Search Results (4,536)

The growing demand for sustainable construction materials has intensified research on eco-efficient lightweight artificial aggregates (LWAs). This study evaluates the feasibility of producing LWAs with potential structural applicability from smectite (bentonite) clays from Paraíba, Brazil, combined with porcelain polishing residue (PPR). Raw materials were comprehensively characterized by XRD, XRF, and TGA, confirming montmorillonite as the dominant mineral phase in the clays and revealing the high silica and alumina content of the residue. The incorporation of PPR proved essential, as the clays alone could not be effectively sintered. An experimental matrix comprising ten formulations across four clay types was tested at five sintering temperatures (1100–1250 °C), resulting in 50 formulation–temperature experimental conditions. Approximately 66% of the 50 formulation–temperature experimental conditions met key physical and mechanical criteria typically associated with structural lightweight aggregates, demonstrating strong potential for use in structural lightweight concrete, although concrete-scale validation is still required to confirm their performance within cementitious mixtures. Mechanical performance was strongly influenced by thermal processing and residue incorporation, with peak strengths observed within a narrow sintering window around 1150 °C, where conditions were consistent with enhanced vitrification and pore evolution. The lightweight behavior was directly associated with the formation and expansion of internal pores during sintering, which are essential for density reduction. In this context, an optimal balance between mechanical strength and internal porosity must be achieved, since excessive densification may limit pore development. Water absorption was used as an indirect indicator of pore connectivity and internal structure evolution. An environmental assessment based on modeled production scenarios demonstrated that increasing residue content and reducing firing temperature generally reduced the calculated cumulative energy demand and global warming potential under the adopted inventory assumptions. Because thermal-energy requirements were estimated rather than directly measured in industrial kilns, the environmental results are interpreted as comparative scenario-based estimates rather than direct measurements of industrial-scale performance. Overall, the developed aggregates show strong potential for structural lightweight concrete applications, although concrete-scale validation remains necessary to confirm their performance in cementitious mixtures. This approach establishes a quantitatively grounded framework for designing low-carbon LWAs, contributing to decarbonization strategies in the ceramic and construction sectors. Full article

Turmeric (Curcuma longa L.) is one of the most important spice crops and a valuable medicinal plant, but it is seriously affected by various types of diseases such as fungal, bacterial, nematode and viral diseases. In this paper, a complete mathematical model of the turmeric plant disease dynamics is developed under a fractal-fractional model in this context, encompassing all four types of pathogens and associated treatment classes. The fractal-fractional Caputo derivative operator captures memory effects and, through its fractal exponent, a genuine deformation of the classical memory kernel, allowing the underlying biological dynamics to be represented more flexibly than under the classical integer-order derivative; we do not, however, claim that this kernel deformation corresponds to demonstrated self-similarity or spatial heterogeneity in the turmeric plant–pathogen system. We show the positivity and boundedness of the solutions, calculate the next-generation matrix approach-based basic reproduction number ${\mathcal{R}}_0$ and investigate the local and global stability of both disease-free and endemic equilibria by Lyapunov functionals. A sensitivity analysis of ${\mathcal{R}}_0$ is conducted to determine the most important parameters influencing disease transmission and control. The existence and uniqueness of solutions and Ulam-Hyers stability of solutions are established by fixed point theory. For the associated integer-order system, we formulate an optimal control problem is formulated with three time-dependent controls: the prevention effort ($u_1$), the enhancement of treatment ($u_2$), and the care management ($u_3$), and the optimality conditions are derived via Pontryagin’s maximum principle. Numerical simulations are conducted with three different fractal-fractional operators, namely Caputo, Caputo-Fabrizio and Atangana-Baleanu. A deep neural network is developed and trained to approximate the solution of the integer-order system. The third-layer deep neural network consists of neurons of sizes 80, 32, and 24, with activation functions of logistic sigmoid, radial basis and hyperbolic tangent, respectively, and is trained to approximate the system dynamics with the fourth-order Runge-Kutta method as a reference. The DNN is found to be very accurate in predicting the values with Nash-Sutcliffe Efficiency between 0.79 and 0.99 and Theil Inequality Coefficient around ${10}^{-2}$ in all 11 compartments, and hence proved capable of being a good surrogate modelling tool for the ODE systems. The present work contributes towards SDG 2 (Zero Hunger) and SDG 3 (Good Health and Well-being) by laying a mathematical basis for integrated disease management in turmeric cultivation for sustainable agriculture and food security. Full article

