Biomass Particles Research Articles

Experiment investigation and multiscale modeling of biomass oxidative fast pyrolysis in a fluidized bed reactor

Experiments were conducted in a fluidized bed reactor to study the oxidative fast pyrolysis of biomass. The pressure drops along the bed height were measured, and the yield and composition of gas, liquid, and solid products were analyzed at various O2 concentrations. It was found that with the increase in oxygen concentration, the yield of biogas increased, especially CO2 and CO, while yields of bio-oil and biochar decreased. Under oxidative conditions, the fraction of tar in bio-oil was significantly reduced. A multiscale model was developed in the open-source code MFiX by integrating the reactor model based on the coarse-grained DEM-CFD, the intraparticle model, and the biomass oxidative fast pyrolysis kinetics. The model was verified by comparison with experimental data. As the oxygen concentration increases, the mixing and separation of biomass particles decreases, the residence time increases, the axial distribution moves upward, and the Lacey mixing index decreases. This study established experimental and theoretical foundations for designing and scaling up oxidative fast pyrolysis of biomass in fluidized beds.

Numerical study on inter-particle effects for multiple reacting biomass and coal particles based on Micro-CT morphology

Numerical study on inter-particle effects for multiple reacting biomass and coal particles based on Micro-CT morphology

2-D modeling of torrefaction of a large biomass particle: effect of L/D ratio, internal convection and shrinkage

ABSTRACT Torrefaction of a large biomass particle was investigated using a transient 2-D model, including primary and secondary reactions kinetics and heat transfer, internal convection, and shrinkage. The model predictions matched with the experimental results within +2%. Spatial and temporal distributions of temperature, residual mass fraction, velocity, and pressure inside the particle and the effect of reactor temperature, residence time, particle size, and shrinkage on the torrefaction behaviour were investigated. Evolution of moisture, volatiles and gases due to drying and torrefaction increase the pressure inside the particle, setting up a velocity field and internal convection. Average velocity and pressure reached a peak during the initial drying period due to moisture evolution, and a subsequent second peak due to the formation of volatiles and gases by torrefaction at a reactor temperature > 493 K. Internal convection influenced torrefaction significantly but the particle shrinkage did not impact it appreciably. The degree of overshoot of the particle center temperature above the reactor temperature increased with the reactor temperature and the particle diameter. Simulations suggest that a reactor temperature of 550 K and residence of about 30 min would be suitable for torrefaction of a particle with L = D = 25.4 mm.

Numerical study of a chemical looping combustion system: Effects of fuel type and particle size distributions on the operating performance

Chemical looping combustion (CLC) using biomass offers a promising pathway for achieving negative carbon emissions. However, the different properties of coal and biomass affect reaction performance, which has not been fully explored in the CLC system. Additionally, the effects of particle size distributions (PSDs) of solid fuels and oxygen carriers (OCs) are inadequately addressed. In this study, a 3D reactive model using the computational particle fluid dynamics (CPFD) method is developed to investigate the effects of PSDs of both solid fuels and oxygen carriers on operating performance with coal and biomass as fuels. Results indicate that the average residence time in FR of coal and biomass particles is 0.86 s and 0.68 s, respectively, but biomass outperforms coal in reaction efficiency. For coal-fueled CLC, the average residence time is 0.46 s for coal particles with diameters of 100–200 μm, whereas it reaches 0.86 s for coal diameters of 300–700 μm. However, the reaction performance is better with smaller coal sizes due to char gasification being the rate-limiting step. In comparison, for biomass-fueled CLC, the reaction efficiency remains consistent across various particle sizes under the specified conditions due to the rapid release of volatile components and the low content of char. Additionally, it is found that the OC conversion ratio is mainly determined by their residence time in the zones with relatively higher concentrations of the combustible gas in FR. Employing OCs with overly wide PSDs such as 300–800 μm can compromise the material seal above the AR, increase the risk of gas leakage and decrease the separation efficiency of the inertial separator.

