Search Results (245)

Limonitic nickel laterite is difficult to sinter because of its high loss on ignition, high combined-water content, and complex refractory mineral composition, which often result in poor sinter strength and high solid fuel consumption. In this study, a pellet-sintering process was adopted to improve the sintering performance of limonitic nickel laterite. Pot sintering tests were carried out to investigate the effects of key process parameters—including moisture content, solid fuel dosage, return fines dosage, and drying–holding regime—on yield, tumble index, productivity index, and solid fuel consumption. The selected conditions were determined as follows: moisture content of 21%, solid fuel dosage of 5.8%, return fines dosage of 25%, drying at 450 °C for 5 min, and holding at 1000 °C for 10 min, under a fixed basicity of 1.5 and a bed height of 850 mm. Under these conditions, the yield, tumble index, productivity index, and solid fuel consumption reached 70.19%, 57.87%, 1.37 t·m⁻²·h⁻¹, and 95.86 kg·t⁻¹, respectively. Compared with conventional sintering, pellet sintering increased the yield, tumble index, and productivity index by 24.05%, 35.56%, and 31.73%, respectively, while reducing solid fuel consumption by 22.87%. XRD, OM, quantitative image analysis, and SEM–EDS analyses showed that pellet sintering reduced the average two-dimensional pore area fraction from 33.29% to 18.05% and the large-pore area fraction from 22.25% to 11.61%, while promoting a more continuous bonding structure characterized by a spinel-rich mineral framework, spinel–olivine eutectic-type composite bonding phases, and SFCA-type bonding phases. These results demonstrate that pellet sintering is a feasible route for improving the sintering performance and consolidation behavior of limonitic nickel laterite. Full article

Black soldier fly (Hermetia illucens) larvae meal (BSF meal) has emerged as a promising sustainable protein source in aquafeed formulation. This study examined the effects of graded BSF meal inclusion (0%, 20%, 40%, 60%, 80%, and 100% fishmeal replacement) and die head temperature (80 °C, 100 °C, and 120 °C) on the physical properties of extruded diets for Asian seabass (Lates calcarifer), with particular attention to their interactive effects. Both factors significantly affected most pellet quality parameters (p < 0.05), with the exception that no significant interaction effect was observed for moisture content (p = 0.2817). PDI increased progressively with BSF meal inclusion, peaking at 99.14% at 100% substitution and significantly exceeding the control. Higher BSF meal inclusion levels were associated with reduced expansion ratio (ER), bulk density (BD), and sinking velocity (SV). Notably, pellets produced at 80–100% BSF meal inclusion combined with moderate die temperatures (80–100 °C) achieved complete buoyancy (SV = 0.00 m/s). Processing at 80 °C yielded the highest ER and water absorption index (WAI), while 120 °C was associated with elevated water solubility index (WSI), indicating a higher risk of nutrient leaching. These results suggest that BSF meal can replace fishmeal at up to 100% without compromising pellet durability. Extrusion of BSF-based diets at 60–100% inclusion and 80–100 °C is recommended to achieve an optimal balance of structural integrity, hydration properties, and buoyancy for Asian seabass feeds. Full article

Transient extrusion defects are a fundamental process control challenge in fused granular fabrication (FGF), arising from the finite melt pressurization time of screw-driven extruders at each start–stop event. This study presents an integrated experimental and analytical framework for the characterization and open-loop feedforward compensation of these transient dynamics, demonstrated on two composite thermoplastic feedstocks: a recycled random polypropylene (RPP1) and a 20 wt% wood-fiber-reinforced polypropylene composite (WFPP). Unlike prior filament- or single-material feedforward strategies, this framework derives and statistically validates material-specific compensation parameters across two rheologically distinct feedstocks. Single-layer road experiments were conducted on a custom instrumented FGF platform across a 2³⁻¹ half-fraction factorial design varying melt temperature, print acceleration, and nozzle diameter, with screw speed stepped among 20, 40, and 80 RPM to excite transient states; deposited road geometry was digitized and spatially registered to the synchronized process signals. Main-effects regression confirmed that nozzle diameter is the dominant predictor of mean road width, while screw velocity exerts a significant negative effect attributable to speed-dependent backflow. Prediction-error minimization on the pooled multi-experiment dataset yielded a parsimonious first-order transfer function, G(s) = 0.990/(1 + 1.909s), whose time constant is physically attributed to melt compressibility in the barrel volume upstream of the nozzle restriction. This model was embedded in a G-code post-processor implementing two sequential corrections: a material-specific steady-state slip gain and a discrete linear-advance term parameterized by the identified time constant. For RPP1 at the nominal gain, the print latency interquartile range decreased from 5–20 mm to 2–8 mm without degrading steady-state dimensional accuracy; the combination of nominal gain with active retraction further reduced latency to near-zero. Analysis of covariance (ANCOVA) confirmed that optimal feedforward gains are statistically material-dependent across all three quality metrics (p < 0.05), providing statistical justification for material-specific compensator parameterization. The results establish a practical, hardware-agnostic route to reduce transient deposition defects in pellet-based additive manufacturing, extensible to additional feedstocks. Full article

