Supercritical Water Gasification Of Biomass Research Articles

Investigating Salt Precipitation in Continuous Supercritical Water Gasification of Biomass

The formation of solid deposits in the process of supercritical water gasification (SCWG) is one of the main problems hindering the commercial application of the process. Seven experiments were conducted with the grass Reed Canary Grass with different preheating temperatures, but all ended early due to the formation of solid deposits (maximum operation of 3.8 h). The position of solid deposits in the lab plant changed with the variation in the temperature profile. Since the formation of solid deposits consisting of salts, coke, and corrosion products is a severe issue that needs to be resolved in order to enable long-time operation, inner temperature measurements were conducted to determine the temperature range that corresponds with the zone of solid formation. The temperature range was found to be 400 to 440 °C. Wherever this temperature was first reached solid deposits occurred in the system that led to blockage of the flow. Additional to the influence of the temperature, the influence of the flow direction (up-flow or down-flow) on the operation of the continuous SCWG plant was examined. If salts are not separated from the system sufficiently, up-flow reactors should be avoided because they amplify the accumulation of solid deposits leading to a shortened operation time. The heating concept coupled with the salt separation needs to be redesigned in order to separate the salts before entering the gasification reactors. Outside of the determined temperature zone no deposition was visible. Thus, even though the gasification efficiency was low it could be shown that the operation was limited to the deposits forming in the heating section and not by incomplete gasification in the reactor where T > 600 °C.

Developing a hybridized thermodynamic and data-driven model for catalytic supercritical water gasification of biomass for hydrogen production

Supercritical water gasification (SCWG) of biomass offers a promising pathway for sustainable energy production. This study presents a novel approach that combines an artificial intelligence (AI) technique with the Gibbs minimization (GM) method to enhance the GM approach by involving the catalyst effect on the gasified yield. The proposed strategy incorporates a modified Gibbs energy calculation, incorporating a delta term that quantifies the influence of the catalyst’s properties on the Gibbs free energy. The delta term is determined using experimental data, including characteristics of biomass and the employed catalysts. An artificial neural network (ANN) model is developed to predict the delta value and is integrated with the GM method to improve the estimation of gasified product yields in the presence of a catalyst. The ANN model establishes correlations between the catalyst specifications such as pore volume, specific surface area, and pore diameter, and delta value. The trained model can predict the delta term, allowing the catalyst’s role to be considered within the GM technique. This integration addresses a limitation of the conventional thermodynamic model, which typically ignores the catalyst’s influence. The developed ANN model exhibits high accuracy, with an R2 value of 0.92 and a mean squared error (MSE) of 0.042. The hybridized GM approach substantially improves the hydrogen yield prediction compared to the basic model, enhancing (reducing) the MSE and mean absolute error by 98% and 93%, respectively. Furthermore, sensitivity analysis reveals that increasing temperature and reducing pressure contribute to improved hydrogen production. Additionally, lower biomass concentrations are shown to be beneficial for enhancing the hydrogen yield.

System development and thermodynamic performance analysis of a system integrating supercritical water gasification of black liquor with direct-reduced iron process

Hydrogen metallurgy is an effective way to decarbonize the steel industry. In this study, a new system integrating biomass supercritical water gasification (SCWG) with hydrogen generation-shaft furnace-electric arc furnace (HSE) was proposed. The thermodynamic performance of SCWG-HSE system were analyzed and optimized. The results show that the gasification and energy efficiency of SCWG system increase with an increase in the gasification temperature. The carbon emission of the SCWG-HSE system are effectively reduced, and the product yield and energy efficiency of the system are improved by increasing gasification temperature and recovering furnace top gas. The energy and exergy efficiency of the SCWG-HSE system are 46.66% and 40.17%, respectively. The exergy destruction of SCWG gasifier and electric arc furnace are the major exergy damage sources of the SCWG-HSE system. The exergy efficiency of the ironmaking system reaches 51.60%, and the energy consumption and carbon emission per unit product are 18.49 GJ/t and 902.40 kg/t, respectively. Compared with the traditional Coking-Blast furnace ironmaking process, the energy consumption and carbon emission of this system are reduced by 7.32% and 40.84% respectively. This work is expected to open a new way for the application of biomass in the low-carbon steel industry.

