Search Results (5,444)

Polysaccharide-based organic−inorganic hybrid carriers combine renewable polymer matrices with inorganic phases that can modify mechanical integrity, swelling, barrier performance, payload retention, and release behavior. This review critically evaluates alginate as a reference matrix together with chitosan, cellulose/nanocellulose, starch/maltodextrin, pectin, carrageenan, and related polysaccharides, focusing on how matrix chemistry, inorganic-phase properties, interfacial interactions, and fabrication route govern encapsulation efficiency, loading, structural stability, swelling, mechanical and barrier properties, storage retention, and release kinetics. Silica and mesoporous silica, clays and halloysite, layered double hydroxides (LDHs), metal oxides, hydroxyapatite, magnetic particles, and metal−organic frameworks are compared according to their reservoir, reinforcing, diffusion-controlling, responsive, and safety-related functions. Representative quantitative findings illustrate the importance of hybrid architecture; for example, incorporation of LDHs into an alginate matrix reduced erythropoietin release after 108 h from 86% to 24% while increasing mechanical performance by approximately 5–30-fold. In this review, particular attention is given to volatile and bioactive compounds, for which storage retention, oxidation stability, headspace behavior, and application-relevant release are as important as initial encapsulation efficiency. Key challenges, such as long-term stability, standardization of release studies, scalability, safety assessment, and performance in real formulations, are also discussed, together with future directions for sustainable, application-specific hybrid carrier systems. Overall, the review provides a structure−property-application framework for selecting matrix−filler-processing combinations for controlled-release systems. Full article

The pathogenesis and progression of liver diseases are characterized by marked zonal heterogeneity, yet conventional research paradigms have long overlooked this intrinsic spatial logic. Ferroptosis and cuproptosis have been widely implicated in liver disease; however, their precise intralobular distribution and zonal susceptibility patterns remain poorly defined. We present a narrative synthesis of the literature on the spatial zonation of hepatic metabolism, redox homeostasis, and metal handling, and assess their potential roles as determinants of region-specific cell death vulnerability. We propose the novel “spatial redox–metalloptosis axis” hypothesis. The pericentral zone (Zone 3), characterized by hypoxia, high cytochrome P450 activity, and a redox environment that may favor lipid peroxidation under specific pathological conditions, is hypothesized to form a ferroptosis-susceptible niche under metabolic stress. Conversely, the periportal zone (Zone 1), characterized by active copper handling and oxidative phosphorylation-dependent metabolism, is hypothesized to be preferentially vulnerable to cuproptosis (proposed hypothesis; direct zone-resolved evidence of cuproptosis execution in Zone 1 is currently absent). Ceruloplasmin is proposed as a candidate molecular link between copper and iron metabolism. We further identify shared molecular hubs and a hypothesized spatial redox–metalloptosis axis linking these two regulated cell death modalities, while direct biological crosstalk remains to be demonstrated. We also highlight critical technological, mechanistic, and translational gaps. This review aims to shift liver disease research from viewing the liver as a homogeneous organ to a functionally compartmentalized zoned ecosystem, providing a testable theoretical framework for deciphering region-specific liver injury and developing spatially informed therapeutic strategies. Full article

The growing problem of air pollution and its direct impact on human health have created an urgent need for reliable, intelligent, and machine learning (ML)-enabled gas-sensing technologies. Among various sensing platforms, metal oxide gas sensors (MO-GSs) have emerged as promising candidates owing to their low cost, high sensitivity, and scalability. However, their practical application is limited by poor selectivity, cross-sensitivity, sensor drift, and high operating temperatures. Recent advances in ML have provided effective strategies to overcome these limitations through data-driven optimization of sensing performance. This review summarizes recent progress in ML-assisted MO-GSs, covering sensor array design, feature engineering, and classification algorithms, including support vector machines (SVMs), random forests (RFs), and deep neural networks (DNNs). In addition, key data-processing techniques such as preprocessing, dimensionality reduction, and hybrid learning approaches are critically discussed. The application of ML-enabled MO-GSs in medical diagnostics, environmental monitoring, industrial safety, and food quality assessment is also reviewed. Despite significant progress, challenges including limited dataset availability, sensor drift, and poor model generalization remain. Future research should focus on developing adaptive, energy-efficient, and IoT-enabled smart sensing systems. The integration of machine learning with metal oxide gas sensors represents a significant step toward intelligent, next-generation, high-performance gas-sensing technologies. Full article

