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Increasing demands for mass storage and new paradigm computing ask for non-volatile memories that can meet reliability requirements. Hf0.5Zr0.5O2-based (HZO) memory has attracted growing attention due to its excellent CMOS compatibility. This letter investigated the time dependent dielectric breakdown (TDDB) of HZO ferroelectric under both forward and reverse stress conditions, which is relevant to the memory’s practical operation. The key similarities and the differences for both breakdown conditions have been identified and the underlying mechanism is explored. It is found that the pre-existing oxygen vacancies near the bottom electrode play the key role and all the observed phenomenon can be explained. Therefore, the precise control of these pre-existing oxygen vacancies can be critical for future TDDB improvement.

Increasing renewable energy sources in power system has brought forth many challenges in terms of power system stability, one of which is voltage stability. Preventive and corrective actions to alleviate voltage instability are mainly developed for traditional power systems without high share of renewables. This article aims to assess the reactive power based voltage support from wind power plants under stressed voltage conditions. Firstly, the performances of the conventional wind power plant control strategies applied during stressed voltage conditions are studied. A novel enhanced wind power plant control strategy is developed, which increases wind power plant reactive power capability through control of wind power plant tap changing transformer. Performance of this novel strategy is compared and evaluated against the conventional wind power plant control strategies applied during the stressed voltage conditions. Results show that the developed control strategy helps in alleviating voltage instability 5% more effectively when compared to the conventional WPP control strategies applied during stressed voltage conditions. The developed control strategy is implemented and simulated in a snapshot of the Hellenic power system to verify the implementation feasibility and effectiveness in a real large power system.

To mimic outdoor photovoltaic (PV) degradation mechanisms, combinatory accelerated tests are being proposed. However, to design experiments that represent the diverse outdoor conditions, it requires considerable time and costs. In this case, mathematical models are used to simulate the different stress conditions that can be experienced in the field. In this paper, we present a model for combined ultraviolet-damp-heat conditions based on experimental observations. The model is applied to correlated indoor to outdoor conditions using monitored climatic from three different locations and also global climatic data extracted from ERA5 reanalysis. In the paper, it is shown that relative humidity has a big impact on degradation mechanisms induced during Ultraviolet-Damp-Heat conditions.

The combination of multiple accelerated stress conditions is critical to understanding and predicting the performance of PV module materials and designs over the > 30 year expected lifetime of the product. Several research groups have investigated this topic using either a multi-stress sequential stress approach or simultaneous stress approach with some success in predicting field performance. This paper describes an accelerated test approach that combines elements of both methods guided by modelling of temperature and moisture concentration in the module structure that best matches the outdoor environment. The total duration of the exposure and the correlation to field performance are key considerations in the test protocol method development. The effectiveness of this approach is demonstrated in modules with backsheets with known outdoor durability issues.

The study deals with health monitoring systems performing post-prognostic decision and maintenance indication tasks. An open issue in post-prognostics is the quantification, propagation, and management of uncertainty associated with the Remaining Useful Life (RUL) estimate. The research work aims to evaluate the impact of a posteriori estimated customer stress profiles by using functional profile modeling with a set of common RUL probability density functions (PDF). The proposed method enables to take into account the usage profiles, stress conditions, and idle states of machines to update the RUL estimate. Results are rather insensitive to the PDF associated to the RUL itself, while the estimates are more accurate with respect to methods that do not embed future loading information. Practical tuning details are also discussed for a real-life industrial case.

Manufacturing defects in FinFET SRAMs can cause hard-to-detect faults such as Undefined State Faults (USFs). Detection of USFs is not trivial, as they may not lead to incorrect functionality. Nevertheless, undetected USFs may have a severe impact on the memory’s quality: they can cause random read outputs, which might lead to test escapes and no-trouble-found devices later when the device is already in the field, as well as compromise the circuit’s quality by reducing the memory cell’s Static Noise Margin (SNM). Therefore, the detection of USF is critical. This paper proposes a test solution to improve the detection of USFs in FinFET SRAMs. To achieve this, we first analyze the impact of USFs on the cell’s SNM and bitline swing during read operations. Then, we perform an experimental study of stress conditions’ (SCs) impact on sensitizing and detecting USFs. Finally, we propose a dedicated Design-For-Testability (DFT) scheme for FinFET SRAMs to detect such faults. This scheme introduces a small area overhead while significantly improving USF detection. Hence, using the proposed DFT leads to fewer test escapes and higher-quality FinFET SRAMs.

