Lifetime Improvement Research Articles

Charge lifetime improvement of the Continuous Electron Beam Accelerator Facility photogun with a biased anode

GaAs photocathodes in dc high-voltage photoguns are highly susceptible to ion back-bombardment, which reduces the photocathode quantum efficiency and limits the useful operating lifetime for producing polarized electron beams. This paper demonstrates that applying a small positive bias to the photogun anode can significantly suppress ion back-bombardment and increase charge lifetime. This technique was studied extensively using the Continuous Electron Beam Accelerator Facility photogun, where highly polarized electron beams created using a strained-superlattice GaAs/GaAsP photocathode were used and charge lifetimes improved by almost a factor of 2. A new simulation code was developed to model ion production and tracking in order to better understand and explain the factors that led to the performance improvement. Results of the experiments and simulations are discussed in detail. Published by the American Physical Society 2024

Stoch-IMC: A bit-parallel stochastic in-memory computing architecture based on STT-MRAM

In-memory computing (IMC) offloads parts of the computations to memory to fulfill the performance and energy demands of applications such as neuromorphic computing, machine learning, and image processing. Fortunately, the main features that stochastic computing (SC) and IMC share, which are low computation complexity and high bit-parallel computation capability, promise great potential for integrating SC and IMC. In this paper, we exploit this potential by using stochastic computation as an approximation method to present effective in-memory computations with a good trade-off among design parameters. To this end, first, commonly used stochastic arithmetic operations of applications are effectively implemented using the primitive logic gates of the IMC method. Next, the in-memory scheduling and mapping of applications are obtained efficiently by a proposed algorithm. This algorithm reduces the computation latency by enabling intra-subarray parallelism while considering the IMC method constraints. Subsequently, a bit-parallel stochastic IMC architecture, Stoch-IMC, is presented that enables bit parallelization of stochastic computations over memory subarrays/banks. To evaluate Stoch-IMC’s effectiveness, various analyses were conducted. Results show average performance improvements of 135.7X and 124.2X across applications compared to binary IMC and related in-memory SC methods, respectively. The results also demonstrate an average energy reduction of 1.5X compared to binary IMC, with limited energy overhead relative to the in-memory SC method. Furthermore, the results reveal average lifetime improvements of 4.9X and 216.3X over binary IMC and in-memory SC methods, respectively, along with high bitflip tolerance.

Double Deep Q- energy aware Service allocation based on Dynamic fractional frequency reusable technique for lifetime maximization in HetNet-LTE network

The development of mobile communication in heterogeneous networks is incredible in providing various services through wireless cellular communication through advanced long-term evaluation networks. Increasing multi-concern services and frequencies in spectrum channels are highly layered to select the bandwidth to provide the fastest network without interference. Selecting the channel through macro cell selection is essential to improve network communication and provide the quickest service. Most frequency reuse techniques use service optimality and route selection-based protocols to enrich the packet flow. Still, the improper spectrum delights create more delay tolerance due to short-range service optimality due to energy loss by selecting the short spectrum signal to reuse, which doesn't support the lifetime improvement of the LTE network. To resolve these problems, we propose a Double Deep Q- energy-aware Service allocation based on a Dynamic fractional frequency reusable technique for lifetime maximization in the HetNet-LTE network. Initially, the heterogenous communication environment and node deplanement were carried out to construct the LTE network under the WCC. The communication logs are Route Table (RT), and its services are taken by all node LTE Communication Impact Rate (LTE-CIR). Then, the Backhaul Traffic Algorithm (BTA) is applied to predict the interference on traffic rate from the channel frequency margin. Select the balanced node using the Channel Interference Macro Cell Selection (CIMCS) technique. Considering frequency limits with the Double Deep Q- Network (DDQN) approach, energy-aware selects the optimal route to reuse the frequency level using Frequency Domain Packet Scheduling (FDPS) to improve communication. The proposed system improves the overall throughput by up to 97.8 % with adopted channel selection from the macro unit to improve the latency performance. Also, the interference frequency limits are dynamically reused at an energy optimal level with low-level delay tolerance to improve the link stability by up to 98.4 % with higher lifetime maximation in the LTE network.

