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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. [ABSTRACT FROM AUTHOR]

The tandem organic solar cell could absorb the complementarity sunlight spectra by the sub-cells based on the different energy gap of the active-layer materials. In this work, a wide-band gap of the organic material PTB7-Th: PC71BM is used as the front sub-cells active layer, and the narrow-band gap of PTB7-Th: IEICO-4F is used as the rear sub-cells active layer. The front and rear sub-cells present the complementary absorption spectra leading to the sufficiently improvement of the sunlight absorption. MoO3/Au/ZnO multilayer film is the interconnecting layer. ZnO film was prepared by the sputtering method is smaller root-mean-square than that of the film prepared by the solution synthesis, resulting in a good contact interfacial between the sub-cells. This is in favor of the JSC and FF of the tandem organic solar cell. Importantly, the short-circuit current density of the tandem solar cell is handily controlled by the active-layer concentration of the front sub-cell, the tandem cell exhibits an optimal PCE of 11.77% with a large VOC of 1.45 V. [ABSTRACT FROM AUTHOR]

• An accurate FD model for PV array based on only a small dataset is proposed • A WGAN structure is proposed to generate large number of ETSG dataset that similar to real ETSG samples • A CNN structures is applied to create the FD model using the augmented ETSG dataset • Experimental results demonstrate high accuracy and reliability of the proposed method Accurate faults diagnosis for photovoltaic (PV) array is one of the vital factors that guarantee the reliable operation of PV power plant. Artificial intelligence (AI) based fault detection and diagnosis (FDD) models are promising techniques. In order to automatically extract the faults features from the raw electrical data of PV array and create efficient FDD model with small dataset, a FDD scheme using Wasserstein generative adversarial network (WGAN) and convolutional neural network (CNN) is designed. The proposed FDD model is consisting of three modules, a discriminator, a generator and a classifier for fault diagnosis. By analyzing sequential PV data in a 2-Dimension way, the proposed discriminator and generator learn the distribution of PV data under various PV system operations. Then they are utilized to generate more labeled samples to improve the performance of the CNN based classifier. Thus, the proposed FDD model can be trained only requiring minor labeled samples. A laboratory grid-connected PV system is established to experimentally investigate the performance of the developed method. The results demonstrate that the designed FDD model can accurately diagnose line-line and open circuit faults. [ABSTRACT FROM AUTHOR]

Antimony sulfide (Sb2S3) with a 1D molecular structure has strong bending characteristics, showing great application potential in flexible devices. Herein, the flexible substrate-structured Sb2S3 solar cells is developed and improve device performances by the back interface selenization. The high-quality Sb2S3 film with an optimal thickness of 1.8 μm, ensuring efficient spectra utilization, is deposited on flexible Mo foils by the rapid thermal evaporation technique. To solve the issues of back interfacial recombination and charge transport, the 20 nm MoSe2 layer between Sb2S3 film and Mo foil is fabricated by substrate selenization in the tube furnace. Further investigations indicate that the MoSe2 layer improves the interfacial energy band alignments and induces the [hk1] orientation of Sb2S3 film, thereby passivating defects and enhancing the carrier transport capacity. The flexible solar cell in the structure of Mo foil/MoSe2/Sb2S3/CdS/ITO/Ag, exhibiting good flexibility to stand thousands of bending, achieves an efficiency of 3.75%, which is the highest for Sb2S3 devices in substrate configuration. The presented flexible structure and back interfacial selenization study will provide new prospects for inorganic Sb2S3 thin film solar cells. [ABSTRACT FROM AUTHOR]

Vision‐based displacement measurement is promising and emerging for structural monitoring. However, the accuracy of visual measurement is commonly limited by the resolution of the camera. The super‐resolution (SR) technique can reconstruct high‐resolution images from the corresponding low‐resolution images within the constraints of prior knowledge. Existing SR algorithms mainly focus on improving the overall quality of the image. By contrast, the accurate extraction of the coordinates of feature points is the most important for the visual measurement. Besides, the SR network is usually trained by an artificial dataset whose low‐resolution images are obtained by artificially degrading the corresponding high‐resolution images, instead of those directly captured by cameras. However, this degradation usually is only a simple bicubic downsampling that cannot reflect the real degradation, which will provide inaccurate constraints to the network training. Therefore, this paper proposes a novel SR framework that can significantly preserve the feature coordinators for visual measurement (SRFCP). First, a deep learning‐based SR network that focuses on feature preservation is proposed, which introduces both feature weighted branch and feature preserving loss. Second, an image degradation model is built based on the blur kernel and noise extracted from the images captured in real scene. Experiments on public datasets show that the proposed SRFCP performs well both in terms of the objective evaluation index and the subjective visual effect. Then, a binocular visual measurement platform is set up to measure the distance of adjacent feature points on a chessboard. Lastly, several SR algorithms are evaluated by the improvement they bring to the measurement accuracy. Experimental results show that the distance measurement performance can be significantly improved by the images reconstructed by the SRFCP. Therefore, the proposed SRFCP can accurately reconstruct the high‐resolution images while preserving the features coordinates, which is crucial for the visual measurement in structural monitoring. [ABSTRACT FROM AUTHOR]

Two-dimensional (2D) materials have been showing broad application prospect in energy storage field as electrode of metal ion battery. Here, we use first-principles calculations to explore the possibility of using 2D VSi 2 P 4 as an anode material for lithium-ion batteries and illustrate the function of the structure in improving battery performance. On the basis of this, we model a seven-atom-layer structure and evaluate its performance. Our results show that 2D VSi 2 P 4 have excellent stability and its lower reaction energy barrier of Li ions (0.16 eV) represents the ultra-high charge and discharge rate of Li ions for batteries. The larger theoretical capacity (928 mA h/g) and lower open-circuit voltage (OCV) further improve their battery performance. Our research indicates that VSi 2 P 4 is expected to be an extremely attractive anode material and provides a possible research direction for the application of novel materials in the battery domain. • A new two-dimensional layered material VSi 2 P 4 recently discovered is proposed. • The material displays wonderful anode material properties with high capacity (928 mA h/g). • VSi 2 P 4 has the lowest reaction energy barrier of Li ions (0.16 eV). [ABSTRACT FROM AUTHOR]

Noble metal surface plasmon resonance or photonic crystals (PCs) effect is a novel and effective method for improving upconversion luminescence (UCL). UCL can be effected by the size, thickness of the noble metal film and the photonic band gap (PBG) of the PCs. So it is important to improve UCL by coupling surface plasmons resonance (SPR) with PCs effect. In this work, the PCs/Ag/UC composite films were fabricated to improve the upconversion emission of NaGdF4:Er3+/Yb3+/Al3+ nanocrystals, and the influence of the Ag layer thickness on spectral properties was investigated. Studies reveal that the Ag layer thickness and morphology have a major impact on the Ag nanoparticles (NPs) plasma resonance and UCL intensity of NaGdF4:Er3+/Yb3+/Al3+ nanocrystals for PCs/Ag/UC composite films. The highest enhancement factors of the red and green emissions were found to be 43 and 42 under 980 nm excitation, respectively. That is attributed to the coupling effect of the Ag NPs local SPR and PCs Bragg reflection, the local electromagnetic field enhancement produced by the excitation wavelength overlapping with the photonic band gap and strong plasmon resonance band overlapping with emission wavelength. [ABSTRACT FROM AUTHOR]

