Zhenhua Li

The thermal stability of additively manufactured aluminum alloys is often dictated by a complex interplay between high-temperature precipitation strengthening and grain- boundary-driven degradation. However, the presence of heterogeneous microstructures, composed of coarse- and fine-grained regions, introduces competing mechanisms that are rarely disentangled. Here, we report on two LPBF-processed TiC-modified Al-Mn-Mg-Sc-Zr alloys with distinct Sc/Zr contents and grain architectures, subjected to thermal exposure at 250-400 ℃ for up to 100 h. Our results establish a clear hierarchy of precipitate stability, wherein Al3(Sc,Zr) resists coarsening most effectively, followed by icosahedral quasicrystals, whereas Al6Mn and Al30Mg23 exhibit marked temperature sensitivity and anisotropic growth, particularly above 300 ℃. Critically, we uncover that the fine-equiaxed-grain-dominated alloy, despite its higher initial strength, accelerates grain-boundary-mediated coarsening of Al6Mn and Al30Mg23, leading to a paradoxical strength-ductility trade-off during prolonged thermal exposure, even though it retains yield strengths above 530 MPa after 100 h at 250-300 ℃. In contrast, the coarse-columnar-grain-dominated counterpart exhibits more sluggish microstructural degradation and superior ductility retention. These findings demonstrate that the long-term performance of these alloys is governed by a competition between stable nanoscale precipitation and grain-boundary-mediated phase evolution. Our work thus underscores that optimizing thermal stability requires not only enhancing the resistance to precipitate coarsening but also tailoring grain boundary architecture, a design criterion that extends beyond conventional alloy development for high-temperature applications.

To address the problems of poor machinability of dual-metal network composites and unclear material removal mechanisms, this paper fabricated 316L stainless steel porous networks by selective laser melting technology, and prepared 316L network-reinforced ZA8 composites via squeeze casting process. The microstructure and dry milling performance were investigated. The composites formed dense three-dimensional interpenetrating structures, and an Al-enriched interfacial layer containing the Al ₀ . ₉₈₃ Cr ₀ . ₀₁₇ intermetallic compound was identified at the interface. The cutting force fluctuation amplitude of the composites was larger than that of pure ZA8 alloy, with an optimal cutting speed of 75 m/min. The surface roughness of the composite first decreased then increased but that of the ZA8 alloy continuesd to decrease with the increase of cutting speed. The cutting force and surface roughness of the composite increased with the increase of feed rate and depth of cut and machining defects were mainly concentrated at the interface.

High-reflectivity metals (HRMs) have low absorption of near-infrared laser radiation and are prone to defects such as lack of fusion, balling, and pores during laser powder bed fusion (LPBF), making process stability and quality consistency difficult to ensure. Traditional trial-and-error experiments and purely numerical simulations involve long development cycles, high costs, and delayed feedback in process development, whereas machine learning provides new data-driven tools for parameter screening, process monitoring, and performance prediction. With the low absorptivity and high thermal conductivity of HRMs as the underlying physical basis, this review systematically summarizes the application progress of machine learning in process parameter optimization, process monitoring and quality assessment, and performance prediction. It further discusses the limitations of current studies in terms of data scale, cross-material generalization, physical consistency, and engineering validation, and proposes constructing standardized multimodal datasets, developing small-sample and transfer-learning strategies, and integrating physical information with interpretable models to support quality control and process optimization in HRMs-LPBF.

This study independently develops a software system with adaptive compatibility to the hardware platform. Based on this, wire arc additive manufacturing (WAAM) of 4043 aluminum alloy thin-walled components is conducted, and forming process parameters are optimized. According to the average melt width and residual height of single-pass single-layer deposits, the optimal parameters are determined as welding speed 8 mm/s and wire feeding speed 3.5 m/min. The optimized interlayer cooling time is set to 240 s for the bottom layer, 120 s for the middle layer, and 60 s for the top layer. Microstructural observations reveal banded fusion lines at adjacent layer interfaces, with denser interlayer regions featuring developed dendrites. Si phase granulation occurs in the upper region; the middle region has smaller grains dominated by heterogeneous grains, while the upper region consists mainly of columnar grains. Microhardness reaches a minimum of 74.7 HV in delamination zones and rises to 80.4 HV in interlayer regions, with fluctuations gradually weakening as layer thickness increases.

Different contents of WC particle‐reinforced 18Ni300 composites are prepared by selective laser melting method, and the tribological properties are comparatively studied before and after solution aging heat treatment. The results show that a part of WC particles are dissolved, and no obvious pore defects appear. With the increase of WC content, the microstructure gradually transforms from cellular and fine columnar α‐Fe martensite to γ‐Fe austenite. After solution aging heat treatment, the phase is transformed into acicular martensite. The grain size significantly decreases, and the Vickers hardness increases. The grain size decreases and the hardness increases with increasing WC contents. For the as‐built composite, the friction coefficient first decreases and then increases, and the wear rate first increases and then decreases with the increase of WC content. With WC content increasing, the wear rate first decreases and then increases. After heat treatment, the tribological properties are improved. The groove of the specimens before heat treatment is deep with large delaminated craters, and the wear mechanism is dominated by adhesive and abrasive wear. The grooves become shallower, and the adhesive trace becomes lighter after heat treatment. The wear mechanism is mainly adhesive wear and abrasive wear, accompanying with oxidative wear.