IFKC and Optimized DeTrac Deep Convolutional Neural Network Based Location Prediction in the Mobile IOT

Wireless Sensor Network (WSN) is a noteworthy technological advancement in the Internet of Things (IoT). Due to its severe resource constraints, this network necessitates the development of energy-efficient routing strategies. In the context of the Internet of Things, a cluster-based routing problems frequently struggle with unequal power usage. Therefore, this paper proposes an Improved Fractional Rough Fuzzy K-means Clustering and Optimized DeTraC Deep Convolutional Neural Network based Location Prediction in Mobile Internet of Things (IFKC-ODTN-LP-MIoT) system to address unequal power consumption in cluster-based IoT routing. By proposing Improved Fractional Rough Fuzzy K-means (IF-RFKM) for cluster head selection and an optimized DeTraC Deep Convolutional Neural Network (DT-DCNN) the system aims to enhance energy efficiency for location prediction. Then Adolescent Identity Search Algorithm (AISA) optimizes DT-DCNN parameters for improved accuracy. The experimental results demonstrate significant improvements in Computational efficiency, network lifetime and delay compared to the existing approaches.

Passivation with sputtered silicon nitride and modified heat treatment for lifetime improvement

It is widely inferred that Light and Elevated Temperature Induced Degradation (LeTID) is attributed to the diffusion of hydrogen into bulk silicon from the rear PECVD SiNx:H layer of PERC during the high-temperature firing process. We propose not only a simplified heat treatment flow for the typical PERC structure but also a new degradation-reduced structure with sputtered SiNx. The common N2 annealing after Al2O3 formation can be skipped to reduce process complexity and cost because we found that the lifetime can be even improved by omitting the moderate-temperature annealing while retaining the unavoidable high-temperature firing process for metallization. In the light soaking measurement of lifetime, the sputtered-SiNx passivated wafer displayed a higher lifetime than the PECVD-SiNx:H passivated wafer. The absence of excess hydrogen in the sputtered-SiNx film contributes to the suppression of LeTID. We further demonstrate that the sputtered-SiNx cells own higher VOC compared to PECVD-SiNx:H cells under light soaking.

Dodecagonal Parameter-Based Energy-Efficient Routing in Wireless Sensor Networks

Wireless Sensor Networks (WSNs) are composed of several sensor nodes (SN) that are dispersed geographically and interact with one another over wireless media in order to track and log physical data from their environment. At the moment, WSNs frequently use routing and clustering strategies to extend the life of their networks. This paper proposes a DODECAGONAL parameter-based Energy-Efficient Routing in WSN (DOPE-WSN) for improvement of network lifetime and saving the energy consumption. Initially the cluster is selected using Agglomerative clustering. In the second phase, Pelican optimization (PELO) based Cluster head selection (CHs) meant for considering Congestion, Node Degree, Node Density, Network area, Network Coverage, Number of clusters, Number of nodes, Communication cost, Distance, Residual Energy, Distance to neighbor, Node Centrality. Moreover, the Sooty Tern Optimization (STO) model are utilized for the determination of the best routing path for the cluster heads. Taking into account node degree, residual energy, and distance, the STO maximizes network performance. The suggested approach has undergone thorough testing for ensuring network durability and energy efficiency. The proposed model achieved a maximum 97% Packet Delivery Ratio (PDR) with 900 nodes in comparison with 91%, 89%, 83%, and 82% for CRPSH, HQCA, EACRLEACH, and BWO-IACO algorithms respectively.

Nonplanar Nanographene: A Hydrocarbon Hole-Transporting Material That Competes with Triarylamines.