Perovskite solar cells have gradually become the most attractive alternative for next-generation photovoltaic devices due to their excellent photovoltaic conversion efficiencies and low manufacturing costs. Defect engineering is an essential topic for improving the performance of perovskite devices. In this study, we utilize a bifunctional alkylamine sulfonate to modify the perovskite interfaces. The TsO− of sulfonates coordinates with Pb2+, while –NH 2 of alkylamine forms hydrogen bonds with iodine, which reduces charge recombination and improves energy level arrangement. The molecular size and the alkylamine's dielectric constant significantly influence the interface modification performance. For the champion device with BATsO treatment, there is an enhancement in both the fill factor and the open-circuit voltage, resulting in a power conversion efficiency (PCE) of 23.53%. After 400 h of working condition, the device maintains roughly 90.40% of its initial efficiency. Therefore, this study postulates that modifying bifunctional alkylamine sulfonates could effectively enhance the PSC's performance. • Diverse alkylamine sulfonates were used in PSCs to study cationic alkyl' impact on interface passivation. • Sulfonates' TsO− coordinates with Pb2+, while alkylamine's –NH 3 + forms bonds with iodine, enhancing energy level order. • PSCs treated with BATsO achieved the best efficiency of 23.53%. [ABSTRACT FROM AUTHOR]

Abstract: Spectra of circular photogalvanic effect (CPGE) and linear photogalvanic effect (LPGE) for inter-band transition have been experimentally investigated in In0.15Ga0.85As/Al0.3Ga0.7As multiple quantum wells (QWs) at room temperature. The CPGE and LPGE spectra are quite similar during the spectral region corresponding to the transitions 1e1hh (the first valence subband of heavy hole to the first conduction band) and 1e2hh, which is also similar to that of the photoconductivity. Comparing the photocurrent induced by LPGE and CPGE along [110] and directions, we obtain the anisotropic ratio of the linear photogalvanic tensor and circular photogalvanic tensor to be and =1.3 ( and ), which indicate that the symmetry of the structure belongs to C 2v point group and the Rashba spin splitting is the dominant mechanism to induce the k-linear spin splitting of the subband in the In0.15Ga0.85As/Al0.3Ga0.7As QWs. The magnitude of the LPGE is nearly at the same order with that of the CPGE for the investigated spectral region at room temperature. [Copyright &y& Elsevier]

• A DcCNN is used to extract fault features from PVA normalized current and voltage. • A feature selection structure is proposed to evaluate extracted features. • A penalty is developed to train the proposed model in an end-to-end way. • Results show that the DcCNN can extract high-discriminative features. • The DcCNN has superior performance for different faults even LLF under complex conditions. The effective fault diagnosis algorithm for the DC side photovoltaic (PV) array of a PV system (PVS) plays an important role in the operation efficiency and safety for PV power plants. But for fault diagnosis models it may fail to diagnose PV array (PVA) faults without detailed and quite fine fault features, especially line-line faults (LLF) occurring in the PVS that works under complex working conditions like low irradiance conditions and LLF with fault impedance. To address these challenges, this paper proposes a fault diagnosis scheme to diagnose different PVA faults using a proposed Dual-channel Convolutional Neural Network (DcCNN), which is able to automatically extract features and weight these features for fault classification. The important and fine features from the current and voltage electrical time series graph (ETSG) are extracted respectively by DcCNN in a double input way. Then, a proposed feature selection structure (FSS) is designed to improve the proposed fault diagnosis model capacity for diagnosing PVA faults under various conditions, including LLF, partial shading condition (PSC) and open circuit faults (OCF). Comparing to manually designed features, FSS not only helps DcCNN extract important features from PVA current and voltage automatically but also evaluates extracted features for further classification of DcCNN. Moreover, in the training stage, a proposed penalty is applied on DcCNN to constrain FSS, resulting in its sparse weight distribution. A comprehensive experiment based on a laboratory roof grid connected PVS is conducted. The results demonstrate the superior performance of the proposed approach compared with other algorithms as it can extract high-discriminative features from PVA current and voltage for different PVA faults, which is also effective on diagnosing LLF under low irradiance conditions and LLF with fault impedance. [ABSTRACT FROM AUTHOR]

• A pyramid-shaped micron-structured PDMS film was used in organic solar cells. • The size of the pyramid plays an important role of the devices performance. • The power conversion efficiency of PTB7-Th: PC 71 BM-based cells reaches to 10.18%. • The devices with the pyramid-shaped PDMS film presents better stability. Since the light harvesting of the organic solar cells (OSCs) is limited by the ultra-thin active layer film due to the low carrier mobility of the organic materials. This study presents a tractable and cost-effective method for enhancement of the light capture of OSCs. A pyramid-shaped micron-structured polydimethylsiloxane (MST-PDMS) anti-reflection film was pasted on the back surface of the OSCs. The MST-PDMS film can reduce the reflectivity of incident light and enhance light capture. Comparing with that of the devices based on the normal indium tin oxide (ITO) glass substrates, the performance of the devices with MST-PDMS was significant improved. The size of the pyramid is an important factor to the performances of the devices. The short circuit current density could increase mostly without sacrificing the open circuit voltage and fill factor, when the width of the pyramid is 9 µm, and a maximum power conversion efficiency (PCE) of PTB7-Th: PC 71 BM-based OSCs reaches to 10.18%. Compared with that of the device without the anti-reflection film, PCE was increased by 17.96%. Further, the OSCs with the pyramid-shaped MST-PDMS exhibits a relatively high hydrophobic properties leading to a better stability of the devices at the ambient environment. [ABSTRACT FROM AUTHOR]

Surface plasmon effects of Ag nanoparticles (NPs) have been extensively applied to enhance upconversion luminescence (UCL) properties of the nanoparticles doped with rare earth ions. However, it is important to control the effective coupling distance between the Ag NPs and the upconversion nanoparticles (UCNPs). In this work, the Ag/ZnO/UC composite films were fabricated by vacuum methods, and the influence of the ZnO spacer layer thickness on spectral properties was investigated. These studies reveal that the ZnO spacer thickness has a strong effect on the Ag NPs plasma resonance and UCL intensity. The highest enhancement factors of the red and green emissions were found to be 18.6 and 5.3 under 980 nm excitation, respectively. That is attributed to the enhancement of the absorption and excitation rate for UCNPs under the equilibrium between non-radiative energy and local field effect. [ABSTRACT FROM AUTHOR]

• Compound fault and open-set fault of PV array are studied together. • The 1D VoVNet-SVDD is proposed for PV array open-set FD. • Three compound FD tasks are designed to simulate PV array scenarios in detail. • The proposed model can accurate classify known faults and identify unknown faults. • The performance of the proposed model is superior to the four compared models. As photovoltaic (PV) arrays are exposed to the outdoors year-round, they are susceptible to various faults. The shading condition, degradation or dust coverage can make fault signals more complex, forming compound faults. These faults can lead to a large loss of power generation or irreversible damage to the PV modules, and even fires in severe cases. Moreover, unknown fault types that have never been seen in the training set may occur at actual working conditions. Therefore, accurate diagnosis of various types of single and compound faults (closed-set faults) by considering the identification of unknown faults, namely open-set faults diagnosis, is crucial to improve the efficiency of operation and maintenance. A 1D VoVNet-SVDD based open-set fault diagnosis model for PV arrays is proposed. The model is a two-stage network model consisting of a 1D VoVNet network and a multi-classification Support Vector Data Description (SVDD) in series. The 1D VoVNet network automatically extracts fault features from the input original I-V curve data. These extracted fault features are then combined with environmental parameters to construct the SVDD model. The SVDD identifies known fault types by constructing a hypersphere for each fault type. Fault types that are not classified into any of the hyperspheres are considered as unknown faults, enabling open-set diagnosis. The experimental results show that the proposed model can accurately classify the closed-set faults among the three designed testing tasks while identify unknown type faults. The comparison demonstrates that the proposed algorithm is superior to the compared models. [ABSTRACT FROM AUTHOR]

