4,970 research outputs found
Electromechanical Probing of Ionic Currents in Energy Storage Materials
The electrochemical processes in energy storage materials are generally
linked with changes of molar volume of the host compound. Here, the frequency
dependent strain response of 1D electrochemically active systems to periodic
electric bias is analyzed. The sensitivity and resolution of these
electrochemical strain measurements are compared to the current-based
electrochemical impedance spectroscopy. The resolution and detection limits of
interferometric and atomic force microscopy based systems for probing
electrochemical reactions on the nanoscale are analyzed.Comment: 12 pages, 4 figures, 2 tables, 2 appendices, submitted to Appl. Phys.
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Pyroelectric response of ferroelectric nanoparticles: size effect and electric energy harvesting
The size effect on pyroelectric response of ferroelectric nanowires and
nanotubes is analyzed. The pyroelectric coefficient strongly increases with the
wire radius decrease and diverges at critical radius Rcr corresponding to the
size-driven transition into paraelectric phase. Size-driven enhancement of
pyroelectric coupling leads to the giant pyroelectric current and voltage
generation by the polarized ferroelectric nanoparticles in response to the
temperature fluctuation. The maximum efficiency of the pyroelectric energy
harvesting and bolometric detection is derived, and is shown to approach the
Carnot limit for low temperatures.Comment: 17 pages, 4 figures, 1 Appendi
Experimental and Theoretical Investigation into the Effect of the Electron Velocity Distribution on Chaotic Oscillations in an Electron Beam under Virtual Cathode Formation Conditions
The effect of the electron transverse and longitudinal velocity spread at the
entrance to the interaction space on wide-band chaotic oscillations in intense
multiple-velocity beams is studied theoretically and numerically under the
conditions of formation of a virtual cathode. It is found that an increase in
the electron velocity spread causes chaotization of virtual cathode
oscillations. An insight into physical processes taking place in a virtual
cathode multiple velocity beam is gained by numerical simulation. The
chaotization of the oscillations is shown to be associated with additional
electron structures, which were separated out by constructing charged particle
distribution functions.Comment: 9 pages, 8 figure
Mesoscopic mechanism of the domain wall interaction with elastic defects in ferroelectrics
The role of elastic defects on the kinetics of 180-degree uncharged
ferroelectric domain wall motion is explored using continuum time-dependent LGD
equation with elastic dipole coupling. In one dimensional case, ripples, steps
and oscillations of the domain wall velocity appear due to the wall-defect
interactions. While the defects do not affect the limiting-wall velocity vs.
field dependence, they result in the minimal threshold field required to
activate the wall motions. The analytical expressions for the threshold field
are derived and the latter is shown to be much smaller than the thermodynamic
coercive field. The threshold field is linearly proportional to the
concentration of defects and non-monotonically depends on the average distance
between them. The obtained results provide the insight into the mesoscopic
mechanism of the domain wall pinning by elastic defects in ferroelectrics.Comment: 18 pages, 6 figures, 1 appendi
FPGA Implementation of Convolutional Neural Networks with Fixed-Point Calculations
Neural network-based methods for image processing are becoming widely used in
practical applications. Modern neural networks are computationally expensive
and require specialized hardware, such as graphics processing units. Since such
hardware is not always available in real life applications, there is a
compelling need for the design of neural networks for mobile devices. Mobile
neural networks typically have reduced number of parameters and require a
relatively small number of arithmetic operations. However, they usually still
are executed at the software level and use floating-point calculations. The use
of mobile networks without further optimization may not provide sufficient
performance when high processing speed is required, for example, in real-time
video processing (30 frames per second). In this study, we suggest
optimizations to speed up computations in order to efficiently use already
trained neural networks on a mobile device. Specifically, we propose an
approach for speeding up neural networks by moving computation from software to
hardware and by using fixed-point calculations instead of floating-point. We
propose a number of methods for neural network architecture design to improve
the performance with fixed-point calculations. We also show an example of how
existing datasets can be modified and adapted for the recognition task in hand.
Finally, we present the design and the implementation of a floating-point gate
array-based device to solve the practical problem of real-time handwritten
digit classification from mobile camera video feed
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