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RW
Verified CAS / Academic Author20 Decoded Studies

Prof. Runchuan Wang

East China University of Science and Technology

Co-Affiliations:School of Metallurgical Engineering, Anhui University of Technology, Ma'anshan, Anhui 243032, ChinaKey Laboratory of Biobased Polymer Materials, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of SciencesNot explicitly stated in the provided text; likely Chinese Academy of Sciences or a university.

Research Publications & English Decoded Briefs

Showing 20 publications
SCIENCE CHINA Materials2026DOI: 10.1007/s40843-025-3848-7

Exciton Tuning and Charge Steering in Donor-Acceptor Covalent Triazine Frameworks toward Boosted Photocatalytic Oxidation

Conventional heterogeneous photocatalysts often suffer from insufficient light absorption, rapid charge recombination, and a lack of specific reactive sites for efficient photocatalytic oxidation. To overcome these limitations, we propose a molecular polarization engineering approach utilizing structurally well-defined donor (D)-acceptor (A) covalent triazine frameworks (CTFs). The construction of dipole-induced built-in electric fields within the D-A-structured CTFs enables enhanced exciton dissociation and facilitates directional charge transfer. Specifically, the asymmetric A1-D-A2 moiety enhances molecular polarization in the dual-acceptor system CTF-TBT (A1-D-A2), enabling efficient charge separation through multiple electron-withdrawing units. This structural design promotes directional electron transfer toward the secondary acceptor (benzothiazole, A2), while simultaneously concentrating holes on the donor unit. Consequently, the A2 moiety acts as a site for efficient O2 activation via electron accumulation, whereas the highly oxidized donor unit provides strongly positive holes (h+) that facilitate substrate oxidation. Experimental and DFT calculation results confirm that CTF-TBT demonstrates highly enhanced photocatalytic oxidation performance, which can be attributed to its multi-channel charge separation mechanism and spatially separated redox-active sites. This study highlights the effectiveness of molecular dipole engineering in designing heterogeneous photocatalysts with controlled charge transfer pathways and improved redox capabilities. The proposed design principles provide a universal approach for promoting solar-driven chemical synthesis applications.

SCIENCE CHINA Materials2026DOI: 10.1007/s40843-025-3738-1

Natural Biomass-Derived Polysaccharide Materials for Flexible Wearable Smart Textiles

The escalating demand for intelligent and functional textiles, driven by technological advancements, has shifted focus from conventional attributes like warmth and aesthetics to smart functionalities. Natural biomass-derived polysaccharides, owing to their biocompatibility, biodegradability, renewability, and unique chemical structures, are pivotal for next-generation flexible wearable smart textiles. This review systematically outlines common natural polysaccharides (e.g., cellulose, chitosan, starch, alginate) used in such textiles, detailing their structural features and modification strategies. It critically evaluates current fabrication methods, highlighting their advantages and limitations. The performance characteristics, action mechanisms, and application scenarios of polysaccharide-based smart textiles are examined, with emphasis on healthcare, motion tracking, smart clothing, and energy storage/management. The review concludes by addressing existing challenges and proposing future directions for integrating polysaccharide materials into smart textile systems, aiming to guide the development of efficient, green flexible wearable devices.

SCIENCE CHINA Materials2026DOI: 10.1007/s40843-025-3610-7

Dual-confinement of reconstructed covalent organic framework for enhanced CO2 electrolysis in acid

Electrochemical CO2 reduction reaction (CO2RR) offers an attractive route to produce value-added multicarbon (C2+) products, yet suffers from competing hydrogen evolution and monocarbon production. Here, we propose a dual-confinement effect on CO2 reactant and *CO intermediate, induced by tuning the pore configuration of reconstructed covalent organic frameworks (RC-COFs). The highly crystalline microporous RC-COF-1, when coated on a Cu electrode, enhances local CO2 concentration and restricts CO diffusion, thereby promoting C-C coupling. In acidic electrolyte, the RC-COF-1@Cu electrode achieves a maximum C2+ Faradaic efficiency (FE) of 67.0% at 500 mA cm−2, while maintaining a total carbon product FE above 90% across a broad current density range (100–500 mA cm−2). Experimental and theoretical analyses confirm that the ordered micropores of RC-COF-1 modulate reactant adsorption and intermediate diffusion, leading to improved C2+ selectivity. This work underscores the critical role of COF pore architecture in microenvironment engineering for heterogeneous catalysis.