In this paper, our recent studies on the hot carrier degradation (HCD) in FinFETs, as well as HCD-induced dynamic variability, are summarized. The kinetics and statistics of FinFET HCD are experimentally investigated. New observations on HCD are reported, which are due to the simultaneous generation of both interface and oxide traps. Based on the trap-based approach, instead of the conventional carrier-based approach, the HCD and its variations are well-described with the proposed multi trap-based compact models, that are unified over the full $\{V_{gs},V_{ds}\}$ bias region. The typical average locations of the HCD-induced traps in FinFET under the worst-case stress condition are also identified. The results are helpful for the physical understanding and modeling of HCD, and the reliability-aware circuit design for FinFET technology.

The incidence rate of diabetes has increased dramatically. However, there are still some problems in diagnosing diabetes based on blood glucose and other Physical examination target. For example, trauma or other stress conditions can cause temporary hyperglycemia, which can disrupt the diagnosis of diabetes. In order to solve above problems, a large-scale word vector model in the field of diabetes is constructed to better represent the diabetes related words, and a new hybrid prediction model called Diabetes hybrid convolution neural network (DhCNN) is proposed. The model integrates numerical physical examination data and patient's description of their own symptoms, which makes up for the defect that only one type of data leads to insufficient features in diabetes data. More features also enable the convolution layer to capture more disease features, thus improving the accuracy of diabetes prediction. Experimental results on multiple datasets show that DhCNN has better performance in prediction accuracy than machine learning-based models and deep learning models that use a single type of data, especially in datasets with insufficient number of features.

FinFET, which could be applied to sub 22 nm technology nodes, is the novel 3D transistor device structure to effectively inhibit short channel effect for the continuous microminiaturization of transistor components. This study focuses on the comparison of silicon and germanium, as the channel material, to FinFET for calculating carrier distribution and carrier mobility on inversion layer as well as the stress response. A mobility stress response model (piezomobility model) which could rapidly and accurately predict carrier mobility changes under different stress conditions is also investigated.

This paper presents an overview of the reliability differences of devices optimized for high-performance (HP) and medium-breakdown (MB) in SiGe HBT technologies. To explore the physics of failure, a MB variant in a fourth-generation SiGe HBT technology is described from a processing standpoint to understand any subtle distinctions between its HP counterpart. Reliability stress measurement data is shown to provide insight into the differences between HP and MB SiGe HBTs when biased under high-current and mixed-mode stress conditions. TCAD simulations are presented to aid in the physical understanding of Auger generation/recombination rates, impact ionization rates, and power density across a wide range of conditions where these devices are typically biased and used.

This paper is focused on the development of an intelligent system to identify if one person is stress or not stress using physiological parameters through machine learning. In this study, the dataset was acquired from three hundred (300) male and female participants ages 18 to 25. The gathered dataset is composed of five (5) features (i.e. heart rate, systolic blood pressure, diastolic blood pressure, galvanic skin response and gender). An intelligent system was developed using machine learning algorithms for classification such as Linear Regression (LR), K-Nearest Neighbor (KNN), and Support Vector Machine (SVM) using Python IDE with sci-kit learn machine learning libraries. Google Colaboratory (Colab) was utilized to perform optimization using Gridsearch to identify the best parameters of each algorithm. Feature selection methods are implemented to identify the most significant features related to stress condition of one person. After optimization, the results showed that SVM has the best performance to classify if one person is stress or not stress with optimized training-testing accuracy score of 95.00% - 96.67%.

