Heating Value Research Articles

Two-Stage Global Biomass Pyrolysis Model for Combustion Applications: Predicting Product Composition with a Focus on Kinetics, Energy, and Mass Balances Consistency

This work presents a comprehensive model for lignocellulosic biomass pyrolysis, addressing kinetics, energy balances, and gas product composition with the aim of its application in wood combustion. The model consists of a two-stage global mechanism in which biomass initially reacts into tar, char, and light gases (non-condensable gases), which is followed by tar reacting into light gases and char. Experimental data from the literature are employed for determining Arrhenius kinetic parameters and key energy parameters, like tar and char heating values and the specific enthalpy of primary and secondary reactions. A methodology is introduced to derive correlations, allowing the model’s application to diverse biomass types. This work introduces several novel approaches. Firstly, a pyrolysis model that determines the composition of light gases by solving mass, species, and energy balances is developed, limiting the use of correlations from the literature only for tar and char elemental composition. The mass rate of light gases, tar, and char being produced is also determined. Secondly, kinetic parameters for primary and secondary reactions are determined following a Shafizadeh and Chin scheme but with a modified Arrhenius form dependent on Tn, significantly enhancing the accuracy of product composition prediction. Additionally, correlations for the enthalpies of reactions, both primary and secondary, are determined as a function of pyrolysis temperature. Primary reactions exhibit an overall endothermic behavior, while secondary reactions exhibit an overall exothermic behavior. Finally, the model is validated using cases reported in the literature, and results for light gases composition are presented.

Hydrochar and Value-Added Chemical Production Through Hydrothermal Carbonisation of Woody Biomass

This study investigates the optimisation of hydrothermal carbonisation (HTC) parameters for transforming Whitewood biomass into hydrochar, focusing on bioenergy production and valuable chemical extraction as by-products. The optimal carbonisation was achieved at a process temperature of 240 -260 °C, which optimised the higher heating value of the hydrochar to 27-30 kJ/g and ensured a structural integrity similar to lignite coal. Increasing the temperature beyond 260 °C did not significantly enhance the energy content or quality of the hydrochar, establishing 260 °C as the practical upper limit for the HTC process. Residence times between 30 to 60 min were found to have minimal impact on the yield and quality of hydrochar, suggesting significant operational flexibility and the potential to double throughput without increasing energy consumption. The study also revealed that the process water by-product is rich in furan compounds, particularly furfural and hydroxymethyl furfural, with their highest concentration (125 mg/g of feedstock) occurring at 220 °C. The implementation of these findings could facilitate the development of a large-scale HTC facility, significantly reducing reliance on fossil fuels and enhancing economic viability by producing high-energy-density biofuels and high-value chemical by-products.

Testing Pellets Fuel Production from Sewage Sludge of Palm Oil Industry

The wastes from the palm oil production process were used in this study, such as wastewater sludge and cake decenter or decanter waste. That moisture was less than 40% and increased density by the cold pelletizing process. The aim is to use pellet fuel for heating. Analysis of pellet fuel consists of physical properties, proximate (moisture, ash, volatile matter and fixed carbon) and heating value. The results showed that cake decenter and wastewater sludge had similar high volatile matter. The decenter cake had a higher heating value than the wastewater sludge at 26.649 and 14.965 MJ/kg, respectively. The ash of decenter cake was lower than wastewater at 11.71% and 22.34%, respectively. Blending both raw materials for pelletization increased the volatile matter that did not mix with another material. Therefore, both materials can be used to produce pellet fuel that has an optimal shape and size. That was hard to break. The results of chemical property testing show that it is within acceptable limits and can be used as pellet fuel.