Journal of Environmental Engineering Technology2026DOI: 10.13205/j.hjgc.202604025

A Multi-Pollutant Time-Series Prediction Model Based on Long Short-Term Memory Networks

To meet the minute-level early-warning requirements for odor and multi-pollutant emissions at waste treatment facilities, this study proposed a multivariate short-term time-series prediction framework applicable to multi-tier scenarios covering source and boundary points (i.e., workshops and plant boundaries). Based on continuous online monitoring data with a 5-second resolution, a long short-term memory (LSTM) model using a sliding-window and recursive multi-step prediction strategy was constructed to jointly model odor concentration (OU) and pollutants including VOCs, NH3, H2S, and CH3SH (mg/m³). An evaluation protocol aligned with environmental supervision practice was established, incorporating mean absolute error (MAE), root mean square error (RMSE), goodness-of-fit (R²), skill scores (SS) relative to a persistence baseline, and threshold-based error stratification to characterize uncertainty during peak emission periods. The results showed that at workshop monitoring sites with relatively stable operating conditions, VOCs, NH3, H2S, and CH3SH exhibited a high goodness of fit and low prediction errors. In contrast, at boundary sites affected by plume arrival delays and diffusion-dilution non-stationarity, OU and VOCs displayed significantly amplified errors during peak episodes, and the skill score advantage over the baseline became unstable at certain sites. Stratified analysis consistently revealed that non-peak periods outperformed peak periods, indicating that event-driven fluctuations were the main sources of error. Accordingly, this study suggested incorporating exogenous variables such as wind speed and direction, ventilation and gate access control, and operational rhythms, along with peak-sensitive loss functions, into the model to enhance its capacity to characterize and provide early warnings for transient emission pulses. Overall, this study established a reusable methodological baseline and evaluation paradigm for minute-scale multi-pollutant prediction, providing quantitative support for the operational management and source-to-boundary coordinated control of waste treatment facilities.

Journal of Fuel Chemistry and Technology2026DOI: 10.1016/S1872-5813(25)60625-6

Design of Catalysts for Electrochemical Nitric Oxide Reduction to Ammonia Based on Stacked Ensemble Learning

The electrocatalytic reduction of nitric oxide to ammonia (NORR) is a key green energy conversion technology. Its efficiency relies on high-performance electrocatalysts to enhance both ammonia yield (YNH3) and Faradaic efficiency (FNH3). Conventional experimental screening methods are resource- and time-intensive. Here, machine learning combined with SHAP feature analysis was employed to establish a stacked ensemble model integrating multiple algorithms, enabling systematic investigation of key descriptors governing NORR performance based on an experimental dataset. Evaluation of eight model algorithms revealed that the Stacked-SVR model achieved an R² of 0.9223 and RMSE of 0.0608 for predicting YNH3 on the test set, while the Stacked-RF model achieved an R² of 0.9042 and RMSE of 0.0900 for predicting FNH3. The stacked ensemble model integrates strengths of individual algorithms, demonstrating strong prediction performance while avoiding overfitting. SHAP analysis revealed that Cu content in catalyst composition has the most significant impact on catalytic performance. Moreover, the combination of wet chemical reduction synthesis, carbon fiber (CF) conductive substrate, and HCl electrolyte is more favorable for enhancing catalytic activity. Additionally, moderately lowering working potential, controlling electrolyte volume at low-to-medium levels, reducing catalyst loading, and increasing electrolyte concentration synergistically enhance both YNH3 and FNH3.

