Master Plot Method Research Articles

Mechanism and process study of spent lithium iron phosphate batteries by medium-temperature oxidation roasting strategy

In this study, we determined the oxidation roasting characteristics of spent LiFePO4 battery electrode materials and applied the iso-conversion rate method and integral master plot method to analyze the kinetic parameters. The ratio of Fe (II) to Fe (III) was regulated under various oxidation conditions. The results showed that 95.50 % of LiFePO4 was oxidized to Li3Fe2(PO4)3 and Fe2O3 under the most cost-effective roasting conditions (500°C, 1000 mL/min, 30 min, air atmosphere) and only approximately 18 % graphite was involved in the reaction. More than 99 % of the lithium was leached under these roasting conditions, with minimal impurities. Medium-temperature selective oxidation roasting effectively avoided the high-temperature sintering phenomenon that affects the crystal structure of the product. Instead, a fine, uniform oxidized phase was formed, and the polyvinylidene fluoride impurity that typically persists throughout the recycling process was avoided. This study provides a sufficient theoretical basis and experimental prerequisites for selective, time-efficient, and economical lithium leaching or reductive regeneration of the cathode materials.

Thermal evolution of mercury from waste rare earth phosphor: Effect of thermal treatment conditions and kinetic analysis

Waste phosphor (WP) from fluorescent lamp is a hazardous waste and an important secondary resource for recycling mercury and rare earths. To avoid mercury pollution during rare earth recovery, it is necessary to conduct deep mercury removal before rare earth recovery. However, the mechanism of mercury removal in WP is not clear, which restricts the progress of efficient mercury removal methods. Effects of treatment temperature and time on thermal evolution of WP were analyzed by different characterization methods. Model-free, model-fitting and z(α) master plots method are used in combination to explain the complex mechanism of mercury removal in WP. The mechanism of mercury removal will change gradually with the process of mercury removal. The average Eα for mercury removal is 100.76 kJ/mol and 190.36 kJ/mol at conversion α (i.e. mercury removal efficiency) of 0.1–0.3 and 0.3–0.9, respectively. Simple mercury compounds are decomposed at α less than 0.3 (∼600 °C), according with the model of random nucleation and subsequent growth. A large amount of tightly combined mercury is released rapidly at α of 0.3–0.75 (600–700 °C), ascribing to the decomposition of carbonate and the structure transformation of silicon oxide. The process mechanism gradually change from 1D/2D diffusion to 3D diffusion, increasing the mass transfer resistance of mercury diffusion. Thermal desorption of residual bound mercury at α larger than 0.75 (∼700 °C) is controlled by phase boundary reaction. More efficient mercury removal effects can be obtained by adding additives to roasting. The results are beneficial to the research of deep mercury removal methods of WP.

Co-pyrolysis of chrome-tanned leather shavings with wheat straw: Thermal behavior, kinetics and pyrolysis products

The thermal behavior and kinetics of chrome-tanned leather shavings (CLS)/wheat straw (WS) blends at different mass ratios during co-pyrolysis were investigated, and the pyrolysis products were characterized. Model-free isoconversional and master-plots methods were applied to determine kinetic triplet of the pyrolysis/co-pyrolysis of CLS, WS and their blends based on thermogravimetric (TG) analysis. Results showed that the activation energy for CLS pyrolysis was reduced by the addition of WS, and a synergistic promoting effect predominated across the majority of temperature ranges and feedstock compositions during the co-pyrolysis process. TG-Fourier transform infrared spectrometry-Mass spectrometry analysis showed the changes in evolution profiles of H2O, CO, CO2, HNCO and pyrrole during pyrolysis. The pyrolysis solid residues were characterized and results indicated that the addition of WS to CLS can increase solid residue yield and potentially inhibit the formation of hexavalent chromium during pyrolysis. This study helps to foster a promising solution for the valorization and safe disposal of chromium-containing solid wastes from leather industry.

