SCIENCE CHINA Materials•2026•DOI: 10.1007/s40843-026-4205-8
The global energy crisis and environmental pollution necessitate efficient recovery and utilization of thermal energy resources such as industrial waste heat. Thermoelectric materials, enabling direct conversion between thermal and electrical energy, offer broad application prospects in waste heat power generation and chip cooling. The energy conversion efficiency is determined by the dimensionless figure of merit, ZT = (S^2σ/κ)T, where S is the Seebeck coefficient, σ is the electrical conductivity, κ is the thermal conductivity, and T is the absolute temperature. Ideal thermoelectric materials require both a high power factor (PF = S^2σ) and low thermal conductivity. However, the strong coupling between electrical and thermal transport parameters makes synergistic optimization challenging. Over the past two decades, strategies such as band engineering, nanostructuring, liquid-like ions, interstitial atoms, phonon softening, and defect engineering have been explored. Among these, entropy engineering has emerged as a novel strategy that achieves synergistic optimization by introducing multiple components to increase configurational entropy. High entropy materials, originating from alloys, are defined as multi-principal element systems with five or more elements in near-equiatomic ratios forming single-phase solid solutions. The molar configurational entropy ΔS_conf = R∑x_i ln x_i, with materials classified as high entropy (ΔS_conf > 1.5R), medium entropy (1R < ΔS_conf < 1.5R), or low entropy (ΔS_conf < 1R). Four core effects are summarized: high entropy effect, lattice distortion effect, sluggish diffusion effect, and cocktail effect. Research has expanded from alloys to oxides, chalcogenides, and half-Heusler compounds. This review systematically summarizes the mechanisms by which lattice distortion in high entropy materials affects electrical and thermal transport, and discusses optimization strategies for thermoelectric performance.
SCIENCE CHINA Materials•2026•DOI: 10.1007/s40843-025-3665-2
Immuno-phototherapy faces a critical bottleneck: achieving high singlet oxygen (1O2) quantum yield and efficient photothermal conversion simultaneously under a single near-infrared (NIR) laser. Here, we report an acceptor-donor-acceptor (A-D-A) structured molecule, 3,9-bis(2-methylene-((3-(1,1-dicyanomethylene)-6/7-methyl)-indanone))-5,5,11,11-tetrakis(4-hexylphenyl)-dithieno[2,3-d:2',3'-d']-s-indaceno[1,2-b:5,6-b']-dithiophene (m-ITIC), formulated into nanoparticles (NPs) via self-assembly with DSPE-PEG-NH2. The NPs exhibit strong NIR absorption and fluorescence at 688 and 768 nm, respectively. Under single-laser irradiation, they generate heat, superoxide anion (O2•−), and 1O2, with a 1O2 quantum yield of 56.8% and photothermal conversion efficiency (PCE) of 27.4%. This enables NIR fluorescence imaging-guided synergistic photodynamic therapy (PDT) and photothermal therapy (PTT). Notably, the nanoplatform induces PANoptosis—a coordinated cell death program integrating pyroptosis, apoptosis, and necroptosis—in tumor cells, amplifying immunogenic cell death (ICD). This triggers robust dendritic cell activation, macrophage polarization toward M1 phenotype, elevated CD8+ T cell infiltration, and suppression of immunosuppressive Treg cells, leading to significant tumor growth inhibition and prevention of lung metastasis in vivo. Therapeutic efficacy was validated in patient-derived tumor organoids, underscoring translational potential. This study presents a novel single-laser-activated nanoplatform that simultaneously mediates efficient photothermal and photodynamic effects and induces PANoptosis-driven ICD for synergistic cancer immunotherapy.
Chinese Journal of Environmental Engineering•2026•DOI: 10.12030/j.cjee.202506020
The rotary kiln roasting of lepidolite for lithium extraction faces challenges of unstable lithium conversion rates and high energy consumption. To address this, a multi-objective optimization method coupling improved neural network simulation with a multi-objective genetic algorithm was proposed, targeting the synergistic optimization of lithium conversion rate (TRLi) and natural gas consumption intensity (EIng). Using long-term industrial time-series data of batching parameters and kiln operating variables, back-propagation (BP) neural network and its particle swarm optimization (PSO) improved variant were developed to model TRLi and EIng. The PSO-BP model demonstrated superior accuracy in capturing the complex nonlinear relationships, reducing mean absolute percentage errors (MAPE) to 0.278 and 0.284 for TRLi and EIng, respectively. Subsequently, the non-dominated sorting genetic algorithm II (NSGA-II) was employed to construct a multi-objective optimization model, yielding a Pareto-optimal set of process parameters that maximize TRLi and minimize EIng. The results revealed that under NSGA-II optimized conditions, TRLi could be stabilized between 82.45% and 87.96%, an average increase of 3.61 percentage points over baseline operations, while EIng could be reduced to 53.7 m3 per ton of clinker. For an annual processing capacity of 3.2×105 tons of lepidolite concentrate and sulfate mixture, this corresponds to an additional 127.1 tons of lithium metal recovery, a reduction of 1,964,912 m3 in natural gas consumption, and a decrease of 3,763.84 tons in CO2 emissions annually. This study provides theoretical and technical support for the green, high-quality, and low-carbon supply of critical raw materials for the lithium battery new energy industry.
