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Quasi-two-dimensional (quasi-2D) Ruddlesden–Popper (RP) perovskites such as BA 2 Cs n –1 Pb n Br 3 n +1 (BA = butylammonium, n  > 1) are promising emitters, but their electroluminescence performance is limited by a severe non-radiative recombination during the energy transfer process. Here, we make use of methanesulfonate (MeS) that can interact with the spacer BA cations via strong hydrogen bonding interaction to reconstruct the quasi-2D perovskite structure, which increases the energy acceptor-to-donor ratio and enhances the energy transfer in perovskite films, thus improving the light emission efficiency. MeS additives also lower the defect density in RP perovskites, which is due to the elimination of uncoordinated Pb 2+ by the electron-rich Lewis base MeS and the weakened adsorbate blocking effect. As a result, green light-emitting diodes fabricated using these quasi-2D RP perovskite films reach current efficiency of 63 cd A −1 and 20.5% external quantum efficiency, which are the best reported performance for devices based on quasi-2D perovskites so far. Owing to large exciton binding energy, quasi-2D perovskite is promising for light-emitting application, yet inhomogeneous phases distribution limits the potential. Here, the authors improve the performance by using MeS additive to regulate the phase distribution and to reduce defect density in the films.

The remaining useful life (RUL) and utilization strategy of an aero-engine are related to the flight safety of an aircraft, which directly affects the flight itself and the safety of the occupants. Aiming at the complexity of aero-engine condition monitoring data, an aero-engine predictive maintenance planning framework based on RUL prediction is proposed, which aims to analyze the engine RUL and design predictive maintenance strategies. First, a deep learning integrated model (Trans-LSTM), including Transformer and Long Short Memory Network Model (LSTM), is proposed. Second, Bayesian optimization is used to optimize the hyperparameters of the integrated model to further improve the accuracy of the predictive model. Based on the prediction data, an engine alarm threshold was designed. When the threshold is triggered during engine operation, a predictive maintenance task is applied. The optimal alarm threshold under the Trans-LSTM model is calculated by comparing the total flight cost and other indicators under different flight hours. Experimental results demonstrate that the data-driven predictive maintenance strategy can monitor engine status in real time, promptly identify potential failure risks, and prevent engines from operating in an unknown state. This effectively reduces the risk of sudden engine failures and significantly enhances flight safety compared to the periodic maintenance strategy. In addition, through the accurate prediction of the engine state and reasonable arrangement of maintenance tasks, it can effectively reduce the cost of using the engine and avoid the waste of manpower, material and financial resources caused by excessive maintenance. Moreover, it enhances engine task availability, prolongs the engine’s optimal operating period, better meets the actual needs of air transportation, and brings higher economic benefits and operational efficiency for airlines, thus showing great value and potential in practical application.

In the context of national fitness and ecological construction, urban water, as the core carrier of water sports, is increasingly being explored. Through empirical analysis of urban water bodies in Nanjing and Shanghai, the Spearman model and an XGBoost model, based on SHAP, are used to examine the correlation between the subjective perceptions of water-landscape images by various types of water-sports participants and objective evidence of urban water-landscape elements. The results show that amateurs prefer a high green-view index (>20%) + low water visibility (≤30%) + low sky visibility (≤30%) + shallow-water area (≤1.5 m), which enhances their satisfaction with the leisure experience; progressors prefer a moderate green-view index (10–20%) + moderate water visibility (30–40%) + moderate sky visibility (30–40%) + medium water-depth area (1.5–2.5 m), which helps them achieve better perception of skill improvement and training effectiveness; professionals prefer high water visibility (≥40%) + high sky visibility (≥40%) + low green-view index (≤10%) + deep-water area (≥2.5 m), which meets their training requirements for professional competitions. This study provides a scientific basis for urban water landscape planning and design in order to create urban water sports spaces that respond to the needs of various types of water sports participants.

Deep-sea submersibles, often featuring a symmetrical design for hydrodynamic stability, operate as safety-critical systems in extreme environments, where the tight dynamic coupling between subsystems like hydraulics and propulsion creates complex failure modes that are challenging to diagnose. A localized fault in one system can propagate, inducing anomalous behavior in another and confounding conventional single-system monitoring approaches. This paper introduces a novel unsupervised anomaly detection framework, the Dual-Stream Coupled Autoencoder (DSC-AE), designed specifically to address this cross-system fault challenge. Our approach leverages a dual-encoder, single-decoder architecture that explicitly models the normal coupling relationship between the hydraulic and propulsion systems by forcing them into a shared latent representation. This architectural design establishes a holistic and accurate baseline of healthy, system-wide operation. Any deviation from this learned coupling manifold is robustly identified as an anomaly. We validate our model using real-world operational data from the deep-sea submersible, including curated test cases of intra-system and inter-system faults. Furthermore, we demonstrate that the proposed framework offers crucial diagnostic interpretability; by analyzing the model’s reconstruction error heatmaps, it is possible to trace fault origins and their subsequent propagation pathways, providing intuitive and actionable decision support for submersible operation and maintenance. This powerful diagnostic capability is substantiated by superior quantitative performance, where the DSC-AE significantly outperforms baseline methods in detecting propagated faults, achieving higher accuracy and recall, among other performance metrics.

