Comment on “A symmetrical method to obtain shear moduli from microrheology” by K. Nishi, M. L. Kilfoil, C. F. Schmidt, and F. C. MacKintosh, <i>Soft Matter</i>, 2018, <b>14</b>, 3716

Tassieri, Manlio

doi:10.1039/c8sm00806j

Cited by 6 publications

(1 citation statement)

References 15 publications

(15 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Moreover, even when attempts are made to derive the materials' viscoelastic 185 properties directly from the analysis of S(ω), the use of predetermined fitting functions or Kramers-Kronig transformations are needed •• [61].…”

Section: Passive Motmentioning

confidence: 99%

Microrheology with optical tweezers: peaks & troughs

Tassieri

2019

Current Opinion in Colloid & Interface Science

Self Cite

View full text Add to dashboard Cite

Since their first appearance in the '70s, Optical Tweezers have been successfully exploited for a variety of applications throughout the natural sciences, revolutionising the field of micro-sensing. However, when adopted for microrheology studies, there exist some peaks & troughs on their modus operandi and data analysis that I wish to address and possibly iron out, providing a guide to future rheological studies from a microscopic perspective.

show abstract

Section: Passive Motmentioning

confidence: 99%

Microrheology with optical tweezers: peaks & troughs

Tassieri

2019

Current Opinion in Colloid & Interface Science

Self Cite

View full text Add to dashboard Cite

show abstract

Measurement of quasi-static and dynamic mechanical properties of soft materials based on instrumented indentation using a piezoelectric cantilever

Yao

2021

Polymer Testing

View full text Add to dashboard Cite

i-RheoFT: Fourier transforming sampled functions without artefacts

Smith

Gibson

Tassieri

2021

Sci Rep

Self Cite

View full text Add to dashboard Cite

In this article we present a new open-access code named “i-RheoFT” that implements the analytical method first introduced in [PRE, 80, 012501 (2009)] and then enhanced in [New J Phys 14, 115032 (2012)], which allows to evaluate the Fourier transform of any generic time-dependent function that vanishes for negative times, sampled at a finite set of data points that extend over a finite range, and need not be equally spaced. I-RheoFT has been employed here to investigate three important experimental factors: (i) the ‘density of initial experimental points’ describing the sampled function, (ii) the interpolation function used to perform the “virtual oversampling” procedure introduced in [New J Phys 14, 115032 (2012)], and (iii) the detrimental effect of noises on the expected outcomes. We demonstrate that, at relatively high signal-to-noise ratios and density of initial experimental points, all three built-in MATLAB interpolation functions employed in this work (i.e., Spline, Makima and PCHIP) perform well in recovering the information embedded within the original sampled function; with the Spline function performing best. Whereas, by reducing either the number of initial data points or the signal-to-noise ratio, there exists a threshold below which all three functions perform poorly; with the worst performance given by the Spline function in both the cases and the least worst by the PCHIP function at low density of initial data points and by the Makima function at relatively low signal-to-noise ratios. We envisage that i-RheoFT will be of particular interest and use to all those studies where sampled or time-averaged functions, often defined by a discrete set of data points within a finite time-window, are exploited to gain new insights on the systems’ dynamics.

show abstract

Comment on “A symmetrical method to obtain shear moduli from microrheology” by K. Nishi, M. L. Kilfoil, C. F. Schmidt, and F. C. MacKintosh, Soft Matter, 2018, 14, 3716

Abstract: We clarify some issues that were raised by an article that appeared in this journal (K. Nishi, M. L. Kilfoil, C. F. Schmidt, and F. C. MacKintosh, Soft Matter, 2018, 14, 3716).

Cited by 6 publications

References 15 publications

Microrheology with optical tweezers: peaks & troughs

Microrheology with optical tweezers: peaks & troughs

Measurement of quasi-static and dynamic mechanical properties of soft materials based on instrumented indentation using a piezoelectric cantilever

i-RheoFT: Fourier transforming sampled functions without artefacts

Contact Info

Product

Resources

About