• Mo incorporated CZTS with no secondary phases deposited by magnetron co-sputtering. • Formation of bilayer CZTS absorber with different grain microstructure and porosity. • Mo enhances P -type conductivity and absorbance of CZTS for wavelengths <600 nm. • V oc deficit, J sc , and FF improved for CZTS/CdS devices with optimized Mo content. • PCE of optimized Mo incorporated CZTS solar cell increased to 5.49% from 1.63% Molybdenum (Mo) incorporated Cu 1.69 ZnSnS 4 (CZTS) absorber has been deposited onto Mo-coated soda lime glass (SLG) by co-sputtering of Mo and non-stoichiometric quaternary compound targets. After sulfurization at 600 °C, Mo incorporation into CZTS was confirmed by X-ray diffraction (XRD) and secondary ion mass spectrometry (SIMS). From the observed shifts for the (1 1 2) and (2 2 0) peaks, both lattice parameters a and c of the CZTS unit cell were found to decrease with increasing Mo incorporation suggesting cationic substitution by Mo. The Mo incorporated CZTS has a bilayer microstructure in which the lower sub-layer adjacent to the substrate has a smaller grain size and higher porosity than the upper sub-layer. The lower sub-layer is also richer in Mo and has a graded Mo profile. Sheet resistance measurements on Mo incorporated CZTS films deposited on SLG and on quartz show resistivity that decreases with the amount of Mo in CZTS and Mo acts as an acceptor dopant. The energy band gap of CZTS on SLG increases from 1.38 eV to about 1.68 eV as a result of Mo incorporation and the absorbance of Mo incorporated CZTS is increased for wavelengths shorter than 600 nm. When Mo is co-deposited at the optimized DC sputtering power of 10 W, Mo incorporated CZTS/CdS solar cells attain a maximum power conversion efficiency (PCE) of 5.49% versus 1.63% for the reference device under 1 Sun AM 1.5 illumination. Device efficiency enhancement is due to back surface field, increased carrier concentration and reduced band tailing. [ABSTRACT FROM AUTHOR]

Highlights • A deep residual network based black-box modeling method is proposed for PV modules. • The proposed method is tested using large measured I-V curve datasets from NREL. • Abnormal detection and grid sampling is used to preprocess I-V datasets. • The proposed model is compared with a white-box model and three ANN based models. • The proposed black-box model is superior in terms of accuracy and generalization. Abstract Accurate and reliable modeling of photovoltaic (PV) modules is significant for optimal design, operation and evaluation of PV systems. PV models can be classified into equivalent circuit-based white box models and data-driven black box models. Due to the difficulty to obtain the ground true model parameters and the limitation posed by the predetermined model structure, white-box modeling methods generally suffer relatively low accuracy and generalization performance for arbitrary operating conditions. In addition, reported black-box models are based on the conventional artificial neural networks (ANN) that are efficient but have limited performance. In this study, motivated by the high performance of fast developing deep learning techniques, we propose a novel black-box modeling method for the PV modules using a new modified one-dimensional deep residual network (1-D ResNet) and measured I-V characteristic curves, which can predict a whole I-V curve at a time for arbitrary operating conditions. To alleviate the overfitting issue caused by imbalanced data, original I-V curve datasets with highly non-uniform operating conditions are resampled by a grid sampling approach to obtain the datasets with relatively uniform conditions for the subsequent modeling. The proposed 1-D ResNet based model is comprehensively verified and compared with a proposed single-diode based white-box model and three other conventional ANN based black-box models, using large datasets of measured I-V characteristic curves from the National Renewable Energy Laboratory (NREL). Experimental results indicate that black-box models are generally better than the white-box model. Especially, the proposed 1-D ResNet based PV model is obviously superior to other three conventional ANN based black-box models, in terms of accuracy, generalization performance and reliability. [ABSTRACT FROM AUTHOR]

Highlights • A novel random forest based fault diagnosis method is proposed for PV arrays. • Fault features only consist of PV array voltage and string currents. • Gird search method is used to optimize the parameters of random forest algorithm. • Both simulation and real experiments validate the high accuracy and generalization performance. • The proposed fault diagnosis method is implemented in a developed system prototype. Abstract With the rapid growth of installed capacity of photovoltaic power systems, status monitoring and fault diagnosis of PV arrays becomes increasingly important for improving the energy conversion and maintenance efficiency. In recent years, many machine learning algorithms were successfully applied to automatically build fault diagnosis models using the fault data samples. However, most of them suffer overfitting problem and the generalization performance is still limited. In this paper, the random forest (RF) ensemble learning algorithm is explored for the detection and diagnosis of PV arrays early faults (including line-line faults, degradation, open circuit, and partial shading), which combines multiple learning algorithms to achieve a superior diagnostic performance. The proposed RF based fault diagnosis model only takes the real-time operating voltage and string currents of the PV arrays as the fault features, which is irrelevant to the environment conditions. In addition, a grid-search method is used to optimize the parameters of the RF model by minimizing the out-of-bag error estimation, so as to improve the fault diagnosis model. In order to obtain sufficient fault data samples, comprehensive fault experiments are conducted on both a Simulink based simulated PV system and a laboratory PV system. The simulation and experimental results both demonstrate that the optimized RF based fault diagnosis model can achieve a high overall detection and diagnosis performance. Moreover, the comparison results indicate that the generalization performance of the proposed RF based model is better than the one of the decision tree based model. Therefore, the proposed optimal RF based method is an effective and efficient alternative to detect and classify the faults of PV arrays. Furthermore, the proposed RF based fault diagnosis model is successfully integrated into a Matlab based real-time monitoring system prototype developed for the laboratory PV system, which validates the practicability as well. [ABSTRACT FROM AUTHOR]

Highlights • Short-term PV power prediction model using favorable historical data is presented. • GRA and K-means++ algorithms are used to find similar days and optimal similarity. • The samples of similar days and optimal similarity are used to train the Elman NN. • Comparative results show the outstanding performance of the proposed method. Abstract With the continuous consumption of fossil fuels such as coal, oil and natural gas, the environmental energy problem has become the focus of attention in the world. The utilization of clean and non-polluting solar energy for photovoltaic (PV) power generation can effectively utilize renewable energy. However, the instability of weather condition makes the output of PV power have strong randomness, fluctuations and intermittence. Therefore, reliable PV power prediction method can reduce the disadvantages of PV power generation, which is of great significance to maintenance and repair of power plants. In the study, a novel hybrid prediction model combining improved K-means clustering, grey relational analysis (GRA) and Elman neural network (Hybrid improved Kmeans-GRA-Elman, HKGE) for short-term PV power prediction is proposed. The proposed model is established by using multivariate meteorological factors and historical power datasets for two years. The improved K-means approach is applied to cluster the historical power datasets, and combining the GRA method to determine the similarity days and the optimal similarity day of the forecasting day. The Elman neural network model is employed to better develop the nonlinear relationship between multivariate meteorological factors and power data. Compared with the other eight prediction methods, the results show that the proposed method has an outstanding performance on improving the prediction accuracy. [ABSTRACT FROM AUTHOR]