A Preliminary Experimental Study on Biodegradation of 3D-Printed Samples from Biomass–Fungi Composite Materials

Products made from petroleum-derived plastic materials are linked to many environmental problems, such as greenhouse gas emissions and plastic pollution. It is desirable to manufacture products from environmentally friendly materials instead of petroleum-based plastic materials. Products made from biomass–fungi composite materials are biodegradable and can be utilized for packaging, construction, and furniture. In biomass–fungi composite materials, biomass particles (derived from agricultural wastes) serve as the substrate, and the fungal hyphae network binds the biomass particles together. There are many reported studies on the 3D printing of biomass–fungi composite materials. However, there are no reported studies on the biodegradation of 3D-printed samples from biomass–fungi composite materials. In this study, two types of biomass materials were used to prepare printable mixture hemp hurd and beechwood sawdust. The fungi strain used was Trametes versicolor. Extrusion based 3D printing was used to print samples. 3D-printed samples were left for five days to allow fungi to grow. The samples were then dried in an oven for 4 h at 120 °C to kill all the fungi in the samples. The samples were buried in the soil using a mesh bag and kept in an environmental chamber at 25 °C with a relative humidity of 48%. The weight of these samples was measured every week over a period of three months. During the testing period, the hemp hurd test samples lost about 33% of their original weight, whereas the beechwood sawdust samples lost about 30% of their original weight. The SEM (scanning electron microscope) micrographs showed the presence of zygospores in the test samples, providing evidence of biodegradation of the test samples in the soils. Additionally, the difference in peak intensity between the control samples and test samples (for both hemp hurd and beechwood sawdust) showed additional evidence of biodegradation of the test samples in the soils.

Characterization of 3D printed samples from biomass-fungi composite materials

Biomass-fungi composite materials are derived from sustainable sources and can biodegrade at the end of their service. In these composite materials, the biomass particles (made from agricultural waste such as hemp hurd) act as the substrate, and a network of fungal hyphae grow through and bind the biomass particles together. These composite materials can be used to manufacture products traditionally made from petroleum-based plastics. Potential applications of these products are in the packaging, furniture, and construction industries. Typically, molding-based methods are used to manufacture products using these composite materials. Recently, the authors reported a novel 3D printing-based method using these composite materials. This paper reports a follow-up investigation into the characterization of 3D printed samples from biomass-fungi composite materials. Tensile and compressive testing samples were shaped using molds from a portion of each printed sample. Mechanical properties of these tensile and compressive testing samples and chemical properties of the printed samples were measured. Tensile and compressive testing measurement results showed that, at the significance level of 0.05, effects of 3D printing parameters studied (printing speed and extrusion pressure) were not statistically significant on Young’s modulus and ultimate tensile strength of the tensile testing samples, as well as on compressive strength and compressive modulus of the compressive testing samples. Results obtained from the Fourier transform infrared spectroscopy analysis show that chemical composition of printed samples was consistent with the data in the literature.

Assessing the effect of size and shape factors on the devolatilization of biomass particles by coupling a rapid-solving thermal-thick model

In CFD modeling, while the isothermal assumption has conventionally been coupled for updating particle temperature, its applicability diminishes when dealing with thermally thick particles. A thermal-thick discrete phase model (DPM) is developed to simulate pyrolysis of biomass particle group at high heating rates and temperatures, with particles tracked in a Lagrangian scheme. The effects of particle size and shape on the volatile release and heating history are investigated. For spherical particles with a diameter of 9.6mm, the temperature difference between the surface and center (∆T) does not disappear even up to 50seconds. In the particle size range spanning from 200 μm to 9.6mm, the duration required for a complete volatile release extends from 1.5 to 40s. For cylindrical particles, in contrast to the particles with an aspect ratio (AR, ratio of particle length to diameter) of 1, the devolatilization time of particles with an AR of 15 can be shortened by more than 50%. In addition, both the particle shape and size can significantly influence the volatile distribution within the reactor. This work contributes to understanding both the particle size and shape impact on heat and mass transfer during biomass pyrolysis at high heating rates.

