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Enregistrement W2145913472 · doi:10.1071/ch02188

New Developments and Applications of Solvent-Free Sampling and Sample Preparation Technologies for the Investigation of Living Systems

2003· article· en· W2145913472 sur OpenAlexaff
Janusz Pawliszyn

Notice bibliographique

RevueAustralian Journal of Chemistry · 2003
Typearticle
Langueen
DomaineChemistry
ThématiqueAnalytical chemistry methods development
Établissements canadiensUniversity of Waterloo
Organismes subventionnairesnon disponible
Mots-clésAnalyteSample preparationCoatingSampling (signal processing)Process engineeringSample (material)Solid-phase microextractionChemistryBioanalysisMatrix (chemical analysis)ChromatographyNanotechnologyComputer scienceMaterials scienceEngineeringMass spectrometryGas chromatography–mass spectrometry

Résumé

récupéré en direct d'OpenAlex

In recent years there has been considerable interest in developing techniques to monitor levels of biologically active compounds in living systems in natural environments. These efforts represent a significant departure from conventional ‘sampling’ techniques, where a portion of the system under study is removed from its natural environment, and the compounds of interest extracted and analyzed in a laboratory environment. An in vivo sampling approach can eliminate errors and reduce the time associated with sample transport and storage, and can therefore result in the collection of more accurate, precise, and faster analytical data. An ideal in vivo sampling technique should be portable, solvent-free, and offer integration of the sampling, sample preparation and sample analysis steps. These requirements are met by two techniques based on coated fibre and membrane technologies, presently under development in our laboratory.[1] Fibre solid-phase microextraction (fibreSPME) involves exposing a polymer-coated fused silica fibre to a sample. The analytes partition into the fibre coating until an equilibrium is reached. The fibre is then removed from the solution and the analytes are desorbed in the injector or injection loop of an analytical instrument such as a gas chromatograph (GC). The fibre is contained in a syringe-like device to facilitate handling.[2] Fibre-SPME can be used for both spot and time-averaged sampling. For spot sampling, the fibre is typically exposed to a sample matrix until the partitioning equilibrium between sample matrix and the coating material is reached. In the time-averaged technique the fibre remains in the needle during exposure of the SPME device to the sample. The fibre coating works as a trap for analytes that diffuse into the needle. In membrane extraction with a sorbent interface (MESI) a polymeric hollow fibre or a flat sheet membrane, in contact with a sample, is fitted directly into the carrier gas line of a GC equipped with a sorbent trap.[3]Analytes partition into the polymeric phase of the membrane and, after diffusion through the membrane, are carried by the gas to the sorbent trap. The concentrated analytes are periodically delivered onto the front of the column by a thermal pulse. MESI is a dynamic system, where the rate of analyte intake is dependent on both the diffusion coefficients of analytes in the membrane material and the membrane/sample matrix distribution constant. Similar to fibre-SPME, MESI can be used for both spot and time averaged monitoring. Both fibre-SPME and MESI techniques integrate sampling, sample preparation, and sample introduction to the analytical instrument, into a simple procedure. In fibreSPME mechanical movement of the fibre is necessary, as the sampling and sample introduction steps are separated in space, allowing one instrument to analyse large numbers of fibres. MESI, on the other hand, requires a dedicated, permanently attached instrument to one or several membrane/sorbent systems, eliminating the need for mechanical movement and therefore reducing the possibility of failure. MESI is thus suitable for continuous operation, allowing conversion of the analytical separation and detection instrument into a sensor-like device suitable for monitoring operations. Calibration procedures can be made very simple in both methods. For example, in air monitoring, the air/coating distribution constant can be estimated using the linear temperature-programmed retention index system (LTPRI). This allows quantification, even without identification, as long as the stationary phase used in the analytical column is identical to the fibre coating. The diffusion coefficient can be calculated by knowing the molecular weight of the target compound. To facilitate analysis of very polar analytes, a derivatization procedure can be used. For example, the validation field measurement of formaldehyde in ambient air, using both spot and time average sampling, was conducted using several techniques. Similar results were obtained for this challenging analyte using fibre-SPME and other more established procedures.[4]

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,003
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: Expérimental (laboratoire)
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,324
Score d'incertitude au seuil0,431

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,003
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,056
Tête enseignante GPT0,316
Écart entre enseignants0,260 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeExpérimental (laboratoire)
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations11
Publié2003
Routes d'admission1
Résumé présentoui

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