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In the 5G massive machine type communication (mMTC) scenario, user equipment with poor signal quality requires numerous repetitions to compensate for the additional signal attenuation. However, an excessive number of repetitions consumes additional wireless resources, decreasing the transmission rate, and increasing the energy consumption. An insufficient number of repetitions prevents the successful deciphering of the data by the receivers, leading to a high bit error rate. The present study developed adaptive repetition approaches with the k-nearest neighbor (KNN) and support vector machine (SVM) to substantially increase network transmission efficacy for the enhanced machine type communication (eMTC) system in the 5G mMTC scenario. The simulation results showed that the proposed repetition with the learning approach effectively improved the probability of successful transmission, the resource utilization, the average number of repetitions, and the average energy consumption. It is therefore more suitable for the eMTC system in the mMTC scenario than the common lookup table. [ABSTRACT FROM AUTHOR]

Micro‐light‐emitting diodes (Micro‐LEDs) based on gallium nitride (GaN) materials offer versatile platforms for various applications, including displays, data communication tools, photodetectors, and sensors. In particular, the introduction of Micro‐LEDs in the optoelectronic industry enables the development of novel short‐distance wireless communication applications for the Internet of Things as well as near‐to‐eye displays for virtual reality and augmented reality. Micro‐LEDs used in conjunction with colloidal quantum dots (QDs) as color‐conversion layers provide efficient full‐color displays as well as white LEDs for high‐speed visible light communications (VLCs). Here, the latest progress on full‐color Micro‐LED displays with a printed QD color conversion layer, GaN material‐based Micro‐LEDs for VLC systems, and the photostability of novel QD materials for Micro‐LEDs is comprehensively reviewed. Outlooks on the efficiency of Micro‐LEDs with sizes ≤10 µm, QD stability issues, and flexible Micro‐LED displays are also provided. [ABSTRACT FROM AUTHOR]

An effective System-on-Chip (SoC) for smart Quality-of-Service (QoS) management over a virtual local area network (LAN) is presented in this study. The SoC is implemented by field programmable gate array (FPGA) for accelerating the delivery quality prediction for a service. The quality prediction is carried out by the general regression neural network (GRNN) algorithm based on a time-varying profile consisting of the past delivery records of the service. A novel record replacement algorithm is presented to update the profile, so that the bandwidth usage of the service can be effectively tracked by GRNN. Experimental results show that the SoC provides self-aware QoS management with low computation costs for applications over virtual LAN. [ABSTRACT FROM AUTHOR]

Polarizers play a key role in generating polarized light for display, imaging, and data communication, but adoption often suffers from high optical loss. Recently, due to superior optoelectronic properties, halide perovskites have been widely developed for lighting applications; however, highly polarized emission (polarization degree >0.8) has not yet been realized with perovskites. Herein, by incorporating inkjet printing and an anodic aluminum oxide (AAO) confinement strategy, highly ordered perovskite nanowire (NW) arrays are demonstrated for anisotropic optical applications. The optical device based on perovskite NW arrays reveals a high photoluminescence external quantum efficiency of 21.6% and emits highly polarized light with polarization degree up to 0.84. The highly polarized emission from perovskite NW arrays has potential to considerably reduce the optical loss of polarizers, which may attract great interest in developing polarized light sources for next‐generation optoelectronic applications. [ABSTRACT FROM AUTHOR]

This paper aims to present a novel dynamic quality of service (QoS) algorithm for home networks. The algorithm carries out the QoS management of a service for a user in a home network based on the profile consisting of the past responses of the user for that service. It performs the prediction of the future responses to the service from the profile using the general regression neural network algorithm. The algorithm finds the bandwidth allocation consuming minimum total bandwidth among those predicted to produce desired responses. The minimum bandwidth allocation is then used for the service. The corresponding user responses are used to update the profiles for the subsequent dynamic QoS managements. The algorithm requires no offline training and achieves fast adaptation to the user responses. Both analytical and numerical results reveal that the proposed algorithm provides an effective alternative for user-oriented QoS management in the heterogeneous home networks. [ABSTRACT FROM PUBLISHER]

The effects of Hf content on the radiation hardness of Hf–In–Zn–O thin-film transistors (HIZO TFTs) and HIZO TFT-based circuits are systemically examined. The evaluated circuits, including current-starved ring oscillator, energy harvesting, and RF circuits, are essential for space electronic systems. It is shown that HIZO TFTs with low Hf concentration have better initial performance while TFTs with high Hf concentration are more stable against radiation. On the other hand, for circuit application, the stable HIZO TFTs are not necessarily preferred for all circuits. This letter demonstrates that understanding the device-circuit interactions is necessary for device optimization and circuit reliability improvements for harsh electronic systems. [ABSTRACT FROM AUTHOR]

