SCIENCE CHINA Materials•2026•DOI: 10.1007/s40843-026-4502-1
Near-infrared-II (NIR-II, 1000-1700 nm) luminescent materials are pivotal for deep-tissue bioimaging and optical communication, yet their performance is often limited by low quantum yields and thermal quenching. Here, we report a thermal-enhanced NIR-II luminescence in Sb3+/Er3+ co-doped Cs3GdCl6 microcrystals synthesized via a modified Bridgman method. Under ultraviolet excitation, the co-doped microcrystals exhibit intense NIR-II emission centered at 1532 nm corresponding to Er3+: 4I13/2 → 4I15/2 transition, with a maximum relative sensitivity of 1.2% K−1 at 303 K. Notably, the integrated NIR-II emission intensity increases by 2.3-fold from 298 K to 373 K, demonstrating anomalous thermal enhancement. This behavior is attributed to the thermally activated energy transfer from Sb3+ sensitizers to Er3+ activators, as confirmed by temperature-dependent photoluminescence spectra and decay kinetics. The energy transfer efficiency reaches 86% at room temperature and further improves with rising temperature. The microcrystals also show excellent photostability, retaining 95% of initial intensity after 120 min continuous UV irradiation. Furthermore, we demonstrate a proof-of-concept wireless optical communication link using the microcrystals as a NIR-II phosphor, achieving a signal-to-noise ratio of 30 dB at 400 Hz modulation frequency. These findings provide a new strategy for designing thermal-enhanced NIR-II luminescent materials and expand their potential in temperature sensing and optical communication.
SCIENCE CHINA Materials•2026•DOI: 10.1007/s40843-026-4138-5
Electrocoagulation (EC) has emerged as a promising electrochemical technology for wastewater treatment, offering distinct advantages over conventional chemical coagulation and membrane processes. This review systematically summarizes recent advancements in EC, focusing on the underlying mechanisms, key operating parameters, and diverse technical applications. The EC process involves three stages: electrolytic oxidation and in-situ coagulant formation, destabilization of contaminants, and floc formation. Unlike chemical coagulation, EC requires no external chemical additives, and process control is achieved by adjusting current density, voltage, or electrode materials, enabling adaptation to varying wastewater qualities. The review highlights the influence of dissolved organic matter (DOM) on EC efficiency, as clarified by Luo et al. (Water Research, 2025). Furthermore, it discusses reactor design innovations, including continuous-flow and cascade-type configurations, and the role of current waveforms in mitigating electrode passivation. The integration of EC with membrane bioreactors and forward osmosis is also examined, demonstrating enhanced treatment performance and fouling mitigation. Key challenges, such as energy consumption and electrode scaling, are addressed, along with future research directions. This comprehensive analysis provides a critical framework for optimizing EC systems and scaling them for industrial wastewater treatment, emphasizing the need for holistic reactor design and process integration to achieve sustainable water reuse.
SCIENCE CHINA Materials•2026•DOI: 10.1007/s40843-026-4373-2
Infrared stealth technology demands materials with simultaneously low infrared emissivity and robust environmental stability. Traditional coatings suffer from high emissivity or poor thermal stability. Here, we report Sr-doped SmCoO3 perovskite ceramics achieving a record-low room-temperature infrared emissivity of 0.12 in the 8–14 μm atmospheric window. Systematic doping (x = 0, 0.1, 0.2, 0.3, 0.4, 0.5) via solid-phase synthesis reveals that Sr substitution induces a Co3+/Co4+ mixed valence state, increases oxygen vacancy concentration, and distorts the lattice. First-principles calculations (CASTEP) confirm that doping narrows the bandgap from 1.8 eV to 0.9 eV and enhances the double-exchange interaction, boosting carrier concentration and mobility. The optimized composition (x = 0.3) exhibits an electrical conductivity of 1.2×10^3 S/cm and a carrier density of 3.5×10^21 cm^-3, leading to strong infrared reflection. The material maintains emissivity below 0.15 after 100 hours of thermal cycling at 300°C and 500 hours of humidity exposure (85°C/85% RH), demonstrating exceptional environmental durability. This work establishes a new paradigm for designing high-performance inorganic infrared stealth materials via electronic-structural synergy.
