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At least 19 records

Materials Data on Li(YSi)2 by Materials Project

Li(YSi)2 crystallizes in the tetragonal P4/mbm space group. The structure is three-dimensional. Li is bonded in a distorted square co-planar geometry to four equivalent Si atoms. All Li–Si bond lengths are 2.86 Å. Y is bonded in a 6-coordinate geometry to six equivalent Si atoms. There are two shorter (2.93 Å) and four longer (3.02 Å) Y–Si bond lengths. Si is bonded in a 9-coordinate geometry to two equivalent Li, six equivalent Y, and one Si atom. The Si–Si bond length is 2.39 Å.

36 MATERIALS SCIENCE↗

Materials Data on YSi by Materials Project

YSi crystallizes in the orthorhombic Cmcm space group. The structure is three-dimensional. Y is bonded in a 5-coordinate geometry to seven equivalent Si atoms. There are a spread of Y–Si bond distances ranging from 2.96–3.13 Å. Si is bonded in a 9-coordinate geometry to seven equivalent Y and two equivalent Si atoms. Both Si–Si bond lengths are 2.50 Å.

36 MATERIALS SCIENCE↗

Materials Data on YSI by Materials Project

YSI crystallizes in the hexagonal P-6 space group. The structure is three-dimensional. there are two inequivalent Y3+ sites. In the first Y3+ site, Y3+ is bonded in a trigonal planar geometry to three S2- and six I1- atoms. There are one shorter (2.62 Å) and two longer (2.63 Å) Y–S bond lengths. There are two shorter (3.64 Å) and four longer (3.68 Å) Y–I bond lengths. In the second Y3+ site, Y3+ is bonded in a trigonal planar geometry to three equivalent S2- and six equivalent I1- atoms. All Y–S bond lengths are 2.62 Å. All Y–I bond lengths are 3.70 Å. There are two inequivalent S2- sites. In the first S2- site, S2- is bonded in a trigonal planar geometry to three Y3+ and six I1- atoms. There are four shorter (3.68 Å) and two longer (3.69 Å) S–I bond lengths. In the second S2- site, S2- is bonded in a trigonal planar geometry to three equivalent Y3+ and six equivalent I1- atoms. All S–I bond lengths are 3.65 Å. There are two inequivalent I1- sites. In the first I1- site, I1- is bonded to six Y3+ and six S2- atoms to form a mixture of distorted edge and face-sharing IY6S6 cuboctahedra. In the second I1- site, I1- is bonded to six equivalent Y3+ and six equivalent S2- atoms to form a mixture of distorted edge and face-sharing IY6S6 cuboctahedra.

36 MATERIALS SCIENCE↗

Materials Data on YSi by Materials Project

YSi crystallizes in the hexagonal P-62m space group. The structure is three-dimensional. Y is bonded to five Si atoms to form a mixture of edge and corner-sharing YSi5 square pyramids. There are four shorter (2.91 Å) and one longer (3.00 Å) Y–Si bond lengths. There are two inequivalent Si sites. In the first Si site, Si is bonded in a trigonal planar geometry to three equivalent Y atoms. In the second Si site, Si is bonded to six equivalent Y atoms to form a mixture of distorted edge, corner, and face-sharing SiY6 pentagonal pyramids.