High value-added syngas production by supercritical water gasification of biomass: Optimal reactor design

Supercritical water gasification (SCWG) emerges as a highly encouraging technique for the efficient generation of syngas from biomass feedstock. The performance of the SCWG reactor plays a pivotal role in determining the overall success of the process. This study employs a mathematical modeling and optimization method to design an optimal tubular-type reactor for the SCWG of biomass. First, the reactor is divided into cells, and mathematical models are established to describe the reactions within each cell, as well as the mass balances between cells. Afterwards, the optimal reactor design problem is formulated as a non-linear optimization problem, which involves integration of all the individual models along the reactor length. The objective is to maximize the high heating value (HHV) of gaseous products and simultaneously satisfying multiple constraints. Once the problem is solved, the optimal decision variables (i.e., reactor axial fluid temperature profiles, diameter and length) are obtained. Here, two reactor design scenarios are investigated to showcase the adaptability of this optimization method. The obtained outcomes indicate that non-isothermal reactors with a zigzag-shaped temperature profiles are more advantageous than traditional isothermal ones for high value-added syngas production. Specifically, optimal non-isothermal reactors can achieve a remarkable increase of 50.08% (i.e., 26.94 vs 17.95 MJ/kg glycerol) in the HHV of gaseous products compared to isothermal reactors. These findings provide valuable insights on designing efficient SCWG reactors for industrial high value-added syngas production.

Molecular Dynamics Investigation of the Gasification and Hydrogen Production Mechanism of Phenol in Supercritical Water

Supercritical water gasification is an efficient and clean method for converting biomass into hydrogen-rich gas. Phenol plays a crucial role as an intermediate product in biomass supercritical water gasification, and studying its reaction pathway in supercritical water is essential for understanding the chemical reaction mechanism and optimizing biomass energy conversion processes. In this paper, we investigated the conversion mechanism of phenol gasification and hydrogen production in supercritical water using a combined approach of reactive force field (ReaxFF) and density functional theory (DFT). We determined the decomposition pathways and product distribution of phenol in supercritical water. The calculation results demonstrate that in the supercritical water system, the efficiency of phenol conversion for hydrogen production is approximately 27 times higher than that of hydrogen production through gasification in the pyrolysis state. Moreover, both the carbon conversion rate and hydrogenation rate in the supercritical water system are significantly higher compared to those in the pyrolysis system. Furthermore, we found that the energy in the supercritical system is approximately half that of the pyrolysis system, favoring the ring-opening reactions of phenol and promoting hydrogen production. In contrast, the pyrolysis system produces a greater quantity of aromatic compounds, leading to tar formation and having significant implications for both the reaction process and reactor design. Additionally, we conducted comparative experiments between the supercritical water gasification process and the pyrolysis process to explore the advantages of supercritical water gasification.

AI Prediction of H2 Production in a Biomass Supercritical Water Gasification Fluidized Bed under Pulsating Inlets

AI Prediction of H₂ Production in a Biomass Supercritical Water Gasification Fluidized Bed under Pulsating Inlets

High Dimensional Model Representation Approach for Prediction and Optimization of the Supercritical Water Gasification System Coupled with Photothermal Energy Storage