Chinese Journal of Environmental Engineering•2026•DOI: 10.12030/j.cjee.202506019
Acidic in-situ leaching of sandstone-type uranium deposits leaves residual acid and uranium in groundwater, posing environmental risks. This study investigated the feasibility of loading hydroxyapatite (HAP) onto aquifer sandstone particles for in-situ remediation. Sandstone particles were collected from an aquifer and reacted with a HAP-generating solution for 52 days to produce sandstone/HAP composite. Batch experiments examined the effects of initial pH, initial uranium concentration, composite dosage, and interfering ions on uranium removal. Results showed successful HAP loading on sandstone surfaces. At initial pH 3, uranium concentration 5 mg/L, composite dosage 3 g/L, and 24 h reaction, uranium removal reached 95.6%. Interfering ions suppressed removal in the order Fe3+ > Mn2+ > Ca2+ > Mg2+ > SO4^2-. Removal mechanisms included electrostatic adsorption, ion exchange, and dissolution-reprecipitation, with good stability of immobilized uranium. This work validates the concept of in-situ HAP loading in aquifers and provides a basis for practical application in acidic uranium-contaminated groundwater remediation.
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.
Environmental Chemistry•2026•DOI: 10.7524/j.issn.0254-6108.2025010203
The production and disposal of lithium batteries release not only hazardous metals and particulates but also substantial amounts of harmful organic pollutants. This study focuses on N-methyl-2-pyrrolidone (NMP) to investigate the environmental release and human exposure of organic pollutants throughout the lithium battery lifecycle. Using liquid chromatography-high-resolution mass spectrometry (LC-HRMS), NMP was quantified in environmental samples from battery production and dismantling facilities, as well as in pyrolysis products from simulated thermal recovery of mainstream lithium batteries. Key release stages were identified: slurry mixing and coating/drying during production; shredding, electrolyte volatilization, and high-temperature pyrolysis during disposal. In unprotected occupational settings, estimated NMP exposure via dust ingestion exceeded reference doses, underscoring the need for health impact assessments and evaluation of protective measures. This research provides critical insights into the environmental release and population exposure of organic pollutants across the lithium battery lifecycle, informing health policy for vulnerable populations.
Journal of Environmental Engineering Technology•2026•DOI: 10.13205/j.hjgc.202604004
Tire wear particles (TWPs) are emerging pollutants and constitute the dominant type of microplastics (MPs) in urban stormwater runoff, accounting for up to 90% of MPs in some cases. They are characterized by small size, high mobility, complex composition, and significant toxicity. Current research on TWPs remains fragmented, lacking a comprehensive understanding of their environmental behaviors and pollution control in aquatic systems. This review systematically analyzes the enrichment and vectoring roles of TWPs for coexisting pollutants, and their environmental fate, including ecotoxicological impacts, detection methodologies, release of intrinsic additives, and aggregation and sedimentation behaviors. Drawing on insights from other microplastic studies, the paper explores control technologies across the pollution pathway—source, transport, and terminal treatment—and proposes feasible management strategies. Key findings indicate that TWPs can adsorb heavy metals and organic contaminants, with adsorption capacities influenced by aging processes. Their aggregation is governed by solution chemistry, with critical coagulation concentrations varying with ionic strength and pH. The release of additives such as zinc and benzothiazoles is significant, posing ecological risks. Future research should focus on real-water aggregation mechanisms, additive release under natural conditions, long-term performance of treatment facilities like constructed wetlands under TWPs stress, enzymatic degradation pathways, and integration of AI, big data, and IoT for cost-effective detection and risk modeling. This review provides a scientific basis for developing targeted pollution control measures for TWPs in aquatic environments.
Journal of Environmental Engineering Technology•2026•DOI: 10.13205/j.hjgc.202604024
To enhance sludge dewatering efficiency, an MnFe2O4/BC/PMS system was constructed for sludge disintegration. Single-factor and multi-factor experiments were conducted to investigate the effects of MnFe2O4/BC (MFB) dosage, PMS dosage, and reaction time on sludge dewatering performance, establishing the optimal process parameters and the primary-secondary relationships among environmental factors. Active species identification in the MnFe2O4/BC/PMS system revealed the main free radicals responsible for sludge disintegration and the primary pathways of EPS breakdown. Results showed that the influence order of environmental factors on sludge moisture content (Wc) and total organic carbon (TOC) was MFB > PMS > reaction time, while the interaction effects followed MFB-PMS > PMS-reaction time > MFB-reaction time. Optimal dewatering occurred at MFB dosage of 132.99 mg/g DS, PMS dosage of 421.80 mg/g DS, and 18 min reaction time, achieving Wc of 45.8% and TOC of 489.2 mg/L. The ·OH and SO4−· radicals released from MnFe2O4/BC-activated PMS oxidized protein main chains, causing peptide chain breakage. This primarily reduced protein content in sludge from 174.6 mg/L to 75.7 mg/L, with TB-EPS protein content decreasing from 91.8 mg/L to 36.3 mg/L, thereby reducing EPS hydrophilicity and improving sludge dewatering efficiency.
