Recent Research Progress in Combustion Kinetics of Biomass-Derived Oxygenated Fuels

Xiao Liu; Chung K. Law; Bin Yang

doi:10.1016/j.eng.2025.10.012

Engineering ›› 2026, Vol. 59 ›› Issue (4) :60 -81. DOI: 10.1016/j.eng.2025.10.012

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Recent Research Progress in Combustion Kinetics of Biomass-Derived Oxygenated Fuels

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Abstract

Biofuels are promising alternatives to fossil fuels due to diminishing reserves and increasing environmental concerns. This review focuses on recent progress in understanding the combustion kinetics of oxygenated biofuels derived from biomass. The review begins with fundamental concepts and research methodologies in reaction kinetics, intended as a primer for engineering researchers. Subsequently, kinetic studies from the past decade on typical oxygenated biofuels are summarized, including alcohols, fatty acid methyl esters (FAMEs), ketones, ethers, and carbonates. Emphasis is placed on the influence of different oxygenated functionalities and their positions within the molecule on combustion characteristics and reaction pathways. Distinct reaction patterns for each class are highlighted. Alcohols exhibit a characteristic unimolecular dehydration reaction. FAME kinetics are similar to long-chain hydrocarbons, with unsaturation significantly impacting low-temperature oxidation. Ketone oxidation is influenced by the formation of resonance-stabilized radicals, while straight-chain ethers demonstrate a unique double negative temperature coefficient (NTC) behavior. Carbonates, relevant to lithium-ion battery safety, have gained research attention and can undergo a distinctive reaction pathway identified as CO₂ elimination reaction. To advance predictive kinetic models for biomass-derived oxygenated fuels, several targeted research directions are essential. First, there is a critical need to expand experimental datasets that capture the combustion behavior of diverse oxygenated compounds, particularly under low-temperature conditions. This must be coupled with enhanced combustion diagnostics capable of resolving key reaction intermediates characteristic of oxygenated fuel oxidation. Second, detailed quantum chemical calculations and theoretical explorations of potential energy surfaces are required to accurately determine reaction rate parameters for oxygen-involved pathways, which are often determinant in fuel decomposition and pollutant formation. Finally, progress in model predictability will depend on the adoption of advanced computational methods, including automated mechanism generation for complex oxygenated structures, systematic optimization frameworks leveraging experimental data, and the incorporation of physics-informed artificial intelligence approaches tailored to oxygenated fuel chemistries.

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Biofuel / Oxygenated fuels / Combustion kinetics / Gas-phase oxidation / Detailed kinetic models

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Xiao Liu, Chung K. Law, Bin Yang. Recent Research Progress in Combustion Kinetics of Biomass-Derived Oxygenated Fuels. Engineering, 2026, 59 (4) : 60-81 DOI:10.1016/j.eng.2025.10.012

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1. Introduction

Industrial progress has significantly enhanced production capabilities and the quality of life. Concurrently, issues pertaining to energy scarcity and climate change have progressively emerged as subjects of critical concern. The Energy Institute (EI) reports that fossil fuels, including oil, coal, and natural gas, remain the foundation of global primary energy consumption, making up 84% of the energy mix in 2023 [1]. Consequently, the world is facing an energy crisis due to the finite nature of these resources and the gradual exhaustion of energy reserves [2]. Additionally, the widespread use of fossil fuels has led to an increase in atmospheric CO₂ levels, contributing to global warming, the melting of glaciers, and rising sea levels [3]. Mitigating greenhouse gas emissions and addressing energy challenges are critical issues facing humanity.

In response to energy conservation and environmental protection, numerous nations have implemented regulations to curb fossil fuel usage and minimize pollutant emissions from vehicles [4], [5], [6], [7]. In addition to improvements in car engines and exhaust after-treatment technology to reduce emissions [8,9], scientists are actively working on developing clean and renewable energy sources to decrease the reliance on fossil fuels [10]. However, these sources all face the challenges of intermittent production and geographical dependence [11], necessitating the storage of energy in secondary energy carriers through processing to meet utilization demands [12]. In recent years, considerable interest has been focused on three types of secondary energy carriers: solar fuel [13], electric fuel (e-fuel) [14], and biomass fuel (biofuel) [15]. The production of biofuels and e-fuels is derived from carbon dioxide and emits an equivalent quantity of carbon dioxide upon combustion, thereby maintaining carbon neutrality throughout their life cycle. Relative to e-fuels, biofuels can be obtained from processing various feedstocks such as plant, algae, or animal waste, and thereby have the advantages of raw materials and costs [16]. Numerous nations have enacted laws endorsing biofuels to address potential future transportation demands [17]. The International Energy Agency (IEA) anticipates that by 2025, biofuels will account for approximately 5.4% of the energy needed for road transportation [18]. Besides, from an economic and energy security perspective, the integration of biofuels will decrease a country’s dependence on traditional petroleum imports from abroad and boost the domestic economy [16,19].

Biofuels have developed rapidly in the past few decades. Depending on raw materials and methodology, biofuels can be categorized into several classes designated as first, second, third, and fourth generation. The first generation of biofuels, such as biomethanol, bioethanol, and biodiesel, are produced using agricultural products. The process of fermenting crops to produce this generation has reached a considerable level of technical maturity [20]. However, it has been subject to scrutiny regarding the competition between biofuel feedstocks and foods [21], [22], [23]. Due to the limitation, research focus has been increasingly shifting towards second-generation biofuels that utilize forest, agricultural, and municipal waste as feedstocks, which are more cost-effective and readily accessible [24], [25], [26]. Regarding production methods, utilizing lignocellulose as an example, the primary approaches encompass biological and thermochemical processes [27]. The third-generation biofuels represent a fuel production technology based on algae, which are aquatic photosynthetic microorganisms that exhibit rapid growth in saline water, coastal seawater, municipal sewage, or land unsuitable for agricultural purposes and cultivation [28,29]. Biofuels produced in this way are highly carbon-neutral. According to Chisti [30], the process of cultivating 1 kg of microalgae can sequester up to 1.8 kg of carbon dioxide. A significant advantage of algae as biomass feedstocks over first- and second-generation biofuels is their rapid growth rate, as they can double their biomass in 2-5 d [28]. The most promising advanced biofuels are derived from fourth-generation sources, which utilize genetically modified microalgae, microbes, yeast, and cyanobacteria as feedstocks [16]. Currently, significant advances have been made in genetic editing techniques and metabolic engineering aimed at developing excellent microalgae with high photosynthetic efficiency, resistance to disease, and high lipid content [31], [32], [33], [34]. Fourth-generation biofuels offer higher productivity, increased CO₂ absorption capacity, and the potential for carbon-negative energy production through genetically engineered microorganisms compared with the lower generations.

