Search

Perovskite solar cells (PSCs) have garnered significant attention in the photovoltaic field owing to their exceptional photoelectric properties, including high light absorption, extensive carrier diffusion distance, and an adjustable band gap. Temperature is a crucial factor influencing both the preparation and performance of perovskite solar cells. The annealing temperature exerts a pronounced impact on the device structure, while the operational temperature influences carrier transport, perovskite band gap, and interface properties. This paper provides a comprehensive review of the influence of varied annealing temperatures on the hole transport layer, electron transport layer, and perovskite layer. Additionally, we present an overview of innovative annealing methods applied to perovskite materials. The effects of diverse working temperatures on the overall performance of perovskite cells are thoroughly examined and discussed in this review. In the end, different temperature conditions under ISOS testing conditions are summarized.

We analyse the joint scheduling of spare parts production and service engineers in a multi-site maintenance system. In the system, for each failure, a service engineer with the required spare part needs to be allocated for on-site maintenance. If one of the required resources is not readily available, the maintenance task can be satisfied via an external channel with quick responsiveness but high involved costs. Service providers need to make an efficient plan, including production scheduling of spare parts, allocation of service engineers and outsourcing strategy. First, a mathematical model with the objectives of minimum total outsourcing costs and minimum weighted tardiness is formulated. Then, a novel and knowledge-based heuristic algorithm is developed, namely progressive Pareto algorithm based on step-size (PPAS). To verify the performance of PPAS, it is compared against other well-known algorithms, including NSGA-II, MOEA/D, NNIA, RIPG, MMOIG and MNNIA. Finally, the effectiveness of the joint scheduling mode is demonstrated by comparing it with the separate optimisation mode of spare parts production and workforce allocation. Highlights Analyse the joint scheduling of spare parts production and service engineers Construct a bi-objective optimisation model Develop a progressive Pareto algorithm based on step-size Verify the superiority of the proposed algorithm and joint scheduling mode [ABSTRACT FROM AUTHOR]

The previous studies on service resource scheduling for maintenance, repair and operation (MRO) ignore the diverse service processes from different complex equipment and the coordination of task scheduling and resource allocation, which is less realistic when multiple tasks exist. In this work, we propose an integrated scheduling model of distributed service resources for on-site MRO, which simultaneously considers different service processes, service teams and material resources. The MRO service process is decomposed into multiple subtasks with hierarchical relationships (dependency and independency). Within the duration of the subtask, all multi-skill technicians in service team stay together and material resources are delivered from service providers. Resource allocation and task scheduling are integrated to minimise the makespan, the excessive human resources and the cost performance index of material resources. Further, we introduce six classic multi-objective evolutionary algorithms (MOEAs) to solve the scheduling problem, in which a novel and practical encoding method mixed with integers and decimals is developed. The design-of-experiment (DOE) method is used to determine the optimal combination of crucial parameters. Finally, 20 benchmark instances of multiple MRO tasks are tested. Experiment results show MOEA/D-DU could obtain higher quality scheduling solutions with relatively low computational costs in the integrated scheduling model. [ABSTRACT FROM AUTHOR]

Perovskite solar cells (PSCs) have garnered significant attention in the photovoltaic field owing to their exceptional photoelectric properties, including high light absorption, extensive carrier diffusion distance, and an adjustable band gap. Temperature is a crucial factor influencing both the preparation and performance of perovskite solar cells. The annealing temperature exerts a pronounced impact on the device structure, while the operational temperature influences carrier transport, perovskite band gap, and interface properties. This paper provides a comprehensive review of the influence of varied annealing temperatures on the hole transport layer, electron transport layer, and perovskite layer. Additionally, we present an overview of innovative annealing methods applied to perovskite materials. The effects of diverse working temperatures on the overall performance of perovskite cells are thoroughly examined and discussed in this review. In the end, different temperature conditions under ISOS testing conditions are summarized. [ABSTRACT FROM AUTHOR]

The friction between a molybdenum disulphide (MoS2) nanoflake and a MoS2 substrate was analyzed using a modified Tomlinson model based on atomistic force fields. The calculations performed in the study suggest that large deformations in the substrate can induce a dramatic decrease in the friction between the nanoflake and the substrate to produce the so-called superlubricity. The coefficient of friction decreases by 1–4 orders of magnitude when a high strain exceeding 0.1 is applied. This friction reduction is strongly anisotropic. For example, the reduction is most pronounced in the compressive regime when the nanoflake slides along the zigzag crystalline direction of the substrate. In other sliding directions, the coefficient of friction will reduce to its lowest value either when a high tensile strain is applied along the zigzag direction or when a high compressive strain is applied along the armchair direction. This anisotropy is correlated with the atomic configurations of MoS2. [ABSTRACT FROM AUTHOR]

Due to the scattering and attenuation of light into the water, the underwater image usually appears with color distortion, blurred details, and low contrast. To address these problems, a novel two-stage underwater image convolutional neural network (CNN) based on structure decomposition (UWCNN-SD) for underwater image enhancement is proposed by considering the characteristics of underwater imaging. Specifically, the raw underwater image is decomposed into high-frequency and low-frequency based on theoretical analysis of the underwater imaging. Then, a two-stage underwater enhancement network including a preliminary enhancement network and a refinement network is proposed. In the first stage, the preliminary enhancement network, which contains the high-frequency and the low-frequency enhancement networks, is proposed. The high-frequency part is enhanced directly by a deep learning network, and the low-frequency enhancement network is based on the underwater imaging, which is integrated transmission map and background light into joint component map. In the second stage, the refinement network is designed to further optimize the color of the underwater image by considering complexity of underwater imaging. The experimental results of synthetic and real-world underwater images/videos demonstrate that the proposed UWCNN-SD method can perform color correction and enhancement on different types of underwater images. The ablation study verifies the effectiveness of each component, and application tests further illustrate that the proposed UWCNN-SD method can obtain underwater images with higher visual quality. The trained model is available at: https://github.com/wushengcong/UWCNN-SD. [ABSTRACT FROM AUTHOR]

In this paper, a multi-exposure image fusion (MEF) method is proposed based on tensor decomposition and saliency model. The main innovation of the proposed method is to explore a tensor domain for MEF and define the fusion rules based on tensor feature of higher order singular value decomposition (HOSVD) and saliency. Specifically, RGB images are converted to YCbCr images to maintain the stability of color information. For luminance channels, luminance patches of luminance images are constructed 3-order sub-tensors, and HOSVD is used to extract features of sub-tensors. Then, the sum of absolute coefficients (SAC) of weight coefficients are defined. Meanwhile, considering the impact of saliency on visual perception, visual saliency maps (VSMs) is used to evaluate luminance patches quality and guide the fusion rules to define the rule of fusion. For chrominance channels, VSMs of the chrominance channels is used to define fused rule. The experimental results show that the fused image with more texture details and saturated color is successfully generated by proposed method. [ABSTRACT FROM AUTHOR]