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One of the most important challenges the tire industry faces is becoming carbon-neutral and using 100% sustainable materials by 2050. Utilizing materials from renewable sources and recycled substances is a key aspect of achieving this goal. Petroleum-based oils, such as Treated Distillate Aromatic Extract (TDAE), are frequently used in rubber compounds, and a promising strategy to enhance sustainability is to use bio-based plasticizer alternatives. However, research has shown that the replacement of TDAE oil with bio-based oils or resins can significantly alter the glass transition temperature (T_g) of the final compound, influencing the tire properties. In this study, the theory was proposed that using a plasticizer blend, comprising oil and resin, in a rubber compound would result in similar T_g values as the reference compound containing TDAE. To test this, the cycloaliphatic di-ester oil Hexamoll DINCH, which can be made out of bio-based feedstock by the BioMass Balance approach, was selected and blended with the cycloaliphatic hydrocarbon resin Escorez 5300. Various oil-to-resin ratios were investigated, and a linear increase in the T_g of the vulcanizate was obtained when increasing the resin content and decreasing the oil content. Additionally, a 50/50 blend, consisting of 18.75 phr Hexamoll DINCH and 18.75 phr Escorez 5300, resulted in the same T_g of −19 °C as a compound containing 37.5 phr TDAE. Furthermore, this blend resulted in similar curing characteristics and cured Payne effect as the reference with TDAE. Moreover, a similar rolling resistance indicator (tan δ at 60 °C = 0.115), a slight deterioration in wear resistance (ARI = 83%), but an improvement in the stress–strain behavior (M300 = 9.18 ± 0.20 MPa and Ts = 16.3 ± 0.6 MPa) and wet grip indicator (tan δ at 0 °C = 0.427) were observed. The results in this work show the potential of finding a balance between optimal performance and sustainability by using plasticizer blends. Full article

This study investigates the co-pyrolysis behavior of two lignocellulosic biomass blends, bamboo (B), and rice straw (R) with a plastic polyethylene (P). A total of 15 samples, including binary and ternary blends, were analyzed. Firstly, X-ray diffraction (XRD) analysis was performed to reveal high crystallinity in the B25R75 blend (I/I_c = 13.39). Whereas, the polyethylene samples showed persistent ZrP₂O₇ and lazurite phases (I/I_c up to 3.12) attributed to additives introduced during the manufacturing of the commercial plastic feedstock. In addition, scanning electron microscopy with energy-dispersive X-ray (SEM-EDX) spectroscopy was performed to characterize the surface morphology and elemental composition of the feedstock. Moreover, thermogravimetric analysis (TGA) was employed at temperatures up to 700 °C at three different heating rates (5, 10, and 20 °C/min) under pyrolysis conditions. Kinetic analysis used TGA data to calculate activation energy via Friedman’s isoconversional method, and the blended samples exhibited a decrease in activation energy compared to the individual components. Furthermore, the study evaluated transient interaction effects among the components by assessing the deviation between experimental and theoretical weight loss. This revealed the presence of significant synergistic behavior in certain binary and ternary blends. The results demonstrate that co-pyrolysis of bamboo and rice straw with polyethylene enhances thermal decomposition efficiency and provides a more favorable energy recovery route. Full article

Combining potassium-containing rocks with conventional KCl may improve the agronomic use of K rock and reduce leaching from high-soluble sources. The aim of this study was to evaluate K rocks (phonolite and alkaline) and the mixture with KCl at different K rates on the biomass production of maize and rice (residual effect), K uptake, and K leaching. The experiment was conducted in greenhouse columns with sandy soil. The experimental design included four K sources: PR (phonolite rock), PR + KCl in an 86:14 mass ratio, AR (alkaline rock), and KCl; three K rates (100, 200, and 400 mg kg⁻¹); and a control (no K), with five replicates. PR + KCl resulted in similar maize biomass (120 g column⁻¹) and K uptake (18 mg g⁻¹) compared to KCl, and it was higher than the PR, the AR, and the control, which produced 86, 48, and 32 g column⁻¹, respectively. The residual effect of PR, PR + KCl, and KCl generated similar rice biomass. K leaching reached 15% of K applied with KCl and was reduced by 50% with K rocks. Thus, the mixture of PR + KCl can improve K fertilization compared to KCl, enhancing maize and rice biomass while reducing K leaching. Full article

