Search Results (12,936)

Carbon fiber-reinforced thermoplastic composite drilling is a secondary manufacturing process because the quality of drilled holes affects assembly system performance, structure, and sustainability. This paper compares all drill coating types and cutting conditions for PEEK-CF30 composite drilling utilizing a hybrid experimental–statistical method. DLC-, TiN-, and TiCN-coated HSS drills, as well as cutting speed and feed rate were tested using the Taguchi L27 design. Performance indicators were measured by including thrust force, surface roughness, drilling torque, and energy consumption. Experimental results showed that increasing cutting speed and feed rate increased the thrust force while decreasing torque and energy consumption. Smearing on the hole surface, chip adhesion, and short fiber adhesion/pull were identified as indicators of poor surface quality, and these occurrences increased with increasing drill coating removal at high cutting parameters. In terms of overall performance, the TiCN-coated drill created the lowest thrust force (50.85 N), surface roughness (1.038 µm), torque (17.54 Ncm), and energy consumption (136.45 J) at high feed conditions. Taguchi-based gray relational analysis methodology revealed that the TiCN-coated drill, a cutting speed of 40 m/min, and a feed rate of 0.1 mm/rev are the optimum parameters. Second-order prediction models developed for all responses proved to have high predictive capabilities with coefficients of determination above 94%. Ultimately, drill coating quality considerably affected surface integrity and drilling energy consumption performance in drilling PEEK-CF30. A hybrid optimization and modeling framework demonstrates that the drill quality cutting parameter will allow for optimum selection to ensure efficient processing of advanced thermoplastic composites. Full article

Green Total Factor Productivity (GTFP) serves as a pivotal indicator for balancing high-quality economic growth with increasingly stringent environmental regulations. However, empirical evidence regarding whether and how firm-level GTFP is associated with enhanced Environmental, Social, and Governance (ESG) performance in emerging markets remains limited. This study addresses this gap by examining the GTFP–ESG nexus within the macro-context of China’s “Dual-Carbon” goals (aiming for peak carbon emissions by 2030 and carbon neutrality by 2060). Utilizing an unbalanced panel dataset of Chinese A-share listed companies strictly covering the period from 2011 to 2022 (with 2010 data exclusively used for one-period lagged variables), we construct firm-level GTFP metrics using a non-radial SBM-DDF global Malmquist–Luenberger index—incorporating both desirable economic outputs and undesirable environmental emissions—and link them with Huazheng ESG ratings. To ensure robust empirical identification, we employ two-way fixed-effects models with lagged variables, propensity score matching (PSM), and an instrumental variable two-stage least squares (IV-2SLS) approach utilizing the leave-one-out provincial average GTFP as an instrument. The results indicate a significant positive association between GTFP and overall ESG performance, as well as its three sub-pillars. Specifically, a one-standard-deviation increase in GTFP corresponds to a 0.15-standard-deviation increase in the ESG score, a marginal effect of profound economic significance, providing robust associational insights via the IV estimates. Mechanism analyses reframe traditional mediation as descriptive associational pathways, revealing that digital transformation, green innovation, and information transparency serve as significant channels, theoretically demonstrating how resource efficiency translates into social legitimacy. Heterogeneity tests show that this association is more pronounced for non-state-owned enterprises, firms in eastern China, and those with lower financing constraints. These findings unpack the “black box” between technical efficiency and sustainability, providing empirical support for policymakers to align corporate productivity with international disclosure standards (such as the EU’s CSRD). Full article

Alpha-linolenic acid (ALA) is an essential omega-3 fatty acid and a vital component in food applications. In this study, we investigated a range of physicochemical culture conditions—including pH, temperature, and carbon source—to evaluate biomass and ALA accumulation in Chlorella sp. L166 and its mutant, C-12. The study aimed to identify favorable culture conditions and evaluate the feasibility of using diluted bean curd (tofu) wastewater as a low-cost medium. Under mixotrophic cultivation, ALA content was determined via GC-MS, and the removal efficiencies of total nitrogen (TN), total phosphorus (TP), and chemical oxygen demand (COD) were simultaneously monitored. The results showed that L166 achieved its highest ALA accumulation at pH 6.0 and 23 °C with maltose. C-12 exhibited appropriate ALA accumulation at pH 7.0 and 23 °C with maltose and reached its maximum biomass at pH 8.0 and 25 °C with glucose. After 8 days of cultivation in threefold-diluted tofu wastewater, C-12’s ALA content reached 6.1 mg/g, significantly higher than that observed in BG11 medium. Meanwhile, both strains removed 81.2–83.2% of TN, 35.7–36.0% of TP, and 42.6–43.5% of COD. This study provides preliminary data on the effects of culture conditions on microalgal ALA production, highlighting the potential for future practical applications of C-12. Full article