The influence of different stress methods on Metal-Oxide-Nitride-Oxide-Silicon (MONOS) layer breakdown was investigated. In this paper, two different stress modes, DC and AC stress, were applied to systematically study stress condition effects on MONOS breakdown. According to the electrical failure analysis (EFA) results, MONOS layer is more vulnerable to dielectric breakdown under AC stress due to its higher defects generation efficiency. Besides, the physical failure analysis (PFA) revealed different breakdown mechanisms for DC and AC stress modes. These results help understand different stress methods impact on 3D NAND flash reliability.

In this paper, we propose a method for measuring stress levels using pulse rate variability features without any contact devices. Mental stress can be considered as a crucial factor which triggers mental diseases such as depression. In order to deal with the mental stress, many researchers tried to quantize the mental stress making full use of vital signs. However, contact sensors provides discomfort to people and the person who have skin irritation or damage are not able to attach the sensors. Instead of contact sensors, imaging photoplethysmography (iPPG) is growing field of interest. Despite some papers are demonstrated the effectiveness of pulse rate variability (PRV), almost papers did not investigate the effectiveness of PRV analysis. Moreover, PRV analysis provides only binary classes which are relaxed or stress conditions. Therefore, the contribution of our paper are follows. First, we investigate the effectiveness of PRV measurement in each iPPG method and proposed method from 78 videos for benchmark. Second, we extracted multiple features from PRV parameters for measuring the stress levels, not binary classes. Third, the combination method of optical-based and spatial subspace rotation methods indicates the best accuracy in all previous iPPG methods.

Reliability has increasingly become an important concern in Superjunction MOSFET (SJ-MOS) design. Failure mechanism and improvement in the process of unclamped inductive switching (UIS) are always the research focuses of SJ-MOS reliability. This paper analyzes the failed SJ-MOS devices in the UIS test, and then studies the influences of drift-region design on the avalanche durations of SJ-MOS and proposes the improvement suggestions.

Lifetime of packaged Phosphor- Quantum dot (QDs) based white LEDs is studied. Various stress parameters such as blue light luminance, temperature and moisture are considered and their effect on the performance of the Phosphor- QD based LED is investigated. The lumen degradation rate and degradation trend for LEDs is observed to be different under varying stress conditions. Lumen recovery process is also observed under light stress test.

The device characteristics and reliability of the In-Ga-Zn-O (IGZO) TFTs employing the HfO 2 gate insulator prepared by atomic-layer deposition (ALD) at a temperature as low as 150°C were investigated. The leakage current density and the dielectric constant for this HfO 2 thin film were obtained to be 3.8×10−7 A/cm2 and 22, respectively. The IGZO TFT showed a saturation mobility of 6.8 cm2/Vs and a subthreshold swing of 0.26 V/dec. Under the positive bias stress condition, the threshold voltage shift was evaluated to be less than −0.19 V.

The effect of non-conductive films (NCF) and under-bump metallization (UBM) materials on the electromigration (EM) failure mechanism of Sn-Ag microbumps was investigated under stress conditions at current densities ranging from 0.5~1.3 × 105 A/cm2 at 150°C. In the case of NCF microbumps, the EM failure mechanism were almost similar to that involving Cu/Ni/Sn-Ag microbumps with NCF and non-NCF. However, the NCF applications increased EM lifetime for the Cu/Ni/Sn-Ag microbumps. In the case of Ni and Cu UBM microbumps, the EM failure mechanism varied between Sn-Ag microbumps with Ni UBM and Cu UBM. No EM-induced failure was observed in Cu UBM microbump. However, EM-induced voids were found on the cathode side of the Al trace in the Ni UBM microbump. The three-dimensional (3-D) finite element method was used to simulate the current density and temperature distributions of the microbumps. The results showed that the Joule heating of the Ni UBM microbump was higher than that of the Cu UBM microbump. Thus, the increased Joule heating due to thicker Ni UBM resulted in a negative effect on the EM failure time. Therefore, the Cu UBM microbumps are expected to display enhanced EM resistance.

