A memristor is characterized by its electrical memory resistance (memristance), which is a function of the historic profile of the applied current (voltage). Using this unique ability, we proposed novel memristive charge- and flux-based sensing schemes that reduce the capacitance, inductance, and power measurements to a straightforward resistance measurement. The memristive measurement seeks a memristor with a constant modulation of the memristance (memductance) for charge (flux)-based measurement. The dynamic properties of a propagating magnetic domain wall in different shape geometrical structures (figure 1b) make the spintronic memristor suitable for the charge-based capacitance and flux-based inductance measurements.
Electrical manipulation of the magnetization orientation using the Spin Transfer Torque (STT) effect has great application potential for future nanoscale spintronic devices. The STT mechanism also provides memristive capabilities to the electronic devices, for which the total electrical resistance through a Magnetic Tunnel Junction (MTJ) depends upon the magnetization state. The STT effect eliminates the difference between reading and writing in conventional Magnetoresistive Random Access Memory (MRAM) and shows great promise for enabling highly scalable and low power STT-MRAM. In STT-MRAM, the magnetization direction of the free layer in the magnetic tunnel junction is reversed by the (spin) current. We have shown the possibility of the realization of a logic operation (figure 2a) named material implication (p IMP q; equivalent to "(NOT p) OR q") in the two different circuit topologies (figure 2b and 2c), each including a conventional resistor and two MTJs. The generalization of these spintronic IMP gates to a nonvolatile logic-in-memory system enables extending nonvolatile electronics from memory to logical computing applications, for which the STT-MTJ cells serve simultaneously as logic gates and latches. This can improve the conventional CMOS logic, which combines logic circuits and memory elements to transfer the information back and forth between them and opens the door for innovation in computational paradigms by shifting away from the Von Neumann architecture.