SCIENCE CHINA Materials•2026•DOI: 10.1007/s40843-025-3935-1
Silk fibroin (SF)-based hydrogels are promising for biological interfaces, yet achieving multifunctionality—mechanical robustness, adhesion, conductivity, and stability—often requires chemical modification that compromises biocompatibility. Here, we report a protonation-mediated SF/polyvinyl alcohol (PVA) hydrogel adhesive that retains natural silk properties while gaining tailored functionalities. The physically crosslinked network is formed solely via molecular interactions, with phosphoric acid (H3PO4) as a protonation agent to modulate hydrogen bonding, enabling precise control over adhesion, mechanical strength, and electronic conductivity. Glycerol (Gly) is incorporated as a moisturizing agent to enhance long-term stability for skin applications. The resulting hydrogel exhibits excellent performance in monitoring electrophysiological signals, including electrocardiogram (ECG), electromyogram (EMG), and electroencephalogram (EEG), demonstrating its potential as a platform for advanced biological interfaces. This work addresses the critical challenge of developing SF-based hydrogels that combine natural advantages with multifunctionality, offering a promising route for wearable health monitors and human-machine interfaces.
SCIENCE CHINA Materials•2026•DOI: 10.1007/s40843-025-3756-5
Photochemical organic synthesis exploits the distinctive redox properties of excited-state photocatalysts to avoid stoichiometric redox reagents, enabling green and sustainable transformations. However, the conversion efficiency of light-to-chemical energy remains a key bottleneck for large-scale application. Here, we synthesize ultra-thin graphitic carbon nitride (g-C3N4) nanosheets by regulating precursor types and thermal protocols. In photochemical Minisci-type cross-couplings, this ultra-thin carbon nitride exhibits high catalytic efficiency, achieving rates of 40 mmol g_cat−1 h−1 under LED irradiation and 10.9 mmol g_cat−1 h−1 under natural sunlight. The photocatalyst's high specific surface area (120 m2 g−1) enhances substrate adsorption capacity and accelerates surface electron transfer, boosting photocatalytic efficiency. Furthermore, the material demonstrates excellent recycling stability, and the reaction system was successfully scaled to gram-level, highlighting its potential for industrial applications. This work provides a typical case for solar-driven organic synthesis and inspires further developments in heterogeneous photocatalysis.
Environmental Chemistry•2026•DOI: 10.7524/j.issn.0254-6108.2025021903
Volatile organic compounds (VOCs) are key precursors of secondary organic aerosols (SOA), and their oxidation reactions are regulated by reactive intermediates. A deep understanding of the reaction mechanisms of VOCs-derived reactive intermediates is crucial for evaluating SOA formation. Atmospheric peroxyalkyl radicals (RO2·) are important intermediates produced during VOCs oxidation and can generate highly oxygenated organic molecules (HOMs) through a unique atmospheric autoxidation mechanism, contributing significantly to SOA formation. This article reviews recent advances in computational studies on the autoxidation mechanisms of RO2· with different functional groups, focusing on the autoxidation reactions of RO2· derived from alkanes, alkenes, carbonyl compounds, aromatic hydrocarbons, heteroatom-containing compounds, and other substances. The review highlights the commonalities and differences in autoxidation mechanisms across these functional groups, emphasizing the role of intramolecular hydrogen shifts and subsequent O2 addition steps. Furthermore, we emphasize that future research should focus on the autoxidation of second-generation RO2· and autoxidation mechanisms driven by different intramolecular reactions. Quantum chemical calculations, often combined with kinetic modeling, provide molecular-level insights into reaction pathways and rate constants, which are essential for predicting HOM formation and SOA yields. This review aims to guide further theoretical investigations and support the development of more accurate atmospheric chemistry models.
