Device Scaling Research Articles

Chemical Vapor Deposition Growth of 2D Ferroelectric Materials for Device Applications

Abstract2D ferroelectric materials have garnered extensive attention for promising applications in next‐generation electronic devices, which provides a platform to explore ferroelectricity without the critical thickness constraint of traditional perovskite oxide‐based ferroelectric materials. Recent studies have shown that chemical vapor deposition (CVD) can synthesis the large‐area 2D ferroelectric materials, making the 2D ferroelectric materials to be compatible with scalable semiconductor devices. In this Review, the CVD‐grown 2D ferroelectric materials are summarized in terms of materials, properties to devices application view. First, the synthesis strategy and recent advances of the CVD growth of 2D ferroelectric materials are highlighted in the aspects of diverse groups of 2D materials. Second, the recent experimental progress of 2D ferroelectric devices is introduced, and the potential applications of 2D ferroelectric devices are discussed. The availability of the CVD‐grown 2D ferroelectrics provides an abundant playground for not only deep studying the ferroelectric properties, but also conceiving various device applications. Lastly, the perspectives are provided to address the current challenges in terms of materials design, physics mechanism, device, and multifunctional application.

Self‐Aligned Photonic Defect Microcavity Lasers with Site‐Controlled Quantum Dots

AbstractSelf‐assembled semiconductor quantum dots face challenges in terms of scalable device integration because of their random growth positions, originating from the Stranski–Krastanov growth mode. Even with existing site‐controlled growth techniques, for example, nanohole or buried stressor concepts, a further lithography and etching step with high spatial alignment requirements is necessary to accurately integrate quantum dots into the nanophotonic devices. Here, the fabrication and characterization of strain‐induced site‐controlled microcavities are reported, where site‐controlled quantum dots are positioned at the antinode of the optical mode field in a self‐aligned manner without the need of any further nano‐processing. It is shown that the cavity properties such as Q‐factor, mode volume, and mode splitting can be tailored by the geometry of the integrated buried stressor, with an opening <4 µm. The experimental results are complemented with theory calculations based on continuum elasticity. Lasing signatures, including super‐linear input‐output response and linewidth narrowing, are observed for a 3.6‐µm self‐aligned cavity with a Q‐factor of 18 000. Furthermore, the quasi‐planar site‐controlled cavities exhibit no detrimental thermal effects. This approach integrates seamlessly with the industrial‐matured manufacturing process and the buried‐stressor technique, paving the way for exceptional scalability and straightforward manufacturing of high‐β microlasers and bright quantum light sources.

The psychosocial impact of eye-gaze assistive technology on everyday life of children and adults

Purpose This study investigates the psychosocial impact of eye-gaze assistive technology (EGAT) in both children and adults with long-term experience using eye-gaze assistive technology in everyday life, as well as the psychosocial impact as related to duration of use. Methods In this descriptive comparative study, 34 adult and 27 child EGAT users participated in a structured individual interview using the Psychosocial Impact of Assistive Devices Scale (PIADS). Results The participants’ age ranged from 5–74 years, 50% were female and 52% had been diagnosed with cerebral palsy. The EGAT had a positive psychosocial impact on competence, adaptability, and self-esteem among adult and child users. Competence was the only subscale with a higher value for adults (p = 0.038), compared to children. The items with the highest impact for the psychosocial aspects were quality of life, ability to participate, and self-esteem. The adults had longer duration of use than children, but for high-, medium-, and low-duration users, the device showed a positive psychosocial impact. Conclusions Participants considered EGAT to have high positive impacts for participation and quality of life. The study adds new knowledge in that high positive psychosocial impact may be found even among low-duration users of EGAT, which is important to consider for service providers.

Inactivation of SARS CoV-2 on porous and nonporous surfaces by compact portable plasma reactor.