Regarding chemical composition, oxygenated biofuels primarily comprise alcohols, fatty acid methyl and ethyl esters, ethers, and ketones. Fig. 1 illustrates the main pathways of obtaining them from biomass. Methanol can be synthesized from syngas derived from biomass, while the fermentation of sugars and cellulose can produce C₂-C₃ alcohols [35]. Methyl and ethyl esters of fatty acids, which are produced by transesterifying vegetable oils or animal fats with methanol or ethanol, respectively [35], are the main components of biodiesel. Ethers can be produced through various catalytic processes, such as direct etherification of alcohols, reductive etherification of alcohols with aldehydes or ketones, and etherification of olefins with alcohols, using heterogeneous catalysts to achieve high selectivity and yield [36]. Lignocellulose, as the second-generation biofuel feedstock with the highest commercial application potential, can undergo various processes, including pretreatment, hydrolysis, fermentation, detoxification, and distillation to produce diverse biofuels and platform compounds, including alcohols, ketones, acids, furans, and aromatic compounds [37]. Furthermore, ketones can also be indirectly synthesized from lactic acid and acetone-butanol-ethanol (ABE) fermentation products derived from biomass [38,39]. It is noteworthy that carbonates, as chemical synthesis products of alcohols, can also be indirectly derived from biomass [40,41]. Due to their extensive application in lithium-ion battery (LIB) electrolytes, carbonates have drawn significant attention in recent years [42], [43], [44].

Combustion is a significant process of energy utilization. The combustion process is a complex physicochemical phenomenon characterized by the coupling of chemical reactions with heat and mass transfer. The investigation of combustion kinetics aims to clarify the context of these reactions, from fuel consumption to the combustion intermediates and eventually products, and to provide a scientific explanation for macroscopic combustion phenomena at the microscopic molecular level. An effective kinetic model not only can elucidate the underlying causes of existing combustion phenomena, such as ignition delay time, but it can also be utilized to simulate and predict combustion parameters under unknown conditions, thereby guiding the design of burners and the control of pollutants [45].

Compared to conventional hydrocarbon fuels, oxygenated biofuels have raised new scientific challenges in combustion kinetics, particularly concerning: ① the influence of operating conditions, ② the effects of oxygenated functional groups, and ③ the interactions between oxygenates and hydrocarbons. While the combustion kinetics of certain simple biofuels such as ethanol [46], [47], [48] have been extensively studied since the early 1900s, more complex oxygenated compounds present ongoing research questions. This review begins by presenting fundamental concepts and research methodologies in combustion kinetics. It then offers a comprehensive summary of studies from the past decade on the combustion behavior of various biofuels, highlighting—through selected examples—how oxygenated functional groups influence reaction pathways and combustion characteristics. It should be noted that, although small-molecule hydrocarbon fuels derived from biomass, such as syngas [49] and biomethane [50], represent related alternatives, their kinetic networks are relatively well-established and straightforward. Therefore, they will not be discussed in detail here.

2. Combustion kinetics

Combustion kinetic models, consisting of a set of reactions and species that describe the actual reaction path, can offer valuable chemical insights into the underlying chemistry of the combustion process [51]. This precies description of actual chemical processes facilitates enhancements in combustor efficiency, significant reductions in pollutant discharge, and advancements in combustion technology.

2.1. Basic concept of kinetic mechanism

A complete kinetic model consists of thermodynamic data and transport parameters, as well as elementary chemical reactions with associated rate constants, which can be written in Arrhenius form [52]. The reverse rate of the elementary reaction can be derived from the relation $k_{\mathrm{r}}=k_{\mathrm{f}} / K_{\mathrm{P}}$, where K_P is the equilibrium constant of the reaction, while k_f and k_r are the rate coefficients for the forward and reverse reactions respectively. For elementary reactions with pressure dependence (e.g., unimolecular fuel decomposition), the rate constants can be expressed using the TORE [53] or pressure–logarithmic interpolation formalism (PLOG). The temperature-dependent thermochemical properties of the species, specifically enthalpy, entropy, and heat capacities, can be represented by thermodynamic data, usually in the form of “National Aeronautics and Space Administration (NASA) polynomials” [54]. To use chemical mechanisms for simulating reactions in practical devices, it is necessary to develop the numerical model. There are several programs that are commonly used in simulating chemically reacting systems, such as Chemkin [55], Cantera [56], and OpenSMOKE [57]. These computational models address a set of differential equations that necessitate initial conditions derived from the experiments.

A comprehensive mechanism consists of numerous sub-mechanisms, with the species of these sub-mechanisms interconnected through chemical reactions. One of the most important characteristics of kinetic mechanisms is their hierarchical structure, which means that the mechanism of the large species is built upon the sub-mechanisms involving smaller species [51]. Fig. 2 [58] shows a diagram of this scheme. Currently, the widely accepted method for developing fuel kinetic mechanisms involves adding the target fuel sub-mechanism, which requires construction or further optimization, into the extensively validated C₀-C₄ core mechanism. To date, various core mechanisms have been developed and are available on the internet, such as Gas Research Institute Mechanism (GRI-Mech) [59], University of Southern California Mechanism Version II (USC Mech II) [60], foundational fuel chemistry model (FFCM) [61], National University of Ireland Galway Mechanism version 1.1 (NUIGMech1.1) [62], and AramcoMech [63], [64], [65]. Among them, NUIGMech1.1 [62] and AramcoMech [63] incorporate detailed mechanisms for the oxidation of common C₁-C₄ oxygenated fuels, encompassing alcohols, ethers, ketones, esters, and aldehydes. And AramocMech [63] has been extensively validated against experimental data for small oxygenated fuels such as methanol, ethanol, dimethyl ether (DME), and acetone across a broad temperature range. The most recently updated core mechanism is FFCM 2.0 [61], which contains C₁-C₂ alcohols and aldehydes, as well as acetone. It mainly focuses on high-temperature combustion conditions of oxygenate fuels. The elementary reactions within the fuel sub-mechanism can be categorized into distinct reaction classes [51,66,67]. These reactions, which predominate in fuel consumption, vary across different temperature ranges. Consequently, they can be classified into high-temperature and low-temperature reaction classes [68], [69], [70]. There are different rules for determining the rate constants of different reaction classes, which are progressively being refined, especially for alkanes [71], [72], [73], [74]. It is noteworthy that, in recent years, quantitative calculations have increasingly contributed to determining the reaction rate constants. Moreover, the actual performance of a mechanism is often assessed against experimental results, and usually, some degree of optimization is necessary [58].