Quantum dots (QDs) of formamidinium lead triiodide (FAPbI3) perovskite hold great potential, outperforming their inorganic counterparts in terms of phase stability and carrier lifetime, for high‐performance solar cells. However, the highly dynamic nature of FAPbI3 QDs, which mainly originates from the proton exchange between oleic acid and oleylamine (OAm) surface ligands, is a key hurdle that impedes the fabrication of high‐efficiency solar cells. To tackle such an issue, here, protonated‐OAm in situ to strengthen the ligand binding at the surface of FAPbI3 QDs, which can effectively suppress the defect formation during QD synthesis and purification processes is selectively introduced. In addition, by forming a halide‐rich surface environment, the ligand density in a broader range for FAPbI3 QDs without compromising their structural integrity, which significantly improves their optoelectronic properties can be modulated. As a result, the power conversion efficiency of FAPbI3 QD solar cells (QDSCs) is enhanced from 7.4% to 13.8%, a record for FAPbI3 QDSCs. Furthermore, the suppressed proton exchange and reduced surface defects in FAPbI3 QDs also enhance the stability of QDSCs, which retain 80% of the initial efficiency upon exposure to ambient air for 3000 hours. An in situ surface ligand regulation strategy for deliberately controlling protonated‐oleylamine (OAm) dominated surface binding of formamidinium lead triiodide quantum dots (FAPbI3 QDs) is demonstrated. The QDs present reduced long‐chain insulating ligand density without compromising their structural integrity, leading to the corresponding QD solar cell a record power conversion efficiency of 13.8% for FAPbI3 QDSCs.

Deep space exploration, generally referring to the space exploration activities targeting the Moon and more distant extraterrestrial celestial bodies, stands as a critical indicator of a nation’s comprehensive capabilities and technological prowess [...]

This paper presents a novel third-order super-twisting-like integral sliding mode controller (3-ISMC) for trajectory tracking of nanopositioning applications. Different from traditional sliding mode control methods presenting with chattering problems, the proposed approach provides continuous control inputs, which brings much convenience for practical applications. Moreover, the fixed-time convergence of the proposed 3-ISMC is guaranteed independently of initial conditions. The estimation of the fixed convergence time and stability are derived based on the Lyapunov method. Simulation results demonstrate that the proposed controller exhibits chattering free and quick transient response performance for a piezoelectric nanopositioning system under model uncertainties and external disturbances.

Perovskite materials, as emerging semiconductors, have attracted significant attention for their exceptional optoelectronic properties, tunable bandgaps, ease of fabrication, and cost-effectiveness, making them promising candidates for next-generation optoelectronic devices. The all-inorganic perovskite Cs2AgBiBr6 distinguishes itself from other perovskite materials due to its remarkable optical absorption and emission properties, excellent stability, prolonged carrier recombination lifetime, and nontoxic characteristics. However, a deeper understanding of its unique luminescent properties and a further optimization of its structure and performance are still necessary. This study systematically investigates the optimization of Cs2AgBiBr6 double perovskite films through A-site Na+ doping. At an optimal Na+ doping concentration of 3.5% (Na0.07Cs1.93AgBiBr6), the film shows 1.4 times and 2.7 times enhancement in light absorption and photoluminescence intensity, compared to the undoped film. Low-temperature spectroscopy measurements indicate that Na0.07Cs1.93AgBiBr6 exhibits higher exciton binding energy and phonon energy. Based on Na0.07Cs1.93AgBiBr6, the photodetectors demonstrate significant performance improvements, with a high photocurrent response of 10−2 A, a photo-to-dark current ratio (PDCR) of 7.57 × 104, a responsivity (R) of 16.23 A/W, a detectivity (D*) of 2.92 × 1012 Jones, a linear dynamic range (LDR) of 98.75 dB, and a fast response time of 943 ms. This work provides a promising strategy for optimizing all-inorganic perovskite materials through doping and offers guidance for enhancing high-performance photodetectors.

The aim of this paper is to analyze dynamic characteristics and stability of magnetic sail-based planetary displaced orbits, and the feasibility of using a magnetic sail as an advanced propellantless control technology for formation flying around elliptic planetary displaced orbits (EPDOs). The thrust can be obtained from the momentum exchange between solar wind and an artificial magnetic field. First, the requirements of a magnetic sail for generating and maintaining a planetary circular displaced orbit is discussed including the value of attitude angles and characteristic acceleration. Based on different orbital periods, the circular displaced orbits are divided into three types and their linear stability is analyzed. For elliptical orbits, the conditions required to maintain an EPDO are investigated and the dynamical models of magnetic sail formation system are established. A finite time coordinated control algorithms relying on the protocols formulated on an undirected communication graph is proposed to achieve synchronized formation tracking rapidly while enhancing the robustness of formation system due to information interaction between spacecraft. Several numerical simulations are conducted to demonstrate that spacecraft formation can be effectively controlled by the proposed propellantless propulsion system.

The dysfunction of membraneless organelles (MLOs) has been implicated in tumorigenesis and progression by aberrant liquid-liquid phase separation (LLPS). However, the role of MLOs in the prognosis and tumor immune microenvironment (TIME) of colorectal cancer (CRC) remains unclear. We integrated transcriptomic data of MLO-related genes to identify distinct CRC subtypes and constructed a prognostic risk score termed MPRS. Then, we systematically demonstrated the characteristics of MPRS based on multi-omics analyses. We further assessed NRG1's LLPS possibility, prognostic significance, and its correlation with methylation through comprehensive analysis and experiment. A prognostic signature called MPRS associated with prognosis, tumor ecotypes, genomic alterations, TIME patterns, immunotherapy responses, chemotherapy sensitivity in CRC patients. NRG1, identified as the most important MPRS gene with high predicted LLPS propensity-was significantly downregulated in CRC tissues and correlated with prognosis. Promoter methylation was found to be a crucial mechanism underlying NRG1 downregulation, which could be rescued by 5-Aza-2-deoxycytidine (Aza) treatment. The qRT-PCR, IHC and Aza treatment were utilized for validation. Our integrated multi-omics analysis constructed the MPRS model to delineate CRC tumor ecology and identified NRG1 as a methylation biomarker with predicted phase-separation propensity, with potential therapeutic implications that warrant prospective validation.