Three-dimensional (3D) topological insulators (TIs) have attracted much attention due to their topologically protected surface states. Here, we use circularly polarized light to induce the photo-induced anomalous Hall effect (PAHE) in 3D TIs Sb 2 Te 3 thin films with different thicknesses of 5, 7, 12 and 20 quintuple layers (QLs) at room temperature. The dependence of PAHE current on the light spot locations of Sb 2 Te 3 thin films is investigated, which is found to show a completely different behavior from that observed in two-dimensional electron gas (2DEG) systems. This is due to the fact that the total PAHE current is the superposition of the PAHE of the top and bottom surface states. A theoretical model has been proposed to separate the PAHE current of the top and bottom surface states. In addition, as the thickness of the Sb 2 Te 3 film increases from 5 QL to 20 QL, the PAHE currents of the top and bottom surface states first increase and then decrease. The photo-induced anomalous Hall, conductivity of the top surface states in the 7-QL Sb 2 Te 3 film excited by 1064 nm light is as large as 592 nA ⋅ V − 1 ⋅ cm ⋅ W−1, which is much larger than that observed in InGaAs/AlGaAs quantum wells (4.45 nA ⋅ V − 1 ⋅ cm ⋅ W−1) and GaN/AlGaN heterostructures (1.43 nA ⋅ V − 1 ⋅ cm ⋅ W−1). The giant PAHE value observed in Sb 2 Te 3 films suggests that 3D TIs may provide a good platform for spintronic devices. • The spatial distribution of the PAHE currents has been investigated in the Sb 2 Te 3 film. • A model has been developed to separate the PAHE currents in the Sb 2 Te 3 film. • The photo-induced anomalous Hall conductivity of the Sb 2 Te 3 is much larger than 2DEG. [ABSTRACT FROM AUTHOR]

• A lithiophilic and conductive interlayer is prepared by electrospinning. • The interlayer can be used as both a Li+ redistributor and a lithiophilic host. • The composite anode has superior performance at ultrahigh current and capacity. Lithium metal battery is strongly deemed as the most promising next-generation energy-storage devices due to its high theoretical energy density. However, uneven lithium deposition and infinite volume change are still the main challenges that significantly hinder their practical applications. Herein, a silicon nanoparticle-decorated carbon nanofibers (Si@CNFs) mat was explored as a novel lithiophilic and conductive interlayer for commercial Li foil. The Si@CNFs interlayer with three-dimensional porous and conductive structure can act as a Li+ redistributor and a lithiophilic host to regulate Li deposition behaviors and buffer the volume changes during the Li plating/stripping processes. The obtained Si@CNFs-Li anodes possess outstanding cycling stability under ultrahigh currents and capacities (e.g. 1800 cycles at 20 mA cm−2/5 mAh cm−2 and 900 cycles at 80 mA cm−2/40 mAh cm−2). This strategy is facile and efficient in inhibiting Li dendrite growth and can be extended to other alkali metal batteries. [ABSTRACT FROM AUTHOR]

[Display omitted] • Fluorophlogopite mica can be used as an alkali metal source to assist in the growth of 2D materials. • Fluorophlogopite mica can act as alkali metal ions to assist in the growth of 2D materials at high temperatures. • The obtained 2D MoO 2 has a good conductivity. Everyone familiar with two-dimensional (2D) materials is aware of fluorophlogopite mica (FM), which has an atomic-level flat surface that provides an ideal platform for the growth of 2D materials. Since it has been demonstrated that the alkali metal ions (AMI) can aid in the growth of large-sized 2D materials by chemical vapor deposition (CVD) in recent years, it became a major mystery whether FM which contains AMI benefits from them in the preparation of 2D materials by CVD, too. In this article, we dispelled this ambiguity and discovered that temperature is the key for FM as an AMI source to boost the growth of large-sized 2D materials. We carried out variable temperature experiments and found that FM can indeed be incorporated into the growth of large-sized 2D materials as an AMI source at high temperatures and successfully obtained the highly crystalline MoO 2 with a larger size compared to those without FM. This finding is of great importance to the understanding of the growth mechanism of FM for 2D materials by CVD and to better exploit its role in the growth of 2D materials. [ABSTRACT FROM AUTHOR]

A unique bilayer carbon structure was developed as a flexible sulfur host for high-performance lithium-sulfur batteries. Effective physical blocking, storing and chemical anchoring of polysulfides is achieved by integrating the synergistic effect of chemical adsorption of the internal Co and carbon nanotube skeleton and the micrometer-level physical confinement of the external graphene nanoflower layer. [Display omitted] • A unique bilayer carbon structure strategy is proposed to inhibit the shuttle effect of polysulfides. • Micrometer-level physical confinement is obtained by developing external graphene nanoflowers layer. • The Co/CNT@GF-S cathode delivers good cycling stability and rate capability. With the exceptional merits of high energy density, low cost, and environmental friendliness, lithium-sulfur batteries are considered to be one of the most promising next-generation flexible rechargeable batteries. However, the notorious "shuttle effect" has seriously hindered their practical applications. Herein, a strategy for designing multi-functional bilayer carbon structures is proposed, specifically, by employing a micrometer-thick graphene nanoflowers (GF) layer to encapsulate a micrometer-scale hybrid network skeleton composed of metallic Co and carbon nanotubes (CNT) as a flexible sulfur cathode host (Co/CNT@GF). Beneficial from the merits of chemical adsorption, electrocatalysis and volume expansion mitigation from the internal skeleton as well as the micrometer-level physical domain confinement by the external GF layer, the developed host could chemically trap, electrochemically catalyze, physically block and storage the lithium polysulfides. Due to the synergistic effect of these functions, the Co/CNT@GF-S delivers a superior discharge capacity of 799 mAh g−1 with a decay rate as low as 0.08 % per cycle after 400 cycles at 1 C. Even at a high sulfur loading of 8.16 mg cm−2, the average discharge capacity is as high as 5.05 mAh cm−2 in 100 cycles. This work does not only contribute to the rational design of multi-functional bilayer structures but also offers a novel design method for the commercialization of flexible lithium-sulfur batteries with high-energy–density. [ABSTRACT FROM AUTHOR]

Perovskite solar cells have drawn significant attention due to their excellent photovoltaic characteristics. Upconversion luminescence material modification is a good strategy to extend the device response to the near-infrared region, which can further increase device efficiency. By adding NaGdF 4 :Er3+/Yb3+ nanorods into chlorobenzene as an additive in the antisolvent to modify the perovskite layer, we found that upconversion luminescence nanoparticles can effectively improve the perovskite solar cell performance. However, unexpectedly, the photocurrent contributed by the infrared part is lower. The efficiency increase of perovskite solar cells is contributed by defect passivation. Further research shows that nanoparticles can effectively fill the holes and gaps at the grain boundaries, eliminate surface defects of the perovskite, and modify the perovskite film, which reduces carrier recombination and effectively improves the device's performance. Finally, the power conversion efficiency of the champion device can reach 21.1%. This research demonstrates the function of upconversion luminescence nanoparticles in PSCs and provides a simple way to improve the device's efficiency. • The up-conversion luminescence NaGdF 4 :Er3+/Yb3+ is introduced into the perovskite layer via anti-solvent chlorobenzene. • The champion device achieved an efficiency of 21.1% by passivating perovskite grain defects through NaGdF 4 nanocrystals. • The reason for the efficiency enhancement is the increase of carrier lifetime rather than spectrum broadening to infrared field. [ABSTRACT FROM AUTHOR]

Metal halide perovskite solar cells have experienced unexpected rapid growth in the past decade due to their excellent photoelectric conversion efficiency. SnO 2 has attracted great attention as a candidate electron transport layer to replace TiO 2 in perovskite solar cells. However, the mixture of crystalline and amorphous states produces a large number of oxygen vacancy defects in the SnO 2 lattice and surface, leading to nonradiative recombination at the SnO 2 /perovskite interface. In this work, an effective method of doping the rare earth element Gd in SnO 2 is developed for planar perovskite solar cells. Doping with Gd ions can effectively passivate oxygen vacancy defects at the SnO 2 interface, leading to a decrease in surface energy, which contributes to facilitating the formation of high-quality perovskite films. Gd doping can also optimize the energy level matching between SnO 2 and the perovskite layer, thus improving the charge extraction and transport capabilities. As a result, the optimized device achieves a high power conversion efficiency of 22.40%, with a certified value of 21.95%. [Display omitted] • Gd was first introduced into SnO 2 -based planar PSCs. • Gd doped SnO 2 PSCs achieved the best efficiency of 22.4%. • Gd doping reduces interfacial trap-assisted charge recombination. • Gd doped SnO 2 exhibited a better energy level arrangement with the perovskite. [ABSTRACT FROM AUTHOR]