Journal of Environmental Engineering Technology•2026•DOI: 10.13205/j.hjgc.202606001
Municipal sludge anaerobic resource recovery efficiency in China lags behind developed countries. Widespread chemical phosphorus removal increases iron and aluminum salt precipitates in waste activated sludge, forming chemical-biological sludge that reduces acidogenic efficiency. This study identified key factors and developed a high-precision prediction model. Integrating literature and experimental data, acidogenic performance indicators under various conditions were compiled. Five machine learning models—Backpropagation Neural Network, Adaptive Neuro-Fuzzy Inference System, Support Vector Machine, K-Nearest Neighbors, and Random Forest—were systematically compared. Random Forest achieved the best predictive performance with a test set coefficient of determination (R²) of 0.9463, significantly outperforming others with minimal overfitting risk, demonstrating strong capability for high-dimensional, nonlinear, multi-factor coupled problems. Feature importance analysis revealed pH and Volatile Suspended Solids (VSS) as primary drivers, with aluminum salts exerting greater influence than iron salts. Engineering optimization should follow the pathway: 'adjust pH, stabilize organic matter, control aluminum salts'. This study provides an intelligent predictive tool and clarifies optimization directions, advancing precision and intelligent sludge treatment.
SCIENCE CHINA Materials•2026•DOI: 10.1007/s40843-025-3967-x
Metal-halide perovskites exhibit exceptional optical gain, narrow emission linewidths, and high emission efficiency, positioning them as promising candidates for next-generation lasers. Thermal evaporation, a mature semiconductor fabrication technique, offers scalability, yet monitoring phase distribution during deposition remains challenging. This study systematically investigates and regulates thermally evaporated FAxCs0.8PbBr3 perovskite films by tuning formamidinium (FA) content to optimize phase distribution. At intermediate FA content, films achieve a balanced distribution of n=2 to n=5 quantum-well phases, facilitating ultrafast carrier transfer (<0.31 ps) and suppressing nonradiative recombination. FA+ actively incorporates as an A-site cation, promoting ordered crystallization and reducing defect densities. The optimized films exhibit a net modal gain of 1041 cm−1 and a gain lifetime of 129 ps. Benefiting from efficient internal scattering, the threshold for cavity-free random lasing is reduced to below 5 μJ/cm2 at room temperature. The low spatial coherence of random lasing enables speckle-free imaging with a speckle contrast as low as 0.011 and improved contrast-to-noise ratios across all spatial frequencies. This work provides a scalable strategy for perovskite composition-phase engineering, advancing speckle-free laser imaging systems compatible with semiconductor-grade, large-area manufacturing.
Journal of Environmental Engineering Technology•2026•DOI: 10.13205/j.hjgc.202608023
Zinc-containing steel dust sludge, a by-product of steelmaking, contains high levels of chlorine (Cl) along with valuable metals such as Fe, Zn, K, and Na. When recycled into the steel production process, Cl accumulates, causing sintering instability and severe corrosion of blast furnace linings. This study investigated water leaching for Cl removal from zinc-containing steel dust sludge. Under optimal conditions (liquid-to-solid ratio 5 mL/g, temperature 70 °C, time 60 min, rotation speed 160 r/min), the Cl leaching rate reached 87%. Furthermore, a three-stage countercurrent water washing process at a liquid-to-solid ratio of 6 mL/g and room temperature for 45 min achieved a Cl leaching rate exceeding 90%. The water washing also reduced the leaching toxicity of metals in the sludge to a certain extent. Characterization via XRD, SEM, FT-IR, and XPS revealed that water washing primarily dissolved soluble chlorides (NaCl, KCl, etc.), increasing the specific surface area from 2.71 to 10.11 m²/g and average pore size from 12.83 to 16.29 nm. These findings provide theoretical and technical support for efficient Cl removal from zinc-containing steel dust sludge, facilitating its safe resource utilization.
SCIENCE CHINA Materials•2026•DOI: 10.1007/s40843-025-4077-0
Flexible memristors are pivotal for advancing neuromorphic computing in wearable electronics, yet the intrinsic brittleness of inorganic oxides poses a critical challenge. Here, we employ an entropy-engineering strategy to control the amorphization of oxide compositions, yielding a precisely controlled crystalline/amorphous microstructure in a BaTi0.25Sn0.25Hf0.25Zr0.25O3 thin film. This film withstands bending angles up to 180°, enabling an Au/BaTi0.25Sn0.25Hf0.25Zr0.25O3/ITO/Mica device that functions as a memristor. Entropy engineering increases oxygen vacancy concentration, imparting stable resistive switching behavior under both flat and bent conditions. The device exhibits exceptional endurance and reproducibility over multiple bending cycles, demonstrating a significant strategy for advancing flexible memristor technologies and holding promise for next-generation high-performance flexible electronics.