Microstructural and rheological training and memory of nanocolloidal soft glasses under cyclic shear
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| Format: | Preprint |
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2023
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| _version_ | 1866910851177381888 |
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| author | Chen, Yihao Rogers, Simon A. Narayanan, Suresh Harden, James L. Leheny, Robert L. |
| author_facet | Chen, Yihao Rogers, Simon A. Narayanan, Suresh Harden, James L. Leheny, Robert L. |
| contents | An intrinsic feature of disordered and out-of-equilibrium materials, such as glasses, is the dependence of their properties on their history. An important example is rheological memory, in which disordered solids obtain properties based on their mechanical history. Here, we employ x-ray photon correlation spectroscopy (XPCS) with \textit{in situ} rheometry to characterize memory formation in a nanocolloidal soft glass due to cyclic shear. During a cycle, particles undergo irreversible displacements composed of a combination of shear-induced diffusion and strain fields. The magnitudes of these displacements decrease with each cycle before reaching a steady state where the microstructure has become trained to achieve enhanced reversibility. The displacements resemble a random walk in which the directions in each cycle are independent of those in preceding cycles. Accompanying the training is a steady decrease in the dissipation during each cycle towards a steady state value. Memory of this training is revealed by measurements in which the amplitude of the shear is changed after steady state is reached. The magnitude of the particle displacements as well as the dissipation and the change in residual stress vary non-monotonically with the new strain amplitude, having minima near the training amplitude, thereby revealing both microscopic and macroscopic signatures of memory. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2312_17696 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Microstructural and rheological training and memory of nanocolloidal soft glasses under cyclic shear Chen, Yihao Rogers, Simon A. Narayanan, Suresh Harden, James L. Leheny, Robert L. Soft Condensed Matter Disordered Systems and Neural Networks Materials Science An intrinsic feature of disordered and out-of-equilibrium materials, such as glasses, is the dependence of their properties on their history. An important example is rheological memory, in which disordered solids obtain properties based on their mechanical history. Here, we employ x-ray photon correlation spectroscopy (XPCS) with \textit{in situ} rheometry to characterize memory formation in a nanocolloidal soft glass due to cyclic shear. During a cycle, particles undergo irreversible displacements composed of a combination of shear-induced diffusion and strain fields. The magnitudes of these displacements decrease with each cycle before reaching a steady state where the microstructure has become trained to achieve enhanced reversibility. The displacements resemble a random walk in which the directions in each cycle are independent of those in preceding cycles. Accompanying the training is a steady decrease in the dissipation during each cycle towards a steady state value. Memory of this training is revealed by measurements in which the amplitude of the shear is changed after steady state is reached. The magnitude of the particle displacements as well as the dissipation and the change in residual stress vary non-monotonically with the new strain amplitude, having minima near the training amplitude, thereby revealing both microscopic and macroscopic signatures of memory. |
| title | Microstructural and rheological training and memory of nanocolloidal soft glasses under cyclic shear |
| topic | Soft Condensed Matter Disordered Systems and Neural Networks Materials Science |
| url | https://arxiv.org/abs/2312.17696 |