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Record W7019719859

Global Optimization of Resonant X-ray Reflectometry Models: Analysis of Perovskite Oxide Heterostructures

2023· dissertation· en· W7019719859 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueUniversity Library (University of Saskatchewan) · 2023
Typedissertation
Languageen
FieldMaterials Science
TopicChemical and Physical Properties of Materials
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Twente
KeywordsReflectometryHeterojunctionSoftwareNeutron reflectometryProcess (computing)Perovskite (structure)
DOInot available

Abstract

fetched live from OpenAlex

Resonant x-ray reflectometry is an emerging synchrotron technique used to characterize the depth-dependent structure of quantum materials. The main challenge impeding the success of resonant x-ray\nreflectometry is the extreme difficulty of analyzing the data because the process involves both large-scale\ncomputational quantum mechanics simulations and the fitting of many independent variables. This leads\nto prolonged analysis periods that require a significant amount of engagement. As a part of this thesis, a\nnew data analysis software named Global Optimization of Resonant X-ray Reflectometry was developed for\nresearchers to use to more effectively analyze resonant x-ray reflectometry data and to mitigate some of these\nchallenges. It has been shown throughout this thesis that multiple features in the software have been able\nto ease the data analysis process. A large focus will be put on the customizable objective function because\nthe boundaries and weights and total variation features have been proven to be integral components to the\nsuccess of the software.\nThe developed software was used to analyze resonant x-ray reflectometry (RXR) data of the catalyst\nLa0.7Sr0.3MnO3/SrTiO3 (LSMO/STO) for electrochemical water splitting. Resonant x-ray reflectometry is\nused to develop a new enhanced understanding of the structural, electronic, and magnetic depth profiles of\nthin LSMO films by characterizing the depth-dependence of such materials for varying film thickness and\nmeasurement temperature. The results provide evidence of a magnetically dead layer at the surface and\ndemonstrate a decrease in the magnetic moment near the Curie temperature. These findings are significant\nbecause they help understand the mechanisms involved in the oxygen evolution reaction and methods that\ncan be used to improve water splitting efficiency.\nResonant x-ray reflectometry is also employed to study the thickness relationship between film thickness\nand the presence of ferromagnetism in the LaMnO3/SrTiO3 heterostructure. The electronic reconstruction\ndue to polar catastrophe is the leading theory for the mechanism involved in the magnetic phase transition,\nbut this study provides a new understanding of the emergence of magnetism in ultra-thin films of LaMnO3\nthat contradict the polar catastrophe mechanism. Notably, ferromagnetism is detected below the critical\nthickness, as supported by density functional theory calculations. Moreover, this study provides evidence\nthat the magnetic moment is related to the distortions in the material. It is possible that octahedral distortions are formed and are the proposed cause for the observed ferromagnetism.

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.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.391
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.012
GPT teacher head0.198
Teacher spread0.186 · 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