Environmental Chemistry2026DOI: 10.7524/j.issn.0254-6108.2025010804

Research Progress on Heterogeneous Fenton Technology Based on Carbon/Iron-Based Catalysts and Physical Field-Assisted Systems

Heterogeneous Fenton technology employs solid catalysts to activate H2O2, generating hydroxyl radicals (·OH) that oxidatively degrade organic pollutants. Among reported catalysts, iron-based materials are most prevalent but suffer from insufficient active sites and sluggish Fe(III)/Fe(II) cycling. Compositing iron with carbon materials increases active site density and accelerates Fe(II) regeneration, thereby enhancing catalytic efficiency. This review summarizes recent advances in carbon/iron-based heterogeneous Fenton catalysts, analyzing reaction mechanisms and characteristics for organic pollutant removal. It also discusses external energy field-assisted strategies (e.g., photo-, electro-, and ultrasound-assisted) that augment reaction kinetics. The paper concludes with perspectives on future development of carbon/iron-based Fenton-like materials, emphasizing the need for scalable synthesis and mechanistic elucidation. Key challenges include maintaining stability under continuous operation and achieving cost-effective production. The review highlights that carbon/iron composites with optimized interfacial properties can significantly improve H2O2 utilization and broaden pH applicability, addressing limitations of conventional Fenton processes. Future research directions include designing catalysts with tailored porosity and surface functionality, and integrating physical fields to synergistically enhance pollutant mineralization.

The Chinese Journal of Process Engineering2026DOI: 10.12034/j.issn.1009-606X.225250

Research Progress and Intelligent Trend of Slag Foaming Prediction

Slag foaming is a critical phenomenon in electric arc furnace (EAF) steelmaking, enhancing thermal efficiency, suppressing metal splashing, and stabilizing the refining process. Accurate prediction and control of slag foaming are essential for green and efficient steelmaking. This review systematically examines research progress on slag foaming prediction, clarifying the applicability, advantages, and limitations of different predictive methods to support intelligent control of foamy slags. Following the framework of 'influencing factors-prediction methods-development trends', the study summarizes the coupling effects of multiple variables such as basicity, viscosity, surface tension, suspended particles, gas parameters, and temperature on foam formation and stability. It compares five major prediction approaches: empirical formulas, dimensionless modeling, thermodynamic calculations, computational fluid dynamics (CFD) simulations, and machine learning models, analyzing their core concepts, merits, and constraints. Results indicate that single models often struggle to balance real-time capability and accuracy, particularly under multi-variable coupling and complex operating conditions. Therefore, a hybrid prediction framework combining mechanism-based and data-driven models is proposed, emphasizing physical constraints, multi-scale coupling, and multi-source data fusion. This integrated approach is expected to advance slag foaming prediction from 'computable' to 'controllable and adjustable', offering methodological insights for the development of green and intelligent EAF steelmaking.

The Chinese Journal of Process Engineering2026DOI: 10.12034/j.issn.1009-606X.225141

Effect of the Number of Clogged Bottom-Blowing Elements on the Flow Characteristics of Liquid Steel in Converter

This study established a three-dimensional transient gas-liquid two-phase flow model based on a 150-tonne converter to investigate the influence of the number of clogged bottom-blowing elements on the stirring efficiency of the molten pool. The numerical simulation results were validated against actual converter operating conditions. The findings revealed that the primary reason for deteriorated flow characteristics under multiple clogged tuyeres was the overall reduction in stirring energy input from the bottom-blowing gas. Specifically, when the number of clogged tuyeres reached three, the numerically simulated mixing time increased from 150.6 s to 219.3 s, a significant increase of 45.62%. This numerical result was in good agreement with water model experiments, indicating that prompt furnace bottom maintenance and tuyere replacement should be considered under such circumstances. At the same bottom-blowing intensity, the effective stirring area of a single inner-ring tuyere was 0.919 m2, while that of a single outer-ring tuyere was 1.651 m2. The combined effective area achieved through the synergy of inner and outer ring tuyeres was 2.940 m2, which was 14.4% greater than the sum of their individual areas. Clogging disrupted this synergistic stirring effect. A single clogged tuyere had a negligible impact on the distribution of dead zones. However, when tuyeres in both the inner and outer rings were clogged, dead zones became more numerous and concentrated. With 3 and 4 clogged tuyeres, the dead zone volume reached 3.703 and 5.946 m3, accounting for 17.31% and 27.79% of the total molten pool volume, respectively. An industrial plant trial conducted based on the numerical simulation scheme showed that key performance indicators deteriorated as the number of clogged tuyeres increased. With three clogged tuyeres, the average end-point oxygen content reached 0.0669wt%, which was 22.1% higher than that under non-clogged conditions. Concurrently, the total iron content in the slag reached 19.44%, a 24.5% increase compared to the non-clogged baseline.