2.2. Combustion kinetics experiments and diagnostics

To thoroughly investigate the intricate kinetic reaction networks, the actual engineering environment is unsuitable due to its complex structure and flow characteristics. The experimental conditions governing combustion kinetic investigations usually involve temperature (T), pressure (P), and equivalence ratio (φ). Experimental devices widely adopted in research include shock tubes [75], [76], [77], rapid compression machines (RCMs) [78], [79], [80], jet-stirred reactors (JSRs) [81], plug-flow reactors (PFRs) [82], and laminar premixed flame or counterflow flame reactors [83,84], which have been subject to decades of updates and optimizations. Fig. 3 [85] provides a summary of the typical operational ranges for some selected combustion reactors. These instruments are designed to evaluate critical characteristics such as laminar burning velocities (LBVs) and ignition delay times (IDTs), to assess the influence of temperature and pressure on individual elementary reactions, and to examine the pyrolysis and oxidation behavior of fuels under specific conditions [45]. In recent years, the development of experimental facilities for combustion kinetics has progressed towards acquiring data with a broader range of experimental conditions and integrating with more precise diagnostic methods. For example, Zhao et al. [86] made high-pressure (above 100 bar; 1 bar = 10⁵ Pa) JSR experiments possible through a novel design, while Kang et al. [87] addressed the significant axial vibration of RCM to enable molecular beam mass spectrometry sampling.

In principle, the methodologies employed for chemical analysis can similarly be applied to combustion diagnostics, with some adaptation to account for the temperature, pressure, and geometry of the species being measured. Combustion diagnostic techniques can generally be categorized into two types: non-invasive and invasive methods. The non-invasive methods avoid disrupting the reaction environment, typically based on laser diagnostics, which benefit from the laser probe’s coherent properties, offering excellent spatial and temporal resolution, as well as multidimensional imaging of various quantities [88], [89], [90]. Prior to diagnosis, it is generally essential to possess a detailed understanding of cross sections, the spectral signatures, and the expected concentration range of the target species in order to appropriately configure the laser settings. Consequently, the simultaneous detection of multiple species is often challenging due to the intricate setups [45]. In contrast to non-invasive laser-based techniques, invasive methods rely on direct sampling by a probe from the reaction environment. Common techniques include mass spectrometry (MS) and chromatography (GC) [91], [92], [93], which are suitable for the diagnosis of chemical-rich systems. Among them, photoionization molecular-beam MS (PI-MBMS), using tunable vacuum ultraviolet (VUV) synchrotron radiation for photoionization (PI) [92], is especially effective for exploring chemical pathways in intricate reaction systems due to its ability to identify substances through mass and PI efficiency (PIE) spectra [94]. Mass spectrometric analysis does not require extensive prior knowledge about the target species, and it also facilitates the detection of radicals or unstable intermediates [95,96].

2.3. Uncertainty quantification (UQ) and optimization of kinetic models

In comparing experimental data sets with simulation results, it is essential to assess the uncertainties inherent in both. Inevitably, a large number of thermodynamic parameters and rate coefficients that vary with temperature and possibly pressure will lead to uncertainties during the application process of kinetic models. A significant challenge in evaluating these model uncertainties is determining how the uncertainty ranges of individual parameters contribute to the overall uncertainty. This is often challenging since these parameters are not independent of one another [97]. Systematic quantification of uncertainties and the refinement of models through mathematical techniques have become an active field of research [98], [99], [100], [101]. The most impactful advancement in combustion chemistry uncertainty analysis was Michael Frenklach’s pioneering systematic framework for kinetic parameter uncertainties [102]. Sheen and Wang [103] devised a method for quantifying and minimizing uncertainty through polynomial chaos expansion (MUM-PCE) and advanced its use by creating the software “mumpce_py” [102]. Nagy et al. [104] and Nagy and Turányi [105] introduced a technique for assessing the uncertainties associated with correlated Arrhenius parameters, and also conducted UQ and optimization on several existing models [99,106,107]. Global or local sensitivity analysis (SA) also plays a significant role in UQ and model optimization. Based on this, graphical user interface-high dimensional model representation (GUI-HDMR), a software tool for SA, was developed by Tomlin [108] and Ziehn and Tomlin [109].

By quantifying uncertainties and investigating their propagation, one can more effectively identify targets for experiments and model enhancements, thereby facilitating mechanism optimization and uncertainty minimization. Developing a good experimental design approach is effective to minimize uncertainty; several frameworks for experimental design have been proposed [110], [111], [112], [113]. It is worth noting that some experimental designs often depend on data from the posterior distributions of model parameters or the results of constrained optimization to determine the most suitable experiments for optimizing the model, which can be quite time-consuming considering the computation of posterior distributions for massive potential experimental conditions [114]. Fig. 4 [114] illustrates the workflow of OptEx, a framework designed for UQ and experimental design. Within this framework, an artificial neural network (ANN) serves as a surrogate model to perform UQ and global SA. These techniques assess the probability distribution of model predictions and identify the primary sources of uncertainty, respectively. Notably, sensitivity entropy and surrogate model similarity can be derived from global sensitivity indices, facilitating informative experimental design and data categorization. Subsequently, using the available datasets, the model can be refined through Bayesian inference.

3. Kinetic research of oxygenated components of biofuels

3.1. Alcohols

The kinetics of alcohols with short carbon chains, especially methanol and ethanol, have been extensively studied since the previous century [115], [116], [117], [118], [119]. Despite the development of many kinetic models, accurately predicting combustion characteristics across a wide range of experimental conditions remains challenges [120]. Fig. 5(a) [121], [122], [123], [124] compares the measured and predicted LBV of methanol. Notably, the predictive models show significant discrepancies under fuel-rich conditions, where the deviations are particularly pronounced. Fig. 5(b) illustrates the results of sensitivity analysis performed by Zhang et al [121]. The results indicate that under highly fuel-rich conditions, the reduced flame temperature enhances the dominance of reactions involving HO₂ radicals (e.g., CH₃OH + HO₂ = CH₂OH + H₂O₂ and CH₂OH + O₂ = CH₂O + HO₂). Thus, continued research efforts over the past decade have further investigated these small molecular alcohols, yielding new experimental data. Much of this recent work has aimed to broaden the range of experimental conditions—such as high-pressure environments and low-temperature regimes achieved via additives such as DME [125] and ozone [126]—while also diversifying the types of data collected, including flame properties [121] and time-resolved species concentration profiles [127], [128], [129]. In terms of reaction mechanisms, recent studies have focused more on optimizing parameters for key elementary reactions—such as CH₂OH + O₂ = CH₂O + HO₂ [121] and the branching ratios of H-abstraction from ethanol by OH radicals [127]—rather than developing entirely new models. These kinetic parameters are often highly constrained by experimental data obtained under specific conditions. Notably, neither methanol nor ethanol oxidation exhibits negative temperature coefficient (NTC) behavior. Additionally, advances in UQ have enabled more systematic model optimization [106,114,130,131]. For instance, Zhou et al. [114] applied a framework they developed, OptEx, to quantify uncertainties in the methanol model proposed by Zhang et al. [121] and to identify key sources of these uncertainties. Their analysis revealed that the IDT is highly sensitive to two critical parameters across all experimental conditions: the rate constant of H₂O₂ decomposition and that of H-atom abstraction from methanol by HO₂ radicals. Consequently, targeted experimental measurements under specific conditions can significantly improve the accuracy of model predictions over a wide range of scenarios.