Carbon dioxide (CO₂) capture through adsorption using porous materials has emerged as a promising strategy for mitigating industrial greenhouse gas emissions. However, selecting an optimal adsorbent material under varying operating conditions remains a complex and time-consuming process when relying solely on experimental studies. In this project, a machine-learning-based framework is developed to predict CO₂ adsorption capacity and identify the most suitable adsorbent material using process and material parameters. A comprehensive dataset was constructed comprising multiple classes of adsorbent materials including activated carbon, zeolites, metal–organic frameworks (MOFs), porous organic polymers (POPs), alumina/silica, and amine-functionalized sorbents. The dataset includes key parameters such as temperature, pressure, CO₂ mole fraction, humidity, BET surface area, micropore characteristics, amine loading, heat of adsorption, particle density, pellet diameter, and bed void fraction. Two machine learning models based on the XGBoost algorithm were implemented. An XGBoost Regressor was used to predict the experimental CO₂ adsorption capacity, while an XGBoost Classifier was trained to identify the type of adsorbent used based on the input parameters. The models were trained and validated using a train–test split approach to ensure reliable performance evaluation. The results demonstrate that gradient boosting models can accurately capture complex nonlinear relationships between adsorption conditions, material properties, and adsorption performance. The developed framework provides a fast and efficient predictive tool that can assist researchers and engineers in screening adsorbent materials and optimizing CO₂ capture systems for industrial applications. Using this model, one can predict the adsorption capacity of any adsorbent used in the training dataset and predict its type with 95% accuracy. Full article

Alfalfa densification is a critical step in feed utilization and biomass energy conversion because it directly affects the transport efficiency, storage stability, and energy consumption of biomass processing systems. However, the thermodynamic behavior of the densification process remains poorly understood, especially under open-die conditions without external heating. This study investigated the thermo-mechanical characteristics of alfalfa pellet open-die densification without external heating by combining experimental measurements with ANSYS macro-continuum simulation. Stress transmission and temperature field distributions were analyzed. The results showed that the pellet quality index under different process conditions remained above 800, meeting the requirements for pelleted feed. Moisture content had a more significant effect on forming pressure than other factors; as moisture content increased, the forming pressure decreased. At an aspect ratio of 5.0, the forming pressure was below 45 kN. Simulation results further indicated that aspect ratio had a stronger influence on frictional behavior during densification. Under an aspect ratio of 5.0, the energy consumption was 888.53 J, and the heat flux reached 0.0062 W/mm². These results indicate that frictional dissipation driven by radial force is the dominant mechanism governing thermo-mechanical coupling. Moisture content and aspect ratio significantly affected both peak compression force and coupling intensity. Although reducing moisture content or increasing aspect ratio improved pellet quality, it also increased die load due to enhanced radial force. The coupling intensity followed the order: peak pressure stage > moving stage > compression stage. These findings reveal the evolution of stress and temperature fields during alfalfa densification, offering critical theoretical guidance for optimizing densification process parameters. Full article