The purpose of this work was to synthesize and study catalytic systems based on a carbon-containing support obtained from coke fines from the Shubarkol deposit as a waste product of the coal industry for the processing of phenolic compounds. Based on the obtained carbon sorbent, mono- and binary catalysts with active phases of transition metal oxides (Fe, Co, Ni) were synthesized by wet impregnation, followed by heat treatment at 500–700 °C, as well as the aluminum oxide compositions. The surface morphology and elemental composition of the samples were studied by scanning electron microscopy (SEM) with energy dispersion analysis and elemental mapping (EDS mapping), and the content of active phases was determined using inductively coupled plasma optical emission spectrometry (ICP-OES). The catalytic activity was studied in phenol hydrogenation reactions. The CoO/C catalyst demonstrated the greatest activity, providing a 62.36% benzene yield during phenol hydrogenation. The catalytic activity of the CoO/C catalyst has also been studied in the hydrogenation reactions of structurally and functionally more complex compounds, pyrocatechol and resorcinol. The yield of benzene was 63.16% in the hydrogenation of pyrocatechol and 48.64% in the hydrogenation of resorcinol. It was found that the CoO/C catalyst exhibits the highest efficiency at a temperature of 420 °C, a pressure of 6–6.5 MPa and a reaction duration of 120 min. The results obtained make it possible to evaluate the prospects of using a carbon sorbent obtained from coke fines from the Shubarkol deposit as a support for CoO as part of an active and stable catalytic system designed for deep processing of phenolic compounds. Full article

Growing municipal solid wastes, environmental deterioration, and the world’s increasing energy demand highlight the urgent need for effective, sustainable energy recovery solutions. Uncontrolled municipal solid wastes contribute explicitly to the global crises of climate change, pollution, and biodiversity loss. Food and organic waste are converted into value-added products using biochemical and thermochemical techniques. Anaerobic digestion (AD) is a versatile, multi-phase waste-to-energy technology that transforms organic waste into renewable energy in an oxygen-free environment. AD uses microorganisms to break down waste, yielding biogas (mostly methane and carbon dioxide) and digestate, a nutrient-fortified by-product. Compared with traditional Single-Stage Anaerobic Digesters (SSAD), Two-Stage Anaerobic Digesters (TSAD) offer notable benefits by separating hydrolysis–acidogenesis from acetogenesis–methanogenesis. These include increased methane yield, improved process control, increased microbial stability, and resistance to inhibitory substances. According to the literature, TSAD systems have been shown to increase methane yield by about 10–30% compared to SSAD. This article covers the dynamics of the microbial population at various stages, the impact of operational factors (HRT, OLR, pH, and temperature), and novel reactor designs with modular and multi-state functions. In line with Oman’s Vision 2040, this study discusses the continuous operation of a two-phase AD co-digestion process and the in-depth techno-economic feasibility of decentralized waste management through optimized biogas production. Optimizing the carbon-to-nitrogen (C/N) ratio within the range of 20–30 in co-digestion systems significantly enhances microbial activity and methane production. The potential of recent developments, such as microbial immobilization, biogas generation techniques, and hybrid integration with photobioreactors or electrochemical systems, to enhance the scalability and efficiency of bioconversion is addressed in a TSAD system. In addition to encouraging circular economy principles through efficient organic waste valorization, this review identifies TSAD as a promising approach to achieving the SDGs related to sustainable cities, clean energy, and responsible consumption. Full article

