Functions of extreme stretchability, ultrahigh tensile strength, high-level conductivity and self-healing capacity endow polymer-based soft electronics with enhanced reliability and prolonged lifespan in deformable applications. However, it is still a huge challenge to achieve such a performance portfolio in individual electronic systems because ultrahigh strength is hardly compatible with self-healing ability in polymers. Herein, a hydrogen-bonded nanoconfinement strategy is proposed to synthesize supertough self-healing polyurethane (TSPU). The hierarchical hydrogen bonds, slight covalent crosslinking and rigid nanoconfinement phases result in self-healing polymers with super stretchability and ultrahigh strength. Self-healing soft electrodes were fabricated possessing the above functions simultaneously with the TSPU polymer as the supporting layer on which a eutectic gallium–indium (EGaIn) liquid metal is spread. By means of the dynamic nanoconfinement strategy, the soft electrodes showed a break elongation of ca. 2500% and a tensile strength of ca. 50 MPa, and 200 000 times its own weight could be lifted up. Remarkably, the resistance of the soft conductor only changed a little even at 2000% strain illustrating an outstanding conductive reliability. The ultrahigh strength, extreme ductility and high reliability bring self-healing electronics to a new high level. Such self-healing soft electronic devices could find promising potential in heavy-duty deformable electronic applications.

The Al-Si-Cr-Co-Ni High Entropy Alloy (HEA) with low density (about 5.4 g/cm³) and excellent performance had significant potential in the lightweight engineering material field. To further research and optimize the Al-Si-Cr-Co-Ni system HEA, the influences of element Cr on the microstructures and performances of lightweight AlSi_0.5Cr_xCo_0.2Ni (in mole ratio, x = 1.0, 1.2, 1.4, 1.6, and 1.8) HEAs were investigated. The experiment results manifested that AlSi_0.5Cr_xCo_0.2Ni HEAs were composed of A2 (Cr-rich), B2 (Ni-Al), and Cr₃Si phases, indicating that the addition of Cr did not result in the formation of a new phase. However, ample Cr increased the Cr₃Si phase composition, further ensuring the high hardness (average HV 981.2) of HEAs. Electrochemical tests demonstrated that HEAs with elevated Cr₃Si and A2 phases afforded greater corrosion resistance, and the improvement in corrosion was more pronounced when x > 1.6. This work is crucial in the development of lightweight engineering HEAs, which are of tremendous practical utility in the fields of cutting tools, hard coating, etc.

As Bayan Obo rare-earth tailings, which are generated after the production of mineral products with the raw ore from different mining areas, are considered secondary resources rich in valuable elements such as F, Fe, REE, and Nb, an effective method is urgently needed to recover such valuable elements for resource recycling and environmental conservation. A mineralogical analysis can enable process diagnosis, design, and optimization and is the key to comprehensively utilizing valuable elements. Hence, detailed mineralogical characterization is necessary as a starting point to develop a feasible processing flowsheet. In this study, various detection methods, namely inductively coupled plasma-optical emission spectrometry (ICP), X-ray Fluorescence Spectrometer (XRF), X-ray powder diffractometer (XRD), scanning electron microscopy system with an energy dispersive spectrometer (SEM-EDS), mineral liberation analysis (MLA), and electron probe microanalysis (EPMA), were applied to conduct detailed mineralogical characterization of Bayan Obo rare-earth tailings, and the occurrence state of Sc in the main Sc-bearing minerals was studied using density functional theory (DFT). The results showed that Fe mainly occurs in hematite, riebeckite, ankerite, siderite, and pyrite, with contents of 50.15 wt%, 27.94 wt%, 8.34 wt%, 4.92 wt%, and 5.59 wt%, respectively. Nearly all F occurs in 26.8 wt% fluorite. The main rare-earth minerals are bastnasite, apatite, and monazite (La), with contents of 5.0%, 5.0%, and 1.6% in Bayan Obo rare-earth tailings, respectively. Notably, 48.47%, 21.70%, 10.34%, and 10.28% of niobium element occurs in nioboaeschynite, pyrochlore, dingdaohengite, and ilmenorutile, respectively. Scandium was detected in five minerals, namely aegirine, riebeckite, monazite, ilmenorutile, and niobite, with average contents of 0.04 wt%, 0.22 wt%, 0.06 wt%, 0.06 wt%, and 1.58 wt%, respectively. According to the DFT analysis, the state of Sc in aegirine is different from that in riebeckite. Scandium in aegirine mainly substitutes Fe or enters the interstitial lattice site, while Sc in riebeckite tends to replace Fe. Based on these results, a process for recovering valuable elements from tailings is proposed.