Pyrolysis of Euphorbia Rigida: A study on thermal characterizations, kinetics, thermodynamics via TG-FTIR analysis

Euphorbia Rigida (E. Rigida), a lignocellulosic biomass with low ash content, is a suitable feedstock for pyrolysis. This work investigated the physicochemical characteristics and thermokinetic analysis of E. Rigida pyrolysis by using isoconversional and master plots methods. Ultimate and proximate analyses and oxygen bomb calorimeter were used to determine the physicochemical parameters. The activation energies were calculated using model-free methods (KAS, Friedman and Starink) and were found as 184, 178 and 185 kJ/mol, respectively. Using Fraser-Suzuki deconvolution, pseudo-components were also calculated and the active pyrolysis region was divided into three zones. The master plots showed that reaction order mechanisms (Fn) were effective in Zone I, and diffusion mechanisms (Dn) were well matched in Zone II and Zone III. The thermodynamic parameters (ΔH, ΔG and ΔS) were calculated and according to these results, E. Rigida pyrolysis was an endothermic and non-spontaneous process.

Investigation on prospective bioenergy from pyrolysis of macadamia nut shell waste using multicomponent Fraser-Suzuki kinetic model, kinetic triplet and thermodynamic parameters

The investigation of macadamia nut shell waste (MNSW) was conducted to elucidate its bioenergy potential through the analysis of physicochemical properties, kinetic triplet, reaction mechanism models, and thermodynamic parameters. The thermal degradation experiments were carried out using a thermogravimetric analyzer under nitrogen atmosphere at four different heating rates. The multicomponent Fraser-Suzuki kinetic model revealed that the primary decomposition stage could be successfully divided as the parallel devolatilization process of two, three, or four pseudo components. The thermal degradation process of MNSW can be divided into pseudo hemicellulose (PE-H), hemicellulose-lignin (PE-HL), hemicellulose-cellulose (PE-HC), cellulose (PE-C), and lignin (PE-L) employing the multicomponent Fraser-Suzuki kinetic model. The apparent activation energy (E) was calculated using Friedman, Ozawa-Flynn-Wall, Starink, and Kissinger-Akahira-Sunose four model-free methods. The average apparent activation energy calculated through the Starink model-free method was found to be 190.13 and 174.18 kJ/mol for PE-HL and PE-C, 143.79, 169.99, and 249.88 kJ/mol for PE-H, PE-C and PE-L, and 142.98, 157.15, 169.84, and 244.62 kJ/mol for PE-H, PE-HC, PE-C and PE-L, respectively. Evaluation of thermodynamic parameters showed that the pyrolysis process of each pseudo component was an endothermic non-spontaneous reaction independent of surface area and required additional heat and energy input. The pyrolysis process of all pseudo components was accurately characterized using order-based, nucleation, geometrical contraction, power law, and diffusional reaction mechanism models using master plots method. This work provides a theoretical basis for MNSW or other biomass wastes as attractive and environmentally friendly alternatives for bioenergy production, offering crucial insights for reactor design and improving conversion efficiency.

ANN approach for the prediction of pyrolytic behaviour of pigeon pea stalk and insight into thermo-kinetics of pseudo components using RSM

Artificial neural network (ANN) is the widely used technique for prediction and modeling of complex processes. In this study, ANN was applied for predicting the complex pyrolysis behaviour by employing critical process parameters like heating rate (°C/min) and temperature (°C). Two anticipated variables in input layer were used to predict the derivative weight loss (%/°C) by propagating in twelve neurons. The model's reliability and adequacy were validated by the best training performance data recorded at 36 training epochs with an MSE value of 2.34 × 10−5. In order to estimate the thermo-kinetics of the Pigeon pea stalks (PPS), thermogravimetric analysis was done at four heating rates (10–40 °C/min). The TG-spectra were resolved into their pseudo components using deconvolution technique. The activation energy and pre-exponential factor were estimated by Friedman isoconversional method. In continuation, response surface method (RSM) was employed to explore the effect of process parameter on thermodynamic parameters ΔG, ΔH, and ΔS. The recorded statistical values illustrated the adequacy and robustness of the fitted model with anticipated variables. Pyrolytic reaction order was also determined for each pseudo components through master plot method.

