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Record W2084240890 · doi:10.1149/1.1792648

Direct Photopatterning of Metal Oxide Structures Using Photosensitive Metallorganics

2004· article· en· W2084240890 on OpenAlexfundno aff
Sean J. Barstow, Augustin Jeyakumar, Paul J. Roman, Clifford L. Henderson

Bibliographic record

VenueJournal of The Electrochemical Society · 2004
Typearticle
Languageen
FieldEngineering
TopicSemiconductor materials and devices
Canadian institutionsnot available
FundersSimon Fraser UniversityGeorgia Institute of Technology
KeywordsMaterials scienceOxideThin filmFourier transform infrared spectroscopyX-ray photoelectron spectroscopyTitaniumSubstrate (aquarium)Titanium oxideSiliconChemical engineeringNanotechnologyOptoelectronics

Abstract

fetched live from OpenAlex

A novel process employing photosensitive metallorganic precursor materials is used to pattern thin-film mixed-metal oxide structures. In this process a photosensitive metallorganic precursor is coated onto a silicon substrate and exposed to ultraviolet light through a mask to form patterned oxide structures or baked at low temperatures to produce blanket metal oxide thin films. In the case of direct photopatterning, a negative-tone process occurs in which the unexposed areas can be washed away using a developer solvent. The photochemical conversion of the precursor films was monitored using transmission Fourier transform infrared FTIR spectroscopy, and lithographic contrast experiments were conducted to estimate the dose required to pattern mixed oxide films of barium, strontium, and titanium. It was determined that the minimum dose required to print an image with the set of precursors investigated in this work was approximately 440 mJ/cm 2 for a precursor film thickness of 800 nm. Based on FTIR data, this dose corresponds to removal of approximately 20% of the organic material from the original precursor film. Dielectric properties were measured for photochemically converted oxide films via parallel-plate capacitance testing. The composition of the oxide films produced from a given precursor stoichiometry was determined by using X-ray photoelectron spectroscopy.

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 score0.005
Threshold uncertainty score0.368

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 head0.009
GPT teacher head0.216
Teacher spread0.206 · 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

Citations2
Published2004
Admission routes1
Has abstractyes

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