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Record W2968502847 · doi:10.22215/etd/2016-11517

An Implementation of Wang Tilings for the Representation of Metallic Glasses in Molecular Dynamics

2016· dissertation· en· W2968502847 on OpenAlexaff
Roxana Barcelo Singh

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEngineering
TopicMetallic Glasses and Amorphous Alloys
Canadian institutionsCarleton University
FundersConsejo Nacional de Ciencia y TecnologíaConsejo Estatal de Ciencia y Tecnología de Jalisco
KeywordsRepresentation (politics)Amorphous metalMolecular dynamicsAmorphous solidTileMaterials scienceShear (geology)Statistical physicsCrystallographyPhysicsChemistryComposite materialComputational chemistry

Abstract

fetched live from OpenAlex

This thesis presents an implementation of a mathematical model, Wang tilings, for the representation of metallic glasses in Molecular Dynamics. The purpose is to assess whether a Wang tiling specimen can be considered a representation of a metallic glass. The implementation of Wang tilings for the representation of amorphous structures can potentially increase system sizes and enable the study of small tile sets that achieve the same results. A technique for creating a Wang tiling specimen and a true specimen is developed. These specimens are then submitted to uniaxial tension deformation and analyzed macroscopic and microscopically. The analysis consisted of stress-strain curves, atomic bond deficiency defect concentrations and a shear banding analysis. The technique for the creation of a Wang tiling specimen was accurately developed, however, the tiled system is not a surrogate of the true specimen. This research is a first approach for implementing Wang tilings in Molecular Dynamics.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.063
Threshold uncertainty score0.471

Codex and Gemma teacher scores by category

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 head0.011
GPT teacher head0.304
Teacher spread0.294 · 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.

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
Published2016
Admission routes1
Has abstractyes

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