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Record W4386072888 · doi:10.11159/mmme23.112

Sputtering of Ultra-thin Cu Nano-twinned Films on Si Wafers for Application in Advanced 3D-IC Packaging

2023· article· en· W4386072888 on OpenAlexvenueno aff
Zi-Hong Yang, Tung‐Han Chuang

Bibliographic record

VenueProceedings of the World Congress on Mechanical, Chemical, and Material Engineering · 2023
Typearticle
Languageen
FieldMaterials Science
TopicCopper Interconnects and Reliability
Canadian institutionsnot available
FundersHsinchu Science Park Bureau, Ministry of Science and Technology, Taiwan
KeywordsWaferMaterials scienceSputteringOptoelectronicsNano-Sputter depositionThin filmNanotechnologyComposite material

Abstract

fetched live from OpenAlex

The nanotwinned structure has been attracting a great deal of attention due to its excellent mechanical and electrical properties.In this study, ultra-thin nanotwinned Cu (nt-Cu) films with a thickness of 1.5 um were fabricated by DC magnetron sputtering with moderate substrate bias.Within these films, an equiaxed-grain transition layer only 100-400 nm thick was formed between the nanotwinned region and Si substrate and observed by focused ion beam (FIB).The XRD and EBSD analyses indicated that the as-deposited nanotwinned films had a strong (111) preferred orientation.The surface roughness of the films, as measured with an atomic force microscope (AFM), was below 10 nm, which was sufficiently smooth for chip bonding at low temperature with minor pressure.Direct bonding of Si chips sputtered with such ultra-thin nt-Cu films with (111) preferred orientation has been evidenced to yield a sound interface, and this bonding method can be applied for the manufacturing of 3D-IC packages.

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 score0.001
Threshold uncertainty score0.002

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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.008
GPT teacher head0.229
Teacher spread0.221 · 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
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the World Congress on Mechanical, Chemical, and Material EngineeringSame topicCopper Interconnects and ReliabilityFrench-language works237,207