Search Results (12,949)

The Ordos Basin hosts abundant lacustrine shale oil resources. Adequately retained hydrocarbons in source rocks, together with favorable mobility, are prerequisites for large-scale shale oil exploitation. Therefore, the quantitative characterization of retained hydrocarbon content and mobility is a core research focus in shale oil exploration and development. This study investigates Chang 7 shale with varying lithofacies and geochemical characteristics. Stepwise pyrolysis and pyrolysis gas chromatography–mass spectrometry (GC–MS) were applied to analyze retained hydrocarbons in different occurrence states, their compositions, and biomarkers. In addition, nuclear magnetic resonance (NMR) combined with CO₂ flooding experiments was conducted, and the collected products under different displacement pressures were analyzed using GC–MS. The aim was to quantitatively examine the variations in expelled oil volume, compositional differences during migration, and occurrence features of shale oil within reservoir micro-pores. The results show the following: (1) Organic-rich shale is characterized by higher proportions of light and medium hydrocarbons, lower heavy fractions, and elevated aromatic hydrocarbon content. In contrast, low-organic-carbon mudstone or siltstone contains more medium and heavy hydrocarbons, with lower light and aromatic fractions. The C13−/C14+ ratio increases with total organic carbon (TOC). (2) In black shale, oil displacement is mainly contributed by mesopores. At low pressures, oil expulsion is difficult and dominated by heavy hydrocarbons. When pressure reaches a threshold, the capillary-bound oil in micropores is released, increasing production and improving oil quality. Muddy siltstone shows higher displacement efficiency than black shale, with contributions from pores of all sizes. At low pressures, its expelled oil volume is larger and lighter than that of black shale. With increasing pressure, the oil yield rises significantly, and medium–large pores produce heavier fractions compared with micropores, likely because light hydrocarbons preferentially enter micropores and are less prone to dissipation. (3) The main controlling factors for shale oil enrichment include retained hydrocarbon content, mobile hydrocarbon fraction, fluidity, and engineering-related parameters. Thick shale layers with high organic matter abundance, high proportions of light–medium hydrocarbons, and favorable porosity–permeability conditions, as well as interbedded siltstone, are enriched in mobile hydrocarbons. Full article

The increasing demand for platinum group metals (PGMs) and critical base metals (BMs) underscores the critical roles these metals play in renewable energy and advanced technologies, enabling more efficient, environmentally sustainable operations. A hydrometallurgical approach to Au, Pd, and Pt tailings, derived from the glycine leaching of low-grade nickel and iron sulfide flotation concentrates, is investigated. The proposed process evaluates two glycine-based systems: glycine combined with KMnO₄ and catalyzed by cyanide under starvation conditions. Leaching with glycine in the presence of KMnO₄ (72 h, 25% solids, 60 °C, pH 11, dissolved oxygen 10 ppm, 126.7 kg/t glycine, and 7 kg/t KMnO₄) achieved extraction efficiencies of up to 66.7% Au, 89.1% Pd, and 95.8% Pt. In comparison, the cyanide-starved glycine system (72 h, 30% solids, 60 °C, pH 11, dissolved oxygen 20 ppm, 98.5 kg/t glycine, and 3.3 kg/t cyanide) resulted in up to 80.8% Au, 78.3% Pd, and 14.3% Pt. Activated carbon and Amberlite resin demonstrated selective adsorption of Au and PGMs. For activated carbon, Au adsorption exhibited a non-linear dependence on carbon dosage, reaching a maximum of 77.61% at 20 g/L, then decreasing to 50.85% at 25 g/L, and finally increasing to 65.04% at 30 g/L, indicating variable adsorption behavior. In contrast, Amberlite resin exhibited more consistent, progressive adsorption with increasing dosage. Au adsorption remained high across all conditions, increasing from 88.06% at 10 g/L to 99.67% at 30 g/L. Similarly, Pd and Pt adsorption improved significantly with resin dosage, reaching maximum values of 81.32% and 83.36% at 25 g/L, respectively, followed by a slight decline at 30 g/L. Implementing a two-stage process using carbon + resin (30 g/L) increased PGM recovery, achieving 99.89% Au, 81.8% Pd, and 92.4% Pt. Elution tests showed that Au (61.97%) and Pd (60.55%) were desorbed efficiently using thiourea (2% w/v) and HCl (0.5 M), whereas Pt elution proved difficult and required alternative strategies. The findings confirm glycine-based technologies as a promising, environmentally friendly alternative to conventional methods and provide a basis for further process development and optimization. Full article

