Characterization of low permittivity (low-<i>k</i>) polymeric dielectric films for low temperature device integration
Bibliographic record
Abstract
Spin-coated low-k dielectrics are now widely used in integrated circuit processing due to their low permittivity and planarization properties. Another area of potential application is in large area digital imaging using amorphous silicon (a-Si:H) technology where low-k dielectrics enable new integration schemes for thin film transistors (TFT) and sensors. In this work, the properties of spin-coated, polymeric, low-k dielectric materials, BCB (benzocyclobutene) and HSQ (hydrogen silsesquioxane), are studied after treating them with low temperature anneals. Fourier transform infrared spectroscopy (FTIR), high frequency capacitance–voltage, topographic planarization, and wafer deflection stress measurements have been used to characterize the films so as to correlate with processing conditions. Lower k values are obtained for lower process temperatures and are correlated by capacitance and FTIR measurements. Annealing in the presence of O2 appears to increase the permittivity. The BCB films yield low stress and good (>90%) planarization and are suitable as interlevel dielectrics in the vertical integration of a-Si TFT and sensor arrays.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".