Inverse spin Hall effect (ISHE) provides an important way to manipulate and detect spin current via spin–orbit coupling. However, it is difficult to distinguish the ISHE of the top and bottom surface states of topological insulators (TIs). Photo-induced inverse spin Hall effect (PISHE) is a powerful tool to investigate the ISHE of the Dirac surface states of TIs. In this work, PISHE of three-dimensional topological insulators Sb 2 Te 3 with a thickness of 7 and 30 quintuple layer (QL) has been investigated. It is revealed that both of the PISHE currents of the top and bottom surface states are observed in the 7-QL and the 30-QL samples. Besides, a model has been developed to separate the PISHE current of the top and bottom surface states. It is found that the PISHE currents of the top and bottom surface states of the Sb 2 Te 3 films almost do not change with temperature in the range of 77 to 300 K. It is demonstrated that the PISHE current changes linearly with light power, which agrees well with the theoretical model. This study provides a method utilizing circularly polarized light to manipulate and detect the ISHE of the top and bottom surface states of three-dimensional topological insulators. • Both of the PISHE currents of the top and bottom surface states are observed in the 7-QL and the 30-QL Sb 2 Te 3 films. • A model has been developed to separate the PISHE current of the top and bottom surface states. • The PISHE currents of the top and bottom surface states of the Sb 2 Te 3 films almost do not change with temperature in the range of 77 to 300 K. [ABSTRACT FROM AUTHOR]

• A detection method for bundled log ends using K-median clustering and improved YOLOv4-Tiny network is proposed. • The multi-scale anchors make the height and width of predicted boxes more consistent with labeled boxes. • The three detection scales are applied and the SPP is added to detect small log ends. • The SE is applied to reduce the error gathering of the centers of log ends and predicted boxes. • The proposed model has promising performance in the detection of bundled log ends. In log trade, precise measuring log volume is directly related to the economic benefits. Usually, the length of the same batch of wood is relatively fixed, but the shape and size of log end are different. Therefore, the variability of the size, shape and density of log end, and the sophisticated scenarios lead to great challenge for log detection from bundled log ends images. In addition, the large number of logs in the bundled log ends image results in less pixels occupied by a single log, and it is essential to detect the small log ends. In order to accurately detect each log from bundled log ends image, a new approach of log detection based on K-median clustering and improved You Only Look Once (YOLO)v4-Tiny network has been developed. The specific methods are as follows: (1) In consideration of the characteristics of log size, shape and its distribution, the K-median clustering method is used to select a more appropriate size of multi-scale anchor boxes to achieve a more consistent detection boxes for the log ends; (2) The detection scales of YOLOv4-Tiny network are increased to three and the spatial pyramid pooling (SPP) module is added to enhance the ability of feature extraction for small targets, such as small log end; (3) The self-attention mechanism based on squeeze and excitation (SE) is inserted into the deep structure of the network, which automatically determines the threshold without relevant professional knowledge to eliminate the high-dimensional noise that may result in error gathering of the centers of log ends and predicted boxes. The Precision , Recall and F1-score of YOLOv4-Tiny in the experimental test set are 91.87%, 94.91% and 0.93 respectively, while the three indicators are improved to 93.97%, 95.34% and 0.95 respectively by using the proposed model. Moreover, the complete intersection over union (CIoU) loss of our model is 2.46 and is reduced by 51.48% compared to the YOLOv4-Tiny with 5.07, which means the predicted boxes of our model are closer to the target bounding boxes. Consequently, the experiment results demonstrate that the performance of the proposed approach is better than that of YOLOv4-Tiny network. [ABSTRACT FROM AUTHOR]

Abstract: The heterogeneous catalytic hydrogenation of acetophenone (Aceph) over Pt/Al2O3 in -toluene/-toluene at 273 K was performed in semibatch mode, using a recycle configuration and on-line quantitative Fourier transform infrared (FTIR) spectroscopy measurements. Based on the -toluene solvent used and the multivariate analysis applied, further details of the reaction chemistry were elucidated, including the following: (i) Solvent activation occurred during reaction, leading to observable hydrogenation and H–D exchange, and (ii) 1-phenylethanol (Phel), cyclohexyl methyl ketone (CMK), and cyclohexylethanol (Che) were observable products, and little H–D exchange occurred. The on-line FTIR measurements, with sensitivity on the order of , also lead to the following kinetic observations: (i) Water had a strong inhibiting effect on the hydrogenation rates, and (ii) very interesting short time-scale kinetic behavior occurred after some perturbations. The latter included rapid initial hydrogenations on fresh catalyst (due to the presence of spillover hydrogen) and observable adsorption–desorption of other reactants. The reaction rates obtained from the well-defined experiments in -toluene were fit to a number of Langmuir–Hinshelwood–Hougen–Watson (LHHW) models, in which the effects of solvent and water were included. A model involving a pairwise addition of adsorbed dissociated hydrogen to the adsorbed substrate provided the best fit of the data. The regression of the kinetic data suggested that water made a statistically significant contribution to the competitive adsorption on the catalyst surface. In more general terms, the present contribution suggests the utility of detailed on-line liquid-phase spectroscopy together with multivariate techniques for exploratory studies of heterogeneous catalytic systems. [Copyright &y& Elsevier]

• An extreme learning machine based rapid modeling method is proposed for PV modules. • The input features and single-hidden layer feedforward neural network are optimized. • Anomaly detection and grid resampling methods are proposed to preprocess datasets. • The ELM based PV model is compared with BPNN, GRNN, SVM, RF and RNN based PV models. • The ELM based PV model is greatly superior in terms of training speed. Efficient and accurate photovoltaic (PV) modeling plays an important role in optimal evaluation and operation of PV power systems. Using current–voltage (I-V) curves measured at different operating conditions, a novel extreme learning machine (ELM) based modeling method is proposed for characterizing the electrical behavior of PV modules, which features high training speed and generalization performance. Firstly, a voltage-current grid based method is used to resample each raw measured I-V curve for reducing data redundancy of I-V curves, a slope change based detection method is proposed to exclude the abnormal I-V curves for improving the data quality, and an irradiance-temperature grid based method is applied to downsample the dataset. Secondly, a single hidden-layer feedforward neural network (SLFN) is proposed as the model structure, which is then trained by the ELM learning algorithm. Particularly, the configuration of the ELM is optimized by cross-validation. Finally, the proposed ELM based PV modeling method is verified and tested on the preprocessed large datasets of I-V curves of six PV modules from the National Renewable Energy Laboratory. Moreover, in order to verify the advantage, the ELM based PV modeling is further compared with some commonly used machine learning based methods. Experimental results demonstrate that the proposed ELM based PV modeling method features fast training, high accuracy and generalization performance. The comparison results further indicate that the ELM based model is greatly superior in terms of the training time, and is slightly better than other algorithms in terms of the model accuracy and generalization performance. [ABSTRACT FROM AUTHOR]