Ground-source heat pump (GSHP) systems are widely used because of their energy-saving and environmentally friendly characteristics. However, the long-term operation of a standalone GSHP system leads to heat accumulation in the soil for cooling load-dominated buildings, which results in a decline in system performance. To address this issue, in this study, a high-speed railway station in Jinan was considered as the research object, and a hybrid system scheme in which a GSHP is coupled with an air-source heat pump (ASHP) was developed. The system uses the outdoor dry-bulb temperature as the control parameter and establishes a multi-unit operation control strategy. A dynamic simulation model of the hybrid system was constructed using TRNSYS software, and then the energy consumption, soil thermal balance, economics and environmental benefits of the system under various schemes and operating conditions were simulated and analyzed. Through a comparative analysis of the operating strategies, the optimal strategy that achieved the best performance was determined. Under the optimal strategy, the soil thermal imbalance rate after 10 years of operation was only 1%, the total energy consumption was significantly lower than that of a standalone ASHP system, and the initial investment was clearly lower than that of a standalone GSHP system. The results demonstrate that the hybrid system ensures soil thermal balance and high-efficiency operation while providing significant energy savings (a 28% primary energy savings rate compared to a standalone ASHP) and environmental benefits (reducing annual CO₂, SO₂, NOx, and dust emissions by 56.5 t, 384.2 kg, 361.6 kg, and 339 kg, respectively). Therefore, the emission of atmospheric pollutants such as CO₂, SO₂, NOx, and dust can be effectively reduced, thus providing an important reference for the development of building energy-saving technologies under the “dual carbon” goals. Full article

Background: Optimized nitrogen (N) application and planting density can enhance sweet potato yield. However, the agronomic mechanisms underlying their effects on photosynthetic efficiency and carbohydrate metabolism in sweet potato remain unclear. Methods: To address this, a two-year field experiment was conducted using a split-plot design with two varieties (YS-25 and GX-14), three N levels (60, 90, and 120 kg/ha; designated N60, N90, and N120, respectively), and three planting densities (D1–D3: 50,000, 62,500, and 83,333 plants/ha). Each treatment was replicated three times. Results: The results showed that the N60D2 treatment (60 kg/ha N; 62,500 plants/ha) optimized canopy light distribution by significantly increasing IPAR, light transmission rate, and extinction coefficient (K). This treatment enhanced individual plant photosynthetic capacity (higher photosynthetic rate: Pn, Ci, Gs, and Tr) and light energy use efficiency (Fv/Fm, Y(II), ETR, and qP), and promoted carbohydrate metabolism (sucrose, starch, fructose, and glucose) by increasing enzyme activities (Rubisco, SuSy, SPS, NI, SSS, and AGPase) in functional leaves and roots. These effects improved source–sink coordination, ultimately increasing storage root yield by 63.27–95.47% compared with the control plants (N120D1). Correlation analysis revealed that single-plant root weight and medium-sized root count were important yield determinants for both varieties. Conclusions: These results indicate that reducing nitrogen fertilizer combined with dense planting shapes a reasonable canopy structure for light distribution at the population level and optimizes light and carbon use efficiency at the individual plant level, thereby improving storage root yield and commercial characteristics of sweet potato. Full article

