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Record W4285398530 · doi:10.1149/ma2022-01251213mtgabs

Defect-Free Metallization of through-Glass Vias (TGV) with Engineered Geometry

2022· article· en· W4285398530 on OpenAlexaff
Prantik Mazumder, Shrisudersan Jayaraman, Matthew Sevem, Mandakini Kanungo, Rajesh Vaddi

Bibliographic record

VenueECS Meeting Abstracts · 2022
Typearticle
Languageen
FieldEngineering
Topic3D IC and TSV technologies
Canadian institutionsResearch & Development Corporation
Fundersnot available
KeywordsElectroplatingMaterials scienceVoid (composites)Bridging (networking)Copper platingPlating (geology)Conformal mapResistMicroelectromechanical systemsComposite materialOptoelectronicsGeometryComputer science

Abstract

fetched live from OpenAlex

Metallized through-glass vias (TGVs) have attracted interest in recent years due to their promise in enabling 2.5D and 3D electronic architectures and high-density MEMS devices. However, unlike metallization of PCB, metallization of TGV is challenging, and the electroplating processes are not well-established. This is mostly due to the form factor associated with TGVs - high length (L) and small diameter (Φ). During electrolytic process, for example electroplating of Copper inside the TGVs, such form factor often leads to severe transport limitation and subsequent formation of defects such as seams or voids in the samples. This has led to intense research in the past decade to develop special additives and processes to achieve defect-free filling of TGVs. It has been accepted that defect-free filling of TGVs is not possible without specialized additives in the solution. We will first demonstrate through simplified theoretical analysis and numerical modeling why that is the case when the geometry of the TGV has uniform cross-section. Even when the electroplating is carried out in in fully kinetic-controlled regime (Thiele modulus, μ ≤ 1), it will be clear from the analysis that a complete defect-free metallization is not achievable as long as the TGV cross-section is uniform. Next, we will report a novel metallization technique using an engineered via with an X-shape in the middle and operating in the kinetic-limited regime without the requirement of any specialized additives. This leads to Cu bridging of the vias at the waist, after which continued conformal plating ensures void-free filling. It would be emphasized that by combining these two effects – novel shape of TGV and kinetic controlled electroplating – void-free filling is achievable even in the absence of any additives. While additive-based bath is required and will continue to be used to optimize between plating speed, low stress and roughness of plated copper, the objective of this talk is to demonstrate the advantage of engineered vias in which even an additive-free bath could provide defect-free metallization. At very low current densities, an anomalous increase in thickness in the middle compared to the top of the via was observed. This cannot be explained by a simple 1D model and is an interesting next step in understanding additive-free electroplating.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.953
Threshold uncertainty score0.647

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.010
GPT teacher head0.196
Teacher spread0.185 · 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 designSimulation or modeling
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
Published2022
Admission routes1
Has abstractyes

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