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Record W3184459041 · doi:10.1149/ma2021-0121851mtgabs

(Invited) Plasma Immersion Ion Implantation: Technology, Modelling, and Applications for Nanofabrication and 2D Materials

2021· article· en· W3184459041 on OpenAlexaff
Michael P. Bradley

Bibliographic record

VenueECS Meeting Abstracts · 2021
Typearticle
Languageen
FieldEngineering
TopicIon-surface interactions and analysis
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsPlasma-immersion ion implantationWaferIon implantationMaterials scienceNanolithographyPlasmaFluenceOptoelectronicsNanotechnologyFabricationSiliconIonChemistryPhysics

Abstract

fetched live from OpenAlex

Plasma Immersion Ion Implantation (PIII) is an ion implantation technology in which the target to be implanted (i.e. a semiconductor wafer) is immersed in a plasma, and implanted with positive ions by the application of a high-voltage negative-bias pulse to the target. Because of the high plasma density achievable in modern plasma sources, large fluences can be implanted across large wafer areas, without beam scanning. PIII is well suited for a variety of nanofabrication applications. Because of its compatibility with ordinary silicon CMOS device processing, high fluence PIII is a versatile method for in situ fabrication of nanocrystals for integrated circuit applications. This talk will review the physics of energetic ions implanted into solid materials, and illustrate how post-implant thermal treatment can be used to form nanocrystals in the ion-implanted region. A number of potential applications of PIII as a materials synthesis technique will be discussed.

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 score0.207
Threshold uncertainty score0.439

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 head0.010
GPT teacher head0.229
Teacher spread0.219 · 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
Published2021
Admission routes1
Has abstractyes

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Same venueECS Meeting AbstractsSame topicIon-surface interactions and analysisFrench-language works237,207