Pyrolysis of macadamia nut peel using multicomponent Gaussian kinetic modeling and ANN analysis

The physicochemical properties of macadamia nut peel (MNP) were explored based on pyrolysis characteristics, kinetics, thermodynamic parameters, reaction mechanism, and artificial neural network (ANN) application to evaluate its suitability and potential for pyrolytic conversion into bioenergy products. Pyrolysis experiments of MNP were performed using a thermogravimetric analyzer in a nitrogen atmosphere. The thermal degradation process of MNP can be successfully modeled into pseudo hemicellulose (PS–H1), cellulose (PS–C2), and lignin (PS-L3) using a multicomponent Gaussian kinetic model with high correlation coefficient (R2 > 0.99). The average apparent activation energy was 179.28 kJ/mol for PS-H1, 192.31 kJ/mol for PS-C2, and 129.42 kJ/mol for PS-L3 using Ozawa-Flynn-Wall, Kissinger-Akahira-Sunose, Starink, and Tang four model-free methods. Master plots method was used to determine the reaction mechanism models of three pseudo components, and the pyrolysis progress can be described well using order-based and nucleation mechanism models. The thermal degradation behaviors of MNP were predicted using artificial neural network, and the best artificial neural network prediction model was ANN (3*15*1). Based on the physicochemical properties, pyrolysis characteristics, kinetics, thermodynamic parameters, reaction mechanism and ANN prediction model, MNP is suitable for pyrolytic conversion into bioenergy products.

Pyrolysis of natural rubber–cellulose composites: isoconversional kinetic analysis based on thermogravimetric data

Despite the current growing interest in rubber composites with natural organic fillers, there is a lack of kinetic analyses that describe the decomposition of these materials during pyrolysis. For this reason, the main objective of this study was the kinetic analysis and determination of formal kinetic parameters for the pyrolytic decomposition of NR–CEL composites with different cellulose content (0, 30, 45, and 55 phr). Thermogravimetric measurements were made at heating rates of 2, 4, 6, 8, 10, and 20 °C min–1 in the temperature range of 20–600 °C. First, Friedman and KAS model-free methods were applied. Therefore, model-based methods and the model-fitting procedure were used to find the optimal multi-step kinetic model. The proposed final model consists of two parallel processes, which are kinetically independent: A → B → C and D → E → F. For each step, a kinetic triplet was calculated: the apparent activation energy, the pre-exponential factor, and the kinetic parameters of the extended empirical Prout–Tompkins model. The master plots method was used to determine the kinetic decomposition mechanism of the individual steps. It was found that step A → B has the shape of an nth-order model, step B → C mainly follows the diffusion model, the mechanism of step D → E transfers from a random scission kinetics model to an nth-order model with an increasing amount of CEL, and step E → F obeys the chain scission mechanism.

Thermal Degradation Analysis of Mamoncillo (<i>Melicoccus bijugatus</i>) Waste: Thermal Behaviors, Kinetics, and Thermodynamics

This research studied the thermal conversion characteristics, kinetics, and thermodynamics of mamoncillo peels and seeds using non-isothermal thermogravimetric analysis. Kinetic analysis was performed using the Kissinger-Akahira-Sunose, Flynn-Wall-Ozawa, Starink, and Friedman methods. The reaction kinetic models were obtained by means of the master-plots method for 18 different empirical reaction models, calculating the enthalpy, Gibbs free energy, and entropy as thermodynamics parameters. It was found that the average activation energy for mamoncillo peels and seeds was 238,71 and 197,60 kJ/mol, respectively. The frequency factor was found to be between 109 and 1031 s-1 for mamoncillo peels and between 109 and 1034 s-1 for mamoncillo seeds. The average values of DH and DG were also found to be 233,83 and 192,81 kJ/mol and 164,84 and 162,10 kJ/mol for mamoncillo peels and seeds, respectively. The reaction kinetic models regarding the thermal decomposition of mamoncillo peels were found to be described by the contracting cylinder (R2) and third-order (F3) models, while those for mamoncillo seeds can be described by the second-order (F2) and contracting sphere (R3) models. It was concluded that the pyrolysis process of mamoncillo waste can be described by a complex reaction mechanism, and that these wastes have thermal properties with the potential to produce bioenergy.

