Researchers have conducted a comprehensive techno‑economic analysis and life cycle assessment comparing the industrial mainstream one‑step isobutene ammoxidation process with the emerging two‑step route for methacrylonitrile production. Under unified conditions of 99.5 % product purity and 1 t·h⁻¹ isobutene feed, the two‑step process achieves a higher yield of 82.4 % compared with 77.3 % for the one‑step process. However, the one‑step process is superior in unit production cost at 1.90 vs. 2.23 USD·kgMAN⁻¹ and life cycle carbon emissions at 7.42 vs. 9.10 tCO₂‑eq·tMAN⁻¹. Sensitivity analysis reveals that each 1 % increase in the two‑step yield reduces cost by 0.07 USD·kgMAN⁻¹ and emissions by 0.37 tCO₂‑eq·tMAN⁻¹, and a yield of 86.9 % makes it economically and environmentally comparable to the one‑step process.

By pre-programming dense stacking faults into diamond, researchers have created a material that stays ultrahard (140 GPa) yet resists cracking, with toughness improved by 120%. The defects actively respond to crack-tip stress, triggering local phase transformations that absorb energy from the very moment a crack starts. This strategy offers a new path to alleviate the hardness–toughness trade-off in superhard materials.

Researchers have developed a multi‑step crosslinking strategy to construct UiO‑66‑AC@PEG by covalently bridging maleic anhydride‑prefunctionalized UiO‑66‑NH₂ with polyethylene glycol, enabling simultaneous interfacial engineering and pore regulation. The resulting crosslinked architecture incorporates abundant amide and ether oxygen moieties, generating CO₂‑philic domains that enhance CO₂ sorption through dipole‑quadrupole interactions. Meanwhile, crosslinking induces pore constriction within UiO‑66‑NH₂, strengthening size‑sieving effects toward CO₂/N₂ separation. The optimized UiO‑66‑AC@PEG/Pebax membrane achieved a CO₂ permeability of 125.8 Barrer and a CO₂/N₂ selectivity of 81.1, corresponding to increases of 56.6 % and 33.5 %, respectively, compared with the UiO‑66‑NH₂/Pebax MMM.

A latest study published in National Science Review has resolved inconsistencies in the responses of Western Pacific Subtropical High (WPSH) to greenhouse warming that arise from earlier definitions. The study reports a robust increase in WPSH’s area and intensity, its northwestward expansion, as well as in occurrence of stronger, longer-lasting record-breaking WPSH events under the past and future climate change scenario. These changes imply increasing risk exposure to monsoon rainfall extremes and heatwaves beyond historical experience for human society and communities.

 Researchers have systematically reviewed the application of electromagnetic induction heating in energy chemical engineering, focusing on three susceptor categories: carbon‑based materials, macroscopic metals, and magnetic nanoparticles. Carbon‑based susceptors enable reactant‑heat source integration for high‑temperature endothermic reactions such as calcium carbide synthesis, achieving solid‑phase synthesis with reaction temperatures reduced by 400‑500 °C compared to the electric arc process. Macroscopic metal susceptors combine heat generation and catalytic functions, with iron‑based induction heating reducing ammonia decomposition activation energy by more than half and maintaining high conversion at ultra‑high space velocities. Magnetic nanoparticles generate heat precisely at catalytic sites, enabling nanoscale hot spots under mild macroscopic temperatures for reactions such as reverse water‑gas shift and dry reforming.

Researchers have developed a zirconium‑modified LiMn₂O₄ film electrode for selective lithium extraction from brine via electrochemically switched ion exchange. Zr modification simultaneously enhanced electronic conductivity and structural stability by tuning the electronic structure and strengthening Mn–O hybridization. In real brine from Qarhan Salt Lake, the optimized LZMO‑0.03 electrode achieved a lithium intercalation capacity of 22.16 mg·g⁻¹ and a Li/Mg separation factor of 685.43, with energy consumption as low as 3.61 Wh·mol⁻¹ under constant current‑constant voltage mode. After 20 cycles, Mn dissolution was reduced to approximately 51.8 % of that of the pristine LMO electrode.

Researchers have developed a nickel‑cobalt layered double hydroxide nanosheet catalyst supported on nickel foam for the selective electrooxidation of isobutanol to isobutyric acid under mild alkaline conditions. The optimized catalyst exhibits a three‑dimensional hierarchical nanosheet architecture with an enlarged electrochemically accessible surface area and favorable charge‑transfer behavior. It achieved a Faradaic efficiency of 91.3 % and selectivity of 93.2 % toward isobutyric acid at 1.52 V vs. RHE, significantly outperforming the corresponding monometallic hydroxide catalysts. Mechanistic studies supported a sequential oxidation pathway via adsorbed isobutyraldehyde intermediates.

As brain-computer interfaces become increasingly precise in reading human emotions, a practical question arises: Will a model trained today still be able to recognize the emotions of the same person tomorrow, in a few weeks, or even months later? Recently, the team led by Shuang Liu from the Medical School of Tianjin University/Haihe Laboratory of Brain-Computer Interaction and Human-Machine Integration published a research paper titled "Toward Sustainable Cross-Time Affective Brain–Computer Interfaces: Explicit Modeling and Structural Calibration of Temporal Variability" in the National Science Review (NSR). This study offers a cross-time "EEG ruler" for affective brain-computer interfaces (aBCIs). To address temporal variability in cross-time emotion recognition, the researchers propose a Multi-level Dynamic Integrated Perception Network (MDIN), which explicitly models and structurally calibrates temporal variability on three levels: emotional neural representation, dynamic functional connectivity, and cross-time discriminative structures, offering a new technical pathway for long-term stable affective brain-computer interfaces. This work may further accelerate the transition of aBCIs from short-term experimental validation to long-term, adaptive use in real-world mental health monitoring and human-machine interaction.

Researchers have developed a high‑accuracy Al‑O‑H machine learning interatomic potential combined with global optimization to explore the structural landscape of γ‑Al₂O₃ and its influence on propane dehydrogenation over single‑atom Pt catalysts. Two energetically favorable structures, γ‑NAV and γ‑AV, were identified with energies lower than the conventional model by up to 34.44 meV·(f.u.)⁻¹. These optimized structures expose abundant penta‑coordinated Al³⁺ sites on the (100) surface, serving as preferred anchoring sites for Pt atoms. Catalytic calculations demonstrate that γ‑NAV and γ‑AV significantly reduce propane dehydrogenation activation barriers through enhanced metal‑support interactions.

High‑throughput workflows have revolutionized experimental heterogeneous catalysis by enabling rapid, parallel synthesis and screening of catalyst libraries. This review traces the evolution of high‑throughput technology from manual experiments in the early 1900s to today‘s autonomous, artificial intelligence‑driven platforms that integrate robotics, machine learning, and self‑driving laboratories. The state‑of‑the‑art mode encompasses five key steps: experiment design, catalyst synthesis, catalyst testing and screening, catalyst characterizations, and data handling and analysis. Despite its transformative potential, high‑throughput workflows face critical pitfalls—including gaps between microscale reactor results and industrial performance, pressure limitations, and chemical information disparity in funnel‑shaped screening—that must be addressed to fully realize its promise for rational catalyst discovery.