36 MATERIALS SCIENCE↗

Materials Data on Ce(YSi)4 by Materials Project

CeY4Si4 crystallizes in the orthorhombic P2_12_12_1 space group. The structure is three-dimensional. Ce4+ is bonded to seven Si4- atoms to form distorted CeSi7 pentagonal bipyramids that share corners with four equivalent YSi6 octahedra, corners with six equivalent CeSi7 pentagonal bipyramids, corners with five YSi6 pentagonal pyramids, edges with three equivalent YSi6 pentagonal pyramids, faces with two equivalent YSi6 octahedra, and faces with three YSi6 pentagonal pyramids. The corner-sharing octahedra tilt angles range from 44–55°. There are a spread of Ce–Si bond distances ranging from 3.02–3.67 Å. There are four inequivalent Y3+ sites. In the first Y3+ site, Y3+ is bonded to six Si4- atoms to form YSi6 octahedra that share corners with four equivalent YSi6 octahedra, corners with four equivalent CeSi7 pentagonal bipyramids, corners with six YSi6 pentagonal pyramids, faces with two equivalent CeSi7 pentagonal bipyramids, and faces with four YSi6 pentagonal pyramids. The corner-sharing octahedra tilt angles range from 55–56°. There are a spread of Y–Si bond distances ranging from 2.90–3.24 Å. In the second Y3+ site, Y3+ is bonded to six Si4- atoms to form distorted YSi6 pentagonal pyramids that share corners with three equivalent YSi6 octahedra, corners with four equivalent CeSi7 pentagonal bipyramids, corners with four equivalent YSi6 pentagonal pyramids, edges with three equivalent YSi6 pentagonal pyramids, faces with two equivalent YSi6 octahedra, faces with two equivalent CeSi7 pentagonal bipyramids, and a faceface with one YSi6 pentagonal pyramid. The corner-sharing octahedral tilt angles are 40°. There are a spread of Y–Si bond distances ranging from 2.83–3.01 Å. In the third Y3+ site, Y3+ is bonded to six Si4- atoms to form distorted YSi6 pentagonal pyramids that share corners with three equivalent YSi6 octahedra, a cornercorner with one CeSi7 pentagonal bipyramid, corners with four equivalent YSi6 pentagonal pyramids, edges with three equivalent CeSi7 pentagonal bipyramids, edges with three equivalent YSi6 pentagonal pyramids, faces with two equivalent YSi6 octahedra, a faceface with one CeSi7 pentagonal bipyramid, and a faceface with one YSi6 pentagonal pyramid. The corner-sharing octahedra tilt angles range from 39–40°. There are a spread of Y–Si bond distances ranging from 2.85–3.00 Å. In the fourth Y3+ site, Y3+ is bonded in a 6-coordinate geometry to six Si4- atoms. There are a spread of Y–Si bond distances ranging from 3.02–3.14 Å. There are four inequivalent Si4- sites. In the first Si4- site, Si4- is bonded in a 9-coordinate geometry to one Ce4+, seven Y3+, and one Si4- atom. The Si–Si bond length is 2.53 Å. In the second Si4- site, Si4- is bonded in a 9-coordinate geometry to two equivalent Ce4+, six Y3+, and one Si4- atom. The Si–Si bond length is 2.47 Å. In the third Si4- site, Si4- is bonded in a 8-coordinate geometry to two equivalent Ce4+, five Y3+, and one Si4- atom. In the fourth Si4- site, Si4- is bonded in a 9-coordinate geometry to two equivalent Ce4+, six Y3+, and one Si4- atom.

36 MATERIALS SCIENCE↗

Elucidating the Chemical Pathways Responsible for the Sooting Tendency of 1 and 2-phenylethanol

Yield Sooting Index (YSI) measurements have shown that oxygenated aromatic compounds (OACs) tend to have lower YSI than aromatic hydrocarbon (AHC) compounds. For example, typical AHCs such as toluene and ethyl benzene have a YSI of 170 and 216, respectively, in contrast, OACs such as phenol and anisole have a YSI of 81 and 111, respectively. However, this trend is not always true as was observed for the structural isomers 1-phenylethanol (1PE, YSI=142) and 2-phenylethanol (2PE, YSI=207), where 2PE contains a YSI more representative of AHCs than OACs. We applied flow reactor experiments and density functional theory (DFT) calculations to examine how oxygen functionality present in 1PE and 2PE alters the reaction pathways leading to the observed difference in soot formation. It was determined that the proximity of the oxygen functional group to the aromatic ring determines whether the oxygen remains attached to the primary reacting species (for 1PE) or is eliminated early in the combustion sequence (for 2PE). For these alcohols, preservation of the oxygen in the molecule leads to further OACs, while loss of the oxygen leads to AHCs and benzyl radical. The direct pathways to AHCs and benzyl radical result in the higher YSI observed for 2PE.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Sooting tendencies of 20 bio-derived fuels for advanced spark-ignition engines

