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In this work, a RTN analysis has been carried out to characterize the defects activated by forward-biased gate stress in GaN-HEMTs with Schottky p-GaN gate. The RTN signal, measured after each stress phase up to time-dependent gate breakdown, revealed four 1/f2 components. Three have been observed on both IG and ID, suggesting defects in the AlGaN barrier, whereas the last one showed up only on IG, possibly related to the Schottky depletion region.

IRPS 2024 Main Conference

Analysis of RTN Induced by Forward Gate Stress in GaN HEMTs with a Schottky p-GaN Gate

trapping effects

rtn analysis

pgan hemts

technical paper

#### Welcome to the 62nd IEEE International Reliability Physics Symposium (IRPS)! 
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**IRPS 2024 General Chair Welcome Message**

On behalf of the Management Committee of the IEEE International Reliability Physics Symposium (IRPS) and the IRPS Board of Directors, it gives me great pleasure to extend a warm welcome to all who are planning to attend the IRPS 2024, scheduled to take place from April 14-18, 2024, in Dallas, TX. 
Over its 62-year history, IRPS has solidified its position as the premiere conference for engineers and scientists to present new and original work in the field of microelectronics reliability. Drawing participants from the United States, Europe, Asia, and other parts of the world, IRPS aims to deepen our understanding of reliability of semiconductor devices, integrated circuits, and microelectronic assemblies through an improved understanding of both the physics of failure as well as the application environment. IRPS offers diverse opportunities for attendees to enhance their knowledge and understanding of all aspects of microelectronics reliability. It is also an outstanding chance to meet and network with reliability colleagues from around the world.

The IRPS 2024 technical activities will begin with two days of a total of twenty tutorial sessions covering a broad spectrum of emerging reliability topics beyond CMOS device, circuit and system reliability. These sessions are devoted to both newcomers as well as experts. Three reliability Year in Review (YIR) talks focusing on neuromorphic computing, dielectric breakdown in leading edge devices, and GaN technology will be provided on Monday after the tutorials.

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**About IRPS** 
The IEEE International Reliability Physics Symposium (IRPS) is the premiere conference for engineers and scientists to present new and original work in the area of microelectronics reliability. Drawing participants from the United States, Europe, Asia, and all parts of the world, IRPS seeks to understand the reliability of semiconductor devices, integrated circuits, and microelectronic assemblies through an improved understanding of both the physics of failure as well as the application environment. IRPS provides numerous opportunities for attendees to increase their knowledge and understanding of all aspects of microelectronics reliability, and to meet and network with reliability colleagues from around the world.

To access the site please register [**here**](https://www.irps.org/registration-fees). 

The IEEE International Reliability Physics Symposium (IRPS) is the premiere conference for engineers and scientists to present new and original work in the area of microelectronics reliability. IRPS seeks to understand the reliability of semiconductor devices, integrated circuits, and microelectronic assemblies through an improved understanding of both the physics of failure as well as the application environment. 

RTN in FinFET at cryogenic temperature is charaterized and RTN caused by traps near Metal/HfO2 interface interacting with gate can be observed, which is often overwhelmed by background noise at room temperature. Combining TCAD, the trap location can be determined. Furthermore, full quantumcalculations and compact modeling considering band tail states and interface trap states are conducted to obtain accurate trap parameters. The results reveal a remarkable variety of traps at cryogenic temperature.

New Insights into the Random Telegraph Noise (RTN) in FinFETs at Cryogenic Temperature

A novel deep learning-assisted trap extraction method is proposed to extract trap spatial and energetic distribution from the noise power spectral density (PSD). The method comprises two steps: 1) rough extraction using a Convolutional Neural Network and 2) refinement using a Backpropagation Optimization network. This automated approach achieves precise trap extraction with a mean difference as low as 1.5x.  The method is applied to a practical case and successfully extracts the trap distribution.

Deep Learning-Assisted Trap Extraction Method from Noise Power Spectral Density for MOSFETs

We present a characterization methodology for on-resistance and threshold voltage extraction through pulsed IV, where the transition from off-state to measurement phase is tuned to move from soft- to hard-switching. Results demonstrate that: i) RON may show significant increase (with saturation) moving from soft- to hard-switching; ii) VTH is strongly affected by hard-switching; iii) improved passivation results in lower on-resistance increase; iv) gate field plate length impacts RON increase with marginal effect on VTH shift.

