Search Results (413)

Biomass gasification, a key waste-to-energy technology, is a complex thermochemical process with many input variables influencing the yield and quality of syngas. In this study, data-driven machine learning models are developed to capture the nonlinear relationships between feedstock properties, operating conditions, and syngas composition, in order to optimize process performance. Random Forest (RF), CatBoost (Categorical Boosting), and an Artificial Neural Network (ANN) were trained to predict key syngas outputs (syngas composition and syngas yield) from process inputs. The best-performing model (ANN) was then integrated into a multi-objective optimization framework using the open-source Optimization & Machine Learning Toolkit (OMLT) in Pyomo. An optimization problem was formulated with two objectives—maximizing the hydrogen-to-carbon monoxide (H₂/CO) ratio and maximizing the syngas yield simultaneously, subject to operational constraints. The trade-off between these competing objectives was resolved by generating a Pareto frontier, which identifies optimal operating points for different priority weightings of syngas quality vs. quantity. To interpret the ML models and validate domain knowledge, SHapley Additive exPlanations (SHAP) were applied, revealing that parameters such as equivalence ratio, steam-to-biomass ratio, feedstock lower heating value, and fixed carbon content significantly influence syngas outputs. Our results highlight a clear trade-off between maximizing hydrogen content and total gas yield and pinpoint optimal conditions for balancing this trade-off. This integrated approach, combining advanced ML predictions, explainability, and rigorous multi-objective optimization, is novel for biomass gasification and provides actionable insights to improve syngas production efficiency, demonstrating the value of data-driven optimization in sustainable waste-to-energy conversion processes. Full article

Microwave pretreatment (MWP) has emerged as a promising strategy to enhance the pyrolysis of lignocellulosic biomass due to its rapid, volumetric, and selective heating. By disrupting the recalcitrant structure of cellulose, hemicellulose, and lignin, MWP improves biomass deconstruction, increases carbohydrate accessibility, and enhances yields of bio-oil, syngas, and biochar. When combined with complementary pretreatments—such as alkali, acid, hydrothermal, ultrasonic, or ionic-liquid methods—MWP further reduces activation energies, facilitating more efficient saccharification and thermal conversion. This review systematically evaluates scientific progress in this field through bibliometric analysis, mapping research trends, evolution, and collaborative networks. Key research questions are addressed regarding the technical advantages of MWP, the physicochemical transformations induced in biomass, and associated environmental benefits. Findings indicate that microwave irradiation promotes hemicellulose depolymerization, reduces cellulose crystallinity, and weakens lignin–carbohydrate linkages, which facilitates subsequent thermal decomposition and contributes to improved pyrolysis efficiency and product quality. From an environmental perspective, MWP contributes to energy savings, mitigates greenhouse gas emissions, and supports the integration of renewable electricity in biomass conversion. Full article

This study presents a thermodynamic equilibrium analysis of hydrogen-rich syngas production via biomass–methane co-pyrolysis, employing the Gibbs free energy minimization method. A critical temperature threshold at 700 °C is identified, below which methanation and carbon deposition are thermodynamically favored, and above which cracking and reforming reactions dominate, enabling high-purity syngas generation. Methane addition shifts the reaction pathway towards increased reduction, significantly enhancing carbon and H₂ yields while limiting CO and CO₂ emissions. At 1200 °C and a 1:1 methane-to-biomass ratio, cellulose produces 50.84 mol C/kg, 119.69 mol H₂/kg, and 30.65 mol CO/kg; lignin yields 78.16 mol C/kg, 117.69 mol H₂/kg, and 19.14 mol CO/kg. The H₂/CO ratio rises to 3.90 for cellulose and 6.15 for lignin, with energy contents reaching 43.16 MJ/kg and 52.91 MJ/kg, respectively. Notably, biomass enhances methane conversion from 25% to over 53% while sustaining a 67% H₂ selectivity. These findings demonstrate that syngas composition and energy content can be precisely controlled via methane co-feeding ratio and temperature, offering a promising approach for sustainable, tunable syngas production. Full article

