Title:	Inter-particle adhesion induced strong mechanical memory in a dense granular suspension
Authors:	Chattopadhyay, Sebanti Majumdar, Sayantan
Issue Date:	22-Jun-2022
Publisher:	American Institute of Physics
Citation:	Journal of Chemical Physics, 2022, Vol.156, p241102
Abstract:	Repeated/cyclic shearing can drive amorphous solids to a steady state encoding a memory of the applied strain amplitude. However, recent experiments find that the effect of such memory formation on the mechanical properties of the bulk material is rather weak. Here, we study the memory effect in a yield stress solid formed by a dense suspension of cornstarch particles in paraffin oil. Under cyclic shear, the system evolves toward a steady state showing training-induced strain stiffening and plasticity. A readout reveals that the system encodes a strong memory of the training amplitude (γT) as indicated by a large change in the differential shear modulus. We observe that memory can be encoded for a wide range of γT values both above and below the yielding albeit the strength of the memory decreases with increasing γT. In situ boundary imaging shows strain localization close to the shearing boundaries, while the bulk of the sample moves like a solid plug. In the steady state, the average particle velocity ⟨𝑣⟩ inside the solid-like region slows down with respect to the moving plate as γ approaches γT; however, as the readout strain crosses γT, ⟨𝑣⟩ suddenly increases. We demonstrate that inter-particle adhesive interaction is crucial for such a strong memory effect. Interestingly, our system can also remember more than one input only if the training strain with smaller amplitude is applied last
Description:	Restricted Access.
URI:	http://hdl.handle.net/2289/7968
ISSN:	0021-9606 1089-7690 (Online)
Alternative Location:	https://doi.org/10.1063/5.0089721
Copyright:	2022 American Institute of Physics
Appears in Collections:	Research Papers (SCM)

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