Transient electrophoretic current in a nonpolar solvent

The transient electric current of surfactants dissolved in a nonpolar solvent is investigated both experimentally and theoretically in the parallel-plate geometry. Due to a low concentration of free charges the cell can be completely polarized by an external voltage of several volts. In this state, all the charged micelles are compacted against the electrodes. After the voltage is set to zero the reverse current features a sharp discharge spike and a broad peak. This shape and its variation with the compacting voltage are reproduced in a one-dimensional drift-diffusion model. The model reveals the broad peak is formed by a competition between an increasing number of charges drifting back to the middle of the cell and a decreasing electric field that drives the motion. After complete polarization is achieved, the shape of the peak stops evolving with further increase of the compacting voltage. The spike-peak separation time grows logarithmically with the charge content in the bulk. The time peak is a useful measure of the micelle mobility. Time integration of the peak yields the total charge in the system. By measuring its variation with temperature, the activation energy of bulk charge generation has been found to be 0.126 eV.Comment: 7 pages, 5 figure

Optimizing Write Fidelity of MRAMs by Alternating Water-filling Algorithm

Magnetic random-access memory (MRAM) is a promising memory technology due to its high density, non-volatility, and high endurance. However, achieving high memory fidelity incurs high write-energy costs, which should be reduced for large-scale deployment of MRAMs. In this paper, we formulate a biconvex optimization problem to optimize write fidelity given energy and latency constraints. The basic idea is to allocate non-uniform write pulses depending on the importance of each bit position. The fidelity measure we consider is mean squared error (MSE), for which we optimize write pulses via alternating convex search (ACS). We derive analytic solutions and propose an alternating water-filling algorithm by casting the MRAM’s write operation as communication over parallel channels. Hence, the proposed alternating water-filling algorithm is computationally more efficient than the original ACS while their solutions are identical. Since the formulated biconvex problem is non-convex, both the original ACS and the proposed algorithm do not guarantee global optimality. However, the MSEs obtained by the proposed algorithm are comparable to the MSEs by complicated global nonlinear programming solvers. Furthermore, we prove that our algorithm can reduce the MSE exponentially with the number of bits per word. For an 8-bit accessed word, the proposed algorithm reduces the MSE by a factor of 21. We also evaluate MNIST dataset classification supposing that the model parameters of deep neural networks are stored in MRAMs. The numerical results show that the optimized write pulses can achieve 40% write-energy reduction for the same classification accuracy. IEEEFALS