Engineering a new class of thermal spray nano-based microstructures from agglomerated nanostructured particles, suspensions and solutions: an invited review
Notice bibliographique
Résumé
From the pioneering works of McPherson in 1973 who identified nanometre-sized features in thermal spray conventional alumina coatings (using sprayed particles in the tens of micrometres size range) to the most recent and most advanced work aimed at manufacturing nanostructured coatings from nanometre-sized feedstock particles, the thermal spray community has been involved with nanometre-sized features and feedstock for more than 30 years. Both the development of feedstock (especially through cryo-milling, and processes able to manufacture coatings structured at the sub-micrometre or nanometre sizes, such as micrometre-sized agglomerates made of nanometre-sized particles for feedstock) and the emergence of thermal spray processes such as suspension and liquid precursor thermal spray techniques have been driven by the need to manufacture coatings with enhanced properties. These techniques result in two different types of coatings: on the one hand, those with a so-called bimodal structure having nanometre-sized zones embedded within micrometre ones, for which the spray process is similar to that of conventional coatings and on the other hand, sub-micrometre or nanostructured coatings achieved by suspension or solution spraying. Compared with suspension spraying, solution precursor spraying uses molecularly mixed precursors as liquids, avoiding a separate processing route for the preparation of powders and enabling the synthesis of a wide range of oxide powders and coatings. Such coatings are intended for use in various applications ranging from improved thermal barrier layers and wear-resistant surfaces to thin solid electrolytes for solid oxide fuel cell systems, among other numerous applications. Meanwhile these processes are more complex to operate since they are more sensitive to parameter variations compared with conventional thermal spray processes. Progress in this area has resulted from the unique combination of modelling activities, the evolution of diagnostic tools and strategies, and experimental advances that have enabled the development of a wide range of coating structures exhibiting in numerous cases unique properties. Several examples are detailed. In this paper the following aspects are presented successively (i) the two spray techniques used for manufacturing such coatings: thermal plasma and HVOF, (ii) sensors developed for in-flight diagnostics of micrometre-sized particles and the interaction of a liquid and hot gas flow, (iii) three spray processes: conventional spraying using micrometre-sized agglomerates of nanometre-sized particles, suspension spraying and solution spraying and (iv) the emerging issues resulting from the specific structures of these materials, particularly the characterization of these coatings and (v) the potential industrial applications. Further advances require the scientific and industrial communities to undertake new research and development activities to address, understand and control the complex mechanisms occurring, in particular, thermal flow—liquid drops or stream interactions when considering suspension and liquid precursor thermal spray techniques. Work is still needed to develop new measurement devices to diagnose in-flight droplets or particles below 2 µm average diameter and to validate that the assumptions made for liquid–hot gas interactions. Efforts are also required to further develop some of the characterization protocols suitable to address the specificities of such nanostructured coatings, as some existing ‘conventional’ protocols usually implemented on thermal spray coatings are not suitable anymore, in particular to address the void network architectures from which numerous coatings properties are derived.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,002 | 0,003 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,002 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».