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Record W7020675760

Modeling Zirconium Under Neutron Irradiation: Interatomic Potentials, Displacement Cascades, and Electron-Ion Coupling

2025· dissertation· en· W7020675760 on OpenAlexaboutno aff

Bibliographic record

VenueQSpace (Queen's University Library) · 2025
Typedissertation
Languageen
FieldMaterials Science
TopicNuclear Materials and Properties
Canadian institutionsnot available
Fundersnot available
KeywordsEmbedded atom modelMolecular dynamicsNeutronAtom (system on chip)Coupling (piping)AnisotropyDisplacement (psychology)DiffusionNeutron flux
DOInot available

Abstract

fetched live from OpenAlex

This thesis presents a comprehensive atomistic computational study on the effects of neutron irradiation on Zr, a material extensively used in CANada Deuterium Uranium (CANDU) reactors. Our goal is to improve the understanding of microstructural changes under irradiation, focusing on displacement cascades that produce defects. Point defects and their clusters influence the mechanical properties, dimensional stability, and service life of components in reactor environments. The key contributions are: 1. Reparameterization of Interatomic Potentials: Three embedded atom method (EAM) potentials were reparameterized to improve simulation accuracy. Using density functional theory (DFT) calculations, the two-body and embedding energy functions were refitted to better describe atomic interactions at short distances. The modified potentials maintained similar near-equilibrium properties such as defect formation energies and elastic constants but significantly improved threshold displacement energies (TDEs), particularly for [0001] direction. 2. Simulation of Displacement Cascades: Large-scale molecular dynamics (MD) simulations modeled high-energy collision cascades in hexagonal close-packed (HCP) α-Zr. The study examined defect generation, damage morphology and diffusion behaviour. For this purpose, a novel post-processing technique was developed. Self-interstitial atom (SIA) clusters displayed greater anisotropy than equilibrium clusters. 1D and 2D diffusion modes were observed. Findings were integrated into a rate-theory model that predicted radiation-induced growth strains. 3. Effect of Electron Stopping: MD simulations that incorporate ion-electron coupling were conducted using a calibrated version of the unified two-temperature model (UTTM). This approach allowed for a more accurate assessment of electronic effects on primary damage production in Zr, representing the first application of the UTTM to neutron irradiation in Zr. The results suggested that the electronic stopping and the assisted recovery altered the damage production. This thesis advances the atomic-scale understanding of radiation-induced damage in Zr. The reparameterized EAM potentials enhance the fidelity of future MD simulations. The insights into the anisotropy of defect diffusion and its role in radiationinduced growth, along with the novel UTTM-based simulations, contribute significantly to the field. These findings provide a stronger foundation for ongoing experimental, operational, and regulatory efforts to maintain the safety and performance of nuclear reactors.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.198
Teacher spread0.191 · 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 designSimulation or modeling
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
Published2025
Admission routes1
Has abstractyes

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