SCIENCE CHINA Materials2026DOI: 10.1007/s40843-025-3754-1

Chemically Recyclable Chiral Polyesters Synthesis via Kinetic Resolution Polymerization Strategies

Chiral polyester materials that integrate chemical recyclability with high performance have become a focal point in sustainable polymer research. Their thermal and mechanical properties are intrinsically linked to polymer microstructure, with stereoregular chiral polyesters typically exhibiting superior crystallinity and performance relative to atactic counterparts. Asymmetric kinetic resolution polymerization (AKRP) has emerged as a powerful method for synthesizing stereoregular chiral polyesters from racemic monomers, utilizing chiral catalysts to selectively recognize and polymerize one enantiomer while leaving the other unreacted. Recent advances have expanded AKRP scope to include targeted recognition of specific substrate sites based on chiral discrimination. This review summarizes recent progress in AKRP across representative monomer systems, categorized by ring size, highlighting breakthroughs in catalyst design, mechanistic understanding, and material properties. Key metrics such as kinetic resolution coefficient (k_rel) and selectivity factor (s-factor) are discussed as quantitative measures of stereoselective control. The review underscores the potential of AKRP to circumvent costly enantiomer separation, offering a promising route to advanced chiral polyesters with tailored properties for applications ranging from biodegradable plastics to biomedical materials.

SCIENCE CHINA Materials2026DOI: 10.1007/s40843-025-3933-9

MOF-Based Hierarchical Bilayer Membranes for Radiative Evaporative Cooling in Fruit Preservation

The global cold chain consumes vast amounts of energy and emits greenhouse gases, while many regions lack proper refrigeration. To address this, we developed a dual-layer electrospun membrane (PZ-PML) for energy-free fruit preservation. The top PVDF-HFP/ZIF-8 layer offers 97.64% solar reflectance and 92.5% mid-infrared emissivity, providing 70 W/m2 radiative cooling. The bottom PAN/MIL-101/LiCl layer, with 2.18 g/g water uptake at 80% RH, delivers ~156 W/m2 evaporative cooling, lowering surface temperature by 6.1 °C under ~400 W/m2 irradiation. The membrane also shows ≥99% antibacterial efficiency against E. coli and S. aureus. Applied to strawberries, it reduced dehydration to 20.2% after 9 days, compared to 68.2% and 74.4% in controls. Additionally, it demonstrates durability, superhydrophobicity, and UV stability. This scalable solution offers energy-free fruit cooling, reducing postharvest losses while maintaining quality and safety.

Journal of Fuel Chemistry and Technology2026DOI: 10.1016/S1872-5813(26)60652-4

Fluorescence Nanoscopy Unveils the Black Box of Industrial Zeolite Catalysts: Mechanisms and Optimization of Mass Transfer-Acidity-Coke Formation

The performance of industrial zeolite catalysts, exemplified by fluid catalytic cracking (FCC) catalysts, is governed by microscopic behaviors including mass transfer, acidity, and coking. Conventional characterization techniques such as XRD, N2 physisorption, and TPD provide bulk-averaged or static ex situ information, failing to resolve dynamic processes under realistic reaction conditions. Recent advances in super-resolution fluorescence imaging enable nanoscale visualization of these key processes. This review systematically summarizes three critical applications: (1) Mass transfer diffusion: heterogeneous diffusion of reactant molecules within hierarchical pore networks is revealed, quantifying diffusion barriers and tortuosity. (2) Acid site accessibility: nanoscale localization of acid sites and their accessibility is achieved, correlating with catalytic activity. (3) Coking behavior: spatiotemporal evolution of coke species is identified, linking coke precursors to deactivation. The review elaborates how super-resolution imaging deepens understanding of fundamental catalytic mechanisms, providing theoretical support for rational design of high-performance catalysts through pore structure optimization, acid site regulation, and coking suppression. Current challenges and future directions are discussed, emphasizing the need for in situ correlation with catalytic performance.