Enhancement of partial discharge resistance of PP due to the incorporation of nanofillers indicates an improvement in its reliability under high voltage operating conditions. Partial discharge measurement is a well-established technique to evaluate the condition, quality and reliability of insulation material. Certain ratios of partial discharge inception voltage were applied on each sample for a fixed aging duration and partial discharge parameters were acquired at regular intervals. It is reported that unfilled and nanofilled polypropylene behave differently under different electrical stress conditions. Partial discharge parameters such as maximum discharge magnitude, Weibull scale and shape parameters were acquired at regular time intervals and were analyzed. Profilometric depth analysis and surface study were performed with 3D Hirox Microscope on the aged samples to evaluate the amount of degradation and resistance offered to surface discharges. Breakdown strength measurement were performed to understand the effect of aging on the remnant breakdown strength in unfilled and nanofilled polypropylene.

In this paper, the NBTI-induced circuit frequency degradation is found having a non-monotonic bias dependence, thus an optimal V DD can be assessed based on this reliability tradeoff. As a demonstration, based on our recently-developed compact aging model and circuit reliability simulator, NBTI-induced frequency degradation in inverters are simulated, in terms of various V th and V DD , considering two typical stress waveforms. The results show the relationships between the optimal V DD of circuit and various stress conditions, which are useful to the reliability-aware V DD optimization for CMOS technology.

A rigorous electrothermal model that describes and correlate the behavior of the ESD devices during TLP and HBM stress conditions for various device types is developed, nearly five decades after well-known Wunsch-Bell and Tasca models.

The impact of channel Germanium content (Ge%) and gate stack Nitrogen content (N%), on bulk trap generation $(\Delta \text{V}_{\text{oT}})$ time kinetics is studied by using DC and AC stress at different voltage $(\text{V}_{\text{GSTR}})$ and temperature (T) in RMG HKMG Si and SiGe p-FinFETs. It is shown that $\Delta \text{V}_{\text{OT}}$ magnitude is dependent on frequency $(f)$ , which can make the resulting threshold voltage shift $(\Delta \text{V}_{\text{T}})$ dependent on $f$ for some stress conditions. The $f$ dependence of $\Delta \text{V}_{\text{OT}}$ and $\Delta \text{V}_{\text{T}}$ becomes stronger at higher Ge% and weaker at higher N%. The $\Delta \text{V}_{\text{T}}$ time kinetics is modeled for DC and AC stress under different stress conditions (V GSTR , T and $f)$ and for different processes (Ge%, N%).

Currently, stress is one of the main factors which causes most physical and mental illnesses. It has become part of our everyday life and is considered a physiological response to different physical, emotional or mental challenges causing the occurrence of discomfort states, tension or even of the burn-out syndrome. Since in every day of our lives all activities are carried out under the influence of a higher or lower level of stress, we decided to investigate the daily stress experienced by ordinary people, during typical days of their lives, by using an acquisition and quantification system. The current paper aim is to investigate the stress level of a group of patients during a word colour test by testing these patience’s ability to concentrate, in both resting and under stress conditions, using a simple and easy to implement acquisition and quantification system. Our primary goal is to achieve conclusive results to demonstrate the impact of stress on health both on the short and long-term and to make the population more aware of the harmful lifestyle it has the impact of any type of stress on our health. 'Prevention is better than cure.'

3D-IC is a promising solution to the “Memory Wall”. The transmission issue of data between processor and memory will be migrated in this way, and the high bandwidth can achieve further performance improvement. However, high operation temperature and long-term stress condition induce more severe Bias Temperature Instability (BTI) effect in 3D-IC. This paper explores the activation failure of DRAM caused by BTI effect in 3D stacked system which degrades circuit functionality over time. Meanwhile, additional compensation logic is proposed to compensate the sensing failure. The charge saving in memory storage cell when being activated can obtain about 15% improvement in the scenario of heavy unbalanced workload.

