Synergistic Effects of Solid and Solvent Additives on Film Morphology Enable Binary Organic Solar Cells with Efficiency of Over 19%

Regulating the film morphology features of the photoactive layer is critically important for developing high-performance organic solar cells (OSCs). Adding solvent or solid additives is widely used to realize fine-tuned film morphology. However, most high-performance OSCs are processed only using single component additive, either solvent additive or solid additive. Herein, two structurally similar analogs of 1-benzothiophene (BT) and benzo[1,2-b:4,5-b']dithiophene (BDT) are applied as volatilizable solid additives and are used with the well-known solvent additive 1-chloronaphthalene (CN), respectively. Comprehensive morphology analysis revealed that the addition of BT with better volatilization can promote the formation of stronger molecular packing and desirable phase separation, resulting in higher charge mobility and more efficient charge separation. However, the insufficient volatilization of BDT caused excessive aggregation, leading to severe recombination. Consequently, the PMZ-10:Y6 based binary OSCs treated with the hybrid additives of CN and BT delivered a notable efficiency of 19.03%, which is one of the best values of the Y6-based binary devices reported so far. Overall, this work highlights the importance of hybrid additive strategy and the reasonable combination of solid and solvent additives in further advancing the development of OSCs field

An improved method to predict man-made slope failure using machine learning tools

Landslide hazards associated with man-made slopes are increasing due to ageing and extreme weather conditions under a changing climate. To effectively mitigate landslide risks, the implementation of regional landslide early warning systems is desirable, albeit challenging, if not impossible, due to the scarcity of reliable landslide data and suitable predictive tools. In this paper, a thorough analysis has been conducted on reasonably reliable and substantial amounts of historical rainfall data, slope features, and landslide inventory of man-made slope failures in Hong Kong. Four different machine learning methods, namely logistic regression (LR), decision tree (DT), random forest (RF), and extreme gradient boosting (XGBoost), have been employed. The predicted number of landslides from the machine learning methods is compared with the predictions made by the current Landslip Warning System in Hong Kong. The effects of rainfall parameters and slope features on model performance are also investigated. The analysed results show that dynamic rainfall conditions are identified as the most influential factors for predicting man-made slope landslide. A combination of 1 and 12 h maximal rolling rainfall (MRR) demonstrates superior performance compared to relying solely on the 24 h MRR. Therefore, this combination is recommended for predicting man-made slope failures in Hong Kong. © 2025 The Author(s)

Improving the Urban Boundary Layer Wind Speed by Coupling the TKE-ACM2 PBL Scheme with the Building Effect Parameterization Model

Realistically representing the vertical turbulent transport of surface layer fluxes dealt with by the planetary boundary layer (PBL) scheme is of paramount importance in a numerical weather forecasting model. Further complexity arises due to the presence of heterogeneous surface obstacles whose height can be comparable to the model's vertical resolution, which poses a challenge in improving and revisiting the PBL scheme. In this presentation, we derive the numerical method to couple one of the recently validated turbulent kinetic energy (TKE)-based non-local PBL schemes, namely the TKE-ACM2 scheme, with the commonly used multi-layer Building Effect Parameterization (BEP) model in WRF. The behavior of TKE-ACM2+BEP is first examined under idealized convective atmospheric conditions where a simplified staggered urban morphology is prescribed. Its performance is benchmarked against the state-of-the-art large-eddy simulation by PALM and also compared with the operational PBL scheme Boulac+BEP. The idealized simulation results reveal that TKE-ACM2+BEP exhibits superiority in simulating the potential temperature and wind speed profiles compared to Boulac+BEP, corroborating its better non-local treatment of the momentum fluxes near the roughness sublayer. Furthermore, we apply the coupled model to the Pearl River Delta region in South China, where a few extensively urbanized mega-cities exist. The one-month high-resolution wind speed LiDAR observations indicate that TKE-ACM2+BEP provides a more reasonable reproduction of wind speed profiles in the upper surface layer compared to the Bulk methods (i.e., without urban canopy model) by reducing the overestimation at the urban LiDAR site. In addition, the 10-m wind speeds (U10) are compared with surface stations aggregated based on the Local Climate Zone classification. The results suggest that the BEP model can improve the performance of the TKE-ACM2 PBL scheme at low- to moderate-building grids, but may not be consistently better at high-building density grids as it overly reduces U10