Design and experimental study of solar-driven biomass gasification based on direct irradiation solar thermochemical reactor

Solar-driven biomass steam gasification is a promising technology to produce H2-rich syngas, meanwhile achieve flexible storage of renewable energy. However, the solar gasification application also faces numerous challenges, due to its involved complex chemical reaction characteristics and the inherent the multi-physics energy conversion processes. This work designs a novel direct irradiation solar gasification reactor, with the improved optical acceptance structure and reasonable test module, and the wheat straw particle is selected as experimental sample. Employing a 9 kWe high flux solar simulator, the maximum temperature of reaction bed in this prototype reactor reaches to 1260 °C, with the average solar flux of 1171.3 kW/m2. With adjustable radiation flux as experiment factor, under the highest total radiation of 3.35 kW, the molar fraction of H2 in the produced syngas is 47.1 % with the energy upgrade factor of 1.15, and the cellulose component completes decomposition. Increasing the mass flow rate of steam reduces the syngas output while raising the H2/CO ratio of the syngas. In addition, smaller biomass particle size facilitates the reaction, thereby improving the conversion efficiency of direct irradiation gasification. The investigation results provide a meaningful reference for the efficient utilization of abundant solar and biomass energy.

Understanding the role of porous particle characteristics and water state distribution at multi-scale variation on cellulase hydrolysis of lignocellulosic biomass

Porous particle characteristics of lignocellulosic biomass and the water state distribution surrounding particles determine enzyme/solute transfer, while inherently affecting the liquefaction and hydrolysis reactions. For submillimeter biomass particles (<500 μm), deep eutectic solvent pretreatment tended to create additional macropores (∼4%, pore volume of 4.3 mL/g) and micropores (∼3%, pore area of 2.26 m2/g) at the extragranular and cell wall scales, simultaneously with reducing particle size by 15%. The pretreated biomass exhibited preferential rapid liquefaction over sugar production, leading to a ∼70% reduction in particle size only after 3 h hydrolysis. This further increased particle porosity (∼85% after 12 h hydrolysis) with the transition from large surface-pores to interior micropores. The increases in the tissue/cell-scale pore size and intraparticle area had greater significance for improving hydrolysis performance than particle size reduction. Additionally, particle liquefaction released constrained water in capillary pores and enhanced slurry fluidity; capillary water and free water became main transfer carriers during the hydrolysis. Free water activity was positively related to sugar production (r = 0.80–0.85), and integrating it with particle component and porosity allowed for accurate prediction of hydrolysis yields (R2 = 0.98–0.99). Inspired by particle liquefaction, a short-time feeding strategy was proposed to reconstruct high-solid hydrolysis.

Investigations into the flow dynamics of mixed biomass particles in a fluidized bed through Hilbert-Huang transformation and data-driven modelling

Flow dynamics of binary particles are investigated to realize the monitoring and optimization of fluidized beds. It is a challenge to accurately classify the mass fraction of mixed biomass, considering the limitations of existing techniques. The data collected from an electrostatic sensor array is analyzed. Cross correlation, empirical mode decomposition (EMD), Hilbert-Huang transform (HHT) are applied to process the signals. Under a higher mass fraction of the wood sawdust, the segregation behavior occurs, and the high energy region of HHT spectrum increases. Furthermore, two data-driven models are trained based on a hybrid wavelet scattering transform and bidirectional long short-term memory (ST-BiLSTM) network and a EMD and BiLSTM (EMD-BiLSTM) network to identify the mass fractions of the mixed biomass, with accuracies of 92% and 99%. The electrostatic sensing combined with the EMD-BiLSTM model is effective to classify the mass fraction of the mixed biomass.

Evaluation of Empty Fava Beans Pods as Bioadsorbent for the Removal of Pb2+ from Aqueous Solutions Using Phytoadsorption Technique

Environmental contamination with toxic heavy metals is a globally concerned issue. Cleaning up heavy metals from contaminated aquatic systems forces a lot of challenges. Phytoremediation processes are the interesting safe techniques that were focused by scientists and governments during the last decades for the up-taking of toxic heavy metals from ecosystems. Consequently, phytoadsorption approach was applied in this research using dry empty pods of fava beans (Vicia faba L.) to evaluate their potential for the removal of toxic lead heavy metal from its aqueous solutions. We have developed a green and simple method to remove lead ions (Pb2+) from their aquatic system. The obtained results have showed that the 350‒1000-μm biomass particles of fava beans pods were able to take up lead ions at highly rated removal percentages and high adsorption capacity using 100-ml, 100-ppm solutions at room temperature and neutral pH. For example, the highest removal percentage of lead ions was 66.8% with an absorption capacity of 3.34 mg/g using 2.0 g at a shaking rate of 200 OSC/min after 30 min. On the other hand, the removal percentage of lead ions using 0.1 g of fava beans pods biomass was 36.8 % with the highest absorption capacity of 36.8 mg/g at a shaking rate of 800 OSC/min at the same period of time. Therefore, the empty fava beans (Vicia faba L.) pods can be used as potential phytoadsorbents for the removal of lead and other heavy metals from the contaminated aquatic ecosystems.