Integrating solid oxide electrolysis cells and H2-O2 combustion for low-emission high-temperature heating with heat pump in the chemical industry

Low-emission high-temperature heating could be achieved by exploiting electrical heating, clean fuel, or carbon capture. However, it is difficult to replace current coal or natural gas furnaces in some places because the high-temperature thermal demand needs combustion. In the present work, the green hydrogen production process by solid oxide electrolysis cells (SOEC) and H2-O2 combustion is integrated into ethylene production. The working conditions of electrolyzer and furnace are analyzed. The SOEC should work over 800°C to keep endothermic state no matter the current density. To produce the hydrogen of 80 MW heat value, the electric consumption is at least 69.4 MW. With the high-temperature waste heat of 7.76 MW, an additional 3 MW power is required for water electrolysis. The heat released during condensation of combustion products is 30.52 MW, much higher than 13.19 MW from SOEC products. Therefore, the heat pump is necessary to recycle the waste heat of water condensation and generate steam as the electrolysis ingredient and cooling medium, which saves 63 % of energy. Although the total energy consumption increases by 11.23 % from 80.23 MW to 89.24 MW, the CO2 emission drops by 84.28 %.

Analysis of the Influence of Variation in Medical Waste Heating Value on the Electrical Energy Output of Generator in Medical Waste Cogeneration Incinerator System using Gatecycle Solver

Abstract Medical waste incinerator is a technology capable of processing and exterminating hazardous medical waste through combustion at temperatures exceeding 800°C. Medical waste exhibits a range of heating values depending on its material composition. The heating value represents the potential heat energy released when a substance undergoes complete combustion. A cogeneration incinerator is designed to treat medical waste while also harnessing the heat of the flue gas that emanates from the combustion process. The flue gas acts as a hot fluid that transfers its heat, causing the water temperature inside the boiler to increase and transform into high-temperature steam. This steam drives a steam turbine connected to a generator to generate electrical energy. The amount of electrical energy generated is influenced by the steam quality produced through the boiler’s water-heating process. This study aims to investigate the influence of variation in the heating value in medical waste on the electrical energy output of the generator in a medical waste cogeneration incinerator system. The range of heating value variations used in the testing varies from 25 MJ/kg to 35 MJ/kg. The variation is tested through thorough simulations using GateCycle software to obtain data on the electrical energy generated. To achieve a maximum electrical energy output of 200 kW, fuel with a total heating value of 32.25 MJ/kg is required. This study is beneficial to be implemented as renewable energy sources based on biomass powerplant systems.

Sensitivity analysis of the INRA 2018 feeding system for ruminants by hybrid local and global approaches: Comparing the contribution of dietary input variables to multiple response prediction in dairy cattle

We conducted sensitivity analysis (SA) of the INRA 2018 feeding system for ruminants applied to dairy cows. We evaluated which dietary input variables contribute most to changes in each output variable, considering the potential interactions presence among input variables. A quantitative analysis (one-at-a-time analysis, OAT; i.e., local SA) and a relative comparative analysis (global SA, GSA) through variance-based SA considering potential interactions and non-monotonicity were applied. The 5 likely influential dietary input variables were selected: CP, Gross energy (GE), OM apparent digestibility (OMd), effective degradability of nitrogen assuming a passage rate of 6%/h (ED6_N) and true intestinal digestibility of nitrogen. The sensitivity of 5 selected animal responses (output variables) to input variables was analyzed: DMI, milk protein yield (MPY), energy in methane (ECH4), nitrogen utilization efficiency (NUE), and ratio between urine and total N excretion (UN/TN). Six diets for dairy cattle, reflecting the diversity of diets commonly used in practice, were formulated to meet 95% of the potential milk production (37.5 kg/d) of a multiparous dairy cow at wk 14 of lactation. For each diet, the 5 input variables were randomly sampled around the INRA 2018 feed table values (reference point), and the animal responses around this reference situation were calculated using the rationing software INRAtion®V5. In OAT, the sensitivity of animal responses was quantified by calculating the normalized tangent value at the reference point, and in GSA, the Sobol indices were calculated for relative influence of each input and their interaction. The influence of the 5 key input variables on the 5 main animal responses predicted from the INRA feeding system was consistent across both SA approaches. With the 6 diets, GE and OMd appeared as the main contributors to changes in DMI, MPY, ECH4, and NUE. Crude protein was the main contributor to changes in UN/TN and another major contributor to changes in NUE. When considering OAT, the sensitivity of outputs showed differences depending on diet, more particularly for DMI and MPY. With grass hay-based diets (GH diets), DMI was less sensitive and MPY was more sensitive to variations in input variables than other diets. When considering GSA, interactions between input variables were also noticeable for DMI and MPY; the interactions were high with the GH diets for DMI, and with fresh ryegrass and grass silage diets for MPY. On the other hand, for MPY, the non-GH diets were less sensitive to variations in input variables and the interaction between inputs was higher than with GH diets. In both cases, the interactions were mainly related to energy-related inputs (i.e., OMd and GE). Our results support the hypothesis that MPY, unlike DMI, is more responsive to energy-related factors at high PDI/UFL ratio (i.e., between metabolizable protein and NEL, e.g., GH diets >117 g PDI/UFL), than at lower PDI/UFL ratio. Hence, hybridizing the SA methods can help to interpret the system and facilitate a more precise evaluation thereof, especially GSA, which is amenable to non-monotonic models such as those characterizing complex feeding systems integrating multiple nutritional and animal factors.