We next note that methanol and ethanol suffer from drawbacks such as low energy density, hygroscopicity, and high corrosiveness. These limitations have spurred growing interest in alcohols with longer carbon chains, particularly those spanning C₃-C₅ [132]. Among C₃ alcohols, two structural isomers exist: n-propanol and i-propanol. A variety of experimental techniques have been employed to measure their IDTs, LBVs, and species concentration profiles during oxidation [132], [133], [134], [135]. These studies reveal that the location of the hydroxyl group significantly influences oxidation characteristics. Specifically, n-propanol demonstrates higher reactivity than i-propanol, manifesting as shorter ignition delays and higher burning velocities. The linear structure of n-propanol facilitates the formation of active radicals such as formyl, vinyl, and ethyl, which promote H-atom production and enhance overall reactivity. In contrast, the branched structure of i-propanol favors the generation of more stable radicals like CH₃ and allyl, thereby inhibiting oxidation [135]. Across all alcohols, the water elimination reaction represents a key unimolecular pathway, proceeding via a four-center transition state that involves β H atoms and the hydroxyl oxygen atom, as illustrated in Fig. 6 [120]. This reaction yields an alkene and water, and the stability of the resulting alkene influences the overall reactivity of the parent alcohol. Experimental approaches have been instrumental in quantifying reaction rates across different alcohols, as summarized in Ref. [120].

Alcohols with longer carbon chains, such as butanol and pentanol, offer higher energy density and reduced polarity compared to shorter-chain counterparts, making them promising candidates as engine fuels or additives to hydrocarbon fuels [136]. These compounds can be produced via biological routes, including glucose biosynthesis using Escherichia coli [137] and natural microbial fermentation facilitated by engineered microorganisms [138]. In 2012, Sarathy et al. [139] developed a detailed kinetic model encompassing all four butanol isomers (1-, 2-, iso-, and tert-butanol), which incorporated both high- and low-temperature reaction pathways. The model was validated against experimental data from premixed flames, shock tubes, and JSRs, helping to clarify dominant reaction pathways and the impact of molecular structure on combustion behavior. For pentanol isomers, Togbé et al. [140] proposed the first kinetic model for 1-pentanol, though it omitted low-temperature chemistry. This was later addressed by Heufer et al. [141], who introduced a more comprehensive model for 1-pentanol that included low-temperature reaction pathways. Köhler et al. [142] developed models for all three straight-chain pentanol isomers, still without low-temperature kinetics. Subsequently, Chatterjee et al. [143] established comprehensive kinetic models for low-temperature oxidation of 2- and 3-pentanol, enhancing model accuracy through RCM experiments. Notably, among the straight-chain pentanol isomers, low-temperature reactivity follows the order: 1-pentanol shows the highest reactivity, followed by 2-pentanol, and then 3-pentanol. Fig. 7 [143] presents a simplified reaction pathway analysis that helps clarify the low reactivity of 3-pentanol. Upon H-atom abstraction, 3-pentanol forms three distinct fuel radicals: α, β, and γ. Among these, only the γ radical can further react to form ·O₂QOOH radicals and ketohydroperoxides (KHP), which are essential for chain branching at low temperatures [143]. Consequently, the low-temperature reactivity of 3-pentanol is primarily governed by γ-radical chemistry, contrasting with other pentanol isomers that exhibit more extensive chain-branching pathways. According to the reaction pathway analysis by Chatterjee et al. [143], approximately 42% of 1-pentanol molecules undergo H-abstraction at specific sites followed by chain branching, promoting OH radical accumulation and enhancing reactivity. In comparison, only 33% of 2-pentanol molecules follow similar pathways, explaining its intermediate reactivity relative to 1- and 3-pentanol. This systematic variation in radical branching efficiency accounts for the observed reactivity trend among the pentanol isomers. Table 1 [125], [126], [127],[133], [134], [135], [136],139,142,[144], [145], [146], [147], [148], [149], [150] summarizes key recent studies on alcohol combustion kinetics (C₁-C₅) for reference.

Despite considerable research on alcohols, significant knowledge gaps remain even for small alcohols such as methanol and ethanol. For methanol, quantitative species profiles in high pressure flame environments are still scarce compared to data from reactor experiments [120]. Meanwhile, most ethanol models do not adequately address low-temperature kinetics (below 800 K), despite evidence confirming its reactivity in this regime [151]. Although the combustion kinetics of methanol and ethanol have been widely studied, achieving accurate model predictions across a broad range of conditions remains a challenge. This requires improved UQ and systematic analysis of error sources. The presence of the hydroxyl group also significantly influences bond dissociation energies: α C-H bonds are weakened, whereas β C-H bonds are slightly strengthened compared to those in alkanes. Consequently, key reaction rate constants—particularly for dominant pathways such as H-atom abstraction by HO₂ radicals under low-temperature conditions—still lack sufficient theoretical or experimental determination. Moreover, sub-mechanisms of critical intermediates like enols and aldehydes are not yet well established, leading to inaccuracies in predicting global reactivity and intermediate species concentrations. [133,144,145].

3.2. Fatty acid methyl esters (FAMEs)

Biodiesel is widely regarded as one of the most economically viable biofuels and a promising alternative to fossil diesel, capable of partially or fully replacing it. It consists of a complex mixture of saturated and unsaturated methyl esters with carbon chains ranging from C₁₄ to C₂₄ [152]. The composition of FAMEs in biodiesel varies considerably depending on the feedstock source, presenting considerable challenges for the development of accurate kinetic models. As a result, a surrogate fuel approach has been adopted, wherein a single methyl ester is selected to represent the combustion behavior of real biodiesel [153]. Methyl esters commonly employed as surrogate fuels comprise both saturated species (such as methyl butanoate, methyl decanoate, methyl palmitate, and methyl stearate) and unsaturated esters (including methyl oleate, methyl linoleate, and methyl linolenate). Among these, methyl palmitate, stearate, oleate, linoleate, and linolenate are major constituents of soybean and rapeseed biodiesels, all featuring long alkyl chains [154]. Fig. 8 illustrates the chemical structures of these key surrogate compounds. Compared to saturated esters, the presence of carbon-carbon double bonds in unsaturated esters significantly influences their combustion behavior, particularly under low-temperature conditions. Specifically, the allylic sites adjacent to double bonds lower the energy barrier for H-atom abstraction, promoting rapid consumption of reactive radicals in the early stages of oxidation. Subsequently, the resulting RO₂ radicals—characterized by relatively weak R-O bonds at the allylic positions—readily decompose back into fuel radicals, thereby terminating low-temperature chain propagation pathways [155]. As a result, the presence of C=C double bonds in FAMEs suppresses low-temperature oxidation activity, with the inhibitory effect becoming more pronounced as the number of double bonds increases [156].