As the Italian hop industry undergoes consolidation, assessing the environmental pressure of diverse cultivation and processing models is essential for sustainable growth. This study characterizes the Product Environmental Footprint (PEF) of Italian hop production through a multi-case analysis of eight representative farms. A primary data collection tool was utilized to quantify resource inputs, including water management, nutritional strategies, and phytosanitary defense. Following a rigorous thermodynamic consistency screening of the field data to eliminate unrepresentative parameters, the life cycle inventory focused on two validated regional anchor cases. The findings reveal a high degree of management heterogeneity, with dry cone yields ranging from 400 to 1673 kg of dry matter per hectare. Two functional units were defined: 1 kg of fresh hop cones (FU1) to assess cultivation impacts, and 1 kg of processed products (FU2) at the brewery gate to evaluate the full supply chain. Integrating deterministic life cycle impact outputs with a probabilistic Monte Carlo uncertainty analysis, the results indicate that the environmental impact varies significantly across commercial formats: Cryogenic Powder (2.33 ± 0.34 mPt/kg) represents the most resource-intensive format, while Raw Bales and T90 Pellets from high-yield models exhibit scores as low as 1.36 and 1.55 mPt/kg, respectively. The study identifies the agricultural phase as the primary environmental hotspot, driven predominantly by water deprivation. To address these burdens, a Sustainable Italian Hop (SIH) integrated scenario was developed. By combining precision irrigation, thermal decarbonization via biomass valorization, and a direct-to-pellet processing flow, this model achieved a 70% total reduction in the environmental footprint score (0.465 ± 0.076 mPt/kg) and an 86% reduction in water use impacts. Finally, the socio-technical and financial barriers to implementing the SIH framework are qualitatively evaluated. These results provide actionable benchmarks for aligning the emerging Italian hop supply chain with European Union climate neutrality objectives. Full article

Driven by the urgent demand of the steel industry for utilizing low-grade, high-crystal-water iron ores, this study focuses on the thermal decrepitation problem in Guisha limonite pellet preparation caused by goethite dehydroxylation. Different from previous studies that mainly focused on single factors or single performance indicators, this work establishes a multi-factor experimental framework that simultaneously considers bentonite dosage, preheating temperature, and pellet size. This framework enables the strength–decrepitation trade-off of Guisha limonite pellets to be evaluated quantitatively rather than empirically. This work systematically investigated bentonite addition (0.8–1.6 wt%), preheating temperature (600–800 °C), and pellet diameter (9–13 mm). These factors were evaluated in terms of thermal cracking mass ratio and compressive strength. Their interactive effects on thermal cracking behavior and mechanical properties were quantitatively revealed. A target-oriented dual-window process control strategy was then proposed. The results show that thermal cracking intensifies with increasing preheating temperature and decreases with increasing bentonite content; compressive strength peaks at 1.2 wt% bentonite (approx. 1456 N). On this basis, a Min–Max normalization and weighted scoring method was adopted. A quantitative decision-making model was established for strength-prioritized and safety-prioritized objectives. The model identified two optimal process control windows at 1.2 wt% and 1.4 wt% bentonite. An optimized thermal regime—preheating at 700 °C, roasting at 1250 °C, and slow furnace cooling—was established. This regime provides directly referable process parameters. It also offers a decision-making framework for pellet production of similar ores. Full article

Sustainable production in dental and orthodontic 3D printing has gained increasing attention due to environmental concerns and the need for cost-effective and resource-saving solutions. This study presents a proof of concept for using recycled polymers and fused granular fabrication (FGF) in a closed-loop 3D printing approach, omitting intermediate filament manufacturing. A desktop 3D printer served as the kinematic platform and was modified with a pellet-based extruder to directly process recycled polyethylene terephthalate glycol (PETG) flakes, obtained by shredding previously printed PETG parts, into dental models. Dimensional accuracy was evaluated using optical 3D scanning analysis. The results indicate that models produced from recycled PETG are, in principle, suitable for dental and orthodontic applications within the investigated scope. This technical note provides initial evidence supporting the integration of recycled thermoplastics into dental and orthodontic model fabrication as part of sustainable additive manufacturing workflows. Potential pathways for workflow integration in clinical and laboratory environments, as well as directions for future research, are outlined, including the optimization of printing parameters and process stability. The main technical challenges were unreliable feedstock flow, causing bridging and jamming, while thermal creep from insufficient inlet cooling promoted premature softening of the flakes, causing torque spikes and unstable feeding. Full article

