Surface Technology (表面技术)•2026•DOI: 10.16490/j.cnki.issn.1001-3660.2026.09.008
Zirconia (ZrO2) ceramics are extensively utilized in aerospace, automotive, and biomedical sectors due to exceptional mechanical properties and favorable biocompatibility. However, inherent high hardness and brittleness pose significant challenges for conventional polishing tools in achieving effective surface removal. This study proposes a Halbach-array magnetic-field-assisted shear thickening polishing (HMSTP) method to achieve high-efficiency, low-damage, and low-cost precision polishing of ZrO2 ceramics. Magnetic-field rheological tests were conducted on magnetic shear thickening slurries prepared with carbonyl iron powder at different mass fractions. A slurry containing 4% carbonyl iron powder at a magnetic induction of 150 mT was selected as optimal, demonstrating the most pronounced synergistic enhancement between magnetorheological and shear thickening properties. The Halbach array magnetic field was designed comprising 11 magnets, characterized by a maximum magnetic induction of 192 mT and uniform central distribution. Experimental measurements confirmed an average magnetic induction of 150.2 mT, consistent with simulation. Polishing experiments revealed that increased polishing speed enhances shear rate and material removal rate (MRR), while excessive or insufficient polishing angle impairs slurry flow. Workpiece rotation ensures uniform force distribution but excessive rotation speed diverts slurry, weakening shear thickening. After 60 min of HMSTP, surface roughness (Ra) decreased from 601 nm to 11 nm, and MRR reached 7.26 μm/h. Compared to conventional shear thickening polishing without magnetic field, Ra was reduced by 85.6% and MRR increased by 1.33 times. The HMSTP method effectively improves surface quality and material removal rate of zirconia ceramics, achieving efficient, low-damage, and low-cost processing.
Nano-Micro Letters•2026•DOI: 10.1007/s40820-025-02007-5
Recent advancements in Zn-halogen batteries have focused on enhancing the adsorptive or catalytic capability of host materials and stabilizing complex intermediates with electrolyte additives, while the halogen-ion electrolyte modifications exhibit strong potential for integrated interfacial regulation. Herein, we design an electrically insulating rigid electrolyte container to immobilize a liquid halogen-ion electrolyte for separator-free Zn-halogen batteries with customizable electron transfer. Robust hydrogen bonding of hydroxyl groups in SiO2 with fluorinated moieties in PVDF-hfp regulates Zn2+ solvation and suppresses H2O activity, while multi-channels formed by microcracks and interparticle gaps not only enhance mass transfer but also buffer interfacial electric field, jointly enabling a durable Zn plating/stripping. Effective confinement of intermediates also ensures the high reversibility across single-(I−/I0), double-(I−/I0/I⁺), and triple-(I−/I0/I⁺, Cl−/Cl0) electron transfer mechanisms at cathode, as evidenced by the double-electron transfer systems exhibiting a low capacity decay rate of 0.02‰ over 4500 cycles at 10 mA cm−2 and a high areal capacity of 11.9 mAh cm−2 at 2 mA cm−2. This work presents a novel “container engineering” approach to halogen-ion electrolyte design and provides fundamental insights into the relationships between redox reversibility and reaction kinetics.
Nano-Micro Letters•2025•DOI: 10.1007/s40820-025-01733-0
Shuttle effect of polysulfides overshadows the superiorities of lithium–sulfur batteries. Size–sieving effect could address this thorny trouble rely on size differ in polysulfides and lithium ions. However, clogged polysulfides pose some challenges for cathode and are rarely recycled during charging/discharging. Herein, an amino functionalized titanium-organic framework is designed for modifying lithium–sulfur batteries separator to address the aforementioned challenges. Wherein, the introduction of amino narrows titanium–organic framework pore size, enabling functional separator to selectively modulate lithium ions and polysulfides migration using size-sieving effect, thereby completely suppressing polysulfides shuttle. Furthermore, the blocked polysulfides will be adsorbed on the separator surface by positively charged amino leveraging electrostatic adsorption, ensuring polysulfides to redistribute and reuse, and boosting active materials utilization. Significantly, the migration of lithium ions is not hindered since there are lithium ions transfer channels formed via Lewis acid–base interaction with the help of amino. Combined with these virtues, the lithium–sulfur batteries with amino functionalized titanium-organic framework modified separator enjoy an ultralow attenuation rate of 0.045% per cycle over 1000 cycles at 1.0C. Electrostatic adsorption and Lewis acid–base interaction cover deficiencies existing in the inhibition of polysulfides shuttle by size-sieving effect, providing fresh insight into the advancement of lithium-sulfur batteries.