Supercritical water gasification (SCWG) coupled with solar energy systems is a new biomass gasification technology developed in recent decades. However, conventional solar-powered biomass gasification technology has intermittent operation issues and involves multi-variable characteristics, strong coupling, and nonlinearity. To solve the above problems, firstly, a solar-driven biomass supercritical water gasification technology combined with a molten salt energy storage system is proposed in this paper. This system effectively overcomes the intermittent problem of solar energy and provides a new method for the carbon-neutral process of hydrogen production. Secondly, the high dimensional model representation (HDMR) approach, as a surrogate model, was used to predict the production and lower heating value of syngas developed in Aspen Plus, which were validated using experimental data obtained from the literature. The ultimate analysis of biomass, temperature, pressure, and biomass-to-water ratio (BWR) were selected as input variables for the model. The non-dominated sorted genetic algorithm II (NSGA II) was considered to maximize the gasification yield of H2 and the LHV of syngas in the SCWG process for five different types of biomass. Firstly, the results showed that HDMR models demonstrated high performance in predicting the mole fraction of H2, CH4, CO, CO2, gasification yield of H2, and lower heating value (LHV) with R2 of 0.995, 0.996, 0.997, 0.996, 0.999, and 0.995, respectively. Secondly, temperature and BWR were found to have significant effects on SCWG compared to pressure. Finally, the multi-objective optimization results for five different types of biomass are discussed in this paper. Therefore, these operating parameters can provide an optimal solution for increasing the economics and characteristics of syngas, thus keeping the process energy efficient.

Catalytic Biomass Gasification in Supercritical Water and Product Gas Upgrading

AbstractThe gasification of biomass with supercritical water, also known as SCWG, is a sustainable method of hydrogen production. The process produces a mixture of hydrogen, carbon oxides, and hydrocarbons. Upgrading this mixture through steam or dry reforming of hydrocarbons to create synthesis gas and then extra hydrogen is a viable way to increase hydrogen production from biomass. This literature review discusses combining these two processes and recent experimental work on catalytic SCWG of biomass and its model compounds and steam/dry reforming of produced hydrocarbons. It focuses on catalysts used in these processes and their key criteria, such as activity, selectivity towards hydrogen and methane, and ability to inhibit carbon formation and deposition. A new criterion is proposed to evaluate catalyst performance in biomass SCWG and the need for further upgrading via reforming, based on the ratio of hydrogen bound in hydrocarbons to total hydrogen produced during SCWG. The review concludes that most catalysts used in biomass SCWG trap a large proportion of hydrogen in hydrocarbons, necessitating further processing of the product stream.

A Review of the Design and Performance of Catalysts for Hydrothermal Gasification of Biomass to Produce Hydrogen-Rich Gas Fuel.

Supercritical water gasification has emerged as a promising technology to sustainably convert waste residues into clean gaseous fuels rich in combustible gases such as hydrogen and methane. The composition and yield of gases from hydrothermal gasification depend on process conditions such as temperature, pressure, reaction time, feedstock concentration, and reactor geometry. However, catalysts also play a vital role in enhancing the gasification reactions and selectively altering the composition of gas products. Catalysts can also enhance hydrothermal reforming and cracking of biomass to achieve desired gas yields at moderate temperatures, thereby reducing the energy input of the hydrothermal gasification process. However, due to the complex hydrodynamics of supercritical water, the literature is limited regarding the synthesis, application, and performance of catalysts used in hydrothermal gasification. Hence, this review provides a detailed discussion of different heterogeneous catalysts (e.g., metal oxides and transition metals), homogeneous catalysts (e.g., hydroxides and carbonates), and novel carbonaceous catalysts deployed in hydrothermal gasification. The article also summarizes the advantages, disadvantages, and performance of these catalysts in accelerating specific reactions during hydrothermal gasification of biomass, such as water-gas shift, methanation, hydrogenation, reforming, hydrolysis, cracking, bond cleavage, and depolymerization. Different reaction mechanisms involving a variety of catalysts during the hydrothermal gasification of biomass are outlined. The article also highlights recent advancements with recommendations for catalytic supercritical water gasification of biomass and its model compounds, and it evaluates process viability and feasibility for commercialization.