Pengaruh variasi besar butir dan variasi komposisi bahan terhadap kinerja briket arang tempurung kelapa dan sekam padi

Abundant biomass waste is often thrown away. Careless disposal of waste will have a negative impact on environmental quality. Research regarding variations in composition and grain size of biomass waste charcoal briquettes on briquette performance is feasible. The aim of the research is to obtain briquettes that have high performance. The research method used was experimental research, coconut shell charcoal and rice husk charcoal, made in sizes 20 mesh, 60 mesh and 100 mesh. Then mixed with 15% starch adhesive with variations in the composition of coconut shell charcoal (TK): rice husk charcoal (SP), namely: I (75%:25%), II (50%:50%) and III (25%:75% ), After printing, the biket is dried in the sun and in the oven until it reaches a moisture content of (14-15)%. After the briquettes are dry, the heating value, flame duration and water boiling time are tested. In the calorific value test, the greater the composition (TK), the greater the calorific value produced. The highest heating value of 5937 kcal/kg was obtained from composition I, mesh 60 and the lowest heating value of 3714 kcal/kg was obtained from composition III mesh 60. The shortest flame duration of 1386.6 seconds occurred in mesh 20 composition III and the longest flame duration was 1933.2 seconds. obtained on mesh 100 composition I. In the Boilling Time test, it was found that the larger the grain size and the greater the composition of the coconut shell charcoal mixture in bioarang briquettes, the faster the water boiling time.

Upgrading vacuum residue in a supercritical CO2 environment with polypropylene and steam: Insights into products distribution and characterization of liquid products

The pyrolysis of vacuum residue (VR) using polypropylene (PP) under supercritical carbon dioxide (scCO2) conditions represents a novel approach to converting this abundant and difficult-to-process feedstock into lighter liquid products. In this paper, a set of experiments was performed to analyze the impact of scCO2, PP and steam on the yields of pyrolysis products (i.e., liquid, gas and coke) and characteristics of the liquid fractions. The findings indicated notable improvements when scCO2 was used instead of subcritical CO2 in the pyrolysis of VR with PP. These included decreased viscosity and improved API gravity, alongside increased maltene yield and reduced coke yield. Furthermore, the inclusion of PP markedly elevated the quality of the obtained liquid, whereas steam + scCO2 primarily affected the product distribution by raising the yield of coke and gas fractions. VR pyrolysis under scCO2 conditions at 380 °C, 8 MPa, PP/VR ratio of 0.23 for 60 min in a batch system, without the use of catalyst, resulted in the highest liquid yield of 83.7 ± 1.9 wt%, and minimum coke yield of 9.8 ± 1.3 wt%. Under these conditions, the upgraded liquid consisted of 75.2 wt% light and middle distillates with boiling points below 350 °C. Additionally, the proportion of oxygenates in the pyrolysis oil reduced by 60.5 %, improving its heating value. Moreover, adding PP to the upgrading process resulted in a higher proportion of isoparaffins, cycloparaffins, and aromatics, coupled with a decrease in olefins, aligning the liquid specifications more closely with fuel standards.