Energy consumption and different methods for determining energy efficiency were evaluated for drying of extruded rainbow trout feed pellets using a pilot-scale, heated air, integrated conveyor dryer and cooler. Impact of drying parameters on product quality, especially final moisture and pellet durability index (PDI), was also studied. From an initial moisture of 21.2 to 22.1% wet basis (wb), the drying–cooling process reduced the pellet moisture to 3.5 to 5.0% wb. Dryer throughput (82–121 kg/h) did not have statistically significant impact on final moisture (p = 0.0965) although the highest throughput corresponded to highest moisture; but increase in drying temperature from 93 to 115 °C led to a significant decrease in final moisture (p = 0.0285). Increase in dryer throughput led to a significant increase in PDI from 82.8 to 88.0% (p = 0.0003), while increase in drying temperature resulted in a slight decrease in PDI from 84.3 to 83.6%, although not statistically significant (p = 0.0811). Sorghum-based aquatic feed had a slightly lower PDI than wheat-based feed (82.8 versus 83.7%, respectively), but the difference was not statistically significant (p = 0.3009). Differences in pellet durability were attributed primarily to structural weakness induced by product shrinkage during drying, which in turn was impacted by drying rates. Specific energy consumption (SEC) during drying decreased from 136.3 to 101.1 MJ/kg-water with increase in throughput and increased from 122.5 to 150.1 MJ/kg-water with increase in drying temperature. An inverse trend was observed for various measures of dryer energy efficiency, with increase in efficiency for higher throughput and decrease for higher temperature. Sorghum-based aquatic feed had a higher drying SEC as compared to wheat-based feed and a lower energy efficiency. Overall, the results highlighted trade-offs between throughput, drying efficiency and pellet quality during drying of aquatic feeds. Full article

To address the poor coating quality and low efficiency of Astragalus membranaceus seed pelletizing, this study combined theoretical analysis, DEM simulations, and experiments. The motion and force conditions of seed-powder particles were analyzed to identify key parameters. Using the coefficient of variation (Cv) as the evaluation index, the disc diameter, pan edge inclination, and rotational speed were optimized via response surface methodology. The optimal structural parameters were 605.5 mm, 15.7°, and 20.3 r·s⁻¹. Liquid adhesion was represented by a custom time-varying cohesion model in DEM. Physical experiments showed that the optimized structure increased the pelletization qualification rate from 74.8% to 94.3%. Orthogonal experiments further optimized the process parameters: a single powder feed of 20 g, a single binder solution feed of 25 mL, and a coating duration of 8 min, achieving a qualification rate of 98.3%. Seedling emergence tests revealed that pelleted seeds had a significantly higher emergence rate (97.6%) than non-pelleted seeds (67.3%). These findings provide theoretical and technical references for pelletizing the coating of irregularly shaped seeds. Full article

The transition toward industrial-scale, year-round production of Pleurotus pulmonarius necessitates efficient and standardized spawn production. Liquid spawn technology plays a pivotal role in this process; however, recommended formulations and science-based quality criteria remain lacking. This study aimed to screen a high-performance liquid spawn medium and define key quality parameters for industrial application. Ten culture media formulations were evaluated to determine their effects on mycelial growth, as well as the subsequent yield and quality of fruiting bodies. The optimal formulation (Formula 4) contained glucose (1.6%), soybean meal (0.3%), corn flour (0.2%), peptone (0.2%), KH₂PO₄ (0.1%), and MgSO₄ (0.055%). The growth rhythm of the selected formulation was meticulously tracked, leading to the identification of a critical inoculation window between 4.75 and 5.5 days. Spawn within this window exhibited a mycelial biomass of 1.60~1.86 g/L, pellet diameter of 1.83~1.92 mm, pellet density of 12.25~13.75 per mL, and fermentation broth pH of 6.35~6.44, which were strongly correlated with peak yield (up to 284 g/bag) and premium-grade ratio (up to 87.97%). The multi-parameter composite standard is proposed as a practical tool for quality control in industrial fermenters, enabling precise harvest timing and ensuring the consistent, high-yield, and high-quality production of P. pulmonarius. Full article