Co-combustion characteristics and reaction mechanism of coal slime and sewage sludge using a novel multilateral double volumetric parallel model and dendrite neural network

The co-combustion of coal slime (CS) and sewage sludge (SS) presents an effective method for significantly reducing solid waste on large-scale. This study conducted experimental research to investigate the combustion and co-combustion characteristics of CS and SS, focusing on exploring the synergistic effects and mechanisms during co-combustion processes. Novel multilateral double parallel models (Multi-DPM) were proposed to analyze the contributions of volatile and char components in CS/SS mixtures across different ratios during co-combustion. The effects of temperature, mixing ratio, and heating rate on the co-combustion process were evaluated using a new novel dendrite neural network (DD-NN) model. The results revealed varyied degrees of interaction between CS and SS during co-combustion. Kinetic and thermodynamic analyses revealed that the most significant enhancement in the CS/SS mixing ratio of 6:4. Both the double parallel volumetric model (DPVM) and the newly proposed multilateral double parallel volumetric models (Multi-DPVM) demonstrated the best fit with experimental conversion and proved their suitability for analyzing the co-combustion process of CS and SS. These models were further employed to predict the combustion kinetic parameters and conversion profiles of total volatiles and total char of single and mixed materials, as well as the volatiles and char of the individual CS and SS materials within the mixture. The obtained conversion data and activation energy values from the DPVM and Multi-DPVM were used to assess the best fit reaction mechanism using the master-plots method. This validation underscored the reliability of the DPVM and Multi-DPVM based on integral fitting model solution. Moreover, the application of the new DD-NN model demonstrated good predictive performance for the co-combustion process of CS and SS, identifying key transfer functions influencing the co-combustion process. Overall, this study provides valuable insights into comprehensively understanding the co-combustion mechanism of CS and SS, providing crucial information for industrial product design.

Kinetic study of sesame stalk pyrolysis by thermogravimetric analysis

Sesame stalk is a promising agricultural residue for generating renewable bioenergy, but still remains undeveloped on account of the lack of reliable pyrolysis kinetic information. The novelty of present work lies in that it gives the first thorough examination of kinetic and thermodynamic parameters for pyrolysis of sesame stalk. Non-isothermal pyrolysis experiments in N2 via thermogravimetric analysis were conducted at 5–20 K/min with temperatures programmed from 350 to 900 K. Experimental results indicate that pyrolysis of sesame stalk seems to occur in multi-stage reactions, model-free kinetic analysis methods, including differential Friedman, integral Kissinger-Akahira-Sunose, Flynn-Wall-Ozawa and Vyazovkin-Dollimore methods, are isoconversionally attempted to perform kinetic analysis of two-stage sesame stalk pyrolysis, respectively resulting in the mean activation energy of 136, 125, 128 and 125 kJ/mol for stage I and 140, 146, 150 and 146 kJ/mol for stage II. The master-plots method and differential composite method are integrated for determining pyrolysis mechanism, and the Ginstling−Brounshtein model is found to be the most appropriate and verified very well by experimental results. The averaged pre-exponential factors for two stages are determined to be 2.80 × 108 and 1.04 × 109 min−1, respectively. Besides, thermodynamic parameters in terms of ΔH, ΔG and ΔS are also evaluated for the whole pyrolysis process. The findings acquired from this study suggest sesame stalk is a promising biomass for sustainable bioenergy generation and kinetic and thermodynamic information is of significance for advancing the design of a sesame stalk pyrolysis reactor.

