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Record W7132946827

Microstructure Evolution and Mechanical Behavior of Laser Additively Manufactured Alloys with Heterogeneous Microstructures

2024· dissertation· W7132946827 on OpenAlexfundno aff
Haoxiu Chen

Bibliographic record

VenueTSpace · 2024
Typedissertation
Language
FieldEngineering
TopicAdditive Manufacturing Materials and Processes
Canadian institutionsnot available
FundersUniversity of WaterlooUniversity of TorontoCanadian Light Source
KeywordsMicrostructureNanoindentationEutectic systemAlloyUltimate tensile strengthDuctility (Earth science)Elastic modulusDeformation (meteorology)
DOInot available

Abstract

fetched live from OpenAlex

Metals and alloys with heterogeneous microstructures exhibit an enhanced combination of strength and ductility, compared to their counterparts with homogeneous microstructures. Additive manufacturing (AM) techniques offer a new opportunity to induce heterogeneous microstructures in a wide range of metals and alloys, thereby optimizing their mechanical properties. My PhD thesis aims to study the microstructure evolution and mechanical behavior of laser additively manufactured alloys with heterogeneous microstructures. The employed strategy is optimizing processing parameters to obtain designed microstructures and mechanical properties. Three representative heterostructured alloys are studied in this thesis: TiAl/Ti2AlNb alloys, AlSi10Mg alloys, and AlCoCrFeNi2.1 eutectic high-entropy alloys.In the first project, a piece of γ-TiAl/Ti2AlNb composition gradient alloy is fabricated by depositing γ-TiAl powder on a Ti2AlNb alloy substrate. The transition zone includes three layers (I, II and III) with gradient compositions and phases. The results of nanoindentation mapping show good correlations between the mechanical properties (nanohardness and elastic modulus) and microstructure in the transition zone. Attributing to the rule of mixtures, the nanohardness and elastic modulus gradually increase from the substrate Ti2AlNb to Layer I, and gradually decrease from Layer I to γ-TiAl. For harmonic structured AlSi10Mg components produced by laser powder bed fusion (LPBF), I investigate the local strain evolution, microvoid growth, and crack formation in the melt pool boundary regions using in situ tensile testing and synchrotron-based X-ray microtomography. Results indicate that decreasing area fractions of melt pool boundaries from 5.5% to 4.5% leads to an increase of tensile ductility from 7.2% to 9.8% in the LPBF AlSi10Mg samples. For the third project, I employ in situ synchrotron-based high-energy X-ray diffraction and tomography to study a directed energy deposition-fabricated directional nanolamellar AlCoCrFeNi2.1, comprised of face-centered cubic (fcc) and ordered body-centered cubic (B2) phases. The eutectic high entropy alloys that are loaded along three orientations present obvious mechanical anisotropy: (i) Samples HEA0, loaded along the lamellar direction, exhibit both the highest strength and ductility; (ii) Samples HEA45, loaded along a 45-degree angle with the lamellar direction, exhibit lowest strength and medial ductility; (iii) Samples HEA90, perpendicular to the lamellar direction, exhibit medial strength and lowest ductility. I find that such mechanical anisotropy is associated with the sequence of work hardening in the B2 and fcc phases, as well as martensitic transformation in the B2 phase. Overall, this thesis suggests the great opportunity of AM in fabricating alloys with gradient, harmonic, and lamellar heterogeneous microstructures with exceptional mechanical 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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.007
GPT teacher head0.248
Teacher spread0.242 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2024
Admission routes1
Has abstractyes

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