The microporous layer (MPL) is a key functional component in proton exchange membrane fuel cells (PEMFCs), and clarifying the quantitative relationship between its microstructure and mass transport properties is essential for improving cell performance. In this study, a three-dimensional MPL model was developed using a stochastic reconstruction method, and, together with a random walk algorithm, was employed to systematically investigate the effects of porosity, carbon sphere radius, maximum overlap ratio, seed ratio, and polytetrafluoroethylene (PTFE) content on permeability, effective diffusivity, and tortuosity. The results reveal that increasing porosity reduces tortuosity from 1.7 to 1.3, while permeability and effective diffusivity increase by factors of approximately 6.5 and 1.8, respectively. As the carbon sphere radius increases, tortuosity decreases from 1.55 to 1.35, accompanied by an increase in permeability from 2 × 10⁻¹⁶ m² to 20 × 10⁻¹⁶ m². Moreover, increasing the PTFE content raises permeability from 5 × 10⁻¹⁶ m² to 22.5 × 10⁻¹⁶ m², corresponding to an enhancement by a factor of approximately 4.5. The high-accuracy fitting equations obtained from the simulation results provide theoretical guidance for the microstructural design and optimization of MPLs, which can enhance oxygen transport and water management, reduce mass transport losses, and thereby benefit high-power-density operation and the overall efficiency of PEM fuel cells. Full article

Rapid urbanization has intensified challenges regarding urban waterlogging and vehicle exhaust pollution. While permeable asphalt mixtures mitigate waterlogging and nano-TiO₂ offers photocatalytic exhaust degradation capabilities, the direct application of nano-TiO₂ is hindered by agglomeration and low photocatalytic efficiency. This study developed a composite modified nano-TiO₂ via metal ion doping and support treatment to enhance its performance in asphalt pavements. Specifically, nano-TiO₂ was doped with Fe³⁺, Ag⁺, and La³⁺ via the sol–gel method, and supported on activated carbon (AC) or Al₂O₃. The exhaust degradation performance was evaluated using a custom-built system, while dispersion properties were assessed via fluorescence microscopy and UV-Vis spectrophotometry. Furthermore, X-ray diffraction (XRD) and Fourier-transform infrared (FTIR) spectroscopy were conducted to investigate the microstructural mechanisms underlying the doping modification and support treatment. Photocatalytic permeable asphalt mixtures were prepared by partially replacing mineral powder with the composite modified nano-TiO₂ to validate exhaust degradation and pavement performance. The results indicated that metal doping substituted Ti⁴⁺ in the lattice, inducing defects and reducing crystallite size to boost photocatalytic activity. The optimal doping concentrations are determined to be 1.0% for Fe³⁺, 1.5% for Ag⁺, and 1.0% for La³⁺. Among these, Fe³⁺-doped nano-TiO₂ at 1.0% content exhibits superior exhaust degradation, achieving 46.7% efficiency for hydrocarbons (HC) and 33.5% for nitrogen oxides (NO). Regarding dispersion, while AC performs better at low support content, Al₂O₃ at 40% content provides superior dispersion properties by increasing active sites and surface hydroxyl groups. For photocatalytic permeable asphalt mixtures, replacing 40–50% of mineral filler with the composite modifier is recommended. The optimized mixture demonstrates superior exhaust degradation performance while maintaining the required high-temperature stability, low-temperature cracking resistance, water stability, and fatigue life. Specifically, compared to the control group, these indicators for the mixture with 50% of the mineral filler replaced by the composite modifier increases by 7.0%, 12.5%, 13.4%, and 22.9%, respectively. This study presents a viable technical solution for developing multifunctional asphalt mixtures with photocatalytic functionality as the core innovation and mechanical performance as the application baseline. Full article

Laser lift-off (LLO) is a critical process for separating ultra-thin polyimide (PI) films in flexible electronics manufacturing, yet traditional methods often induce thermal and mechanical damage due to high laser energy processing. To address this, we propose a low-threshold LLO method by integrating carbon nanotubes (CNTs) at the interface between a 500 nm PI film and a glass substrate. The interfacial thermal dynamics and separation quality were evaluated through finite element simulations and experimental validations using a 355 nm ultraviolet nanosecond laser. Results demonstrate that CNTs significantly enhance interfacial ultraviolet absorption and promote lateral heat diffusion due to their high axial thermal conductivity. This mechanism broadens the thermal decomposition zone and suppresses vertical heat transfer, thereby reducing the required LLO threshold from 180 mJ/cm² to 120 mJ/cm². Furthermore, the integration of CNTs reduces interfacial adhesion and alters the separation dynamics, resulting in the formation of smoother blisters with increased diameters and reduced heights compared to conventional LLO. These effects effectively minimize thermal and mechanical damage to the ultra-thin PI film and its integrated devices. This CNT-assisted LLO approach provides an efficient, low-damage solution for ultra-thin film separation, showing strong potential for advancing high-performance flexible electronics. Full article