Production and optimization of briquette (solid fuels) from waste biomass using industrial starch as binder

This study aims to develop an efficient means of transforming municipal solid waste and agricultural waste to produce and optimize briquettes from biomass as an alternative energy source capable of replacing fossil fuels. The project involved the production of briquettes from paper, sawdust, and charcoal, using industrial starch, and sodium hydroxide pellets as binders. The fuel briquettes were produced from paper and charcoal combination, paper, charcoal and sawdust combination, sawdust and charcoal combination, and wastepaper and sawdust combination at different amounts of binders of 100%, 120%, 140%, 160%, and 180% weight of water to the respective briquettes produced. The combustion-related properties were determined. The data obtained, and the optimization of the briquettes produced from paper, charcoal, and sawdust combinations were done using the design expert software program. From the experiment, it was seen that the briquettes made from the paper, charcoal, and sawdust combination had a better combustion capacity with heating values of 34,469.1 KJ/kg, an ash content of 7.656%, and a volatile matter content of 87% for 180% binder. Also, from the result obtained, it can be confirmed that the briquettes made from paper, charcoal, and sawdust had a higher dry density value of 985.6 g. The cost analysis and evidence from literature show that briquettes are not only a better and more reliable alternative fuel source to the high-rising conventional cooking fuel available but also reduce the problems associated with rapid deforestation environmental degradation, and pollution.

Hydrothermal bio-oil yield and higher heating value of high moisture and lipid biomass: Machine Learning modeling and feature response behavior analysis

The yield and higher heating value (HHV) of bio-oil products are significant performance parameters for the hydrothermal conversion of high-water and high-lipid biomass. Machine learning (ML) modeling prediction is a fast and convenient means of obtaining performance parameters. An informative dataset with 243 samples was prepared, and two highly adapted ML algorithms were used: Random Forest (RF) and Extreme Gradient Boosting Tree (XGBoost). It is interesting to note that the developed ML models demonstrated great prediction ability; for example, the regression coefficient () of the XGBoost model for yield and HHV prediction was as high as 0.942 and 0.940, respectively. Furthermore, partial dependence plots and SHAP (SHapley Additive exPlanations) interpretability methodologies were adopted to address the main contributions of the feature identification and response behavior analysis of the features. The results demonstrated that the biomass composition had the greatest effect on bio-oil yield, with fat contributing up to 40%. In contrast, the elemental composition had the most significant effect on the HHV of bio-oil. Notably, hydrogen content affected the HHV of up to 4.5 units. The interaction response behavior showed that the interaction of the process parameters with feedstock properties was most common and significant. The information obtained from the response mechanism can be used to enhance the subsequent hydrothermal fuel preparation process for bio-oils.

Modeling CO2 loading capacity of triethanolamine (TEA) aqueous solutions via a deep learning approach

Capturing carbon dioxide (CO2) from natural gas is essential for reducing CO2 emissions as a greenhouse gas as well as increasing the gas heating value. Absorption of CO2 by amine solutions is a method that has seen a widespread use as a CO2 collection technique. In this research, advanced ML approaches are utilized to simulate the CO2 loading capacity of triethanolamine (TEA) aqueous solutions as a function of system temperature, CO2 partial pressure, and amine concentration in the aqueous phase. Deep neural network (DNN), Gaussian process regressor (GPR), deep belief network (DBN) and bagging regressor (BR) are the models that have been developed. The DNN model with the coefficient of determination (R2) of 0.9990 as well as the root mean square error (RMSE) of 0.0073 outperformed other models in terms of accuracy and validity. The R2 values of 0.9911, 0.9861, and 0.9745 for DBN, BR, and GPR, accordingly, showed that other models could likewise perform with high accuracy. Moreover, trend analysis of the results confirmed that the DNN method can correctly estimate the behavior of CO2 loading with variations in the input parameters. Furthermore, a sensitivity analysis showed that temperature has a decreasing effect on the CO2 loading, while amine concentration and CO2 partial pressure exhibited to have an incremental effect. Herein, the temperature had the greatest influence on the amount of CO2 loading. The final stage of the research was the leverage approach, which stated that about 99% of the data are statistically valid and the DNN model is reliable to be replaced by experimental approaches in the prediction of CO2 absorption into certain type of solutions.

