Assessment\nof Accelerated Aging Effect of Bio-Oil\nFractions Utilizing Ultrahigh-Resolution Mass Spectrometry and k‑Means\nClustering of van Krevelen Compositional Space

Bio-oils contain a substantial number of highly oxygenated\nhydrocarbons,\nwhich often exhibit low thermal stability during storage, handling,\nand refining. The primary objectives of this study are to characterize\nthe hydroxyl group in bio-oil fractions and to investigate the relationship\nbetween the type of hydroxyl group and accelerated aging behavior.\nA bio-oil was fractionated into five solubility-based fractions, classified\nin two main groups: water-soluble and water-insoluble fractions. These\nfractions were then subjected to chemoselective reactions to tag molecules\ncontaining hydroxyl groups and analyzed by negative-ion electrospray\nionization 21 T Fourier transform ion cyclotron resonance mass spectrometry\n(FT-ICR MS). The fractions were also subjected to accelerated aging\nexperiments and characterized by FT-ICR MS and bulk viscosity measurements.\nExtracting insightful information from ultrahigh-resolution data to\naid in predicting upgrading methodologies and instability behaviors\nof bio-oils is challenging due to the complexity of the data. To address\nthis, an unsupervised learning technique, k-means clustering analysis,\nwas used to semiquantify molecular compositions with a close Euclidean\ndistance within the (<i>O</i>/<i>C</i>, <i>H</i>/<i>C</i>) chemical space. The combination of\nk-means analysis with findings from chemoselective reactions allowed\nthe distinctive hydroxyl functionalities across the samples to be\ninferred. Our results indicate that the hexane-soluble fraction contained\nnumerous molecules containing primary and secondary alcohols, while\nthe water-soluble fraction displayed diverse groups of oxygenated\ncompounds, clustered near to carbohydrate-like and pyrolytic humin-like\nmaterials. Despite its high oxygen content, the water-soluble fraction\nshowed minimal changes in viscosity during aging. In contrast, a significant\nincrease in viscosity was observed in the water-insoluble materials,\nspecifically, the low- and high-molecular-weight lignin fractions\n(LMWL and HMWL, respectively). Among these two fractions, the HMWL\nexhibited the highest increase in viscosity after only 4 h of accelerated\naging. Our results indicate that this aging behavior is attributed\nto an increased number of molecular compositions containing phenolic\ngroups. Thus, the chemical compositions within the HMWL are the major\ncontributors to the viscosity changes in the bio-oil under accelerated\naging conditions. This highlights the crucial role of oxygen functionality\nin bio-oil aging, suggesting that a high oxygen content alone does\nnot necessarily correlate with an increase of viscosity. Unlike other\nbio-oil categorization methods based on constrained molecule locations\nwithin the van Krevelen compositional space, k-means clustering can\nidentify patterns within ultrahigh-resolution data inherent to the\nunique chemical fingerprint of each sample.

Publication Details

Journal
Figshare
Published
2024-08-20
DOI
https://doi.org/10.1021/acs.energyfuels.4c02605.s002
Primary Topic
Plant pathogens and resistance mechanisms
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Assessment\nof Accelerated Aging Effect of Bio-Oil\nFractions Utilizing Ultrahigh-Resolution Mass Spectrometry and k‑Means\nClustering of van Krevelen Compositional Space

Figshare
Plant pathogens and resistance mechanisms
article

Assessment\nof Accelerated Aging Effect of Bio-Oil\nFractions Utilizing Ultrahigh-Resolution Mass Spectrometry and k‑Means\nClustering of van Krevelen Compositional Space

article en

Abstract

Bio-oils contain a substantial number of highly oxygenated\nhydrocarbons,\nwhich often exhibit low thermal stability during storage, handling,\nand refining. The primary objectives of this study are to characterize\nthe hydroxyl group in bio-oil fractions and to investigate the relationship\nbetween the type of hydroxyl group and accelerated aging behavior.\nA bio-oil was fractionated into five solubility-based fractions, classified\nin two main groups: water-soluble and water-insoluble fractions. These\nfractions were then subjected to chemoselective reactions to tag molecules\ncontaining hydroxyl groups and analyzed by negative-ion electrospray\nionization 21 T Fourier transform ion cyclotron resonance mass spectrometry\n(FT-ICR MS). The fractions were also subjected to accelerated aging\nexperiments and characterized by FT-ICR MS and bulk viscosity measurements.\nExtracting insightful information from ultrahigh-resolution data to\naid in predicting upgrading methodologies and instability behaviors\nof bio-oils is challenging due to the complexity of the data. To address\nthis, an unsupervised learning technique, k-means clustering analysis,\nwas used to semiquantify molecular compositions with a close Euclidean\ndistance within the (<i>O</i>/<i>C</i>, <i>H</i>/<i>C</i>) chemical space. The combination of\nk-means analysis with findings from chemoselective reactions allowed\nthe distinctive hydroxyl functionalities across the samples to be\ninferred. Our results indicate that the hexane-soluble fraction contained\nnumerous molecules containing primary and secondary alcohols, while\nthe water-soluble fraction displayed diverse groups of oxygenated\ncompounds, clustered near to carbohydrate-like and pyrolytic humin-like\nmaterials. Despite its high oxygen content, the water-soluble fraction\nshowed minimal changes in viscosity during aging. In contrast, a significant\nincrease in viscosity was observed in the water-insoluble materials,\nspecifically, the low- and high-molecular-weight lignin fractions\n(LMWL and HMWL, respectively). Among these two fractions, the HMWL\nexhibited the highest increase in viscosity after only 4 h of accelerated\naging. Our results indicate that this aging behavior is attributed\nto an increased number of molecular compositions containing phenolic\ngroups. Thus, the chemical compositions within the HMWL are the major\ncontributors to the viscosity changes in the bio-oil under accelerated\naging conditions. This highlights the crucial role of oxygen functionality\nin bio-oil aging, suggesting that a high oxygen content alone does\nnot necessarily correlate with an increase of viscosity. Unlike other\nbio-oil categorization methods based on constrained molecule locations\nwithin the van Krevelen compositional space, k-means clustering can\nidentify patterns within ultrahigh-resolution data inherent to the\nunique chemical fingerprint of each sample.

Figshare
Openalex Percentile: Top 40%
Plant pathogens and resistance mechanisms
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.