• A dynamic capacitor charging based fast I-V curve tracer is designed for PV arrays. • An adaptive sampling interval method is proposed to achieve the uniform sampling. • A hybrid optimization algorithm is proposed for model parameter extraction. • The parameter extraction method is superior in terms of accuracy and convergence. • The I-V curve tracer is validated by field testing on a laboratory PV array. In order to accurately and efficiently evaluate the actual operating status of photovoltaic (PV) power stations, this study proposes a novel design of quick current–voltage (I-V) curve tracer with automatic parameter extraction for PV arrays. The I-V tracer exploits the dynamic capacitor charging to quickly and safely scan the output I-V curve of PV array. Particularly, an adaptive sampling interval and charging and discharging time estimation method is proposed to achieve the uniform sampling of the I-V curve for improving the data quality. Moreover, an efficient grid search and improved Nelder-Mead simplex (GS-INMS) based hybrid optimization algorithm is proposed for PV model parameters identification. In the GS-INMS algorithm, the grid search method is used for finding starting point for the NMS optimization algorithm, which can improve the global search capability. Meanwhile, the basic NMS algorithm is modified to improve the local convergence. The performance of the proposed algorithm is verified and compared with some state-of-the-art methods on several experimental datasets, including two benchmark I-V curves, large dataset of I-V curves from the National Renewable Energy Laboratory (NREL), and the I-V curves collected by the designed I-V tracer system. Comprehensive comparison results demonstrate that the proposed GS-INMS shows obvious superiority in accuracy, convergence and robustness. Meanwhile, because of low complexity, this algorithm is embedded in the designed tracer for real-time parameters extraction of the single-diode model of PV arrays. In addition, the experimental results of field testing on a small-scale PV array indicate that the I-V tracer can quickly acquire I-V curves of high quality and perform accurate model parameter identification in real time. [ABSTRACT FROM AUTHOR]

• A FR-FDOCT was proposed based on Mach–Zehnder interferometer with a tilted mirror which could generate simultaneously a series of accurate phase-delay interference signal. • FR-FDOCT is capable of acquiring artifact-free images by construction of both amplitude and phase of interferogram from multiple sets of phase-delay signals. • The Mach–Zehnder interferometric structure with a tilted mirror in reference arm could actively promote the innovation and development of OCT technology. We proposed a full-range Fourier-domain optical coherence tomography (FR-FDOCT) based on a Mach–Zehnder interferometer with a tilted mirror which could generate a series of accurate phase-delay interference signals simultaneously. The FR-FDOCT is capable of acquiring artifact-free images by the construction of both amplitude and phase of the interferogram from multiple sets of phase-delay signals. The Mach–Zehnder interferometer make the reference arm became single-way optical path which is more convenient to adjust the reference beam than the return-way optical path (which means the incident and reflected beams use the same optical path) of traditional systems. A series of phase-delay interference signals were simultaneously acquired by a home-made two-dimensional spectrometer when tilting the mirror in the reference arm. The technique was employed to measure an anterior chamber of a porcine eye with a high symmetric artifact suppression of more than 45 dB. The technology could achieve double-range images effectively without any additional scanning device. It could actively promote the innovation and development of OCT technology. [ABSTRACT FROM AUTHOR]

• A deep residual network based fault diagnosis method is proposed for photovoltaic arrays. • Current-voltage curve is combined with irradiance and temperature to form data samples. • The deep residual network features automatic feature extraction and high performance. • Fault experiments are performed on a real photovoltaic array and its Simulink based model. • Experimental results obviously validate the superiority of the proposed method. Automatic fault detection and diagnosis techniques for photovoltaic arrays are crucial to promote the efficiency, reliability and safety of photovoltaic systems. In recent decades, many conventional artificial intelligence approaches have been successfully applied to automatically establish fault detection and diagnosis model using fault data samples, but most of them rely on manual feature extraction or expert knowledge to build diagnosis models, which is inefficient and may ignore some potential useful features. In addition, they usually use shallow neural networks with limited performance. Addressing the issues, this paper proposes a novel intelligent fault detection and diagnosis method for photovoltaic arrays based on a newly designed deep residual network model trained by the adaptive moment estimation deep learning algorithm, which can automatically extract features from raw current-voltage curves and ambient irradiance and temperature, and effectively improve the performance with a deeper network. In order to validate the proposed fault diagnosis model, a Simulink based simulation model is designed for a real laboratory photovoltaic array, and both fault simulation and real experiments are carried out to obtain simulation and experimental fault datasets. Furthermore, two other popular deep learning based models are used for comparison, including convolution neural network and convolutional auto-encoder. Both of simulation and real experimental comparison results demonstrate that the proposed deep residual network based method achieves high and best overall performance in terms of accuracy, generalization performance, reliability and training efficiency. [ABSTRACT FROM AUTHOR]

Ion doping is an effective strategy for achieving high-performance flexible Cu 2 ZnSn(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 Cu Zn anti-site defects is decreased by 8.13% after Li incorporation, and that of the benign Na Zn 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 cm 2 ) and obtains 9.41% PCE. The co-doping investigation to synergistically regulate defects provides a new perspective for efficient flexible CZTSSe solar cells., (© 2023 The Authors. Advanced Science published by Wiley-VCH GmbH.)

Antimony sulfide (Sb 2 S 3 ) photodetectors (PDs) have great potential in commercial applications. The performances are affected by photocarrier distribution and recombination. Here, the gate-controlled Sb 2 S 3 thin film PD is fabricated on the TiO 2 /SiO 2 /Si substrate by the vacuum method. The p-channel Sb 2 S 3 transistor obtained a threshold voltage of 0.6 V and a switching ratio of 1064, achieving an effective regulation by gate voltages. A negative gate voltage can enhance conductivity and can suppress recombination. The responsivity and detectivity of the PD reach 1.6 A/W and 1.2 × 10 11  Jones, respectively. The device realizes logic outputs by the signal inputs of illumination and gate voltage.

Bismuth oxyselenide (Bi 2 O 2 Se) is a two-dimensional (2D) layered semiconductor material with high electron Hall mobility and excellent environmental stability as well as strong spin-orbit interaction (SOI), which has attracted intense attention for application in spintronic and spin optoelectronic devices. However, a comprehensive study of spin photocurrent and its microscopic origin in Bi 2 O 2 Se is still missing. Here, the helicity-dependent photocurrent (HDPC) was investigated in Bi 2 O 2 Se nanosheets. By analyzing the dependence of HDPC on the angle of incidence, we find that the HDPC originates from surface states with C s symmetry in Bi 2 O 2 Se, which can be attributed to the circular photogalvanic effect (CPGE) and circular photon drag effect (CPDE). It is revealed that the HDPC current almost changes linearly with the source-drain voltage. Furthermore, we demonstrate effective tuning of HDPC in Bi 2 O 2 Se by ionic liquid gating, indicating that the spin splitting of the surface electronic structure is effectively tuned. By analyzing the gate voltage dependence of HDPC, we can unambiguously identify the surface polarity and the surface electronic structure of Bi 2 O 2 Se. The large HDPC in Bi 2 O 2 Se nanosheets and its efficient electrical tuning demonstrate that 2D Bi 2 O 2 Se nanosheets may provide a good platform for opto-spintronics devices.

