Inverse gas chromatography for natural fibre characterisation: Identification of the critical parameters to determine the Brunauer-Emmett-Teller specific surface area

Legras, A., Kondor, A., Heitzmann, M.T. and Truss, R.W. (2015) Inverse gas chromatography for natural fibre characterisation: Identification of the critical parameters to determine the Brunauer-Emmett-Teller specific surface area. Journal of Chromatography A, 1425 273-279. doi:10.1016/j.chroma.2015.11.033

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Author Legras, A.
Kondor, A.
Heitzmann, M.T.
Truss, R.W.
Title Inverse gas chromatography for natural fibre characterisation: Identification of the critical parameters to determine the Brunauer-Emmett-Teller specific surface area
Journal name Journal of Chromatography A   Check publisher's open access policy
ISSN 1873-3778
0021-9673
Publication date 2015-11-18
Year available 2015
Sub-type Article (original research)
DOI 10.1016/j.chroma.2015.11.033
Open Access Status File (Author Post-print)
Volume 1425
Start page 273
End page 279
Total pages 7
Place of publication Amsterdam, Netherlands
Publisher Elsevier
Language eng
Subject 1602 Analytical Chemistry
1303 Biochemistry
1605 Organic Chemistry
Abstract Inverse gas chromatography (IGC) is an alternative technique to determine the specific surface area of natural fibres. Natural fibres have a complex surface chemistry and unique microstructure that challenge the current capabilities to perform surface characterisation. This study investigated the influence of multiple parameters on the measured Brunauer–Emmett–Teller (BET) specific surface area for samples of flax, kenaf and BioMid cellulose fibres using IGC. The BET surface area of kenaf and flax differed with 0.51 m g and 1.35 m g respectively, the former being similar to the cellulose fibres (0.54 m g). The data was calculated under conditions where the BET equation showed good linearity (R ⩾ 0.995). Repeatability was excellent so that two runs sufficed to obtain representative BET surface area values. The findings showed the choice of solvent was important for all specimens to avoid any misleading data comparison due to molecular orientation effects that impact the adsorbent–adsorbate interactions. The higher surface area of the flax sample, and its higher variability, was correlated with a higher surface roughness observed under optical microscopy. Packing the chromatography column with long or chopped fibres produced results that were statistically insignificant.
Formatted abstract
Inverse gas chromatography (IGC) is an alternative technique to determine the specific surface area of natural fibres. Natural fibres have a complex surface chemistry and unique microstructure that challenge the current capabilities to perform surface characterisation. This study investigated the influence of multiple parameters on the measured Brunauer–Emmett–Teller (BET) specific surface area for samples of flax, kenaf and BioMid® cellulose fibres using IGC. The BET surface area of kenaf and flax differed with 0.51 m2 g−1 and 1.35 m2 g−1 respectively, the former being similar to the cellulose fibres (0.54 m2 g−1). The data was calculated under conditions where the BET equation showed good linearity (R2 ⩾ 0.995). Repeatability was excellent so that two runs sufficed to obtain representative BET surface area values. The findings showed the choice of solvent was important for all specimens to avoid any misleading data comparison due to molecular orientation effects that impact the adsorbent–adsorbate interactions. The higher surface area of the flax sample, and its higher variability, was correlated with a higher surface roughness observed under optical microscopy. Packing the chromatography column with long or chopped fibres produced results that were statistically insignificant.
Keyword Brunauer-Emmett-Teller theory
Inverse gas chromatography
Natural fibres
Specific surface area
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: School of Mechanical & Mining Engineering Publications
Official 2016 Collection
 
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Citation counts: TR Web of Science Citation Count  Cited 3 times in Thomson Reuters Web of Science Article | Citations
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