VideoRepainter: Keyframe-Guided Creative Video Inpainting

Video inpainting, which aims to fill missing regions with visually coherent content, has emerged as a crucial technique for editing and virtual tour applications. While existing approaches achieve either visual consistency or text-guided generation, they often struggle to balance between coherence and creative diversity. In this work, we introduce VideoRepainter, a two-stage framework that first allows users to inpaint a keyframe using established image-level techniques, and then propagates the corresponding change to other frames. Our approach can leverage state-of-the-art image diffusion models for keyframe manipulation, thereby easing the burden of the video-inpainting process. To this end, we integrate an image-to-video model with a symmetric condition mechanism to address ambiguity caused by direct mask downsampling. We further explore efficient strategies for mask synthesis and parameter optimization to reduce costs in data processing and model training. Evaluations demonstrate our method achieves superior results in both visual fidelity and content diversity compared to existing approaches, providing a practical solution for high-quality video editing and creation

Numerical Unique Ergodicity of Monotone SDEs Driven by Nondegenerate Multiplicative Noise

We first establish the unique ergodicity of the stochastic theta method (STM) with θ∈[1/2,1] for monotone SODEs, without growth restriction on the coefficients, driven by nondegenerate multiplicative noise. The main ingredient of the arguments lies in constructing new Lyapunov functions involving the coefficients, the stepsize, and θ and deriving a minorization condition for the STM. We then generalize the arguments to the Galerkin-based full discretizations for a class of monotone SPDEs driven by infinite-dimensional nondegenerate multiplicative trace-class noise. Applying these results to the stochastic Allen–Cahn equation indicates that its Galerkin-based full discretizations are uniquely ergodic for any interface thickness. Numerical experiments verify our theoretical results

High-temperature N ion implantation for performance-enhanced current-blocking layers in β-Ga₂O₃

This work reveals the significant advantages of high-temperature nitrogen (N) ion implantation for fabricating current-blocking layers (CBLs) in β-Ga2O3. A comparative investigation on the structural and electrical properties of N-implanted β-Ga2O3 was conducted under different implantation temperatures and post-implantation annealing (PIA) conditions. The results showed that the high-temperature implantation (HTI) at 500 °C, compared to the room-temperature implantation (RTI), introduced fewer structural defects and less lattice distortion to β-Ga2O3. The HTI-formed CBL demonstrated a far superior current-blocking capability than those formed by the RTI with/without a PIA, in terms of a much lower and more stable leakage current and a significantly enhanced breakdown voltage. Additionally, lateral MOSFETs fabricated with the HTI isolation exhibited a three orders of magnitude lower off-state leakage current while maintaining excellent on-state performance, compared to those using the isolation formed by RTI with PIA. These findings indicate that the in situ dynamic annealing effect of HTI effectively reduces implantation-induced damage, enhances impurity activation, and improves the overall performance of the N-implanted CBLs in β-Ga2O3. © 2025 Author(s)

An efficient three-phase interface reconstruction algorithm for two-dimensional VOF method

In this work, we propose an efficient three-phase interface reconstruction algorithm for two-dimensional Volume-of-Fluid (VOF) method in regular Cartesian mesh, which includes new tagging, separation, and triple-point optimization strategies. The proposed Dynamic Point (DP) algorithm is material-order-independent and designed to address the interface reconstruction issue around three-phase cells with both triple point and layered topologies, enabling a quick convergence speed owing to the tailored feedback design in the localization procedure. A special strategy is applied in the case of layered topology to ensure the uniformity of the methodology. When utilized, the algorithm is hybridized with the Piecewise Linear Interface Calculation (PLIC) algorithm to further increase the efficiency and robustness, especially in the two-phase cells unaffected by the three-phase junction. With some symmetrically designed functions in the DP algorithm and the conditional inheriting of the intersections from neighboring cells in the hybrid strategy, better interface connectivity across the cell boundaries is attained. Static cases have demonstrated that the present DP algorithm is able to reconstruct the interface in and around the three-phase cells with high fidelity. The T- and Y-shape configurations are clearly captured with good connectivity, regardless of the in-cell position of the triple point. The three-phase layered topology can also be accurately recovered by the activation of the special strategy. Advection cases have shown a significant increase in the computational efficiency and an obvious improvement in the reconstruction of triple-point configurations during the evolution process, especially in the reversed vortex test