The presence of the ester group (CH₃OC=O) lowers the bond dissociation energy of the C-C bond linking the ester carbon and the adjacent carbon atom. This weakening promotes cleavage of the bond in the FAME, yielding a methoxyformyl radical (CH₃OC=O·), a key intermediate in oxygenated fuel chemistry. This radical can subsequently decompose to form CO or CO₂:

(1)$\mathrm{CH}_{3} \mathrm{OC}=\mathrm{O} \cdot=\mathrm{CH}_{3} \cdot+\mathrm{CO}_{2}$

(2)$\mathrm{CH}_{3} \mathrm{OC}=\mathrm{O} \cdot=\mathrm{CH}_{3} \mathrm{O} \cdot+\mathrm{CO}$

This process suppresses soot formation by directing carbon atoms toward the formation of small molecules, thereby inhibiting the aggregation into soot precursors [157]. Among the decomposition pathways, the route leading to CO is particularly effective in reducing soot emissions, as each oxygen atom binds a carbon atom, preventing its incorporation into larger carbonaceous species. Zhao et al. [158] calculated the potential energy surface (PES) and temperature- and pressure-dependent rate constants for these competing pathways. Their research indicates that the pathway yielding CO₂ exhibits a lower activation energy, consequently making it dominant for the decomposition of CH₃OC=O·. A sub-mechanism for methyl propanoate incorporating these reactions successfully predicted CO and CO₂ formation during pyrolysis in a laminar flow reactor [158]. In contrast, developing kinetic models for long-chain FAMEs is relatively straightforward in principle, as their oxidation can largely be described using rate rules derived from alkane combustion [159].

Following the progression of combustion kinetics research, methyl butanoate—the shortest-chain methyl ester surrogate—has been the most extensively studied. Fisher et al. [160] developed the first detailed mechanism in 2000, and Dooley et al. [161] later proposed a comprehensive model validated across a wide range of conditions. Subsequent work by Gaïl et al. [162] and Hakka et al. [163] further optimized the mechanism by incorporating low-temperature reaction pathways. However, despite its utility, methyl butanoate fails to capture key kinetic behaviors of long-chain methyl esters that dominate biodiesel composition, such as NTC behavior, which is absent in its oxidation [164]. In recent decades, research has shifted toward long-chain saturated and unsaturated methyl esters. Herbinet et al. [165] developed the first detailed kinetic model for methyl decanoate based on n-heptane oxidation principles, and Glaude et al. [166] constructed a model using EXGAS software. In 2010, Herbinet et al. [159] automatically generated a mechanism for methyl palmitate with EXGAS and validated it against JSR data. Naik et al. [167] created large-scale models for methyl stearate and methyl oleate, comprising around 3500 species and 17 000 reactions, highlighting the strong influence of double bonds on low-temperature pathways. More recently, Zhou et al. [168] and Zhou et al. [169] provided IDT data from an RCM for methyl palmitate and methyl stearate at low-to-intermediate temperatures, refining their kinetic models, respectively. They also measured IDTs for methyl oleate and methyl linoleate to assess the impact of double bonds on reactivity and autoignition, improving model predictions through SA [156]. Fig. 9 [156,[168], [169], [170], [171], [172], [173] compares low-temperature IDT measurements for several FAMEs with predictions from existing models, revealing significant discrepancies in ignition behavior under these conditions. Earlier reviews, such as that by Tran et al. [35], have summarized major detailed kinetic models for biodiesel surrogates and their validation status before 2012.

A paucity of experimental data and related research persists regarding authentic long-chain FAMEs present in biodiesel (e.g., methyl oleate, methyl linoleate, and methyl linoleate). Furthermore, the predictive capability of existing models, when validated against experimental results, consistently proves to be unsatisfactory (Fig. 9). The extension of the carbon chain greatly increases the complexity of kinetic models for FAMEs. For example, a detailed model representing the five main FAME components of soybean and rapeseed biodiesel includes approximately 4800 species and nearly 20 000 reactions [174]. A kinetic network of this size increases the difficulty of optimization and prohibits its use in industrial-scale simulations. As a result, research over the past decade has focused on developing simplified skeletal or lumped mechanisms with practical applicability [171,173,175,176]. Since this topic falls beyond the scope of the present review, it will not be discussed further.

3.3. Ketones

Ketones, which can be derived from lignocellulose, offer higher energy densities, improved anti-knock properties, and lower soot emissions compared to alkanes [177], [178], [179]. These advantages make them attractive as transportation fuels or fuel additives. Moreover, ketones serve as critical intermediate species in the low-temperature oxidation of alkanes [65], making their kinetic study essential for elucidating complex low-temperature reaction networks. Common ketones include acetone, butanone, 2-pentanone, and 3-pentanone. While acetone and butanone have no isomers, 2-pentanone and 3-pentanone represent the simplest straight-chain ketones exhibiting structural isomerism. Although the combustion behavior of simpler ketones such as acetone has been studied since the last century, their kinetic models have been continually refined in recent years. For instance, Hong et al. [180] significantly improved prediction accuracy by re-evaluating the dissociation reaction CH₃COCH₃ = CH₃CO· + CH₃· based on updated experimental data (Fig. 10). A summary of recent detailed kinetic studies on ketones is provided in Table 2 [181], [182], [183], [184], [185], [186], [187], [188], [189], [190], [191], [192], [193], [194], [195], [196], [197], [198], [199], [200], [201], [202], [203], [204], [205].

