In this paper a multifunctional tactile sensor system using PVDF (polyvinylidene fluoride),
is proposed, designed, analyzed, tested and validated. The working principle of the sensor is
in such a way that it can be used in combination with almost any end-effectors.
However, the sensor is particularly designed to be integrated with minimally
invasive surgery (MIS) tools. In addition, the structural and transduction materials
are selected to be compatible with micro-electro-mechanical systems (MEMS)
technology, so that miniaturization would be possible. The corrugated shape of the
sensor ensures the safe tissue grasping and compatibility with the traditional
tooth-like end effectors of MIS tools. A unit of this sensor comprised of a base, a
flexible beam and three PVDF sensing elements. Two PVDF sensing elements
sandwiched at the end supports work in thickness mode to measure the magnitude and
position of applied load. The third PVDF sensing element is attached to the
beam and it works in the extensional mode to measure the softness of the contact
object. The proposed sensor is modeled both analytically and numerically and a
series of simulations are performed in order to estimate the characteristics of the
sensor in measuring the magnitude and position of a point load, distributed load,
and also the softness of the contact object. Furthermore, in order to validate the
theoretical results, the prototyped sensor was tested and the results are compared. The
results are very promising and proving the capability of the sensor for haptic
sensing.
Due to their exceptional properties, graphene and hexagonal boron nitride (h‐BN) nanofillers are emerging as potential candidates for reinforcing the polymer‐based nanocomposites. Graphene and h‐BN have comparable mechanical and thermal properties, whereas due to high band gap in h‐BN (~5 eV), have contrasting electrical conductivities. Atomistic modeling techniques are viable alternatives to the costly and time‐consuming experimental techniques, and are accurate enough to predict the mechanical properties, fracture toughness, and thermal conductivities of graphene and h‐BN‐based nanocomposites. Success of any atomistic model entirely depends on the type of interatomic potential used in simulations. This review article encompasses different types of interatomic potentials that can be used for the modeling of graphene, h‐BN, and corresponding nanocomposites, and further elaborates on developments and challenges associated with the classical mechanics‐based approach along with synergic effects of these nano reinforcements on host polymer matrix.
This article is categorized under:
Molecular and Statistical Mechanics > Molecular Mechanics
Structure and Mechanism > Computational Materials Science
Molecular and Statistical Mechanics > Molecular Dynamics and Monte‐Carlo Methods
Aim of this article was to investigate the effect of grain boundaries on the interfacial properties of bi-crystalline graphene/polyethylene based nanocomposites. Molecular dynamics based atomistic simulations were performed in conjunction with the reactive force field parameters to capture atomic interactions within graphene and polyethylene atoms, whereas non-bonded interactions were considered for the interfacial properties. Atoms at the higher energy state in bi-crystalline graphene helps in improving the interaction at the nanocomposite interphase. Geometrical imperfections such as wrinkles and ripples helps the bi-crystalline graphene in increasing the number of adhesion points between the nanofiller and matrix, which eventually improves the strength and toughness of nanocomposite. These outcomes will help in opening new opportunities for defective nanofillers in the development of nanocomposites for future applications.
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