C1 biotechnology—bioprocesses that valorize one-carbon feedstocks such as CO₂, CO-rich gases (blast furnace gas or synthesis gas), CH₄ and CH₃OH—has evolved from laboratory curiosity to industrial reality. In the quest to de-fossilize the chemical industry, the circular bioeconomy is widely seen as a solution. However, today it is still mostly based on primary agricultural feedstocks. Compared to thermochemical and catalytic processes, bioprocesses (fermentations) are carried out at ambient conditions, achieve high selectivities and good productivities. By decoupling fermentation from sugar-based substrates, gas fermentation of C1 substrates offers a scalable technology platform for producing biofuels, bioplastics, bio-based building blocks and alternative proteins, to name a few large-volume products. C1 platforms enable a circular, resource-efficient and virtually feedstock-independent bioeconomy that directly supports multiple United Nations Sustainable Development Goals (SDGs). In this article, we analyze the current technological landscape and discuss the (potential) impact of C1 routes on key SDGs using recent research advances and commercial case studies. Full article

Under the strategic context of building a transportation powerhouse in China, the transportation sector faces the dual challenge of reducing emissions while improving efficiency. This study constructs a two-dimensional regional classification framework based on the “economic-carbon” dimension and systematically investigates the coordinated evolution of the development level (TD) and carbon emission intensity (TCEI) of the transportation systems in 31 provinces of China from 2014 to 2023, using methods such as entropy weight TOPSIS, the coupling coordination degree (CCD) model, kernel density estimation (KDE), spatial autocorrelation analysis, and the XGBoost-SHAP explainable machine learning framework based on transfer learning. The study finds that (1) TD shows a fluctuating upward trend, while TCEI continues to decline, with regional imbalances; (2) in terms of time, CCD shows a general upward trend with an N-shaped evolution; spatially, CCD presents a pattern of stronger coordination in the east and weaker in the west, with sustained regional heterogeneity, forming a development pattern of “Region I leading, Region II breaking through, Region III maintaining, Region IV catching up”; and (3) regarding the driving factors, freight volume, transport industry output value, and passenger turnover are the core driving factors of CCD, with significant regional heterogeneity in their mechanisms. This study provides a systematic analytical framework and differentiated policy tools for promoting coordinated regional development of green transportation. Full article

Space constraints in shipboard carbon capture require compact absorbers with high gas–liquid mass-transfer efficiency. However, the performance of emerging packing geometries cannot be inferred reliably from bed-scale correlations alone because liquid distribution and interfacial transport depend on unit-cell flow organization. This study aims to compare the micro-scale hydrodynamics and CO₂ mass-transfer behavior of the Kelvin cell and a Mellapak 250Y corrugated sheet unit using three-dimensional CFD simulations over liquid loads of 10 to 100 m³/(m²·h). The corrugated sheet guides liquid mainly along corrugation crimps, whereas the Kelvin cell redistributes liquid through its strut network and node intersections. For the M250Y unit, the periodic dripping cycle shortens as liquid load increases, and liquid holdup reaches only about 8% at 100 m³/(m²·h). In contrast, the Kelvin cell evolves from discrete dripping to liquid bridging and secondary breakup, maintains a liquid holdup about 3 to 6 times that of the corrugated sheet and delivers 2 to 3 percentage points higher mass-transfer efficiency. These results suggest a local hydrodynamic and mass-transfer advantage of the Kelvin cell over the M250Y benchmark under the present REU-scale conditions. Full article

This study examines agricultural and rural carbon emission efficiency and the underlying “low-carbon efficiency illusion” in China, where measured efficiency gains fail to translate into genuine environmental improvements. Using panel data from 30 Chinese provinces spanning 2000 to 2022, this study employs a meta-frontier slack-based measure (SBM) model to assess agricultural and rural carbon emission efficiency across meta-frontier and group-frontier benchmarks and investigates the efficiency illusion from the perspective of carbon emission reduction cost constraints. We further combine the Extreme Gradient Boosting (XGBoost) model and Shapley Additive Explanations (SHAP) explainability methods to identify core drivers of agricultural carbon emission reduction costs. We find that technical inefficiency is the primary constraint on China’s agricultural and rural carbon emission efficiency; the number of provinces with an efficiency illusion shows an initial increase followed by a decrease between 2005 and 2022; and core drivers of emission reduction costs exhibit heterogeneous impacts and significant threshold effects across the two frontier frameworks. These findings offer evidence-based guidance for designing differentiated, targeted emission reduction strategies to mitigate the efficiency illusion, advance low-carbon agricultural transition, and support the sustainable development of agricultural and rural systems in the context of the United Nations Sustainable Development Goals. Full article

