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Record W2324919773 · doi:10.1149/1.3483522

Surface and Interface Characterization of Sequentially Plasma Activated Silicon, Silicon dioxide and Germanium Wafers for Low Temperature Bonding Applications

2010· article· en· W2324919773 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueECS Transactions · 2010
Typearticle
Languageen
FieldEngineering
Topic3D IC and TSV technologies
Canadian institutionsMcMaster University
Fundersnot available
KeywordsGermaniumWaferMaterials scienceSiliconReactivity (psychology)Surface roughnessSilicon dioxidePlasma activationPlasmaCharacterization (materials science)NanotechnologyAnalytical Chemistry (journal)Composite materialChemistryOptoelectronics

Abstract

fetched live from OpenAlex

This article reports the sequentially plasma activated bonding (SPAB) of n-Ge with p-Si and SiO2 at low temperature. Surface activation resulted in highest hydrophilicity of Ge compared with Si and SiO2 counterparts. The highest hydrophilicity of Si, Ge and SiO2 induced by O2 RIE plasma was combined with their highest reactivity induced by MW N2 radicals while maintaining smooth surface roughness. Weak bonding strength of Si/Ge and SiO2/Ge in the SPAB at room temperature was improved after heating at 200°C, but they were still lower than that of Si/Si in the SPAB at room temperature, which is due to the unique reactivity of Ge. The deviation of the reverse bias behavior from a typical p-n junction is due to the low doping concentration in Ge. The degradation of current in the sequential heating resulted mainly from the oxidized surfaces of Ge and Si as well as the bonded interface.

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.

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 score0.059
Threshold uncertainty score0.541

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 head0.006
GPT teacher head0.210
Teacher spread0.204 · 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