Based on the low-carbon transition needs of coal-fired boilers, this study conducted industrial trials of direct biomass co-firing on a 620 t/h high-temperature, high-pressure circulating fluidized bed (CFB) boiler, gradually increasing the co-firing ratio. It used compressed biomass pellets, achieving stable 20 wt% (weight percent) operation. By analyzing boiler parameters and post-shutdown samples, the comprehensive impact of biomass co-firing on the boiler system was assessed. The results indicate that biomass pellets were blended with coal at the last conveyor belt section before the furnace, successfully ensuring operational continuity during co-firing. Further, co-firing biomass up rates of to 20 wt% do not significantly impact the fuel combustion efficiency (gaseous and solid phases) or boiler thermal efficiency and also have positive effects in reducing the bottom ash and SO_x and NO_x emissions and lowering the risk of low-temperature corrosion. The biomass co-firing slightly increases the combustion share in the dense phase zone and raises the bed temperature. The strong ash adhesion characteristics of the biomass were observed, which were overcome by increasing the ash blowing frequency. Under 20 wt% co-firing, the annual CO₂ emissions reductions can reach 130,000 tons. This study provides technical references and practical experience for the engineering application of direct biomass co-firing in industrial-scale CFB boilers. Full article

Population growth has led to an increased volume of wastewater from industrial, domestic, and municipal sources, contaminating aquatic bodies in the state of Veracruz. This study aimed to assess the efficacy of a water treatment system incorporating a DAF stage, followed by the cultivation of a microalgal consortium to eliminate pollutants from the blended effluent. The cultivation of Nannochloropsis oculata in wastewater entailed the assessment of a single variable (operating pressure) within the DAF system, in conjunction with two supplementary variables (residence time and F:M ratio), resulting in removal efficiencies of 70% for CODt, 77.24% for CODs, 78.34% for nitrogen, and 77% for total organic carbon. The water sample was found to contain elevated levels of organic matter and pollutants, beyond the permitted limits set forth in NOM-001-SEMARNAT-2021. The obtained removal percentages indicate that the suggested physicochemical–biological process (DAF-microalgae) is a suitable method for treating mixed wastewater. This approach reduces atmospheric pollution by sequestering greenhouse gases such as carbon dioxide through the photosynthetic activity of N. oculata cells, so facilitating the production of oxygen and biomass while limiting their accumulation in the atmosphere. Full article

The projected depletion of fossil resources has initiated research on new and sustainable fuels which can be utilized in combination with conventional fuels. Lignocellulosic biomass, and more specifically lignin, can be depolymerized towards phenolic and aromatic bio-oils which can be converted downstream into bunker fuel blending components. Within this study, solvolysis under critical ethanol conditions and mild catalytic hydrotreatment were applied to heavy fractions of lignin pyrolysis bio-oils with the aim of recovering bio-oils with improved properties, such as a lower viscosity, that would allow their use as bunker fuel blending components. The mild reaction conditions, i.e., low temperature (250 °C), short reaction time (1 h) and low hydrogen pressure (30–50 bar), led to up 65 wt.% recovery of upgraded bio-oil, which exhibited a high carbon content (63–73 wt.%), similar to that of the parent bio-oil (68.9 wt.%), but a lower oxygen content and viscosity, which decreased from ~298,000 cP in the parent lignin pyrolysis oil to 526 cP in the hydrotreated oil, with a 10%Ni/Beta catalyst in methanol, and which was also sulfur-free. These properties permit the potential utilization of the oils as blending components in conventional bunker fuels. Full article