Pretreatment of Vine Shoot Biomass by Choline Chloride-Based Deep Eutectic Solvents to Promote Biomass Fractionation and Enhance Sugar Production.

Vine shoots hold promise as a biomass source for fermentable sugars with efficient fractionation and conversion processes. The study explores vine shoots as a biomass source for fermentable sugars through pretreatment with two deep eutectic solvents mixtures: choline chloride:lactic acid 1:5 (ChCl:LA) and choline chloride:ethylene glycol 1:2 (ChCl:EG). Pretreatment conditions, such as temperature/time, solid/liquid ratio, and biomass particle size, were studied. Chemical composition, recovery yields, delignification extent, and carbohydrate conversion were evaluated, including the influence of washing solvents. Temperature and particle size notably affected hemicellulose and lignin dissolution, especially with ChCl:LA. Pretreatment yielded enriched cellulose substrates, with high carbohydrate conversion rates up to 75.2% for cellulose and 99.9% for xylan with ChCl:LA, and 54.6% for cellulose and 60.2% for xylan with ChCl:EG. A 50% acetone/water mixture increased the delignification ratios to 31.5%. The results underscore the potential of this pretreatment for vine shoot fractionation, particularly at 30% solid load, while acknowledging the need for further process enhancement.

Modelling the ejection of primary aerosols during the fast pyrolysis of biomass anisotropic particles

A model for the fast pyrolysis of anisotropic biomass particles is presented which considers bubbling dynamics within the liquid intermediate phase (metaplast) and aerosol ejection from this phase. The model employs the population balance equation and the method of moments to estimate the production rate and resultant size distribution of aerosol ejections, incorporating a detailed CRECK reaction mechanism, and considers the effect of anisotropic biomass microstructure on the intraparticle transport of mass and energy. This study investigates the impact of particle size, heating rate (heat transfer coefficient), and lignocellulosic composition on aerosol ejection. The model predicts that, at high heating rates (convective heat transfer coefficient of 359 W/m2.K), aerosols can contribute over 20% to the heavy fraction yield in bio-oil for small particles (1 mm diameter, 4 mm length). The model can predict aerosol size distribution and surface area, indicating an average size of 20 μm for bubbles and 5 μm for aerosols during increased bubble production and aerosol ejection rates. These findings are consistent with prior experimental results and provide essential information for future modeling of extra-particle reactions of the aerosols as they progress through the reactor.

Dynamic dielectric properties of biomass fractionation system using ethylene glycol

The unclear interaction between microwaves and reaction systems limits the further application of microwave in biomass fractionation. This article explored the main factors and their influencing mechanisms that affect biomass fractionation system’s dielectric properties at the frequency of 915 MHz. The experimental results shown that as the temperature of the system increases from 30 to 140 °C, its dielectric constant varies between 23 and 36, while the dielectric loss ranges from 10.5 to 17. The dielectric properties of the system can be influenced by its moisture content, biomass particle content, and ion concentration, except for the intermediate products formed during the biomass fractionation process. Based on the experimental data, empirical expressions for the dielectric constant and dielectric loss factors of biomass fractionation systems as a function of temperature was constructed with the correlation coefficients of 0.9779 and 0.9902, respectively. This study introduces a novel approach to explore the changes in dielectric properties of non-equilibrium systems. The findings of this study are highly significant for the design and optimization of microwave heating processes.

