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Abstract Ion doping is an effective strategy for achieving high‐performance flexible Cu2ZnSn(S,Se)4 (CZTSSe) solar cells by defect regulations. Here, a Li&Na co‐doped strategy is applied to synergistically regulate defects in CZTSSe bulks. The quality absorbers with the uniformly distributed Li and Na elements are obtained using the solution method, where the acetates (LiAc and NaAc) are as additives. The concentration of the harmful CuZn anti‐site defects is decreased by 8.13% after Li incorporation, and that of the benign NaZn defects is increased by 36.91% after Na incorporation. Synergistic Li&Na co‐doping enhances the carrier concentration and reduces the interfacial defects concentration by one order of magnitude. As a result, the flexible CZTSSe solar cell achieves a power conversion efficiency (PCE) of 10.53% with certified 10.12%. Because of the high PCE and the homogeneous property, the Li&Na co‐doped device is fabricated to a large area (2.38 cm2) and obtains 9.41% PCE. The co‐doping investigation to synergistically regulate defects provides a new perspective for efficient flexible CZTSSe solar cells.

Indoor lighting is weak and multi-directional, thus the requirement for photovoltaic differs from that designed for outdoor. To efficiently harvest the indoor energy, the authors designed CZTSSe bifacial solar cells on flexible Mo substrate using double-sided deposition to ensure consistency and to save cost.

Flexible CZTSSe solar cells have attracted much attention due to their earth-abundant elements, high stability, and wide application prospects. However, the environmental problems caused by the high toxicity of the Cd in the buffer layers restrict the development of flexible CZTSSe solar cells. Herein, we develop a Cd-free flexible CZTSSe/ZnO solar cell. The influences of the ZnO films on device performances are investigated. The light absorption capacity of flexible CZTSSe solar cells is enhanced due to the removal of the CdS layer. The optimal thickness of the ZnO buffer layers and the appropriate annealing temperature of the CZTSSe/ZnO are 100 nm and 200 °C. Ultimately, the optimum flexible CZTSSe/ZnO device achieves an efficiency of 5.0%, which is the highest efficiency for flexible CZTSSe/ZnO solar cells. The systematic characterizations indicate that the flexible CZTSSe/ZnO solar cells based on the optimal conditions achieved quality heterojunction, low defect density and better charge transfer capability. This work provides a new strategy for the development of the environmentally friendly and low-cost flexible CZTSSe solar cells.

The nonlinear output characteristics of PV arrays and maximum power point tracking (MPPT) techniques bring more difficulties to fault diagnosis. The fault diagnosis model based on electrical transient time-domain analysis is an effective method for solving the above problems. However, existing studies using transient processes usually train their models by extensive labeled datasets, and some approaches apply normalization methods with environmental condition sensors or reference PV panels. Therefore, Fisher discrimination dictionary learning (FDDL) for sparse representation is explored for diagnosing PV array faults, including line-to-line faults (LLF), open-circuit faults (OCF), and partial shading faults (PSF), with a small labeled dataset, and a dynamic normalization method without additional sensors is proposed to process transient data. Moreover, LLF and PSF that have similar characteristics under low mismatch should be further distinguished. The proposed model is designed with two stages. In the first stage, a multiple classifier trained using small labeled datasets with all fault types is applied to diagnose all kinds of studied PV array faults. Then, a dictionary only for PSF and LLF is learned in the second stage to further identify LLF and PSF. Finally, a 1.8 kW rooftop grid-connected PV system with $6\times3$ PV arrays is applied to validate the performance of the proposed model. The comparison result shows the superiority of the proposed model.

