An Experimental Evaluation of Resistive Defects and Different Testing Solutions in Low-Power Back-Biased SRAM Cells

This paper compares different types of resistive defects that may occur inside low-power SRAM cells, focusing on their impact on device operation. Notwithstanding the continuous evolution of SRAM device integration, manufacturing processes continue to be very sensitive to production faults, giving rise to defects that can be modeled as resistances, especially for devices designed to work in low-power modes. This work analyzes this type of resistive defect that may impair the device functionalities in subtle ways, depending on the defect characteristics and values that may not be directly or easily detectable by traditional test methods. We analyze each defect in terms of the possible effects inside the SRAM cell, its impact on power consumption, and provide guidelines for selecting the best test methods.

Advanced Soft Defect Screen Methodology for Nano-Scale SRAM Yield Improvement

As technology scales down, the density of Static Random Access Memory (SRAM) devices increases drastically, and their storage capacity grows at the same time. Moreover, SRAMs become more prone to physical defects in each technology node. In addition, resistive defects and parametric defects are increasing which are hard to detect by the conventional test. Thus, the need of effective tests with high fault coverage and low cost increases. In this work, we study the reuse of assist technique (read and write assist) and timing margin control technique, commonly applied to improve the functional margins of SRAM core-cells, to improve the coverage of hard-to-detect marginal defects. This analysis is based on extensive injection of resistive bridging defects in core-cells of a commercial low-power SRAM. We show that assist circuits and timing control circuits can be leveraged to increase the defect coverage can be increases up to 28% at nominal operation voltage by simulation. Some successful case studies are also discussed to demonstrate the efficiency of the proposed electrical stress test methodology.

Non-Destructive Vector Fault Locator to Detect Resistive Open Defects in Static Random Access Memory with Improved Performance

The efforts in the semiconductor industry lead to the up-gradation of device size and performance of the devices. Extensive use of cache memory with significant size has become the requirement of most devices, applications, and gadgets. Advanced nanotechnology has resulted in scaled devices and more components with complex circuitry on system-on-chip. The memories are placed incredibly more profound in the die, and memory pins are not accessible readily, leading to more complications in testing the memories. The manufacturing of scaled devices is also a challenging task. A slight variation in doping concentration or process, supply voltage, temperature variations leads to faults in the memory. Advanced technology has increased the possibilities of occurrences of resistive defects in memories. For the smooth operation of systems with high reliability, it is essential to detect all the defects in the memory. In this paper, the detection of resistive defects is proposed at an early stage to increase the life span of the memory cells. Feeble cell detected at an early stage inhibits the more mutilation of the cells and improves memory reliability. An extensive range of defective values is used to analyze the proposed method to cover all positions of the defects in the cell. The proposed method detects the resistive defects with a minimum test time of 81.95μs for 4KB of the memory and contributes a negligible area overhead of 0.77%.

Evaluation of Single Event Upset Susceptibility of FinFET-based SRAMs with Weak Resistive Defects

Fin Field-Effect Transistor (FinFET) technology enables the continuous downscaling of Integrated Circuits (ICs), using the Complementary Metal-Oxide Semiconductor (CMOS) technology in accordance with the More Moore domain. Despite demonstrating improvements on short channel effect and overcoming the growing leakage problem of planar CMOS technology, the continuity of feature size miniaturization tends to increase sensitivity to Single Event Upsets (SEUs) caused by ionizing particles, especially in blocks with higher transistor densities such as Static Random-Access Memories (SRAMs). Variation during the manufacturing process has introduced different types of defects that directly affect the SRAM's reliability, such as weak resistive defects. As some of these defects may cause dynamic faults, which require more than one consecutive operation to sensitize the fault at the logic level, traditional test approaches may fail to detect them, and test escapes may occur. These undetected faults, associated with weak resistive defects, may affect the FinFET-based SRAM reliability during its lifetime. In this context, this paper proposes to investigate the impact of ionizing particles on the reliability of FinFET-based SRAMs in the presence of weak resistive defects. Firstly, a TCAD model of a FinFET-based SRAM cell is proposed allowing the evaluation of the ionizing particle’s impact. Then, SPICE simulations are performed considering the current pulse parameters obtained with TCAD. In this step, weak resistive defects are injected into the FinFET-based SRAM cell. Results show that weak defects can positively or negatively influence the cell reliability against SEUs caused by ionizing particles.