Developing efficient technologies for vanadium recovery from refractory raw materials requires an understanding of the thermodynamic and electrochemical behavior of vanadium during acid leaching. This study investigates hydrogen peroxide-assisted sulfuric acid leaching of roasted vanadium-bearing ores from the Greater Karatau region using standard Gibbs free-energy calculations, Pourbaix diagrams, and electrode-potential calculations in HSC Chemistry 8.1.5. The reactions of the model vanadates NaVO₃, Na₃VO₄, and Na₄V₂O₇ with H₂SO₄ exhibited negative ΔG⁰ values at 25 and 65 °C, indicating thermodynamically favorable acid dissolution. The more negative ΔG⁰ values in the presence of H₂O₂ largely reflect the thermodynamic contribution of its decomposition and do not directly quantify its effect on vanadium extraction. Pourbaix diagrams indicated VO₂⁺ as the thermodynamically stable dissolved V(V) species under strongly acidic oxidizing conditions. The higher equilibrium potential of the H₂O₂/H₂O couple relative to VO₂⁺/VO²⁺ indicates the thermodynamic feasibility of oxidizing residual V(IV) to V(V). Competing reactions of Na₂CO₃ with mineral–matrix components may consume the sodium reagent during roasting. The calculations were qualitatively consistent with previously obtained vanadium extraction of 78.70–80.15% from roasted Balasauskandyk and Kurumsak ores at 65 °C. An integrated five-stage physicochemical model is proposed, requiring direct experimental validation of individual stages. Full article

Post-contingency corrective dispatch restores a feasible AC voltage–current state, but the corrected state is usually not carried forward to responsibility allocation. This paper proposes a matrix state-to-responsibility mapping (MSRM) model that maps the corrected AC state to network use, loss allocation, regional marginal cost, and line-level carbon responsibility indices. The model treats the corrected post-contingency state as a common attribution basis, so feasibility recovery and responsibility assessment are linked within the same state-dependent mapping. Corrective dispatch is formulated in rectangular coordinates as a constrained optimization problem that minimizes generation cost and controllable redispatch amount under current balance, generator output, voltage, and line capacity constraints. The resulting voltage–current solution is used to build generator-side and load-side contribution matrices, from which settlement quantities and line-level responsibility are obtained through a unified matrix sequence. Carbon responsibility is calculated after redispatch from the generator-side traced flow matrix and generator carbon intensity matrix; it is not imposed as a dispatch objective. A feasibility-guided adaptive particle swarm optimization method is adopted to obtain the corrected state. Reported data from a practical 58-bus Taipower 345 kV transmission system are used for validation. In the line outage and generator outage cases, maximum line loading is reduced from 110% to 98.973% and from 103.99% to 98.99%, respectively. The positive carbon responsibility of Line 36 decreases from 91.72 to 88.80 tCO₂/h, whereas that of Line 80 remains nearly unchanged despite wider redispatch. In the two tested contingency cases, feasibility recovery, settlement quantities, total emissions, and line-level responsibility change in different directions after corrective redispatch, indicating that these indices should be evaluated separately under stressed post-contingency operation. Full article

Pressure-dependent pore-volume deformation is a critical but poorly constrained variable in dynamic reserve assessment for ultra-deep fractured-vuggy carbonate reservoirs, where fractures, dissolution pores, and vugs respond differently to effective-stress loading. In this work, a pore-structure-aware evaluation strategy was developed by integrating high-temperature and high-pressure volumetric measurements with data-driven regression. Twelve carbonate core plugs from the Ordovician Yijianfang and Yingshan formations of the Fuman Oilfield were selected to represent matrix-pore, dissolution-pore, fracture-vug, and fracture-dominated pore systems. Stepwise net-pressure experiments were performed under simulated reservoir conditions, and pore-volume compressibility (Cp) was calculated from corrected pore-volume changes. Measured C_p values reveal a distinct stress-sensitive response: C_p declines sharply during the low-net-pressure stage and then tends toward a quasi-stable level as net pressure increases, indicating progressive closure of mechanically compliant fractures, narrow throats, and weakly supported dissolution pores. Although porosity is positively associated with Cp, samples with comparable porosity display markedly different compressibility values, confirming that pore-space geometry and fracture-related compliance must be considered. Eight representative regression algorithms were then compared, using net pressure, porosity, permeability, initial pore volume, surface porosity, temperature, and a pore-structure index as model inputs. To further assess model generalization to completely unseen core plugs, additional core-ID-based leave-one-core-out (LOCO) validation was performed for k-nearest neighbors and AdaBoost. Under this grouped validation, k-nearest neighbors yielded an RMSE of 13.5978 × 10⁻⁴ MPa⁻¹ and an R² of 0.8408, whereas AdaBoost achieved an RMSE of 10.0160 × 10⁻⁴ MPa⁻¹ and an R² of 0.9136, indicating greater cross-core robustness of AdaBoost. Permutation-importance analysis of the split-specific KNN model indicated that net pressure, porosity, surface porosity, and pore-structure index made the largest predictive contributions within that model. Moreover, the predicted normalized Cp values reproduced the experimentally observed decreasing trend with increasing net pressure, supporting the physical consistency of the k-nearest neighbors predictions. The proposed experimental–machine learning framework offers a pressure-dependent method for estimating pore-volume compressibility within the geological and petrophysical domain represented by the investigated Fuman Oilfield cores, and provides more representative inputs for material-balance analysis, dynamic reserve evaluation, and production adjustment. Full article