We report the inactivation of SARS CoV-2 and its surrogate-Human coronavirus OC43 (HCoV-OC43), on representative porous (KN95 mask material) and nonporous materials (aluminum and polycarbonate) using a Compact Portable Plasma Reactor (CPPR). The CPPR is a compact (48cm3), lightweight, portable and scalable device that forms Dielectric Barrier Discharge which generates ozone using surrounding atmosphere as input gas, eliminating the need of source gas tanks. Iterative CPPR exposure time experiments were performed on inoculated material samples in 3 operating volumes. Minimum CPPR exposure times of 5-15min resulted in 4-5 log reduction of SARS CoV-2 and its surrogate on representative material samples. Ozone concentration and CPPR energy requirements for virus inactivation are documented. Difference in disinfection requirements in porous and non-porous material samples is discussed along with initial scaling studies using the CPPR in 3 operating volumes. The results of this feasibility study, along with existing literature on ozone and CPPR decontamination, show the potential of the CPPR as a powerful technology to reduce fomite transmission of enveloped respiratory virus-induced infectious diseases such as COVID-19. The CPPR can overcome limitations of high temperatures, long exposure times, bulky equipment, and toxic residuals related to conventional decontamination technologies.

All-Automated Fabrication of Freestanding and Scalable Photo-Thermoelectric Devices with High Performance.

Flexible photo-thermoelectric (PTE) devices have great application prospects in the fields of solar energy conversion, ultrabroadband light detection, etc. A suitable manufacturing process to avoid the substrate effects as well as to create a narrow transition area between p-n modules for high-performance freestanding flexible PTE devices is highly desired. Herein, an automated laser fabrication (ALF) method is reported to construct the PTE devices with rylene-diimide-doped n-type single-walled carbon nanotube (SWCNT) films. Thewet-compressing approach is developed to improve the thermoelectric power factors and figure of merit (ZT) of the SWCNT hybrid films. Then, the films are cut and patterned automatically to make PTE devices with various structures by the proposed ALF method. The freestanding PTE device with a narrow transition area of ≈2-3 µm between the p and n modules exhibits a high-power density of 0.32 µW cm-2 under the light of 200 mW cm-2, which is among the highest level for freestanding-film-based PTE devices. The results pave the way for the automatic production process of PTE devices for green power generation and ultrabroadband light detection.

Advancements and Challenges in IoT Simulators: A Comprehensive Review.

The Internet of Things (IoT) has emerged as an important concept, bridging the physical and digital worlds through interconnected devices. Although the idea of interconnected devices predates the term "Internet of Things", which was coined in 1999 by Kevin Ashton, the vision of a seamlessly integrated world of devices has been accelerated by advancements in wireless technologies, cost-effective computing, and the ubiquity of mobile devices. This study aims to provide an in-depth review of existing and emerging IoT simulators focusing on their capabilities and real-world applications, and discuss the current challenges and future trends in the IoT simulation area. Despite substantial research in the IoT simulation domain, many studies have a narrow focus, leaving a gap in comprehensive reviews that consider broader IoT development metrics, such as device mobility, energy models, Software-Defined Networking (SDN), and scalability. Notably, there is a lack of literature examining IoT simulators' capabilities in supporting renewable energy sources and their integration with Vehicular Ad-hoc Network (VANET) simulations. Our review seeks to address this gap, evaluating the ability of IoT simulators to simulate complex, large-scale IoT scenarios and meet specific developmental requirements, as well as examining the current challenges and future trends in the field of IoT simulation. Our systematic analysis has identified several significant gaps in the current literature. A primary concern is the lack of a generic simulator capable of effectively simulating various scenarios across different domains within the IoT environment. As a result, a comprehensive and versatile simulator is required to simulate the diverse scenarios occurring in IoT applications. Additionally, there is a notable gap in simulators that address specific security concerns, particularly battery depletion attacks, which are increasingly relevant in IoT systems. Furthermore, there is a need for further investigation and study regarding the integration of IoT simulators with traffic simulation for VANET environments. In addition, it is noteworthy that renewable energy sources are underrepresented in IoT simulations, despite an increasing global emphasis on environmental sustainability. As a result of these identified gaps, it is imperative to develop more advanced and adaptable IoT simulation tools that are designed to meet the multifaceted challenges and opportunities of the IoT domain.

