High Performance Capabilities Research Articles

Halide Remixing under Device Operation Imparts Stability on Mixed‐Cation Mixed‐Halide Perovskite Solar Cells

Mixed-halide mixed-cation hybrid perovskites are among the most promising perovskite compositions for application in a variety of optoelectronic devices due to their high performance, low cost, and bandgap-tuning capabilities. Instability pathways such as those driven by ionic migration, however, continue to hinder their further progress. Here, an operando variable-pitch synchrotron grazing-incidence wide-angle X-ray scattering technique is used to track the surface and bulk structural changes in mixed-halide mixed-cation perovskite solar cells under continuous load and illumination. By monitoring the evolution of the material structure, it is demonstrated that halide remixing along the electric field and illumination direction during operation hinders phase segregation and limits device instability. Correlating the evolution with directionality- and depth-dependent analyses, it is proposed that this halide remixing is induced by an electrostrictive effect acting along the substrate out-of-plane direction. However, this stabilizing effect is overwhelmed by competing halide demixing processes in devices exposed to humid air or with poorer starting performance. The findings shed new light on understanding halide de- and re-mixing competitions and their impact on device longevity. These operando techniques allow real-time tracking of the structural evolution in full optoelectronic devices and unveil otherwise inaccessible insights into rapid structural evolution under external stressconditions.

Anti-bacterial and multi-functional smart wearable sensor based on organo-hydrogel for diagnosis of the anterior cruciate ligament injuries, and sensing glove for rehabilitation of joints motion

Stretchable multi-functional electronic skin devices capable of interface with parts of human body and/or internal organs to diagnose the anterior cruciate ligament (ACL) injuries and rehabilitation of human joint motion are attractive candidates for next-generation wearables biomedical devices, soft robots, and the Internet of Things (IoT). Such devices need to be of excellent mechanical property, anti-freezing, antibacterial, biocompatible to be comfortable to wear for long term usage and accommodate strains from repeated movement and prevent skin irritation. To address this need, we introduced conductive organo-hydrogels based on silver quantum dots (COH@AgQDs) as multi-functional stretchable sensor with outstanding high-performance diagnostic capabilities. We demonstrated a prototype from the developed sensors integrated into a wirelessly Arduino board and a smartphone was selected to transmit data which offers promising wireless system for rehabilitation after surgeries. Additionally, the developed device has ability to differentiate between ACL injury and healthy knee with different pattern shapes and high sensitivity. Moreover, the flexible sensor can inhibit the growth of bacteria (Escherichia coli (E-coli)) and Staphylococcus aureus (S. aureus) and protect human health for long-term use. It exhibited outstanding anti-freezing property (−53 °C), antibacterial, self-healing, robust mechanical property (strain 420% at stress 96 kPa), and high linearity.

Edge Computing for Cyber-physical Systems: A Systematic Mapping Study Emphasizing Trustworthiness

Edge computing is projected to have profound implications in the coming decades, proposed to provide solutions for applications such as augmented reality, predictive functionalities, and collaborative Cyber-Physical Systems (CPS). For such applications, edge computing addresses the new computational needs, as well as privacy, availability, and real-time constraints, by providing local high-performance computing capabilities to deal with the limitations and constraints of cloud and embedded systems. Edge computing is today driven by strong market forces stemming from IT/cloud, telecom, and networking—with corresponding multiple interpretations of “edge computing” (e.g., device edge, network edge, distributed cloud). Considering the strong drivers for edge computing and the relative novelty of the field, it becomes important to understand the specific requirements and characteristics of edge-based CPS, and to ensure that research is guided adequately, e.g., avoiding specific gaps. Our interests lie in the applications of edge computing as part of CPS, where several properties (or attributes) of trustworthiness, including safety, security, and predictability/availability, are of particular concern, each facing challenges for the introduction of edge-based CPS. We present the results of a systematic mapping study, a kind of systematic literature survey, investigating the use of edge computing for CPS with a special emphasis on trustworthiness. The main contributions of this study are a detailed description of the current research efforts in edge-based CPS and the identification and discussion of trends and research gaps. The results show that the main body of research in edge-based CPS only to a very limited extent consider key attributes of system trustworthiness, despite many efforts referring to critical CPS and applications like intelligent transportation. More research and industrial efforts will be needed on aspects of trustworthiness of future edge-based CPS including their experimental evaluation. Such research needs to consider the multiple interrelated attributes of trustworthiness including safety, security, and predictability, and new methodologies and architectures to address them. It is further important to provide bridges and collaboration between edge computing and CPS disciplines.