Self-heating optimization of integrated system of supercritical water gasification of biomass for power generation using artificial neural network combined with process simulation

Self-heating optimization of integrated system of supercritical water gasification of biomass for power generation using artificial neural network combined with process simulation

Catalytic gasification of indole in supercritical water with non-noble bimetallic catalysts

Indole is commonly reported as a N-containing heterocyclic compounds in biomass supercritical water gasification (SCWG), and is difficult to be degraded to small molecule substances. In this work, Ni/AC, Ni–Cu/AC, Ni–Co/AC, Ni–Ce/AC were prepared and tested for catalytic SCWG of indole. The results showed that Ni–Cu/AC had the highest activity for converting indole and producing gases, leading to the highest hydrogen gasification efficiency (135.1%) and carbon gasification efficiency (33.1%). During the catalytic SCWG of indole, the addition of auxiliary metal Cu in multi-component catalyst showed synergistic effects by changing reaction pathways and reaction rates. It significantly promoted water-gas shift and steam reforming reactions, so forming the highest H2 yield of 2.62 mol mol−1. Furthermore, large specific surface, Ni reduction and high catalyst stability point to potential advantages of the Ni–Cu/AC catalyst for catalytic SCWG of recalcitrant N-containing compounds.

Partial oxidation gasification kinetics of indole in supercritical water for hydrogen production

Indole is one of refractory intermediate products in hydrothermal conversion of biomass, and its decomposition significantly restricts the improvement of gasification efficiency and hydrogen production in biomass supercritical water gasification (SCWG). In order to improve gasification efficiency of indole and moderate reaction conditions for hydrogen production in biomass SCWG, indole (0.25 mol/L) was gasified in supercritical water at 540–600 °C, 25 MPa, 0–0.8 of oxidation coefficients (OC) in min-batch reactors. Corresponding pathways and kinetics of partial oxidation of indole in supercritical water for hydrogen production were explored. The results showed that the addition of oxidant (hydrogen peroxide) promoted steam reform and decomposition, especially ring-opening reactions, so increasing the gasification efficiency of indole and the yields of H2 and CO2 in gaseous products. The maximum hydrogen gasification efficiency could reach up to 60.3% at OC = 0.6, which was about twice that of non-oxidant. Moreover, 29 groups of reaction rate constants, activation energies and Arrhenius constants were obtained in the established kinetic model.

Development of a Partitioning Kinetic Model of Biomass Gasification in Supercritical Water with a Fluidized Bed Reactor

Biomass supercritical water gasification technology is considered an effective way to realize the utilization of biomass, and further development of this technology depends on an accurate kinetic model. In this work, the reactor was distributed into a nozzle affected zone, a dense phase zone, and a freeboard zone according to the characteristic of the physical and chemical field, and a reaction kinetic model suitable for each zone was developed, which could be used for dynamic and scale-up studying of the reactor. First, three groups of gasification experiments (feedstock and biochar with low and high concentrations) were conducted to obtain the gas yield for calculation of the kinetic parameter, and obtain the evolution of the specific area of biochar for the calculation of the porous structure constant ψ. Then, detailed reaction pathways for biomass and biochar were proposed and a random pore kinetic model taking specific surface area into account was developed based on the first order of each reactant.

Supercritical water gasification of lignocellulosic biomass: Development of a general kinetic model for prediction of gas yield

• A general kinetic model of biomass supercritical water gasification was developed. • The kinetic model was validated successfully based on results from real biomass. • Temperature played the most important role in producing gaseous species. • The effect of residence time on gas formation was found to be minor. • SCWG of lignin produced the highest yield of hydrogen. Supercritical water gasification (SCWG) utilizes water as the reaction medium to convert biomass into a mixture of gases (i.e., H 2 , CO 2 , CO, CH 4 , and other short-chain hydrocarbons) at typical operating temperature ≥ 400 °C and pressure ≥ 23 MPa. Understanding kinetics of SCWG processes is critically important for future development and scale-up application of the SCWG technology. Thus, this study aimed to develop a general kinetic model to predict the yields of gases from SCWG of various lignocellulosic feedstocks with varying contents of cellulose, hemicellulose and lignin. The model was established based on the experimental results from K 2 CO 3 -catalyzed SCWG of various biomass model compounds including cellulose, xylan and lignin at 450–550 °C for 10–50 min, followed by validation of the model using the experimental data obtained from SCWG of real biomass (i.e., corn stalk and pinewood) under same reaction conditions. The validation results showed that the general kinetic model developed could accurately predict the yields of gases from real biomass SCWG and the quantitative influences of temperature and residence time on the gas yield in biomass SCWG. Additionally, the kinetic model has been validated other SCWG data in the literature obtained with various facilities and different lignocellulosic biomass feedstocks. The development of the general kinetic model provides an applicable way to assess the potential of SCWG of various lignocellulosic biomass feedstocks for producing combustible gases at various conditions.