Ignition [206], [207], [208] and low temperature oxidation experiments [182], [183], [184] for acetone and butanone indicate negligible low-temperature reactivity. With the extension of the carbon chain in 1- and 2-pentanone, the intramolecular hydrogen migration reaction of ROO· radicals (i.e., ROO· → ·QOOH) becomes more favorable. As a result, Fenard et al. [185] observed NTC behavior in 2-pentanone and 3-pentanone, while Kang et al. [186] identified two-stage ignition in RCM experiments, demonstrating that linear pentanones exhibit distinct low-temperature reaction pathways and reactivity. Notably, the presence of the carbonyl group in ketones influences intramolecular bond energies, specifically weakening the C-C bonds adjacent to the carbonyl group and the C-H bonds at the α-carbon positions [187,188]. This reduction in bond energy significantly promotes unimolecular decomposition and H-atom abstraction reactions at these sites. However, for intramolecular hydrogen migration reactions, the effect of the carbonyl group on the energy barrier within the transition state must also be considered. As illustrated in Fig. 11 [186,189,209], although the formation of C5KET2-OOH3-R1 involves cleavage of a C-H bond with relatively low dissociation energy, participation of the carbonyl group in the transition state leads to a higher overall energy barrier. Furthermore, unlike in alcohols, H-atom loss from the α-methylene (-CH₂-) or methyl (-CH₃) groups adjacent to the carbonyl group produces resonance-stabilized radicals [210]. When intramolecular hydrogen migration involves H-atoms from these groups, such resonance-stabilized radicals can be formed (indicated by rectangular boxes in Fig. 12 [186]). Fig. 13 [211] shows the PES for the reaction of 5-pentanone fuel radicals with O₂, revealing that the resonance-stabilized radical has the lowest relative energy among the three ·QOOH isomers. This implies a higher energy barrier for the reverse reaction to reform ROO· radicals. Consequently, although the carbonyl group slows the rate of ·QOOH formation, the low-temperature reaction network of ketones still favors the generation of these ·QOOH radicals due to the elevated reverse energy barrier—especially compared to alkanes, as depicted in Fig. 12. As a result, more fuel radicals participate in subsequent secondary oxygen addition and chain-branching reactions, leading to the formation of KHP and OH radicals, thereby enhancing low-temperature reactivity. Fig. 12 compares the reaction flux among ROO· radicals in 2-pentanone, 3-pentanone, and n-pentane. It can be observed that pathways yielding resonance-stabilized radicals show notably high reaction fluxes.

Regarding the oxidation of ketones at medium and high temperatures, Kang et al. [190] experimentally identified a distinctive “addition-dissociation reaction” facilitated by the carbonyl group. This reaction is proposed to proceed in two steps: first, an H or CH₃ radical adds to the carbon atom of the carbonyl group; then, the adduct dissociates into a shorter-chain aldehyde or ketone along with an alkyl radical [190]. Their developed model for pentanone oxidation incorporates this pathway using theoretically derived rate coefficients. Sun et al. [187] investigated laminar premixed flames of cyclopentanone and 3-pentanone, measuring species concentrations. They constructed a new kinetic model that showed good agreement with the experimental speciation data. Under high-temperature flame conditions (above 2000 K), the carbonyl groups in ketones are primarily released as CO, which hinders the incorporation of these carbon atoms into soot precursors. This property suggests that ketones have the potential to reduce soot emissions when used as fuel additives. Moreover, the oxygen atoms in ketones contribute only minimally to the formation of hazardous pollutants such as aldehydes and shorter-chain ketones, which arise mainly from the oxidation of hydrocarbon intermediates [187]. Minwegen et al. [212] compared IDTs measured in a shock tube and established the reactivity order of four common ketones at medium to high temperatures as follows: 3-pentanone > butanone > 2-pentanone > acetone.

The construction of a comprehensive experimental database for ketone combustion remains highly valuable—even for fundamental compounds like acetone [191]. Such databases are crucial for refining kinetic models and improving predictive accuracy across a range of combustion conditions. Aldehydes, which are significant intermediate products during ketone oxidation, require deeper investigation into their formation and consumption pathways. For instance, studies on biodiesel oxidation have demonstrated that aldehydes such as formaldehyde and acetaldehyde can increase dramatically under certain conditions, underscoring the need for precise mechanistic insights. Furthermore, there is a pressing need for experimental data on special intermediates such as ketenes and vinyl ketones (e.g., methyl vinyl ketone), to accurately construct and validate their oxidation mechanisms [183,184]. The low-temperature chemistry of ketones also demands more comprehensive and detailed examination. To address these challenges, more accurate rate constants for critical reactions are essential. Advanced theoretical studies and PES calculations are also needed to uncover new reaction classes and improve existing kinetic rules.

3.4. Ethers

Chain ethers are derived from alcohols [35] and can be categorized into two distinct types: straight chain ethers and branched chain ethers. Straight chain ethers primarily consist of DME, diethyl ether (DEE), and di-n-propyl ether (DPE), whereas branched chain ethers include methyl tert-butyl ether (MTBE), ethyl tert-butyl ether (ETBE), and diisopropyl ether (DIPE). These compounds are mainly utilized as gasoline additives [213]. The presence of an ether bond significantly reduces the bond dissociation energy of the adjacent C-C and C-H bonds, thereby enhances their low-temperature reactivity in comparison to the corresponding alkanes. DME, recognized as the simplest ether, is among the most extensively studied. In 1996, Dagaut et al. [214] proposed the first detailed combustion mechanism of DME. Following numerous updates and optimizations, the current models showed satisfactory predictive performance on measured IDTs data, NTC behavior, and the concentration profiles of some key intermediates such as formaldehyde and formic acid [215], [216], [217]. For long straight ethers, such as DEE [218], DPE [219], and di-n-butyl ether [220], an interesting phenomenon was observed, that there are two NTC zones in their oxidation. These two zones can be distinctly identified in Fig. 14(a) [218], [219], [220], [221]. Fig. 14(b) compares the experimental results of two dipropyl ether isomers, and it can be observed that the branched ether does not exhibit NTC behavior in similar conditions. Fan et al. [219] elucidated this double NTC behavior in their oxidation investigation of DPE and Fig. 15 shows their reaction pathway analysis results. The emergence of the first NTC zone of DPE can be attributed to factors similar to those affecting alkanes, specifically the competition between the decomposition of the fuel radical and the low-temperature reaction pathway. As illustrated in Fig. 15 [219], at 530 K, fuel radicals formed from H-atom abstraction undergo a sequential reaction pathway to produce ROO· (C₃H₇OC₃H₆OO-A), ·QOOH (C₃OC₃-AOOH-1), ·OOQOOH (C₃OC₃-AOOH-1OO), and KHP (C₃OC₃KETA-1), ultimately resulting in the net generation of OH radicals and demonstrating the low-temperature activity of DPE. Around 590 K, an increased temperature favors the decomposition of fuel radicals, primarily producing n-C₃H₇ and C₂H₅CHO, which diminishes the overall reactivity and contributes to the first NTC behavior. With further increases in temperature, the concentrations of intermediates n-C₃H₇ and C₂H₅CHO rose rapidly, becoming predominant in the oxidation system at this stage. Due to their typically higher low-temperature activity range (around 600-700 K) compared to DPE, these species once again undergo a similar reaction competition as mentioned above, leading to the emergence of second NTC behavior. This theory also accounts for the NTC behavior observed in other ethers [219]. Fig. 16 [219,222] shows the concentration profiles of some typical intermediate species during the DPE oxidation process. Propanal exhibits the highest peak mole fraction in the low-temperature region, which is consistent with its key role in the formation of the observed double-NTC behavior. The observed substantial formation of small molecular hydrocarbons (CH₄, C₂H₄, and C₃H₆) at elevated temperatures also supports the conclusion drawn from the reaction pathway analysis. Furthermore, significant discrepancies remain between model predictions and experimental data for certain oxygenated intermediates (e.g., C₂H₃OH and CH₂CO), which provides a direction for future works. Differently, branched chain ethers do not demonstrate such significant low-temperature activity, although the presence of O atoms still facilitates the H-atom abstraction reactions and the ROO· isomerization. The primary reason is that the branched-chain structure results in a higher energy barrier for the subsequent formation of hydroperoxyalkyl peroxy radicals (·OOQOOH) and KHP, thereby diminishing the production of OH radicals [221]. Major detailed kinetic models of chain ethers proposed in recent years are summarized in Table 3 [215], [216], [217], [218], [219], [220], [221], [222], [223], [224], [225], [226], [227], [228], [229], [230], [231], [232], [233], [234], [235], [236], [237].