Unlocking the potential of pequi (Caryocar brasiliense) residues for bioenergy and renewable chemicals: Multicomponent kinetic modeling, thermodynamic parameter estimation, and characterization of volatile products through TGA and Py-GC/MS experiments

The first study in the literature on the pyrolysis of pequi (Caryocar brasiliense) residues, focusing on the kinetic triplet, thermodynamic parameters, and characterization of volatile products utilizing TGA and Py−GC/MS techniques, is presented in this paper. Slow pyrolysis experiments were conducted on a thermogravimetric scale in a controlled atmosphere of pure nitrogen, with five distinct heating rates (5, 10, 20, 30 and 40 ºC min−1). The pyrolysis progress profiles were fitted using the Asym2Sig function to deconvolute the devolatilization rates of individual biomass pseudo-components, including extractives, hemicellulose, cellulose, and lignin. The average activation energies for pequi peel pyrolysis, as determined by the isoconversional methods of Friedman, Flynn−Wall−Ozawa, Kissinger−Akahira−Sunose and Starink, were higher (114.30 −319.13 kJ mol−1) than those estimated for pequi seeds (88.05 −168.39 kJ mol−1). The pre-exponential factors, obtained through the kinetic compensation effect method, exhibited a range of values between 3.6 × 1011 and 2.4 × 1030 min−1 for pequi peel and between 1.2 × 107 and 9.4 × 108 min−1 for pequi seeds. Utilizing the master-plots method revealed the involvement of F-type, A-type, and D-type reaction models in the pyrolysis of pequi residues. A slight difference between the Ea and ΔH values, less than 5 kJ mol−1, indicates the facile formation of reaction products during pyrolysis. The main organic volatile products obtained from the fast pyrolysis of pequi peel, as revealed by Py−GC/MS analysis, include furans, ketones, aldehydes, and ethers, constituting up to 52% of the total yield of the condensable fraction at 550 °C. Aliphatic hydrocarbons are the major organic volatile products derived from the fast pyrolysis of pequi seeds, accounting for approximately 74% of the total condensable fraction yield at 650 °C. This study provides new insights into the valorization of residues resulting from pequi fruit processing. As a result, a novel pathway for bioenergy and biobased chemical production via pyrolysis is established, aligning with the circular economy principle and capable of promoting energy matrix diversification.

Pyrolysis of cashew nutshell residues for bioenergy and renewable chemicals: Kinetics, thermodynamics, and volatile products

The present study's motivation and novelty are related to the potential of raw (RCNS) and pressed (PCNS) cashew nutshell residues for producing bioenergy and renewable chemicals through their physicochemical characterization and pyrolysis processing (multicomponent kinetic analysis, thermodynamic study, and volatile product analysis). A thermogravimetric analyzer and an analytical pyrolyzer coupled with gas chromatographymass spectrometry (Py–GC/MS) were used to perform the pyrolysis reactions. The pyrolysis behavior of RCNS and PCNS was accurately modeled with the help of the Asym2sig deconvolution function through five and four parallel devolatilization events, respectively. The average activation energies for the pyrolysis of RCNS and PCNS fell in the ranges of 63.8 − 249.3 and 91.1 − 167.4 kJ mol−1, respectively, as determined by four isoconversional methods (Friedman, Flynn–Wall–Ozawa, Kissinger–Akahira–Sunose, and Starink). Pre-exponential factors ranging from 4.2 × 108 to 6.9 × 1016 min−1 (RCNS) and 4.8 × 108 to 3.2 × 1011 min−1 (PCNS) were estimated from the kinetic compensation effect. The master plots method evidenced that the most likely reaction models involved in the pyrolysis pertain to the nucleation-growth and n-order reaction mechanisms. Based on the multiple kinetic triplets acquired, the verification step of the summative rate expressions indicated excellent agreement between the simulated behavior and the experimental data, with a minimum quality of fit of 93.1%. The pyrolysis route can valorize both cashew nutshell residues to obtain renewable chemicals promoting the circular economy, as verified by Py-GC/MS analysis. Aliphatic hydrocarbons were the dominant components of the condensable volatile products at 650 °C, while reaction temperatures of 450 and 550 °C favored the production of oxygenated compounds. Due to the low potential energy barrier, the thermodynamic study attests to the viability of converting the studied residues into valuable products. The present results play an essential role in the utility of both cashew nutshell residues as inexpensive feedstocks for pyrolysis, possibly leading to bioenergy and biobased chemicals, which fall under the principle of valorization of lignocellulosic residues.