Interpretable machine learning for predicting and evaluating hydrogen production via supercritical water gasification of biomass

Supercritical water gasification (SCWG) of biomass for hydrogen production is a clean and promising technology. However, due to many factors involved in SCWG process, including biomass properties and process parameters, it is time consuming and capital intensive to evaluate the multi-dimensional relationship between them, as well as the hydrogen production capability using the experimental method. Therefore, it is necessary to develop an accurate model to predict and evaluate SCWG process in an economic way. This study established four machine learning models to predict hydrogen production via SCWG of biomass, interpreted the inner workings of the optimal model and evaluated the performance of SCWG. The results suggested that random forest (RF) model outperformed gaussian process regression, artificial neural network and support vector machine models for predicting H2 yield (R2 = 0.9782). Feature importance and partial dependence analysis combined with the RF model were used to visually present the relative importance and average partial relationship selected biomass properties and process parameters for H2 yield. The contour plots based on the RF model indicated that maximum hydrogen reaction efficiency (45.6%) and exergy efficiency (43.3%) were achieved when biomass with a high O content and low H/C ratio were used as feedstock. This study demonstrated that the machine learning model is a practical tool for predicting hydrogen production. Meanwhile, the interpretation of the model can clarify the influence of the variables involved in SCWG on hydrogen production, which is helpful for selecting the appropriate feedstock and optimize the process parameters in the experiment or practical engineering.

Implications on Feedstock Processing and Safety Issues for Semi-Batch Operations in Supercritical Water Gasification of Biomass

Biomass with a large amount of moisture is well-suited to be processed by supercritical water gasification, SCWG. The precipitation of inorganics, together with char formation and re-polymerization, can cause reactor plugging and stop the process operations. When plugging occurs, sudden injections of relatively large mass quantities take place, influencing the mass flow dynamics significantly in the process. Reactor plugging is a phenomenon very well observed during SCWG of industrial feedstock, which hinders scale-up initiatives, and it is seldom studied with precision in the literature. The present study provides an accurate evaluation of continuous tubular reactor dynamics in the event of sudden injections of water. An interpretation of the results regarding water properties at supercritical conditions contributes to comprehending mass and heat transfer when plugging occurs. Experiments are then compared to SCWG of a biomass sample aiming to give key insights into heat transfer and fluid dynamics mechanisms that could help develop operational and control strategies to increase the reliability of SCWG. In addition, a simplified model is presented to assess the effect of material integrity on burst-event likelihood, which states that SCWG is safe to operate, at 250 bar and 610 °C, in tubular reactors made of 0.22 wall thickness-to-diameter ratio Inconel-625 with superficial microfractures smaller than 30 µm. We also suggest improvement opportunities for the safety of SCWG in continuous operation mode.

Gasification of Biomass in Supercritical Water, Challenges for the Process Design—Lessons Learned from the Operation Experience of the First Dedicated Pilot Plant

Gasification of organic matter under the conditions of supercritical water (T > 374 °C, p > 221 bar) is an allothermal, continuous flow process suitable to convert materials with high moisture content (<20 wt.% dry matter) into a combustible gas. The gasification of organic matter with water as a solvent offers several benefits, particularly the omission of an energy-intensive drying process. The reactions are fast, and mean residence times inside the reactor are consequently low (less than 5 min). However, there are still various challenges to be met. The combination of high temperature and pressure and the low concentration of organic matter require a robust process design. Additionally, the low value of the feed and the product predestinate the process for decentralized applications, which is a challenge for the economics of an application. The present contribution summarizes the experience gained during more than 10 years of operation of the first dedicated pilot plant for supercritical water gasification of biomass. The emphasis lies on highlighting the challenges in process design. In addition to some fundamental results gained from comparable laboratory plants, selected experimental results of the pilot plant “VERENA” (acronym for the German expression “experimental facility for the energetic exploitation of agricultural matter”) are presented.

