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The multi‐component strategy has proven effective in advancing the performance of organic photovoltaics (OPVs), enhancing photocurrent and fill factor through spectral complementarity and morphology optimization. However, the open‐circuit voltage (VOC) mechanism in multi‐component systems lacks systematic investigation. In this study, we explore the influence of alloy‐like phases on energy level distribution and energy loss mechanisms in multi‐component OPVs. Appropriate modulation of donor alloy‐like phases maintains the original intermolecular stacking, enhances component compatibility, reduces acceptor aggregation, and improves acceptor phase purity, mitigating non‐radiative recombination losses. Additionally, suitable alloy‐like phase modulation elevates charge transfer (CT) states, reducing the gap between CT and local exciton state, lowering reorganization energy, and alleviating radiative recombination loss below the bandgap. Through synergistic optimization (layer‐by‐layer method with solid additive), ternary devices based on Y6 acceptor achieve a notable 19.41% power conversion efficiency, offering new insights for the analysis of the energy loss of the multi‐component OPVs. [ABSTRACT FROM AUTHOR]

Battery characterization and prognosis are essential for analyzing underlying electrochemical mechanisms and ensuring safe operation, especially with the assistance of superior data‐driven artificial intelligence systems. This review provides a unique perspective on recent progress in data‐driven battery characterization and prognosis methods. First, recent informative image characterization and impedance spectrum as well as high‐throughput screening approaches on revealing battery electrochemical mechanisms at multiple scales are summarized. Thereafter, battery prognosis tasks and strategies are described, with the comparison of various physics‐informed modeling strategies. Considering unlocking mechanisms from tremendous battery data, the dominant role of physics‐informed interpretable learning in accelerating energy device development is presented. Finally, challenges and prospects on data‐driven characterization and prognosis are discussed toward accelerating energy device development with much‐enhanced electrochemical transparency and generalization. This review is hoped to supply new ideas and inspirations to the next‐generation battery development. [ABSTRACT FROM AUTHOR]

The edge detection method based on the magnetic gradient tensor data plays an important role in magnetic exploration because it is free from geomagnetic interference and contains more abundant information. This paper proposes a new anomaly edge detection method using the magnetic gradient tensor components. The model is established to compare with other methods, such as directional total horizontal derivative (THDz), analytical signal (AS), tilt angle, theta map, and so on, under conditions of vertical magnetization, oblique magnetization, and noise interference. Through the study of the anomaly distribution of the rectangular model, it is observed that the edge detection method proposed in this paper is nearly impervious to noise interference, exhibits strong anti-interference capabilities, delivers a high-quality boundary identification effect, and provides greater accuracy in anomaly edges with minimal error. When multiple anomalous bodies are present, the edge detection results are less susceptible to interference from each other, resulting in higher resolution. The efficiency of the algorithm is demonstrated by real magnetic data from some study areas in Jiangxi Province, China. The experimental results show that the proposed method is more precise and accurate than the total horizontal derivative, analytical signal, tilt angle, and theta map methods. [ABSTRACT FROM AUTHOR]

With uncertainty intensifying the international technological innovation environment, the innovation situation of Chinese manufacturing enterprises has been impacted. Based on 12,781 micro panel data in 2011–2020 of 2347 Chinese A-share manufacturing listed enterprises, this paper empirically analyzes the impact of innovation plight faced by enterprises on operational efficiency. The innovation plight in this article refers to the degree to which the actual innovation performance of enterprises has not reached the expected innovation performance or is introduced by an innovation gap, measured by the difference when actual innovation performance is lower than the expected innovation performance. The empirical results show that the innovation plight of manufacturing enterprises significantly inhibits operational efficiency by reducing their risk tolerance, development ability expectation, and profitability. After using a series of tests, such as the instrumental variable method, replacing the dependent variable, and changing the parameters for measuring the independent variable, the conclusion is still robust. In addition, the results illustrate that the inhibitory effect of innovation plight on operational efficiency is more obvious for non-state-owned enterprises, small and medium-sized enterprises, high-tech enterprises, and enterprises in the eastern region. Finally, we formulate some relevant management suggestions. [ABSTRACT FROM AUTHOR]

Machining special microstructures on the surface of silicon nitride ceramics helps improve their service performance. However, the high brittleness and low fracture toughness of silicon nitride ceramics make it extremely difficult to machine microstructures on their surface. In this study, a femtosecond laser is used to machine parallel grooved microstructures on the surface of silicon nitride ceramics. The effects of the laser polarization angle, laser single pulse energy, scanning line spacing, and laser scan numbers on the surface morphology and geometric characteristics of grooved microstructures are researched. It is found that a greater angle between the direction of the scanning path and laser polarization is helpful to obtain a smoother surface. As the single pulse energy increases, debris and irregular surface structures will emerge. Increasing the laser scan line spacing leads to clearer and more defined parallel grooved microstructures. The groove depth increases with the increase in the scan numbers. However, when a certain number of scans is reached, the depth will not increase further. This study serves as a valuable research foundation for the femtosecond laser processing of silicon nitride ceramic materials. [ABSTRACT FROM AUTHOR]

To effectively stimulate the activity of copper tailings to prepare cementitious materials with good performance, copper tailings were used as the main raw materials, water glass and NaOH were added as alkali initiators, and the response surface optimization method was used to carry out the optimization experiment of cementitious material ratio, and the influence of independent variables and their interaction on the compressive strength of 28 d was studied by analysis of variance and three-dimensional curved plot. XRD, SEM, FT-IR, TG-DTG, etc. were used to characterize the mineral composition, micromorphology and other characteristics of the sample. The results show that the optimal ratio obtained by optimization experiment is 50% sodium carbonate content, 1% sodium hydroxide content and 22 g/100 g water glass content, and the compressive strength of copper tailings cementitious material in 28 d is 30. 41 MPa. After 40 min of mechanical ball milling, sodium carbonate excites the activity of copper tailings to a better state under an appropriate alkaline environment, and a large number of C-S-H gels with high crystallinity and prismatic calcium vanadium and other hydration products are generated by hydration of copper tailings, which are connected with each other to form a network structure, so that the cementitious material maintains high strength performance. [ABSTRACT FROM AUTHOR]