The sooting tendencies of 20 bio-derived fuels indicated as potential blendstocks for spark-ignition engines by the Co-Optimization of Fuels & Engines (Co-Optima) Initiative are studied. The Yield Sooting Index (YSI) is used to quantify the sooting tendencies. The Co-Optima Chemical Model is used to predict the numerical YSIs for all test fuels, and these results are compared with measurements. Experimental YSIs are newly measured for 2 furans and are taken from our previous work for the other compounds. Overall, the predicted YSIs agree well with measurements, within the experimental uncertainties, except for 2,5-dimethylfuran (2,5-DMF). It is found that Polycyclic Aromatic Hydrocarbons (PAH) growth reactions have little influence on the relative soot production from each fuel and therefore on YSI predictions. A modified sensitivity coefficient formulation is proposed to evaluate reaction sensitivities specifically for YSI. This formulation is applied to the 2,5-DMF-doped flame, and six 2,5-DMF initial decomposition reactions, which lead to different major soot precursors, are identified as the most sensitive reactions. The impact of the chemical kinetic uncertainties embedded in these reactions is quantified by randomly perturbing their reaction rates within a factor of two. The resulting prediction uncertainty in the 2,5-DMF-doped flame is found to be ± 8 YSI units (±11%), which demonstrates that the test-fuel-specific decomposition reactions indeed have considerable influence on its YSI prediction. Our research suggests that more accurate kinetic parameters for fuel initial decomposition reactions can potentially improve YSI predictions effectively, without altering the YSI predictions of other fuels with significantly different molecular structures.

09 BIOMASS FUELS↗

Sooting tendencies of terpenes and hydrogenated terpenes as sustainable transportation biofuels

Terpenes are a diverse group of molecules that are synthesized by plants and microorganisms through combining units of isoprene (2-methyl-1,3-butadiene). They typically contain rings and methyl branches, which gives them high energy densities and low freezing points and makes them appealing candidates for sustainable transportation biofuels. Between the original biosynthesis and upgrading options such as hydrogenation, they have a large degree of freedom of structures, e.g., different carbon skeletons, positions of double bonds, and functional groups. Therefore, structure-property data is needed to downselect potential fuel candidates. Here, we measured the sooting tendencies of 17 C10 monoterpenes and 7 of their hydrogenated analogues. The hydrogenated compounds were custom synthesized, so the quantities were too small for conventional smoke point measurements. Thus, the sooting tendencies were quantified with yield sooting index (YSI), which is based on the soot yield in a fuel-doped non-premixed methane flame. Derived smoke points (DSPs) were estimated from a correlation between YSI and smoke point for other hydrocarbons. The YSI of terpenes and their derivatives varies widely from 85.6 to 248.5. The YSI follows the trend: terpenes > dihydroterpenes > tetrahydroterpenes. The DSPs of all the tetrahydroterpenes and some dihydroterpenes are higher than that of a Jet-A fuel sample, suggesting that they offer soot reduction benefits. Further, the YSIs depend strongly on molecular structure; for example, α-pinene and β-pinene have identical carbon skeletons and differ only in the position of one carbon-carbon double bond, but the YSI of α-pinene is 34% higher than that of β-pinene. Detailed decomposition analysis via density functional theory (DFT) suggests that compared with β-pinene, α-pinene requires fewer steps to form the first aromatic ring and the process is more thermodynamically favorable. The YSI difference between the pinenes is mainly affected by the identity of the products from the dominant decomposition pathways.

09 BIOMASS FUELS↗

Reactive Molecular Dynamics Simulations and Quantum Chemistry Calculations To Investigate Soot-Relevant Reaction Pathways for Hexylamine Isomers

Sooting tendencies of a series of nitrogen-containing hydrocarbons (NHCs) have been recently characterized experimentally using the yield sooting index (YSI) methodology. This work aims to identify soot-relevant reaction pathways for three selected C6H15N amines, namely, dipropylamine (DPA), diisopropylamine (DIPA), and 3,3-dimethylbutylamine (DMBA) using ReaxFF molecular dynamics (MD) simulations and quantum mechanical (QM) calculations and to interpret the experimentally observed trends. ReaxFF MD simulations are performed to determine the important intermediate species and radicals involved in the fuel decomposition and soot formation processes. QM calculations are employed to extensively search for chemical reactions involving these species and radicals based on the ReaxFF MD results and also to quantitatively characterize the potential energy surfaces. Specifically, ReaxFF simulations are carried out in the NVT ensemble at 1400, 1600, and 1800 K, where soot has been identified to form in the YSI experiment. These simulations account for the interactions among test fuel molecules and pre-existing radicals and intermediate species generated from rich methane combustion, using a recently proposed simulation framework. ReaxFF simulations predict that the reactivity of the amines decrease in the order DIPA > DPA > DMBA, independent of temperature. Both QM calculations and ReaxFF simulations predict that C2H4, C3H6, and C4H8 are the main nonaromatic soot precursors formed during the decomposition of DPA, DIPA, and DMBA, respectively, and the associated reaction pathways are identified for each amine. Both theoretical methods predict that sooting tendency increases in the order DPA, DIPA, and DMBA, consistent with the experimentally measured trend in YSI. This work demonstrates that sooting tendencies and soot-relevant reaction pathways of fuels with unknown chemical kinetics can be identified efficiently through combined ReaxFF and QM simulations. Overall, predictions from ReaxFF simulations and QM calculations are consistent, in terms of fuel reactivity, major intermediates, and major nonaromatic soot precursors.

