A kinetic model for halogenation of the zinc content in franklinite

Altarawneh, Mohammednoor; Ahmed, Oday H.; Al-Harahsheh, Mohammad; Jiang, Zhong Tao; Dlugogorski, Bogdan Z.

doi:10.1016/j.apsusc.2021.150105

Cited by 15 publications

(10 citation statements)

References 64 publications

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“…20 The seminal work by Al-Harahsheh and co-workers provided thermo-kinetic parameters that underpin the interaction of BFRs (mainly TBBA) with a wide array of pure and mixture of transition metal oxides. 21,22 Though calculations of kinetic and thermodynamics parameters that reflect the copyrolysis process are important such as that by Altarawneh et al, 16 application of ML methods will enable us to eliminate the need for physical experimentation tools such as TGA, FTIR, and XRF instruments and directly predict the respective data for different conditions. This has a 2fold advantage of minimizing human error involved in sample preparation and performing the experiments as well as reducing the manpower due to the potential for online monitoring and automation.…”

Section: ■ Introductionmentioning

confidence: 99%

“…Over the years, thermal analysis methods such as thermogravimetric analysis (TGA) have provided critical insights into the mechanisms that govern the interaction between the BFRs and the copyrolytic metal oxides. , The most important part of interpreting the data from the TGA for the TBBA:Ca(OH) 2 combined samples is linking the mass loss regions observed with corresponding possible chemical events, which was achieved by intercoupling the TGA instrument with gas analysis (py-GCMS/FTIR). In this way, three regions of extravagant decomposition were identified in our work, and these were ascribed to decomposition of long-chained TBBA units with no release of HBr, dehydration of the precursor Ca(OH) 2 with CaCO 3 formation, and finally, the decarbonization of CaCO 3 to form CaO.…”

Section: Introductionmentioning

confidence: 99%

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Prediction of Thermogravimetric Data in Bromine Captured from Brominated Flame Retardants (BFRs) in e-Waste Treatment Using Machine Learning Approaches

Ali

Sivaramakrishnan

Kuttiyathil

et al. 2023

J. Chem. Inf. Model.

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The principal objective in the treatment of e-waste is to capture the bromine released from the brominated flame retardants (BFRs) added to the polymeric constituents of printed circuits boards (PCBs) and to produce pure bromine-free hydrocarbons. Metal oxides such as calcium hydroxide (Ca(OH)2) have been shown to exhibit high debromination capacity when added to BFRs in e-waste and capturing the released HBr. Tetrabromobisphenol A (TBBA) is the most commonly utilized model compound as a representative for BFRs. Our coauthors had previously studied the pyrolytic and oxidative decomposition of the TBBA:Ca(OH)2 mixture at four different heating rates, 5, 10, 15, and 20 °C/min, using a thermogravimetric (TGA) analyzer and reported the mass loss data between room temperature and 800 °C. However, in the current work, we applied different machine learning (ML) and chemometric techniques involving regression models to predict the TGA data at different heating rates. The motivation of this work was to reproduce the TGA data with high accuracy in order to eliminate the physical need of the instrument itself, so that this could save significant experimental time involving sample preparation and subsequently minimizing human errors. The novelty of our work lies in the application of ML techniques to predict the TGA data from e-waste pyrolysis since this has not been conducted previously. The significance of our work lies in the fact that e-waste is ever increasing, and predicting the mass loss curves faster will enable better compositional analysis of the e-waste samples in the industry. Three ML models were employed in our work, namely Linear, random forest (RF), and support vector regression (SVR), out of which the RF method exhibited the highest coefficient of determination (R 2) of 0.999 and least error of prediction as estimated by the root mean squared error (RMSEP) at all 4 heating rates for both pyrolysis and oxidation conditions. An 80:20 split was used for calibration and validation data sets. Furthermore, for showing versatility and robustness of the best-predicting RF model, it was also trained using all the data points in the lower heating rates of 5 and 10 °C/min and predicted on all the data points for the higher heating rates of 15 and 20 °C/min to again obtain a high R 2 of 0.999. The excellent performance of the RF model showed that ML techniques can be used to eliminate the physical use of TGA equipment, thus saving experimental time and potential human errors, and can further be applied in other real-time e-waste recycling scenarios.