Psychosocial predictors of mobility assistive devices non-adherence among older adults

Background: Mobility assistive devices (MADs) provide support to older adults to improve their quality of life; however, research shows that as many as 75% of older adults are non-adherent to prescribed MADs. This study investigated the psychosocial factors that predict non-adherence to MADs among older adults.Methods: A sample of Canadian older adult MADs users who resided in a long-term care facility was included. The data was collected using the Psychosocial Impact of Assistive Devices Scale (PIADS), and the Medical Outcomes Study Social Support Survey (mMOS-SS). Data analysis was performed using SPSS 28. Descriptive statistics were used to describe the sample and the study variables. Pearson correlation coefficients were used to evaluate the association between the study variables. Variables that were associated with non-adherence in a univariate analysis were subsequently entered into a multiple regression analysis.Results: The sample comprised 48 residents (26 females and 22 males), with a mean age of 86.8. In the univariate analysis, scores from the three PIADS subscales, namely, Competence, Adaptability, and Self-esteem, and the Social Support scale were significantly correlated with non-adherence (p < 0.05). In the multiple regression analyses, only Self-esteem significantly predicted non-adherence (p < 0.05), and this model explained between 43.5 and 54.3% of the variance in non-adherence.Conclusion: This study revealed that the Self-esteem construct, which includes several concepts related to psychological well-being, was the only significant predictor of non-adherence among the studied sample of older adults. The clinical implications of the findings are subsequently discussed.

Chiplets for Integration of Electronic Systems

Scaling down of transistor sizes has made it possible to integrate billions of devices in the same chip, allowing us to build entire electronic systems into tiny “systems on chip” (SoC). For about four decades after the proclamation of Moore's law, device scaling resulted in improvements in area, performance as well as power. In the last two decades, many semiconductor manufacturers stopped investing in new technology nodes since the design, manufacturing, and test challenges in deep submicron technologies are far too steep. Today, semiconductor companies do not rely on improvements in photolithography alone to build more complex systems. Similarly, optimizations at gate level or register-transfer level through electronic design automation tools will not suffice to bring in order-of-magnitude increase in the complexity of SoC, since these tools are already mature. Therefore, optimization at the system level is the only logical step forward. Chiplets represent a system-level packaging innovation and there is much research and development in using this technology for building high-performance computing systems. We believe that it will be worthwhile to include the topic of system-level integration in a course on Very Large-Scale Integrated Circuit Design taught in the Universities and provide a tutorial treatment to help teachers and students.

Energy density enhancement of scalable thermoelectric devices using a low thermal budget method with film thickness variation

Additive manufacturing has been investigated as a more time, energy, and cost-efficient method for fabricating thermoelectric generators (TEGs) compared to traditional manufacturing techniques. Early results have been promising but are held back by including a high-temperature, long-duration curing process to produce high-performance thermoelectric (TE) films. This work investigates the synergistic effect of four factors – a small amount of chitosan binder (0.05wt%), a combination of micron and nano-sized particles, the application of mechanical pressure (20 MPa), and thickness variation (170, 240, 300 µm) – on the performance of stencil printed p-Bi0.5Sb1.5Te3 (p-BST) and n-Bi2Te2.7Se0.3 (n-BTS) TE composite films. The combination of these four factors controls the micro and nanostructure of the films to decouple their electrical and thermal conductivity effectively. This resulted in figures of merit (ZTs) of 0.89 and 0.5 for p-BST and n-BTS thinner (170 µm) films, respectively, comparable to other additive manufacturing methods despite eliminating the high-temperature, long-duration curing process. The process was also used to fabricate a 6-couple TEG device, which could generate 357.6 µW with a power density of 5.0 mW/cm2 at a ∆T of 40 K. The device demonstrated air stability and flexibility for 1000 cycles of bending. Finally, the device was integrated with a voltage step-up converter to power an LED and charge and discharge capacitor at a ∆T of 17 K, demonstrating its applicability as a self-sufficient power source.

Sustainable biomimetic solar distillation with edge crystallization for passive salt collection and zero brine discharge

The urgency of addressing water scarcity and exponential population rise has necessitated the use of sustainable desalination for clean water production, while conventional thermal desalination processes consume fossil fuel with brine rejection. As a promising solution to sustainable solar thermal distillation, we report a scalable mangrove-mimicked device for direct solar vapor generation and passive salt collection without brine discharge. Capillarity-driven salty water supply and continuous vapor generation are ensured by anti-corrosion porous wicking stem and multi-layer leaves, which are made of low-cost superhydrophilic nanostructured titanium meshes. Precipitated salt at the leaf edge forms porous patch during daytime evaporation and get peeled by gravity during night when saline water rewets the leaves, and these salt patches can enhance vaporization by 1.6 times as indicated by our findings. The proposed solar vapor generator achieves a stable photothermal efficiency around 94% under one sun when treating synthetic seawater with a salinity of 3.5 wt.%. Under outdoor conditions, it can produce 2.2 L m−2 of freshwater per day from real seawater, which is sufficient for individual drinking needs. This kind of biomimetic solar distillation devices have demonstrated great capability in clean water production and passive salt collection to tackle global water and environmental challenges.