Chinese Journal of Environmental Engineering2026DOI: 10.12030/j.cjee.202511076

Distribution and Enrichment Characteristics of Heavy Metals in Soil and Plants Along an Altitude Gradient in the Northern and Southern Mountains of Lhasa

This study investigated the altitudinal distribution and enrichment characteristics of heavy metals in the soil-plant system of the northern and southern mountains of Lhasa on the Tibetan Plateau. Soil and dominant plant samples were collected from three sites along an elevation gradient from 3,650 to 4,150 m, and concentrations of Cr, Cd, Cu, Zn, Ni, As, and Pb were analyzed. Soil heavy metal concentrations ranged from 0.06 to 184.4 mg·kg−1, with all elements except Cd and Pb exceeding local background values. Plant heavy metal concentrations were within normal ranges, indicating no obvious stress. Correlation analysis revealed significant positive correlations between soil Zn and Cd, Cr and Ni, and plant Zn and Cu. Except for Cr, Cu, and Cd, plant and soil concentrations of the same element were significantly correlated. Bioconcentration factor (BCF) analysis showed that most plants had weak enrichment capacity (BCF < 1), but five species, including Ephedra sinica and Rheum likiangense, exhibited BCF > 1 for Cd, with R. likiangense showing the highest BCF of 4.01. The enrichment capacity varied with altitude and species. Potential ecological risk assessment indicated that Cd posed a relatively high risk in plants, warranting attention. This study fills a gap in understanding the spatial distribution and enrichment of heavy metals in this region, providing a scientific basis for ecological management and environmental protection.

Environmental Chemistry2026DOI: 10.7524/j.issn.0254-6108.2025040102

Performance and Mechanism of Calcium Peroxide for Fluoride Removal and Site Energy Distribution

Calcium peroxide (CaO2) with a rich porous structure was synthesized via chemical precipitation for efficient fluoride removal from aqueous solutions. The adsorbent was characterized by SEM, BET, LPSA, and XRD, revealing a mesoporous material with a total pore volume of 0.51 cm3·g−1. Batch experiments investigated the effects of adsorbent dosage, initial fluoride concentration, reaction time, pH, and coexisting anions. Adsorption kinetics followed a fractal-like pseudo-first-order model, with intraparticle diffusion as the rate-limiting step. Equilibrium data were well described by the Sips isotherm, predicting a maximum adsorption capacity of 479.8 mg·g−1. Site energy distribution analysis indicated a normal distribution with an average energy of 13.36 kJ·mol−1. Mechanistic studies using FTIR and XPS revealed that fluoride removal proceeds via surface precipitation, ligand exchange, and electrostatic attraction. The high density of active sites contributes to the exceptional defluoridation performance, positioning CaO2 as a promising adsorbent for fluoride-contaminated water treatment.

SCIENCE CHINA Materials2026DOI: 10.1007/s40843-025-4107-x

Quaternary Ammonium-Mediated I+ Complexation for Stable High-Energy Four-Electron Aqueous Fiber Zinc-Iodine Batteries

Aqueous fiber zinc-iodine batteries (FZIBs) with four-electron redox exhibit inherent safety and high energy density for wearable electronics. Nevertheless, their practical implementations are hindered by unsatisfactory cycling stability and low realistic energy density, mainly caused by severe H2O-induced nucleophilic attack toward iodine species and poor zinc anode reversibility. Here, we report a quaternary ammonium-mediated coordination strategy to simultaneously address the irreversible cathode/anode redox behavior and thus promote the electrochemical performance of four-electron FZIBs. The cationic choline ion (Ch+) induces complexation with ICl2− via electrostatic interaction, homogenizing the electron cloud density and suppressing irreversible hydrolysis of I+ species, enabling a reversible near-theoretical high capacity of 418.3 mAh g−1. Meanwhile, preferentially adsorbed Ch+ on the zinc anode surface creates positively charged shielding layers, mitigating the tip effect caused by localized electric field and achieving robust zinc stripping/plating. The enhanced cathode/anode reversibility and improved interfacial stability enable stable FZIBs operation for over 20,000 cycles at 20.0 A g−1. Moreover, successful integration of FZIBs into electronic textiles with glucose and cardiac rhythm sensors demonstrates great potential for next-generation wearable electronics.

