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Sectioning soft materials with an oscillating blade.
- Source :
-
Precision Engineering . Mar2019, Vol. 56, p96-100. 5p. - Publication Year :
- 2019
-
Abstract
- Abstract Sectioning soft tissues, e.g., brain, into thin slices is frequently performed using an oscillating blade microtome; it is generally observed that a combination of normal and shear cutting forces at an appropriate frequency will minimize the material deformation, leading to better sectioning results. To understand and better exploit this phenomenon, we theoretically and experimentally study the cutting mechanism of soft materials using a custom-built oscillating blade microtome. Analytical models are derived to deterministically link the sectioning quality to the cutting parameters, including blade oscillation frequency, amplitude, and sample feed rate. Experiments have been performed on 2% agarose gels to verify the predicted results over a range of operating parameters. Importantly, for the first time the study reveals that the sectioning results given by microtomes can be greatly enhanced when the cutting frequency is above 150 Hz due to the material stiffening effect—a unique trait of viscoelastic materials. The model may be used to predict the optimal cutting parameters for various tissues. As most state-of-the-art microtomes operate below 100 Hz, the results also set the new requirements for the next-generation tissue sectioning and surgical instruments. Highlights • A new parametric model that explains the cutting mechanisms of soft materials using an oscillating blade. • For the first time, the analytical modeldeterministically links the sectioning quality to the cutting parameters. • The sectioning quality will be enhanced at high cutting frequency (> 150 Hz) due to the material stiffening effect. • As all microtomes operate < 100 Hz, the model sets new requirements for future tissue sectioning and surgical instruments. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 01416359
- Volume :
- 56
- Database :
- Academic Search Index
- Journal :
- Precision Engineering
- Publication Type :
- Academic Journal
- Accession number :
- 135661453
- Full Text :
- https://doi.org/10.1016/j.precisioneng.2018.11.002