In fitting a power-law process, we show that the construction of the empirical recurrence rate time series either simplifies the modeling task, or liberates a point process restrained by a key parametric model assumption such as the monotonicity requirement of the intensity function. The technique can be applied to seasonal events occurring in spurts or clusters, because the autoregressive integrated moving average (ARIMA) procedure provides a comprehensive set of tools with great flexibility. Essentially, we consolidate two of the most powerful modeling tools for the stochastic process and time series in the statistical literature to handle counts of events in a Poisson or Poisson-like process. [ABSTRACT FROM PUBLISHER]

A physics-based SPICE model that takes into account the statistical impacts of both successive and progressive oxide breakdowns is presented to evaluate the time-dependent dielectric breakdown (TDDB)-induced performance degradation in static random access memory cells and peripheral circuits. The postbreakdown $I$ – V$ characteristics and the distribution of time to breakdown (t_{\rm {BD}}) have been verified against experimental data from 45-nm Silicon on insulator technology. We show that peripheral circuits, such as word-line driver, sense amplifier, and write driver, also contribute to degradation of performance during read and write operations. Using the model, the statistical impact of TDDB on sensing delay and write access time can be properly modeled for read and write failure prediction. [ABSTRACT FROM AUTHOR]

In this paper, the feasibility of a low-temperature polysilicon (LTPS) microscale energy harvester for a wireless sensor node is investigated. For that purpose, two device-level models for the LTPS solar cell and thin-film transistors are proposed and employed in system-level evaluation of an energy harvesting system. The results of our analysis indicate that: 1) the maximum power operating point for the solar cell is different when connected to a lossy power converter; 2) increasing the average grain size of the LTPS film can reduce the circuit area by 20 times, while increasing the output power by 6%; and 3) the proposed bottom–up approach enables the designers to identify system bottlenecks and improve the performance accordingly. [ABSTRACT FROM AUTHOR]

This paper analyzes the root cause of performance degradation and the impact of hot-carrier injection (HCI) on the lifetime prediction of an $LC$ voltage-controlled oscillator ( $LC$ -VCO). Observed from both constant voltage stress and ramped voltage stress tests, it is shown that the dominant degradation mechanism shifts from a negative bias temperature instability to an HCI due to the accelerated aging condition. Furthermore, simulations show that a frequency increase of degraded VCO is mainly attributed to the degradation in the pMOSFET of a cross-couple pair, while the degradations in the pMOSFET and nMOSFET have relatively the same impact on the startup voltage shift. Compared with the frequency change, the degradation of the startup voltage of an $LC$ -VCO is less sensitive to device width. Based on the observed results, methodologies to optimize the reliability tests and mitigate the frequency shift of $LC$ -VCO are proposed. [ABSTRACT FROM PUBLISHER]

Time-dependent dielectric breakdown (TDDB), in which the traps in oxide bulk form a conducting path under application of stress voltage for long period of time, has emerged as one of the important sources of performance degradation in advanced devices. In this paper, we give an overview of the recent progress in the understanding of ultra-thin dielectric breakdown in devices and consider its impact at the circuit-level. From the device point of view, the breakdown (BD) phenomenon, including the BD statistics, trap generation models, and BD evolution in ultra-thin dielectric are presented followed by the recent studies on TDDB in high- k metal gate (HKMG) devices and magnetic tunnel junction (MTJ) memories. On the circuit side, we explore methodologies for circuit lifetime assessment, the impact of TDDB on circuit performance degradation, and design techniques to improve circuit reliability. [ABSTRACT FROM AUTHOR]

Positive bias temperature instability (PBTI) has become one of the major reliability concerns in the present day CMOS technology. The PBTI mostly degrades the performance of high- \(\kappa \) /metal gate (HK/MG) nMOSFETs and is dominated by time dependent stress induced trap generation. The PBTI models proposed so far in different literature are deterministic in nature and overlook the randomness of the temporal degradation of transistor threshold voltage, \(V_{\rm th}\) . In this paper, we present a stochastic model for PBTI to predict the behavior of HK/MG nMOSFETs under inversion mode stress. The model is scalable and is verified against experimental data from two different groups. Our model separately considers each trap to predict their impact on device performance. The simulations are carried out at accelerated voltage and temperature conditions and we noted the variations in \(V_{\rm th}\) . In addition, we have analyzed the impact of PBTI on the performance of a ring oscillator and concluded that the circuit speed suffers significant degradation due to this effect. We have also observed that the adverse effect of PBTI becomes more severe as we go deeper into the nanometer technology. [ABSTRACT FROM AUTHOR]

In this paper, we present a physics-based SPICE model for statistical soft breakdown (SBD) in ultrathin oxide. Statistical SBD induces an increase in gate leakage current (IG{\_BD}) based on the time to breakdown (tBD) and the location of the percolation path in the channel. The proposed model has been validated with experimental data, and fed into circuit simulators to predict the degradation of device/circuit performance. Using the model, we analyzed the impact of the increased IG{\_BD} due to the first SBD on cell stability and performance in SRAM cells. We observed that IG{\_BD} variation due to SBD increases READ and WRITE failure probability, resulting in reduced lifetime. [ABSTRACT FROM PUBLISHER]