Nano-Micro Letters•2025•DOI: 10.1007/s40820-025-01715-2
Sequential processing (SqP) of the active layer offers independent optimization of the donor and acceptor with more targeted solvent design, which is considered the most promising strategy for achieving efficient organic solar cells (OSCs). In the SqP method, the favorable interpenetrating network seriously depends on the fine control of the bottom layer swelling. However, the choice of solvent(s) for both the donor and acceptor have been mostly based on a trial-and-error manner. A single solvent often cannot achieve sufficient yet not excessive swelling, which has long been a difficulty in the high efficient SqP OSCs. Herein, two new isomeric molecules are introduced to fine-tune the nucleation and crystallization dynamics that allows judicious control over the swelling of the bottom layer. The strong non-covalent interaction between the isomeric molecule and active materials provides an excellent driving force for optimize the swelling-process. Among them, the molecule with high dipole moment promotes earlier nucleation of the PM6 and provides extended time for crystallization during SqP, improving bulk morphology and vertical phase segregation. As a result, champion efficiencies of 17.38% and 20.00% (certified 19.70%) are achieved based on PM6/PYF-T-o (all-polymer) and PM6/BTP-eC9 devices casted by toluene solvent.
Nano-Micro Letters•2025•DOI: 10.1007/s40820-025-01678-4
Engineering nanomaterials at single-atomic sites could enable unprecedented catalytic properties for broad applications, yet it remains challenging to do so on the surface of multimetallic nanocrystals. Herein, we present the multifactorial engineering (size, shape, phase, and composition) of the fully ordered PtBi nanoplates at atomic level, achieving a unique catalyst surface where the face-centered cubic (fcc) Pt edges are modified by the isolated Pd atoms and BiOx adatoms. This Pd1/Pt-BiOx electrocatalyst exhibits an ultrahigh mass activity of 16.01 A mg−1 Pt+Pd toward ethanol oxidation in alkaline electrolyte and enables a direct ethanol fuel cell of peak power density of 56.7 mW cm−2. The surrounding BiOx adatoms are critical for mitigating CO-poisoning on the Pt surface, and the Pd1/Pt single-atom alloy further facilitates the electrooxidation of CH3CH2OH. This work offers new insights into the rational design and construction of sophisticated catalyst surface at single-atomic sites for highly efficient electrocatalysis.
Nano-Micro Letters•2025•DOI: 10.1007/s40820-025-01664-w
Although supported solid amine adsorbents have attracted great attention for CO2 capture, critical chemical deactivation problems including oxidative degradation and urea formation have severely restricted their practical applications for flue gas CO2 capture. In this work, we reveal that the nature of surface hydroxyl groups (metal hydroxyl Al–OH and nonmetal hydroxyl Si–OH) plays a key role in the deactivation mechanisms. The polyethyleneimine (PEI) supported on Al–OH-containing substrates suffers from severe oxidative degradation during the CO2 capture step due to the breakage of amine-support hydrogen bonding networks, but exhibits an excellent anti-urea formation feature by preventing dehydration of carbamate products under a pure CO2 regeneration atmosphere. In contrast, PEI supported on Si–OH-containing substrates exhibits excellent anti-oxidative stability under simulated flue gas conditions by forming a robust hydrogen bonding protective network with Si–OH, but suffers from obvious urea formation during the pure CO2 regeneration step. We also reveal that the urea formation problem for PEI-SBA-15 can be avoided by the incorporation of an OH-containing PEG additive. Based on the intrinsic understanding of degradation mechanisms, we successfully synthesized an adsorbent 40PEI-20PEG-SBA-15 that demonstrates outstanding stability and retention of a high CO2 capacity of 2.45 mmol g−1 over 1000 adsorption–desorption cycles, together with negligible capacity loss during aging in simulated flue gas (10% CO2 + 5% O2 + 3% H2O) for one month at 60–70 °C. We believe this work makes great contribution to the advancement in the field of ultra-stable solid amine-based CO2 capture materials.