The aim of this study is to evaluate whether a random-forest model trained on conventional well logs can reconstruct missing shear-wave slowness (DTS) with sufficient transparency for downstream geomechanical calculations. Field-acquired DTS and 12 conventional curves from Well A were used for model development and progressive feature screening; an 11-variable subset was retained as a parsimonious input set, and Well Y was used as an external cross-block test. A re-audit of the prediction pairs embedded in the manuscript gave R² = 0.97, MAE = 3.404 μs/ft, and RMSE = 5.718 μs/ft for the plotted Well A profile (n = 1873), and R² = 0.91, MAE = 3.103 μs/ft, and RMSE = 3.658 μs/ft for Well Y (n = 255). Because the archived dataset lacks the raw feature-by-depth matrix, complete training settings, aligned density data, and core-based static-property measurements, depth-blocked retraining and numerical validation of mechanical properties could not be performed. The contribution is therefore an error-audited two-well DTS-completion case study and a transparent interface to potential geomechanical applications, not a validated hydraulic-fracturing design method. Full article

Short-fiber-reinforced thermoplastics are widely used in lightweight structural applications, but reliable prediction of their Young’s modulus remains challenging because classical analytical models usually neglect interfacial effects. In this study, the Cox–Krenchel model was extended by an adhesion efficiency factor derived from surface-energy-based interfacial tension to account for incomplete elastic load transfer at the fiber–matrix interface. Injection-molded polypropylene (PP) and polyamide 6.6 (PA 6.6) composites reinforced with basalt and glass fibers were produced and characterized experimentally. Model inputs comprised the matrix and fiber modulus, measured fiber volume fraction, experimentally determined individual fiber lengths incorporated through an effective Cox length efficiency factor, and experimentally determined fiber orientation factors. Interfacial tension was calculated from polar and dispersive surface-tension components using the Owens–Wendt–Rabel–Kaelble approach. The classical Cox–Krenchel model described the PA–basalt system with high accuracy but systematically overestimated the stiffness of the PP-based systems. Using a single globally calibrated proportionality constant of ω = 0.8, the adhesion-extended model reduced the mean absolute percentage error on the full condition-specific dataset of 55 data points from 14.2% to 2.7%. The results indicate that morphology remains the dominant basis of stiffness prediction, while surface-energy-based interfacial compatibility provides a relevant additional descriptor for residual system-dependent error. For the investigated systems, the proposed extension improved predictive accuracy while preserving the analytical simplicity of the Cox–Krenchel framework. Full article

