The As-grown-Generation (AG) model: A reliable model for reliability prediction under real use conditions

Modeling the negative bias temperature instability (NBTI) can optimize circuit design. Several models have been proposed and all of them can fit test data well. These models are extracted typically by fitting short accelerated stress data. Their capability to predict NBTI aging outside the test range has not been fully demonstrated. This predictive capability for long term aging under low operation bias is what needed by circuit designers. In this work, we test the predictive capability of the well-known reaction-diffusion (RD) based framework for samples fabricated by a variety of processes. Results show that the RD model cannot make an acceptable generic prediction. The recently proposed As-grown-Generation (AG) model is then introduced. By dividing defects into two groups, as-grown and generated defects, and measuring the as-grown defects experimentally, we demonstrate that it can make reliable prediction for the same set of data where the RD model failed

Superderivations for Modular Graded Lie Superalgebras of Cartan-type

Superderivations for the eight families of finite or infinite dimensional graded Lie superalgebras of Cartan-type over a field of characteristic $p>3$ are completely determined by a uniform approach: The infinite dimensional case is reduced to the finite dimensional case and the latter is further reduced to the restrictedness case, which proves to be far more manageable. In particular, the outer superderivation algebras of those Lie superalgebras are completely determined

DEFECTS AND LIFETIME PREDICTION FOR GE PMOSFETS UNDER AC NBTI STRESSES

Germanium has higher hole mobility and is a candidate for replacing silicon for pMOSFETs. This work reviews the recent progresses in understanding the negative bias temperature instability (NBTI) of Ge pMOSFETs and compares it with SiON/Si devices. Both Ge and SiON/Si devices have two groups of defects: as-grown hole traps (AHT) and generated defects (GDs). The generation process, however, is different: GDs are interface-controlled for SiON/Si and dielectric-controlled for Ge devices. This leads to substantially higher GDs under DC stress than under AC stress for Ge, although they are similar for SiON/Si devices. Moreover, GDs alter their energy levels with charge status and can be reset to original precursor states after neutralization for Ge, but these processes are insignificant for SiON/Si. The impact of these differences on lifetime prediction will be presented and the defects and physical mechanism will be explored

DEFECTS FOR RANDOM TELEGRAPH NOISE AND NEGATIVE BIAS TEMPERATURE INSTABILITY

Random Telegraphy Noise (RTN) and Negative Bias Temperature Instability (NBTI) are two important sources of device instability. Their relation is not fully understood and is investigated in this work. We examine the similarity and differences of the defects responsible for them. By following the As-grown-Generation (AG) model proposed by our group, we present clear evidences that the As-grown hole traps (AHTs) are responsible for the RTN of pMOSFETs. AHTs also dominate NBTI initially, but the generated defects (GDs) become increasingly important for NBTI as stress time increases. The GDs, however, do not cause RTN

NBTI prediction and its induced time dependent variation

Negative bias temperature instability (NBTI) prediction relies on a reliable extraction of power exponents from its kinetics. When measured by fast pulse technique, however, the kinetics does not follow a power law. This paper reviews the recent progresses on how to restore the power law, based on the As-grown-Generation (AG) model. For nanometer sized devices, NBTI is different for different devices, inducing a time-dependent variation. The new technique proposed for characterizing this Time-dependent Variation accounting for within-a-device-Fluctuation (TVF) will be reviewed

Hot carrier aging of nano-scale devices: characterization method, statistical variation, and their impact on use voltage

Hot carrier aging (HCA) has attracted a lot of attentions recently, as it can be a lifetime limiting mechanism for both I/O and core devices. The applicability of the conventional characterization method developed for large devices to nano-scale devices is questionable, as nano-scale devices suffers from within-a-device-fluctuation (WDF). This work shows that the inclusion of WDF measured by the commercial quasi-DC SMU gives erroneous results. A method is proposed to separate the WDF from the real HCA for reliable parameter extraction of the HCA model. The lifetime and use voltage become yield dependent and the impact of statistical variations on SRAM is assessed