Hole-transporting materials (HTMs) are essential for optoelectronic devices, such as organic light-emitting diodes (OLEDs), dye-sensitized solar cells, and perovskite solar cells. Triarylamines have been employed as HTMs since they were introduced in 1987. However, heteroatoms or side chains embedded in the core skeleton of triarylamines can cause thermal and chemical stability problems. Herein, we report that hexabenzo[a,c,fg,j,l,op]tetracene (HBT), a small nonplanar nanographene, functions as a hydrocarbon HTM with hole transport properties that match those of triarylamine-based HTMs. X-ray structural analysis and theoretical calculations revealed effective multidirectional orbital interactions and transfer integrals for HBT. In-depth experimental and theoretical analyses revealed that the nonplanarity-inducing annulative π-extension can achieve not only a stable amorphous state in bulk films, but also a higher increase in the highest occupied molecular orbital level than conventional linear or cyclic π-extension. Furthermore, an in-house manufactured HBT-based OLED exhibited excellent performance, featuring superior curves for current density-voltage, external quantum efficiency-luminance, and lifetime compared to those of representative triarylamine-based OLEDs. A notable improvement in device lifetime was observed for the HBT-based OLED, highlighting the advantages of the hydrocarbon HTM. This study demonstrates the immense potential of small nonplanar nanographenes for optoelectronic device applications.

Nonplanar Nanographene: A Hydrocarbon Hole‐Transporting Material That Competes with Triarylamines

AbstractHole‐transporting materials (HTMs) are essential for optoelectronic devices, such as organic light‐emitting diodes (OLEDs), dye‐sensitized solar cells, and perovskite solar cells. Triarylamines have been employed as HTMs since they were introduced in 1987. However, heteroatoms or side chains embedded in the core skeleton of triarylamines can cause thermal and chemical stability problems. Herein, we report that hexabenzo[a,c,fg,j,l,op]tetracene (HBT), a small nonplanar nanographene, functions as a hydrocarbon HTM with hole transport properties that match those of triarylamine‐based HTMs. X‐ray structural analysis and theoretical calculations revealed effective multidirectional orbital interactions and transfer integrals for HBT. In‐depth experimental and theoretical analyses revealed that the nonplanarity‐inducing annulative π‐extension can achieve not only a stable amorphous state in bulk films, but also a higher increase in the highest occupied molecular orbital level than conventional linear or cyclic π‐extension. Furthermore, an in‐house manufactured HBT‐based OLED exhibited excellent performance, featuring superior curves for current density–voltage, external quantum efficiency–luminance, and lifetime compared to those of representative triarylamine‐based OLEDs. A notable improvement in device lifetime was observed for the HBT‐based OLED, highlighting the advantages of the hydrocarbon HTM. This study demonstrates the immense potential of small nonplanar nanographenes for optoelectronic device applications.

Enhanced performance of ambient-air processed CsPbBr3 perovskite light-emitting electrochemical cells via synergistic incorporation of dual additives

Metal halide perovskite light-emitting electrochemical cells (MHP-LECs) are promising due to their facile solution processability and exceptional optoelectrical properties. However, commercialization is hindered by poor thin-film coverage and the need for glovebox processing. This study addresses these issues by incorporating poly(ethylene oxide) (PEO) and potassium hexafluorophosphate (KPF6) into cesium lead bromide perovskite (CsPbBr3) emitting layers (EML), processed under ambient-air conditions. These perovskite composite thin films were spin-coated on a preheated substrate, and the device structure was ITO/PEDOT:PSS/EML/Al. Notably, the MHP-LEC based on CsPbBr3:PEO:KPF6 (100:65:0.2, weight ratio) exhibited pure-green emission with a peak at 524 nm and a narrow full width at half-maximum of 27 nm. Compared to a reference device (CsPbBr3:PEO (100:65, weight ratio)), the new device showed 1.5-, 4-, and 5-fold improvements in current density, electroluminescence (EL) intensity, and lifetime, respectively. These enhancements are attributed to reduced non-radiative current leakage, improved film surface coverage and passivation, and balanced charge carrier injection and transportation. This study offers a straightforward approach for processing CsPbBr3 thin films under ambient-air conditions, enhancing the EL performance of MHP-LECs.