Anthropogenic pollution of aquatic ecosystems presents a significant global challenge, underscoring the urgent need for resilient, biologically mediated remediation strategies. In this context, microalgae have emerged as a compelling solution, owing to their inherent adaptability to diverse environments and their capacity for efficient contaminant mitigation through bioremediation. These organisms possess the potential to sequester and remove a broad spectrum of pollutants from wastewater streams, including excess nutrients, organic substrates, heavy metals, and various emerging contaminants. Specifically, their metabolic versatility allows these microorganisms to tolerate and degrade complex substances such as recalcitrant micropollutants and hydrocarbons even under fluctuating environmental conditions. This review evaluates extremophilic microalgae as specialized biological agents capable of functioning under harsh anthropogenic stressors that may constrain the performance of microalgal strains commonly investigated for wastewater treatment. Their distinctive stress tolerance may provide advantages for treating wastewater characterized by extreme physicochemical conditions. By examining the unique metabolic pathways of these extremophiles, this analysis addresses critical gaps in the current bioremediation literature regarding the practical scalability and economic viability of integrating such specialized biomass into large-scale treatment infrastructure. Full article

Hydrogenation reactors are critical equipment in the petrochemical industry, yet their material degradation is governed by coupled multi-mechanism damage. Current assessment practices largely neglect this complexity, remaining single-factor oriented and overlooking synergistic interactions and temporal evolution. This paper proposes a regionally differentiated, multi-level framework integrating 5 primary and 17 secondary indicators with a hybrid AHP-EWM weighting strategy that synthesizes expert knowledge and measured data. A multi-factor coupling correction coefficient is introduced to provide a preliminary estimate of the synergistic acceleration effect among damage mechanisms, while a GM(1,1) gray model enables dynamic trend prediction. Applied to a 25-year 2.25Cr-1Mo steel reactor, the method produces regional degradation values of 0.378, 0.607, and 0.533 for the base metal, welds, and cladding layer, respectively, with an overall baseline of 0.453 rising by 11% to 0.503 after coupling correction. Compared with exponential regression, ARIMA, and BP neural networks, GM(1,1) is selected for its balanced performance in small-sample fitting, extrapolation stability, and physical interpretability. Sensitivity analysis confirms stable degradation grading even with ±50% coupling coefficient variations. The proposed approach mitigates the underestimation inherent in conventional single-mechanism assessments and offers a quantitative tool for full-lifecycle risk management and predictive maintenance of hydrogenation reactors. Full article

Effective iron removal from highly acidic leachates without neutralizer addition is a long-standing challenge in hydrometallurgy. For Cu-Co-bearing pyrite cinder, we demonstrate that a cyclic leaching process achieves this outcome. Operating entirely without neutralizers, the process consumed 96% of residual acid, enriched Cu and Co 4.76- and 3.88-fold, and removed 48.2% of iron, all while maintaining pH below 1.5 across four closed-loop cycles. Thermodynamic analysis reveals that Fe³⁺-${\mathrm{SO}}_4^{2-}$ complexation suppresses free Fe³⁺ to approximately 10⁻⁸ mol/L, ruling out conventional hydrolytic precipitation and directing precipitation towards schwertmannite-type basic ferric sulfate (Fe₈O₈(OH)₆SO₄). The formation of this sulfate-bearing Fe precipitate is consistent with the thermodynamic analysis, the iron mass balance, and a 176% increase in solid-phase sulfur. This neutralizer-free strategy offers a sustainable paradigm for recovering critical metals from iron-rich secondary resources. Full article

