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Understanding the formation of solidified microstructures adjacent to the fusion boundary of a melt pool can provide valuable insights for optimizing process parameters and achieving the desired microstructure in directed energy deposition (DED). However, existing analytical models fail to consider internal and external factors, particularly the solute concentration and scan speed, leading to low prediction accuracy of the solidified microstructure. A vc model of grain growth rate is developed based on the continuous growth restriction factor QC, that considers the coupling effect of both the internal factors and external factors. QC can also be used to describe the evolution of the growth restriction factor Q along the solidification path of liquid metal within the melt pool. The vc model can accurately predict variations in the rate of grain growth and evaluate the influence of solute concentration and scan speed on the Planar to Cellular Transition (PCT) of the Solid/Liquid interface and grain size. The QC value increases with the rise of solute concentration and scan speed, resulting in further growth resistance decreasing the vc value, thereby permitting secondary embryos to nucleate only after the S/L interface moves a short distance. This study fills the gap left by the inability of Q to explain the influence of solutes on the microstructure during DED, and presents a novel approach for analyzing the formation mechanism of solidified microstructure adjacent to the fusion boundary of the melt pool.

Here we propose to employ wire-arc directed energy deposition (WA-DED) to tune the microstructure and the mechanical property of Mg-Al-Si alloys, on the basis of its sub-rapid solidification effect. According to finite element analysis, WA-DED shows higher cooling rate than conventional casting, reaching 598.3 K/s for Mg-Al-Si alloy, and the lower heat input, the larger cooling rate of WA-DED. Significant microstructure refinement is thus achieved, with reduced grain size and Mg2Si particle diameter. The transition from hypereutectic to fully eutectic microstructure is triggered by reducing the heat input. Compared with the as-cast alloy, WA-DED alloys demonstrate higher ultimate tensile strengths (UTS) at both room- and high-temperature (150 ℃) properties, increasing by 50.1% and 30.3%, respectively. The superior strength-ductility synergy for Mg-Al-Si alloys results from the microstructure tuning via sub-rapid solidification of WA-DED.

The wire arc additive manufacturing (WAAM) process often results in geometric inaccuracies in the produced struts, highlighting the need for in-situ monitoring. Industrial cameras struggle to capture accurate images due to interference from arc light and metal radiation. This study introduces a real-time visual reconstruction method that leverages regions of interest (ROI) to enhance profile accuracy. Initially, the melt pool is analyzed and segmented from a series of frames to establish an initial strut profile. This profile then serves as the ROI for segmenting the solidified weld bead regions, yielding a more precise strut profile. Comparative analysis shows that the proposed method achieves a high Intersection Over Union (IOU) score of 0.911 and an Average Symmetric Surface Distance (ASD) error of 0.355 mm, demonstrating both accuracy and robustness. Additionally, the inclination angle and diameter are extracted from the reconstructed profiles.

Here, wire-arc additive manufacturing (WAAM) is employed to fabricate Al–Ce–Mg heat-resistant aluminum alloy, considering its capability to manufacture large complex structures more efficiently. Large-sized faceted Al11Ce3 intermetallic compounds are formed in the as-cast alloy with a hypereutectic microstructure. The microstructure is transformed to a eutectic microstructure by non-equilibrium solidification of WAAM, consisting lamellar α-Al/A111Ce3 eutectics. The WAAM alloy shows enhanced mechanical strength and ductility at 200 °C, compared with the as-cast alloy. The significant improvements of ultimate tensile strength and elongation for the WAAM alloy are correlated with its higher strain hardening rate, along with the transition from cleavage fracture to dimple fracture. The cracking of All1Ce3 particles occurs preferentially during the elastic deformation stage, as revealed by in-situ testing, and the strain hardening capability of the as-cast alloy is reduced. Pore defects, 0.15 % in volume fraction, are produced via WAAM processing, and the plastic deformation promotes the pore growth and mergence, increases the pore volume fraction, and decreases the pore sphericity. Our results demonstrate that WAAM is strongly attractive for the fabrication of Al–Ce–Mg alloys, due to the enhanced high-temperature strength-ductility synergy.

Wire-arc additive manufacturing (WAAM) is favored by the industry for its high material utilization rate and low cost. However, wire-arc additive manufacturing of lattice structures faces problems with forming accuracy such as broken rod and surface morphology defects, which cannot meet the industrial demand. This article innovatively combines the melt pool stress theory with visual perception algorithms to visually study the force balance of the near-suspended melt pool to predict the state of the melt pool. First, the method for melt pool segmentation was studied. The results show that the optimized U-net achieved high accuracy in melt pool segmentation tasks, with accuracies of 98.18%, MIOU 96.64%, and Recall 98.34%. In addition, a method for estimating melt pool force balance and predicting normal, sagging, and collapsing states of the melt pool is proposed. By combining experimental testing with computer vision technology, an analysis of the force balance of the melt pool during the inclined rod forming process was conducted, showing a prediction rate as high as 90% for the testing set. By using this method, monitoring and predicting the state of the melt pool is achieved, preemptively avoiding issues of broken rods during the printing process. This approach can effectively assist in adjusting process parameters and improving welding quality. The application of this method will further promote the development of intelligent unmanned WAAM and provide some references for the development of artificial intelligence monitoring systems in the manufacturing field.