Design and Analysis of Ultra-low Power Voltage Controlled Oscillator in Nanoscale Technologies

In latest wired and wireless communication equipment, VCO (voltage-controlled oscillator) is the major building block and particularly used as the stable high frequency clock generator. VCO performance is measured through frequency range, power supply used, area occupied, power consumption, delay, and phase noise. VCO is the cascaded of odd number of inverter stages in a ring format, hence it is also articulated as a ring oscillator. Today’s portable communication devices are battery operated. Hence, low power and area efficient designs play a key role in battery life enhancement and device size reduction. Device scaling improves the effective silicon area utilization, but it leads to more leakages. Therefore, low power techniques along with the technology scaling is the best way of low power designs. In this article, discussed various low power schemes. The ring oscillator designs are carried out in various nano meter scaled technologies such as 180nm, 90nm,65nm and 45nm. A 5-stage ring oscillator is implemented in each technology along with low power schemes, simulated in Cadence virtuoso, and noted power, delay, and area. Observed that the proposed ring oscillator with sleepy keeper technique generated a stable frequency of oscillations in the range of 1GHz-2GHz. A control voltage of 1.8V to 0.4V is applied and targeted the power less than 30mW and delay in 0.25p sec.

Evaluating performance of vortex-diode based hydrodynamic cavitation device scale and pressure drop using coumarin dosimetry

The present work investigates the hydrodynamic cavitation (HC) performance of vortex-diode based devices, which show early inception and superior cavitational performance compared to conventional devices. The study provides novel data on the cavitational efficiency at different operating pressures for two sizes of cavitation devices, addressing a gap in the literature. Using coumarin as a chemical dosimeter in acidic conditions, the study tracked the formation of 7-hydroxycoumarin (7OHC), a hydroxylation product of coumarin, to evaluate cavitational performance. Optimization of solution pH and initial concentration led to selecting pH 3 and a 15 ppm concentration for subsequent experiments with two vortex-diode devices of 12 mm (D12) and 6 mm (D6) diameters. These devices were tested under various pressure conditions. The formation of 7OHC was analyzed in relation to process time, number of passes, and a characteristic number of passes (n*) – which correlates device dimensions with operating velocity. The results indicated that the D6 device outperformed the D12 in terms of efficiency at inlet pressures ranging from 100 to 400 kPag. Analysis of 7OHC formation trends with respect to n* revealed that while there were variations within different pressures for a given device, the performance was comparable across different scales. By keeping a constant n* across varying pressures (P1 = 100 to 400 kPag and P2 = 0 to 300 kPag), the study observed comparable 7OHC formation across different operating conditions and scales. This data is vital for selecting suitable scales and conditions for HC devices and for validating multi-scale models in this field.

Ultrahigh-fidelity spatial mode quantum gates in high-dimensional space by diffractive deep neural networks

While the spatial mode of photons is widely used in quantum cryptography, its potential for quantum computation remains largely unexplored. Here, we showcase the use of the multi-dimensional spatial mode of photons to construct a series of high-dimensional quantum gates, achieved through the use of diffractive deep neural networks (D2NNs). Notably, our gates demonstrate high fidelity of up to 99.6(2)%, as characterized by quantum process tomography. Our experimental implementation of these gates involves a programmable array of phase layers in a compact and scalable device, capable of performing complex operations or even quantum circuits. We also demonstrate the efficacy of the D2NN gates by successfully implementing the Deutsch algorithm and propose an intelligent deployment protocol that involves self-configuration and self-optimization. Moreover, we conduct a comparative analysis of the D2NN gate’s performance to the wave-front matching approach. Overall, our work opens a door for designing specific quantum gates using deep learning, with the potential for reliable execution of quantum computation.