Spouting behavior of binary mixtures of spherocylindrical and spherical particles in a spouted bed

Gas-solid spouted bed systems involving biomass utilization have received much attention in recent years. In actual biomass industrial processes, some fine inert particles are usually added to assist the fluidization of biomass particles. However, the flow mechanisms of binary particle systems containing biomass particles in spouted beds are still poorly understood so far. In this study, spherocylindrical particles representing biomass particles and spherical particles representing inert particles were used as the objects of study. The macroscopic and microscopic flow characteristics were explored based on CFD-DEM modeling when the volume fractions of spherocylindrical particles in the binary particle mixtures were 25 %, 50 %, 75 % and 100 %, respectively. The results showed that the minimum spouting velocities (Ums) were in the range of 150–173 m/s, but did not show a correlation with the different particle systems. During fluidization in binary particle systems, separation of spherocylindrical and spherical particles occurs. There is no significant correlation between the particle systems with different volume fractions of spherocylindrical particles and particle orientation. As the volume fraction of spherocylindrical particles increases, the average bed height of the particles decreases and the translational kinetic energy of the particles decreases/rotational kinetic energy increases. Furthermore, the wall effect influences the spherocylindrical particle orientation and volume fraction, driving the spherocylindrical particles near the wall surface toward the vertical direction.

An Entrained Flow Biomass Gasification Technology with the Fluidized Bed Concept for Low-carbon Fuel Production

For accomplishing the vision of building of a net-emission zero society, low-carbon fuels such as e-fuel, Sustainable Aviation Fuel (SAF), and chemical products generation, plays a significant role. Especially, among the low carbon fuels, SAF is the most crucial. Ammonia and electric aircraft are under way as alternatives to fossil-derived jet fuel (kerosene). However, none of these have yet found their way to commercialization. Among the SAF production technology, biomass gasification and Fischer-Tropsch (FT) synthesis technology are one of the lowest CO2 emission processes, according to Life Cycle Assessment (LCA) analysis. However, at present there are some issues about biomass grinding, tar, ash treatment, gas purification and wastewater. We, at Mitsubishi Heavy Industries (MHI) R&D laboratory have developed entrained bed gasification, adopting the fluidized bed concept in which biomass particles are recirculated in the gasifier without fluidizer. Principally desired outcomes of this development was to reduce the grinding power, simplify the structure by using atmospheric pressure process, and lower tar concentration while maintain suitable temperature to prevent ash from melting inside gasifier. Empirical and actual results showed that the developed gasifier can obtain high carbon conversion ratio and low tar as compared to the traditional gasification processes for low-carbon fuel production and produce reliably stable syngas for low-carbon fuel synthesis with single gasifier. Based on the pilot plant operation results, effectiveness of moderate (1223 – 1323 K) temperature gasification with this concept has been demonstrated too. As a conclusion, development needs and expectation of gasification technology for contributing to carbon neutral society are mentioned.

Innovative Method of Biomass Combustion in the Binary Fluidised Bed

Abstract In this study, a binary fluidised bed made out of quartz sand and cenospheres for the biomass combustion process was created. Materials were fluidised with air to achieve a vertical density profile (from 0.5 g/cm³ to 1.1 g/cm³) resulting from grains segregation. The density profile was selected to ensure optimal control over the location of the combusted fuel particle. This involved positioning the process as close to the bottom sieve as possible. Fluidised bed combustion was carried out at temperatures of 600 °C, 700 °C, 820 °C and 870 °C using straw, willow and sawmill pellets as fuels. Qualitative and quantitative analysis of flue gases was performed using an FTIR spectrometer. Over 90 % carbon conversion from the biomass to carbon dioxide was achieved at 700 °C. At 820 °C and 870 °C, 100 % of biomass carbon left the reactor as CO2. The composition of organic compounds in the process products remained low, reaching a maximum of 3.0 % wt. at 600 °C. To gain further insights into the processes occurring in the immediate vicinity of biomass samples, a complementary TGA/FTIR analysis was conducted. This aimed to clarify the impact of the biomass particle decomposition stage in the fluidised bed combustion process. The proposed mechanism for biomass combustion in the binary fluidised bed contains the particle decomposition stage and the subsequent stage resulting from the coalescence of bubbles containing flammable components and bubbles containing oxidiser.