Ron and Vth extraction in Hard-Switched E-mode GaN HEMTs: impact of passivation and layout

In this work, we reveal the presence of unique phonon-assisted hot electron transitions during semi-ON state operation of AlGaN/GaN HEMTs resulting in distinct self-heating behavior of the device. This establishes the importance of considering hot electron-triggered transitions, in addition to conventionally considered self-heating sources, while estimating heating effects in these devices. The phenomena are probed through detailed experimentation involving devices with different field plate lengths, electroluminescence microscopy and spectroscopy, and thermal imaging analysis.

Experimental Insights into the Role of Inter-valley and Defect Transitions of Hot Electrons in Determining Self-heating in AlGaN/GaN HEMTs

We show that thanks to the existence of NBTI, pFETs can be used to build a physical reservoir. We demonstrate this using the Compact-Physical (Comphy) framework for BTI modeling and substantiate it with a gait and voice authentication example. Subsequently, a hardware demonstration reveals that only 9 pFETs are sufficient to distinguish gait signals from different subjects. Notably, this implementation obviates the need for specialized device engineering, allowing for direct utilization of CMOS technology.

Exploiting Bias Temperature Instability for Reservoir Computing in Edge Artificial Intelligence Applications

The reliability issues of the In-3D-NAND approximate searching system for Hamming distance computing are evaluated and solved by optimized high VT level, recovery healing process, and reliability tracking array. The chip with optimized high Vt level can pass the commercial 3D-NAND retention criteria. Recovery healing can mitigate over-program issue in high data update situations. Tracking array enables sensing level calibration for long-term operations. The chip provides reliable in-memory database processing function suitable for neuromorphic computing.

Reliability Assessment for an In-3D-NAND Approximate Searching Solution

This work investigated the statistical modeling for post-programming conductance drift of 3-bit analog RRAM. We proposed a novel criterion, WRMSE, to substantiate that the conductance drift ought to be separated into two distinct phases: relaxation and RTN. We further developed a compact model based on CTMC to capture the variation of post-programming conductance distribution. The established model could provide useful guidelines for the future design of analog-RRAM based neuromorphic computing systems.

Statistical Modeling of Time-Dependent Post-Programming Conductance Drift in Analog RRAM

Recent discoveries of ferroelectricity and field-induced ferroelectricity in HfO2 and ZrO2 have led to increased interest in devices based on both materials, enabling a growing number of applications, including high aspect ratio ferroelectric capacitors and field effect transistors. One-transistor/one-capacitor memory arrays of Kbit to Gbit size are reported. From detailed reliability characterization, a complete picture of ferroelectric oxide/metal interface dynamics can be presented, explaining key reliability issues like field cycle endurance and retention.

Ferroelectric HfO2-based Capacitors for FeRAM: Reliability from Field Cycling Endurance to Retention

This work investigates the behavior of vth, subthreshold swing , and interface state density of commercial SiC MOSFETs during burn-in process. This study aims to determine the critical stress time to mitigate excessive Vth shift caused by the increase of Dit . The research approach offers insights for optimization of burn-in techniques in the industry, with the objective of reducing shift and preventing the degradation of the intrinsic lifetime of gate oxide while ensuring efficiency.

Evaluation of Burn-in Technique on Gate Oxide Reliability in Commercial SiC MOSFETs

An accelerated self-heating effect (SHE) simulation methodology is presented for GAAFETs, which, in combination with a compact thermal model that considers the geometry dependence of the device, can rapidly evaluate the SHE at the device-circuit level. The compact thermal model of 3nm GAAFET is developed and validated, and SHE can be evaluated in Open Model Interface based on the dynamic time evolution method, which ensures accuracy while significantly improving efficiency without introducing additional circuit nodes.

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Analysis of RTN Induced by Forward Gate Stress in GaN HEMTs with a Schottky p-GaN Gate

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New Insights into the Random Telegraph Noise (RTN) in FinFETs at Cryogenic Temperature

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