Analysis of the Effect of More Fuel and Air Variations Excess Air on Combustion Process Simulation at a 10 kW Biomass Power Plant Using ASPEN PLUS

Abstract The utilization of biomass as an alternative energy can support the achievement of Net Zero Emissions. Each type of biomass fuel can provide different combustion effects from one another. This is due to the different heating values of each fuel. The calorific value is one of the things that affect the combustion performance of the biomass power plant. The main purpose of this study is to examine how different amounts of excess air used during the combustion process affect the outcomes. Combustion is a chemical reaction involving decomposition and gasification that simultaneously occurs in a space where a large amount of energy is released. The modeling and simulation of the decomposition and gasification processes were carried out using Aspen Plus. In this simulator, the decomposition process takes place in the Yields Reactor, while the gasification process occurs in the Gibbs Reactor. The biomass and ash components are characterized by their ultimate, proximate, and sulfur analysis. Then the excess air is varied to analyze its impact on the flame temperature from the reaction. The simulation findings emphasize crucial considerations for achieving complete combustion and reducing harmful gas emissions. Maintaining excess air close to the stoichiometric level ensures maximum combustion temperature at 1616.15 °C while minimizing excess air reduces NOx gas concentration. Approaching stoichiometric air level decreases CO gas and increases CO2, indicating more thorough combustion. However, excess air leads to lower adiabatic flame temperature due to nitrogen formation.

Enhancing bioenergy and feed production in Southern Thailand: An approach through Leucaena cultivation and hydrothermal carbonization

This study addresses sustainability challenges in Southern Thailand, particularly the scarcity of biomass fuel and animal feed. It investigates the integration of Leucaena leucocephala cultivation with hydrothermal carbonization. The research compares the biomass yield and economic feasibility of growing Leucaena as a sole crop versus intercropping it with Para rubber trees. Sole cropping Leucaena produces higher biomass yields and is more economically viable. The wood stem of Leucaena is competitive with other biomass fuels used in local power plants, while its leaves, with over 14 % protein content, meet local animal feed market standards. Additionally, branches, which constitute 15.15 % to 30.58 % of the total biomass, are usually left as residue but can be used for hydrochar production. The study examines the effects of temperature (235 °C and 265 °C) and retention time (1, 2, and 3 hours) on hydrochar properties. Optimal condition (265 °C for 1 hour) produces hydrochar with high heating value and energy yield. Using these branches for hydrochar can significantly boost total revenue, with hydrochar contributing 54.9 % to overall revenue (4522.00 USD/ha). Integrating Leucaena cultivation with hydrothermal carbonization offers a sustainable solution, enhancing revenue, supporting local energy and feed needs, and promoting environmental sustainability.

Performance of anhydrous ethanol and gasoline blends on a SI engine: Decoupling evaporation enthalpy and knock resistance

Blending bioethanol with gasoline is recognized as a rapid solution for mitigating nonrenewable carbon dioxide emissions. This approach proves particularly meaningful in markets where the production of this biofuel aligns with sustainable practices. Understanding the alterations in the combustion process holds significance within these markets, contributing to informed decision-making and fostering environmentally conscious practices. In this context, it is widely known that highly ethanol blended fuels can provide benefits regarding suppression of knocking combustion in spark ignited engines if the quality of the base-fuel is not deteriorated to maintain octane ratings. However, the results of engine knocking investigations can be affected by two effects simultaneously. Firstly, ethanol has a beneficial effect on knock suppression due to its high enthalpy of evaporation compared to gasoline, which results in inner mixture cooling especially with direct injection. Secondly, ethanol can have beneficial effects on knock suppression by its decreased self-ignition tendency. This paper provides the set-up and results of an adapted engine testing procedure to diminish the effects of evaporation enthalpy during the knocking investigations of different highly ethanol blended fuels. The presented testing procedure at a single-cylinder research engine includes three technical steps: (1) the engine is equipped with a port fuel injection in stoichiometric operation for all tested fuels; (2) the engine is operated with constant speed of 1500 rpm and constant spark timing of 33° firing top dead center; (3) the engine is operated with fuel individual settings for the intake manifold gas pressure and intake manifold gas temperature. These parameters are adjusted to test all fuels with similar in-cylinder conditions at spark timing. The differing heating values of the fuels obviously result in differing engine loads. However, the presented testing procedure is aimed to achieve comparable in-cylinder conditions at spark timing without the effect of evaporation enthalpy. The novelty of the study lies in its adapted engine testing procedure that mitigates the cross-effects of fuel properties and operational conditions to isolate the true influences on knock occurrence. The paper provides a comprehensive description of the theoretical backgrounds, experimental set-up and post-processing procedures and also shows the results of the first measurement campaign.