High-entropy alloys (HEAs) were prepared with strong antioxidant metals Al, Cr, Ti, and Si as matrix elements, and the effects of rare earth (RE) lanthanum (La) and yttrium (Y) doping on their microstructures and high-temperature oxidation resistance were explored in this study. The AlCrTiSi_0.2RE_0.02 HEAs were prepared by using vacuum arc melting and were oxidized mass gain at 1000 °C. After oxidation for 53 h, AlCrTiSi_0.2 HEA had a mass increase of 1.195 mg/cm², and it had the best oxidation resistance of three HEAs (AlCrTiSi_0.2, AlCrTiSi_0.2La_0.02, and AlCrTiSi_0.2Y_0.02). The surface oxide layers of three HEAs mainly consisted of Al and Ti oxides; the layered oxide film of AlCrTiSi_0.2 alloy was mainly composed of dense Al₂O₃, and the acicular oxide films of AlCrTiSi_0.2La_0.02 and AlCrTiSi_0.2Y_0.02 alloys were primarily composed of loose Ti oxide. Doping La and Y decreased the oxidation resistance of AlCrTiSi_0.2. In the early stage of oxidation of rare earth HEAs, the surface oxide layer was loose because La and Y reacted with the matrix metal, which slowed down the diffusion of element Al or accelerated the diffusion of element Ti. In the late stage of oxidation, La and Y interacted with O and entered the matrix metal to form rare earth oxides.

The preparation of sintered NdFeB magnets is complex, time-consuming, and costly. Data-driven machine learning methods can enhance the efficiency of material synthesis and performance optimization. Traditional machine learning models based on mathematical and statistical principles are effective for structured data and offer high interpretability. However, as the scale and dimensionality of the data increase, the computational complexity of models rises dramatically, making hyperparameter tuning more challenging. By contrast, neural network models possess strong nonlinear modeling capabilities for handling large-scale data, but their decision-making and inferential processes remain opaque. To enhance interpretability of neural network, we collected 1,200 high-quality experimental data points and developed a multi-head attention regression model by integrating an attention mechanism into the neural network. The model enables parallel data processing, accelerates both training and inference speed, and reduces reliance on feature engineering and hyperparameter tuning. The coefficients of determination for remanence and coercivity are 0.97 and 0.84, respectively. This study offers new insights into machine learning-based modeling of structure-property relationships in materials and has potential to advance the research of multimodal NdFeB magnet models.

Production of rare earth enrichment from the in situ leaching solution of ion-adsorbed rare earth ores greatly decreases the treatment scale and significantly reduces production energy consumption and cost. However, the generated rare earth enrichment has a high content of impurities. Further purification of rare earth is necessary. Therefore, a process comprised of sulfuric acid leaching and removing aluminum by the neutralization precipitation method to obtain the purified rare earth solution was proposed. The results of acid leaching revealed that at a sulfuric acid concentration of 1.75 mol/L, a temperature of 60 °C, a liquid–solid ratio of 5:1 mL/g, a leaching time of 0.5 h, and a stirring rate of 300 r/min, leaching efficiency of rare earth and magnesium reached 99.11% and 97.39%, respectively, while the leaching efficiencies of aluminum and silicon reached 72.91% and 55.26%, respectively. The comparison of different precipitants during the neutralization precipitation process showed that MgO was the best precipitant for the efficient removal of aluminum and low loss of rare earth. The results of removing aluminum revealed that when the final pH of the rare earth leaching solution was controlled to be 4.7, the reaction temperature was 25 °C, the slurry concentration of MgO was 0.3 mol/L, and the feeding rate of the MgO slurry was 0.5 mL/min, the removal rate of aluminum was 99.49%, and the loss rate of rare earth was 13.93%. The obtained purified rare earth solution contained 19 g/L of rare earth and less than 0.01 g/L of aluminum. Kinetic studies showed that the apparent activation energy of the aluminum removal process was 6.8 kJ/mol, indicating that the precipitation process was controlled by a mass transfer diffusion reaction.