Study of catalytic pyrolysis mechanism of guaiacol using seaweed-derived carbon catalyst: Based on density functional theory and machine learning

Machine Learning


To address the dual pressures of increasing global energy demand and environmental pollution, biomass has emerged as one of the most abundant and promising renewable energy sources.has attracted a lot of attention in recent years [1], [2], [3], [4], [5]. Estimated global biomass production is 1011 tons per year, and lignocellulosic biomass accounts for the majority of this figure. [6]. Currently, annual global lignin production exceeds 50 million tons, and this figure is expected to increase to 220 million tons by 2030. [7]. However, the current uses of lignin are limited. More than 90% of lignin is burned, discarded, or directly emitted, leading to environmental pollution and significant waste of lignin resources. [8], [9], [10]. Lignin is mainly composed of a heterobranched network structure formed by the attachment of phenylpropanoid groups via ether or CC bonds, and is composed of three main units: p-Hydroxyphenylpropane, guaiacyl, and syringyl [11].

More than 50% of the molecular structure of lignin is a guaiacol-like structure derived from guaiacyl and syringyl units. [12], [13]. Therefore, guaiacol is usually chosen as a model compound to study lignin transformation. [14], [15]. Nowakowska et al. [16] The main products of guaiacol thermal decomposition were observed to be catechol, o-hydroxybenzaldehyde, methyl catechol, and light products such as methane, carbon monoxide, ethylene, and hydrogen. The transformation mechanism of guaiacol is proposed to involve unimolecular OC bond cleavage and free radical mechanisms. A growing number of researchers have proposed that the pyrolysis process of guaiacol is primarily dominated by free radicals. [17], [18], [19], [20]. Lee et al. [21] We used free radical detection technology (electron paramagnetic resonance, EPR) to study the thermal decomposition process of guaiacol and found that the thermal decomposition reaction of guaiacol is mainly a free radical reaction.6HFour(OH)O* radical, 5-C6HFour(OCH3)O* radical, methyl radical, hydrogen radical) undergo rearrangement and reaction continuously. This can be further analyzed to obtain the microscopic mechanism of guaiacol thermal decomposition through quantum chemical calculations. [22].Ryu [23] Cleavage of O-CH was suggested.3 We proposed that conjugation is an important pathway for catechol production and that H radicals and CH combine.3 Radicals are the key to the formation of phenol and cresol. Therefore, in the current research of lignin pyrolysis process and mechanism, guaiacol is a very important model compound and has great guiding importance for lignin pyrolysis research.

In recent years, carbon-based metal-free catalysts produced by thermochemical conversion of biomass such as seaweed have been attracting attention in the industrial and agricultural fields. [24], [25], [26], [27], [28]. Currently, various types of carbon source precursors have been applied to prepare biochar as catalysts in the field of biomass pyrolysis, which also proves their catalytic effectiveness. Wang et al.[29] demonstrated the use of low-cost corn stalk biochar as a catalyst to recover discarded disposable masks. This indicates an increase in aromatic content compared to the uncatalyzed reaction. Arantes et al.[30] used coconut peel to prepare activated biochar as a low-cost catalyst and studied its effect on the co-thermal decomposition of waste polystyrene and coconut peel. The results showed that the potassium element and oxygen-containing functional groups in the biochar effectively reduced oxygenated compounds, resulting in a high yield of aromatic compounds. The xylene content is high at 60% and the calorific value is 34.11 MJ/kg. Cao et al. We also prepared a series of low-cost algae-derived biochar catalysts for improving bio-oils, and the study yielded acid-free bio-oils with rich ester and sugar substances. [24]. On the other hand, there are few studies focusing on the structure of biochar catalysts to reveal the catalytic processes occurring on the biochar surface, which are beneficial for improving the catalytic performance to promote lignin catalytic conversion.

In this study, oxygen- and nitrogen-containing biochar models were established to investigate the possible catalytic reaction pathways of guaiacol. The kinetic and thermodynamic parameters of each reaction pathway were calculated by DFT. Next, we elucidated the catalytic mechanism of algal biochar through the surface electrostatic potential, molecular orbital, and electronic information of the algal biochar catalyst. Potential descriptors representing the reactivity of algal biochar catalysts were screened. After screening the relevant catalyst descriptors, the dataset is acquired for further machine learning to establish an accurate model to predict the activity of the biochar model. This approach provides a new perspective in understanding the catalytic mechanism at the molecular level and contributes to the field of biomass pyrolysis and catalyst development.



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