Transmission electron microscopy (TEM) is an essential technique for characterizing nanomaterials. However, specimen preparation, which is a critical factor affecting image quality, remains a practical challenge. Focusing on nanopowders used in materials and chemical science, this article employs case studies to analyze the key steps in TEM specimen preparation. Carbon support films (CSFs) are essential tools for specimen preparation, and this study introduces several commonly used, cost-effective options, including conventional CSFs, conventional holey CSFs, ultrathin holey CSFs, and double-grid support films. We characterize their structural and morphological characteristics and evaluate their suitability for different types of samples. Several representative case studies of nanopowders, spanning from zero-dimensional (0D) to one-dimensional (1D) and two-dimensional (2D) materials, are used to illustrate tailored specimen preparation approaches, which serve as practical references for researchers conducting TEM characterization. These findings facilitate higher image reliability and experimental efficiency, thereby providing critical support for advancing fundamental exploration and frontier innovation in nanomaterial science. Full article

This study optimized corncob-derived magnetic biochar (MBC) with tailored iron content for laccase immobilization to boost nonylphenol (NP) degradation in water. Low-iron MBC (LMBC) and high-iron MBC (HMBC) from corncob were prepared via impregnation–pyrolysis at 700 °C, followed by modification with polyethyleneimine (PEI) and covalent immobilization of laccase using glutaraldehyde. Compared to HMBC, LMBC exhibited more mesopores, superior laccase activity recovery (60.5%) and Fe²⁺ release that was only 1/78 of HMBC’s. Furthermore, PEI modification and subsequent laccase immobilization on LMBC significantly reduced iron leaching (p < 0.05). X-ray diffraction and vibrating sample magnetometry analyses indicated that LMBC consists of crystalline Fe₃O₄, α-Fe, graphite, and carbon, with a saturation magnetization of 45.8 emu g⁻¹. Scanning electron microscopy, Fourier transform infrared spectroscopy, and X-ray photoelectron spectroscopy confirmed the microporous and mesoporous structure of LMBC, the successful PEI modification, and the effective immobilization of laccase on LMBC (L-LMBC). L-LMBC exhibited enhanced stability under acidic conditions (pH 3–7) and elevated temperatures (20–70 °C). After six repeated cycles, the NP removal efficiency by L-LMBC remained at 84.8%. Moreover, L-LMBC demonstrated effective NP removal in real environmental water samples. This study provides fundamental insights and demonstrates the potential application of MBC-immobilized laccase for degrading persistent pollutants in aqueous systems. Full article

To achieve carbon neutrality, increasing efforts have been devoted to the clean utilization of fossil fuels. This study investigates the effect of reaction temperature on methane catalytic cracking over a biochar-supported iron catalyst. Corn stalks were heated to make biochar which was used as the carrier. To obtain biochar with a high specific surface area and well-developed porous structure, chemical activation was employed. The catalyst was made by adding iron to the biochar using the soaking method. This iron biochar catalyst is used to study its effectiveness in catalyzing methane cracking. The biochar-supported Fe catalyst was studied for its effectiveness in catalyzing methane cracking at different temperatures (800–950 °C). The results indicate that a higher temperature favors methane conversion in terms of reaction efficiency and cumulative conversion levels. At 950 °C, the catalyst exhibits the best performance, with a peak conversion rate of up to 85%, and it can still maintain a stable conversion rate of around 55% after prolonged reaction, yielding the total conversion of 57.6%. Raising the temperature can significantly promote the transformation of solid-phase products from highly blocking amorphous carbon to more ordered graphitized carbon. In addition, the reacted catalyst shows a remarkably reduced specific surface area, the disappearance of micropores, and a considerable increase in average pore size. Carbon nanotubes with various diameters and morphologies were formed on the catalyst surface. Full article