The electrical performance of low-temperature polysilicon (LTPS) thin-film transistors (TFTs) has improved considerably in the last decade, due to the flourishing active-matrix liquid crystal display industry. However, there is a need to further scale down LTPS TFT devices on flexible substrates to explore other application domains. In order to realize this goal, self-heating-induced negative bias temperature instability (NBTI) in LTPS TFTs needs to be modeled to determine its effect on transistor degradation and to develop mitigation techniques. Although the characteristics of NBTI for TFTs are widely known, the effects of device geometry and substrate on temperature-dependent NBTI have not been considered. In this paper, for the first time, a self-consistent electrothermal model that considers the effects of device geometry, substrate, and stress conditions on NBTI is proposed. With the proposed modeling methodology, we show the significant impact of device geometry, substrate, and supply voltage on NBTI in LTPS TFTs. [ABSTRACT FROM AUTHOR]

Single-ZnO-nanowire (NW) memory based on resistive switching is demonstrated for the first time. The NW memory is stable, rewritable, and nonvolatile with on/off ratio up to \7.7 \times \10^5. The O vacancies at the surfaces of ZnO NWs and around the interface of Ti/ZnO NWs observed using X-ray phototelectron spectroscopy, transmission electron microscopy (TEM), selected-area electron diffraction, and high-resolution TEM might play a role in the resistive switching behavior. The endurance of resistive switching can be enhanced by further increasing the sweeping voltage. This paper brings an exciting possibility of building next-generation memory devices based on NWs. [ABSTRACT FROM AUTHOR]

To explore the surface effect on resistive random-access memory (ReRAM), the impact of surface roughness on the characteristics of ZnO ReRAM was studied. The thickness-independent resistance and the higher switching probability of ZnO ReRAM with rough surfaces indicate the importance of surface oxygen chemisorption on the switching process. Furthermore, the improvements in switching probability, switching voltage, and resistance distribution observed for ReRAM with rough surfaces can be attributed to the stable oxygen adatoms under various ambience conditions. The findings validate the surface-controlled stability and the uniformity of ReRAM and can serve as the guideline for developing practical device applications. [ABSTRACT FROM AUTHOR]

Objectives: Although uncommon, prolonged postoperative air leaks are a troublesome complication of lung surgery. This study was performed to determine if buttressing pulmonary staple lines would reduce air leakage at varying airway pressures, and if there was a difference between buttressing materials.Methods: Using cadaver lungs, the development of air leak from staple lines was evaluated at incremental airway pressures. Unreinforced staples were compared to staples reinforced with bovine pericardium and staples reinforced with expanded polytetrafluorethylene (ePTFE).Results: Unreinforced staple lines began to leak air at an airway pressure of 20 mm Hg, and > 90% leaked at a pressure of 35 mm Hg. Both bovine pericardium and ePTFE significantly reduced the incidence of air leak at these airway pressures. At higher airway pressures, ePTFE was superior to bovine pericardium.Conclusion: Staple line reinforcement with either material protects against air leak. Patients at risk for elevated airway pressures and/or postoperative ventilator support should be considered for utilization of these staple reinforcing materials. [ABSTRACT FROM AUTHOR]

In this letter, we present a physics-based compact SPICE model to predict statistical time-dependent dielectric breakdown (TDDB) in nanoscale circuits. In our model, an increase in the gate leakage current ( IG\BD) induced by TDDB is estimated using a quantum point contact (QPC) model depending on temperature. In addition, IG\BD is based on the statistics of time to breakdown (BD) ($t_{{\rm BD}}$ ) and location of percolation path ($x_{{\rm BD}}$ ) in the channel considering third successive BDs. We show that the model can be easily implemented to circuit simulators to predict the degradation of circuit lifetime. With the proposed model, we validated post-BD I–V characteristics with experimental data in ultrathin oxide technology. [ABSTRACT FROM PUBLISHER]

For the static random access memories (SRAMs) with high- \(k\) /metal gate transistors, positive bias temperature instability (PBTI)-induced stability degradation can be significant. In this letter, we analyze the temporal variations of the READ/WRITE operations and static noise margin of a conventional 6T-SRAM cell using a physics-based PBTI model. We show that the dependence of BTI effects on intrinsic variations and the design parameters of SRAM are significant A 10 mV increase in intrinsic variations can lead to double the BTI-induced read failure rate. Furthermore, SRAM is more sensitive to PBTI effects as compared with negative bias temperature instability These results validate that stochastic modeling of PBTI is required for reliable SRAM design. [ABSTRACT FROM AUTHOR]