Experimental and Theoretical Study of Oxolan-3-one Thermal Decomposition

Legg, Heather N; Narkin, Kathryn; McCunn, Laura R.; Parish, Carol A.; Song, Xinli

doi:10.1021/acs.jpca.2c03254

Cited by 5 publications

(1 citation statement)

References 45 publications

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“…Finally, with the increasing amount of high-level quantum chemical data for OMEs and OME-derived species becoming available in the literature, ,,,,− it would be interesting to compare the estimation methods developed in this work with novel methods, such as machine learning. The performance of kinetic group additivity, which can be seen as a simplified version of machine learning, indicates the potential of machine learning tools such as deep learning.…”

Section: Results and Discussionmentioning

confidence: 99%

Unimolecular Decomposition of 1,3-Dioxetane and 1,3,5-Trioxane Derivatives: Fast and Accurate Estimation of Kinetic Parameters

Dossche,

De Ras,

Thybaut

et al. 2024

Energy Fuels

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Oxymethylene ethers (OMEs) are a high-potential novel type of e-fuel, which could play an important role in the transition toward a sustainable transportation sector. During the low-temperature oxidation of these OMEs, various cyclic ethers, such as 1,3-dioxetane and 1,3,5-trioxane derivatives, can be formed. However, the current lack of accurate reaction rate coefficients for the unimolecular decomposition of these cyclic ethers has been highlighted as an important obstacle in the development of detailed kinetic models for the low-temperature oxidation of larger OME molecules. In this light, a database with quantum chemical results has been constructed consisting of 34 4-membered ring and 34 6-membered ring cyclic ethers representing important functional groups present during the low-temperature oxidation of OMEs. This database has been used for the development of three estimation methods for the reaction rate coefficients, i.e., rate rules, the Evans−Polanyi relationship, and kinetic group additivity. Balancing performance and complexity, these three methods are currently still the most commonly used estimation methods by automatic kinetic model generation tools. Based upon an assessment of the results, kinetic group additivity was found to be the most accurate method, reaching kinetic accuracy, i.e., a maximum deviation of 1 order of magnitude, for all but one of the 4-membered rings and all but four of the 6-membered ring cyclic ethers. Interactions between the terminal end of a substituent and the ring in combination with the relative stability of different isomers have been proposed to be the main reason for the significant variations between the reaction rate coefficients of the various species. The kinetic parameters can be easily used for the development of detailed kinetic models for larger OMEs based on first principles.

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Section: Results and Discussionmentioning

confidence: 99%

Unimolecular Decomposition of 1,3-Dioxetane and 1,3,5-Trioxane Derivatives: Fast and Accurate Estimation of Kinetic Parameters

Dossche,

De Ras,

Thybaut

et al. 2024

Energy Fuels

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Evaluating the thermal stability of chemicals and systems: A review

Andriani,

Pio,

Salzano

et al. 2024

Can J Chem Eng

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In the realm of chemical processing, particularly at the industrial scale, safety is of utmost importance. A predominant factor causing accidents within the chemical industry is runaway phenomena, primarily initiated by uncontrolled exothermic reactions. This review critically examines the often‐overlooked decomposition mechanisms as a significant contributor to thermal energy release, necessitating a comprehensive revision and understanding of both experimental and theoretical strategies for assessing thermal degradation. Key to this discourse is the explication of calorimetry as the principal experimental technique, alongside ab initio quantum chemistry simulations as a robust theoretical framework for quantifying the most relevant properties. However, more than mere cognisance of these methodologies is required for a meticulous thermal stability assessment. The review emphasizes identifying and quantifying fundamental parameters through experimental and theoretical investigations. Only upon acquiring these parameters, including kinetic, thermodynamic, onset, and peak characteristics of the exothermic decomposition reactions, can one effectively mitigate risks and hazards in designing and optimizing chemical processes and apparatus. Furthermore, this review delineates qualitative and quantitative methodologies for hazard assessment, proffering strategies for estimating safe operational conditions and sizing relief devices. The paper culminates in exploring future trajectories in thermal stability assessments, focusing on emerging applications in lithium‐ion batteries, electrolyzers, electrified reactors, ionic liquids, artificial intelligence and machine learning approaches. Thus, the paper underlines the evolving landscape of thermal risk management in contemporary and future chemical industries.

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