The concept of health indicates physical, mental and social well-being. Psychological stress is commonly present among freshmen due to social and environmental changes. An approach to study the impact of stress on students relied on biological data assessment. In this work, electrocardiogram signals from first year students, from the Biomedical Engineering course, were collected during an oral presentation, acquiring the RR time series. Linear and nonlinear methodologies are used to extract features that best characterize the RR time series in young subjects under stress conditions.

Human cognition analysis from EEG signal is one of the most significant way to find the causes which affect human brain. Songs are familiar stimuli to analyze the effectiveness of different EEG bands because it is a common source of entertainment. According to linguistic variation, subject age and preference, volume level of songs, the impact on different EEG bands varies. In this research, a work has been performed to estimate the effect of songs on different EEG bands (delta, theta, alpha, beta). The songs have been categorized into three types: mild, pop, rock according to their PSD value which are 0.2114 W/Hz, 0.3271 W/Hz and 0.8448 W/Hz respectively. the volume levels are considered as 0 %-14 % volume level for low volume, 26%- 60% volume level for comfortable volume and 61%-100% volume level for high volume. An ANOVA test has been conducted to indicate the significance variation in EEG band and in which P-value has been set 0.05. For the mild, pop, and rock songs the P-values for alpha bands are 0.0146, 0.006 and 0.0006 respectively and the values indicate that alpha band is mostly active while listening to different songs. A topographical representation has been done based on the effects of songs on the alpha band activity for mild, pop and rock songs at three volume level. The maximum percentage of alpha band activation is 60% in comfortable volume which indicates that, when the volume is high human cognition state moves from relax to stress condition in which beta band is active.

Underground mines usually perform works at considerably large depths at which the stress conditions on the rock mass are observed to increase (for example, the Yauliyacu mining unit). This mine exhibits a depth of approximately 1,500 meters, and its depth is being increased even further. The operations at this mine are divided into the upper and lower zone operations. This division eventually created a problem related to the seismicity induced by the mining activities, resulting in a high concentration of stress and accumulated energy, which further led to landslides or rock bursts that directly affected workers, equipment, and the mine infrastructure. The Yauliyacu mining unit exhibits a microseismic system that is strategically distributed throughout the mine, monitoring the occurrence of these events in real time. The microseismic event records during the second semester of 2017 were analyzed to identify the affected levels or the levels exhibiting considerable susceptibility to the manifestation of rock bursts. The redistribution behavior of the main stress in underground horseshoe openings were analyzed for the Yauliyacu mining unit using another type of opening proposed in this study.

In real world, it is impossible to run the farm without plant stress condition. Thus the early stress detection is very important for next generation of smart farming. This paper proposes internet of things (IoT) based stress detection to identify lettuce stresses during their lifecycle. Practical environment features and leaf features have been introduced to effectively control the stresses (heat stress, nitrogen stress, and so on). Chlorophyll fluorescence (ChF) technique has been proved to be a powerful tool for extracting the leaf stress features. The proposed IoT based stress detection system brings us to the generation of inclusiveness era among farm manger, farm expert and farm owner in real-time analysis and discussion.

In this paper, the degradation of drain-induced barrier lowering (DIBL) in FinFETs is experimentally studied under various hot carrier degradation (HCD) stress conditions. A test method is developed to characterize channel barrier height modulation under different HCD stress conditions. A linear relationship of ΔV thlin and ΔV thsat after HCD is found. Then a compact model of HCD-induced ΔDIBL is proposed. The results are helpful for the physical understanding and modeling of HCD in nanoscale FinFETs and aging-aware circuit design.

During the lifetime of a High Voltage composite insulator, the housing of that latter is exposed to stress conditions. Those exposures alter the insulating behavior of the insulator in term of Electrical field (E-field) distribution and, consequently, the leakage current flow. The assessment of that evolution is an important parameter to be considered during the design of the insulator in order to prevent additional stresses such as dry band arcing which is caused by the leakage current increase. In this paper, an attempt has been made to build a model based on the Finite Element Method (FEM) for the calculation of the E-field distribution around a composite insulator. This model was used to assess the impact of the aging of the housing material. A program was developed in order to minimize the effect of the aging of the housing. That optimization was done by modifying the construction parameters of the insulator.