Wearable Inertial Sensor-Based Limb Lameness Detection and Pose Estimation for Horses

Accurate objective, automated limb lameness detection and pose estimation play an important role for animal well-being and precision livestock farming. We present a wearable sensor-based limb lameness detection and pose estimation for horse walk and trot locomotion. The gait event and lameness detection are first built on a recurrent neural network (RNN) with long short-term memory (LSTM) cells. Its outcomes are used in the limb pose estimation. A learned low-dimensional motion manifold is parameterized by a phase variable with a Gaussian process dynamic model. We compare the RNN-LSTM-based lameness detection method with a feature-based multi-layer classifier (MLC) and a multi-class classifier (MCC) that are built on support vector machine/K-nearest-neighbors and deep convolutional neural network methods, respectively. Experimental results show that using only accelerometer measurements, the RNN-LSTM-based approach achieves 95% lameness detection accuracy and also outperforms the feature-based MLC or MCC in terms of several assessment criteria. The pose estimation scheme can predict the 24 limb joint angles in the sagittal plane with average errors less than 5 and 10 degs under normal and induced lameness conditions, respectively. The presented work demonstrate the successful use of machine learning techniques for high performance lameness detection and pose estimation in equine science. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —Automation technologies are increasingly used for precision agriculture but few have focused on monitoring individual animals in open field for precision livestock farming. Limb lameness detection and pose estimation in open field is labor-intensive, unsafe for farmers, and inefficient. The presented machine learning-enabled, wearable inertial sensor-based design provides an effective and efficient approach for horse limb lameness detection and pose estimation applications. We present an RNN-LSTM for lameness detection and an integrated manifold learning model is used to predict the horse limb joint angles in walk and trot gaits under normal and induced lameness conditions. We also present a systematic analysis and experiments to demonstrate the impacts of the wearable sensor locations and signal information on lameness detection and pose estimation performance. Several other machine learning-based lameness detection methods are also presented and compared. The extensive multi-horse testing results are presented to demonstrate the superior accuracy and higher performance than other types of machine learning methods. One attractive feature of the proposed design lies in its high performance and fast computational capability for potential real-time applications in open field.

Development of a novel simulated neutron pulse signal generator for flux measurement

Neutron flux measure systems perform an important role in both nuclear power plants and thermonuclear reactors. However, strong neutron sources are necessary to test these modern neutron flux monitoring systems. Due to the dangerous nature of neutron radiation, developers opt for simulated neutron signals instead. This paper details the design of a random pulse signal generator capable of perfectly reproducing high count rate neutron signals (up to 109 counts per-second) for the purpose of testing flux monitoring systems in-lab without any radiation source involved. Fully digitalized waveforms were created within FPGA to assure that important elements of neutron signal, including pulse shape, pulse amplitude spectrum, count rate, and add-on white noise intensity were all able to be accessed and changed separately over the PCI&PCIe bus. A Labview-based Human Machine Interface (HMI) was also built to show all of these aspects and allowed real-time modifications. When compared to other signal generators, our signal generator has a significantly longer non-repetitive waveform and higher performance capability. This made it a reliable way to diagnose flux measurement systems by comparing count rates set on the signal generator to record results.

Technical Review of Dual Inverter Topologies for More Electric Aircraft Applications

Electric drives are an essential part of more electric aircraft (MEA) applications with ever-growing demands for high power density, high performance, and high fault-tolerant capability. High-speed motor drives can fulfill those needs, but their speeds are subject to the relatively low dc-link voltage adopted by MEA. The power inverters are thus expected to efficiently and effectively manage that limited voltage. A recently popular topology is represented by the dual inverters. They are featured by inherited fault tolerance, a high dc-link voltage utilization, and an excellent output power profile. This article aims to present a comprehensive review of different structures based on the dual inverter. To meet the stringent requirements of MEA applications, three performance aspects, including the voltage utilization, the inverter output quality, and the fault-tolerant capability, are selected. Based on the chosen performance metrics, the key features of adopting dual inverter topologies against other converter selections are explicitly demonstrated. Finally, a practical guideline for choosing suitable dual inverters for different MEA applications is provided.

Study of the Method of Electro-Crystallization and the Study of Effective Factors in the Production of Nanostructures in this Method

Due to the fact that nanostructures have very high-performance capabilities in various scientific and industrial fields, during the last few years these nanostructures have become available for production in order to produce particulate matter with appropriate composition and distribution. One of the focal points of the current study is the exploration of a number of different researches carried in the field. Considering that the method of electro crystallization compared to other methods available for the production of nanostructures is relatively new, this study gives a brief overview of the effective methods of electro crystallization and the effective parameters in the production of nanostructures produced at high speed, the integrity of materials and the sustainability of particles produced, the diversity in production, low cost and simple use of equipment. The findings of the study are presented that explore the effective parameters in the production of nanostructures, the voltage applied, the time it takes, the concentration of electrolyte and the temperature. The findings further show that the factors of change in voltage and oxidation has the greatest effect on the morphology and particle size. Moreover, the increase in voltage is due to the rapid increase in the speed that leads to the production of resistive crystalline sediments.

