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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/13206

Title: A statistical data-processing methodology of Py-GC/MS data for the simulation of flash co-pyrolysis reactor experiments
Authors: Cornelissen, Tom
Molenberghs, Geert
Jans, Maarten
Yperman, Jan
Schreurs, Sonja
Carleer, Robert
Issue Date: 2012
Publisher: ELSEVIER SCIENCE BV
Citation: CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS, 110(1), p. 123-128
Abstract: Practically it is extremely difficult to collect observations following a fully sound statistical design, typically encompassing a high number of repetitions, of an intensive and elaborate experimental procedure such as flash pyrolysis reactor experiments. Pyrolysis-gas chromatography/mass spectrometry (Py-GC/MS) is an extremely useful analytical technique in order to simulate a high number of repetitive pyrolysis experiments in an acceptable time span. Combining Py-GC/MS experiments and statistical data processing, conclusions can be drawn on the pyrolysis behaviour of any input material, supplying crucial information on its respective behaviour during the actual flash pyrolysis experiments. In this research Py-GC/MS experiments combined with a tailored statistical data processing methodology strongly indicate the occurrence of synergetic interactions during the flash co-pyrolysis of willow/polyhydroxybutyrate (PHB) blends. Such interactions are also indicated by pattern recognition and by the analysis of the condensable and noncondensable pyrolytic gases obtained from Py-GC/MS. Accordingly, the actual influence of the flash co-pyrolysis of willow and PHB, executed with a semi-continuous pyrolysis reactor, on the pyrolytic oil features is investigated by GC/MS. Based on these experiments an explanation for the observed synergy during flash co-pyrolysis of willow and PHB is proposed. (C) 2011 Elsevier B.V. All rights reserved.
Notes: [Cornelissen, Tom; Yperman, Jan; Carleer, Robert] Hasselt Univ, CMK, Res Grp Appl & Analyt Chem, B-3590 Diepenbeek, Belgium. [Molenberghs, Geert] Hasselt Univ, Ctr Stat, B-3590 Diepenbeek, Belgium. [Molenberghs, Geert] Katholieke Univ Leuven, Ctr Biostat, B-3000 Louvain, Belgium. [Jans, Maarten; Schreurs, Sonja] XIOS, Dept TIW, B-3590 Diepenbeek, Belgium.
URI: http://hdl.handle.net/1942/13206
DOI: 10.1016/j.chemolab.2011.10.011
ISI #: 000299712500015
ISSN: 0169-7439
Category: A1
Type: Journal Contribution
Validation: ecoom, 2013
Appears in Collections: Institute for Materials Research
Centre for Statistics
Research Institute Center for Statistics
Applied and Analytical Chemistry

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