solar cells, such as the fill factor (FF), open circuit voltage (VOC), short circuit current (JSC), and PCE. The study shows that random forest (RF) and decision tree (DT) are the best performing algorithms, among which DT produces high accuracy and low error for predicting the PCE with a coefficient of determination R2 of 0.99, Pearson’s coefficient (Rvalue) of 0.99, Spearman’s correlation coefficient (ρ) of 0.99 and root mean square error of 0.08 on the testing set. Finally, this study offers valuable guidance for further experiment optimization by shedding light on the optimal device dimensions and essential components.

Spin effect in the ferromagnetic organic photovoltaics cells

In organic photovoltaic devices, the separation and transport of photogenerated charges play crucial roles for power conversion efficiency. Magnetic doping in organic solar cells can effectively enhance the power conversion efficiency by introducing a static magnetic field. In this study, we observed that in pure organic magnetic solar cells, the spin-polarization-induced spin scattering effect can also efficiently modulate the photocurrent in solar cells. Compared to the demagnetized state, the short-circuit current of PTB7:nw-P3HT:PCBM solar cells increased by approximately 0.3% after magnetization. The dielectric constant only increased by about 0.05%. However, above the Curie temperature 310 K, the long-range spin order in PTB7:nw-P3HT:PCBM solar cells disappears, resulting in consistent circuit currents before and after magnetization. Therefore, magnetic doping can enhance the short-circuit current in organic solar cells by weakening the spin scattering effect and enhancing the charge carrier mobility.