Assessing the Accuracy of Statistical Properties Extracted from a Limited Number of Device Under Test for Time Dependent Variations

As device sizes scale down, device variations scale up. There are two types of device-to-device variations (DDV): as-fabricated or time-zero DDV and the time dependent variations (TDV). Even if two nano-scaled devices were identical at time-zero, they would be different after stresses and result in TDV, since the defect generation and charging-discharging are stochastic. To characterize TDV, statistical properties, such as the mean value and standard deviation, are extracted from tests. Their accuracy improves as the number of device under tests (DUTs) increases. Ageing is time consuming and the typical DUTs used are in the range of tens to hundreds. There is little information on the accuracy of the statistical properties extracted from such a limited DUTs and the objective of this paper is to propose a methodology to assess it. Based on the defect-centric model, the accuracy with a specific confidence level is evaluated for a given number of DUTs and a stress level

Key issues and solutions for characterizing hot carrier aging of nano-meter scale nMOSFETs

Silicon bandgap limits the reduction of operation voltage when downscaling device sizes. This increases the electrical field within a device and hot carrier aging (HCA) is becoming an important reliability issue again for some CMOS technologies. For nano-devices, there are a number of challenges for characterizing their HCA: the random charge-discharge of traps in gate dielectric causes ‘within-a-device-fluctuation (WDF)’, making the parameter shift uncertain after a given HCA. This can introduce errors when extracting HCA time exponents and it will be shown that the lower envelope of the WDF must be used. Nano-devices also have substantial device-to-device variation (DDV) and multiple tests are needed for evaluating their standard deviation, σ, and mean value, µ. Repeating the time-consuming HCA tests is costly and a voltage-step-stress method is applied to reduce the number of tests by 80%. For a given number of devices under tests (DUTs), there is little information on the accuracy of the extracted σ and µ. We will develop a method to provide this information, based on the defect-centric model. For 40 DUTs with an average of 10 traps per device, the extracted µ and σ has an accuracy of ±14% and ±24% respectively with a 95% confidence

Differences between physical and human process simulation in geography: Empirical analysis of two cases

National Natural Science Foundation of China 41125005;Chinese Academy of Sciences KACX1-YW-1001Physical geography and human geography are the principal branches of the geographical sciences. Physical process simulation and human process simulation in geography are both quantitative methods used to recover past events and even to forecast events based on precisely determined parameters. There are four differences between physical process simulation and human process simulation in geography, which we summarize with two specific cases, one of which is about a typhoon's development and its precipitation, and the other of which is regarding the evolution of three industrial structures in China. The differences focus on four aspects: the main factors of the research framework; the knowledge background of the systematic analysis framework; the simulation data sources and quantitative method; and the core of the study object and the method of forecast application. As the human-land relationship is the key ideology of the man-land system, the relationship between the physical and human factors is becoming increasingly close at present. Physical process simulation and human process simulation in geography will exhibit crossing and blending in the future to reflect the various geographical phenomena better

A comparative study of defect energy distribution and its impact on degradation kinetics in GeO2/Ge and SiON/Si pMOSFETs

High mobility germanium (Ge) channel is considered as a strong candidate for replacing the Si in pMOSFETs in near future. It has been reported that the conventional power-law degradation kinetics of Si devices is inapplicable to Ge. In this work, further investigation is carried out on defect energy distribution, which clearly shows that this is because the defects in GeO2/Ge and SiON/Si devices have different physical properties. Three main differences are: 1) Energy alternating defects (EAD) exist in Ge devices but insignificant in Si; 2) The distribution of as-grown hole traps (AHT) has a tail in the Ge band gap but not in Si, which plays an important role in degradation kinetics and device lifetime prediction; 3) EAD generation in Ge devices requires the injected charge carriers to overcome a 2nd energy barrier, but not in Si. Taking the above differences into account, the power law kinetics of EAD generation can be successfully restored by following a new procedure, which can assist in the Ge process/device optimization