It remains challenging to achieve attractive mechanical strength and ductility in commercial 7xxx alloys fabricated by wire-arc additive manufacturing (WAAM). Here, we combine WAAM processing with solution and artificial aging treatments to functionalise their inherent age-hardening capabilities via microstructure controlling. The as-deposit WAAM 7055 alloy shows a heterogeneous microstructure with a bimodal grain size distribution, and the primary metallurgical defects are spherical gas pores with an inter-layer distribution. Upon the optimised T6 temper (470°C/2 h for solution treatment and 120°C/65 h for artificial aging), nano-sized platelike η’ precipitates are generated, and the tensile strength boosts from ∼226 MPa to ∼562 MPa. Evident yielding with a uniform plastic deformation is also mediated by the T6 temper, with the yield strength > 500 MPa and the fracture strain > 5%, which is comparable to conventional wrought 7xxx alloys. This work provides insight into the microstructure tuning for commercial 7xxx alloys via WAAM for achieving excellent mechanical properties.

Abstract For hypereutectic Nb-Si based alloys, primary Nb5Si3 phases typically grow in a faceted mode during equilibrium or near-equilibrium solidification, which damages the ductility and toughness. To address this issue, here we artificially manipulate the growth morphology of Nb5Si3 using electron beam surface melting (EBSM) and subsequent annealing treatments. Results show that such a non-equilibrium solidification pathway enables the transition from faceted growth to non-faceted dendritic growth of Nb5Si3, along with evident microstructure refinement, generation of metastable β-Nb5Si3 phases and elimination of chemical segregation. The transformation from β-Nb5Si3 to α-Nb5Si3 and Nb solid solution (Nbss) particles is triggered by the annealing treatment at 1450 °C for 5 h. Also, we find the annealing-mediated formation of inherited Nb5Si3 dendrites that maintain the dendritic morphology of the original as-solidified β-Nb5Si3 dendrites. This work thus provides a feasible routine to obtain thermally stable and refined α-Nb5Si3 dendrites in hypereutectic Nb-Si based alloys.

The sine and cosine algorithm is a new simple and effective population optimization method proposed in recent years that has been studied in many works of literature. Based on the basic principle of the sine and cosine algorithm, this paper fully studies the main parameters affecting the performance of the sine and cosine algorithm, integrates the reverse learning algorithm, adds an elite opposition solution and forms the hybrid sine and cosine algorithm (hybrid SCA). Combined with the fuzzy k-nearest neighbor method and the hybrid SCA, this paper numerically simulates two-class datasets and multi-class datasets, obtains a large number of numerical results and analyzes the results. The hybrid SCA FKNN proposed in this paper has achieved good accuracy in classification and prediction results under 10 different types of data sets. Compared with SCA FKNN, LSCA FKNN, BA FKNN, PSO FKNN and SSA FKNN, the prediction accuracy is significantly improved. In the Wilcoxon signed rank test with SCA FKNN and LSCA FKNN, the zero hypothesis (significance level 0.05) is rejected and the two classifiers have a significantly different accuracy.

One of the main problems in representing information in the form of nonsystematic logic is the lack of flexibility, which leads to potential overfitting. Although nonsystematic logic improves the representation of the conventional k Satisfiability, the formulations of the first, second, and third-order logical structures are very predictable. This paper proposed a novel higher-order logical structure, named G-Type Random k Satisfiability, by capitalizing the new random feature of the first, second, and third-order clauses. The proposed logic was implemented into the Discrete Hopfield Neural Network as a symbolic logical rule. The proposed logic in Discrete Hopfield Neural Networks was evaluated using different parameter settings, such as different orders of clauses, different proportions between positive and negative literals, relaxation, and differing numbers of learning trials. Each evaluation utilized various performance metrics, such as learning error, testing error, weight error, energy analysis, and similarity analysis. In addition, the flexibility of the proposed logic was compared with current state-of-the-art logic rules. Based on the simulation, the proposed logic was reported to be more flexible, and produced higher solution diversity.

