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Bayesian inference of the viscoelastic properties of a Jeffrey's fluid using optical tweezers

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2021

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Scientific Reports. Springer Nature. 2021, 11(1), 2023. eISSN 2045-2322. Available under: doi: 10.1038/s41598-021-81094-x

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Bayesian inference is a conscientious statistical method which is successfully used in many branches of physics and engineering. Compared to conventional approaches, it makes highly efficient use of information hidden in a measured quantity by predicting the distribution of future data points based on posterior information. Here we apply this method to determine the stress-relaxation time and the solvent and polymer contributions to the frequency dependent viscosity of a viscoelastic Jeffrey's fluid by the analysis of the measured trajectory of an optically trapped Brownian particle. When comparing the results to those obtained from the auto-correlation function, mean-squared displacement or the power spectrum, we find Bayesian inference to be much more accurate and less affected by systematic errors.

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ISO 690PAUL, Shuvojit, Narinder NARINDER, Ayan BANERJEE, K. Rajesh NAYAK, Jakob STEINDL, Clemens BECHINGER, 2021. Bayesian inference of the viscoelastic properties of a Jeffrey's fluid using optical tweezers. In: Scientific Reports. Springer Nature. 2021, 11(1), 2023. eISSN 2045-2322. Available under: doi: 10.1038/s41598-021-81094-x
BibTex
@article{Paul2021-01-21Bayes-52788,
  year={2021},
  doi={10.1038/s41598-021-81094-x},
  title={Bayesian inference of the viscoelastic properties of a Jeffrey's fluid using optical tweezers},
  number={1},
  volume={11},
  journal={Scientific Reports},
  author={Paul, Shuvojit and Narinder, Narinder and Banerjee, Ayan and Nayak, K. Rajesh and Steindl, Jakob and Bechinger, Clemens},
  note={Article Number: 2023}
}
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