This manuscript investigates energy harvesting from arterial blood pressure via the piezoelectric effect for the purpose of powering embedded micro-sensors in the human brain. One of the major hurdles in recording and measuring electrical data in the human nervous system is the lack of implantable and long term interfaces that record neural activity for extended periods of time. Recently, some authors have proposed micro sensors implanted deep in the brain that measure local electrical and physiological data which are then communicated to an external interrogator. This paper proposes a way of powering such interfaces. The geometry of the proposed harvester consists of a piezoelectric, circular, curved bimorph that fits into the blood vessel (specifically, the Carotid artery) and undergoes bending motion because of blood pressure variation. In addition, the harvester thickness is constrained such that it does not modify arterial wall dynamics. This transforms the problem into a known strain problem and the integral form of Gauss's law is used to obtain an equation relating arterial wall motion to the induced voltage. The theoretical model is validated by means of a Multiphysics 3D-FEA simulation comparing the harvested power at different load resistances. The peak harvested power achieved for the Carotid artery (proximal to Brain), with PZT-5H, was 11.7 μW. The peak power for the Aorta was 203.4 μW. Further, the variation of harvested power with variation in the harvester width and thickness, arterial contractility, and pulse rate is investigated. Moreover, potential application of the harvester as a chronic, implantable and real-time Blood pressure sensor is considered. Energy harvested via this mechanism will also have applications in long-term, implantable Brain Micro-stimulation.

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This paper uses the method of Quadratures in conjunction with the Maximum Entropy principle to investigate the effect of parametric uncertainties on the mean power output and root mean square deflection of piezoelectric vibrational energy harvesting systems. Uncertainty in parameters of harvesters could arise from insufficient manufacturing controls or change in material properties over time. We investigate bimorph based harvesters that transduce ambient vibrations to electricity via the piezoelectric effect. Three varieties of energy harvesters — Linear, Nonlinear monostable and Nonlinear bistable are considered in this research. This analysis quantitatively shows the probability density function for the mean power and root mean square deflection as a function of the probability densities of the excitation frequency, excitation amplitude, initial deflection of the bimorph and magnet gap of the energy harvester. The method of Quadratures is used for numerically integrating functions by propagating weighted points from the domain and evaluating the integral as a weighted sum of the function values. In this paper, the method of Quadratures is used for evaluating central moments of the distributions of rms deflection and mean harvested power and, then, in conjunction with the principle of Maximum Entropy (MaxEnt) an optimal density function is obtained which maximizes the entropy and satisfies the moment constraints. The The computed nonlinear density functions are validated against Monte Carlo simulations thereby demonstrating the efficiency of the approach. Further, the Maximum Entropy principle is widely applicable to uncertainty quantification of a wide range of dynamic systems.

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This manuscript details the possibility of achieving one-way sound propagation using a smart fluid such as magnetorheological fluid (MRF) by subjecting it to a spatio-temporally varying magnetic field. The local speed of sound in MRF is dependent on applied magnetic field as demonstrated in several experimental works and this property of MRF has been leveraged, in this work, to induce one-way bandgaps. Initially, a general wave equation pertaining to fluid with space-and-time-varying material properties was derived. Assuming plane wave propagation in one dimension, an approximate Floquet solution was imposed and the dispersion relationship was obtained. A comprehensive finite element analysis was conducted and good agreement was noted between the numerical and theoretical dispersion relations. It was concluded that space-time periodic modulation of fluid density and local sound speed is necessary to induce asymmetry in the band diagram around the ω axis. The feasibility of real-world implementation using MRF has been discussed. A parametric study detailing the effect of viscosity on the one-way bandgaps has been undertaken. It was found that one-way bandgaps formed at relatively lower frequencies are more robust to viscous corruption. A real-world implementation may be feasible if the viscosity of MRF is less than 3000 Pa-s.