The chemical looping steam reforming of methane (CLSR) employing Fe-containing oxygen carriers can produce syngas and hydrogen simultaneously. However, Fe-based oxygen carriers exhibit low CH₄ activation ability and cyclic stability. In this work, oxygen carriers with fixed Fe content and different Fe/Ni ratios were synthesized by the sol–gel method to investigate the effects of Ni-Fe-Al interactions on CLSR performance. Ni-Fe-Al interactions promote the growth of the spinel structure and regulate both the catalytic sites and the available lattice oxygen, resulting in the CH₄ conversion and CO selectivity being maintained at 96–98% and above 98% for the most promising oxygen carrier, with an Fe₂O₃ content of 20 wt% and Fe/Ni molar ratio of 10. The surface, phase, and particle size were kept the same over 90 cycles, leading to high stability. During the CLSR cycles, conversion from Fe³⁺ to Fe²⁺/Fe⁰ occurs, along with transformation between Ni²⁺ in NiAl₂O₄ and Ni⁰. Overall, the results demonstrate the feasibility of using spinel containing earth-abundant elements in CLSR and the importance of cooperation between oxygen release and CH₄ activation. Full article

Biomass gasification, a thermochemical conversion process that turns organic feedstocks like wood, agricultural residues, and solid waste into a combustible gas known as synthesis gas (syngas), is the focus of this study. In this study, Aspen Plus^® as a process simulation platform to optimize key operational parameters for the gasification of sugarcane bagasse was employed. The results are promising, with an equivalence ratio (ER) of 0.25 and a carbon conversion efficiency (XC) of 62.44% achieved, indicating the potential for the produced syngas to be compatible with injection into natural gas distribution networks. The lower heating value (LHV) of the syngas was determined to be 3.93 MJ·kg⁻¹, with an overall gasification efficiency of 49.85%. The simulation results showed strong agreement with experimental data, validating the modeling approach as a reliable predictive tool for biomass gasification systems and reducing unnecessary resource consumption. This validation instills trust and confidence in the reliability of our findings. Full article

Microplastics (MPs) are an increasingly significant environmental problem, and there is growing interest in their potential as an energy source. Current investigations in this area are scarce and heterogeneous, which hinders a comprehensive assessment of both technological feasibility and implementation prospects. The aim of this paper is to provide a comprehensive review of current research on energy recovery from MPs, with particular emphasis on technologies such as pyrolysis, gasification, electrochemical methods, and hybrid biomass-based technologies. The processes were analyzed in terms of energy balance, carbon conversion, composition and energy value of the products, energy losses and by-products, reaction time and process efficiency, as well as technological complexity and scalability. Within the reviewed methodologies, pyrolysis is the most scalable method, producing valuable oils and gases efficiently. Gasification can yield hydrogen-rich syngas but is still at pilot scale. Hybrid approaches improve efficiency but need feedstock optimization, while photodegradation and electrochemical methods remain at the research stage. Further progress requires method standardization, environmental and economic assessment, and integration with existing infrastructure. Full article

Dry reforming of methane (DRM) is an effective strategy to simultaneously convert CH₄ and CO₂ into valuable syngas. However, the widely employed Ni-based catalysts often suffer from rapid deactivation due to metal sintering and deposited carbon under harsh conditions. Herein, Ni/Ce_0.2Zr_0.8O₂ catalysts were synthesized using the evaporation-induced self-assembly (EISA) method with the addition of the triblock copolymer surfactant P123. The addition of an appropriate amount of P123 improved the Ni dispersion; reduced Ni particle size; and enhanced the activation efficiency of both CH₄ and CO₂, thus increasing the reaction rate. In addition, the addition of P123 also enhanced the surface basicity and increased the concentration of oxygen vacancies of the catalyst, which enhanced its carbon removal capability and reduced deposited carbon. The catalyst with 0.2% P123 maintained excellent catalytic activity and stability for 300 min at 700 °C, with CH₄ and CO₂ conversion of 75% and 78%, respectively. These findings provide valuable guidance for the rational design of efficient and stable Ni-based catalysts for DRM. Full article

Dry reforming of methane (DRM) offers a sustainable route to convert two major greenhouse gases—CH₄ and CO₂—into synthesis gas (syngas), enabling low-carbon hydrogen production and carbon utilization. This study applies fifteen machine learning (ML) regression models to simultaneously predict CH₄ conversion, CO₂ conversion, H₂ yield, and CO yield using a published dataset of 27 experiments with Ni/CaFe₂O₄-catalyzed DRM. The comparative evaluation covers linear, tree-based, ensemble, and kernel-based algorithms under a unified multi-output learning framework. Feature importance analysis highlights reaction temperature, CH₄/CO₂ feed ratio, and Ni metal loading as the most influential variables. Predictions from the top-performing models (CatBoost and Random Forest) identify optimal performance windows—feed ratio near 1.0 and temperature between 780–820 °C—consistent with thermodynamic and kinetic expectations. Although no new catalysts are introduced, the study demonstrates how ML can extract actionable parametric insights from small experimental datasets, guiding future DRM experimentation and process optimization for hydrogen-rich syngas production. Full article