Bridging the Reality Gap in Quantum Devices with Physics-Aware Machine Learning

The discrepancies between reality and simulation impede the optimization and scalability of solid-state quantum devices. Disorder induced by the unpredictable distribution of material defects is one of the major contributions to the reality gap. We bridge this gap using physics-aware machine learning, in particular, using an approach combining a physical model, deep learning, Gaussian random field, and Bayesian inference. This approach enables us to infer the disorder potential of a nanoscale electronic device from electron-transport data. This inference is validated by verifying the algorithm’s predictions about the gate-voltage values required for a laterally defined quantum-dot device in AlGaAs/GaAs to produce current features corresponding to a double-quantum-dot regime. Published by the American Physical Society 2024

First 24-Hour-Long Intensive Care Unit Testing of a Clinical-Scale Microfluidic Oxygenator in Swine: A Safety and Feasibility Study.

Microfluidic membrane oxygenators are designed to mimic branching vasculature of the native lung during extracorporeal lung support. To date, scaling of such devices to achieve clinically relevant blood flow and lung support has been a limitation. We evaluated a novel multilayer microfluidic blood oxygenator (BLOx) capable of supporting 750-800 ml/min blood flow versus a standard hollow fiber membrane oxygenator (HFMO) in vivo during veno-venous extracorporeal life support for 24 hours in anesthetized, mechanically ventilated uninjured swine (n = 3/group). The objective was to assess feasibility, safety, and biocompatibility. Circuits remained patent and operated with stable pressures throughout 24 hours. No group differences in vital signs or evidence of end-organ damage occurred. No change in plasma free hemoglobin and von Willebrand factor multimer size distribution were observed. Platelet count decreased in BLOx at 6 hours (37% dec, P = 0.03), but not in HFMO; however, thrombin generation potential was elevated in HFMO (596 ± 81 nM·min) versus BLOx (323 ± 39 nM·min) at 24 hours ( P = 0.04). Other coagulation and inflammatory mediator results were unremarkable. BLOx required higher mechanical ventilator settings and showed lower gas transfer efficiency versus HFMO, but the stable device performance indicates that this technology is ready for further performance scaling and testing in lung injury models and during longer use conditions.

Demonstration of a terahertz coplanar-strip spoof-surface-plasmon-polariton low-pass filter

There is a growing interest in spoof surface plasmon polariton (SSPP) structures at terahertz (THz) frequencies for applications such as filtering, sensing, and communications. However, to date, there are limited experiments that confirm SSPP characteristics at THz frequencies. The majority of literature focuses on simulation or verification by device scaling to Gigahertz (GHz) frequencies where standard vector network analyzers are readily available. This paper presents the first experimental verification of SSPP characteristics at THz frequencies in a guided wave system using coplanar strip (CPS) feedlines. Specifically, we design three SSPP structures with varying band-edge frequencies (1.04 THz, 0.63 THz, and 0.53 THz), then fabricate and verify the low-pass transmission characteristics using a modified THz-time-domain spectrometer (THz-TDS) system. We find strong agreement between simulation, theory, and experiment.

IMPACT OF SUPPLY VOLTAGE ON SRAM CELL POWER DISSIPATION UNDER DIFFERENT TOPOLOGIES

The high storage density and quick access times of Static Random Access Memory (SRAM) make it a critical component of many Very Large Scale Integration circuits. However, device scaling in today's technology leads to an increase in dynamic power and a decrease in noise margin, posing significant challenges to memory circuit design for the next generation of devices. In addition, sub-threshold leakage is also a concern. In recent years, the increasing demand for notebooks, laptops, IC memory cards, and mobile communication devices has driven the development of low-power, low-voltage memory circuits. Static Random Access Memoryis widely used as on-chip and off-chip memory for portable applications because they are easy to use and have minimal standby leakage. Since 60&amp;#37; to 70&amp;#37; of the chip memory is used, SRAM optimization is the focus of research. The SRAM cell's architecture and performance have been studied using various technologies to minimize power dissipation while maintaining stability. Based on the power dissipation, including static and dynamic power dissipation, and Static Noise Margin (SNM), the SRAM cell performance is compared with different topologies. The SNM fluctuation is considered along with the variation of supply voltage.