Accurate machine-learning-based prediction of aerodynamic and heat transfer coefficients for cylindrical biomass particles

Cylindrical biomass (straw) particles play a crucial role in the numerical simulations of biomass co-firing in coal-fired boilers, wherein the aerodynamic and heat transfer coefficients of these particles are particularly important. Despite the existence of models proposed thus far for various specific conditions, developing a universal model for cylindrical particles remains challenging in multiphase flow systems. In this paper, a total of 1092 validated computational fluid dynamics (CFD) datasets of cylindrical drag, lift, torque coefficients and average Nusselt number are acquired based on direct numerical simulations of OpenFOAM body-fitted meshes, and a hybrid algorithmic framework of N+1 convolutional neural network (CNN) machine learning optimality is established. where multiple single-tree models (referred to as N models) are combined with an additional CNN layer (referred to as +1 model).The framework inherits the advantages of a single-tree models while significantly improving the overall algorithmic generalisation performance, with the aim of allowing efficient use of time and minimal expertise in the fluid modelling process. The mean relative absolute errors for drag, lift, torque coefficient, and the average Nusselt number was evaluated, and the results demonstrated a reduction of 75.19 %, 89.48 %, 89.53 %, and 85.70 %, respectively, in the mean relative absolute errors compared to the extremely randomised tree single-tree model. We extended the model scope to different aspect ratios (1 ≤ Ar ≤ 30), angles of incidence (0° ≤ θ ≤ 90°), and Reynolds numbers (1 ≤ Re ≤ 4000), and conducted random predictions. Compared with traditional mathematical relationships, the proposed framework reduced the average relative error to 0.99 %. The simultaneous application of models for the prediction of unknown parameters was validated against relevant early literature, which demonstrated that the average relative error of drag coefficients for the predicted values remained within 2.07 %. The N+1 (CNN) hybrid algorithm framework exhibited high accuracy and excellent adaptability, furnishing a substantial quantity of data to support the Euler–Lagrange model of non-spherical biomass particle multiphase flow in industrial applications.

Predictive modelling of drag, lift and torque coefficients of cylindrical biomass particles under artificial intelligence

The escalating threats of climate change and fossil fuel depletion have greatly spurred the widespread utilization of renewable energy sources. Biomass energy stands out as the most abundant renewable energy resource. Among all biomass conversion technologies, direct combustion of biomass for heating and power generation represents the most common and cost-effective approach. Suspended combustion technology is widely employed in existing biomass combustion power plants worldwide. However, conventional modeling procedures often fail to adequately address the differences between coal and biomass combustion, particularly the significant impact of large-sized and highly non-spherical cylindrical straw biomass particles on their trajectories. This study utilizes OpenFOAM-body-fitted mesh direct numerical simulation (DNS) to generate a Computational Fluid Dynamics (CFD) dataset consisting of 300 data points for cylindrical particles, aimed at constructing a prediction model based on machine learning (N+1) for key aerodynamic parameters (drag coefficient, lift coefficient, and torque coefficient). The proposed model enables precise prediction of aerodynamic parameters for a wider range of different cylindrical particles and flow conditions, thus extending the existing Euler-Lagrangian model for non-spherical biomass multiphase flow.

Assessing thermal hazards and toxicity of raw biomass particles from prevalent agricultural crops in China

Fire and explosion hazards pose significant safety concerns in the processing and storage of biomass particles, warranting the safe utilization of these particles. This study employed scanning electron microscopy, thermogravimetric analysis, and cone calorimetry to investigate the thermal hazards and toxicity of raw biomass particles from four prevalent agricultural crops in China: rice, sorghum, corn, and reed. Among the samples, corn exhibited the highest heat output of 8006.82 J/g throughout the thermal decomposition process. The quantitative evaluation of critical heat flux, heat release rate intensity, fire growth rate index (FIGRA), post-ignition fire acceleration (PIFA) and flashover potential (X) revealed a substantial fire risk inherent to all the examined straw samples. Notably, corn displayed the lowest FIGRA value of 8.30 kW/m2 s, while rice demonstrated the minimum PIFA value of 16.11 kW/m2 s. Moreover, the X values for all four biomass particle types exceeded 10 under varying external heat flux levels, indicating their high propensity for fire hazards. Analysis of CO and CO2 emissions during combustion showed all four biomass samples exhibited high concentrations throughout, from the initial stages to the end. The present study offers crucial insights for formulating comprehensive fire safety guidelines tailored to the storage and processing of biomass particles.