Methods for the improvement of regional lignocellulosic resources (wood and agriculture waste) were studied and analyzed using blends with optimized compositions and a selective pretreatment of the blends using microwaves to enhance their thermochemical conversion and energy production efficiency. A batch-size pilot device was used to provide the thermochemical conversion of biomass blends of different compositions, analyzing the synergy of the effects of thermal and chemical interaction between the components on the yield and thermochemical conversion of volatiles, responsible for producing heat energy at various stages of flame formation. To control the thermal decomposition of the biomass, improving the flame characteristics and the produced heat, a selective pretreatment of blends using microwaves (2.45 GHz) was achieved by varying the temperature of microwave pretreatment. Assessing correlations between changes in the main characteristics of pretreated blends (elemental composition and heating value) on the produced heat and composition of products suggests that selective MW pretreatment of biomass blends activates synergistic effects of thermal and chemical interaction, enhancing the yield and combustion of volatiles with a correlating increase in produced heat energy, thus promoting the wider use of renewable biomass resources for sustainable energy production by limiting the use of fossil fuels for heat-energy production and the formation of GHG emissions. Full article

It has been proven that the performance of fluid catalytic cracking (FCC), as the most important oil refining process for converting low-value heavy oils into high-value transportation fuels, light olefins, and feedstocks for petrochemicals, depends strongly on the quality of the feedstock. For this reason, characterization of feedstocks and their relationships to FCC performance are issues deserving special attention. This study systematically reviews various publications dealing with the influence of feedstock characteristics on FCC performance, with the aim of identifying the best characteristic descriptors allowing prediction of FCC feedstock cracking capability. These characteristics were obtained by mass spectrometry, SARA analysis, elemental analysis, and various empirical methods. This study also reviews published research dedicated to the catalytic cracking of biomass and waste oils, as well as blends of petroleum-derived feedstocks with sustainable oils, with the aim of searching for quantitative relationships allowing prediction of FCC performance during co-processing. Correlation analysis of the various FCC feed characteristics was carried out, and regression techniques were used to develop correlations predicting the conversion at maximum gasoline yield and that obtained under constant operating conditions. Artificial neural network (ANN) analysis and nonlinear regression techniques were applied to predict FCC conversion from feed characteristics at maximum gasoline yield, with the aim of distinguishing which technique provided the more accurate model. It was found that the correlation developed in this work based on the empirically determined aromatic carbon content according to the n-d-M method and the hydrogen content calculated via the Dhulesia correlation demonstrated highly accurate calculation of conversion at maximum gasoline yield (standard error of 1.3%) compared with that based on the gasoline precursor content determined by mass spectrometry (standard error of 1.5%). Using other data from 88 FCC feedstocks characterized by hydrogen content, saturates, aromatics, and polars contents to develop the ANN model and the nonlinear regression model, it was found that the ANN model demonstrated more accurate prediction of conversion at maximum gasoline yield, with a standard error of 1.4% versus 2.3% for the nonlinear regression model. During the co-processing of petroleum-derived feedstocks with sustainable oils, it was observed that FCC conversion and yields may obey the linear mixing rule or synergism, leading to higher yields of desirable products than those calculated according to the linear mixing rule. The exact reason for this observation has not yet been thoroughly investigated. Full article

This review article provides a comprehensive analysis of the recent advancements in combustion science and engineering, focusing on the application of machine learning and genetic algorithms from 2015 to 2024. The study examines the integration of computational methods, including computational fluid dynamics, neural networks, and genetic algorithms, with various fuel types such as biodiesel, biomass, coal, gasoline, hydrogen, and natural gas. A systematic search in the Scopus database identified relevant articles, which were categorized based on fuel types and computational methodologies. The analysis covers key areas such as combustion modelling and simulation, engine applications, alternative fuels, pollutant control, and industrial combustion systems. This review highlights the growing role of machine learning and genetic algorithms in enhancing combustion efficiency, reducing emissions, and optimizing energy production, providing insights into the current state of the art and future trends in this critical field. The study further examines the geographical distribution of research, noting significant contributions from Canada, China, France, Germany, India, Iran, Japan, Malaysia, Pakistan, Saudi Arabia, the United Kingdom, and the United States, alongside other international contributions. A total of 165 peer-reviewed articles were analyzed, covering a range of combustion scenarios and fuel types. The most frequently applied methods include artificial neural networks (ANNs), support vector machines (SVMs), and random forests (RFs) for predictive modeling, as well as genetic algorithms (GAs) for system optimization. ANN-based models achieved high accuracy in predicting NO_x emissions and flame speed, with some studies reporting mean absolute errors below 5%. GA methods demonstrated effectiveness in fuel blend optimization and geometry design, achieving emission reductions of up to 30% in experimental setups. This review also highlights persistent challenges such as data availability, model generalization, and reproducibility, and proposes future directions toward more interpretable and standardized applications of ML/GA in combustion science. Full article