Digital sport platforms increasingly mediate consumer experience through AI-driven interfaces, yet it remains unclear which interactive elements consumers treat as baseline expectations versus genuine engagement drivers. An integrated Kano-SERVQUAL model was applied to evaluate the service quality of virtual cycling platforms in this context. An online survey was conducted with 458 adults who regularly used a virtual cycling platform. Service quality attributes demonstrated a five-dimensional structure: tangibles, reliability, responsiveness, assurance, and empathy. Twenty service attributes were classified following Kano’s model, and Better–Worse coefficients and a combined impact score were calculated to identify strategic priorities. Twenty attributes clustered into four distinct regions based on Timko’s Better–Worse matrix. One-Dimensional Quality (High Better, High Worse) included technical infrastructure attributes such as content updates, platform composition, data consistency, connection stability, and server stability under large-scale connections. Attractive Quality (High Better, Low Worse) was characterized by differentiating features, including event diversity, reflection of user suggestions, tutorial guide clarity, verified workout programs, and post-ride reports. Must-Be Quality (Low Better, High Worse) comprised graphics quality, UI convenience, and avatar design baseline attributes whose absence triggers high dissatisfaction, along with pedal resistance response (Reverse quality). Indifferent Quality (Low Better, Low Worse) encompassed attributes including technical support, testing tools, competitive systems, reward systems, and personalized recommendations, representing lower priority features. Thus, consumer engagement with AI-mediated digital sport platforms is structurally non-linear, requiring attribute-differentiated management strategies that distinguish trust-critical interface reliability from engagement-driving personalization. These findings offer theoretical implications for consumer decision-making in interactive digital commerce, though trust, engagement, and decision-making were not directly measured as outcome variables in this study. Full article

Aiming at the technical bottlenecks of deep coalbed methane (DCBM) reservoirs, including ultra-low permeability, prominent stress sensitivity, difficulty in characterizing complex hydraulic fractures, and the inability to quantitatively differentiate produced free gas and adsorbed gas, this paper constructs a numerical simulation model coupling matrix, cleat fractures, hydraulic fractures and wellbores by adopting the matrix bordering treatment technique. This work couples a DCBM dual-porosity single-permeability model with the embedded discrete fracture model (EDFM) for numerical simulation. On the basis of the established numerical simulation model, a quantitative classification method for the proportions of free gas and adsorbed gas in produced DCBM is proposed to realize quantitative partitioning of the two gas components. Field verification based on vertical DCBM Well A demonstrates that the average relative error of daily gas production predicted by the proposed model is merely 7.54%, which delivers a 7.31% improvement in prediction accuracy compared with a commercial simulation software. Further parametric sensitivity investigations yield the following key findings: the gas content of DCBM reservoir acts as the dominant controlling factor of productivity, and an 8.1% rise in coalbed gas content yields a 98.07% increase in cumulative gas production; compared with the gas content, coalbed stress sensitivity ranks second among reservoir factors in terms of its influence on ultimate cumulative gas production. The impact of coalbed stress sensitivity is mainly reflected in the sharp productivity decline during the middle–late production stage. Hydraulic fracture length serves as the primary controlling factor for late-stage daily gas output; by contrast, early productivity is dominated by hydraulic fracture conductivity. Variations in bottom-hole pressure drawdown rate create marginal discrepancies in total cumulative production, and a drawdown regime of 0.05 MPa/d is recommended to maintain stable gas output over the entire production cycle. Quantitative classification calculation of free and adsorbed gas proportions in produced DCBM indicates that free gas only prevails in the early production stage and is quickly overtaken by adsorbed gas. After 660 days of production, free gas accounts for 33% of the total gas production of Well A, while adsorbed gas accounts for 67%. Moreover, the depletion of reservoir free gas is confined within the well drainage area, with nearly no pressure or gas content disturbance observed in far-well regions. The established model can provide theoretical support for dynamic productivity forecasting, production regime optimization and produced gas composition analysis of DCBM reservoirs. Full article

Alkyl-chain architecture may influence both the enzymatic synthesis and antioxidant performance of phenolic esters. This study examined the esterification of dihydrocaffeic acid with four isomeric C5 alcohols catalyzed by immobilized Candida antarctica lipase B (CALB). The isolated products were evaluated using process metrics, NMR, physicochemical predictions, density functional theory calculations, DPPH and ABTS assays, and pressure differential scanning calorimetry in flaxseed and grape seed oils. The isolated yields of n-pentyl, 2-methylbutyl, and 3-methylbutyl dihydrocaffeates were 61.25%, 49.87%, and 53.08%, respectively, whereas no measurable amount of the 2,2-dimethylpropyl ester was isolated under the applied conditions. The linear derivative showed the highest biocatalyst productivity and the most favorable reaction-stage material-efficiency indices. DPPH activity was similar across all isolated esters, whereas the 3-methylbutyl derivative showed the strongest ABTS activity. The lowest calculated O–H bond dissociation enthalpy was obtained for the 2-methylbutyl derivative. At 0.01%, all three esters provided greater oxidative protection than butylated hydroxytoluene under the applied PDSC conditions. Their effects were similar in flaxseed oil, whereas the n-pentyl derivative was clearly superior in grape seed oil. Under the applied reaction conditions, the linear and branched alcohols showed different synthesis outcomes, whereas antioxidant performance in oils was strongly matrix-dependent and not predicted by any single computational or solution-based descriptor. Full article