Abstract Lithium (Li) has garnered considerable attention as an alternative anodes of next‐generation high‐performance batteries owing to its prominent theoretical specific capacity. However, the commercialization of Li metal anodes (LMAs) is significantly compromised by non‐uniform Li deposition and inferior electrolyte–anode interfaces, particularly at high currents and capacities. Herein, a hierarchical three‐dimentional structure with CoSe2‐nanoparticle‐anchored nitrogen‐doped carbon nanoflake arrays is developed on a carbon fiber cloth (CoSe2–NC@CFC) to regulate the Li nucleation/plating process and stabilize the electrolyte–anode interface. Owing to the enhanced lithiophilicity endowed by CoSe2–NC, in situ‐formed Li2Se and Co nanoparticles during initial Li nucleation, and large void space, CoSe2–NC@CFC can induce homogeneous Li nucleation/plating, optimize the solid electrolyte interface, and mitigate volume change. Consequently, the CoSe2–NC@CFC can accommodate Li with a high areal capacity of up to 40 mAh cm–2. Moreover, the Li/CoSe2–NC@CFC anodes possess outstanding cycling stability and lifespan in symmetric cells, particularly under ultrahigh currents and capacities (1600 h at 10 mA cm−2/10 mAh cm−2 and 5 mA cm−2/20 mAh cm−2). The Li/CoSe2–NC@CFC//LiFePO4 full cell delivers impressive long‐term performance and favorable flexibility. The developed CoSe2–NC@CFC provides insights into the development of advanced Li hosts for flexible and stable LMAs.

Binarization can greatly compress and accelerate deep convolutional neural networks (CNNs) for real-time industrial applications. However, existing binarized CNNs (BCNNs) rely on scaling factor (SF) and batch normalization (BatchNorm) that still involve resource-consuming floating-point multiplication operations. Addressing the limitation, an improved BCNN named BitFlow-Net is proposed, which replaces floating-point operations with integer addition in middle layers. First, it is derived that the SF is only effective in back-propagation process, whereas it is counteracted by BatchNorm in inference process. Then, in model running phase, the SF and BatchNorm are fused into an integer addition, named BatchShift. Consequently, the data flow in middle layers is fully binarized during modeling running phase. To verify its potential in industrial applications with multiclass and binary classification tasks, the BitFlow-Net is built based on AlexNet and verified on two large image datasets, i.e., ImageNet and 11K Hands. Experimental results show that the BitFlow-Net can remove all floating-point operations in middle layers of BCNNs and greatly reduce the memory for both cases without affecting the accuracy. Particularly, the BitFlow-Net can achieve the accuracy comparable to that of the full-precision AlexNet network in the binary classification task.

Self-supported electrodes represent a novel architecture for better performing lithium ion batteries. However, lower areal capacity restricts their commercial application. Here, we explore a facial strategy to increase the areal capacity without sacrificing the lithium storage performance. A hierarchical CuO–Ge hybrid film electrode will not only provide high areal capacity but also outstanding lithium storage performance for lithium ion battery anode. Benefiting from the favorable structural advance as well as the synergic effect of the Ge film and CuO NWs array, the hybrid electrode exhibits a high areal capacity up to 3.81 mA h cm−2, good cycling stability (a capacity retention of 90.5% after 150 cycles), and superior rate performance (77.4% capacity remains even when the current density increased to 10 times higher).

Abstract The inverse spin Hall effect induced by circularly polarized light has been observed in a GaAs/AlGaAs two-dimensional electron gas. The spin transverse force has been determined by fitting the photo-induced inverse spin Hall effect (PISHE) current to a theoretical model. The PISHE current is also measured at different light power and different light spot profiles, and all the measurement results are in good agreement with the theoretical calculations. We also measure the PISHE current at different temperatures (i.e., from 77 to 300 K). The temperature dependence of the PISHE current indicates that the extrinsic mechanism plays a dominant role, which is further confirmed by the weak dependence of the PISHE current on the crystal orientation of the sample.

Fault diagnosis of photovoltaic (PV) arrays plays a significant role in safe and reliable operation of PV systems. In this paper, the distribution of the PV systems’ daily operating data under different operating conditions is analyzed. The results show that the data distribution features significant nonspherical clustering, the cluster center has a relatively large distance from any points with a higher local density, and the cluster number cannot be predetermined. Based on these features, a density peak-based clustering approach is then proposed to automatically cluster the PV data. And then, a set of labeled data with various conditions are employed to compute the minimum distance vector between each cluster and the reference data. According to the distance vector, the clusters can be identified and categorized into various conditions and/or faults. Simulation results demonstrate the feasibility of the proposed method in the diagnosis of certain faults occurring in a PV array. Moreover, a 1.8 kW grid-connected PV system with 6×3 PV array is established and experimentally tested to investigate the performance of the developed method.