fuel decomposition↗

A comparison of computational models for predicting yield sooting index

Sooting propensity, a measurement of how much particulate matter is produced when a fuel is burned, is a property of significant interest among researchers who are striving to discover the next generation of cleaner, more efficient fuels and fuel additives. Many compounds are not viable as fuels and/or fuel additives, and as a result, designing cleaner-burning biofuels using only experimental techniques is inefficient. Predictive models have been instrumental in reducing this inherent difficulty, providing researchers with a tool to preemptively screen compounds before production and testing. The present work compares the accuracies and interpretabilities of existing models used to predict a particular measure of sooting propensity, Yield Sooting Index (YSI). These models include artificial neural networks, graph neural networks, and multivariate equations. A novel equation for predicting YSI based on atom path count and bond order is proposed, which can highlight key structural components that contribute to YSI. It was found that artificial neural networks slightly outperform graph neural networks and greatly outperform multivariate equations in blind (test set) prediction accuracy; however, graph neural networks and multivariate equations provide significantly more interpretability as to how compound structure relates to YSI. Predictions of YSI are compared to experimental measurements for previously un-tested compounds with cetane numbers comparable to diesel fuel (50-60) (butyl decanoate, ethyl decanoate, 1,4-bis(ethenoxymethyl)cyclohexane, and 5-heptyloxolan-2-one), and it was found that these compounds produce significantly less soot compared to diesel fuel.

09 BIOMASS FUELS↗

Soot and PAH formation in high pressure spray pyrolysis of gasoline and diesel fuels

Time-resolved soot and PAH formation from gasoline and diesel spray pyrolysis are visualized and quantified using diffuse back illumination (DBI) and laser induced fluorescence (LIF) at 355 nm, respectively, in a constant-volume vessel at 60 bar from 1400 to 1700 K for up to 30 ms. The delay, maximum formation rate, and yield of soot and PAHs are compared across fuels and temperatures and correlated with the yield sooting indices on either the mass or mole basis. The delays generally decrease with increasing temperature, and the formation rates of both PAHs and soot generally increase with temperature. The apparent PAH-LIF yield may decrease with temperature due to PAH growth and conversion into larger species, signal trapping, and thermal quneching. Soot yield generally increases with temperature. The mass-based YSI correlates reasonably well with soot delay, but YSI does not correlate well with soot yield. Here, the mass-based YSI is a more appropriate predictor of sooting propensity than the mole-based YSI.

42 ENGINEERING↗

Flow Reactor Study of the Soot Precursors of Novel Cycloalkanes as Synthetic Jet Fuel Compounds: Octahydroindene, p -Menthane, and 1,4-Dimethylcyclooctane

