David C. Lin

TL;DR: This paper compiled a series of synergistic strategies into an algorithm that overcomes many of the complications that have previously impeded efforts to automate the fitting of contact mechanics models to indentation data, and allows for improved consistency and minimized user intervention.

TL;DR: Although this finding supports the generally accepted view that many soft materials can be assumed to be linear elastic at small deformations, the nonlinear models facilitate analysis of intrinsically nonlinear tissues and large-strain indentation behavior.

TL;DR: This work surveys recent progress in the application of nanoindentation to characterize the local mechanical properties of polymer gels and biological tissues and stresses the need for contact mechanics models that more accurately represent the large-strain behaviour of soft matter.

TL;DR: The authors' comprehensive algorithm for automated extraction of Young's moduli from AFM indentation data has been expanded to recognize the presence of either adhesive or Hertzian behavior and apply the appropriate contact model.

TL;DR: This framework is then used to address how the network elasticity becomes modified when the network cross-linking is thermoreversible in nature, changes in the stability of the network with deformation, and the effect of a variable rate of network deformation on the non-linear elastic response.