Cyclic ethers, derived either from fructose enzymatically produced from starch [238] or through a catalytic process from cellulosic biomass [239], have the potential to serve as valuable alternatives to fossil fuels for transportation. The reaction classes in the oxidation mechanisms of cyclic ethers are fundamentally analogous to those of cyclic alkanes. However, the reaction rate constants are subject to modification due to the presence of O atoms [35]. Furthermore, polyoxymethylene DME (PODE_n), characterized by its distinctive C-O alternating chain structure (CH₃O(CH₂O)_nCH₃), can be synthesized from methanol, DME, or formaldehyde [240]. It has been demonstrated to reduce particulate matter and soot emissions when used as a fuel additive [241], and relevant combustion kinetic studies have been constructed in recent years. Kinetic models for these mentioned fuels are also listed in Table 3.

So far, discrepancies still persist between models and experimental results at low-temperature regimes for ethers, particularly long-chain ethers. This underscores the need for a deeper understanding of the intricate chemistry involved in their oxidation process at low temperatures. The impact of ether functional groups on the low-temperature chemistry of fuels and the decomposition of oxygen-containing intermediates can serve as a starting point for further theoretical investigations. Additionally, sensitivity analyses of these models indicated that the rate constants of certain key reactions may require reevaluation to enhance model performance. These include H-atom abstraction by HO₂ and OH radicals, decomposition of ethers and KHP species.

3.5. Carbonates

In recent years, the global appetite for electric vehicles (EVs) has surged, and LIBs have become the preferred choice for energy storage in EVs. This is due to their relatively high energy density, excellent cycling performance, high operating voltage, and extended lifespan [242,243]. As the primary component of the electrolyte in LIBs, investigation of the combustion kinetics of carbonates is essential to accurately understand the thermal runaway process of batteries and to develop effective thermal management strategies. Electrolyte solvents commonly consist of mixtures of various carbonates, including linear carbonates dimethyl carbonate (DMC), diethyl carbonate (DEC), and ethyl methyl carbonate (EMC), as well as the cyclic carbonates ethylene carbonate (EC) and propylene carbonate (PC) [244]; their chemical structures are shown in Fig. 17. Since they can be synthesized from alcohols and can be indirect products of biomass [41], the kinetic investigations of carbonates are also included in this review.

In 2005, Glaude et al. [157] proposed the first detailed oxidation kinetic model of DMC. Building upon this model, Hu et al. [245] and Sun et al. [246] subsequently constructed respective high-temperature oxidation mechanisms. These mechanisms were validated using IDTs data and laminar premix flame species data, respectively. The most recent kinetic study of DMC was conducted by Yu et al. [247], who validated the existing models by the measured low-temperature ignition delay data and modified the rate constants of several crucial H-atom abstraction reactions at low temperature. Owing to the relatively weak activity of DMC at low temperatures, none of the proposed mechanisms so far contains low-temperature reaction pathways analogous to those of alkanes. At medium and low temperatures, DMC is primarily consumed through H-atom abstraction reactions to generate fuel radicals (CH₃OC(=O)OCH₂·), which subsequently decompose to CH₃OC(=O)O· and CH₃OC(=O)· radicals [247]. Notably, at high temperatures, linear carbonates are capable of undergoing a distinct unimolecular decomposition reaction known as the CO₂ elimination reaction. In this process, the C atom within the carbonate group is released as CO₂, leaving behind one O atom to form an ether [248]. Fig. 18 [249] illustrates the comparative reaction fluxes of DMC at low and high temperatures. The dominant reaction pathway at low temperatures is H-atom abstraction, leading to the formation and subsequent decomposition of fuel radicals. However, at high temperatures, CO₂ elimination becomes an increasingly important reaction. Table 4 [80,157,246,248,250] presents the rate constants and activation energies for CO₂ elimination reactions of linear carbonates, along with their corresponding literature sources. In 2015, Nakamura et al. [251] developed the first oxidation mechanism for DEC, in which the rate constants of ROO· ⇋ ·QOOH isomerization were determined through quantitative calculation, and other low-temperature pathways and the associated parameters were obtained by analogy. The existence of these pathways could be demonstrated by the observed NTC behavior in RCM and JSR experiments [251,252]. Another significant reason for the higher activity of DEC at low temperature is that DEC can decompose into ethoxyformic acid and ethylene, and a six-membered ring transition state involving an ethyl ester group was formed in this reaction:

(3)$\mathrm{C}_{2} \mathrm{H}_{5} \mathrm{OC}(=\mathrm{O}) \mathrm{OC}_{2} \mathrm{H}_{5}=\mathrm{C}_{2} \mathrm{H}_{4}+\mathrm{C}_{2} \mathrm{H}_{5} \mathrm{OC}(=\mathrm{O}) \mathrm{OH}$

The ethoxyformic acid can rapidly decompose into CO₂ and ethanol. It is noteworthy that, owing to its lower activation energy [248], this reaction becomes the dominant pathway during pyrolysis for carbonates containing ethyl groups, rather than the CO₂ elimination reaction [253].