Environmental Chemistry•2026•DOI: 10.7524/j.issn.0254-6108.2024122406
The effects of different vegetation types on soil quality in the Green Heart Area of the Changsha-Zhuzhou-Xiangtan City Cluster were evaluated to provide a reference for selecting suitable afforestation species and improving forest soil quality. Seven vegetation types (mixed forest, broad-leaved forest, coniferous forest, economic forest, shrub forest, grassland, and abandoned cropland) with similar site conditions were studied. Eleven soil physicochemical indicators were measured, and soil quality was assessed using principal component analysis (PCA), Pearson correlation, total data set (TDS), minimum data set (MDS), and entropy-weighted TOPSIS methods. Results showed no significant differences in soil water content, soil bulk density, and C:N ratio among vegetation types, while significant differences were found in total porosity, capillary porosity, saturated water content, field water holding capacity, total carbon, total nitrogen, available potassium, and available phosphorus. Compared with abandoned cropland, soil water content, total porosity, field water holding capacity, saturated water content, total carbon, total nitrogen, available potassium, and available phosphorus were significantly higher, and soil bulk density was significantly lower. Mixed forest soil exhibited the highest values for field water holding capacity, total porosity, saturated water content, total nitrogen, total carbon, available potassium, and available phosphorus. Correlation analysis revealed that soil bulk density was extremely significantly negatively correlated with soil water content, total porosity, and saturated water content, and significantly negatively correlated with field water holding capacity, total carbon, and total nitrogen. Soil capillary porosity, field water holding capacity, total porosity, and saturated water content were extremely significantly positively correlated with soil nutrients, while soil bulk density showed varying degrees of negative correlation with soil chemical nutrients. Soil chemical properties and stoichiometric ratios showed varying degrees of significant positive correlation. The order of soil quality under different vegetation types was mixed forest > broad-leaved forest > shrub forest > economic forest > grassland > coniferous forest > abandoned cropland. Mixed forest soil quality was the best and significantly higher than other vegetation types, with significant differences among vegetation types. Mixed forest soil quality was clearly superior. In vegetation restoration and plantation establishment in the Green Heart Area, the principle of matching tree species to site conditions should be followed, with a focus on mixed forests to improve overall soil quality and enhance ecological benefits of artificial vegetation restoration.
SCIENCE CHINA Materials•2026•DOI: 10.1007/s40843-025-3809-y
The development of hydrogels that simultaneously achieve high strength and good toughness remains a critical challenge in soft material science, particularly for applications in flexible electronics, soft robotics, and biomedical devices. Conventional approaches often suffer from a trade-off between mechanical robustness and functional performance. In this work, we present a novel solvent-driven dual-network entanglement strategy to fabricate a strong and tough poly(vinyl alcohol) (PVA)-based organo-hydrogel by synergistically combining isopropanol (IPA) solvent substitution to induce dense polymer chain entanglement and a sodium alginate (SA) ionic crosslinked network as a dynamic energy-dissipation phase. The resulting organo-hydrogel exhibits excellent mechanical performance with a tensile strength of 3.18 MPa and a toughness of 16.65 MJ/m3, representing increases of approximately 17 and 49 times that of conventional PVA hydrogels, respectively. Furthermore, the organo-hydrogel displays superior swelling resistance and long-term stability in aqueous environments, enabling reliable operation in challenging conditions such as underwater motion sensing and wearable strain detection. Morphological analyses reveal the critical role of solvent-mediated chain reorganization and dual-network interactions in achieving these properties. This work not only provides a versatile platform for designing robust gel materials but also offers fundamental insights into solvent-network interactions for advanced soft material engineering.
