Mapping stresses in high aspect ratio polysilicon electrical through-wafer interconnects
Bibliographic record
Abstract
Electrical through-wafer interconnect technologies such as vertical through-silicon vias (TSVs) are essential in order to maximize performance, optimize usage of wafer real estate, and enable three-dimensional packaging in leading edge electronic and microelectromechanical systems (MEMS) products. Although copper TSVs have the advantage of low resistance, highly doped polysilicon TSVs offer designers a much larger range of processing options due to the compatibility of polysilicon with high temperatures and also with the full range of traditional CMOS processes. Large stresses are associated with both Cu and polysilicon TSVs, and their accurate measurement is critical for determining the keep-out zone (KOZ) of transistors and for optimizing downstream processes to maintain high yield. This report presents the fabrication and stress characterization of 400-μm deep, 20-Ω resistance, high aspect ratio (25:1) polysilicon TSVs fabricated by deep reactive ion etching (DRIE) followed by low-pressure chemical vapor deposition (LPCVD) of polysilicon with in-situ boron doping. Micro-Raman imaging of the wafer surface showed a maximum stress of 1.2 GPa occurring at the TSV edge and a KOZ of ∼9 to 11 μm. For polysilicon TSVs, the stress distribution in the TSVs far from the wafer surface(s) was not previously well-understood due to measurement limitations. Raman spectroscopy was able to overcome this limitation; a TSV cross section was examined and stresses as a function of both depth and width of the TSVs were collected and are analyzed herein. An 1100°C postanneal was found to reduce average stresses by 40%.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".