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Section: ■ Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Prediction of Thermogravimetric Data in Bromine Captured from Brominated Flame Retardants (BFRs) in e-Waste Treatment Using Machine Learning Approaches

Ali

Sivaramakrishnan

Kuttiyathil

et al. 2023

J. Chem. Inf. Model.

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“…79 In the reaction to generate HBr, zinc bromide is formed by heterologous fission of the halidehydrogen bond on the highly hybridized metal-oxide bond. 80,81 The last but most prevalent form, the fixation of HBr by metal oxides, is similar to the bromination of antimony trioxide (Sb 2 O 3 ) to antimony bromide (SbBr 3 ). 82 As shown in Figure 2 pathway 1, the organic bromides are depolymerized into monomers and dehalogenation at high temperatures or on metal surfaces to produce hydrogen bromide, which then becomes a metal bromide when chemisorbed with the metal.…”

Section: 2mentioning

confidence: 99%

Debromination with Bromine Recovery from Pyrolysis of Waste Printed Circuit Boards Offers Economic and Environmental Benefits

Liu

Zhan

2023

Environ. Sci. Technol.

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Bromine is an important resource that is widely used in medical, automotive, and electronic industries. Waste electronic products containing brominated flame retardants can cause serious secondary pollution, which is why catalytic cracking, adsorption, fixation, separation, and purification have gained significant attention. However, the bromine resources have not been effectively reutilized. The application of advanced pyrolysis technology could help solve this problem via converting bromine pollution into bromine resources. Coupled debromination and bromide reutilization during pyrolysis is an important field of research in the future. This prospective paper presents new insights in terms of the reorganization of different elements and adjustment of bromine phase transition. Furthermore, we proposed some research directions for efficient and environmentally friendly debromination and reutilization of bromine: 1) precise synergistic pyrolysis should be further explored for efficient debromination, such as using persistent free radicals in biomass, polymer hydrogen supply, and metal catalysis, 2) rematching of Br elements and nonmetal elements (C/H/O) will be a promising direction for synthesizing functionalized adsorption materials, 3) oriented control of the bromide migration path should be further studied to obtain different forms of bromine resources, and 4) advanced pyrolysis equipment should be well developed.

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“…Poor debromination performance by ZnO and CuO was ascribed to their reduction into metallic forms rather than undergoing halogenation reactions. 10 Density functional theory (DFT) calculations and thermogravimetric analysis (TGA) experiments provided important mechanistic insight into steps that govern the interaction between the metal oxides additives and the BFRs 18,19 Based on DFT computations, conversion of metal oxides into their bromides and oxybromides ensue via three steps mechanisms, dissociative adsorption of HBr (or bromo-hydrocarbons), intramolecular hydrogen transfer forming surface hydroxyl groups, and desorption of water. As in the case of Fe 2 O 3 , endothermic mass loss step at elevated temperature was ascribed to evaporation of FeBr 2 .…”

Section: Introductionmentioning

confidence: 99%

Degradation of tetrabromobisphenol A (TBBA) with calcium hydroxide: a thermo-kinetic analysis

et al. 2023

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A kinetic model for halogenation of the zinc content in franklinite

Cited by 15 publications

References 64 publications

Prediction of Thermogravimetric Data in Bromine Captured from Brominated Flame Retardants (BFRs) in e-Waste Treatment Using Machine Learning Approaches

Prediction of Thermogravimetric Data in Bromine Captured from Brominated Flame Retardants (BFRs) in e-Waste Treatment Using Machine Learning Approaches

Debromination with Bromine Recovery from Pyrolysis of Waste Printed Circuit Boards Offers Economic and Environmental Benefits

Degradation of tetrabromobisphenol A (TBBA) with calcium hydroxide: a thermo-kinetic analysis

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