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Enregistrement W2739051192 · doi:10.1149/ma2017-02/11/762

Remote Imaging of the Buried Interface Using AFM-IR

2017· article· en· W2739051192 sur OpenAlexaff
S.B. Lyon, Suzanne Morsch, Simon R. Gibbon

Notice bibliographique

RevueECS Meeting Abstracts · 2017
Typearticle
Langueen
DomaineEngineering
ThématiqueAcoustic Wave Resonator Technologies
Établissements canadiensAkzoNobel (Canada)
Organismes subventionnairesnon disponible
Mots-clésKelvin probe force microscopeCorrosionScanning probe microscopyMaterials scienceMicroscopyCoatingScanning electrochemical microscopyInfrared microscopyScanning thermal microscopyNanoscopic scaleDielectric spectroscopyOptical microscopeComposite materialScanning electron microscopeAnalytical Chemistry (journal)NanotechnologyElectrodeOpticsElectrochemistryChemistryAtomic force microscopy

Résumé

récupéré en direct d'OpenAlex

The degradation of corrosion-resistant organic coatings continues to present an analytical challenge to corrosion scientists. This is because failures in corrosion protection are localised events, whereas coating analysis is predominately performed using bulk methodologies (e.g., vibrational spectroscopy, thermal analysis). This is compounded by the paucity of non-destructive techniques capable of detecting and characterising localised coating failure in the early stages (i.e., able to pinpoint the appearance of buried pitting sites, de-adhesion processes or blistering). Ex-situ microscopy has conventionally been used to characterise corrosion phenomena beneath organic coatings. However, physical sectioning precludes meaningful chemical analysis of the polymer at failure sites. Emerging non-destructive approaches that allow direct detection of corrosion at the buried interface include: acoustic microscopy, local electrochemical techniques (e.g. scanning Kelvin probe microscopy, the scanning vibrating electrode and local electrochemical impedance measurements) and can be employed to monitor corrosion of a buried substrate in situ. Whilst these can examine buried corrosion phenomena, little or no information is obtained about the overlying coating. Alternative techniques with improved resolution utilise scanning probe microscopy (SPM) methods (e.g. Kelvin probe force microscopy, KPFM) whilst detailed topographic images of the overlying coating may be simultaneously collected. More recently, SPM has been coupled to vibrational spectroscopy and allows direct nanoscale mapping of functional group chemistry. AFM-IR is a particularly versatile approach, whereby sub-diffraction limit detection of infrared absorbance is achieved by monitoring the deflection of an AFM probe in response to photo-thermal expansion of the sample. During AFM-IR measurements, the sample is illuminated by a rapidly pulsed tuneable infrared source, (an optical parametric oscillator, 10 ns pulses at a repetition rate of 1 KHz.) Upon absorbance of the infrared radiation, transient thermal expansion of the sample induces a contact-mode AFM probe to oscillate at its resonant frequency. A plot of the amplitude of oscillations as a function of infrared wavelength yields spectra that closely match conventional transmission-mode FTIR. Here we examine the degradation of model epoxy-phenolic can coatings on electrolytic chrome-coated steel (ECCS). Substrate materials were mechanically abraded successively to 1200 grit, then polished to 0.25 µm diamond paste to achieve a mirror-like surface finish. Stoichiometric epoxy-phenolic coatings were prepared by adding 1,1,1-tris(4-hydroxyphenyl) ethane to bisphenol-A diglycidyl ether (epoxide equivalent weight 172-176 g mol -1 ) using tetrabutylphosphonium bromide as catalyst. Coatings were spin-coated onto the substrates at 2000 rpm then cured at 150 °C for 60 min. The final coating thickness was around 7 µm. AFM-IR was performed on a NanoIR2 system (Anasys Instruments). In order to induce corrosion the polished ECCS samples were contaminated by spraying with a saturated sodium chloride solution in ethanol prior to coating. Corrosion was then initiated by placing a droplet of deionised water on the coating surface for 5 minutes, after which it was dried. Examination of the sample by optical microscopy subsequently revealed isolated patches of underfilm discolouration discernible through the coating (a). However, no corresponding change in the coating morphology was observed in AFM height images (b), and infrared amplitude maps obtained at 1260 cm -1 (c) and 1604 cm -1 (d) also remained featureless, indicating that significant deformation of the coating had not taken place. In contrast, infrared maps gathered at 916 cm -1 (e) and 1800 cm -1 (f) showed an enhanced signal at the locus of discolouration. Preliminary results using AFM-IR mapping has been shown to detect the steel-polymer interface buried beneath an epoxy-phenolic coating. Generated infrared absorbance maps are sensitive to the substrate composition and morphology, opening up a new avenue for the detection of buried corrosion phenomena. Detection of the interface is dependent upon both the wavelength and power of incident infrared illumination. This is a result of the variable penetration depth of the radiation, in turn dependent on the infrared wavelength and laser power employed. Thus, judicious selection of infrared parameters permits the selective probing of the infrared absorbance of the coating alone, or a combination coating heterogeneity and interfacial reflectance. Figure 1

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)0,000
score de la tête « metaresearch » (Gemma)0,001
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 enseignants0,218
Score d'incertitude au seuil0,518

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,001
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 ouverte0,0010,000
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 Opus0,019
Tête enseignante GPT0,259
Écart entre enseignants0,241 · 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

Citations0
Publié2017
Routes d'admission1
Résumé présentoui

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