Ultra-fast data sanitization of SRAM by back-biasing to resist a cold boot attack.

Although SRAM is a well-established type of volatile memory, data remanence has been observed at low temperature even for a power-off state, and thus it is vulnerable to a physical cold boot attack. To address this, an ultra-fast data sanitization method within 5 ns is demonstrated with physics-based simulations for avoidance of the cold boot attack to SRAM. Back-bias, which can control device parameters of CMOS, such as threshold voltage and leakage current, was utilized for the ultra-fast data sanitization. It is applicable to temporary erasing with data recoverability against a low-level attack as well as permanent erasing with data irrecoverability against a high-level attack.

Cointegration of single-transistor neurons and synapses by nanoscale CMOS fabrication for highly scalable neuromorphic hardware.

Cointegration of multistate single-transistor neurons and synapses was demonstrated for highly scalable neuromorphic hardware, using nanoscale complementary metal-oxide semiconductor (CMOS) fabrication. The neurons and synapses were integrated on the same plane with the same process because they have the same structure of a metal-oxide semiconductor field-effect transistor with different functions such as homotype. By virtue of 100% CMOS compatibility, it was also realized to cointegrate the neurons and synapses with additional CMOS circuits. Such cointegration can enhance packing density, reduce chip cost, and simplify fabrication procedures. The multistate single-transistor neuron that can control neuronal inhibition and the firing threshold voltage was achieved for an energy-efficient and reliable neural network. Spatiotemporal neuronal functionalities are demonstrated with fabricated single-transistor neurons and synapses. Image processing for letter pattern recognition and face image recognition is performed using experimental-based neuromorphic simulation.

Ternary logic decoder using independently controlled double-gate Si-NW MOSFETs.

A ternary logic decoder (TLD) is demonstrated with independently controlled double-gate (ICDG) silicon-nanowire (Si-NW) MOSFETs to confirm a feasibility of mixed radix system (MRS). The TLD is essential component for realization of the MRS. The ICDG Si-NW MOSFET resolves the limitations of the conventional multi-threshold voltage (multi-Vth) schemes required for the TLD. The ICDG Si-NW MOSFETs were fabricated and characterized. Afterwards, their electrical characteristics were modeled and fitted semi-empirically with the aid of SILVACO ATLAS TCAD simulator. The circuit performance and power consumption of the TLD were analyzed using ATLAS mixed-mode TCAD simulations. The TLD showed a power-delay product of 35 aJ for a gate length (LG) of 500 nm and that of 0.16 aJ for LG of 14 nm. Thanks to its inherent CMOS-compatibility and scalability, the TLD based on the ICDG Si-NW MOSFETs would be a promising candidate for a MRS using ternary and binary logic.