Highly Sensitive Integrated Photonic Sensor and Interrogator Using Cascaded Silicon Microring Resonators

Silicon photonic sensors have formed a favorable platform for various sensing applications due to the great advantages of high-performance, compactness, and large-scale integration capability. However, interrogation systems for reading out the encoded sensing information from an integrated sensor are still bulky and inflexible for various portable applications. In this paper, we propose a monolithic silicon refractive index sensor and interrogator by utilizing the cascaded microring resonators. A novel dithering and bias scan interrogation technique is designed for highly sensitive refractive index sensing with a broadband light source. The reflective index for aqueous solutions of ethanol with different concentrations are measured in the experiment, verifying that the sensitivity of the sensor is 125.1 nm/RIU and the detection accuracy of the whole system is 7.76<inline-formula><tex-math notation="LaTeX">$\boldsymbol{\times 10^{-6}}$</tex-math></inline-formula> RIU. This integrated photonic sensor and interrogator will be a promising solution for large-scale applications in biological and chemical sensing scenarios.

Substrate-independent multifunctional nanostructured coating for diverse wastewater treatment

Development of multifunctional superwettable materials that can efficiently separate both insoluble and soluble organic pollutants from wastewater are imperative, but remain challenging. Herein, a substrate-independent coating strategy is proposed for developing multifunctional superwettable materials, using a simple and cost-effective method. A three-dimensional (3D) porous honeycomb Ni–Co layered double hydroxide (LDH) nanostructured coating can impart positive charges and robust superhydrophilicity to various substrates, including metal meshes and inorganic and organic materials. This approach provides multifunctional materials for diverse wastewater treatments, such as immiscible oil/water mixtures, oil/water emulsions, and organic dyes. The as-prepared superhydrophilic materials exhibit remarkable underwater superoleophobicity and oil repellency. Thus, the materials exhibit high-performance separation capabilities for immiscible oil/water mixtures and oil/water emulsions. Additionally, the as-resulted materials achieve good adsorption properties for water-soluble anionic dyes. Moreover, the versatile multifunctional nanostructure-coated materials, which possess exceptional environmental durability and thermal stability, exhibit potential application prospects in real-world wastewater treatment.

Nonflammable, robust and flexible electrolytes enabled by phosphate coupled polymer–polymer for Li-metal batteries

Liquid organic electrolytes commonly employed in commercial Li-ion batteries suffer from safety issues such as flammability and explosions. Replacing liquid electrolytes with nonflammable electrolytes has become increasingly attractive in the development of safe, high-energy Li-metal batteries (LMBs). In this work, nonflammable, robust, and flexible composite polymer–polymer electrolytes (PPEs) were successfully fabricated by flame-retardant solution casting with polyimide (PI) and polyvinylidene fluoride (PVDF). The optimized nonflammable PPEs (e.g., PPE-50) demonstrate not only good mechanical properties (i.e., a high tensile strength of 29.6 MPa with an elongation at break of 87.2%), but also high Li salts dissolubility, the former of which ensures the suppression of Li dendrites, while the latter further improves the ionic conductivity (∼1.86 × 10−4 S cm−1 at 30 °C). The resulting symmetric cells (Li|PPE-50|Li) offer excellent Li stripping and plating stability for 1000 h at 0.5 mA cm−2/0.25 mAh cm−2 and 600 h at 2.0 mA cm−2/1.0 mAh cm−2. In addition, the LiFePO4|PPE-50|Li half cells show high cycling performance (e.g., a reversible discharge capacity of 135.9 mAh g−1 after 300 cycles at 1C) and rate capability (e.g., 117.2 mAh g−1 at 4C). The PPE-50 is also compatible with a high-voltage cathode (e.g., LiNi0.5Mn0.3Co0.2O2), and the resulting batteries demonstrate long-term cycling stability with a high cut-off voltage of 4.5 V vs. Li/Li+. Because of the incorporation of a mechanically robust and thermally stable PI, a polar PVDF, and flame-retardant trimethyl phosphate (TMP) within PPEs, as well as the coordination between Li salts and TMP, and the interaction between Li salts and polymers (especially between Li bis(oxalato)borate) and PI, as well as the bis(oxalato)borate anion and PI), PPEs show great potential for practical and high-energy LMBs without safety concerns.