Pyrolysis kinetics and thermodynamic behavior of pseudo components of raw and torrefied maple wood

ABSTRACT In this work, pyrolysis kinetics and thermodynamic behavior of pseudo components (PCs) of raw and torrefied maple wood (MW) were studied. The MW torrefaction experiments were conducted at 240°C and the pyrolysis process was performed under three distinct heating rates. Through the deconvolution procedure, three PCs, i.e. pseudo-hemicellulose (PC-HC), pseudo-cellulose (PC-CL), and pseudo-lignin (PC-LG), were identified. The activation energy (E α ) of PCs were evaluated using the Starink method, and the pyrolysis reaction mechanisms were analyzed using the Criado’s master plot method. Furthermore, three thermodynamic parameters were also calculated and discussed. Results showed that after torrefaction, the PC-HC content dropped from 47.30% to 7.90%, while the PC-CL and PC-LG contents increased from 33.67% to 55.72% and from 19.03% to 36.38%, respectively. The average E α of raw MW PC-HC, PC-CL and PC-LG were 114.56, 117.12 and 116.02 kJ/mol, respectively, whereas they were 92.86, 103.82 and 159.26 kJ/mol for torrefied PCs, respectively. The master plot results suggested that the pyrolysis of MW PCs involved different order-based models. In addition, the thermodynamic analysis revealed that the torrefied PC-HC required slightly less heat energy during pyrolysis. All these observations can be conducive to better understand the pyrolysis mechanisms of raw and torrefied MW PCs.

Insight into kinetics and thermodynamics of distillers’ dried grains with solubles (DDGS) combustion using an approach simultaneously determining frequency factor and reaction model

The Kissinger and master plots methods are commonly employed to estimate the frequency factor and reaction model, respectively. However, two methods cannot always provide accurate results, especially for solid-state reaction processes with varying kinetic parameters. A new approach for simultaneously determining the frequency factor and reaction model has been developed. The applicability of the new approach was verified through analyzing a theoretically simulated process. The suitability for combustion conversion of distillers’ dried grains with solubles (DDGS) was analyzed through physicochemical characterization and kinetic and thermodynamic investigation. The effective activation energies for DDGS combustion from the Friedman isoconversional method varied significantly from 129.5 to 206.3 kJ mol−1 in the conversion range 0.05–0.95. The frequency factor range and reaction model for DDGS combustion determined by the newly developed approach were 1.7 × 1011–4.2 × 1016 s−1 and f(α) = 5α1.277(1-0.582α)23.877[-ln(1-α)]−0.100, respectively. Thermodynamic analysis revealed that the changes in Gibbs free energy, enthalpy and entropy for DDGS combustion were in the range of 146.7–162.2 kJ mol−1, 125.3–200.4 kJ mol−1, and -42.5 – 57.0 J mol−1 K−1, respectively, which indicating DDGS combustion has a great potential for energy conversion.