System multi-scale analysis of temperature control for spaceborne electronic devices

&lt;sec&gt;To improve the simulation resolution and accuracy in thermal analysis of spaceborne electronic devices and the temperature control performance of passive thermal control devices, a system multi-scale model is established, thereby obtaining the temperature field and heat flux of electronic devices inside the satellite on different scales as illustrated in the below figure. The temperature fluctuation mechanism inside the satellite is analyzed on different physical scales. The thermal analysis resolution of spaceborne electronic equipment is improved, and a method to reduce the power fluctuation of spaceborne equipment is proposed based on the results of system multi-scale thermal analysis.&lt;/sec&gt;&lt;sec&gt;The results indicate that the accuracy deviation between the multi-scale model of the system and the actual model is less than 9%. However, the system multi-scale model saves 99.67% of the mesh generation time, which greatly improves the computation efficiency. The system multi-scale model can capture the thermal information about device-level chip microstructures at a lower computational cost. The system-level model can evaluate the temperature control and insulation performance of passive thermal control materials on a macroscale. The temperature fluctuation amplitude of the platform compartment is 7.95 K, while the temperature fluctuation amplitude of the load compartment decreases to 2.43 K after the temperature of the composite phase change insulation material has been controlled, which is 69.43% lower than that of the platform compartment. Compared with traditional vacuum insulation panels, the composite phase change materials are very superior in controlling the temperature of the chamber and suppressing temperature fluctuations. The temperature fluctuation signal after being insulated by the composite phase change insulation materials shows a characteristic of shifting to the high-frequency domain. After selecting the cabins that require key insulation and temperature control through multiple regression analysis, a simplified model at device level is employed to obtain temperature fields under different thermal control device layouts as a training dataset. A neural network genetic algorithm is used to predict the optimal installation position of passive thermal control device on the device scale and a thermal control layout scheme is obtained, which reduces the maximum temperature fluctuation of the device by 2.74 K. If the temperature uniformity coefficient is taken as the optimization goal, the temperature of each device on PCB board can be reduced to 14.39% of the average temperature of all devices through optimizations.&lt;/sec&gt;

Skin-interfaced microfluidic sweat collection devices for personalized hydration management through thermal feedback.

Non-electronic wearables that utilize skin-interfaced microfluidic technology have revolutionized the collection and analysis of human sweat, providing valuable biochemical information and indicating body hydration status. However, existing microfluidic devices often require constant monitoring of data during sweat assessment, thereby impeding the user experience and potentially missing anomalous physiological events, such as excessive sweating. Moreover, the complex manufacturing process hampers the scalability and large-scale production of such devices. Herein, we present a self-feedback microfluidic device with a unique dehydration reminder through a cost-effective "CAD-to-3D device" approach. It incorporates two independent systems for sweat collection and thermal feedback, including serpentine microchannels, reservoirs, petal-like bursting valves and heating chambers. The device operates by sequentially collecting sweat in the channels and reservoirs, and then activating thermal stimulators in the heating chambers through breaking the valves, initiating a chemical exothermic reaction. Human trials validate that the devices effectively alert users to potential dehydration by inducing skin thermal sensations triggered by sweat sampling. The proposed device offers facile scalability and customizable fabrication, and holds promise for managing hydration strategies in real-world scenarios, benefiting individuals engaged in sporting activities or exposed to high-temperature settings.

Multilayer ferromagnetic spintronic devices for neuromorphic computing applications.

Based on ferromagnetic thin film systems, spintronic devices show substantial prospects for energy-efficient memory, logic, and unconventional computing paradigms. This paper presents a multilayer ferromagnetic spintronic device's experimental and micromagnetic simulation-based realization for neuromorphic computing applications. The device exhibits a temperature-dependent magnetic field and current-controlled multilevel resistance state switching. To study the scalability of the multilayer spintronic devices for neuromorphic applications, we further simulated the scaled version of the multilayer system read using the magnetic tunnel junction (MTJ) configuration down to 64 nm width. We show the device applications in hardware neural networks using the multiple resistance states as the synaptic weights. A varying pulse amplitude scheme is also proposed to improve the device's weight linearity. The simulated device shows an energy dissipation of 1.23 fJ for a complete potentiation/depression. The neural network based on these devices was trained and tested on the MNIST dataset using a supervised learning algorithm. When integrated as a weight into a 3-layer, fully connected neural network, these devices achieve recognition accuracy above 90% on the MNIST dataset. Thus, the proposed device demonstrates significant potential for neuromorphic computing applications.