Co-pyrolysis of biomass/polyurethane foam waste: Thermodynamic study using Aspen Plus

Due to the varieties and identical feature of solid waste, this research aims to consider the use of various feedstocks in pyrolysis process for liquid fuel production. The feedstock considered covers woody and non-woody biomass and plastic waste which are represented by sawdust (SD), palm leaf (PL) and polyurethane foam (PU) waste. In this research, both pure solid waste and the co-pyrolysis of biomass and plastic wastes were determined based on thermodynamics study. The model of pyrolysis process developed through Aspen Plus simulator was implemented to study the product yield, higher heating value (HHV) and energy consumption with a wider range of pyrolysis temperature and blending weight ratio. The simulation results clearly showed the use of pure PU waste can provide the highest oil yield (∼44%wt.) which is corresponded to highest HHV (∼28 MJ/kg). The pyrolysis, operating at 400oC, can provide the most significant quantity of oil. For the co-pyrolysis, the results revealed that more PU waste blended in both biomasses can improve both oil yield and HHV while the energy consumption is lower. From the simulation results, the optimal blending weight ratio of biomass and PU waste at 25:75 can provide suitable oil yield (∼43%wt.), HHV (∼26 MJ/kg) and energy consumption (243kW).

Unveiling the potential of operating time in improving machine learning models’ performance for waste biomass gasification systems

Biomass is a promising renewable energy source, especially regarding local energy production. Gasification is an outstanding thermochemical process for syngas production from biomass. The optimal modeling and control of syngas production from biomass gasification is vital in planning small-scale energy supply. Artificial intelligence methods are widely applied to reveal the nonlinear relations between the gasification parameters and the reaction products. In this study, special attention is paid to the effect of operating time as a predictor on the performances of the models formed, as its introduction provides the phase information to the model which allows the combination of different sequential experimental data. Unlike most preceding studies in which hold-out is preferred, nested cross-validation is utilized for model evaluation emphasizing the unbiased nature of the latter method. Least squares, gaussian kernel, generalized additive models, random forest, and artificial neural networks (ANN) are utilized to model the process's product syngas composition and high heating value (HHV). The significance of operating time on the gasification system is also reflected on the feature importance analysis which is performed. Along with the operating time, temperature is also shown to play a vital role on the hydrogen yield and calorific value of the products.

ANALISIS SIFAT FISIKA DAN SIFAT KIMIA GEL BIODIESEL DARI MINYAK BIJI PALEM PUTRI (Adonidia merrillii)

Biodiesel is an alkyl ester of long-chain fatty acids, the most common of which are methyl esters or ethyl esters. The manufacturing process involves esterification and transesterification. Traditional sources of biodiesel raw materials such as palm oil, soybeans, and jatropha have been widely studied. The princess palm, widely known as an ornamental plant, produces fruit containing seeds with quite high oil potential. This research aims to produce biodiesel and determine the physical and chemical properties from putri palm seeds. This research is experimental research with a quantitative descriptive approach. Putri palm seed oil is extracted using the soxhletation method with n-hexane solvent. The oil was then esterified using methanol with a catalyst of 1% sulfuric acid with a mole ratio of oil and methanol of 1:8 at a temperature of 60°C for 3 hours. The esterified oil is then transesterified using methanol and KOH with a methanol to oil ratio of 1:20 with KOH of 0.8% for 2 hours at a temperature of 60°C. This research has succeeded in making biodiesel from putri palm seeds. The biodiesel produced is in the form of a gel referred to as biodiesel gel with a yellowish brown color with a density of 1,236 gr/ml and a pour point of 36-38°C. The FFA/ALB value is 0.587%, the acid number is 1.177 mg KOH/g, the IOD number is 34.514 (g-I2/100 g), the saponification number is 63.19 mg KOH/g, the heating value is 48.088 MJ/Kg, and the cetane number 38,620. The IOD number, saponification number, and heating value meet the SNI standards for liquid biodiesel in general, while the cetane number and ALB value are close to SNI standards.

