Publicação
Optimizing parameters to improve PDMS surface wettability and the thermal conductivity analysis
| datacite.subject.fos | Engenharia e Tecnologia::Engenharia Mecânica | |
| datacite.subject.fos | Engenharia e Tecnologia::Nanotecnologia | |
| datacite.subject.sdg | 09:Indústria, Inovação e Infraestruturas | |
| dc.contributor.author | Neves, Lucas B. | |
| dc.contributor.author | Afonso, Inês S. | |
| dc.contributor.author | Barbosa, Luiz G. | |
| dc.contributor.author | Lima, Rui A. | |
| dc.contributor.author | Ribeiro, J.E. | |
| dc.date.accessioned | 2026-03-31T10:09:13Z | |
| dc.date.available | 2026-03-31T10:09:13Z | |
| dc.date.issued | 2025 | |
| dc.description.abstract | Due to its remarkable characteristics, Polydimethylsiloxane (PDMS) is widely used in microfluidic devices. However, despite its advantageous physical and chemical properties, its hydrophobic nature poses a challenge when pumping aqueous solutions through microchannels using only capillary forces. Various methods have been proposed to increase the hydrophilicity of PDMS; however, many struggle with hydrophobic recovery within a short time, whereas most commercial devices require long-term stability for storage and distribution. Incorporating surfactants into PDMS has become a promising technique for reducing hydrophobicity and regulating its recovery over time. However, selecting the right surfactant requires a thorough evaluation of its effectiveness, stability, and long-term durability in maintaining hydrophilicity. In this study, three non-ionic surfactants with different critical micelle concentrations and chemical compositions were compared: Triton X-100, Brij L4 (BL4), and Polyethylene Oxide (PEO). For this purpose, different surfactant concentrations, curing temperatures, and types of surfactants were compared. Short- and long-term experiments were conducted, where deionized water droplets were placed on the surface of PDMS mixed with surfactants to access wettability. Additionally, the influence of surfactants on thermal conductivity was analysed, using a Hot Disk 5501 sensor. The Taguchi method results identified the optimal sample as 2.5% PEO cured at 80°C, which achieved a contact angle of 12.8° immediately after curing and maintained superior wettability both at 0 hours and after 3 weeks of curing. For the initial thermal conductivity (0 h), the optimal sample was 0.5% TX-100 at 80°C, and after 3 weeks, BL4 2.5% at 25°C. To identify the best overall sample considering both tests, the Grey Relational Analysis method was applied. Additionally, an ANOVA statistical analysis was performed to evaluate the percentage of influence of each parameter, both in the Taguchi method, in individual tests, and in the Grey Relational Analysis combining both methods. | por |
| dc.description.sponsorship | Financial support was provided by Portugal’s national funding FCT/MCTES (PIDDAC) to Centro de Investigação de Montanha (CIMO) (UIDB/00690/2020 and UIDP/00690/2020) and SusTEC (LA/P/0007/2020). The authors additionally acknowledge the projects https://doi.org/10.54499/2022.02085.PTDC 2022.06207.PTDC (https://doi.org/10.54499/2022.06207.PTDC), PTDC/EEI-EEE/2846/2021 (https://doi.org/10.54499/PTDC/EEI-EEE/2846/2021), COMPETE2030- FEDER-00771500 for the partial financial support, through national funds (OE), within the scope of the Scientific Research and Technological Development Projects (IC&DT) program in all scientific domains (PTDC), PORTUGAL 2020 Partnership Agreement, European Regional Development Fund (FEDER), via the Foundation for Science and Technology, I.P. (FCT, I⋅P) and the R&D Units projects, UIDB/04077/2020, UIDB/00532/2020, and LA/P/0045/2020 (ALiCE). Glauco Nobrega was supported by the doctoral grant PRT/BD/153088/2021 (https://doi.org/10.54499/PRT/BD/153088/2021), financed by the Portuguese Foundation for Science and Technology (FCT), and with funds from MCTES/República Portuguesa, under the MIT Portugal Program. Inês S. Afonso was supported by the doctoral grant 2024.05919.BDANA, financed by FCT. | |
| dc.identifier.citation | Neves, L.; Afonso, I.; Barbosa, L.; Lima, Rui A.; Ribeiro, J.E.; Ribeiro, J.E. (2025). Optimizing parameters to improve PDMS surface wettability and the thermal conductivity analysis. Journal of Molecular Liquids. ISSN 0167-7322. 436, p. 1-11 | |
| dc.identifier.doi | 10.1016/j.molliq.2025.128204 | |
| dc.identifier.eissn | 1873-3166 | |
| dc.identifier.issn | 0167-7322 | |
| dc.identifier.uri | http://hdl.handle.net/10198/36416 | |
| dc.language.iso | eng | |
| dc.peerreviewed | yes | |
| dc.publisher | Elsevier | |
| dc.relation | Mountain Research Center - UIDB/00690/2020 | |
| dc.relation | Mountain Research Center - UIDP/00690/2020 | |
| dc.relation | Portable Microfluidic system for fast molecular diagnostics of Stroke | |
| dc.relation | Multiplexed micro(bio)sensors array integrated into an organ-on-a-chip device for assessing cancer NANOtherapy | |
| dc.relation | Transport Phenomena Research Center | |
| dc.relation | ALICE - Associate Laboratory in Chemical Engineering | |
| dc.relation | Mechanical Engineering and Resource Sustainability Center | |
| dc.relation | Seaweed nanofluids for cooling photovoltaic solar panels used in space missions (PRT/BD/153088/2021) | |
| dc.relation | i9OliveFluids: Development of innovative olive mill wastewaters for metalworking fluids | |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | |
| dc.subject | PDMS (polydimethylsiloxane) | |
| dc.subject | Microfluidic devices | |
| dc.subject | Non-ionic surfactants | |
| dc.subject | Hydrophobicity optimization | |
| dc.title | Optimizing parameters to improve PDMS surface wettability and the thermal conductivity analysis | eng |
| dc.type | journal article | |
| dspace.entity.type | Publication | |
| oaire.awardNumber | UIDB/00690/2020 | |
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| oaire.awardTitle | Portable Microfluidic system for fast molecular diagnostics of Stroke | |
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| oaire.citation.endPage | 11 | |
| oaire.citation.startPage | 1 | |
| oaire.citation.title | Journal of Molecular Liquids | |
| oaire.citation.volume | 436 | |
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| person.familyName | Ribeiro | |
| person.givenName | J.E. | |
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