Cross-contamination during pharmaceutical drug manufacturing can result in expensive recalls. To counter that, companies spend significant time and resources to ensure equipment cleanliness, often relying on the compound solubility data in various solvents as the main indicator of cleaning success. The aim of this work is to provide an alternative way to analyze the fouling and cleaning of surfaces in pharmaceutical manufacturing processes by using the quartz crystal microbalance with dissipation (QCM-D) and Raman spectroscopy. In this study, we chose an active pharmaceutical ingredient (API), sitagliptin phosphate monohydrate (SIT), as the model drug compound and observed its adsorption and desorption on stainless steel (SS2343), borosilicate glass (glass), and polytetrafluoroethylene (PTFE) surfaces. SIT was selected as the model API since it is a product manufactured on a large scale and is part of the widely used dipeptidyl peptidase-IV inhibitor class of oral hypoglycemics used to treat type 2 diabetes mellitus, while the chosen surfaces mimic the wall materials of manufacturing equipment and components such as reactors, transfer lines, and valves. Both the QCM-D and Raman spectroscopy results show the highest physisorption on PTFE, followed by SS2343 and glass. Additionally, QCM-D revealed a harder removal of SIT from SS2343 compared to glass and PTFE. Raman analysis of the chemical interactions disclosed C-F and C═O bond interactions between SIT and the surfaces, and the lack of a peak shift suggested dipole-dipole interactions. Furthermore, contact angle measurements indicate that hydrophobic attraction contributed to SIT adhesion to the PTFE surface. Subsequently, SIT coverage upon deposition on a PTFE surface has a significantly smaller surface area than on SS2343 and glass due to surface hydrophobicity, hence resulting in a longer removal time. These results provide a practical use of QCM-D and Raman spectroscopy to enhance the understanding of fouling and improve the cleaning of complex small molecules on relevant surfaces during the pharmaceutical manufacturing process.

Flexible Cu 2 ZnSn(S,Se) 4 (CZTSSe) solar cells show great potential due to non-toxicity and low cost. The quality of CZTSSe absorber suffering from the high-temperature selenization process is the key to overcoming open-circuit voltage (V OC ) deficit and obtaining high efficiency. In this work, the authors develop a selenization technique to improve the quality of the CZTSSe layer by pre-evaporation selenization. This method provides saturated selenium vapor at the beginning of the selenization process to promote the crystallization process. The oversaturated selenium source greatly shortens the annealing time at high temperatures. The prepared CZTSSe films have larger grains and fewer voids. The measurement of the space charge limited current shows that the defect density of the CZTSSe absorber is significantly reduced from 4.43 × 10 13  cm -3 to 3.46 × 10 13 cm -3 . Electrical tests show that the devices have better charge separation at the interface, resulting in a charge recombination lifetime, increasing from 133 to 197 µs. The power conversion efficiency of the flexible CZTSSe solar cell reaches 10.24% with V OC and the fill factor enhances to 463 mV and 62%, respectively. The safe non-toxicity and efficient selenization method is expected to provide a new strategy for high-efficiency flexible CZTSSe solar cells., (© 2022 Wiley-VCH GmbH.)

The photoinduced inverse spin Hall effect (PISHE) has been studied in three dimensional (3D) topological insulator (TI) Bi 2 Te 3 thin films with different thicknesses (3, 5, 12 and 20 quintuple layer (QL)). The sign of the PISHE current flips only once in the 3- and 20-QL Bi 2 Te 3 films, but it flips three times in the 5-, 7- and 12-QL samples. The three-times sign flip is due to the superposition of the PISHE current of the top and bottom surface states in Bi 2 Te 3 films. By analyzing the x-ray photoelectron spectroscopy (XPS) of the Bi 2 Te 3 films, we find that the top surface of the 3- and 20-QL Bi 2 Te 3 films are severely oxidized, leading to only one sign flip in the PISHE. The PISHE contributed by the top and bottom surface states in Bi 2 Te 3 films have been successfully separated by fitting a theoretical model to the PISHE current. The impact of the bulk states on PISHE current has been determined. The PISHE current is also measured at different light powers, and all the measurement results are in good agreement with the theoretical model. In addition, it is found that the PISHE current in Bi 2 Te 3 films grown on Si substrate is more than two orders larger than that grown on SrTiO 3 substrates, which can be attributed to the larger absorption coefficient for Bi 2 Te 3 /Si samples. It is revealed that the PISHE current in 3D TI Bi 2 Te 3 is as large as 140 nA/W in the 3-QL Bi 2 Te 3 film grown on Si substrate, which is more than one order larger than that reported in GaAs/AlGaAs heterojunction (about 2 nA/W) and GaN/AlGaN heterojunction (about 1.7 nA/W). The giant PISHE current demonstrates that the TIs with strong SOC may have good application prospects in spintronic devices with high spin-to-charge conversion efficiency.

Photodetectors (PDs) for weak light signal detection have wide applications for optical communication and imaging. Antimony sulfide (Sb 2 S 3 ) as a nontoxic and stable light-sensitive material becomes a promising candidate for weak light PDs, which are developing in the direction of high response, high speed, and low cost. Herein, a self-powered Sb 2 S 3 PD with the structure of FTO/TiO 2 /Sb 2 S 3 /Au is developed to achieve weak light detection for 300-750 nm visible light. We control the Sb 2 S 3 thickness with about 460 nm to match depletion region width (438 nm) and obtain an excellent photoresponsivity and 3 dB bandwidth. Furtherly, we prepare pyramid structure polydimethylsiloxane (PDMS) on the illuminating surface to enhance the performance of weak light detection by light-trapping effects. The photocurrent of Sb 2 S 3 PD with 20 μm-sized PDMS texture achieves 13.6% improvement compared with the control one. Under weak 530 nm light illumination of 1 μW cm -2 , the self-powered Sb 2 S 3 PD with PDMS achieves high responsivity (3.41 A W -1 ), large detectivity (2.84 × 10 13 Jones), and ultrafast speed (15 μs). The present Sb 2 S 3 PD and light-trapping strategy are expected to provide an alternative to future commercial weak light detection applications.

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 CoSe 2 -nanoparticle-anchored nitrogen-doped carbon nanoflake arrays is developed on a carbon fiber cloth (CoSe 2 -NC@CFC) to regulate the Li nucleation/plating process and stabilize the electrolyte-anode interface. Owing to the enhanced lithiophilicity endowed by CoSe 2 -NC, in situ-formed Li 2 Se and Co nanoparticles during initial Li nucleation, and large void space, CoSe 2 -NC@CFC can induce homogeneous Li nucleation/plating, optimize the solid electrolyte interface, and mitigate volume change. Consequently, the CoSe 2 -NC@CFC can accommodate Li with a high areal capacity of up to 40 mAh cm -2 . Moreover, the Li/CoSe 2 -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/CoSe 2 -NC@CFC//LiFePO 4 full cell delivers impressive long-term performance and favorable flexibility. The developed CoSe 2 -NC@CFC provides insights into the development of advanced Li hosts for flexible and stable LMAs., (© 2022 The Authors. Advanced Science published by Wiley-VCH GmbH.)

In order to achieve low-cost, high efficiency and stable photoelectric devices, two-dimensional (2D) inorganic halide perovskite photosensitive layers need to cooperate with other functional layers. Here, we investigate the structure, stability and optical properties of perovskite and transition metal dichalcogenide (TMD) heterostructures using first-principles calculations. Firstly, Cs 2 PbX 4 -PtSe 2 (X = Cl, Br, I) heterostructures are stable because of negative interface binding energy. With the halogen varying from Cl to I, the interface binding energies of Cs 2 PbX 4 -PtSe 2 heterostructures decrease rapidly. 2D Cs 2 PbCl 4 -PtSe 2 , Cs 2 PbBr 4 -PtSe 2 and Cs 2 PbI 4 -PtSe 2 heterostructures have an indirect bandgap with the value of 1.28, 1.02, and 1.29 eV, respectively, which approach the optimal bandgap (1.34 eV) for solar cells. In the contact state, the electrons transfer from the PtSe 2 monolayer to Cs 2 PbX 4 monolayer and only the Cs 2 PbBr 4 -PtSe 2 heterostructure maintains the type-II band alignment. The Cs 2 PbBr 4 -PtSe 2 heterostructure has the strongest charge transfer among the three Cs 2 PbX 4 -PtSe 2 heterostructures because it has the lowest tunnel barrier height (Δ T ) and the highest potential difference value (ΔEP). Furthermore, the light absorption coefficient of Cs 2 PbX 4 -MSe 2 heterostructures is at least two times higher than that of monolayer 2D inorganic halide perovskites. With the halogen varying from Cl to I, the light absorption coefficients of the Cs 2 PbX 4 -PtSe 2 heterostructures increase rapidly in the visible region. Above all, the Cs 2 PbX 4 -MSe 2 heterostructures have broad application prospects in photodetectors, solar cells and other fields., Competing Interests: There are no conflicts to declare., (This journal is © The Royal Society of Chemistry.)