The macroscopic mechanical responses of cemented sand and gravel (CSG) are jointly affected by the mesoscopic properties of the aggregate, mortar matrix, and interfacial transition zone, while different parameters exhibit distinct magnitudes and directions of influence on strength, stiffness, and failure deformation. To establish a unified parameter priority across multiple macroscopic responses, a two-dimensional random aggregate finite element model was developed, and the elastic moduli and tensile strengths of the aggregate, mortar matrix, and interface were selected as six mesoscopic parameters. Bidirectional perturbations of ±5% and ±10% were introduced around the baseline state, and dimensionless local sensitivity coefficients were calculated using a central finite-difference formulation. Five statistically independent random aggregate realizations were further considered to evaluate the influence of mesostructural variability. The Ordered Weighted Averaging (OWA) operator and entropy weighting method were used to determine subjective and objective criterion weights, respectively, and a MULTIMOORA-based multi-response parameter-prioritization framework was established using the ratio system, reference point method, and modified multiplicative form. Across the five random realizations, the mean sensitivities of the mortar elastic modulus to the macroscopic elastic modulus and failure displacement are 0.5158 and 0.2664, respectively, while those of the interfacial tensile strength to compressive strength and failure displacement are 0.1550 and 0.4512, respectively. The ±5% and ±10% perturbations yield consistent parameter hierarchies, indicating stable local sensitivity results within the investigated neighborhood of the baseline state. Under the combined OWA–entropy weighting scheme, the multi-response parameter priority is ranked as mortar elastic modulus, interfacial tensile strength, aggregate elastic modulus, interfacial elastic modulus, mortar tensile strength, and aggregate tensile strength. The ratio system and modified multiplicative form yield identical rankings, and both show a Spearman rank correlation coefficient of 0.9429 with the reference point method. Weight-scenario analysis further shows that the mortar elastic modulus and interfacial tensile strength consistently remain the two highest-priority parameters, although their internal order varies with the criterion weights. The resulting ranking therefore represents a model- and evaluation-objective-dependent multi-response parameter priority and provides a quantitative basis for mesoscopic parameter screening and subsequent calibration of CSG numerical models. Full article

To conduct a scientific and comprehensive analysis of the spontaneous combustion tendency of sulfide ores and improve the safety production level of sulfur mines, an indicator system for determining the spontaneous combustion tendency of sulfide ores and a comprehensive classification standard for the spontaneous combustion tendency of sulfide ores were constructed. Based on this, a multidimensional information comprehensive analysis model for ore spontaneous combustion tendency was constructed by combining the interval analytic hierarchy process (IAHP) and the improved interval approximation analysis method. The interval judgment matrix was constructed by the interval analytic hierarchy process, and the weight of the spontaneous combustion tendency for evaluation indicators was calculated. By improving the interval approximation analysis, the indicators of the ore spontaneous combustion tendency were analyzed in the form of interval numbers, and the information potential was deeply explored to obtain multidimensional information such as the grade of the ore spontaneous combustion tendency and the reliability of the ore spontaneous combustion tendency, and then the comprehensive grade of the ore spontaneous combustion tendency was determined. By using this model, a multidimensional information analysis was conducted on the spontaneous combustion tendency of each ore layer in a certain sulfur iron mine, with the indicators of the ore spontaneous combustion tendency as the interval number. It was found that the 30-day oxidation weight gain rate exerts the most significant influence on ore spontaneous combustion. The ore in ore layer no. 1 was prone to spontaneous combustion with relatively reliable results, while the ores in ore layers no. 2 and 3 were susceptible to self-heating with highly reliable results. This study provides a reference and guidance for the targeted prevention of ore spontaneous combustion in the mine. Full article