Improving biomass fuel obtained from Brazil nut residues via torrefaction: A case of kinetic and thermodynamic study

The residues of Brazil nuts (Bertholletia excelsa) were evaluated, in their natural state and in torrefied form, for their energy potential after pyrolysis. Samples of shells (BNS) and husks (BNH) were torrefied at 220, 260 and 300 ºC for 30 and 60 min, and were characterized for their chemical and energetic composition. It was also determined which samples showed, simultaneously, the lowest hemicellulose content and the highest cellulose content after torrefaction via analysis of the decomposition profile at 10 ºC/min under pyrolysis. The evolution of gases such as H2O, CO2 and/or C3H8, and CH4 was observed by simulated pyrolysis on a microscale in a thermogravimetric analyzer coupled to a mass spectrometer (TGA-MS). In addition, the kinetics of the pyrolysis of untorrefied and torrefied samples were evaluated using the Flynn-Wall-Ozawa (FWO) and Vyazovkin (VYZ) models in order to obtain the activation energy, pre-exponential factor and thermodynamic parameters. The predominant reaction mechanism was determined by Criado Master-plot method. The mean value of the activation energies ranged from 132.24 to 134.95 kJ/mol for BNS, from 135.53 to 138.47 kJ/mol for ST263, from 149.10 to 150.96 kJ/mol for BNH and from 145.83 to 148.14 kJ/mol for HT263. It was found that D2 and D4 diffusion mechanisms are prevalent in the decomposition of untorrefied samples, while torrefied samples were better adjusted to the F1/A2/A3/A4 overlapping nucleation models. High pre-exponential factor values indicated the presence of multiple intermolecular collisional reactions. The thermodynamic parameters evaluated, as well as the variations in enthalpy, Gibbs free energy and entropy, indicated that the evaluated process is endothermic, though requires little energy. As a whole, in view of the optimized parameters and elevation of the thermal stability of the material, the results demonstrate good potential for the use of Brazil nut shells and husks torrefied at 260 ºC for 30 min as biochar. In addition, pyrolyzed Brazil nut residues also have great potential in the production of bio-oil and biogas, in view of the high content of volatile matter released during the decomposition of the hemicellulose and lignin.

Machine learning approach for ion imprinted (IIP) and non-imprinted (NIP) polymer discrimination based on pyrolysis kinetic data

The improper disposal of effluents containing toxic elements, such as nickel and mercury, can result in the gradual deterioration of surface water quality, impacting aquatic ecosystems and human health. Ionically imprinted polymers (IIPs) are promising candidates for remediating toxic areas due to their high removal rates and selectivity. In this study, multifunctional IIPs were developed using Ni2+ and Hg2+ as template ions and dithizone, methacrylic acid, and ethylene glycol dimethacrylate as complexing agent, monomer, and cross-linking agent, respectively, to remove Ni (II) and Hg (II) from effluents. The thermal decomposition behavior and degradation mechanism of ion imprinted polymers were investigated to address the issue of limited lifespan. The kinetic study revealed that the samples showed significant thermal stability, and the IIP-Duo sample exhibited higher activation energy compared to the non-imprinted polymer (NIP) and the mono-imprinted polymer (IIP), indicating that double impression alters the structure of the polymer and consequently its thermal degradation. Three machine learning models were applied to classify the samples according to imprinting, successfully predicting 95% or more of the classes correctly without overfitting or overmodelling. The master plot method showed that imprinting did not affect the thermal decomposition pathway, with the IIP, IIP-Duo, and NIP samples presenting the same mechanism geometrical contraction model (R3) at a conversion rate between 0.4 and 0.9. These findings suggest that multifunctional IIPs are promising materials for remediating areas impacted by toxic elements.

Non-isothermal thermal decomposition behavior and reaction kinetics of acrylonitrile butadiene styrene (ABS)