Journal of Fuel Chemistry and Technology•2026•DOI: 10.1016/S1872-5813(26)60655-X
Defect-induced nonradiative recombination critically restricts the power conversion efficiency (PCE) and stability of perovskite solar cells (PSCs). Lewis base additives show great promise in defect passivation, but current screening methods rely heavily on empirical trial and error and lack clear design principles, making it difficult to efficiently discover high-performance candidate materials. Here, we present a machine learning (ML) framework to intelligently screen Lewis base molecules for defect passivation. We trained six ensemble models on a dataset of 146 experimental data points, with Light Gradient Boosting Machine (LightGBM) yielding the best classification performance (87% accuracy). Shapley Additive Explanations (SHAP) interpretability analysis subsequently identifies the highest occupied molecular orbital (HOMO) energy (−7.5 to −6.3 eV), additive concentration (2.5 to 6.5 mg/mL), and simplified molecular backbones (O atom ≤ 2, C atom < 5) as critical design criteria. The ML prediction was experimentally validated: (S)-pyrrolidine-3-carboxylic acid ((S)-PCA) and 2-methyl-1,3-cyclopentanedione (MCPD) (Class Ⅱ) improved PCE by 2.22% and 2.01%, respectively, while 3-hydroxymethyl-3-methylbutanenitrile (3-HMBN) (Class Ⅰ) showed minimal gain. Density functional theory (DFT) calculations further confirmed the stronger binding affinities and elevated defect formation energies of Class Ⅱ additives. Notably, the champion (S)-PCA device achieved a PCE of 24.05%. This work established an ML-accelerated paradigm for the rational design of defect passivators, bridging data science and photovoltaics.
Journal of Fuel Chemistry and Technology•2026•DOI: 10.1016/S1872-5813(26)60762-1
The CO2 dry reforming of methane (DRM) is pivotal for CO2 utilization within the dual-carbon framework, offering advantages in carbon reduction and value-added chemical production. However, shaped catalysts suitable for industrial-scale DRM remain limited. This work constructs a monolithic catalyst using honeycomb cordierite as the structural support, systematically investigating the effects of organic and inorganic binders on coating structure and catalytic performance. Comparative studies reveal that the active coating fabricated with inorganic aluminum sol exhibits a continuous uniform morphology and excellent adhesion strength. During high-temperature calcination, elemental diffusion within Al2O3 networks bridges the cordierite surface with active catalyst particles, forming a (Ni-Mg)AlxO4 composite structure. This creates robust metal-support interactions between active sites and the residual alumina matrix. The interconnected mesoporous framework provides superior pore confinement, contributing to strong coating adhesion, enhanced activity, and improved resistance to carbon deposition in the monolithic m-NCM-Al-sol catalyst. In contrast, coatings derived from inorganic silica sol suffer from detachment and activity loss due to heterogeneous surface structures and poor adhesion. Organic binders demonstrate inferior performance in macroscopic coating uniformity, adhesion strength, mesoporous confinement, and localized electronic effects, resulting in the poorest catalytic performance. By optimizing aluminum sol coating parameters—binder content, active component dosage, and coating cycles—a synergistic balance between coating thickness and mass transfer is achieved. The optimized catalyst demonstrates excellent DRM performance, providing insights for constructing high-performance shaped catalysts with cordierite coatings.
Environmental Chemistry•2026•DOI: 10.7524/j.issn.0254-6108.2025041502
Microplastics (MPs), defined as plastic particles smaller than 5 mm, are ubiquitous environmental contaminants with documented presence in urban, rural, marine, remote, and polar atmospheres. The atmosphere serves as a primary medium for their long-range transport, raising concerns regarding climate interactions and human health. This review synthesizes recent advances in atmospheric MPs research, encompassing sampling strategies, pretreatment protocols, analytical techniques, occurrence characteristics, and ecological ramifications. Passive and active sampling methods are delineated, with active samplers enabling quantitative flux measurements. Pretreatment typically involves sequential steps of sieving, density separation, digestion, staining, and filtration to isolate MPs from complex matrices. Identification relies on visual inspection, micro-Fourier transform infrared spectroscopy (μ-FTIR), micro-Raman spectroscopy, laser direct infrared imaging (LDIR), and mass spectrometry. Reported atmospheric MPs predominantly exhibit dimensions below 700 μm, with fibrous morphologies being most prevalent. Color distribution is dominated by black, followed by white and transparent particles. Over 20 polymer types have been identified, with textiles, tire wear, and dust identified as principal sources. Atmospheric MPs can influence solar radiation balance, cloud formation processes, and pose risks to flora, fauna, and human health. However, research remains nascent; standardization of sampling and analytical protocols, along with comprehensive toxicological assessments, are critical knowledge gaps requiring urgent attention.
Environmental Chemistry•2026•DOI: 10.7524/j.issn.0254-6108.2025042702
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.