Design, Fabrication, and Characterization of Multi-Scale Materials for Integration on Lab-on-a-Chip Devices
Notice bibliographique
Résumé
Currently, molecular diagnosis is conducted by professionals in centralized laboratories, which can be time consuming, expensive, and not readily available in remote locations. This motivates the efforts to develop highly accurate, highly sensitive, and high speed lab-on-a-chip (LOC) platforms for inexpensive point-of-care (POC) diagnostics. Multi-scale materials – with tunable features from the nanometer to millimeter length-scales – have shown to enhance performance of electrodes in LOC biosensing and bioprocessing applications. The controlled fabrication of three-dimensional metallic hierarchical electrodes using standard lithographic, machining, printing, etc. techniques is complex and not suitable for rapid, dynamic, and inexpensive prototyping. The work presented herein addresses the need to develop a benchtop rapid prototyping approach to create tunable multi-scale electrodes for integration in LOC devices. In this work, rapid benchtop fabrication is carried out through a combination of xurography, to create electrodes with specific configurations, and controlled thin film wrinkling using pre-stressed polymer substrates, to structure sputtered electrodes on the nanoscale and microscale. This method creates wrinkled structures with sufficient adhesion (no peeling) and conductance (<1 Ω/󠆾󠆾 sheet resistance) for electrical applications. Further development of this method allows fabrication to be carried out completely on the benchtop using all-solution processing methods to deposit high quality thin films, with similar adhesion (no peeling) and conductance (<1 Ω/󠆾󠆾sq sheet resistance) as sputtered films, on the polymer substrates. Moreover, this fabrication technique is extended to create wrinkled nanoparticle films presenting sub-100 nm wavelengths and a dual degree of tunability, as the nanoparticles tune both the thickness and mechanical properties of the films. Structural tuning of the nanoscale and microscale architectures of wrinkled electrodes is studied with scanning electron microscopy (SEM), transmission electron microscopy (TEM), atomic force microscopy (AFM), and white light interferometry, and then related to functional tuning via four-point probe measurements and electrochemical measurements. As the structure is shown to determine key functional parameters, such as resistance and surface area, various electrodes structures are designed and applied to important LOC bioprocessing and sensing applications. For example, structurally optimized electrodes are applied to low voltage cell lysis and are able to lyse bacteria at only 4 V. Furthermore, the problem of integrating three-dimensional, multi-scale wrinkled electrodes into microfluidic devices is investigated. New approaches combining surface treatment and partial curing of microchannels are developed to solve these issues and create fully contained, functional electro-fluidic devices that can withstand flow rates greater than 25 mL/min and pressures of greater than 125 kPa. Ultimately, we are able to create and integrate high quality, tunable, functional, multi-scale electrodes on the laboratory benchtop at low cost and high speed. Thus, this research enables the expedited development of LOC electrode devices that are functionally optimized through structural tuning.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,002 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,001 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».