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Enregistrement W34325822 · doi:10.1016/j.jsmc.2021.05.004

A novel method to fabricate open-cell silicon nitride foams with a high and controlled level of porosity

2014· dissertation· en· W34325822 sur OpenAlexfundno aff
Ali Alem

Notice bibliographique

RevueSleep Medicine Clinics · 2014
Typedissertation
Langueen
DomaineMaterials Science
ThématiqueAdvanced ceramic materials synthesis
Établissements canadiensnon disponible
Organismes subventionnairesNatural Sciences and Engineering Research Council of CanadaHorizon 2020 Framework ProgrammeNordForsk
Mots-clésMaterials scienceFabricationPorositySilicon nitrideNitridingCastingComposite materialNitrideMonomerSiliconChemical engineeringPolymerMetallurgyLayer (electronics)

Résumé

récupéré en direct d'OpenAlex

There is a significant lack of study on silicon nitride (Si3N4) foams. This is due to the fabrication issues and difficulties of working with silicon nitride powder. In this study a new fabrication procedure has been designed to fabricate highly porous and homogeneous silicon nitride foams with open-cell structures and controlled porosity levels. The combination of three methods including the sacrificial template method, gel-casting, and reaction bonding techniques resulted in the fabrication of reaction bonded silicon nitride (RBSN) foams. The fabrication procedure was studied and optimized in terms of suspension preparation and rheology, gel-casting parameters, and also reaction bonding conditions. The results revealed that pH 8.5 and the presence of 1.5 wt% DS001 would lead to the highest suspension stability. Therefore, the least sediment height and the highest zeta potential would be obtained. Si-PMMA suspensions showed a near Newtonian behavior at pH 8.5 and for 60 wt% solid. The gel-casting parameters including the monomer content, the ratio of monomer to cross-linker, the gelation time, and the sample warpage were also studied. Based on the result the optimum monomer to crass-linker weight ratio was selected to be 15:1. After nitridation, the foams have a precisely controlled level of porosity, which can be controlled between 41 vol% to 87 vol%. The pore interconnectivity was examined both before and after nitriding and showed complete interconnectedness in the foam porosity. \nThe parameters influencing the mechanical strength of the RBSN foams were also investigated. These considerations include the foam porosity, homogeneity, gel-casting parameters, and nitriding conditions. Depending on the foam porosity, the strength can vary between 1 MPa and 18 MPa. It was also observed that for high Si/PMMA ratios, a monomer content of more than 25 wt% in the premix solution is required. Otherwise, the foam strength drops significantly due to inhomogeneities formed in the cast body. In terms of the effect of nitriding conditions on the foam strength, maximum strength was obtained under N2-H2 atmospheres rather than N2. Extensive investigation on the nitridation process also revealed that the high porosity level of the foam and consequently its large surface area significantly affect the nitriding mechanisms and microstructures compared to conventional RBSN ceramics. It was observed that α- and -Si3N4 form based on specific reactions and each phase has distinct morphologies depending on the nitriding reactions. \nThe effect of iron disilicide (FeSi2) on the properties and microstructure of the fabricated RBSN foams was studied in the next step of the investigation. It was observed that the addition of 1 wt% of FeSi2 significantly increases the foam strength regardless of the nitriding condition. After the addition of FeSi2, a maximum strength of 3.41 MPa was achieved under a N2 atmosphere at 1390°C with a foam of 71 vol% porosity. FeSi2 also affects the α/ phase ratio considerably. It was observed that a considerable increase in the α-Si3N4 content occurs up to 1 wt% FeSi2 while the β-Si3N4 content starts to increase thereafter. The XRD and microstructural analysis showed that α-Si3N4 is present in the form of both matte and whiskers while β-Si3N4 forms as whiskers and large faceted angular grains. \nThe influence of α- and -Si3N4 seeds has also been investigated. It was observed that both α- and -seeds improve the foam strength by 30% and 85%, respectively. The optimum contents of the α- and -seeds correspond to the maximum foam strength which was observed for 5 wt% α-Si3N4 and 10 wt% -Si3N4 seeds. The vapor phase reactions were also enhanced by the addition of -seeds resulting in a significant increase in the -whisker content of the microstructure. \nSintered reaction bonded silicon nitride (SRBSN) foams were also fabricated via sintering of RBSN foams in the presence of MgO as a sintering aid. The effect of different amounts of MgO on the foam microstructure and porosity was also studied both before and after sintering. The addition of MgO resulted in significant changes to the microstructure of the RBSN and SRBSN foams. MgO stopped whisker-forming reactions during nitriding; therefore, foams with clean porosity and without the presence of whiskers were produced. The SRBSN foams can have a maximum of 85 vol% porosity and the foam microstructure contained only -Si3N4 grains embedded in an amorphous intergranular phase.

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 machine sur la base complète

Imitation des enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,001
Version: metacan-v3-hybrid-931329e0061cStatut 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: Méthodes · Signal consensuel: aucune
Score de désaccord entre enseignants0,001
Score d'incertitude au seuil0,005

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,001
Science ouverte0,0000,001
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0010,001

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 Opus0,053
Tête enseignante GPT0,356
Écart entre enseignants0,304 · 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 source (Gemma direct ou Codex distillé), 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
GenreMéthodes

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
Publié2014
Routes d'admission1
Résumé présentoui

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