Sustainable aviation fuels (SAFs) or Synthetic aviation turbine fuels (SATFs) derived from nonpetroleum sources are essential for energy security and a strong rural and agricultural economy. Airplanes operating on SAF can have lower particle emissions compared to those of conventional jet fuel, reducing air quality impacts near airports. Processing biobased isoprene or wood and agricultural waste can produce cycloalkane-rich fuels with properties meeting ASTM International’s SATF requirements. The unique structures of these cycloalkanes yield lower soot emissions because of their lack of aromatic rings. We measured the soot formation tendency as yield sooting index (YSI) and used laminar flow reactor experiments to evaluate soot precursors formed for isoprene-derived compounds p-menthane and 1,4-dimethylcyclooctane (DMCO), and octahydroindene (OHI)─ produced from woody biomass via catalytic fast pyrolysis. The combustion chemistry of the OHI and DMCO has not been previously studied. Experiments were conducted at 10 bar from 800 to 1200 K, equivalence ratios of 1.0 and 3.0, and residence times of 1.0 and 0.6 s, respectively. Experimentally detected species were used to elucidate the mechanisms of soot precursor formation. OHI exhibited the highest YSI (94.5) and formed a high concentration of benzene primarily by direct dehydrogenation of the six-membered ring. p-Menthane (YSI 92.0) and DMCO (YSI 85.0) oxidation products included fewer aromatic components but higher benzene precursors, including 1,3-butadiene, propyne, and allene. This suggests that the ring-opening pathway is dominant over the dehydrogenation pathway in the benzene formation for these compounds. This experimental speciation provides insight into the influence of the cycloalkane structure on the sooting tendencies of potential SAF blend components, thereby aiding in fuel design processes.

09 BIOMASS FUELS↗

A numerical study on the sooting tendencies of bio-derived fuels for spark-ignition engines

While more efficient vehicles have been developed over the decades, their performance is limited by the properties of existing fuels. In response, the Co-Optimization of Fuels and Engines Initiative (Co-Optima) under the U.S. Department of Energy (DOE) has developed a rigorous screening approach to identify the most promising biomass-derived blendstocks that are suitable for advanced spark-ignition (SI) engines. A detailed kinetic model has also been developed to predict the combustion properties of the selected blendstocks. This kinetic model has been designed mainly targeting ignition and flame propagation properties, and it has not previously been validated for soot formation. In this work, we numerically predicted the sooting tendency of 20 Co-Optima SI blendstocks using the Co-Optima kinetic model. The sooting tendencies are determined quantitatively using the Yield Sooting Index (YSI) methodology. As shown in Fig. 1, the predicted YSIs show good agreement with measurements, except for 2,5-dimethylfuran. We also quantify the sensitivity of the YSI predictions to aromatic growth reactions and fuel decomposition reactions of the test fuels. It is found that PAH growth reactions have little impact on YSIs for all 20 fuels under investigation. On the other hand, fuel decomposition reactions have a significant influence on the YSI of 2,5-dimethylfuran. Perturbing their reaction rates by a factor of two is shown to lead to 11 % YSI prediction uncertainty.

09 BIOMASS FUELS↗

Post-fire time series of sensor and geochemistry sample data from surface water, groundwater, precipitation, soil, and vegetation across Oak Creek watershed, Washington

This dataset supports a broader study examining wildfire impacts on hydrologic connectivity across 5 sites within the Oak Creek watershed and the resulting biogeochemical impacts. Stream sites were selected using the Advanced Terrestrial Simulator (ATS) hydrologic model to identify locations with varying groundwater contributions and hydrologic responses across different burn severity scenarios. The Retreat Fire burned from July 23 to August 2 in 2024, affecting the five study sites at varying burn severities. Each site is equipped with YSI EXO2 sondes logging sub-hourly throughout the year, and grab samples are collected approximately every six weeks. YSI sondes are used to measure temporally resolved proxies for groundwater inputs (specific conductivity) and organic matter (fluorescent dissolved organic matter; fDOM) along with basic water quality and depth. Grab samples of surface water, groundwater, and precipitation are analyzed for water stable isotopes and conductivity to understand endmembers for hydrologic mixing Grab samples of surface water, groundwater, soil water, and litter/vegetation/soil leachates are analyzed for organic matter composition measured by Fourier-Transform Ion Cyclotron Resonance Mass Spectrometry (FTICR-MS) to understand organic matter dynamics. Game camera photos are provided in a separate data package available at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/3018598. Future versions of this dataset will include time series data from YSI EXO2 sondes (fDOM, dissolved oxygen, temperature, depth, specific conductance, turbidity, pH), BaroTROLL sensors (air temperature and barometric pressure), rain gauges (precipitation), and data from the soil and vegetation samples. Because this study is ongoing, this data package will be updated regularly to include newly collected data and the additional data types. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. In addition to a readme, this data package also includes a file-level metadata (FLMD) file that describes each file and a data dictionary (DD) that describes all column/row headers and variable definitions. This dataset is comprised of (1) a folder of field photos; (2) a folder of surface water sample data; (3) a folder of raw Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) data; (4) a data checks report; (5) file-level metadata; (6) data dictionary; (7) field metadata; (8) readme; (9) international generic sample number (IGSN) mapping file; and (10) field protocols. The sample data subfolder contains (1) dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC) data and averages; (2) total dissolved nitrogen data and averages; (3) stable water isotopes and averages; (4) methods codes; (5) FTICR-MS methods; and (15) a subfolder of 9.4 Tesla (9.4T) FTICR-MS data. This folder contains the processed data and three subfolders, one containing the .xml files, one containing the water CoreMS output files, and the other containing instructions and scripts for processing the files in CoreMS (https://github.com/EMSL-Computing/CoreMS). All files are .csv, .pdf, .R, .xml, .d, .html, .Rmd, .py, .cal, .json, .jpg, .jpeg, .png, .mov, or .mp4.

