In-situ alloying for adjusting the composition of alloys is a promising approach utilizing pre-mixed powders in laser powder bed fusion (LPBF). However, inhomogeneous composition has always hindered the application of this approach. In this study, the Ni51.8 Ti48.2 at.% alloys via in-situ alloying exposed severe cracking, due to inhomogeneous composition and inappropriate heat accumulation. To overcome these difficulties, we optimized the process parameters between volumetric energy density (VED) and layer thickness ( t ) by adjusting the scanning speed ( v ) and fabricated the crack-free, homogeneous, and dense NiTi alloys, thereby proposing a novel in-situ alloying strategy (VED -t ). Computational fluid dynamics (CFD) results demonstrate that the synergistic effects of VED and t significantly extend the melt pool lifespan and change the energy distribution of the melt pool, thus achieving compositional homogenization and porosity minimization. The strategy can also regulate the cracking tendency and crystallographic orientation by changing the melt pool type (connection, keyhole, and flat). The alloys with a B2 matrix possess a strong [001] orientation along the building direction and thus exhibit good superelasticity and elastocaloric cooling under compressive loading. These findings provide a novel approach for printing brittle alloys and drive the adoption of the in-situ alloying strategy of LPBF. (c) 2026 Published by Elsevier Ltd on behalf of The editorial office of Journal of Materials Science & Technology.
Cross-domain recommendation (CDR) offers an effective way to alleviate the cold-start problem, but most existing methods still model cross-domain preference transfer at the level of individual users. This point-wise paradigm relies heavily on overlapping users and struggles to capture the higher-order relational patterns underlying user interests across domains, resulting in limited performance when overlap is scarce. Meanwhile, representing items solely with ID embeddings ignores rich multimodal content, further constraining transferable preference modeling. In this work, we propose Multimodal Group-Level Relational Preference Modeling for Cross-Domain Recommendation, a framework that reformulates the transferable unit from direct user-to-user embedding mappings to user-to-key-user relational signatures, where overlapping users provide supervision and non-overlapping users serve as relational anchors. This design captures more stable and transferable cross-domain interest structures, yielding consistently improved performance. Concretely, we employ a multimodal large language model to extract item representations from textual and visual content, and further adopt a temporal attention pooling encoder to integrate users’ historical interactions with multimodal item semantics for constructing multimodal user representations. Based on these enriched representations, we develop a group-level relation learning module that models relational dependencies between each overlapping user and a domain-specific key user set selected from the non-overlapping ones, thereby enabling group-level preference transfer across domains. We further introduce an adversarial alignment strategy to reduce cross-domain representation discrepancies and enhance generalization. Extensive experiments on real-world datasets demonstrate that our method consistently outperforms state-of-the-art baselines.
For k-out-of-n: G multicomponent redundant systems with wide applicability, this paper develops a reliability modeling and assessment framework based on a stress-strength dependent model. To this end, both stress and strength are assumed to follow two-parameter Weibull distributions with arbitrary scale and shape parameters, and their dependence structure is modeled based on a mixed copula function. Under identical generalized progressive hybrid censoring (GPHC) schemes for stress and strength in life tests, three estimation methods are employed to infer the model parameters and system reliability: the two-step maximum likelihood estimation (MLE), the component-wise Metropolis-Hastings (MH) algorithm, and the proposed two-stage modified approximate Bayesian computation with sequential Monte Carlo (TMABC-SMC) algorithm. To address the difficulty of directly deriving interval estimates from two-step MLE and TMABC-SMC methods, a bootstrap method with conditional imputation is introduced. Simulation results demonstrate that the component-wise MH algorithm yields more accurate estimates, whereas the TMABC-SMC algorithm exhibits higher computational efficiency. Finally, the mentioned model and the developed methods are applied to a real data set to illustrate their practical effectiveness.
The toughness of carbide-free bainitic steel is primarily governed by retained austenite and high-angle grain boundaries (HAGBs). Compared with retained austenite, the role of HAGBs during plastic deformation of bainitic steel is complex and remains insufficiently understood. The present study investigated the formation of different HAGBs. By analyzing the deformation behavior of grains adjacent to various HAGB types, their influence on crack nucleation and the underlying mechanisms affecting the ductility and toughness of bainite were examined. The strategy of increasing the population of prior austenite grain boundaries was employed to modify the bainite nucleation and growth, thereby adjusting the relative fractions of different HAGB types in the resulting microstructure. HAGBs were classified using the Kurdjumov-Sachs relationship, together with assessment of the influence of the prior austenite grain size, to reveal the mechanisms controlling HAGB type and distribution in bainitic steel. In-situ tensile testing was used to identify geometrically necessary dislocation accumulation sites, electron backscatter diffraction and transmission electron microscope were used to characterize the local crystallography, and the Kurdjumov-Sachs relationship was applied to evaluate the deformation behavior across different HAGBs. The study revealed that deformation compatibility across a HAGB was governed by the symmetry of the crystallographic relationship between adjacent grains, with preferential deformation along parallel slip systems at 60 degrees<111> boundaries, leading to strain concentration at non-60 degrees<111> boundaries. Refining 60 degrees<111> variant pairs dispersed this strain by increasing accommodation sites, reducing dislocation accumulation at critical boundaries, and homogenizing the dislocation distribution, thereby suppressing crack initiation and enhancing ductility and toughness.
Ammonia–diesel direct-injection represents a promising low-carbon combustion strategy, yet the spray impingement generated substantially modifies mixing and combustion, with the fundamental mechanisms of flame development remaining unclear. In this study, the mixing and combustion characteristics of impinging ammonia-diesel sprays were investigated within a constant-volume chamber under high-temperature and high-pressure conditions. A combination of optical diagnostics and computational fluid dynamics simulations was employed to analyze the effects of injection sequencing on flame evolution. The findings indicate that diesel injection timing dominates combustion phasing. However, despite comparable turbulence intensities across different injection modes, the diesel first (DA) mode exhibits significantly enhanced flame development relative to the ammonia first (AD) mode. Further investigation reveals that this disparity is not attributable to turbulence intensity itself, but rather to the temporal alignment between turbulence generation and ignition kernel development. In the DA mode, favorable values of Damköhler number (Da) and Karlovitz number (Ka) during early ignition facilitate flame propagation, whereas in the AD mode, reduced Da and elevated Ka shift the flame toward a broken reaction regime, thereby suppressing its development. In addition, spray impingement in the DA mode aids in redistribution of excessively rich fuel into flammable equivalence ratio ranges, further enhancing combustion. Finally, flame sustainability is governed by diesel injection duration rather than total fuel quantity. Continuous diesel supply is required to maintain stable combustion, while ammonia alone fails to sustain flame propagation under the tested conditions. These results offer valuable insight into turbulence-chemistry interaction and provide guidance for optimizing injection strategies in engines.
