TY - JOUR
T1 - Particle-motion-tracking Algorithm for the Evaluation of the Multi-physical Properties of Single Nanoparticles
AU - Park, Yeeun
AU - Kang, Geeyoon
AU - Park, Minsu
AU - Noh, Hyowoong
AU - Park, Hongsik
N1 - Publisher Copyright:
© 2022, Korean Sensors Society. All rights reserved.
PY - 2022/5
Y1 - 2022/5
N2 - The physical properties of biomaterials are important for their isolation and separation from body fluids. In particular, the precise evaluation of the multi-physical properties of single biomolecules is essential in that the correlation between physical and biological properties of specific biomolecule. However, the majority of scientific equipment, can only determine specific-physical properties of single nanoparticles, making the evaluation of the multi-physical properties difficult. The improvement of analytical techniques for the evaluation of multi-physical properties is therefore required in various research fields. In this study, we developed a motion-tracking algorithm to evaluate the multi-physical properties of single-nanoparticles by analyzing their behavior. We observed the Brownian motion and electric-field-induced drift of fluorescent nanoparticles injected in a microfluidic chip with two electrodes using confocal microscopy. The proposed algorithm is able to determine the size of the nanoparticles by i) removing the background noise from images, ii) tracking the motion of nanoparticles using the circular-Hough transform, iii) extracting the mean squared displacement (MSD) of the tracked nanoparticles, and iv) applying the MSD to the Stokes-Einstein equation. We compared the evaluated size of the nanoparticles with the size measured by SEM. We also determined the zeta-potential and surface-charge density of the nanoparticles using the extracted electrophoretic velocity and the Helmholtz-Smoluchowski equation. The proposed motion-tracking algorithm could be employed in various fields related to biomaterial analysis, such as exosome analysis.
AB - The physical properties of biomaterials are important for their isolation and separation from body fluids. In particular, the precise evaluation of the multi-physical properties of single biomolecules is essential in that the correlation between physical and biological properties of specific biomolecule. However, the majority of scientific equipment, can only determine specific-physical properties of single nanoparticles, making the evaluation of the multi-physical properties difficult. The improvement of analytical techniques for the evaluation of multi-physical properties is therefore required in various research fields. In this study, we developed a motion-tracking algorithm to evaluate the multi-physical properties of single-nanoparticles by analyzing their behavior. We observed the Brownian motion and electric-field-induced drift of fluorescent nanoparticles injected in a microfluidic chip with two electrodes using confocal microscopy. The proposed algorithm is able to determine the size of the nanoparticles by i) removing the background noise from images, ii) tracking the motion of nanoparticles using the circular-Hough transform, iii) extracting the mean squared displacement (MSD) of the tracked nanoparticles, and iv) applying the MSD to the Stokes-Einstein equation. We compared the evaluated size of the nanoparticles with the size measured by SEM. We also determined the zeta-potential and surface-charge density of the nanoparticles using the extracted electrophoretic velocity and the Helmholtz-Smoluchowski equation. The proposed motion-tracking algorithm could be employed in various fields related to biomaterial analysis, such as exosome analysis.
KW - Brownian motion
KW - Mean-squared displacement
KW - Motion-tracking algorithm
KW - Multi-physical properties
KW - Single-nanoparticle
UR - http://www.scopus.com/inward/record.url?scp=85168396336&partnerID=8YFLogxK
U2 - 10.46670/JSST.2022.31.3.175
DO - 10.46670/JSST.2022.31.3.175
M3 - Article
AN - SCOPUS:85168396336
SN - 1225-5475
VL - 31
SP - 175
EP - 179
JO - Journal of Sensor Science and Technology
JF - Journal of Sensor Science and Technology
IS - 3
ER -