Carbon nanotube (CNT) materials exhibit ultrahigh electrical and thermal conductivity. Upon electrical excitation, CNT-based transparent conductive films (TCFs) can emit far-infrared radiation (FIR) and provide certain physiotherapeutic efficacy, making them ideal candidates for thermotherapy applications. This work systematically tests and analyzes the fundamental physical properties and physiotherapeutic performance of CNT flexible thin-film heaters (TFHs) for potential use in health physiotherapy. Two types of TFHs with different electrode connection modes were fabricated via the prepared TCFs. Experimental characterizations were conducted on their response time, electrothermal performance, and heat transfer characteristics. The results showed that the temperature rise per unit input power for TFH1 was 16.71 °C/W, while that of TFH2 was 4.29 °C/W at the same voltage of 10 V. In addition, the variation trends of maximum temperature with power density were highly consistent for the two films. This demonstrates that TFHs fabricated using the same TCFs exhibit excellent and high electrothermal conversion efficiency as well as outstanding comprehensive electrothermal performance. In addition, smaller L/W ratio leads to lower resistance of TFHs, resulting in a stronger thermal effect under identical applied voltage. After the temperature stabilized, the surface temperature of the TFHs decreased by approximately 5 °C when attached to the human arm, confirming that the heat generated by the TFHs under electrical excitation could be effectively absorbed by the human body. The TFHs emitted rapid FIR upon electrification, and the peak wavelength ranged from 8 to 12 µm, which fell within the range of 6–14 µm that was easily absorbable by the human body. The heat can be rapidly absorbed by the skin and distributed throughout the body via blood circulation, yielding favorable physiotherapeutic efficacy. This study provides key physical parameters for the application of TFHs in wearable medical devices and physiotherapy equipment. Full article

The construction industry, a global economic pillar and carbon emission giant, faces a critical gap between digital transformation and risk management, which ultimately undermines the sector’s capacity for risk management. This study combines social technical systems theory with the technology–organization–environment framework, using panel data from Chinese listed construction firms to explore how digital transformation affects project risk management. Key findings reveal that digital transformation significantly boosts risk management through two distinct pathways. While environmental governance capacity and green innovation efficiency both serve as significant mediators, the study identifies a notable disparity in the driving forces: digital transformation exerts a stronger impact on green innovation efficiency (17.8%) compared to environmental governance (4.4%). However, the resulting mediating effects of these two paths are found to be remarkably similar (0.0060 vs. 0.0068). Furthermore, labor investment efficiency is identified as a critical boundary condition, with a threshold effect (−0.385) below which the benefits of digital transformation weaken. These findings provide empirical evidence from Chinese context regarding the “technology-institution” co-evolution mechanism in construction. While centered on China, the study offers valuable insights for global stakeholders on how to harness digitalization to mitigate project risks and enhance sustainability. Full article

Industrial Control Systems (ICSs) face dual imperatives: protecting critical infrastructure from escalating cybersecurity threats while reducing the environmental impact of AI-powered defense mechanisms. Current deep learning anomaly detection approaches achieve security performance but consumes substantial computational resources, creating an environmental paradox in which AI solutions designed to protect infrastructure contribute to carbon emissions at scale. This competition between cybersecurity effectiveness and sustainability objectives intensifies as regulatory frameworks increasingly mandate both security resilience and environmental accountability. This research presents Green-USAD, a sustainability-first AI framework that inverts traditional design paradigms by integrating energy efficiency as a primary architectural constraint from inception rather than applying compression retrospectively. The proposed approach advances green computing for critical infrastructure through four key contributions: (1) a compressed architecture with validation-guided convergence protocols achieving competitive detection performance with minimal computational overhead; (2) a multi-objective optimization framework using the Analytic Hierarchy Process to systematically balance security and sustainability requirements; (3) a hardware-validated energy measurement methodology addressing reproducibility challenges in green AI literature; and (4) a comprehensive evaluation demonstrating cross-datasets and edge-deployment viability. Validation on ICS benchmarks demonstrates that sustainability-first design achieves substantial energy reduction while maintaining operational detection accuracy, with measured training consumption below 1% of conventional approaches and proportional carbon emission reductions. Comparative analysis against post hoc compression baselines establishes fundamental advantages of design-from-inception over train-then-compress paradigms. Edge device deployment on resource-constrained hardware confirms real-world applicability for distributed industrial environments. Results establish that robust cybersecurity and environmental sustainability represent unified rather than competing objectives when intelligent systems are designed with sustainability as a foundational principle. Full article