To quickly and precisely extract the parameters for solar cell models, inspired by simplified bird mating optimizer (SBMO), a new optimization technology referred to as population classification evolution (PCE) is proposed. PCE divides the population into two groups, elite and ordinary, to reach a better compromise between exploitation and exploration. For the evolution of elite individuals, we adopt the idea of parthenogenesis in nature to afford a fast exploitation. For the evolution of ordinary individuals, we adopt an effective differential evolution strategy and a random movement of small probability is added to strengthen the ability to jump out of a local optimum, which affords a fast exploration. The proposed PCE is first estimated on 13 classic benchmark functions. The experimental results demonstrate that PCE yields the best results on 11 functions by comparing it with six evolutional algorithms. Then, PCE is applied to extract the parameters for solar cell models, that is, the single diode and the double diode. The experimental analyses demonstrate that the proposed PCE is superior when comparing it with other optimization algorithms for parameter identification. Moreover, PCE is tested using three different sources of data with good accuracy.

Ag-doped In2S3 (In2S3:Ag) thin films have been deposited onto glass substrates by a thermal evaporation method. Ag concentration is varied from 0 at.% to 4.78 at.%. The structural, optical, and electrical properties are characterized using X-ray diffraction (XRD), spectrophotometer, and Hall measurement system, respectively. The XRD analysis confirms the existence of In2S3 and AgIn5S8 phases. With the increase of the Ag concentration, the band gap of the films is decreased gradually from 2.82 eV to 2.69 eV and the resistivity drastically is decreased from ~103 to 5.478×10-2 Ω·cm.

Cu2SnS3 is a narrow-band-gap semiconductor material. It has suitable optical and electrical properties which make it a potential absorber layer of solar cells. In this paper, Cu2SnS3 thin films were successfully obtained by sulfurizing CuSnS2 thin films deposited by RF magnetron sputtering at temperatures of 350–425°C for 2 h in an atmosphere of hydrogen sulfide and nitrogen. The influence of the sulfurization temperature on the electrical and optical properties of the Cu2SnS3 thin films was investigated. The experimental results show that the Cu2SnS3 thin films sulfurized at a temperature of 425°C exhibit better properties than others. The mobility and resistivity of the Cu2SnS3 films are 9 cm2/V·s and 3 Ω·cm, respectively. And its optical band gap is estimated to be about 1.77 eV.

Copper zinc tin sulfur (CZTS) thin films have been extensively studied in recent years for their advantages of low cost, high absorption coefficient (≥104 cm−1), appropriate band gap (~1.5 eV), and nontoxicity. CZTS thin films are promising materials of solar cells like copper indium gallium selenide (CIGS). In this work, CZTS thin films were prepared on glass substrates by vacuum evaporation and sulfurization method. Sn/Cu/ZnS (CZT) precursors were deposited by thermal evaporation and then sulfurized in N2 + H2S atmosphere at temperatures of 360–560°C to produce polycrystalline CZTS thin films. It is found that there are some impurity phases in the thin films with the sulfurization temperature less than 500°C, and the crystallite size of CZTS is quite small. With the further increase of the sulfurization temperature, the obtained thin films exhibit preferred (112) orientation with larger crystallite size and higher density. When the sulfurization temperature is 500°C, the band gap energy, resistivity, carrier concentration, and mobility of the CZTS thin films are 1.49 eV, 9.37 Ω · cm, 1.714×1017 cm−3, and 3.89 cm2/(V · s), respectively. Therefore, the prepared CZTS thin films are suitable for absorbers of solar cells.

ZnO nanowires (NWs) were grown on Si(100) substrates at 975 °C by a vapor-liquid-solid method with ~2 nm and ~4 nm gold thin films as catalysts, followed by an argon plasma treatment for the as-grown ZnO NWs. A single ZnO NW–based memory cell with a Ti/ZnO/Ti structure was then fabricated to investigate the effects of plasma treatment on the resistive switching. The plasma treatment improves the homogeneity and reproducibility of the resistive switching of the ZnO NWs, and it also reduces the switching (set and reset) voltages with less fluctuations, which would be associated with the increased density of oxygen vacancies to facilitate the resistive switching as well as to average out the stochastic movement of individual oxygen vacancies. Additionally, a single ZnO NW–based memory cell with self-rectification could also be obtained, if the inhomogeneous plasma treatment is applied to the two Ti/ZnO contacts. The plasma-induced oxygen vacancy disabling the rectification capability at one of the Ti/ZnO contacts is believed to be responsible for the self-rectification in the memory cell.