Journal of Semiconductors (半导体学报 - 中国科学院半导体研究所)•2025•DOI: 10.1088/1674-4926/25020028
Developing efficient neural network (NN) computing systems is crucial in the era of artificial intelligence (AI). Traditional von Neumann architectures have both the issues of "memory wall" and "power wall", limiting the data transfer between memory and processing units. Compute-in-memory (CIM) technologies, particularly analogue CIM with memristor crossbars, are promising because of their high energy efficiency, computational parallelism, and integration density for NN computations. In practical applications, analogue CIM excels in tasks like speech recognition and image classification, revealing its unique advantages. For instance, it efficiently processes vast amounts of audio data in speech recognition, achieving high accuracy with minimal power consumption. In image classification, the high parallelism of analogue CIM significantly speeds up feature extraction and reduces processing time. With the boosting development of AI applications, the demands for computational accuracy and task complexity are rising continually. However, analogue CIM systems are limited in handling complex regression tasks with needs of precise floating-point (FP) calculations. They are primarily suited for the classification tasks with low data precision and a limited dynamic range. A novel analogue-digital unified CIM architecture (named as AnDi) has been developed by integrating the analogue and digital computing cores, which aims to address the above challenges of analogue CIM. The key component is the dual-domain floating-point (DDFP) processor, which serves as a universal data type to represent both FP and integer (INT) numbers. This processor enables FP compatibility regardless of the native capabilities of analogue CIM or digital cores. The DDFP data structure consists of an INT tensor for the feature map and an FP scale. The DDFP processor manages data flow between the analogue and digital domains, performing quantization or dequantization operation. This effectively decouples the NN algorithm from the underlying hardware, enabling more general NN computation. The training process for the top-level algorithm can proceed without considering specific hardware architectures, as all data-scaling operations are handled at the hardware level. To maximize the potential of AnDi architecture, several strategies have been proposed. The fine-grained dual-domain mapping divides weight matrices larger than analogue CIM arrays into smaller ones. Weights are allocated to either digital or analogue cores based on their size. Low-parallel weight blocks are assigned to digital cores, thus maximizing the utilization rates of digital multiply-accumulate (MAC) cores. This approach enhances system-level energy efficiency by avoiding weight splits into additional blocks within the same layer, thereby reducing memory management overhead. The NN feature-enhancing technique addresses the noise accumulation issue in analogue CIM. Lightweight enhancing layers are integrated into the network and deployed on noise-free digital cores for inference.
Int. Journal of Mining Science and Technology (采矿与安全工程)•2025•DOI: 10.1016/j.ijmst.2025.02.001
Lunar core samples are the key materials for accurately assessing and developing lunar resources. However, the difficulty of maintaining borehole stability in the lunar coring process limits the depth of lunar coring. Here, a strategy of using a reinforcement fluid that undergoes a phase transition spontaneously in a vacuum environment to reinforce the borehole is proposed. Based on this strategy, a reinforcement liquid suitable for a wide temperature range and a high vacuum environment was developed. A feasibility study on reinforcing the borehole with the reinforcement liquid was carried out, and it is found that the cohesion of the simulated lunar soil can be increased from 2 to 800 kPa after using the reinforcement liquid. Further, a series of coring experiments are conducted using a self-developed high vacuum (vacuum degree of 5 Pa) and low-temperature (between −30 and 50 ℃) simulation platform. It is confirmed that the high-boiling-point reinforcement liquid pre-placed in the drill pipe can be released spontaneously during the drilling process and finally complete the reinforcement of the borehole. The reinforcement effect of the borehole is better when the solute concentration is between 0.15 and 0.25 g/mL.
Int. Journal of Mining Science and Technology (采矿与安全工程)•2025•DOI: 10.1016/j.ijmst.2025.06.011
Coal wall stability is a critical factor influencing coal mining efficiency and threatens the safety of working faces, where irregular coal wall surfaces significantly affect the contact and support effectiveness of the support plate, thereby impacting stability. Through a combination of theoretical analysis, mechanical testing, and numerical simulations, this study establishes a mechanical model of irregular coal wall surfaces to investigate the effects of the undulation period and undulation height on coal wall failure characteristics. This research reveals the mechanical response mechanisms of irregular coal wall surfaces and proposes an innovative method to enhance coal wall stability by improving the supporting cushion material of the support plate, which was validated through numerical simulations. The results show that the undulation height and undulation period significantly influence the macroscopic mechanical parameters of the samples, with the undulation height exerting a more pronounced effect. The strength of the samples with undulating surfaces is approximately 50%–60% that of the samples with flat surfaces. The failure mode under uniaxial compression is predominantly tensile, resulting in long and slender block fragments with a characteristic “III”-shaped tensile fracture pattern. During the loading process, samples with undulating surfaces dissipate energy at all stages, with a greater proportion of energy dissipation occurring during the early loading stage because of structural damage and the formation of internal cracks. The surface compressive and tensile stresses are correlated with the curvature radius of the convex surface and the elastic modulus of the supporting plate. Reducing the elastic modulus of the supporting plate material can effectively alleviate the stress concentration at convex locations and increase the peak strength. This study provides theoretical foundations and technical references for the prevention and control of coal wall spalling in deep thick coal seam mining.