Amanita muscaria contains two structurally related neuroactive isoxazole metabolites, ibotenic acid (IA) and muscimol (MUS), which differ markedly in pharmacological activity. IA acts as an agonist at NMDA and metabotropic glutamate receptors, whereas MUS is a potent GABAergic agonist. This review critically evaluates their chemistry and biosynthesis, biological variability, post-harvest transformation, analytical determination, and toxicological significance. Direct evidence demonstrates interspecific variation within Amanita section Amanita. Developmental evidence for A. muscaria is limited but direct: an older maturation study identified tissue-dependent changes in IA and MUS, while concentrations calculated for the whole fruiting body remained comparatively stable; observations in A. subglobosa provide additional species-specific evidence. Controlled studies also demonstrate processing-related changes during drying and heating, whereas storage effects remain condition-dependent and less completely characterized. Cross-study comparison is constrained by differences in species identification, tissue selection, developmental stage, hydration, sample handling, normalization, and analytical procedure. Quantitative study-level comparison shows that LC–MS/MS and UHPLC–MS/MS, capillary electrophoresis, GC–MS, NMR, and rapid ambient-MS approaches serve different matrices and analytical purposes. Their reported sensitivity, recovery, precision, and calibration performance cannot be ranked directly across studies, and matrix-specific validation remains essential. Broader fungal research provides mechanistic context for possible environmental regulation, but direct controlled evidence for stress-dependent IA biosynthesis in A. muscaria remains sparse. The IA/MUS ratio is best treated as a secondary chemical descriptor alongside absolute concentrations and a clearly defined normalization basis. Toxicological interpretation additionally requires consideration of total dose, preparation, matrix composition, and individual susceptibility. Full article

Practical training on embedded systems is a very good way to assess the skills of students in firmware development, real-time programming and hardware–software co-design. However, many low- and middle-income institutions still use closed, proprietary boards, such as the Altera DE series, which hide the physical behavior. To address this, a low-cost, fully reconfigurable Microcontroller Test Board (MTB) was designed and technically validated for application in undergraduate laboratories. The MTB is manufactured as a one-sided through-hole PCB via toner transfer and FeCl3 etching, with a PIC18F2550 in-circuit programmer and support for 28- and 40-pin targets including the PIC16F877A. The MTB integrates six functional blocks, providing five canonical input/output modalities on a single regulated 5 V/0.56 A rail: (1) an ICSP programmer; (2) a multiplexed seven-segment display; (3) an 8 × 8 LED matrix; (4) a matrix keypad with LCD calculator; and (5) a 10-bit ADC stage. All subsystems operate with a flicker-free refresh rate > 122 Hz. The total board power consumption is 6.72 W at 12 V DC, with the linear regulator dissipating 3.92 W under full load. Probe points allow for signal transparency. Models for regulator dissipation, ADC quantization, multiplex refresh duty cycle, LED current limiting, oscillator timing, matrix-scanning latency, LCD timing, keypad response and Fe³⁺ with Cu etch kinetics were first-principles. Bench measurements agree with model predictions to less than 3% error, and confirm worst-case design margins. The MTB provides analytical rigor with accessible hardware to enable measurable experiments in microcontroller labs. The platform is cost-effective, with a material cost of less than USD 18. Each signal is routed to probe points, providing significant cost reduction from commercial trainers, and a transparent hands-on laboratory resource for engineering curricula with limited resources. Full article

Biomethane recovery from lignocellulose is limited by the recalcitrance of the fibre matrix, which pretreatment can relieve. Thermal pretreatment is usually optimised through temperature, whereas the residence time of hydrothermal treatment is seldom isolated as an independent variable, and rarely without added acid. Willow (Salix viminalis) and maize silage (Zea mays) were treated by microwave autohydrolysis with explosive decompression at 130 °C, using residence times of 5, 15 or 25 min against an untreated control, and assessed for solubilisation, by-products, methane potential, kinetics and net energy balance. Relative to the control, the 25 min treatment raised methane potential by 189% in maize silage (to 384.8 ± 21.4 NmL CH₄ g⁻¹ VS) and by 129% in willow (to 333.5 ± 14.2 NmL CH₄ g⁻¹ VS), reaching 72–74% of the theoretical maximum. Silage gained 78% at the first treated point (5 min dwell), whereas willow showed no significant gain before 15 min; in willow, the methane gain tracked continuously released xylose (r = 0.996) rather than the early COD or glucose burst. Furanic by-products remained very low; indicative concentrations and total phenolics stayed below reported methanogenesis inhibition thresholds for phenol (direct equivalence between total phenolics and pure phenol not assumed), so yield rose monotonically without turnover. The incremental energy balance stayed negative; the estimated incremental energy recovery reached 74% of the calculated input for willow and 97% for silage at 25 min. Full article