Syngas fermentation in combination with chain elongation offers great promise for sustainable medium-chain fatty acid production. While immobilization has proven effective for stabilizing monocultures of C. kluyveri for chain elongation, its applicability to co-cultures involving C. carboxidivorans for simultaneous syngas fermentation remains unexplored. This study investigates the physiological compatibility of C. carboxidivorans with agar-based hydrogel immobilization and its co-cultivation potential with C. kluyveri in a synthetic dual-layer biofilm reactor. First, we conducted autotrophic batch fermentations using suspended and immobilized cells, proving metabolic activity similar for both. Applying different sulfur feeding rates, experiments showed best ethanol formation with C. carboxidivorans at increased sulfur feeding, enabling better conditions for chain elongation with C. kluyveri. In the synthetic dual-layer biofilm reactor, with the C. carboxidivorans biofilm in contact with the CO-containing gas phase above the C. kluyveri biofilm, the formation of 1-butyrate and 1-hexanoate was observed with product formation rates of 0.46 g L⁻¹ d⁻¹ 1-butyrate, and 0.91 g L⁻¹ d⁻¹ 1-hexanoate, respectively. The formation rate of 1-hexanoate in the dual-layer biofilm reactor was approximately 7.6 times higher than that reported with suspended cells in a stirred tank bioreactor. Spatial analysis revealed species-specific migration behavior and confirmed that C. carboxidivorans reduced local CO concentrations, improving the environment for C. kluyveri. Full article

The increasing demand for renewable energy has intensified research on lignocellulosic biomass pyrolysis as a versatile route for sustainable energy and resource recovery. This study provides a comparative overview of main pyrolysis regimes (slow, intermediate, fast, and flash), emphasizing operational parameters, typical product yields, and technological readiness levels (TRLs). Reactor configurations, including fixed-bed, fluidized-bed, rotary kiln, auger, and microwave-assisted systems, are analyzed in terms of design, advantages, limitations, and TRL status. Key process parameters, such as temperature, heating rate, vapor residence time, reaction atmosphere, and catalyst type, critically influence the yields and properties of biochar, bio-oil, and syngas. Increased temperatures and fast heating rates favor liquid and gas production, whereas lower temperatures and longer residence times enhance biochar yield and carbon content. CO₂ and H₂O atmospheres modify product distribution, with CO₂ increasing gas formation and biochar surface area and steam enhancing bio-oil yield at the expense of solid carbon. Catalytic pyrolysis improves selectivity toward target products, though trade-offs exist between char and oil yields depending on feedstock and catalyst choice. These insights underscore the interdependent effects of process parameters and reactor design, highlighting opportunities for optimizing pyrolysis pathways for energy recovery, material valorization, and sustainable bioeconomy applications. Full article

CH₄ is a powerful greenhouse gas that is thought to be one of the main causes of global warming. The catalytic conversion of methane in the presence of oxygen into hydrogen-rich syngas, known as the partial oxidation of methane (POM), is highly appealing for environmental and synthetic concerns. In search of a cheap catalytic system, the Ni-supported MgO-based (5Ni/MgO) catalyst and the promotional supplement of 1–3 wt.% Sr over 5Ni/MgO are investigated for the POM reaction. Catalysts are characterized by N₂ sorption isotherm analysis, X-ray diffraction spectroscopy, Raman spectroscopy, temperature-programmed desorption techniques, and thermogravimetry. Increasing the loading of strontium over Ni/MgO induced a strong interaction of NiO with the support, pronouncedly. In the presence of oxygen during the POM, the moderate-level interaction of NiO with the support grows markedly. Overall, at a 600 °C reaction temperature, the 5Ni2Sr/MgO catalyst shows 72% CH₄ conversion (~67% H₂ yield) at 14,400 mL/h/g_cat GHSV and ~86% CH₄ conversion (84% H₂ yield) at 3600 mL/h/g_cat GHSV. Achieving a higher activity towards the POM over cheap Ni, Sr, and MgO-based catalysts might draw the attention of environmentalists and industrialists as a low-cost and high-yield system. Full article

