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Enregistrement W2527907091

Experimental and Numerical Study of the Mechanical Aspects of the Stitch Bonding Process in Microelectronic Wire Bonding

2014· dissertation· en· W2527907091 sur OpenAlexfundno aff
Alireza Rezvanigilkolaee

Notice bibliographique

RevueUWSpace (University of Waterloo) · 2014
Typedissertation
Langueen
DomaineEngineering
ThématiqueElectronic Packaging and Soldering Technologies
Établissements canadiensnon disponible
Organismes subventionnairesNatural Sciences and Engineering Research Council of Canada
Mots-clésMicroelectronicsWire bondingMaterials scienceMechanical engineeringProcess (computing)NanotechnologyEngineeringComposite materialComputer scienceElectrical engineering
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

The goal of this thesis is to improve the understanding of the stitch bonding process in microelectronic wire bonding. In particular, it focuses on investigating the effect of the process parameters bonding force, scrub amplitude, and skid on experimental bond quality responses, including qualitative (non-sticking, sticking, and tail-lifting) and quantitative (stitch pull force, tail pull force). In addition to the experimental work, a finite element (FE) model is
\ndeveloped for the stitch bonding process using ABAQUS software, and compared with the
\nexperimental observations.
\nFor the first set of experiments, the stitch bonding is performed with a 18 μm diameter Pd
\ncoated Cu (PCC) wire on a “low bondability” Au/Ni/Pd plated quad-flat non-lead (QFN) substrate. Results showed that a high bonding force, a high scrub amplitude, and a positive skid provoke the sticking of the stitch bond and reducing the chance of non-sticking observation. However, such parameters also increase the chance of tail-lifting. As a trade-off for a low bondability substrate, a process parameter combination containing a high bonding force and a high scrub amplitude and a negative skid could ensure a strong enough stitch bonding process with low chance of tail-lifting.
\nFor the second set of experiments, the stitch bonding is performed with a 18 μm diameter
\nuncoated Cu wire on a “high bondability” Ag plated QFN substrate. Statistical analysis of
\nstitch and tail pull force showed that the skid and scrub parameters have a more significant
\ninfluence than bonding force. A positive skid can degrade the stitch pull force, while enhancing the tail pull force. A high scrub amplitude is found to degrade both the stitch and the tail pull forces. The bonding force is shown to improve the stitch and tail pull forces slightly. Performing an optimization, process parameters of 70 gf (687 mN) bonding force, 3 μm scrub amplitude, and zero skid result in acceptable stitch and tail pull forces, along with a reliable stitch bond appearance (low peeling and shallow capillary tool impression).
\nThe influence of the process parameters is significantly different depending on if bonding on
\nlow or high bondability substrates. For example, a positive skid increases the chances of sticking and tail-lifting on low bondability substrate, but it decreases the tail pull force and
\nincreases the tail pull force for high bondability substrate. This indicates that finding a general
\nexperimental rule for understanding the effect of process parameters on the stitch bond quality is difficult if not impossible. In other words, instead of general rule, it is more likely to find individual rules for specific individual applications.
\nTo improve the understanding of stitch bonding a three dimensional (3D) dynamic explicit FE
\nmodel is developed in ABAQUS. The model components and boundary conditions are constructed and applied to reflect the experimental conditions. The bonding force, scrub, and skid are successfully implemented into the model. Mass scaling is applied carefully to save calculation time while ensuring there are no artificial effects of inertia. The model is able to render the conventional responses reported in the past including stress and strain distributions. However, these conventional outputs were not sufficient to provide a correlation between model and experiment. Therefore, new candidate responses were developed and extracted from the numerical results. The new responses are based on accepted welding mechanisms.
\nOne of the mechanisms is interfacial cleaning by frictional energy which is beneficial for
\nbonding. Thus the friction energy accumulated during the simulated bond duration is
\nextracted as a candidate response. For classical cold welding processes, the interfacial surface expansion is a key mechanism, as it opens up cracks in the surface contamination and oxide layers and thereby generates paths to bring the fresh metals together under pressure. Therefore, candidate responses related to surface expansion at the contact interface are extracted from the model.
\nThe complete set of new responses extracted from the numerical model includes contact areas,
\nsurface expansion per areas, frictional energy, and combination of frictional energy combined
\nwith surface expansions per areas. In addition the bond interface is divided into “wedge” and
\n“tail” regions. The model is run for the same DOE cells as used in the first set of experiments
\nand candidate responses are extracted and compared with the experimental observations. By ranking the correlation coefficients of each individual candidate responses, for the first time correlations that are relatively strong are found between a numerical response and experimental observations of stitch bonding. Responses that have correlation coefficients of 0.79 and 0.85 were found for wedge sticking and tail-lifting, respectively. Such relatively strong correlation indicates that the friction enhanced cleaning and the surface expansion mechanisms are proper theories for the current stitch bonding system. These theories can be used for developing similar models for other types of the solid-state bonding processes.
\nBased on the best candidate responses, a procedure to determine numerical process windows is demonstrated for a specific application. Such a window defines the parameter ranges which result in an acceptable stitch bonding process and is an excellent indication of how suitable a process is for mass production. Depending on the application, materials, geometries, and tools, the FE model and process window procedure allow a variety of numerical process windows to be produced and compared.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: Expérimental (laboratoire)
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,058
Score d'incertitude au seuil0,610

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0010,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,006
Tête enseignante GPT0,204
Écart entre enseignants0,197 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeExpérimental (laboratoire)
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2014
Routes d'admission1
Résumé présentoui

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