Researchers proposed an image-aided terminal guidance attitude control method for Explosively Formed Penetrator (EFP)-equipped multirotors to achieve long-range precision strikes, solving disturbance, EFP dispersion and visual-attitude coupling problems. Published in Defence Technology, the work built a multi-source EFP dispersion model, designed an NTSM-STO composite controller, and validated its fast response, strong robustness and high hit rate via Monte Carlo simulations and real flight tests.

An international research collaboration, from Sun Yat-sen University, South China University of Technology, University of Liverpool and JiangSu CheeShine Performance Materials Co., has developed a mechanically adaptive artificial interphase for ultrafast zinc metal batteries. By constructing a spider-web-like nitrile butadiene rubber (NBR) nanofiber interphase, the researchers achieved synergistic regulation of homogeneous Zn²⁺ transport, free-water blocking, and interfacial deformation buffering. This strategy transforms unstable zinc growth into a uniform and confined surface deposition process. Based on this interphase, Zn//Zn symmetric cells can operate stably for more than 6,000 hours, while Zn//V₂O₅ full cells deliver stable cycling for 20,000 cycles at an ultrahigh rate of 50 A g^-1, providing a new interfacial engineering strategy for safe and high-power aqueous zinc batteries.

A group of researchers from Beijing Institute of Technology, National Institute of Clean-and-Low-Carbon Energy, Beijing Engineering Research Center of Nano-structured Thin Film Solar Cells and Beijing University of Chemical Technology, has developed a coordination-regulated strategy to stabilize wide-bandgap perovskites for efficient perovskite/CIGS tandem solar cells. By introducing bis(2-pyridylmethyl) sulfide (2PyS) to regulate the local Pb²⁺ coordination environment, the researchers suppressed defect formation, reduced halide ion migration, and mitigated photoinduced phase segregation. The optimized wide-bandgap perovskite solar cells achieved an efficiency of 22.21% and retained more than 91% of their initial performance after 2000 hours of continuous operation. When integrated with a CIGS bottom cell, the resulting four-terminal perovskite/CIGS tandem solar cell delivered an overall efficiency of 29.71%. This study provides a promising molecular design route toward stable and efficient tandem photovoltaics.

Phase-change materials and hydrogels emerge as versatile, low-cost, high-speed platforms for next-generation optical information storage and multi-level encryption. NDAO Lab (Nano Devices and Applied Optics) at UC San Diego developed an optical storage system combining laser-written phase-change antimony trisulfide (Sb₂S₃) with a humidity-responsive CMC-N₃ hydrogel to enable full-color image multiplexing. This scalable approach overcomes limitations of metasurface-based storage, offering rewritable, environmentally responsive optical memory for data security, anti-counterfeiting, and adaptive display applications across large areas with low fabrication complexity and cost.

Hydrogel electrolytes are pivotal for flexible zinc-ion batteries (ZIBs) yet suffer from an intrinsic trade-off between mechanical robustness and ionic conductivity. Herein, drawing inspiration from the “adhesion-conduction” architecture of spider webs, we developed a hierarchical hydrogel electrolyte (MTP) by incorporating tannic acid (TA)-modified MXene nanosheets (MT) into a polyacrylamide (PAM) skeleton to construct uniform 3D ion-conductive pathways. This bioinspired hierarchy serves a dual function: The PAM framework ensures mechanical integrity, while the MT network creates directed low-resistance channels for Zn²⁺ transport. Specifically, the dense array of polar groups on MXene and phenolic hydroxyls on TA act as “sticky sites”, which accelerate desolvation kinetics and homogenize Zn²⁺ flux. Consequently, the MTP electrolyte achieves an impressive ionic conductivity of 27.69 mS cm⁻¹ and a high Zn²⁺ transference number of 0.833. Enabled by this design, Zn//Zn symmetric cells demonstrate an ultralong lifespan of 4600 h (> 6 months) at 0.5 mA cm⁻²/0.5 mAh cm⁻². Furthermore, Zn//Z-VO full cells exhibit outstanding cyclability, retaining 74.5% capacity after 2000 cycles at 2 A g⁻¹ and maintaining durable operation for over 10,000 cycles at 5 A g⁻¹. This work successfully translates a biological blueprint into a practical strategy for resolving the kinetic and stability challenges in high-performance flexible ZIBs.

Polymer-based flexible wireless sensors have demonstrated significant potential in health monitoring. However, existing studies have predominantly focused on material design, energy harvesting, and wireless communication, while research addressing signal attenuation, noise accumulation, and data distortion within wireless links remains relatively limited. Physiological signals are highly susceptible to multi-source interference during acquisition and transmission; without effective data processing and intelligent analysis strategies, monitoring outcomes may fail to meet the accuracy and stability requirements of clinical applications. To address this research gap, this review constructs a comprehensive framework encompassing signal sensing, link transmission, and intelligent processing, building on advances in flexible materials and wireless energy supply modes. Special attention is given to the critical roles of channel compensation, noise suppression, feature extraction, lightweight artificial intelligence models, and edge computing in enhancing data quality and reducing energy consumption. Furthermore, the review systematically analyzes the impact of wireless link stability and energy management on monitoring performance. By reinforcing the synergistic mechanisms between data processing and communication, this work aims to provide design principles and development directions for the next generation of high-reliability, low-power, and intelligent wireless flexible health monitoring systems.

High NOx emissions pose a critical challenge for ammonia engines. This study proposes ammonia post-injection as a strategy to achieve in-cylinder NOx active reduction in ammonia direct-injection engines, offering an innovative approach for NOx emission control. Computational fluid dynamics (CFD) simulation results elucidate the characteristics of ammonia combustion and NOx evolution under ammonia post-injection conditions. The post-injected ammonia can efficiently reduce the in-cylinder NOx it encounters, leading to a significant decrease in NOx concentration. Chemical kinetics analysis was conducted to reveal the underlying mechanisms and reaction pathways of the SNCR effect on NOx. The reduction of NOx primarily proceeds through the reactions between NO/NO2 and NH/NH2. NO is reduced via three pathways, yielding NNH (by NH2), N2O (by NH), and N2 (by NH and NH2), respectively. In contrast, NO2 is reduced via a single pathway that yields N2O under the action of NH and NH2. NH2 plays the overwhelmingly dominant role in reducing both NO and NO2. The effectiveness and feasibility of ammonia postinjection in reducing NOx emissions were evaluated through engine experiments. The experimental results demonstrate that the ammonia post-injection strategy enables significant NOx reduction for ammonia direct-injection engines. In the current work, a 14.4% NOx reduction was achieved without compromising combustion efficiency by appropriately delaying the ammonia post-injection timing, confirming the great potential of ammonia post-injection in NOx emission control.

The Fe–N–C single-atom catalyst represents a promising candidate for promoting the oxygen reduction reaction (ORR), which is crucial for fuel cell applications; yet, identifying optimal modification strategies to enhance its activity and stability remains challenging. Herein, the modulation of Fe–N–C catalysts via in-plane heteroatom doping and axial coordination is systematically investigated using integrated density functional theory (DFT) and machine learning (ML) approaches. The analysis reveals that axial ligands have a more profound influence on ORR performance than in-plane dopants, primarily by modulating the Fe dz2 orbital and weakening *OH adsorption. Through interpretable descriptors extracted from ML models, the key electronic and geometric properties governing catalyst behavior are identified, and several novel dual-modified candidates with enhanced activity relative to pristine Fe–N–C are subsequently predicted and validated by DFT calculations. This work provides a unified mechanistic and data-driven framework for accelerating the design of high-performance Fe–N–C ORR electrocatalysts.