China Foundry•2025•DOI: 10.1007/s41230-025-4101-6
Lightweight aluminum alloy conductor materials (Al-Mg-Si alloys) require not only high electrical conductivity to reduce electrical loss, but also high strength to withstand extreme weather conditions. To improve electrical conductivity and mechanical properties of Al-Mg-Si alloy simultaneously, the rare earth La was introduced to modify the Al-Mg-Si alloy. The effect of La addition on the microstructure, tensile properties and electrical conductivity of cast Al-Mg-Si alloy was investigated systematically. Results indicate that the appropriate La content is helpful to improve the strength and electrical conductivity of Al-Mg-Si alloys. When the addition of La is 0.2wt.%, the α-Al grains are refined apparently, Mg and Si solute atoms in the Al matrix are reduced by the formation of Mg2Si phase; the distribution of Al11La3 phases is uniform, and the morphology of AlFeSi phase transforms from continuous state to discontinuous state. The Al-Mg-Si-0.2La alloy exhibits the optimal tensile properties and electrical conductivity, with an ultimate tensile strength of 170 MPa, a yield strength of 88 MPa, an elongation of 18.9%, and an electrical conductivity of 44.0% IACS. These values represent improvements of 9.0%, 15.8%, 70.3%, and 17.3%, respectively, compared to the Al-Mg-Si alloy without La addition. However, excessive La deteriorates the properties of Al-Mg-Si-xLa alloys.
Chinese Journal of Mechanical Engineering•2025•DOI: 10.1186/s10033-025-01336-1
Autonomous driving technology is constantly developing to a higher level of complex scenes, and there is a growing demand for the utilization of end-to-end data-driven control. However, the end-to-end path tracking process often encounters challenges in learning efficiency and generalization. To address this issue, this paper designs a deep deterministic policy gradient (DDPG)-based reinforcement learning strategy that integrates imitation learning and feedforward exploration in the path following process. In imitation learning, the path tracking control data generated by the model predictive control (MPC) method is used to train an end-to-end steering control model of a deep neural network. Another feedforward exploration behavior is predicted by road curvature and vehicle speed, and adds it and imitation learning to the DDPG reinforcement learning to obtain decision-making experience and action prediction behavior of the path tracking process. In the reinforcement learning process, imitation learning is used to update the pre-training parameters of the actor network, and a feedforward steering technique with random noise is adopted for strategy exploration. In the reward function, a hierarchical progressive reward form and a constrained objective reward function referring to MPC are designed, and the actor-critic network architecture is determined. Finally, the path tracking performance of the designed method is verified by comparing various training results, simulations, and HIL tests. The results show that the designed method can effectively utilize pre-training and feedforward prior experience to obtain optimal path tracking performance of an autonomous vehicle, and has better generalization ability than other methods. This study provides an efficient control scheme for improving the end-to-end control performance of autonomous vehicles.
Chinese Journal of Mechanical Engineering•2025•DOI: 10.1186/s10033-025-01263-1
The research on rolling bearing early fault detection is mainly focused on degradation index extraction and adaptive setting of alarm threshold. The mainstream methods are to extract degradation indicators based on adaptive features and set adaptive alarm thresholds based on the Shewhart control chart. However, the adaptive feature extraction method does not consider the correlation between features, and the Shewhart control chart is not sensitive to small fluctuations caused by early faults. In this study, a rolling bearing early fault detection method based on a feature clustering fusion degradation index is proposed. The multidomain statistical features are extracted to form the initial feature set, and the improved hierarchical clustering algorithm is combined with the feature evaluation index to select features to form a preferred feature subset, to ensure the richness of index information and reduce redundancy. After the construction of the degradation index, to suppress the interference caused by nonstationary and abnormal shocks in early fault detection, the accurate evaluation method and anomaly determination strategy of control chart parameters are studied, and an improved exponential weighted move average control chart is designed to monitor the degradation index. The effectiveness and superiority of the proposed method are verified by public data sets. This research provides a rolling bearing early fault detection method, which can provide comprehensive degradation indicators, eliminate interference caused by random anomalies and running in periods, and achieve an accurate detection of early bearing failures.