Recently, new variants of non-systematic satisfiability logic were proposed to govern Discrete Hopfield Neural Network. This new variant of satisfiability logical rule will provide flexibility and enhance the diversity of the neuron states in the Discrete Hopfield Neural Network. However, there is no systematic method to control and optimize the logical structure of non-systematic satisfiability. Additionally, the role of negative literals was neglected, reducing the expressivity of the information that the logical structure holds. This study proposed an additional optimization layer of Discrete Hopfield Neural Network called the logic phase that controls the distribution of negative literals in the logical structure. Hence, a new variant of non-systematic satisfiability named Weighted Random 2 Satisfiability was formulated. Thus, a proposed searching technique called the binary Artificial Bee Colony algorithm will ensure the correct distribution of the negative literals. It is worth mentioning that the binary Artificial Bee Colony has flexible and less free parameters where the modifications tackled on the objective function. Specifically, this study utilizes a binary Artificial Bee Colony algorithm by modifying the updating rule equation by using not and (NAND) logic gate operator. The performance of the binary Artificial Bee Colony will be compared with other variants of binary Artificial Bee Colony algorithms of different logic gate operators and conventional binary algorithms such as the Particle Swarm Optimization, Exhaustive Search, and Genetic Algorithm. The experimental results and comparison show that the proposed algorithm is compatible in finding the correct logical structure according to the initiate ratio of negative literal.

The microstructure and room-temperature mechanical properties of directionally solidified and heat-treated Nb‑16Si‑23Ti‑4Cr‑2Al‑2Hf‑0/0.3/0.5Sc (at.%) alloys were investigated. All alloys consisted of Nb-based solid solution (Nbss), α‑Nb5Si3 and γ‑Nb5Si3 with preferred 〈001〉 orientation for the first two phases, and Sc was enriched in γ‑Nb5Si3 phase. Sc-added alloys showed a more continuous Nbss matrix in which the finer Nb5Si3 phase distributed uniformly. The volume fraction of both α‑Nb5Si3 and γ‑Nb5Si3 phase was decreased by Sc addition. Sc alloying reduced the Young's modulus and nano-hardness of Nbss phase. 0.50 at.% Sc addition enhanced the fracture toughness and tensile strength from 9.88 MPa m1/2 and 430.3 MPa to 25.95 MPa m1/2 and 1119.7 MPa. The improvement in fracture toughness was due to the better deformability of Nbss phase. The high tensile strength was attributed to the dispersed and refined Nb5Si3 phase, which was not degraded by the increased Nbss volume fraction since dislocations were not open within most Nbss phase. Besides, the strong interface cohesion was preferable for the strength of Sc-added alloys. Keywords: Microstructure, Growth orientation, Young's modulus, Nano-hardness, Fracture toughness, Tensile strength

Our previous data suggested that IL-17A contributes to the inhibition of Th1 cell function in the gut. However, the underlying mechanisms remain unclear. Here we demonstrate that IL-17A signaling in colonic epithelial cells (CECs) increases TNF-α-induced PI3K-AKT and ERK phosphorylation and inhibits TNF-α induced expression of IL-12P35 and of a Th1 cell chemokine, CXCL11 at mRNA level. In a co-culture system using HT-29 cells and PBMCs, IL-17A inhibited TNF-α-induced IL-12P35 expression by HT-29 cells and led to decreased expression of IFN-γ and T-bet by PBMCs. Finally, adoptive transfer of CECs from mice with Crohn's Disease (CD) led to an enhanced Th1 cell response and exacerbated colitis in CD mouse recipients. The pathogenic effect of CECs derived from CD mice was reversed by co-administration of recombinant IL-17A. Our data demonstrate a new IL-17A-mediated regulatory mechanism in CD. A better understanding of this pathway might shed new light on the pathogenesis of CD.

A coated polypyrrole modified carbon carrier material was prepared by low-temperature oxidation in situ polymerization, which improved the defects, such as impurities on the surface, low functionalization, and easy corrosion in a harsh electrochemical environment, of traditional carbon carriers. The modification of polypyrrole onto the traditional carbon carriers was confirmed using techniques, such as TEM, FTIR, XPS, and SEM. The results showed that when the amount of pyrrole was 0.4 mL, the mass and specific activity of Pt3Cu/C@PPy catalyst were 0.45 A mgPt-1 and 0.51 mA cmPt-2, respectively, which are 3.2 and 4.7 times higher than those of the JM Pt/C catalyst. Compared with the Pt3Cu/C catalyst without polypyrrole modification, the modified catalyst also exhibited higher catalytic activity, electrochemical durability, and higher battery power than the JM Pt/C catalyst. The coating of polypyrrole on the carbon carrier can protect the carbon carrier from corrosion, effectively disperse and anchor the metal particles, and enhance the interaction between the metal and the carrier, thereby improving the catalytic activity. [ABSTRACT FROM AUTHOR]