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Enregistrement W3213431515 · doi:10.1149/ma2021-02581751mtgabs

Additive Manufacturing of Microcantilevers of Varying Stiffness for Sensing Applications

2021· article· en· W3213431515 sur OpenAlexaff
Shervin Foroughi, Mohsen Habibi, Muthukumaran Packirisamy

Notice bibliographique

RevueECS Meeting Abstracts · 2021
Typearticle
Langueen
DomaineEnvironmental Science
ThématiqueSmart Materials for Construction
Établissements canadiensConcordia University
Organismes subventionnairesnon disponible
Mots-clésStiffnessMaterials scienceComputer scienceComposite material

Résumé

récupéré en direct d'OpenAlex

Introduction Microcantilevers have numerous applications in physical, biological and chemical sensing. They have been employed for determination of the fluid viscosity and density [1], detection of biomolecular interaction [2], and part per billion (ppb) level of ammonia in ambient atmosphere [3]. The silicon-based microcantilevers are the most common type of these microdevices, however the biological and physical applications of the polymeric and polymer-composite microcantilevers have been reported in the literature [4], [5]. The polymeric cantilevers have lower Young’s modulus compared to the ones made of silicon and are more sensitive for static deflection measurement [6]. The polydimethylsiloxane (PDMS) and SU-8 are examples of polymers used for fabricating cantilevers through the soft-lithography process. Although the soft-lithography is a matured process for fabrication of the micro-electromechanical systems (MEMS), it is time consuming and costly in comparison with the additive manufacturing process. This may justify further investigations on employing Additive Manufacturing (AM) technologies in fabrication of the MEMS devices. In this study, we report additive manufacturing of the polymeric microcantilevers with different dimensions using SLA 3D printing technology for employing in micro-sensing applications. Method Four 300 μm width microcantilevers with different lengths and thicknesses, were 3D printed using the Form 2 SLA 3D printer. Table 1 presents the dimensions of the cantilevers. Figure 1 shows the images of the green parts on the building platform and the final parts after post processing. 50 μm was chosen as a thickness of each layer for printing. The building material was Flexible resin (Formlabs, USA). Table 2 presents the characteristics of the printing material. The printing process of all cantilevers took 2.5 hours. To investigate the mechanical property of printed cantilevers, the linear stiffness of each part was determined by the static load-deflection tests. The tests were performed by imposing the deflection to the tip of cantilever and recording the corresponding load. The maximum deflection applied to cantilevers was 300 μm. The FemtoTools FT-RS1002 Microrobotic Measurement System was employed to perform the measurements using the mounted sensing probe with the needle tip section size of (50 × 50 μm), force range of ±100000 μN, and resolution of 5 μN. Figure 2 illustrates the front and side views of the sensing probe in contact with the one of cantilevers at the beginning of the measurement test. Results and Conclusions The length and thickness of the microcantilever affect its sensitivity. Figure 3 displays the force-deflection graphs of microcantilevers with different length-thickness ratios obtained from the tests explained in methodology. Due to the small deflection imposed to all plastic microcantilevers with respect to their dimensions, the results show the bilinear response of the cantilevers. The linear relation between the force and the deflection can be observed when the samples deflects beyond the 80 μm. Despite various dimensions of the fabricated microcantilevers, the graph confirms that the length-thickness ratio affects the stiffness of the beams which is determined by the slope of each graphs. Table 3 presents the stiffness of fabricated samples. The graphs show increasing the length-ratio of the microbeams results in increasing the stiffness of the beam. The mechanical stiffnesses of the low length-thickness ratio microcantilevers, samples 1 and 2, are comparable with the PDMS cantilever’s stiffness reported in reference [7] . This reveals the possibility of employing the SLA 3D printing method in fabrication of the operational microcantilevers. This manufacturing method offers the simplicity, time and cost reduction in fabrication of the microcantilevers. References Kim, Deokman, et. al. "Determination of fluid density and viscosity by analyzing flexural wave propagations on the vibrating micro-cantilever." Sensors 17, no. 11 (2017): 2466. Amritsar, Jeetender, et. al. "Conformational detection of heat shock protein through bio-interactions with microstructures." Research on Biomedical Engineering 36, no. 1 (2020): 89-98. Liu, Manyi, et. al. "Revealing humidity-enhanced NH3 sensing effect by using resonant microcantilever." Sensors and Actuators B: Chemical 257 (2018): 488-495. Seena, V., et. al. "Polymer microcantilever biochemical sensors with integrated polymer composites for electrical detection." Solid State Sciences 11, no. 9 (2009): 1606-1611. Sadabadi, Hamid, and Muthukumaran Packirisamy. "Nano-integrated suspended polymeric microfluidics (SPMF) platform for ultra-sensitive bio-molecular recognition of bovine growth hormones." Scientific reports 7, no. 1 (2017): 1-10. Chaudhary, Monika, and Amita Gupta. "Microcantilever-based sensors." Defence Science Journal 59, no. 6 (2009): 634-641. Nezhad, Amir Sanati, et. al. "PDMS microcantilever-based flow sensor integration for lab-on-a-chip." IEEE Sensors journal 13, no. 2 (2012): 601-609. 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 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 enseignants0,040
Score d'incertitude au seuil0,386

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 ouverte0,0000,000
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 Opus0,011
Tête enseignante GPT0,225
Écart entre enseignants0,214 · 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
Publié2021
Routes d'admission1
Résumé présentoui

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