Real-time detection of chemical warfare agents (CWAs) and toxic industrial chemicals underpins military protection, counter-terrorism, and emergency response. Yet field instruments usually fail for a reason unrelated to sensitivity: they cannot identify agents that are not already in their reference libraries, such as novel analogs, mixtures, and degradation products. We argue that this unknown-agent problem is a structural limitation of single-modality sensing, because any one class of information (molecular bonds, ion mobility, elemental composition, or chemical reactivity) is rarely sufficient to resolve an unfamiliar threat. We review the dominant field modalities, including FTIR, Raman/SERS, ion mobility and field-asymmetric ion mobility spectrometry, laser- and spark-induced plasma spectroscopy, metal-oxide sensor arrays, and portable mass spectrometry, and show that their weaknesses are largely complementary. We then set out the principle of orthogonal multimodal sensing, in which complementary information axes are combined by machine learning with anomaly and open-set detection so that unfamiliar agents are recognized as such rather than misidentified. Four hybrid architectures are critically compared, and we examine spark-induced decomposition diagnostics, consumable-free self-decontaminating field systems with edge AI, and the open challenges of standardized datasets, calibration transfer, and validation, before outlining a roadmap toward field-relevant recognition of unidentified chemical threats. Full article

Additively manufactured components require machining of functional surfaces to meet geometric requirements. Due to low stiffness and non-nominal as-built geometry, they are susceptible to milling-induced shape deviations. This paper presents a geometric–numerical milling process simulation for predicting shape errors in compliant metallic laser powder bed fusion components. The method combines real-geometry-based technological numerical control simulation, quasi-static force prediction, finite element-based structural response simulation, and surface reconstruction between roughing and finishing to enable multistage operation. The approach is validated for linear and non-linear toolpaths with varying immersion angles and compliance conditions. The results show reproduced force profiles, while magnitude deviations highlight the relevance of deformation-dependent engagement feedback in high-compliance regions. An analytical back-calculation based on the effective engagement cross-section reveals that accounting for deflection-induced engagement reduction reduces force deviations. During roughing, maximum shape errors for linear and non-linear toolpaths are overestimated by 4–5%, and critical high-error regions are identified. The reconstructed intermediate geometry after roughing is essential for finishing, since neglecting geometry feedback underestimates finishing forces. With geometry feedback, the maximum finishing shape error is predicted as 0.090 mm, while the measured value is 0.086 mm. The simulation captures dominant quasi-static shape-error regimes and supports process-chain-oriented prediction in additive–subtractive manufacturing. Full article

Germanium is a critical rare-dispersed metal with irreplaceable applications in infrared optics, fiber-optic communications, and semiconductor industries, making its efficient recovery from secondary resources of great strategic importance. This study investigates the selective recovery of germanium from complex zinc smelting leachates using a novel hydroxamic acid extractant, BGYW, in synergistic combination with P204. The feed solution contained approximately 360 mg/L Ge, 10,790 mg/L Fe²⁺, and 98,530 mg/L Zn, representing a highly complex matrix. Continuous counter-current extraction was performed in a 30-stage miniature mixer-settler. Under optimized conditions of 10% BGYW + 5% P204 in white oil, an O/A ratio of 1:1, and 8 mol/L NH₄F as strippant, the single-stage germanium extraction efficiency reached 99.4%. Over 16 consecutive cycles, the extraction system maintained stable performance with average germanium extraction above 99%. A 3-stage scrubbing section using 50 g/L H₂SO₄ effectively removed co-extracted Zn, Cu, and Al impurities. Iron co-extraction, a major challenge, was successfully mitigated through a 2–3 stage iron scrubbing step using a chloride-containing scrubbing solution, which reduced the iron concentration in the strip liquor from approximately 600 mg/L to below 4 mg/L, and decreased the Fe/Ge mass ratio from 0.197 to below 0.01. The overall germanium recovery across the entire 30-stage continuous process reached 98.82%, and the dissolution loss of BGYW in the aqueous phase was reduced by over 85% compared to the conventional YW100 extractant. Third-phase formation caused by residual organic flocculants from the leaching step was eliminated through enhanced pre-treatment, while ferric fluoride precipitation in the stripping section was resolved by incorporating the iron scrubbing stage. This study demonstrates that the BGYW-P204 extraction system with the integrated iron scrubbing step offers an efficient, stable, and industrially viable approach for germanium recovery from zinc smelting leachates, providing a practical solution to the long-standing challenge of germanium–iron separation and contributing to the sustainable supply of this critical metal. Full article