This paper is based on data from 121 cities in China’s ecologically fragile regions from 2008 to 2022; it constructs an indicator system for the efficiency of pollution control and carbon reduction in agricultural practices. This system includes expenditures on agriculture, forestry, and water affairs, arable land area, agricultural laborers, total agricultural output value, agricultural carbon emissions, and agricultural non-point source pollution. It uses a super-efficiency SBM model that incorporates non-desirable outputs to measure the synergistic efficiency and analyzes its dynamic evolution using the Malmquist–Luenberger index to reveal the spatiotemporal characteristics of the synergistic efficiency. A Tobit model identifies the influence of factors, such as the level of rural economic development, crop planting structure, the strength of fiscal support for agriculture, rural education level, urbanization rate, and mechanization level on the synergistic efficiency. The results show that, from a temporal perspective, the average synergistic efficiency was only 0.58, significantly below the effective value of 1, indicating substantial room for overall improvement. Only 10 cities met the benchmark, with distinctly different reasons for compliance, while the remaining 111 cities remained inefficient. Regarding influencing factors, crop planting structure, the strength of fiscal support for agriculture, and urbanization rate significantly and positively drive efficiency; the level of rural economic development and mechanization level significantly inhibit efficiency, and rural education level shows no significant impact. These findings provide targeted policy recommendations for the synergy effect in ecologically fragile areas, as well as for low-carbon agricultural development. Full article

Ensuring the quality, reliability, and efficiency of cold chain logistics for thermolabile pharmaceutical products, particularly vaccines, remains a critical challenge in global health supply chains. These biologics require stringent temperature control throughout storage, transport, and distribution to preserve their efficacy. Persistent issues such as maintaining product integrity, accurately forecasting vaccine demand, and fostering trust among stakeholders often result in inefficiencies, waste, and public mistrust. This study proposes an intelligent digital management framework specifically designed for vaccine cold chains, integrating blockchain, the Internet of Things (IoT), and machine learning (ML) to address these challenges in a holistic and sustainable manner. The main innovation of the study lies in combining secure traceability, real-time cold chain monitoring, and predictive decision support within a unified vaccine cold chain management framework rather than treating these functions as isolated technological solutions. Using WHO immunization coverage data and vaccine-related review data, the framework supports vaccine demand forecasting through the Informer model and stakeholder trust assessment through BERT-based sentiment analysis. In the sentiment analysis task, the BERT model achieved ~80% accuracy on dominant sentiment classes, with a weighted F1-score of 0.6974, demonstrating strong performance on imbalanced datasets. By minimizing vaccine spoilage and enabling more accurate demand planning, the system reduces excess production and distribution, thus lowering resource consumption, carbon emissions, and financial waste. Moreover, trust-informed analytics support better alignment of supply with actual community needs, fostering equity and resilience in vaccine distribution. While this framework has been validated through simulations and experimental evaluation, further real-world testing is needed to assess long-term stability and stakeholder adoption. Nonetheless, it provides a scalable and adaptive foundation for advancing sustainability and transparency in pharmaceutical cold chains. Full article

Sunset Yellow is a water-soluble synthetic dye resistant to degradation and stable under various conditions, posing an environmental challenge. In the present study pure chitosan hydrogel (PCH) films were synthesized, followed by the assessment of sorption capacity and recyclability compared to chitosan-based films doped with niobium oxide (CHN) or activated carbon (CHC). The aim was to promote the application of sorption methods for Sunset Yellow dye using these films as a treatment option for the pollutant, with the analysis of the effectiveness of the method and its behavior using adsorption kinetic models and thermodynamic analysis. Equilibrium was reached at 240 min for all films tested, with the adsorbed amounts ranging from 18.58 to 18.79 mg g⁻¹ at 30 °C, when the highest kinetic rate constants were observed. The pseudo-first-order kinetic model best described the experimental data, with the lowest Bayesian information criterion, Akaike information criterion, and mean absolute error values. Thermodynamic analysis indicated a spontaneous, exothermic process, with interactions ranging from electrostatic interactions in CHC and PCH to physisorption in CHN. Recycling tests showed 80% efficiency after the third cycle for all three films. These findings highlight the potential of chitosan-based films as an efficient option for removing Sunset Yellow dye from water, thus improving water quality and enhancing wastewater treatment. Full article