With the rapid development of renewable energy, the co-combustion of Zhundong coal and biomass has attracted more and more attention. However, the high content of alkali metals in Zhundong coal and biomass leads to serious slagging and fouling in the co-combustion process. In this study, cotton straw was selected for co-combustion with Zhundong coal. The ash deposition model was established according to the melting ration calculated by Factsage, and the ash deposition characteristics during the co-combustion of Zhundong coal and cotton stalks in the actual boiler were explored by Fluent. The results showed that the K₂O content in ash increased from 0.31% to 9.31% with the increase in the blending ratio, while the contents of other components had no significant changes. In addition, with the increase in the blending ratio, the ash deposition rate increased from 0.00327 kg/(m²·s) to 0.00581 kg/(m²·s), an increase of 77.6%. The reduction in the tangential circle diameter obviously alleviated the ash deposition on the wall. When the tangential circle diameter was reduced to 400 mm, the ash deposition rate was 0.00207 kg/(m²·s), which was 37.6% lower than the original condition. Full article

This study presents an investigation on the potential of using one-year-old field-stored Medicago sativa (alfalfa) as a raw material for a multi-output biorefinery. The main objective was to fractionate the biomass into valuable components—crude protein, hemicellulose-derived polysaccharides, lignin, and cellulose—and to explore the latter’s suitability in papermaking. To this end, three pretreatment strategies (water, alkaline buffer, and NaOH solution) were applied, followed by soda pulping under varying severity conditions. Both solid and liquid fractions were collected and chemically characterized using FTIR, HPLC, and standardized chemical methods. Water-based pretreatment was most effective for protein extraction, achieving over 40% protein content in precipitated fractions. The harshest pulping conditions (20% NaOH, 160 °C, 60 min) yielded cellulose-rich pulp with high glucan content, while also facilitating lignin and hemicellulose recovery from black liquor. Furthermore, the pulps derived from alfalfa stems were tested for papermaking. When blended with old corrugated cardboard (OCC), the fibers enhanced tensile and burst strength by 35% and 70%, respectively, compared to OCC alone. These findings support the valorization of unexploited alfalfa deposits and suggest a feasible biorefinery approach for protein, fiber, and polymer recovery, aligned with circular economy principles. Full article

With increasing emphasis on sustainable horticulture, optimizing substrate composition is essential to reduce peat usage in container production. This study evaluated the effects of biochar and compost amendments on the growth and nutrient status of cherry laurel (Prunus laurocerasus) in two separate experiments conducted over five months. Experiment I assessed growth in pure peat and in peat–compost blends at volume ratios of 100:0, 70:30, 50:50, 30:70 and 0:100. Experiment II investigated the effect of adding biochar to a pure peat substrate at rates of 3 g·dm⁻³ and 5 g·dm⁻³. Key parameters were monitored, including the above and below-ground biomass, leaf and shoot counts, chlorophyll content, and the chemical composition of plant tissue and substrate. Compost addition increased the substrate pH from ~4.6 to ~6.4, while electrical conductivity increased with a higher compost content, reaching values approximately 2–3 times greater than in pure peat. Nutrient levels (Ca, K, Mg, P, NO₃⁻) also rose consistently with an increasing compost share. While a higher compost content generally reduced the biomass, leaf and shoot number, the greatest plant height and relatively favorable biomass were observed at 30% and 50% compost mixtures. Biochar addition slightly increased plant height, while the total biomass, root mass, and shoot number tended to decrease compared to pure peat, particularly at the lower biochar dose (3 g·dm⁻³). The substrate pH remained relatively stable, whereas electrical conductivity (EC) showed a slight upward trend with increasing biochar levels. Biochar also slightly increased the substrate nutrient content (Ca, K, Mg, P, NO₃⁻). Full article