Gas-phase oxidation of volatile organic compounds (VOCs) with the aid of ozone can be an attractive, energy-efficient way of treating exhaust gas streams in a low-temperature process, enabling the sustainable operation of industrial installations in a natural environment. This work is focused on the efficiency and kinetics of toluene oxidation with ozone towards CO₂ and H₂O in the presence of a SiO₂-supported cobalt catalyst. A kinetic model is proposed based on a simplified reaction mechanism, with the parameters determined from measurements carried out in a fixed-bed reactor at 40–65 °C under conditions ensuring negligible mass transfer resistance. The proposed model provided satisfactory agreement between the predicted and measured toluene and ozone conversion rates and the formation rate of CO₂, as well as in conditions when mass transfer resistance due to internal diffusion in the catalyst pellet was necessary to consider. The discussed results provide an assessment of the space velocity and ozone usage necessary to achieve a given degree of toluene conversion and mineralization to CO₂. The proposed model can be used for the design of a sustainable, low-temperature ozone-assisted catalytic process of VOC abatement. Full article

The conversion of biowaste into biofertilizer offers a sustainable alternative to synthetic fertilizers by supporting nutrient recycling and agricultural productivity. However, industrial pelletization can compromise the viability of microorganisms essential for biofertilizer function. In this study, a 40/60 (dry wt%) blend of biochar and commercial potting mix (biowaste blend) was used to produce a biochar biofertilizer (BCBF) through pelletization. Microbial population dynamics were then assessed at different stages of the BCBF pelletization process and under variations in key pelleting parameters—moisture content (15–35%), die surface temperature (70–180 °C), and feed rate (75–150 lb/h). The results showed that fungal and protozoan populations increased during the composting stage of BCBF, but declined to undetectable levels following drying and coating of the BCBF pellets. Bacterial populations increased after composting, but decreased substantially after pelleting and subsequent storage of the BCBF, while actinobacteria remained low throughout the pelletization process. Elevated temperatures and moisture loss were identified as major contributors to microbial inactivation during pelletization. These findings demonstrate that careful control of pelletization parameters is essential for maintaining microbial viability, thereby supporting the development of higher-quality, microbially active biochar-based biofertilizers. Full article

Bait costs constitute 40–50% of the total expenditure in river crab aquaculture, highlighting the critical need for accurately assessing crab growth and scientifically determining optimal feeding regimes across different farming stages. Current traditional methods rely on periodic manual sampling to monitor growth status and artificial feeding platforms to observe consumption and adjust bait input. These approaches are inefficient, disruptive to crab growth, and fail to provide comprehensive growth data. Therefore, this study proposes a machine vision-based monitoring system for river crab feeding platforms. Firstly, the Contrast Limited Adaptive Histogram Equalization (CLAHE) algorithm is applied to enhance underwater images of river crabs. Subsequently, an improved YOLOv11 (You Only Look Once) model is introduced and applied for multi-target detection and counting in crab ponds, enabling the extraction of information related to both river crabs and bait. Concurrently, underwater environmental parameters are monitored in real-time via an integrated environmental information sensing system. Finally, an information processing platform is established to facilitate data sharing under a “detection–processing–distribution” workflow. The real crab farm experimental results show that the river crab quality error rate was below 9.57%, while the detection rates for both corn and pellet baits consistently exceeded 90% across varying conditions. These results indicate that the proposed system significantly enhances farming efficiency, elevates the level of automation, and provides technological support for the river crab aquaculture industry. Full article

This study addresses the management and optimization of decentralized bioresource energy generation under conditions of political instability, using Ukraine as a representative case. The research aims to enhance energy security and operational resilience where centralized energy infrastructure is vulnerable to disruption. A high-efficiency technology for decentralized heat generation is proposed, based on the direct combustion of non-standard agricultural biomass with a one-year renewal cycle. The methodology combines experimental and statistical analysis of biomass feeding processes with advanced three-dimensional modeling of mixture formation and combustion, as well as the development of an artificial intelligence-driven automated control system. The system enables the use of sunflower, rapeseed, wheat, corn, and other agricultural residues with variable particle size and moisture content of up to 40%, without the need for pre-drying or pelletization. An original jet–vortex bioheat generator and optimized dosing systems were designed to ensure continuous and stable combustion. An operational algorithm allowing stable performance within 25–100% of nominal capacity was formulated based on statistical evaluation of screw feeder behavior and optimization of adjustable electric drive parameters, ensuring thermal carrier temperature stability within ±1–2 °C. The main novelty lies in the integrated optimization framework combining unconventional biomass utilization, adaptive electric drive control, and AI-based automation to achieve high energy efficiency and environmental performance. The results indicate that such decentralized systems can substantially strengthen national energy security and support sustainable energy supply in unstable political environments. Full article