PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
May 9, 2026Medical Engineering & Physics0 citationsOpen Access

Development of acoustic systems for ultrasound attenuation measurement in polydimethylsiloxane (PDMS)

View Full Paper
MMMathis Pierre Claude MartinPDPascal DargentWUW. Urbach

Key Points

  • This research aims to determine the ultrasound attenuation coefficient of polydimethylsiloxane (PDMS) for microfluidic applications.
  • Two measurement methods were compared: vector network analyzer (VNA) and pulse transmission method.
  • Ten PDMS samples with thicknesses from 2.5 to 18.5 mm were tested before and after 24-hour water immersion.
  • Measurements were taken within a frequency range of 1-3 MHz.
  • The attenuation coefficient for 5 mm thick microfluidic chip was approximately 21% at 1 MHz and 68% at 3 MHz, affecting cell stimulation significantly.

Abstract

Ultrasound absorption by polydimethylsiloxane (PDMS) can have a significant impact on the acoustic radiation force needed for stimulation of cells in organ-on-a-chip. Hence, finding the PDMS attenuation coefficient is the key to determine the fraction of absorbed acoustic energy in microfluidic systems. To measure the attenuation coefficient of PDMS, two methods were compared: a vector network analyzer (VNA) and a pulse transmission method. Ten PDMS samples with thicknesses ranging from 2.5 to 18.5 mm were tested both before and after 24-hour water immersion. The attenuation coefficient of PDMS, commonly used in microfluidics, was determined within a frequency range relevant to human health, i.e. 1-3 MHz. For a representative 5 mm thick microfluidic chip, the fraction of absorbed acoustic energy (E) is estimated to be approximately 21% at 1 MHz and 68% at 3 MHz. This level of absorption is expected to substantially modulate cell stimulation mediated by acoustic radiation forces.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Martin et al. (2026) studied this question.

synapsesocial.com/papers/69fececcb9154b0b82876078https://doi.org/10.1088/1873-4030/ae691f
Ask AI
Helpful
Bookmark
Share
View Full Paper