Dry reforming of methane is an advantageous technique to produce syngas by using greenhouse gases like CO₂ and CH₄. This study investigated the stability, catalytic effectiveness, and physicochemical characteristics of mono- and trimetallic catalysts based on Ni and supported on γ-Al₂O₃. Adding Co and Fe has been found to modify the structure and surface through the characterizations, including XRD, SEM, TEM, BET, H₂-TPR, and XPS methods. Compared to the monometallic Ni catalyst, the trimetallic catalysts exhibited improved alloy formation, reduced particle size, increased metal dispersion, and enhanced surface area and pore structures. The 10% Ni, 2.5% Co, and 2.5% Fe-Al₂O₃ catalyst exhibits higher CH₄ conversion, surpassing 75%, and also CO₂ conversion around 85% at 700 °C, compared to 15% Ni-Al₂O₃, which showed CH₄ conversion of about 65% and CO₂ conversion of 70%. It also showed comparatively good stability in 24 h testing performed at 700 °C. According to the findings of the research on trimetallic catalysts, their capacity to improve dry reforming of methane (DRM) performance may be attributed to increased stability, which is a crucial challenge in the production of sustainable syngas, as well as higher activity and lower deactivation. Full article

Solar gasification is a thermochemical process that relies on concentrated solar radiation to heat steam and biomass to produce syngas. This study uses Machine Learning to model solar gasification using steam as an oxidizer, incorporating both thermodynamic simulations and predictive algorithms, developed using Python (version 3.11.13) scripting, to understand the relationship between the input and output variables. Three models—Artificial Neural Networks, Support Vector Machines, and Random Forests—were trained using datasets including biomass composition, solar irradiance (considering a solar furnace), and steam-to-biomass ratios in a downdraft or fluidized bed gasifier. Among the models, Random Forests provided the highest accuracy (average R² = 0.942, Mean Absolute Error = 0.086, and Root Mean Square Error = 0.951) and were used for feature importance analysis. Results indicate that radiative heat transfer and steam-to-biomass ratio are the parameters that result in the largest increase in the syngas heating value and decrease in the tar contents. In terms of composition, the hydrogen contents have a direct relationship with the H₂ and tar formed, while the carbon content affects the carbon conversion efficiency. This work highlights the of feature importance analysis to improve the design and operation of solar-driven gasification systems. Full article

This work focuses on the fabrication, characterization, and performance of a structured iron catalyst to produce hydrocarbons by the Fischer–Tropsch synthesis (FTS). The structured catalyst enhances the heat and mass transfer and provides a larger surface area and lower pressure drop. Iron-based structured catalysts indicate more activity in lower H₂/CO ratios and improve carbon conversion as compared to other metals. These catalysts were manufactured using the sponge replication method (powder metallurgy). The performance of the structured iron catalyst was assessed in a fixed-bed reactor under industrially relevant conditions (250 °C and 20 bar). The feed gas was a synthetic syngas with a H₂/CO ratio of 1.2, simulating a bio-syngas derived from lignocellulosic biomass gasification. Notably, the best result was reached under these conditions, obtaining a CO conversion of 84.8% and a CH₄ selectivity of 10.4%, where the catalyst exhibited a superior catalytic activity and selectivity toward desired hydrocarbon products, including light olefins and long-chain paraffins. The resulting structured catalyst reached a one-pass CO conversion of 84.8% with a 10.4% selectivity to CH₄ compared to a traditionally produced catalyst, for which the conversion was 18% and the selectivity was 19%, respectively. The results indicate that the developed structured iron catalyst holds considerable potential for efficient and sustainable hydrocarbon production, mainly C10–C20 (diesel-range hydrocarbons), via Fischer–Tropsch synthesis. The catalyst’s excellent performance and improved stability and selectivity offer promising prospects for its application in commercial-scale hydrocarbon synthesis processes. Full article

Green hydrogen derived from renewable resources is increasingly recognized as a basis for future low-carbon energy systems. This study presents a comprehensive techno-environmental comparison of two thermochemical conversion pathways utilizing biomethane: steam methane reforming (SMR) and chemical looping reforming (CLR). Through integrated process simulations, compositional analyses, energy modeling, and cost evaluation, we examine the comparative advantages of each route in terms of hydrogen yield, carbon separation efficiency, process energy intensity, and economic performance. The results demonstrate that CLR achieves a significantly higher hydrogen concentration in the raw syngas stream (62.44%) than SMR (43.14%), with reduced levels of residual methane and carbon monoxide. The energy requirements for hydrogen production are lower in the CLR system, averaging 1.2 MJ/kg, compared to 3.2 MJ/kg for SMR. Furthermore, CLR offers a lower hydrogen production cost (USD 4.3/kg) compared to SMR (USD 6.4/kg), primarily due to improved thermal integration and the absence of solvent-based CO₂ capture. These insights highlight the potential of CLR as a next-generation reforming strategy for producing green hydrogen. To advance its technology readiness, it is proposed to develop a pilot-scale CLR facility to validate system performance under operational conditions and support the pathway to commercial implementation. Full article