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Record W2304984682

Production and characterization of three-dimensional, cellular, Metal-filled ceramics

2009· dissertation· en· W2304984682 on OpenAlexfundaboutno aff
Duncan Cree

Bibliographic record

VenueSpectrum Research Repository (Concordia University) · 2009
Typedissertation
Languageen
FieldMaterials Science
TopicAdvanced ceramic materials synthesis
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials scienceSilicon carbideComposite materialSiliconScanning electron microscopeCeramicMicrostructurePorosityAlloyAluminiumMetallurgy
DOInot available

Abstract

fetched live from OpenAlex

This research focuses on the infiltration of two porous structures. In the first, two different silicon sources were used to infiltrate structures derived from different Canadian pine, beech and maple species for the production of silicon carbide (SiC). This allows the use of a precursor structure that is already available, thus saving time, energy and cost of manufacturing. Carbonized wood species measuring 15 mm x 11 mm x 13 mm were used as precursors for the production of silicon carbide (SiC) using two silicon sources (sol and powder) in order to produce a porous SiC structure mimicking that of wood. The liquid sol was vacuum infiltrated into the pyrolyzed wood species, dried and reacted at 1575 °C under a 70 L/h flow of argon. Scanning electron microscopy (SEM) showed SiC grains formed on the interior of the tracheid walls and a high density of SiC whiskers were discovered in certain tracheids of pine and vessels of beech and maple. Both cyclic and repeated infiltration processes were undertaken. In addition, infiltration of carbonized pine wood with molten silicon was carried out in order to obtain a porous SiC structure. Infiltration was based on capillary forces within the preform and the infiltration depth was measured. Optical microscope, SEM, EDS and XRD were used for microstructure characterization and phase identification. In the second part of this work, a liquid A356 aluminum alloy was infiltrated into a porous silicon carbide foam structure. Three dimensional silicon carbide (SiC) ceramic foams were employed as reinforcement for producing an aluminum alloy metal matrix composite with potential as a base plate material in electronic packaging. These are commonly manufactured with aluminum/silicon carbide (Al/SiC) particulate materials, nickel-iron and copper alloys. A base plate provides mechanical strength to the integrated circuit design, as well as aids in transfering the heat from the chip to the heat sink. Packaging base plate materials are required to have low coefficient of thermal expansion (CTE), high thermal conductivity, and low density. A356 aluminum alloy was vacuum infiltrated into a 100 PPI (pores per inch), silicon carbide (SiC) foam network, at 775°C using an in-house built apparatus. It has been shown that this metal matrix composite has similar properties to traditional packaging materials with the added benefit of a lower density. CTE and thermal conductivity are within the range of commercially available materials, with porosity levels of 7%, using this method. Flexural strength and Young's modulus of the composite provide reasonable values as a result of the low reinforcement concentration employed. Secondary Electron Microscopy (SEM) was used to investigate the fractured surfaces of the Charpy, flexural strength and compression tests. In the Charpy and flexural strength samples, the A356 aluminum-silicon alloy matrix shows signs of mixed fracture; cleavage regions and some dimpling. In the network structure, the majority of the failure is from SiC layers debonding from the aluminum matrix with some SiC layer peeling (inter-delamination). Compressive loading showed internal damage in the form of failed SiC struts. X-ray Diffraction (XRD) analysis did not detect any brittle aluminum carbide at the Al/SiC interface. The Rule of Mixtures (ROM) is used for a first rough estimate of certain mechanical and thermal properties

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.020
GPT teacher head0.252
Teacher spread0.232 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2009
Admission routes2
Has abstractyes

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