Nanomedicine has advanced cancer theranostics via targeted delivery and phototherapy, yet many high-performance systems rely on inorganic or metal-intensive materials synthesized through energy-demanding routes, raising concerns about biocompatibility, environmental accumulation, and sustainability. This review re-evaluates polypyrrole (PPy)-based nanomedicines from a green chemistry perspective, shifting focus from performance-centric optimization to sustainability-guided design. PPy, an organic conductive polymer with near-infrared photothermal activity and structural tunability, offers a promising platform. However, pristine PPy suffers from limited functionality, poor biodegradability, and insufficient reactive oxygen species (ROS) generation. Reported FeCl₃-, CuCl₂-, and Fe²⁺/H₂O₂-mediated routes are compared to examine formulation-specific relationships among synthesis conditions, polymer characteristics, redox behavior, ROS-related function, and process burdens. Because the underlying studies differ in composition, processing, purification, and assay conditions, these comparisons are used to identify evidence-supported trade-offs and data gaps rather than to establish a universal causal hierarchy. Green strategies are critically assessed, including one-step carboxylated copolymerization for backbone degradability and metal–polyphenol networks for catalytic ROS amplification. To organize the heterogeneous evidence, this review introduces a PPy-specific dual-axis evidence map that considers process-related sustainability alongside biofunctional performance. This qualitative tool is intended to identify trade-offs and evidence gaps rather than provide a validated sustainability score. Full article

Mg-Gd-Y-Zr alloys, with strong age-hardening and thermal stability, are ideal for lightweight load-bearing components, yet forming large complex parts is limited by high sensitivity to hot deformation parameters. This work investigates the hot deformation behavior and microstructure evolution of a Mg-9Gd-4Y-0.5Zr (wt.%) alloy via hot compression at 400 to 510 °C and strain rates of 0.001 to 10 s⁻¹. An Arrhenius constitutive equation with an activation energy Q of 158.63 kJ/mol was established, and a hot processing map was constructed. EBSD characterization revealed the dynamic recrystallization, grain size evolution, and texture transition. The results show that flow stress depends strongly on temperature and strain rate. At strain rates of 0.001~1 s⁻¹, a dynamic balance between work hardening and dynamic softening is achieved, and the post-peak flow stress gradually stabilizes. At a high strain rate of 10 s⁻¹, the flow stress continues to decrease because the competition between softening from dynamic recrystallization and work hardening is disrupted by deformation-induced heating. Low strain rates (≤0.01 s⁻¹) and high temperatures (≥470 °C) promote dynamic recrystallization and significant grain refinement. Two optimal processing windows were determined: 400 to 430 °C at 0.001 to 0.01 s⁻¹, giving fully recrystallized fine equiaxed grains, and 440 to 460 °C at 0.01 to 0.1 s⁻¹ with a power dissipation efficiency η of 0.43 to 0.51, balancing processing efficiency and microstructural uniformity. This work provides systematic theoretical and data support for optimizing hot forming parameters of large Mg-Gd-Y-Zr load-bearing components and offers guidance for applying high-strength magnesium alloys in high-end equipment. Full article

Metal-plate-connected (MPC) joints govern the stiffness and load-bearing performance of many prefabricated timber roof trusses, yet their response to repeated moisture changes remains critical for serviceability and durability. This study evaluated five continuous C24 Norway spruce reference specimens and fifteen specimens joined with GNA20-MIT nail plates using sequential four-point-bending stiffness measurements and wetting–drying conditioning. Test I was used as the initial stiffness stage, whereas Tests II and III followed successive 24 h water-immersion and 6-day natural-drying intervals; the specimens were subsequently tested to failure. The mean apparent modulus of elasticity of the MPC specimens decreased from 1.39 to 1.22 GPa (approximately 12%), but a Friedman repeated-measures test did not show a statistically significant stage effect (χ²(2) = 4.13, p = 0.127). Because the same specimens were repeatedly loaded, and no unexposed MPC control group was included, this change cannot be attributed exclusively to moisture cycling. In the primary analysis retaining all 15 MPC specimens, the mean apparent bending strength of the connected elements was 16.92 MPa, compared with 34.14 MPa for the structurally different continuous reference specimens; excluding M7 yielded 17.87 MPa only as a sensitivity analysis. Failure of the connected specimens was progressive and dominated by plate slip and partial spike withdrawal, whereas solid specimens failed more abruptly in bending. The results therefore support attention to connection flexibility and serviceability under variable environmental and loading histories, while further controlled testing is required to isolate the specific contribution of moisture cycling. Full article