Molecular dynamic investigation on nitrogen migration during hydrogen production by indole gasification in supercritical water

Hydrogen production by supercritical water gasification of biomass has broad application prospects. The migration and regulation mechanism of nitrogen in supercritical water is one of the key issues in biomass utilization. As a nitrogen-containing model compound of biomass, indole was used to study the mechanism of nitrogen migration during supercritical water gasification from a molecular perspective by using reactive empirical force fields (Reaxff) combined with Density functional theory (DFT) method. The pyrrole ring cracking was the first stage and then most of the nitrogen atoms left the carbon skeleton to form ammonia precursor radicals after being attacked by H or OH free radicals in supercritical water. The overall activation energy of each pyrrole ring opening way was calculated. The dominant way for pyrrole ring opening was analyzed and the competitive relationship among the different ring-opening ways was specified by comparing the activation energies of transition states and relative energies of intermediates. Compared with pyrolysis conditions, supercritical water molecules greatly promoted the separation of nitrogen atoms from the carbon skeleton to form NH3 and inhibited the formation of HCN. The higher temperature could facilitate the indole conversion and the hydrogen generation, but it also increased the possibility of char formation, causing part of the nitrogen to re-enter the organic structure. This study revealed the mechanism from the view of microscopic atoms, and provided theoretical support for the nitrogen regulation in supercritical water gasification of biomass.

Particle-resolved numerical study of the forced convection heat transfer characteristics of an endothermic-biomass particle placed in supercritical water crossflow

Abstract Biomass gasification in supercritical water (SCW) for high energy density gas fuel is a promising method for the efficient usage of biomass resource. Researches have indicated that the gasification efficiency is greatly depended on the heat transfer rate during the practical process of cold biomass particle injected into SCW. So the study of the forced convection heat transfer characteristics of an endothermic-biomass particle placed in SCW crossflow is of great significance. Moreover, the study of the particle surface local heat transfer rate distribution is also necessary for the complete gasification of biomass particles in SCW. Therefore, this work performs particle-resolved direct numerical simulation study on SCW flow past an endothermic sphere. Results demonstrate that the heat transfer gets great enhancement when the heat transfer temperature range comprises the large specific heat capacity zone. For the particle surface local heat transfer distribution, the enhancement at the front of particle is much stronger than that at the rear. Furthermore, the heat transfer characteristics under different pressures are also studied. In the end, a new forced convection heat transfer correlation applicable for SCW flow past an endothermic sphere is obtained.

Simulation Study on Hydrogen-Heating-Power Poly-Generation System based on Solar Driven Supercritical Water Biomass Gasification with Compressed Gas Products as an Energy Storage System

Supercritical water gasification driven by solar energy is a promising way for clean utilization of biomass with high moisture content, but direct discharge of liquid residual causes energy waste and decreases energy efficiency. To reduce energy waste, a poly-generation system for hydrogen-rich gas production coupling heat supply and power generation based on supercritical water gasification of biomass driven by concentrated solar energy was established in this paper, which also provided a novel energy storage method to overcome the shortcomings of solar discontinuity. Thermodynamic model of the system was proposed and life cycle assessment (LCA) of the system was conducted. Influence of different parameters (temperature of 600°C to 800°C, outlet temperature of heat exchanger of 42°C to 56°C, biomass slurry concentration of 5% to 6.5%) on the gasification performance, energy and exergy efficiency, energy distribution and global warming potential (GWP) was discussed. The results indicated that hydrogen yield increased as gasification temperature increased since free radical reaction was enhanced which gas production reaction was classified into. Molar fraction of hydrogen increased as gasification temperature increased and reached 65.6% at 750°C. Energy and exergy efficiency of the system reached 74.84% and 34.87% at 700°C and 600°C respectively and that of gas production was 18.15% at 650°C, which was the highest. Increasing reaction temperature and decreasing biomass slurry concentration were effective ways to decrease GWP. Optimal operating parameter was reaction temperature of 650°C, outlet temperature of heat exchanger of 50°C and biomass concentration of 5%.