MétaCan
Menu
Back to cohort
Record W2321148428 · doi:10.1149/1.2980006

Atomic Layer Deposited IrO2-TiO2 Thin Film Resistor for the Thermal Inkjet Printheads

2008· article· en· W2321148428 on OpenAlexaff
Se‐Hun Kwon, Sung‐Wook Kim, Seong‐Jun Jeong, Kwang Ho Kim, Sang-Won Kang

Bibliographic record

VenueECS Transactions · 2008
Typearticle
Languageen
FieldEngineering
TopicSemiconductor materials and devices
Canadian institutionsKootenay Association for Science & Technology
Fundersnot available
KeywordsThin filmMaterials scienceAtomic layer depositionAnnealing (glass)Temperature coefficientElectrical resistivity and conductivityTitaniumLayer (electronics)Analytical Chemistry (journal)NanotechnologyComposite materialMetallurgyChemistryElectrical engineering

Abstract

fetched live from OpenAlex

IrO2-TiO2 thin films were prepared by atomic layer deposition using Ir(EtCp)(COD) and titanium isopropoxide (TTIP). The intermixing ratios between IrO2 and TiO2 in the IrO2-TiO2 thin films were controlled from (IrO2)0.33-(TiO2)0.67 to (IrO2)0.78-(TiO2)0.22. With the IrO2 intermixing ratio less than 0.55, both TCR values and resistivities were abruptly changed. The temperature coefficient of resistance (TCR) for IrO2-TiO2 thin films was controlled from -420 to -75.35 ppm/K by changing the IrO2 intermixing ratios from 0.55 to 0.78, while the resistivities was also controlled from 1500 to 356.7 μΩ•cm. Moreover, the change in the resistivity of IrO2-TiO2 thin films was below 10% even after O2 annealing process at 600{degree sign}C.

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)0.000
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 score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

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 science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.002

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 head0.025
GPT teacher head0.223
Teacher spread0.198 · 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

Citations1
Published2008
Admission routes1
Has abstractyes

Explore more

Same venueECS TransactionsSame topicSemiconductor materials and devicesFrench-language works237,207