Journal of Fuel Chemistry and Technology2026DOI: 10.1016/S1872-5813(26)60710-4

Reaction Network Database for Fast Pyrolysis of Vanillyl Alcohol Based on Molecular Wavefunction Descriptors

Lignin pyrolysis is a promising route for sustainable production of high-value phenolic chemicals, yet the intricate radical reaction network remains a major bottleneck to optimizing product selectivity. This work constructs a standardized DFT computational database that systematically describes the fast pyrolysis of vanillyl alcohol at 823.15 K. The database features three key components: primary reaction pathways, thermodynamic energy barriers, and atomic-level electronic fingerprints. The dataset covers primary reaction pathways, secondary rearrangements, and both global and local reactivity indices of key intermediates. Notably, it innovatively integrates electronic-structure fingerprints, filling the gap in reaction-network–electronic-property correlation data. Standardized computational workflows and rigorous quality control ensure accuracy, consistency, and reproducibility. The public release of this dataset provides a reliable theoretical benchmark for mechanistic studies of lignin pyrolysis and offers foundational data support for rational design of new catalysts and refinement of reaction kinetic models. Ultimately, this database not only provides an important reference for data-driven catalyst development but also lays a theoretical foundation for precise regulation of lignin depolymerization.

Journal of Fuel Chemistry and Technology2026DOI: 10.1016/S1872-5813(26)60693-7

A dataset for electrocatalytic hydrogen evolution reaction performance of non-noble transition metal phosphides

This dataset compiles the hydrogen evolution reaction (HER) performance data of 203 non-noble transition metal phosphide (TMP) catalysts, covering detailed information on catalyst preparation (e.g., phosphating temperature, precursor, synthesis method), chemical composition (mass fractions of elements such as Ni, Co, Fe, P, Mo, W and Zn), and testing conditions (e.g., electrolyte type and concentration, electrode substrate). The key parameters for catalytic performance include the overpotential at 10 mA/cm2 (η10) and the Tafel slope. This dataset has been rigorously extracted, cleaned, and standardized to ensure a high degree of structure and machine readability. This provides a reliable data foundation for data-driven methods, such as machine learning and statistical modeling, enabling rapid screening and design of high-performance HER catalysts, supporting performance prediction, in-depth structure-activity analysis and the rational development of novel catalysts.

Environmental Chemistry2026DOI: 10.7524/j.issn.0254-6108.2025042702

Photochemical Reaction Characteristics and Source Apportionment of VOCs Based on Estimation of Initial Volume Mixing Ratios during Summer in Dalian

This study estimated initial volume mixing ratios of volatile organic compounds (VOCs) in Dalian from June 1 to August 31, 2024, using a photochemical age-based parameterization method, and performed source apportionment with positive matrix factorization (PMF). Observed average TVOCs concentration was 12.49×10⁻⁹, comprising alkanes (84.2%), alkenes (10.4%), and aromatics (5.4%). Corrected initial TVOCs was 14.93×10⁻⁹, indicating a loss rate of 16.4%. Loss rates were highest for alkenes (53.2%), followed by aromatics (23.3%) and alkanes (6.8%). Ozone formation potential (OFP) averaged 21.31×10⁻⁹ (observed) and 38.75×10⁻⁹ (initial), with an OFP loss rate of 45.0%, distributed as alkenes (56.4%), aromatics (32.7%), and alkanes (10.3%). During ozone pollution episodes, TVOCs chemical loss was 1.9 times that of non-pollution periods, with alkene loss reaching 61.6%; OFP loss was 1.2 times higher, with alkenes contributing 88.4% to TVOCs loss. Secondary organic aerosol (SOA) formation potential from 08:00–17:00 was 1.51×10⁻¹ μg·m⁻³, with 99.4% from aromatics and toluene contributing 68.3%. PMF identified five sources: motor vehicles (49.6%), oil and gas volatilization (20.7%), petrochemical enterprises (12.6%), industrial processes (11.2%), and solvent use (5.9%). OFP modeling indicated motor vehicles contributed most to ozone formation (41.1%), followed by petrochemical enterprises (35.8%). During ozone pollution, PMF based on initial concentrations showed petrochemical sources had the highest OFP contribution (42.5%), whereas observed concentrations indicated motor vehicles as the top contributor (42.5%). This discrepancy underscores the necessity of correcting for photochemical losses in source apportionment studies.

