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Record W2966717749 · doi:10.11159/icnfa19.150

Proof-Of-Principle Experiments for Phz Nano-Device Using Semi-Metallization of Dielectrics under Strong Optical Fields

2019· article· en· W2966717749 on OpenAlexvenueno aff
Dong Eon Kim

Bibliographic record

VenueProceedings of the World Congress on New Technologies · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicForce Microscopy Techniques and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsDielectricNano-Materials scienceOptoelectronicsProof of conceptOpticsComputer scienceComposite materialPhysics

Abstract

fetched live from OpenAlex

Ultrafast charge transport and control by electromagnetic fields in semiconductors is an ever-growing demand for faster signal processing.Fascinating avenues for new phenomena and applications in solids has been opened by intense optical fields.The current switching and its control by an optical field may pave a way to PHz optoelectronic devices.Reversible semi-metallization in fused silica on a femtosecond time scale has been demonstrated by Schiffrin et.al. (Nature 493 70-74 (2013)).Wider spread of this technology demands better understanding of whether the strong field behavior is universally similar for different dielectrics.Here we demonstrate the universality of the physical picture explained by the localization of Wannier-Stark states.A carrier-envelope-phase stabilized, few-cycle strong optical field was employed to drive the semimetallization in sapphire, calcium fluoride and quartz.The comparison between these materials show its remarkable similarity in response of these materials, despite the significant differences in their physical properties.Our results pave the way toward PHz-rate optoelectronics.

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)0.001
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.026
GPT teacher head0.322
Teacher spread0.295 · 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 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
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the World Congress on New TechnologiesSame topicForce Microscopy Techniques and ApplicationsFrench-language works237,207