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Record W4324133737 · doi:10.1051/epjap/2023220334

Angular distribution of sputtered particles from Inconel<sup>718</sup>: a simulation study

2023· article· en· W4324133737 on OpenAlexaff
K. Bria, M. Ait El Fqih, Jean‐Michel Nunzi, L. Jadoual, A. Kaddouri

Bibliographic record

VenueThe European Physical Journal Applied Physics · 2023
Typearticle
Languageen
FieldEngineering
TopicIon-surface interactions and analysis
Canadian institutionsQueen's University
Fundersnot available
KeywordsInconelSputteringMaterials scienceAlloyAtomic physicsMetallurgyPhysicsThin filmNanotechnology

Abstract

fetched live from OpenAlex

The angular distribution of sputtered particles is an effective tool for obtaining information on the composition and structure of the target and even on the beam energies. The particles of Inconel718 super alloy sputtered at full angle corresponding to each of the probes were calculated. The SRIM program associated with a new ANGULARE simulation program was used to obtain the sputtering yields and angular distribution of sputtered Fe, Al, Cr, Mo, Nb, Ni and Ti particles from Inconel718. The simulation was performed for a large number of incident ions (5 keV, Kr+) and allows the computer to count the number of particles emitted at the solid angle. Angular distributions of pulverized Inconel718 particles and pulverized yields were compared to the literature. Furthermore, the angular distribution of Inconel718 for the differential sputtering yields shows an under-cosine tendency.

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 score0.008
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.016
GPT teacher head0.242
Teacher spread0.225 · 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
Published2023
Admission routes1
Has abstractyes

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