As a key factor for fast-charging lithium-ion batteries (LIBs), high-rate anode materials that can recharge in a few minutes have aroused increasing attention. However, high-rate performance is always accompanied by low theoretical capacities, such as the widely known high-rate electrode of Li4Ti5O12 (175 mA h g-1), which severely limits its large-scale implementation in the development of high power density LIBs. Here, we report a modified close-spaced thermal evaporation process to deposit 3D-structured Sb2Se3 films (3D-SSF) with tunable morphology as an additive-free anode for LIBs. After a high-rate activation process, 3D-SSF exhibits a flatter discharge plateau than the reported results and could deliver a high capacity of 471 mA h g-1 at an ultrahigh current density of 21 440 mA g-1, which is superior to the widely known high-rate Li4Ti5O12 anode (over 150 mA h g-1 at 8750 mA g-1). Moreover, we reveal a current-regulated Li-ion storage mechanism where 3D-SFF undergoes a synergistic conversion and alloying reaction at low current densities, while an alloying reaction-dominated process at high rates. Beyond that, full batteries with excellent rate performance were successfully assembled by pairing with homemade LiFePO4 (LFP) as the cathode.

Environment-friendly flexible Cu 2 ZnSn(S,Se) 4 (CZTSSe) solar cells show great potentials for indoor photovoltaic market. Indoor lighting is weak and multi-directional, thus the researches of photovoltaic device structures, techniques and performances face new challenges. Here, we design symmetrical bifacial CZTSSe solar cells on flexible Mo-foil substrate to efficiently harvest the indoor energy. Such devices are fabricated by double-sided deposition techniques to ensure bifacial consistency and save cost. We report 9.3% and 9% efficiencies for the front and back sides of the flexible CZTSSe solar cell under the standard sun light. Considering the indoor environment, we verify weak-light response performance of the devices under LED illumination and flexibility properties after thousands of bending. Bifacial CZTSSe solar cells in parallel achieve the superposition of double-sided output current from multi-directional light, significantly enhancing the area utilization rate. The present results and methods are expected to expand indoor photovoltaic applications.

The circular photogalvanic effect (CPGE) provides a method utilizing circularly polarized light to control spin photocurrent and will also lead to novel opto-spintronic devices. The CPGE of three-dimensional topological insulator Bi 2 Te 3 with different substrates and thicknesses has been systematically investigated. It is found that the CPGE current can be dramatically tuned by adopting different substrates. The CPGE current of the Bi 2 Te 3 films on Si substrates are more than two orders larger than that on SrTiO 3 substrates when illuminated by 1064 nm light, which can be attributed to the modulation effect due to the spin injection from Si substrate to Bi 2 Te 3 films, larger light absorption coefficient, and stronger inequivalence between the top and bottom surface states for Bi 2 Te 3 films grown on Si substrates. The excitation power dependence of the CPGE current of Bi 2 Te 3 films on Si substrates shows a saturation at high power especially for thicker samples, whereas that on SrTiO 3 substrates almost linearly increases with excitation power. Temperature dependence of the CPGE current of Bi 2 Te 3 films on Si substrates first increases and then decreases with decreasing temperature, whereas that on SrTiO 3 substrates changes monotonously with temperature. These interesting phenomena of the CPGE current of Bi 2 Te 3 films on Si substrates are related to the spin injection from Si substrates to Bi 2 Te 3 films. Our work not only intrigues new physics but also provides a method to effectively manipulate the helicity-dependent photocurrent via spin injection.

Cation substitution plays a crucial role in improving the efficiency of Cu 2 ZnSn(S,Se) 4 (CZTSSe) solar cells. In this work, we report a significant efficiency enhancement of flexible CZTSSe solar cells on Mo foils by partial substitution of Cu + with Ag + . It is found that the band gap ( E g ) of (Cu 1- x Ag x ) 2 ZnSn(S,Se) 4 (CAZTSSe) thin films can be adjusted by doping with Ag with x from 0 to 6%, and the minimum E g is achieved with x = 5%. We also found that Ag doping can obviously increase the average grain size of the CAZTSSe absorber from 0.4 to 1.1 μm. Additionally, the depletion width ( W d ) at the heterojunction interface of CAZTSSe/CdS is found to be improved. As a result, the open-circuit voltage deficit ( V oc,def ) is gradually decreased, and the band tailing is suppressed. Benefiting from the enhanced open-circuit voltage ( V oc ), the power conversion efficiency (PCE) is successfully enhanced from 4.34% ( x = 0) to 6.24% ( x = 4%), and the V oc,def decreases from 915 to 848 mV., Competing Interests: There are no conflicts to declare., (This journal is © The Royal Society of Chemistry.)

Hydroformylations of cyclopentene and 3,3-dimethylbut-1-ene were performed using both Rh(4)(CO)(12) and (eta(5)-C(5)H(5))Mo(CO)(3)H as precursors in n-hexane at 298 K. Both stoichiometric and catalytic hydroformylations were conducted as well as isotopic labeling experiments. Six organometallic pure component spectra were recovered from the high-pressure FTIR experiments, namely the known species Rh(4)(CO)(12), (eta(5)-C(5)H(5))Mo(CO)(3)H, RCORh(CO)(4), and the new heterobimetallic complexes RhMo(CO)(7)(eta(5)-C(5)H(5)), a weak hydrogen bonded species (eta(5)-C(5)H(5))Mo(CO)(3)H-C(5)H(9)CORh(CO)(4), and a substituted RhMo(CO)(7-y)(eta(5)-C(5)H(5))L(y), where y = 1 or 2 and L = (pi-C(5)H(8)). The main findings were (1) catalytic binuclear elimination (CBER) occurs between (eta(5)-C(5)H(5))Mo(CO)(3)H and RCORh(CO)(4) resulting in aldehyde and RhMo(CO)(7)(eta(5)-C(5)H(5)), and this mechanism is responsible for ca. 10% of the product formation; (2) molecular hydrogen is readily activated by the new heterobimetallic complex(es); (3) FTIR and DFT spectroscopic evidence suggests that the weak hydrogen bonded species (eta(5)-C(5)H(5))Mo(CO)(3)H-C(5)H(9)CORh(CO)(4) has an interaction of the type eta(5)-C(5)H(4)-H...O=C; and (4) independent physicochemical experiments for volumes of interaction confirm that significant solute-solute interactions are present. With respect to the efficiency of the catalytic cycle, the formation of a weak (eta(5)-C(5)H(5))Mo(CO)(3)H-C(5)H(9)CORh(CO)(4) complex results in a significant decrease in the measured turnover frequency (TOF) and is the primary reason for the inhibition observed in the bimetallic catalytic hydroformylation. Such hydrogen bonding through the eta(5)-C(5)H(5) ring might have relevance to inhibition observed in other catalytic metallocene systems. The present catalytic system is an example of concurrent synergism and inhibition in bimetallic homogeneous catalysis.