Jigang Ma

Negative bias temperature instability lifetime prediction: Problems and solutions

Lifetime of pMOSFETs is limited by NBTI. Conventional slow measurement overestimates lifetime due to recovery. The fast techniques suppress recovery, but cannot give reliable prediction. This work proposes a new lifetime prediction technique that overcomes the shortcomings of both slow and fast methods, based on the As-grown-Generation (AG) model. Its advantages over those based on Reaction-Diffusion (RD) and two-stage models include its simple algorithm, only two fitting parameters at a given temperature, and no need for a kinetic model for the as-grown hole traps. This makes it readily implementable in industrial laboratories for process screening.

Energy Distribution of Positive Charges in

The high hole mobility of Ge makes it a strong candidate for end of roadmap pMOSFETs and low interface states have been achieved for the Al2O3-GeO2-Ge gate-stack. This structure, however, suffers from significant negative bias temperature instability (NBTI), dominated by positive charge (PC) in Al2O3/GeO2. An in-depth understanding of the PCs will assist in the minimization of NBTI and the defect energy distribution will provide valuable information. The energy distribution also provides the effective charge density at a given surface potential, a key parameter required for simulating the impact of NBTI on device and circuit performance. For the first time, this letter reports the energy distribution of the PC in Al2O3/GeO2 on Ge. It is found that the energy density of the PC has a clear peak near Ge Ec at the interface and a relatively low level between Ec and Ev. Below Ev at the interface, it increases rapidly and screens 20% of the Vg rise.

{\rm Al}_{2}{\rm O}_{3}{\rm GeO}_{2}/{\rm Ge}

In this letter, dissolvable and biodegradable resistive switching devices with a cell structure of Mg/MgO/Mg were demonstrated. Electrical tests demonstrated good memory characteristics for nonvolatile application. The dissolution rate of Mg and MgO is characterized in deionized (DI) water and in phosphate-buffered saline solution, with clear difference, 0.36, 1.25, 0.057, and 0.13 nm/s, respectively. The Mg/MgO/Mg devices on silk fibroin substrates are able to be completely dissolved as fast as 30 min while immersed in DI water. The Mg/MgO/Mg devices have excellent prospects for the applications in transient electronics, secure memory systems, and implantable medical therapy devices.

pMOSFETs

Ge is a candidate for replacing Si, especially for pMOSFETs, because of its high hole mobility. For Si-pMOSFETs, negative-bias temperature instabilities (NBTI) limit their lifetime. There is little information available for the NBTI of Ge-pMOSFETs with Ge/GeO2/Al2O3 stack. The objective of this paper is to provide this information and compare the NBTI of Ge- and Si-pMOSFETs. New findings include: 1) the time exponent varies with stress biases/field when measured by either the conventional slow dc or pulse I-V technique, making the conventional Vg-accelerated method for predicting the lifetime of Si-pMOSFETs inapplicable to Ge-pMOSFETs used in this paper; 2) the NBTI is dominated by positive charges (PCs) in dielectric, rather than generated interface states; 3) the PC in Ge/GeO2/Al2O3 can be fully annealed at 150 °C; and 4) the defect losses reported for Si sample were not observed. For the first time, we report that the PCs in oxides on Ge and Si behave differently, and to explain the difference, an energy-switching model is proposed for hole traps in Ge-MOSFETs: their energy levels have a spread below the edge of valence band, i.e., Ev, when neutral, lift well above Ev after charging, and return below Ev following neutralization.

Dissolvable and Biodegradable Resistive Switching Memory Based on Magnesium Oxide

Non-filamentary RRAM is a promising technology that features self-rectifying, forming/compliance-free, tight resistance distributions at both high and low resistance states (HRS/LRS). Direct experimental evidence for its physical switching & failure mechanisms, however, is still missing, due to the lack of suitable characterization techniques. In this work, a novel method combining the random-telegraph-noise (RTN), constant-voltage-stress (CVS) and time-to-failure Weibull plot is developed to investigate these mechanisms in the non-filamentary RRAM cell based on amorphous-Si/TiO2. For the first time, the following key advances have been achieved: i) Switching mechanism by defect profile modulation in a critical interfacial region has been identified from defect locations extracted by RTN; ii) Defect profile in this region plays a critical role in device failure, leading to different Weibull distributions during negative (LRS) and positive (HRS) CVS; iii) Progressive formation of a conductive percolation path during electrical stress is directly observed due to defect generation in addition to pre-existing defect movement; iv) Optimizing the critical interfacial region significantly improves memory window and failure margin. This provides a useful tool for advancing the non-filamentary RRAM technology.

Characterization of Negative-Bias Temperature Instability of Ge MOSFETs With

To predict the negative bias temperature instability (NBTI) toward the end of pMOSFETs’ ten years lifetime, power-law-based extrapolation is the industrial standard method. The prediction accuracy crucially depends on the accuracy of time exponents, n. n reported by early work spreads in a wide range and varies with measurement conditions, which can lead to unacceptable errors when extrapolated to ten years. The objective of this paper is to find how to make n extraction independent of measurement conditions. After removing the contribution from as-grown hole traps, a new method is proposed to capture the generated defects (GDs) in their entirety. n extracted by this method is around 0.2 and insensitive to measurement conditions for the four fabrication processes we tested. The model based on this method is verified by comparing its prediction with measurements. Under ac operation, the model predicts that the GD can contribute to ~90% of NBTI at ten years.

{\rm GeO}_{2}/{\rm Al}_{2}{\rm O}_{3}

For the first time, an RTN based defect tracking technique has been developed that can monitor the defect movement and filament alteration in RRAM devices. Critical filament region has been identified during switching operation at various conditions and new endurance failure mechanism is revealed. This technique provides a useful tool for RRAM technology development.

Stack

Conventional lifetime prediction method developed for Si is inapplicable to Ge devices. This work demonstrates that the defects are different in Ge and Si devices. Based on the investigation of defect difference, for the first time, a method is developed for Ge devices to restore the power law for NBTI kinetics, enabling lifetime prediction. This method is applicable for both GeO2/Ge and Sicap/Ge devices, assisting in further Ge process/device optimization.

Identify the critical regions and switching/failure mechanisms in non-filamentary RRAM (a-VMCO) by RTN and CVS techniques for memory window improvement

Discreteness of aging-induced charges causes a Time-dependent Device-to-Device Variation (TDDV) and SRAM is vulnerable to it. This work analyses the shortcomings of existing methods for SRAM application and propose a new technique for its characterization. The key issues addressed include the SRAM-relevant sensing Vg, measurement speed, capturing the maximum degradation, separating device-to-device variation from within-device fluctuation, sampling rate, time window, and test device numbers.

Reliable Time Exponents for Long Term Prediction of Negative Bias Temperature Instability by Extrapolation

The high mobility germanium (Ge) channel is considered as a strong candidate for replacing Si in pMOSFETs in the near future. It has been reported that the conventional power-law degradation kinetics of Si devices is inapplicable to Ge. In this paper, 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. The three main differences are: 1) energy alternating defects (EAD) exist in Ge devices but are insignificant in Si; 2) the distribution of as-grown hole traps has a tail in the Ge bandgap but not in Si, which plays an important role in the degradation kinetics and device lifetime prediction; and 3) EAD generation in Ge devices requires the injected charge carriers to overcome a second 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.