NEGATIVE BIAS TEMPERATURE INSTABILITY STUDIES FOR ANALOG SOC CIRCUITS

Negative Bias Temperature Instability (NBTI) is one of the recent reliability issues in sub threshold CMOS circuits. NBTI effect on analog circuits, which require matched device pairs and mismatches, will cause circuit failure. This work is to assess the NBTI effect considering the voltage and the temperature variations. It also provides a working knowledge of NBTI awareness to the circuit design community for reliable design of the SOC analog circuit. There have been numerous studies to date on the NBTI effect to analog circuits. However, other researchers did not study the implication of NBTI stress on analog circuits utilizing bandgap reference circuit. The reliability performance of all matched pair circuits, particularly the bandgap reference, is at the mercy of aging differential. Reliability simulation is mandatory to obtain realistic risk evaluation for circuit design reliability qualification. It is applicable to all circuit aging problems covering both analog and digital. Failure rate varies as a function of voltage and temperature. It is shown that PMOS is the reliabilitysusceptible device and NBTI is the most vital failure mechanism for analog circuit in sub-micrometer CMOS technology. This study provides a complete reliability simulation analysis of the on-die Thermal Sensor and the Digital Analog Converter (DAC) circuits and analyzes the effect of NBTI using reliability simulation tool. In order to check out the robustness of the NBTI-induced SOC circuit design, a bum-in experiment was conducted on the DAC circuits. The NBTI degradation observed in the reliability simulation analysis has given a clue that under a severe stress condition, a massive voltage threshold mismatch of beyond the 2mV limit was recorded. Bum-in experimental result on DAC proves the reliability sensitivity of NBTI to the DAC circuitry

Simulation study of scaling design, performance characterization, statistical variability and reliability of decananometer MOSFETs

This thesis describes a comprehensive, simulation based scaling study – including device design, performance characterization, and the impact of statistical variability – on deca-nanometer bulk MOSFETs. After careful calibration of fabrication processes and electrical characteristics for n- and p-MOSFETs with 35 nm physical gate length, 1 nm EOT and stress engineering, the simulated devices closely match the performance of contemporary 45 nm CMOS technologies. Scaling to 25 nm, 18 nm and 13 nm gate length n and p devices follows generalized scaling rules, augmented by physically realistic constraints and the introduction of high-k/metal-gate stacks. The scaled devices attain the performance stipulated by the ITRS. Device a.c. performance is analyzed, at device and circuit level. Extrinsic parasitics become critical to nano-CMOS device performance. The thesis describes device capacitance components, analyzes the CMOS inverter, and obtains new insights into the inverter propagation delay in nano-CMOS. The projection of a.c. performance of scaled devices is obtained. The statistical variability of electrical characteristics, due to intrinsic parameter fluctuation sources, in contemporary and scaled decananometer MOSFETs is systematically investigated for the first time. The statistical variability sources: random discrete dopants, gate line edge roughness and poly-silicon granularity are simulated, in combination, in an ensemble of microscopically different devices. An increasing trend in the standard deviation of the threshold voltage as a function of scaling is observed. The introduction of high-k/metal gates improves electrostatic integrity and slows this trend. Statistical evaluations of variability in Ion and Ioff as a function of scaling are also performed. For the first time, the impact of strain on statistical variability is studied. Gate line edge roughness results in areas of local channel shortening, accompanied by locally increased strain, both effects increasing the local current. Variations are observed in both the drive current, and in the drive current enhancement normally expected from the application of strain. In addition, the effects of shallow trench isolation (STI) on MOSFET performance and on its statistical variability are investigated for the first time. The inverse-narrow-width effect of STI enhances the current density adjacent to it. This leads to a local enhancement of the influence of junction shapes adjacent to the STI. There is also a statistical impact on the threshold voltage due to random STI induced traps at the silicon/oxide interface

A Study of Nanometer Semiconductor Scaling Effects on Microelectronics Reliability

The desire to assess the reliability of emerging scaled microelectronics technologies through faster reliability trials and more accurate acceleration models is the precursor for further research and experimentation in this relevant field. The effect of semiconductor scaling on microelectronics product reliability is an important aspect to the high reliability application user. From the perspective of a customer or user, who in many cases must deal with very limited, if any, manufacturer's reliability data to assess the product for a highly-reliable application, product-level testing is critical in the characterization and reliability assessment of advanced nanometer semiconductor scaling effects on microelectronics reliability. This dissertation provides a methodology on how to accomplish this and provides techniques for deriving the expected product-level reliability on commercial memory products. Competing mechanism theory and the multiple failure mechanism model are applied to two separate experiments; scaled SRAM and SDRAM products. Accelerated stress testing at multiple conditions is applied at the product level of several scaled memory products to assess the performance degradation and product reliability. Acceleration models are derived for each case. For several scaled SDRAM products, retention time degradation is studied and two distinct soft error populations are observed with each technology generation: early breakdown, characterized by randomly distributed weak bits with Weibull slope Beta=1, and a main population breakdown with an increasing failure rate. Retention time soft error rates are calculated and a multiple failure mechanism acceleration model with parameters is derived for each technology. Defect densities are calculated and reflect a decreasing trend in the percentage of random defective bits for each successive product generation. A normalized soft error failure rate of the memory data retention time in FIT/Gb and FIT/cm2 for several scaled SDRAM generations is presented revealing a power relationship. General models describing the soft error rates across scaled product generations are presented. The analysis methodology may be applied to other scaled microelectronic products and key parameters