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Enregistrement W2275837360 · doi:10.1149/ma2015-02/45/1796

Functional PDMS Composite Microbridges for Temperature Sensing Applications

2015· article· en· W2275837360 sur OpenAlexaff
Manu Pallapa, Jacob C. K. Leung, Pouya Rezai

Notice bibliographique

RevueECS Meeting Abstracts · 2015
Typearticle
Langueen
DomaineChemical Engineering
ThématiqueAnalytical Chemistry and Sensors
Établissements canadiensYork University
Organismes subventionnairesnon disponible
Mots-clésMaterials sciencePolydimethylsiloxaneMicrofabricationPhotolithographyFabricationReactive-ion etchingEtching (microfabrication)OptoelectronicsLaser ablationComposite numberComposite materialMicrofluidicsNanotechnologyLaserOptics

Résumé

récupéré en direct d'OpenAlex

Microstructures provide excellent sensing and actuating capabilities due to their high surface to volume ratio and have brought about important advancements in life sciences research [1-3]. The development of electrically-conductive polymer composites for such sensors and actuators as well as rapid fabrication techniques will result in microstructures with better transduction, low cost of production and flexibility [4, 5]. Conventional microfabrication techniques for such transducers are photolithography, reactive ion etching (RIE), laser ablation, and focussed ion beam etching. However these techniques are limited by the requirement of multiple processing steps (photolithography and RIE) or serial processing with specialized equipment (laser ablation and focussed ion-beam etching). In this work we report a low-cost, rapid and convenient technique to microfabricate electrically-conductive Iron-Polydimethylsiloxane (Fe-PDMS) microbridges using agar as the sacrificial material and further demonstrate the temperature sensing property of this polymer composite. Fabrication of the Fe-PDMS microbridges by the sacrificial agar technique is illustrated schematically in Fig. 1. A rectangular mold containing a 20mm×0.7mm×0.2mm channel and three pairs of sidewall through-holes (800µm in diameter) was manufactured via 3D printing (Fig.1a-i). Glass capillary guide rods with diameters of 65µm, 240µm and 350µm were inserted into the sidewall though-holes and passed through the channel (Fig.1a-ii). The guide rods functioned as master molds for the sacrificial agar, creating cavities for the Fe-PDMS composite to flow through. A 4% agar solution was prepared and poured into the rectangular mold (Fig.1a-iii). Following the room-temperature curing of the agar, the guide rods were removed horizontally and the agar replica was carefully de-molded, exposing the cylindrical cavities to be filled with Fe-PDMS composite (Fig.1a-iv). The agar replica was transferred into a petri dish (Fig.1a-v). The Fe-PDMS composite was prepared by mixing 80wt% iron particles (200 mesh size) with Sylgard 184 pre-polymer (10:1 elastomer-curing agent ratio). This composite was carefully casted into the aforementioned cylindrical cavities using assistive capillary flow. Undoped Sylgard 184 pre-polymer (10:1 elastomer-curing ratio) was then casted on the entire structure and cured at 37oC for 24 hours (Fig. 1a-vi). The cured structure was then immersed in a 100˚C water bath (Fig. 1a-vii) to dissolve the sacrificial agar and dried to form the suspended microbridge structures (Fig. 1a-viii) before plasma bonding to another flat PDMS layer (Fig. 1a-ix). The scanning electron microscope images of the fabricated microbridges are shown in Fig. 2. The thickness of the fabricated suspended bridges were measured and compared against their respective guide rod thicknesses (Fig. 3). The average thicknesses of the 65µm and 240µm microbridges showed a high precision in fabrication with a standard deviation of ~12µm from the guide rods. The larger deviation of the 350µm microbridge may be attributed to the size range (1-75 µm) of the iron particles in the Fe-PDMS composite which is currently under investigation. Uniform particle size would ensure better consistency in microbridge thicknesses. The temperature sensing ability of the Fe-PDMS composite was experimentally verified as well. A 24 AWG copper wire was used to provide electrical interconnection with the composite. The current-voltage (IV) characteristics of the Fe-PDMS composite in the input voltage range of 1-20V was measured by a Keithley 2410 source meter at four equilibrium temperatures of 45, 50, 60 and 70˚C applied externally via a hot plate. Each equilibrium temperature level produced a distinctive near-ohmic IV curve (Fig. 4a) with a positive correlation between the temperature and electrical conductivity. The obtained mean resistivities (Fig. 4b) imply a positive coefficient of resistance that is analogous to metals. The sacrificial agar fabrication technique in conjunction with the properties of the developed Fe-PDMS polymer composite will be suitable for development of low-cost and flexible electrodes and microstructures in microfluidic devices for thermo-electric temperature sensing and actuating applications. References F. Mei, S. P. J. Fancy, Y.-A. a Shen, J. Niu, C. Zhao, B. Presley, E. Miao, S. Lee, S. R. Mayoral, S. a Redmond, A. Etxeberria, L. Xiao, R. J. M. Franklin, A. Green, S. L. Hauser and J. R. Chan, Nat. Med., 2014, 20, 954–960. F. Liu, Y. Piao, J. S. Choi and T. S. Seo, Biosens. Bioelectron., 2013, 50, 387–392. S. Ito, T. Yasui, Y. Okamoto, N. Kaji and M. Tokeshi, Proc. 16th Int. Conf. Miniaturized Syst. Chem. Life Sci., 2012, 1234–1236. Gong X, Wen W, Polydimethylsiloxane-based conducting composites and their applications in microfluidic chip fabrication, Biomicrofluidics 2009, 3, 012007, pp1-14 Calvert P, Deepak D, Patra P, Agrawal A, Sawhney A, Conducting Polymer and Conducting Composite Strain Sensors on Textiles. Molecular Crystals and Liquid Crystals, 2008; 484 (1), pp291-302 Figure 1

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: metacan-v3-hybrid-931329e0061cStatut 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 enseignants0,005
Score d'incertitude au seuil0,015

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0050,002

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 Opus0,023
Tête enseignante GPT0,241
Écart entre enseignants0,218 · 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 source (Gemma direct ou Codex distillé), 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
Publié2015
Routes d'admission1
Résumé présentoui

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