This study presents a definitive framework for Cocos nucifera (coconut) shell valorization, integrating high-resolution thermogravimetry with advanced machine learning. Physicochemical analysis confirms a high-energy feedstock (45.7% carbon, 71.5% volatiles), with SEM/XEDS and FTIR revealing heterogeneous, lignocellulosic, catalytic-rich structural matrix. TG/DTG analysis identified distinct degradation windows: hemicellulose (135–395 °C), cellulose (270–430 °C), and protracted lignin decomposition (275–675 °C). Kinetic modeling indicates that pyrolysis follows a third-order (F3) continuous degradation mechanism across the studied range, supported by high correlation coefficients (R² = 0.93–0.96). The mean kinetic and thermodynamic parameters—specifically an activation energy of 165 kJ·mol⁻¹ (calculated across the 10–60 wt% conversion range during hemicellulose and cellulose pyrolysis), a positive activation enthalpy (159 kJ·mol⁻¹), and a Gibbs free energy of activation (155 kJ·mol⁻¹)—suggest that the thermochemical conversion of coconut shell is an endothermic, non-spontaneous process with moderate energy requirements. Furthermore, the integration of kNN machine learning yielded near-perfect predictive metrics (R² ≈ 1.000) using optimized hyperparameters (k = 85 for TG, k = 100 for DTG, and k = 50 for conversion). These findings suggest that coconut shells can be efficiently valorized as a high-energy feedstock, with data enabling reliable and optimized prediction of thermal degradation to minimize experimental waste. Full article

Plastic pollution is a global environmental crisis, and microbial degradation represents a promising remediation strategy. While bacteria have been widely studied, yeasts offer unique advantages for plastic degradation due to their metabolic versatility, stress tolerance, and enzymatic capabilities. However, plastic degradative yeasts have not been reviewed comprehensively. Although several yeasts capable of degrading polyethylene terephthalate (PET) or polyethylene (PE) have been reported (e.g., Moesziomyces antarcticus, Candida tropicalis, Yarrowia lipolytica and Rhodotorula mucilaginosa), degraders of other plastic types are less studied. Although some yeasts can assimilate carbon from plastics, the diversity of yeasts capable of participating in plastic mineralization remains vastly underexplored. In recent years, yeast cell surface display systems for bacterial PETase and fungal cutinase have been developed, demonstrating promising PET degradation efficiency. However, PETase is feedback-inhibited by the intermediate product mono(2-hydroxyethyl)terephthalate (MHET). Systems synergizing PETase with MHETase have shown superior stability during long-term PET degradation and enable large-scale depolymerization of PET waste. For high-crystallinity PET, fungal hydrophobins can be used to modify the surface hydrophobicity of PETase-displaying yeast cells, facilitating their attachment to hydrophobic PET surfaces and ultimately enhancing the degradation efficiency of the whole-cell biocatalyst. Limitations of current research and future directions are also discussed. Full article

Zinc sulfide (ZnS) particles and zinc sulfide@multiwalled carbon nanotubes (ZnS@MWCNT) composites were synthesized and characterized using energy-dispersive X-ray (EDX) spectroscopy, X-ray diffraction (XRD), scanning electron microscopy (SEM), thermogravimetric analysis (TGA), and Raman spectroscopy. Photocatalytic degradation activity of methylene blue (MB) under ultraviolet (UV) at 254 nm light irradiation was assessed by UV-visible spectroscopy. The photocatalytic degradation efficiency of MB within 300 min reached 78.85% for ZnS particles and 82.85% for the ZnS@MWCNT composites. Therefore, in comparison to the ZnS nanoparticles, the hybrid ZnS@MWCNT composites exhibited higher photocatalytic degradation activity. The kinetics study for photocatalytic degradation of MB using both ZnS particles and hybrid ZnS@MWCNT nanocomposites followed the pseudo-first-order reaction rate law. Full article

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