Hybrid fuzzy logic and gravitational search algorithm based routing for wireless sensor networks

Over the recent years, the wireless sensor network (WSN) has garnered significant attention from both researchers and the general populace. Its application in diverse environmental scenarios, including weather monitoring, temperature regulation, humidity tracking, and military surveillance, extends beyond conventional boundaries. WSNs consist of numerous nodes, each functioning as a sensor with the primary responsibility of data sensing. These nodes operate under constraints such as power, energy, efficiency, and deployment considerations. Moreover, the power and other resources cannot be replaced and renewed therefore prolonging the network lifetime has become the main aspect of WSNs. Energy aware routing play’s important role to ensure the efficient data transmission with minimal power consumption and ensures the prolonged network lifetime. In this work, we focus on optimizing the routing process therefore we present a hybrid model which uses fuzzy logic for path identification and gravitational search optimization (GSA) for efficient path selection. The fuzzy logic considers energy consumption, residual energy, distance and delay parameters to identify the most suitable path for data transmission. The experimental analysis shows a significant improvement in network lifetime, delay an aspect delivery.

Energy efficient routing protocol for enhancing the network lifetime in wireless sensor network

Wireless sensor networks (WSNs) confront significant challenges related to battery capacity, as sensor nodes operate on limited energy resources. To address this issue, low energy adaptive clustering hierarchy (LEACH) protocol is commonly employed for power management in WSNs. LEACH is commonly used for power management. Here, sensing region is divided into clusters and sectors, placing a gateway node at the center to minimize energy consumption during data transmission. It employs one-hop, two-hop, or three-hop pathways based on node proximity to the base station (BS) to optimize energy usage. Network performance is assessed using rounds, throughput, and energy usage. MATLAB simulations compare the proposed approach with dual layer LEACH (DL-LEACH) and LEACH, showing significant improvements in network lifetime. The proposed scheme outperforms LEACH by 515% and 347% for 20% and 50% node depletion, respectively. Compared to DL-LEACH, it extends network lifetime by 27% and 59% under similar scenarios. Sectoring, clustering, and multi-hop communication reduce energy consumption, enhancing network lifetime and addressing WSN challenges effectively.

Lifetime (Bx) improvement of PV inverter using Si-SiC H-IGBT/Diode: a reliability approach

Technological advancements have made it possible to harness the power of renewable energy sources. The efficiency of power electronic devices has increased to almost 98%. In order to reduce the risks of failure and maintain the operation of photovoltaic (PV)-based energy converters, reliable devices are needed. Due to the increasing number of wide-bandgap silicon in electronic converters, the need for more efficient and reliable devices has become more prevalent. However, the cost of these devices is a major issue. Hence, in this work extensive analysis of hybrid silicon (Si)-IGBT and silicon carbide (SiC) antiparallel Diode (H-IGBT/Diode) based PV inverter is proposed to improve the lifetime (Bx). A reliability oriented lifetime assessment is performed on a test case of single stage three kilowatt photovoltaic inverter with 600 V/30 A hybrid switch. Long term mission profile for one year is considered for evaluation at B. V. Raju Institute of Technology (BVRIT), Telangana, India. Finally, B10 lifetime is calculated, comparison analysis is presented between conventional Si-IGBT and proposed Si-SiC H-IGBT/Diode. The results of the study revealed that the H-IGBT exhibited a significant increase in PV inverter reliability.

Significant Lifetime Improvement of Negative Bias Thermal Instability by Plasma Enhanced Atomic Layer Deposition SiN in Stress Memorization Technique

Significant Lifetime Improvement of Negative Bias Thermal Instability by Plasma Enhanced Atomic Layer Deposition SiN in Stress Memorization Technique

How Ammonium Valeric Acid Iodide Additive Can Lead to More Efficient and Stable Carbon‐Based Perovskite Solar Cells: Role of Microstructure and Interfaces?

