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A 3D-Printed Micro-Optofluidic Chamber for Fluid Characterization and Microparticle Velocity Detection

This work proposes a multi-objective polydimethylsiloxane (PDMS) micro-optofluidic (MoF) device suitably designed and manufactured through a 3D-printed-based master–slave approach. It exploits optical detection techniques to characterize immiscible fluids or microparticles in suspension inside a com...

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Autores principales: Cutuli, Emanuela, Sanalitro, Dario, Stella, Giovanna, Saitta, Lorena, Bucolo, Maide
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10673365/
https://www.ncbi.nlm.nih.gov/pubmed/38004972
http://dx.doi.org/10.3390/mi14112115
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author Cutuli, Emanuela
Sanalitro, Dario
Stella, Giovanna
Saitta, Lorena
Bucolo, Maide
author_facet Cutuli, Emanuela
Sanalitro, Dario
Stella, Giovanna
Saitta, Lorena
Bucolo, Maide
author_sort Cutuli, Emanuela
collection PubMed
description This work proposes a multi-objective polydimethylsiloxane (PDMS) micro-optofluidic (MoF) device suitably designed and manufactured through a 3D-printed-based master–slave approach. It exploits optical detection techniques to characterize immiscible fluids or microparticles in suspension inside a compartment specifically designed at the core of the device referred to as the MoF chamber. In addition, we show our novel, fast, and cost-effective methodology, dual-slit particle signal velocimetry (DPSV), for fluids and microparticle velocity detection. Different from the standard state-of-the-art approaches, the methodology focuses on signal processing rather than image processing. This alternative has several advantages, including the ability to circumvent the requirement of complex and extensive setups and cost reduction. Additionally, its rapid processing speed allows for real-time sample manipulations in ongoing image-based analyses. For our specific design, optical signals have been detected from the micro-optics components placed in two slots designed ad hoc in the device. To show the devices’ multipurpose capabilities, the device has been tested with fluids of various colors and densities and the inclusion of synthetic microparticles. Additionally, several experiments have been conducted to prove the effectiveness of the DPSV approach in estimating microparticle velocities. A digital particle image velocimetry (DPIV)-based approach has been used as a baseline against which the outcomes of our methods have been evaluated. The combination of the suitability of the micro-optical components for integration, along with the MoF chamber device and the DPSV approach, demonstrates a proof of concept towards the challenge of real-time total-on-chip analysis.
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spelling pubmed-106733652023-11-18 A 3D-Printed Micro-Optofluidic Chamber for Fluid Characterization and Microparticle Velocity Detection Cutuli, Emanuela Sanalitro, Dario Stella, Giovanna Saitta, Lorena Bucolo, Maide Micromachines (Basel) Article This work proposes a multi-objective polydimethylsiloxane (PDMS) micro-optofluidic (MoF) device suitably designed and manufactured through a 3D-printed-based master–slave approach. It exploits optical detection techniques to characterize immiscible fluids or microparticles in suspension inside a compartment specifically designed at the core of the device referred to as the MoF chamber. In addition, we show our novel, fast, and cost-effective methodology, dual-slit particle signal velocimetry (DPSV), for fluids and microparticle velocity detection. Different from the standard state-of-the-art approaches, the methodology focuses on signal processing rather than image processing. This alternative has several advantages, including the ability to circumvent the requirement of complex and extensive setups and cost reduction. Additionally, its rapid processing speed allows for real-time sample manipulations in ongoing image-based analyses. For our specific design, optical signals have been detected from the micro-optics components placed in two slots designed ad hoc in the device. To show the devices’ multipurpose capabilities, the device has been tested with fluids of various colors and densities and the inclusion of synthetic microparticles. Additionally, several experiments have been conducted to prove the effectiveness of the DPSV approach in estimating microparticle velocities. A digital particle image velocimetry (DPIV)-based approach has been used as a baseline against which the outcomes of our methods have been evaluated. The combination of the suitability of the micro-optical components for integration, along with the MoF chamber device and the DPSV approach, demonstrates a proof of concept towards the challenge of real-time total-on-chip analysis. MDPI 2023-11-18 /pmc/articles/PMC10673365/ /pubmed/38004972 http://dx.doi.org/10.3390/mi14112115 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Cutuli, Emanuela
Sanalitro, Dario
Stella, Giovanna
Saitta, Lorena
Bucolo, Maide
A 3D-Printed Micro-Optofluidic Chamber for Fluid Characterization and Microparticle Velocity Detection
title A 3D-Printed Micro-Optofluidic Chamber for Fluid Characterization and Microparticle Velocity Detection
title_full A 3D-Printed Micro-Optofluidic Chamber for Fluid Characterization and Microparticle Velocity Detection
title_fullStr A 3D-Printed Micro-Optofluidic Chamber for Fluid Characterization and Microparticle Velocity Detection
title_full_unstemmed A 3D-Printed Micro-Optofluidic Chamber for Fluid Characterization and Microparticle Velocity Detection
title_short A 3D-Printed Micro-Optofluidic Chamber for Fluid Characterization and Microparticle Velocity Detection
title_sort 3d-printed micro-optofluidic chamber for fluid characterization and microparticle velocity detection
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10673365/
https://www.ncbi.nlm.nih.gov/pubmed/38004972
http://dx.doi.org/10.3390/mi14112115
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