Because of the experimental challenges caused by the extremely low saturated vapor pressure of cyclic carbonates (e.g., the saturated vapor pressure of EC is only 390 Pa at 373 K [254]), the advance of combustion kinetics in cyclic carbonates is considerably slower compared to that of linear carbonates. In 2024, Kanayama et al. [255] first developed a detailed surrogate model for LIB electrolytes, which includes the pyrolysis and oxidation of EC, DMC, EMC, and DEC. One year later, Dong et al. [256] enhanced this model by revising and adjusting the rate constants for several reactions associated with the generation and depletion of the formyl methyl radical (·CH₂CHO) and ketene. The optimized model improved the prediction of the species data measured in JSR. The ·CH₂CHO-related and CH₂CO-related chemistry have shown significant influence on the pyrolysis and oxidation of EC. As a cyclic carbonate, EC can also undergo the CO₂ elimination reaction, yielding CO₂ and C₂H₄O isomers, including acetaldehyde (CH₃CHO), oxirane (C₂H₄O_1-2), and vinyl alcohol (C₂H₃OH). This is the main pathway for the consumption of EC in pyrolysis [257]. Furthermore, the authors have not found any pertinent studies on the combustion kinetics of PC. The major detailed kinetic models proposed recently on these carbonates are shown in Table 5 [245], [246], [247], [248], [249],253,255,256,[258], [259], [260]. For further kinetic study of cyclic carbonates, the priority is to enrich the experimental data of oxidation and pyrolysis, particularly the species profiles of key intermediates such as C₂H₄O isomers, ·CH₂CHO, and CH₂CO, thereby further constraining the predictive performance of the existing models. Further refinement of the EC kinetic model requires particular attention to the reaction pathways responsible for acetaldehyde generation at low temperatures (< 900 K). Additionally, the reaction rate coefficients related to ·CH₂CHO may also need to be re-evaluated [256]. In the development of a kinetic model for PC, a suitable initial step would involve the computation of the PES and branching ratios for CO₂ elimination reaction via quantum chemical methods.

4. Conclusions and perspectives

As the energy crisis exacerbated by fossil fuels intensifies, biofuels have garnered increasing attention due to their benefits, including carbon neutrality and the accessibility of raw materials. Maximizing these benefits of biofuels necessitates not only a comprehension of their physical properties but also a thorough understanding of the chemistry underlying the combustion processes. This review introduces the combustion kinetics of oxygenated fuels derived directly or indirectly from biomass, including alcohols, FAMEs, ketones, ethers, and carbonates, over the last decade. The kinetic characteristics of these oxygenated fuels, along with the corresponding detailed models proposed in recent years, are presented. Alcohols have a special unimolecular dehydration reaction with a four-center transition state, generating an alkene and water. For long-chain alcohols, the influence of the hydroxyl group’s position on low-temperature activity is primarily determined by the feasibility of the low-temperature chain branching reactions of the corresponding fuel radicals, which are generated through H-abstraction reactions. Long-chain FAMEs constitute the primary fraction of biodiesel fuel. The ester group contributes to a reduction in soot formation. The reaction classes of FAMEs are fundamentally similar to those of long-chain hydrocarbons. Moreover, the degree of unsaturation in FAMEs exerts a considerable influence on their reactivity, primarily attributable to the week bond dissociation energy at the allylic sites. During the oxidation of ketones, the resonance-stabilized radicals are easily formed, which significantly impact the reaction energy barrier. This, in turn, accounts for the differences in reaction flux between ketones and hydrocarbon fuels. Additionally, a distinct double NTC behavior was observed in the oxidation of straight-chain ethers. This phenomenon is attributed to the varying low-temperature activity of fuel molecules and intermediates generated in the oxidation process. In contrast, due to the higher energy barrier for the formation of ·OOQOOH and KHP, the branched ethers do not exhibit high low-temperature activity. Carbonates, as indirect derivatives of biomass, constitute the primary components of electrolyte solvents in LIBs, and their kinetic properties have garnered significant attention in recent years. For short-chain carbonates and cyclic carbonates, the CO₂ elimination reaction represents a distinctive and significant decomposition pathway particular at high temperature. In the case of long-chain carbonates such as DEC and EMC, owing to the lower activation energy, the fuel molecules are more likely to decompose via a pathway involving the formation of a six-membered ring transition state. The kinetics of cyclic carbonates remain relatively underexplored, necessitating further experimental validation of the models.

To facilitate the extensive application of biofuels, it is significant to gain a comprehensive understanding of their fundamental combustion characteristics and to develop predictive combustion kinetic models that are applicable under practical conditions. This necessitates further requirements for future research:

Deep insights into the combustion chemistry of biofuels are predicated on experimental observations, and further experimental research involving oxidation and pyrolysis remains essential. This includes diversifying the types of fuels studied, broadening the sources of experimental data, and expanding the range of experimental conditions. Particularly, the presence of oxygen-containing functional groups significantly influences the low-temperature activity of fuels, which mean additional low-temperature experimental data for various fuels is still highly necessary. New experimental methods, such as the addition of active component like ozone, hold potential for facilitating kinetic investigations at low-temperature oxidation systems. Meanwhile. it is necessary to advance combustion diagnostic technologies to enable more precise measurement of key intermediates in the combustion process of biofuels. In combustion environments, specific intermediates, such as aldehydes generated during ketone oxidation and enones formed during cyclic carbonate oxidation, are critical for providing essential constraints during kinetic model refinement and optimization.

The presence of oxygen-containing functional groups has a substantial impact on the bond dissociation energy of molecules. Consequently, determining the reaction rate constants needs additional experimental investigations and theoretical calculations, rather than relying solely on analogies with the same reaction classes of alkanes. There is a need for elementary kinetic rate measurements for some key reactions of biofuels, including special decomposition reactions of fuels, H-atom abstraction reactions and decomposition of intermediates. H-atom abstraction reactions by HO₂ and OH radicals warrant increased research attention due to their substantial importance in the low-temperature oxidation of oxygenated fuels. Furthermore, through the application of quantum chemical calculations and theoretical research on PES, special reaction classes can be revealed and their rate parameters can be determined, such as the dehydration reactions of alcohols [261], addition-dissociation reactions of ketones [190] and CO₂ elimination reactions [246,248] of carbonates, as mentioned in this paper.

In addition to the aforementioned experimental and theoretical investigations, advanced mathematical methods leading to more reliable models are highly desired. These include new automated mechanism generation methods, experimental design based on model analysis, and physics-based artificial intelligence methodologies. Moreover, the advances of UQ and model optimization techniques can significantly enhance the predictive accuracy. Suitable and efficient methods for simplifying intricate mechanisms can substantially reduce computational costs, thereby adapting to the practical application of biofuels in energy systems.

CRediT authorship contribution statement

Xiao Liu: Writing - original draft, Methodology, Investigation, Conceptualization. Chung K. Law: Writing - review & editing. Bin Yang: Writing - review & editing, Investigation, Funding acquisition, Conceptualization.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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