As perovskite photovoltaic devices can now compete with silicon technology in terms of efficiency, many strategies are investigated to improve their stability. In particular, degradation reactions can be hindered by appropriate device encapsulation, device architecture, and perovskite formulation. Mesoporous device architectures with a carbon electrode offer a plausible solution for the future commercialization of perovskite solar cells. They represent a low‐cost and stable solution with high potential for large‐scale production. Several studies have already demonstrated the potential of the mixed 2D/3D ammonium valeric acid iodide‐based MAPbI3 formulation to increase the lifetime of pure MAPbI3. They can however not describe the mechanisms responsible for the lifetime improvement. Using a full set of characterization techniques in the initial state and as a function of time during damp‐heat aging, new insights into the performance and degradation mechanisms may be observed. With (5‐AVA)0.05MA0.95PbI3, the solar cells are very stable up to 3500 h and the degradation of performances essentially results from the loss of electrical contacts mainly located at the interfaces. In contrast, for the neat MAPbI3, a poor stability is evidenced (T50 = 500 h) and the loss in performance results from the degradation of the bulk perovskite layer itself.

A perspective on boron-based multiple resonance narrowband emitters and devices

Boron-based multiple resonance thermally activated delayed fluorescent (MR-TADF) emitters have shown great promises for applications in high-definition displays. This class of heteroatom-doped nanographene materials typically show very narrow-band emission, small singlet–triplet split (ΔEST) values, high Photoluminescence quantum yield, quality chemical and thermal stabilities. Undoubtedly, boron-based MR-TADF emitters hold a leading position in satisfying the wide-color gamut standard of BT. 2020 (The International Telecommunication Union announced a new color gamut standard of broadcast service television for ultra-high-definition TV in 2012). Thus, the development of novel boron-based MR-TADF emitters attracted a great deal of attention from both academia and industry. Here, a comprehensive overview of the latest advances in boron-based MR-TADF emitters is presented, therein, rational strategies for molecular designs, as well as the consequent optical behavior and efficiency and lifetime improvement in organic light-emitting diodes (OLED) devices are discussed. Finally, the challenges as well as some future research directions to unlock the full potential of this fascinating class of materials are provided.

Reliability modeling to predict in‐service weatherability of polyurethane nanocomposite coatings: Approach, comparison and validation

AbstractThis article addresses the challenge of comparing in‐service weatherability among newly developed coatings. The study aims to compare the durability of three thermoplastic polyurethane‐based coatings specifically formulated for defense inflatables. It introduces a reliability model that incorporates two weathering stresses, namely, ultra‐violet radiation and temperature, to predict the service life of the coatings. A life–stress relationship has been established from the accelerated aging tests, which facilitates the determination of material service life at use level conditions. Notably, the analysis underscores the significant improvement in service lifetime achieved with nanocomposite‐based coatings. The validity of the proposed model is established through comparison with real‐world field test data, emphasizing the effectiveness of the approach in assessing and comparing the performance of the three coated samples. The insights gained from this research will surely contribute to enhancing the durability assessment of coated systems in real‐world conditions for various fields of applications.Highlights Introduces a unique method to compare weatherability of three polyurethane coatings. Reliability model predicts service life under UV and temperature stresses. Life–stress relationship via accelerated aging for accurate service life. Nanocomposite coatings show longer service life than conventional ones. Model validated with field data, confirming practical applicability.

Recent Advances in Fast-Decaying Metal Halide Perovskites Scintillators.

Fast-decaying scintillators show subnanoseconds or nanoseconds lifetime and high time resolution, making them important in nuclear physics, medical diagnostics, scientific research, and other fields. Metal halide perovskites (MHPs) show great potential for scintillator applications owing to their easy synthesis procedure and attractive optical properties. However, MHPs scintillators still need further improvement in decay lifetime. To optimize the decay lifetime, great progress has been achieved recently. In this Perspective, we first summarize the structural characteristics of MHPs in various dimensions, which brings different exciton behaviors. Then, recent advances in designing fast-decaying MHPs according to different exciton behaviors have been concluded, focusing on the photophysical mechanisms to achieve fast-decaying lifetimes. These advancements in decay lifetimes could facilitate the MHPs scintillators in advanced applications, such as time-of-flight positron emission tomography (TOF-PET), photon-counting computed tomography (PCCT), etc. Finally, the challenges and future opportunities are discussed to provide a roadmap for designing novel fast-decaying MHPs scintillators.