The increasing number of HVDC projects has raised new interest in the design of components used in various materials dedicated to DC applications. For example, the unidirectional electric field in a dielectric subjected to a DC voltage generates specific stress conditions resulting in unique features making up the design of insulators. Likewise, the impact of polarization in the environment near a DC line requires special attention for airborne contamination which modifies the ability of a string of insulators to withstand the operating voltage under any circumstances. This paper will review the main features of DC overhead line insulators with specific details related to the various technologies available. Contamination aspects will also be discussed including the latest developments in IEC 60815 [1] as well as new mitigation methods for severe contamination conditions.

This paper investigates variations in head pose features in response to specific stressors. A proper experiment consisting of neutral and stressful states was performed aiming to cover different types of stress affect. Then, features related to head movements and pose were computationally estimated and analyzed. Towards this direction, facial landmarks were fitted using Active Appearance Models (AAM). Using the 2D AAM facial landmarks, a 3D head pose model was estimated revealing head inclinations. Results indicate that specific stress conditions increase head mobility and mobility velocity, in both translational and rotational features. Even though stress modulates head movements and velocities, the most prominent increases are presented during tasks that include participant's speech. The degree and the intensity of the interaction effect between speech and stress should be investigated in more detail. The analysis reports that specific head pose features can be significant stress indicators that could contribute among other facial cues in reliable stress recognition.

This work presents a systematic study of the off-state drain bias time dependent dielectric breakdown (TDDB) mechanism, especially for the short channel transistors in advanced FinFET technologies. The sub-threshold leakage current was found to play a key role in determining the off-state drain bias TDDB degradation. Short channel transistors show higher electric field (E-Field) near the drain side due to increase in sub-threshold leakage current and hence, the breakdown lifetime is seen to scale with decrease in channel length. Moreover, with additional process optimizations, such as source/drain proximity push, the sub-threshold leakage current increases which results in worse off-state TDDB and shorter lifetime during practical circuit stress conditions. Also, impact of body bias on sub-threshold current is also studied in this work.

In this contribution, impact of extreme environmental conditions in terms of energy-level radiation of protons on SiGe integrated circuits is experimentally studied. Canonical representative structures including linear (passive interconnects/antennas) and non-linear (Low Noise Amplifiers) are used as carriers for assessing impact of aggressive stress conditions on their performances. Perspectives for holistic Modeling and Characterization approaches accounting for various interaction mechanisms (substrate resistivity variations, couplings/interferences, drift in DC and RF characteristics, for actives are down to allow for optimal solutions in pushing SiGe technologies toward applications with harsh and radiation-intense environments (e.g., Space, Nuclear, Military). Specific design prototypes are built for assessing mission-critical profiles for emerging RF and mm-Wave applications.

This paper presents comparison of GaN based switched-tank converter (STC) and traditional cascaded voltage divider (CVD) dc-dc converter for data center applications. The operation principle of two kinds of converters are presented. And simulations with Saber are both conducted to verify the proposed comparison, respectively. The system volume and efficiency are fully compared via GaN based device under the same current stress condition. It is shown that under the same condition, STC can achieve 1% higher efficiency at full load and over 2% higher efficiency at light load when compared with CVD. Furthermore, STC can achieve ∼37% power-density improvement when compared with CVD. Finally, GaN based STC prototype is built and experimental results verify the proposed idea very well.

