To enhance the applicability of dual-phase high-entropy alloys (HEAs) like Fe32Cr33Ni29Al3Ti3, fabricated via laser beam power bed fusion (LB-PBF), a focus on improving their mechanical properties is essential. As part of this effort, heat treatment was explored. This study compares the microstructure and mechanical properties of the as-printed sample with those cooled in water after undergoing heat treatment at temperatures ranging from 1000 to 1200 °C for 1 h. Both pre- and post-treatment samples reveal a dual-phase microstructure comprising FCC and BCC phases. Although heat treatment led to a reduction in tensile and yield strength, it significantly increased ductility compared to the as-printed sample. This strength-ductility trade-off is related to changes in grain sizes with ultrafine grains enhancing strength and micron grains optimizing ductility, also influencing the content of FCC/BCC phases and dislocation density. In particular, the sample heat-treated at 1000 °C for 1 h and then water-cooled exhibited a better combination of strength and ductility, a yield strength of 790 MPa, and an elongation of 13%. This research offers innovative perspectives on crafting dual-phase HEA of Fe32Cr33Ni29Al3Ti3, allowing for tailorable microstructure and mechanical properties through a synergistic approach involving LB-PBF and heat treatment.

The utilization of selective laser melting (SLM) for high entropy alloys (HEAs) holds significant promise in commercial applications, and substantial experimental research efforts have been directed toward this domain. To take advantage of the reported experimental data of SLM manufactured (SLM-ed) HEAs and reduce unnecessary experimentation, this study incorporates machine learning (ML) techniques for the phase and tensile properties prediction of SLM-ed HEAs, thus presenting a novel avenue for accelerating the discovery of new SLM-ed HEAs. Through the adjustment of material descriptors and machine learning models, a model has been developed with an impressive accuracy of 93.8% in distinguishing between face-centered cubic (FCC), body-centered cubic (BCC), and dual-phase (FCC+BCC). Additionally, optimized models have been devised for the prediction of tensile properties, namely ultimate tensile strength (UTS), yield strength (YS), and elongation (δ), achieving noteworthy MAPEs (mean absolute percentage errors) of 10.33%, 8.55%, and 28.48%, respectively. Furthermore, several HEAs were fabricated using SLM, and the experimental outcomes exhibited a favorable alignment with the predicted results. These efforts carry significant implications in advancing the utilization of SLM for HEAs.

Fabricating eutectic high-entropy alloys (EHEAs) via selective laser melting (SLM) presents significant potential for advanced structural applications. This study explores the microstructural evolution of Fe₃₂Cr₃₃Ni₂₉Al₃Ti₃ EHEAs fabricated by SLM under varying laser powers. Electron backscatter diffraction (EBSD) analysis revealed that samples fabricated at 200 W exhibited approximately 70% face-centered-cubic (FCC) and 30% body-centered-cubic (BCC) phases. In comparison, those processed at 160 W showed an increased FCC fraction of 85% with a corresponding reduction in BCC content. Grain size measurements indicated that BCC grains were consistently finer than their FCC counterparts. Thermal simulations demonstrated that higher laser power produced deeper melt pools and broader temperature gradients. By correlating thermal history with phase diagram data, the spatial variation in BCC content was attributed to the differential residence time in the 1350–1100 °C range. This study represents one of the first attempts to quantitatively link local thermal histories with the evolution of dual-phase (FCC + BCC) microstructures in EHEAs during SLM. The findings contribute to the improved understanding and control of phase formation in complex alloy systems, providing valuable guidance for tailoring SLM parameters to optimize the phase composition and microstructure of EHEAs.

Functional glass surfaces with tunable wettability are of growing interest in optical, biomedical, and architectural applications. In this study, we investigate the influence of femtosecond laser processing parameters—including power, scanning speed, and repetition rate—on the surface morphology, wettability, and optical properties of Panda glass. Laser structuring generated microscale ablation features and increased surface roughness (arithmetic mean height, Sa, rising from ~0.02 µm for pristine glass to ~1.85 µm under optimized conditions). The treated surfaces exhibited enhanced hydrophobicity, with static water contact angles up to ~82° and sliding angles exceeding 50°, indicating significant droplet pinning. Optical characterization further showed a reduction in transmittance at 550 nm from ~92% (pristine) to ~68% after laser treatment, consistent with increased scattering by surface textures. These findings demonstrate that femtosecond laser processing is an effective mask-free method to enhance the hydrophobicity of glass surfaces and establish clear process–structure–property relationships, providing guidance for future optimization toward superhydrophobic performance.