Evaluation of an empirical model for predicting the calorific value of biomass briquettes from candlenut shells and kesambi twigs

Biomass briquettes offer a sustainable alternative to conventional fossil fuels, contributing to renewable energy while reducing environmental impact. This research explores the development of biomass briquettes from candlenut shell charcoal (Aleurites moluccanus) and kesambi twigs (Schleichera oleosa), focusing on their physical properties and heating values. Using tapioca as a binder, briquettes were produced with varying ratios: A. Control (90% kesambi twigs + 10% adhesive), B. 3:1 (67.5% kesambi twigs + 22.5% candlenut shell charcoal + 10% adhesive), C. 1:1 (45% kesambi twigs + 45% candlenut shell charcoal + 10% adhesive), and D. 1:3 (22.5% kesambi twigs + 67.5% candlenut shell charcoal + 10% adhesive). The study aimed to optimize briquette composition for maximum density, compressive strength, and calorific value while minimizing moisture, ash, and volatile matter. Results indicated that a higher proportion of candlenut shell charcoal enhanced density, compressive strength, and fixed carbon content, with the highest calorific value exceeding 19 MJ/kg observed in the 1:3 ratio. Additionally, the study evaluated three empirical models for predicting the Higher Heating Value (HHV) of the briquettes, finding the Nhuchhen model to be the most accurate, with an R² value of 0.93, providing a reliable method for predicting calorific value.

Insights into the pelletization behaviors of artificial lignocellulosic biomass based on cellulose, hemicellulose and lignin: A simplex lattice mixture design approach

The use of high quality densified pellet as an alternative to traditional fossil fuels is a promising avenue of research due to their interesting higher density, superior heating values, and enhanced combustion performance. However, little is known about the pelletization behaviors from the aspect of lignocellulosic biomass fundamental components (cellulose, hemicellulose and lignin) and their mixtures. This study presents an artificial biomass developed based on cellulose, hemicellulose and lignin using a simplex lattice design approach, aiming to understand the detailed role of major components and its effects on pellet quality. The correlation between the experimental data obtained from the simplex lattice design and the predicted response parameters were effectively explained by Scheffé's special cubic model, with a coefficient of determination beyond 90 %. Parameter estimates showed a significant synergetic effect of each components for density and Meyer hardness. Results revealed that xylan may be softened like lignin and thereby potentially act as binder. The use of a high cellulose concentration resulted in enhanced pellet strength by acting as a supporting skeleton. Xylan and cellulose played a major role in the thermal degradation of densified pellets. Based on the results obtained, the optimal components composition was determined to be 34.5 % lignin, 36.3 % cellulose, and 29.2 % xylan. Under this, the pellet exhibited the best density and Meyer hardness beyond 1500 kg/m3 and 80 N/mm2, respectively. The results provide a foundation for future efforts to be able to predict pellet properties from the perspective of biomass composition.

Hydrogel Dressing Biomaterial Enriched with Vitamin C: Synthesis and Characterization

Materials engineering has become an important tool in the field of hydrogel dressings used to treat difficult-to-heal wounds. Hydrogels filled with bioactive substances used as a targeted healing system are worthy of attention. Vitamin C has healing and supporting effects in the treatment of many skin problems. The aim of the research was to produce a hydrogel biomaterial enriched with ascorbic acid for use as a dressing for difficult-to-heal wounds. A total of four different dressings were developed, each with different modifications in each layer. The dressing with vitamin C in the third layer was shown to release vitamin C ions more slowly than the dressing with vitamin C in the first layer. The studies conducted have shown that the dressings containing vitamin C have, among other things, a higher compressive strength, are characterised by a lower relative shortening after the application of force and shorten without damage at a lower force than in the case of a dressing without vitamin C. The dressings designed have a very good stability in the temperature range of 18 °C to 60 °C. It was found that the higher the vitamin C content in the dressing, the greater the increase in the specific heat value of the transformations. Therefore, hydrogel dressings containing vitamin C may be candidates for local delivery of vitamin C to the skin and protection of the wound area.