Plant's photosynthetic activity and transpiration are constrained by the amount of water available to them through roots (i.e. root zone soil moisture) as well as nutrient and atmospheric conditions. Therefore, to better understand the response of plants to different stress conditions, knowledge of root zone soil moisture is essential. However, current global satellites dedicated to soil moisture monitoring are limited to L-band frequencies that have a low (< 5cm) penetration depth. In this study, we implement a new root zone soil moisture retrieval algorithm that takes advantage of multi-frequency microwave observations to infer root soil moisture from L-band measurements and inspired by plant hydraulics. The algorithm is a statistical retrieval that uses a set of target data to train an artificial neural network. Results of applying the retrieval algorithm to one year of observations along with future validation measures is presented.

The impact of stress caused by car driving on heart's activity has been extensively studied for over 60 years. In the present paper, we studied the influence of stress on drivers' heart rate. The algorithm was applied on electrocardiographic signals from 6 drivers, and the resulting heart rate variability parameters in the time domain were analyzed comparing those in normal conditions to those in stress conditions. The results show that the stress and heart activity are closely correlated. This finding could be used to create an intelligent system in the car that would monitor the heart rate and adapt the conditions in the cabin in order to relax the driver, or in case of emergency, alert the nearest hospital.

In this contribution we investigate the relationship between potential-induced degradation (PID) and the Bill of Material (BOM) used by module manufacturers. The BOM include two types of solar cells (conventional vs PID-free c-Si cells), two types of EVA films with, respectively, low and high resistivity, and two types of backsheets with, respectively, low and high permeability properties. Our results clearly indicate that to have a “PID-free” module the combination of PID-free cells and a high-resistive EVA encapsulants is recommendable. The use of a conventional c-Si cell in combination with a high-resistive EVA encapsulant, is still more effective than the use of PID-free cells in combination with low-quality EVA. These results, however, largely depend on the stress conditions applied during the PID test. Further, our results show that the permeability properties of the backsheet have apparently no influence on PID degradation.

The availability and efficiency of reliability simulators for analog ICs is becoming critical with the scaling of devices down to the nanometer nodes. Two of the main challenges here are how to simultaneously include different sources of unreliability (such as the time-zero or spatial variability and the aging or time-dependent variability), and how to account for the self-induced changes in device biasing (i.e., stress conditions) caused by the device wear-out. In addition to the already existing stochastic models for time-zero variability, new models for the stochastically-distributed aging mechanisms have been developed in recent years. The combination of these challenges with the need for dealing with a stochastic model for aging, causes a serious computational load issue. This paper presents different methods to accurately include reliability in the simulation of analog ICs while preventing the simulation to become unaffordable in terms of CPU time and load.

As memory technology scales down, memory cells tend to become unreliable. To guarantee reliable operations of circuits and systems, semiconductor devices are tested with accelerated life tests to estimate device-level reliability and to develop a predictive reliability model for circuits and systems based on the estimated reliability of devices. However, to accurately estimate the lifetime of a system, accelerated lifetime testing at the system level is necessary. In this paper, we propose a system-level accelerated life test plan. As a case study, we investigate the reliability of SRAMs under time-dependent dielectric breakdown, one of the major contributors to aging failures in modern computer systems. Using the simulation results, we examine failure trends at various stress conditions for the system-level accelerated life test. From the resulting observations, we suggest a method that optimizes the experimental design of system-level accelerated life tests.

Stress is one of the major problems in society and is being treated using medicine and neurofeedback therapy. Neurofeedback therapy is usually successful. The contents as stimuli for neurofeedback training are not available for stress and anxiety. This paper focuses on giving a comprehensive and critical summary of available contents for neurofeedback training. It also establishes a need for the development of content as a stimulus for neurofeedback which trains the subject on how to control his brain activity, especially in stress condition. The developed content consists of audio and game. The game is used to reduce the power of high-beta brain activity and the audio is used to enhance the amplitude of alpha brainwaves in left-prefrontal lobe. The experimental results show significant improvement in reducing stress level. The outcome is a proposed content for neurofeedback training to reduce stress, and it also improves the neurofeedback training efficacy.

