Pyrolytic kinetics, reaction mechanisms and products of waste tea via TG-FTIR and Py-GC/MS

Cai, Haiming; Liu, Jingyong; Xie, Wei; Kuo, Jia‐Hong; Büyükada, Musa; Evrendilek, Fatih

doi:10.1016/j.enconman.2019.01.031

Cited by 204 publications

(68 citation statements)

References 55 publications

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“…In the production of bio-oil from biomass blended with coal, the pyrolysis kinetics of CS, TCS and their blends are important parameters in the effective and efficient design of co-pyrolysers and co-gasifiers. Cai et al (2019) and Abd-Elghany et al (2017) suggested that the thermal decompositions at the start and end of each stage were not stable. As a consequence, the TG data for these ranges have not been considered when calculating the kinetics of co-pyrolysis.…”

Section: Resultsmentioning

confidence: 99%

Thermogravimetric studies on co-pyrolysis of raw/torrefied biomass and coal blends

et al. 2020

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The pyrolysis and co-pyrolysis behaviours of cotton stalk (CS), torrefied cotton stalk (TCS) and mined coal, as single fuels, and their blends, have been examined through thermogravimetric analysis. Biomass has been torrefied at 250°C for 45 min to enhance physicochemical properties, and then mixed with mined coal for co-pyrolysis. Thermal degradation of CS and TCS is characterized by a reaction. However, this is not the case for mined coal, which shows a single-stage reaction. The thermal degradation of all blends was done in three stages: dehydration; biomass and small mined coal; and lignin or mined coal. A similar trend emerged for mass loss of individual fuels, which depended mainly on their ratios in the blend. The kinetics of pyrolysis and co-pyrolysis of all fuels were calculated at 20°Cmin−1 heating rate using the Coats−Redfern model-fitting method.

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Section: Resultsmentioning

confidence: 99%

Thermogravimetric studies on co-pyrolysis of raw/torrefied biomass and coal blends

et al. 2020

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“…From TG data, the kinetic and thermodynamic parameters and the reaction mechanism models can be derived combining the model-free and model-fitting methods ( Cai et al, 2019 ; Qiao et al, 2019 ; Chen et al, 2015 ; Song et al, 2020 ). For example, the model-free methods of Kissinger-Akahira-Sunose (KAS) and Flynn-Wall-Ozawa (FWO) and the model-fitting method of the integral master-plots were combined to elucidate the three phases of the waste tea degradation mechanism using the best-fit D 3 , F 2 , and F 2.5 models, respectively ( Cai et al, 2019 ). TG-FTIR and Py-GC/MS investigations should be coupled to accurately distinguish the evolved gaseous products, their functional groups, and molecular structures ( Lin et al, 2017 ; Xu et al, 2018a ; Ma et al, 2019 ).…”

Section: Introductionmentioning

confidence: 99%

Pyrolysis dynamics of two medical plastic wastes: Drivers, behaviors, evolved gases, reaction mechanisms, and pathways

Ding

Huashan²,

Liu

et al. 2021

Journal of Hazardous Materials

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110

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“…The kinetic reaction can be represented by the following equation:

\frac{dα}{dt} = k ((), T) f ((), α),

where α, f(α), k(T), T and t are conversion degree, reaction mechanism function, reaction rate constant, absolute temperature and reaction time respectively. The α is defined by Equation ) below 41 :

α = \frac{m_{0} - m_{t}}{m_{0} - m_{f}},

where m o , m t and m f represent initial weight, weight at time t and final weight, respectively. Equation ) shown below is the Arrhenius equation:

k ((), T) = A \exp ((), - \frac{Ea}{RT}),

where A refers to pre‐exponential factor, R is universal gas constant (8.314 J mol −1 K −1 ), and Ea is activation energy.…”

Section: Methodsmentioning

confidence: 99%

“…The master‐plots method was used to accurately find the kinetic mechanism of co‐combustion 36,41,44 . The integral form in Equation ) was first simplified to:

g ((), α) = \frac{AEa}{βR} P ((), u),

where P ( u ) is the integral of temperature and u = Ea/RT .…”

Section: Methodsmentioning

confidence: 99%

Investigation of sewage sludge and peanut shells co‐combustion using thermogravimetric analysis and artificial neural network

Wang

Jiang

et al. 2020

Int J Energy Res

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Summary To solve the problems of energy shortage and waste accumulation, the method of co‐combustion of sewage sludge (SS) and peanut shells (PS) was proposed. SS‐PS co‐combustion characteristics in air were investigated using artificial neural networks (ANN) and thermogravimetric analyses (TGA). The proportion of PS in the mixture was 10%‐50%. The temperature range of PS combustion (160‐560°C) is lower than that of PS combustion (170‐600°C). Activation energy was estimated from two non‐isothermal kinetic analysis methods: Kissinger‐Akahira‐Sunose (KAS) and Flynn‐Wall‐Ozawa (FWO). The kinetic mechanism of the combustion process was determined by using the master‐plots method. Multiple ANN models were established to predict TG data of SS‐PS co‐combustion. The best prediction model (ANN21) was obtained. The results showed a good overlap between the predicted and experimental TG data. The ANN model and the master‐plots method are the main innovations of this study. This study can promote the utilization and reduction of solid waste, and give guidance for the large‐scale application of SS‐PS co‐combustion.

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Pyrolytic kinetics, reaction mechanisms and products of waste tea via TG-FTIR and Py-GC/MS

Cited by 204 publications

References 55 publications

Thermogravimetric studies on co-pyrolysis of raw/torrefied biomass and coal blends

Thermogravimetric studies on co-pyrolysis of raw/torrefied biomass and coal blends

Pyrolysis dynamics of two medical plastic wastes: Drivers, behaviors, evolved gases, reaction mechanisms, and pathways

Investigation of sewage sludge and peanut shells co‐combustion using thermogravimetric analysis and artificial neural network

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