The lifetime improvement of organic light‐emitting diodes with poly(3,4‐ethylenedioxythiophene) polystyrene sulfonate on indium‐tin‐oxide surface and deuterated dopant in emitting layer

AbstractIn this study, the PEDOT:PSS conductive polymer material was spin‐coated on the ITO surface to improve the surface roughness of the ITO and reduce the spikes on the ITO surface, so as to avoid the burning spots generated in the green organic light emitting diode (OLED) when the voltage was applied to light it up. The OLED emitting is successfully survived. Deuterium atoms (isotopes of hydrogen) with heavier atomic weights can strengthen C‐D bonds, slow down the kinetic rate for unwarranted chemical reactions, and improve the performance and stability of OLEDs. In this study, deuterated D‐Ir (mppy)3 was employed as the dopant in the emitting layer of green OLED to replace the general Ir (mppy)3 to improve the optoelectronic properties and extend the lifetime of green OLED. At a constant voltage of 4 V, the initial luminance and half lifetime of general Ir (mppy)3 doped and deuterated D‐Ir (mppy)3 doped OLEDs are 188.1 cd/m2, 7.2 h and 438.3 cd/m2, 42.8 h, respectively. It is shown that doping the deuterated D‐Ir (mppy)3 material in the emitting layer has the effect of prolonging the lifetime of OLED. Compared with the general Ir (mppy)3, the lifetime of deuterated D‐Ir (mppy)3 doped OLED achieved an extension by 5.9 times.

Wireless optimization for sensor networks using IoT-based clustering and routing algorithms.

Wireless sensor networks (WSN) are among the most prominent current technologies. Its popularity has skyrocketed because of its capacity to operate in difficult situations. The WSN market encompasses various industries, including building automation, security networks, healthcare systems, logistics, and military operations. Therefore, increasing the energy efficiency of these networks is of utmost importance. Hierarchical topology, which typically uses a clustering methodology, is one of the most well-known methods for WSN energy optimization. To achieve energy efficiency in WSN, hierarchical topology low-energy adaptive clustering hierarchy (LEACH) was first introduced, and this served as the foundation. However, conventional LEACH has several limitations, which have led to extensive research into improving LEACH's efficacy in its current form. The use of particular algorithms and strategies to enhance the functionality of the conventional LEACH protocol forms the basis of ongoing efforts. Utilizing this enhanced LEACH, performance in terms of throughput and network life may be enhanced by concentrating on elements such as cluster head formation and transmission energy consumption. The enhanced LEACH algorithm demonstrates significant improvements in both throughput and network lifetime compared with conventional LEACH. Through rigorous experimentation, it was found that the enhanced algorithm increases the throughput by 25% on average, which is attributed to its dynamic clustering and optimized routing strategies. Furthermore, the network lifetime is extended by approximately 30%, primarily because of enhanced energy efficiency through adaptive clustering and transmission power control.

A device to device driven approach towards optimizing energy efficiency for 6G networks

Our study aims to develop more energy-efficient mobile communication systems through the exploration of the 6th generation (6G) technology that is expected to be implemented in 2033. We focus on the impact of device-to-device (D2D) communication on power efficiency, which is a crucial need in this domain. To achieve this, we conducted a pioneering experiment using an in-house testbed and K-means clustering to classify locations as D2D enabled or disabled. Our findings show that there is a dynamic clustering mechanism that enables certain nodes to sustain D2D functionality around temporary base stations, resulting in a remarkable 5% improvement in network lifetime per second. This research not only enhances our understanding of 6G networks but also provides a practical methodology for optimizing energy consumption, which holds significant implications for society in advancing sustainable and efficient communication.