Complicated processes of through-silicon-via fabrication makes low yield of through-silicon-via mass production. Through-silicon-via redundancy is one of various ways that have been put forward to improve reliability of electrical interconnections. Allocation of through-silicon-vias is changed as redundant through-silicon-vias are added. Consequently, thermal dissipation and thermal mechanical reliability need evaluating anew. This paper focuses on how thermal mechanical reliability of a three dimensional package changes before and after redundant through-silicon-vias are added. It turns out that stress condition of silicon chip, micro-bumps and through-silicon-vias becomes worse in the case of through-silicon-via redundancy.

Degradation of n-type low temperature poly-Si (LTPS) TFTs is investigated under bipolar gate pulses with a small drain bias. It is found that degradation behaviors are similar to those caused by the bipolar gate pulses with source and drain grounded. Dynamic hot carrier (HC) degradation is the dominant mechanism. However, device degradation also strongly depends on the drain bias. Four-terminal poly-Si TFTs, which have an additional body terminal, degrade much less than conventional TFTs under the same stress condition. The degradation behaviors can be explained based on the non-equilibrium PN junction degradation model.

By means of long-term mixed-mode stress tests of high-speed SiGe HBTs an empirical ageing function for compact models was constructed. This ageing function models saturation of the aging rate as a function of stress time and stress current and is applicable for all relevant mixed-mode stress conditions of this HBT type. Additionally, 1000h stress tests on a high-voltage HBT revealed that not only saturation but even reversal of ageing rate is possible in the long run.

The experimental RTN-trap profiling method bas been demonstrated on both planar and trigate MOSFETs. It was achieved by a simple experimental method to take the 2D profiling of the RTN-trap in both oxide depth (vertical) and channel (lateral) directions in the gate oxide. Then, by arranging various 2D fields for the device stress condition, the positions of RTN traps can be precisely controlled. The positions of RTN-traps can be manipulated, showing significant advances for the understanding of the trap generation and the impact on the device reliability. Results have demonstrated why trigate exhibits much worse reliability than the planar ones.

In this work, the Hot-Carrier-Induced (HCI) degradation mechanism of the 30 V shallow trench isolation (STI) n-type lateral DMOS (nLDMOS) with two-step-oxide process applied in high side application (called as HS-nLDMOS) is investigated. It implies that the Ron, sp (on-resistance measured under high side condition) suffers from more damage impact than Ron, ls (on-resistance measured under low side condition). Moreover, a shift of the worst stress condition from the maximum substrate current stress condition (Isubmax) to the maximum gate voltage stress condition (Vgmax) is observed when the HS-nLDMOS is evaluated with Ron, hs instead of Ron, ls. Hence our investigation suggests estimating the degradation of HS-nLDMOS by Ron, hs under Vgmax stress condition in order to evaluate the exact life of the device.

Due to the increasing interests of using light weight, recyclable and cost efficient materials in electrical applications, thermoplastic materials have been widely investigated under demanding test conditions in recent years. In the previous work, a fast materials screening method on plate geometry were developed in-house, to study surface aging behavior of thermoplastic materials under multi-stress conditions [1-2]. In the present study, two types of modification on thermoplastic plate samples were evaluated with the screening method by applying 1) a surface coating and 2) a special additive. A significant increase of lifetime were observed only by using method 1. The correlation between plate sample test and electrical component test under IEC 60932 technical report of the external coating were also discussed.

In this work, a diffusion-reaction model was implemented and used to study Cu migration during the annealing process and stress test. Its impact on the metastable behavior of CdTe solar cells was also investigated. The preliminary results support our theoretical model presented here that explains rapid changes in atomic concentration of Cu in CdTe as a function of stress conditions.

Demand response (DR) is coming into consideration day by day as it can very well avoid system stress conditions through proper load management. DR can avoid building new large-scale power generation and transmission infrastructures by improving the electric utility load factor. This paper proposes to develop a planning tool for electric utilities for residential sector that can use demand response at the end-user level integrating electric vehicles. The proposed planning tool incorporate control algorithms and DR strategy that are designed to brilliantly manage end-use loads taking care of load priorities and preferences as given by the consumer.