Rapid prototyping of a polymer MEMS droplet dispenser by laser-assisted 3D printing.

Biosensors Electrical and electronic engineering Nanofabrication and nanopatterning

Journal

Microsystems & nanoengineering
ISSN: 2055-7434
Titre abrégé: Microsyst Nanoeng
Pays: England
ID NLM: 101695458

Informations de publication

Date de publication:
2023
Historique:
received: 03 05 2022
revised: 01 05 2023
accepted: 23 05 2023
medline: 6 7 2023
pubmed: 6 7 2023
entrez: 6 7 2023
Statut: epublish

Résumé

In this work, we introduce a polymer version of a previously developed silicon MEMS drop deposition tool for surface functionalization that consists of a microcantilever integrating an open fluidic channel and a reservoir. The device is fabricated by laser stereolithography, which offers the advantages of low-cost and fast prototyping. Additionally, thanks to the ability to process multiple materials, a magnetic base is incorporated into the cantilever for convenient handling and attachment to the holder of a robotized stage used for spotting. Droplets with diameters ranging from ∼50 µm to ∼300 µm are printed upon direct contact of the cantilever tip with the surface to pattern. Liquid loading is achieved by fully immersing the cantilever into a reservoir drop, where a single load results in the deposition of more than 200 droplets. The influences of the size and shape of the cantilever tip and the reservoir on the printing outcome are studied. As a proof-of-concept of the biofunctionalization capability of this 3D printed droplet dispenser, microarrays of oligonucleotides and antibodies displaying high specificity and no cross-contamination are fabricated, and droplets are deposited at the tip of an optical fiber bundle.

Identifiants

pubmed: 37408536
doi: 10.1038/s41378-023-00559-3
pii: 559
pmc: PMC10318032
doi:

Types de publication

Journal Article

Langues

eng

Pagination

85

Informations de copyright

© The Author(s) 2023.

Déclaration de conflit d'intérêts

Conflict of interestThe authors declare no competing interests.

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Auteurs

Rémi Courson (R)

LAAS-CNRS, Université de Toulouse, CNRS, 31400 Toulouse, France.

Oleksii Bratash (O)

Université Grenoble Alpes, CNRS, CEA, IRIG, SyMMES, 38000 Grenoble, France.

Ali Maziz (A)

LAAS-CNRS, Université de Toulouse, CNRS, 31400 Toulouse, France.

Cloé Desmet (C)

Université Grenoble Alpes, CNRS, CEA, IRIG, SyMMES, 38000 Grenoble, France.

Ricardo Alvarado Meza (RA)

Université Grenoble Alpes, CNRS, CEA, IRIG, SyMMES, 38000 Grenoble, France.

Loïc Leroy (L)

Université Grenoble Alpes, CNRS, CEA, IRIG, SyMMES, 38000 Grenoble, France.

Elodie Engel (E)

Université Grenoble Alpes, CNRS, CEA, IRIG, SyMMES, 38000 Grenoble, France.

Arnaud Buhot (A)

Université Grenoble Alpes, CNRS, CEA, IRIG, SyMMES, 38000 Grenoble, France.

Laurent Malaquin (L)

LAAS-CNRS, Université de Toulouse, CNRS, 31400 Toulouse, France.

Thierry Leïchlé (T)

LAAS-CNRS, Université de Toulouse, CNRS, 31400 Toulouse, France.
Georgia Tech-CNRS International Research Laboratory, Atlanta, GA 30332 USA.

Classifications MeSH