SCIENCE CHINA Materials2026DOI: 10.1007/s40843-025-4057-4

Machine Learning-Assisted Rapid Development of High Performance Flexible Lead-Free Radiation Shielding Gels

The escalating use of ionizing radiation in medical and industrial applications necessitates lead-free, flexible, and sustainable shielding materials. Current development relies on empirical trial-and-error, which is inefficient. This study introduces a machine learning-assisted Monte Carlo simulation strategy for rapid optimization of metal filler compositions for X-ray attenuation across 40–120 kV. Guided by this AI-driven approach, polyvinyl alcohol (PVA)-based gels containing uniformly dispersed Bi/W/Gd2O3 nanoparticles were developed, forming within 1 minute at -20°C using a PVA-DMSO/H2O co-solvent system. The optimized gel with 50 wt% metal loading exhibits exceptional mechanical properties: tensile strength of 1.76 MPa, toughness of 6.3 MJ m−3, and elongation of 600%. It achieves >98% X-ray shielding efficiency at 5 mm thickness, outperforming lead composites at 120 kV. The physically cross-linked network provides recyclability and anti-freezing capability, retaining flexibility at -50°C. This work establishes a data-driven paradigm for designing high-performance radiation-shielding materials, demonstrating AI's potential to accelerate materials discovery and enable scalable fabrication of eco-friendly protective systems.

SCIENCE CHINA Materials2026DOI: 10.1007/s40843-025-4026-0

A metabolizable benzothiazole-based covalent organic framework nanodot enables photothermal-boosted cuproptosis for synergistic cancer therapy

Copper-based synergistic therapy integrating chemodynamic therapy (CDT) and cuproptosis holds promise for tumor treatment but faces clinical translation hurdles including long-term toxicity, low catalytic efficiency, off-target effects, and copper ion efflux. Here, we developed metabolizable ultrasmall benzothiazole-based covalent organic framework nanodots (COF NDs) via click condensation followed by liquid exfoliation. The dense donor-acceptor configurations confer a high photothermal conversion efficiency of 51.16%, while bisthiazole motifs enable specific Cu2+/Cu+ chelation (0.56:0.44), facile PEGylation, and mitochondrial targeting. These features enhance physiological stability and enable tumor-specific photothermal-catalytic synergy. Mitochondrial accumulation elevates intracellular copper to a critical threshold, inducing cuproptosis and suppressing tumor growth and metastasis. The NDs are efficiently excreted via renal and fecal pathways, demonstrating favorable biocompatibility and clinical potential as copper-based nanotherapeutics.

SCIENCE CHINA Materials2026DOI: 10.1007/s40843-026-4216-7

Boosting efficiency to 13.07% in flexible Cu2ZnSn(S,Se)4 solar cells via heterojunction regulation of defects and stress

Flexible Cu2ZnSn(S,Se)4 (CZTSSe) solar cells are promising for lightweight and mechanically pliable photovoltaics, yet their performance is limited by severe non-radiative recombination and residual stress. Here, we report a sealed constant temperature (SCT) annealing strategy that simultaneously optimizes the CZTSSe/CdS heterojunction and alleviates stress. Under uniform mild thermal conditions (85°C, 5 h), SCT annealing promotes gradient diffusion of Cd2+ into the absorber, partially substituting Zn2+, which optimizes band alignment, passivates interface defects, and suppresses near-interface CuZn defects. This reduces open-circuit voltage loss and improves fill factor. The flexible device achieves a power conversion efficiency of 13.07%, a significant improvement over the reference (12.1%). The SCT strategy also enhances mechanical flexibility by reducing residual stress. Our findings provide a controllable route to advance both efficiency and flexibility of flexible CZTSSe solar cells.