In this study, a response surface methodology (RSM) using a central composite design (CCD) was implemented to investigate the influence of process variables on ethyl levulinate (EL) production from the ethanolysis of waste corn cob samples, using sulphuric acid as a catalyst. The effects of four independent variables, namely, the temperature (A), the corn cob content (B), corn cob/H₂SO₄ mass ratio (C) and the reaction time (D) on the yields of EL (Y₁), diethyl ether (DEE) (Y₂) and solid residue (Y₃) were explored. Using multiple regression analysis, the experimental results were fitted to quadratic polynomial models. The predicted yields based on the fitted models were well within the experimental uncertainties. Optimum conditions for maximising the EL yield were found to be 176 °C, 14.6 wt. %, 21:1 and 6.75 h for A to D, respectively. A moderate-to-high EL yield (29.2%) from corn cob was achieved in optimised conditions, a result comparable to those obtained from model C₆ carbohydrate compounds. Side products were also produced, including diethyl ether, furfural, levulinic acid, 5-hydroxymethyl furfural, ethyl acetate, ethyl formate and water. Total unknown losses of only 5.69% were reported after material balancing. The results suggest that lignocellulosic waste such as corn cob can be used as a potential feedstock for the production of ethyl levulinate by direct acid-catalysed ethanolysis, but that the treatment of side products will need to be considered. Full article

Sustainable polymers have attracted interest due to their ability to biodegrade under specific conditions in soil, compost, and the marine environment; however, they have comparatively lower mechanical properties, limiting their widespread use. This study explores the effect of incorporating waste soy biomass into sustainable polymers (including biodegradable and biobased) on the thermal and mechanical properties of the resultant blends. The dispersion of the waste soy biomass in the polymer matrix is also investigated in relation to particle size (17 µm vs. 1000 µm). Fine waste soy biomass did not significantly affect the melting temperature of the polymers (polyhydroxyalkanoates, polybutylene adipate terephthalate, polybutylene adipate terephthalate/poly(lactic) acid, and biobased linear low-density polyethylene) used in this study, but their enthalpy of fusion decreased after soy was melt-blended with the polymers. The tensile modulus of the polymers filled with fine waste soy biomass powder (17 µm) was enhanced when melt-blended as compared to unfilled polymers. Additionally, it was found that fine waste soy powder (17 µm) increased the tensile modulus of the polymer blends without significantly affecting processability, while coarse waste soy meal (1000 µm) generally reduced elongation at break due to poor dispersion and stress concentration; however, this effect was less pronounced in PHA blends, where improved compatibility was observed. Full article

Co-combustion of coal and biomass for power generation technology could not only realize the effective utilization of biomass energy, but also reduce the emission of greenhouse gases. In this study, a system of a settling furnace with high temperature is applied to study the ash deposition of the co-combustion of coal and salix. The effects of salix blending ratio, flue gas temperature, and wall temperature on ash deposition are studied. The micro-morphology, elemental content, and compound composition of the ash samples are characterized by scanning electron microscopy and energy-dispersive spectroscopy (SEM-EDS) and X-Ray Diffraction (XRD), respectively. The results show that with the biomass blending ratio increasing from 5% to 30%, the content of Ca in ash increases from 8.92% to 20.59%. In particular, when the salix blending ratio exceeds 20%, plenty of the low-melting-point compounds of Ca aggravate the melting adhesion of ash particles, causing serious ash accumulation. Therefore, the salix blending radio is recommended to be limited to no more than 20%. With the increase in flue gas temperature, ash particles melt and stick, forming ash accumulation. Under the condition of flue gas temperature ≥ 1200 °C, a serious ash particle melting flow occurs, and CaO covers the surface of the ash particles, making the ash particles adhere to each other, which makes them difficult to remove. Therefore, controlling the flue gas temperature below 1200 °C is necessary. When the temperature crosses the threshold range of 500–600 °C, the Ca and K contents increase by 35.6% and 41.9%, respectively, while the Si content decreases by 9.7%. The increase in K and Ca content leads to the thickening of the initial layer of the ash deposit, which facilitates the formation of the sintered layer of the deposited ash. Meanwhile, the reduction in Si content leads to the particles’ adhesion, which markedly increases the degree of ash slagging. Once the wall temperature exceeds 600 °C, severe ash slagging becomes a threat to the safe operation of the boiler. Therefore, the wall temperature should not exceed 600 °C. Full article