The imperative to mitigate climate change has accelerated the development of Carbon Capture, Utilization, and Storage (CCUS) technologies, particularly CO₂ hydrogenation into high-value chemicals and alternative fuels. This work evaluates the fundamental thermodynamic limitations and the primary directions of CO₂ conversion, with a primary focus on methanation, alongside related pathways such as methanol synthesis and the reverse water-gas shift (RWGS) reaction. To overcome the high kinetic barriers of CO₂ activation, various catalytic systems are analyzed. While noble metal catalysts exhibit high catalytic performance, nickel-based catalysts serve as a viable and cost-effective alternative. To overcome nickel’s susceptibility to thermal sintering and coking, advanced bimetallic and multimetallic formulations are being developed to enhance structural stability and selectivity. These advancements are crucial for producing Synthetic Natural Gas (SNG) and sustainable aviation fuels (SAF). Ultimately, the objective of this comprehensive review is to systematically summarize recent advancements in catalyst design, critically analyze the advantages and fundamental bottlenecks of distinct catalytic systems, and outline prospective paths for the efficient industrial-scale production of sustainable alternative fuels. Full article

Whether zinc (Zn) and copper (Cu) bioaccumulation in the Pacific oyster (Magallana gigas) reflects toxicological stress or is an incidental consequence of growth remains unclear. We cultured three commercial triploid M. gigas stocks for approximately one year, sampling gill and hepatopancreas at the start and end of this period, when Zn/Cu burden was naturally low and high, respectively. Pooled samples from both time points were profiled by whole-transcriptome sequencing, enzyme activity and oxidative damage assays, qPCR validation, and protein–protein interaction network analysis. Transcriptome-wide changes in both tissues tracked the culture period, but growth and Zn/Cu burden were too highly collinear (r = 0.92–0.98) to separate statistically. Critically, of the four metals measured (Zn, Cu, iron [Fe], and manganese [Mn]), only Zn and Cu increased with growth, whereas Fe and Mn did not, indicating metal-specific rather than generalized accumulation. Superoxide dismutase (SOD) activity and the transcript abundance of its copper/zinc isoform (Cu/Zn-SOD) increased with growth in both tissues, whereas catalase (CAT) activity was unchanged and glutathione peroxidase (GPX) activity rose only in gill. Malondialdehyde (MDA), a marker of oxidative damage, increased in both tissues. Gill mounted a broader response than hepatopancreas, including upregulation of KEAP1 alongside downregulation of detoxification, proteostasis, and ribosome-related genes. Stock-level qPCR further revealed stock-dependent regulation of antioxidant genes in hepatopancreas. Together, these results indicate that Zn/Cu bioaccumulation in M. gigas co-varies with growth in a metal-specific manner, consistent with cofactor demand for Cu/Zn-SOD. The accompanying oxidative and proteostatic changes therefore more plausibly reflect growth physiology than an independent pollutant signal. Full article

Aerobic composting converts agricultural waste into stable, humus-rich products, and the application of exogenous additives is an efficient strategy to enhance humification. This systematic review synthesized studies published between 2023 and 2026 on additives that promote humification during agricultural waste composting. Based on the distribution of the retrieved literature, additives are categorized into inorganic additives, organic additives, biological strategies, and composite systems, and the effects and mechanisms of each category are systematically discussed. Iron-based additives achieve the highest humic acid (HA) increases of 82–267% through Fenton-like redox catalysis. Clay minerals and biochar produce moderate HA enhancements of 25–163% via physical structuring and surface adsorption with broader applicability. Small-molecule precursors and exogenous humic substances achieve HA gains exceeding 100% at sub-percent doses. Biological strategies provide self-sustaining catalytic activity but are sensitive to environmental conditions. Composite additives, the largest category, generally outperform single additives through functional complementarity, though antagonistic effects have also been documented. Cross-study patterns suggest that different feedstocks respond preferentially to distinct additive types, though systematic experimental validation is lacking. Critical gaps between laboratory findings and practical application are identified, including the predominance of small-scale studies, the absence of techno-economic analysis, and the unassessed environmental fate of metal-based additives. Future research priorities include pilot-scale validation under industrial conditions, the establishment of standardized humification metrics, and long-term field monitoring. Full article