Biogeochemistry↗

Materials Data on Y2TiSi2 by Materials Project

Ti(YSi)2 crystallizes in the tetragonal P4/mmm space group. The structure is zero-dimensional and consists of one titanium molecule and two YSi clusters. In each YSi cluster, Y3+ is bonded in a single-bond geometry to one Si4- atom. The Y–Si bond length is 2.66 Å. Si4- is bonded in a single-bond geometry to one Y3+ atom.

36 MATERIALS SCIENCE↗

Investigation of structural effects of aromatic compounds on sooting tendency with mechanistic insight into ethylphenol isomers

Small aromatic molecules with oxygen-containing functional groups are a promising class of fuel additives, as they can be readily sourced from depolymerized lignin. These oxygenated aromatic compounds (OACs) show a lower sooting tendency than aromatic hydrocarbons, but OACs having alkyl groups such as ethylphenol show a higher sooting tendency than other OACs such as phenol and anisole, despite the oxygen moiety. In this study, we investigate the relationship between chemical structure and soot precursor formation to explain observed differences in the sooting tendency of OACs and to gain insight into how alkyl or oxygenated substituents on the aromatic ring affect soot precursor formation. The weakest bond for 15 aromatic compounds was identified and cleavage of these bonds was shown to generate either benzyl or phenoxy radicals. A linear relationship between standard enthalpy of formation (ΔH f o ) of these radicals and the yield sooting index (YSI) was found, and thus ΔH f ° can be applied as a metric to estimate YSIs of various aromatic compounds; higher ΔH f o of a radical indicates an increase in the radical reactivity and leads to more soot precursor formation. Flow reactor experiments were performed for 2-ethylphenol and 3-ethylphenol to elucidate how ortho and meta substitution effects the sooting tendency. Soot precursors were identified from the experiment and their formation pathways were investigated computationally. 2-ethylphenol produces more oxygenated products than 3-ethylphenol since the ortho position has increased resonance stabilization of radical intermediates, which leads to lower YSI. Overall, these results further inform the selection of potential biomass-derived fuel blendstocks that have favorable sooting tendencies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Predicting the Cetane Number, Sooting Tendency, and Energy Density of Terpene Fuel Additives

Abstract Discovering renewable fuels and fuel additives is paramount in reducing carbon emissions from internal combustion engines. Terpenes, a group of compounds that can be synthesized from plant matter and microorganisms, have gained significant interest in recent years as promising candidates for fuels/additives. Terpenes are a diverse class of compounds that contain rings and methyl branches, resulting in high energy densities and optimal cold weather behavior. Their variation in bond order, carbon chains, and functional groups lead to varying degrees of soot formation and performance in existing engines. The present work leverages predictive models, namely artificial neural networks, to predict the cetane number (CN), sooting tendency (quantified with yield sooting index, YSI), and energy density (quantified with lower heating value, LHV) of terpenes and hydrogenated terpenes whose sooting propensities were previously determined through experimental means. Predicted sooting propensities of these terpenes are compared with experimental values, and predicted cetane numbers and energy densities are used to comment on the compounds’ ability to act as fuels/additives. Expected prediction errors for CN, YSI, and LHV, defined by blind test set median absolute error, are within 5.56 cetane units, 3.63 yield sooting index units, and 0.77 MJ/kg respectively. Additionally, the present work investigates a variety of correlation/dependence metrics for property-property relationships, furthering our understanding of how combustion-relevant properties are related.

09 BIOMASS FUELS↗