Environmental concerns associated with the rapid rising plastic consumption have led to the search for better waste utilization and management. Pyrolysis has emerged as an ideal and promising technique for energy extraction from plastic waste. The aim of this work is to explore the waste plastic pyrolysis behavior under non-isothermal heating conditions. The decomposition characteristics, reaction mechanism, kinetics and thermodynamics of a typical widely used thermosetting plastic, acrylonitrile butadiene styrene (ABS), were studied via coupled thermogravimetry, Fourier transform infrared spectrometry and gas chromatography-mass spectrometry analysis (TG-FTIR-GC/MS). Kinetic analysis showed the average Eα values are estimated to be 187.02, 188.55, 187.04 and 185.67 kJ/mol via advanced Vyazovkin, Flynn-Wall-Ozawa (FWO), Tang and Starink model-free method, respectively. Model-fitting CR and master-plots method indicated that f(α)=(1-α)n is the most probable reaction mechanism. The equation of kinetic compensation effect was further developed as lnA = −3.1955 + 0.1736 Eα. Based on these initial inferences, a new reaction scheme coupled with Particle Swarm Optimization (PSO) was put forward for modeling ABS pyrolysis. The optimized values of E, A and n are 198.07 kJ/mol, 7.61 × 1012 s−1 and 1.56, respectively. The predicted results showed that the experimental data can be well characterized by the optimized parameters from PSO, validating the effectiveness and accuracy of the inverse modeling procedure. Moreover, it is found that the volatile products are mainly composed of aromatic compounds, ketones, amines, esters, nitrile compounds, alkenes and amines. Based on the FT-IR and GC-MS results, the possible chemical reactions for ABS pyrolysis from molecular structure were proposed. Finally, thermodynamic analysis was carried out, the calculated values of enthalpy ΔH, Gibb's free energy ΔG and entropy ΔS indicated that non-spontaneous reactions with low favorability exists during ABS decomposition, the process is complex therefore extra energy is needed to promote the reaction. The obtained results should offer as an important reference for future disposal and thermochemical management of such polymer waste.

Co-pyrolysis of sewage sludge and waste tobacco stem: Gas products analysis, pyrolysis kinetics, artificial neural network modeling, and synergistic effects

This research comprehensively investigates the co-pyrolysis of sewage sludge (SS) and waste tobacco stem (WTS). Various SS and WTS ratios (1:0, 0.75:0.25, 0.50:0.50, 0.25:0.75, and 0:1) were tested over a range of heating rates (30 °C to 800 °C). Apparent activation energies were calculated using model-free methods, and the co-pyrolysis mechanism was described with the master plot method. Results suggest that SS and WTS co-pyrolysis follows power-law models (P3, P4). Among blends, S75W25 exhibited optimal synergy, with the lowest activation energy required for the pyrolysis reactions and inhibits CO2 emissions. S75W25′s pyrolysis gas primarily contained acids (e.g., ethylxanthogenacetic acid, acetic acid), hydrocarbons (e.g., supraene, cyclopropyl carbinol), and other compounds (e.g., CO2, pyrazine, pyridine, indole). ANN was utilized to forecast the temperature-mass loss relationships in co-pyrolysis, with the optimal model being ANN21, yielding a high correlation coefficient (R2 = 0.99999). This study offers guidance for the efficient utilization of waste SS and WTS.

Pyrolysis Characteristics and Determination of Kinetic and Thermodynamic Parameters of Raw and Torrefied Chinese Fir.

Torrefaction influences the structural and physicochemical properties of biomass, thus further altering its thermal degradation behavior. In this study, the pyrolysis characteristics, reaction kinetics, and thermodynamic parameters of raw and torrefied Chinese fir (CF) were investigated. The torrefaction was conducted at 220 °C (mild) and 280 °C (severe), the pyrolysis was performed from ambient temperature to 600 °C, and four different heating rates (i.e., 5, 15, 25, and 35 °C/min) were adopted. The activation energy for pyrolysis was estimated by adopting three isoconversional methods. The master-plot method was employed to analyze the reaction mechanism. Furthermore, thermodynamic parameters, i.e., the enthalpy change (ΔH), Gibbs free energy change (ΔG), and entropy change (ΔS), were calculated. The average activation energy increased with the torrefaction temperature, whose values estimated by using different methods ranged from 88.57 to 97.70, from 121.04 to 126.35, and from 167.51 to 179.74 kJ/mol for raw, mildly, and severely torrefied CF samples, respectively. A compensation effect between the activation energy and pre-exponential factor was observed for all samples. The degradation process was characterized as endothermic, involving the formation of activated complexes and requiring extra energy for torrefied samples.