Interoperable Data Analytics Reference Architectures Empowering Digital-Twin-Aided Manufacturing

The use of mature, reliable, and validated solutions can save significant time and cost when introducing new technologies to companies. Reference Architectures represent such best-practice techniques and have the potential to increase the speed and reliability of the development process in many application domains. One area where Reference Architectures are increasingly utilized is cloud-based systems. Exploiting the high-performance computing capability offered by clouds, while keeping sovereignty and governance of proprietary information assets can be challenging. This paper explores how Reference Architectures can be applied to overcome this challenge when developing cloud-based applications. The presented approach was developed within the DIGITbrain European project, which aims at supporting small and medium-sized enterprises (SMEs) and mid-caps in realizing smart business models called Manufacturing as a Service, via the efficient utilization of Digital Twins. In this paper, an overview of Reference Architecture concepts, as well as their classification, specialization, and particular application possibilities are presented. Various data management and potentially spatially detached data processing configurations are discussed, with special attention to machine learning techniques, which are of high interest within various sectors, including manufacturing. A framework that enables the deployment and orchestration of such overall data analytics Reference Architectures in clouds resources is also presented, followed by a demonstrative application example where the applicability of the introduced techniques and solutions are showcased in practice.

Critical Retrospection of Performance of Emerging Mobile Technologies in Health Data Management.

The recent advancement in mobile technologies has led to opening a new paradigm in the field of medical healthcare systems. The development of WBAN sensors, wearable devices, and 5G/6G wireless technology has made real-time monitoring and telecare of the patient feasible. The complex framework to secure sensitive data of the patient and healthcare professionals is critical. The fast computation of health data generated is crucial for disease prediction and trauma-related services; the security of data and financial transactions is also a major concern. Various models, algorithms, and frameworks have been developed to tame critical issues related to healthcare services. The efficiency of these frameworks and models depends on energy and time consumption. Thus, the review of recent emerging technologies in respect of energy and time consumption is required. This paper reviews the developments in recent mobile technologies, their application, and the comparative analysis of their performance parameters to explicitly understand the utility, capacity, and limitations. This will help to understand the shortcomings of the recent technologies for the development of better frameworks with higher performance capabilities as well as higher quality of services.

FeS2@N-C nanorattles encapsulated in N/S dual-doped graphene/carbon nanotube network composites for high performance and high rate capability anodes of sodium-ion batteries

Developing effective anode materials for sodium-ion batteries (SIBs) remains challenging. Although FeS2 has a high theoretical capacity, it suffers from significant volume changes during charge/discharge and forms soluble polysulfides at lower potentials (below 0.8 V vs. Na/Na+), making practical application difficult. We have developed an effective strategy to synthesize N-doped carbon-coated FeS2 nanorattles encapsulated in N/S dual-doped graphene/single-walled carbon nanotubes (G/SWCNTs) via hydrothermal vulcanization (FSCGS). This approach enabled the simultaneous formation of nanorattle structures and N/S dual-element doping into the G/SWCNT network. Using the FSCGS sample as an anode for SIBs, a remarkable specific capacity of 1,190 mAh g−1 at a current density of 0.1 A g−1 was achieved, with an excellent rate capability of 476 mAh g−1 at 10.0 A g−1. Moreover, it exhibited superior cyclic stability, with a capacity retention of 91.3% at 0.5 A g−1 after 200 cycles. First-principles calculations revealed that pyridinic-N/S doping of the basal graphene network improved Na+ reduction, resulting in enhanced electrochemical performance. The effective electrochemical functioning of the FSCGS anode material was attributed to an optimized hierarchical architecture and the excellent electrical conductivity/electrochemical activity provided by the dual carbon entities (N-doped carbon and N/S dual-doped G/SWCNT network).

The Versatile Test Reactor Project: Mission, Requirements, and Description

The mission of the U.S. Department of Energy (DOE) Office of Nuclear Energy is to advance nuclear power to meet the nation’s energy, environmental, and national security needs. Advanced nuclear technology development, as well as support for the current nuclear power industry, requires a robust infrastructure for experimentation, testing, design evolution, and component qualification. The current lack of fast neutron spectrum testing capabilities has been identified as a significant gap in the U.S. infrastructure that impedes the development of next-generation nuclear reactors—many of which require a fast neutron spectrum for operation—and equally impacts the United States’ ability to regain global technology leadership in this arena. To close the gap and support advanced technology development, the DOE has established the Versatile Test Reactor (VTR) project to provide high-performance testing capability, specifically, a fast neutron source to develop, test, and qualify advanced fuels and materials for the next generation of advanced reactors and existing commercial reactors. This paper describes the establishment of the project, the identification of its mission and requirements, and the design approach and status.

Bioinspired Compound Eyes for Diffused Light-Harvesting Application.

Natural compound eyes endow arthropods with wide-field high-performance light-harvesting capability that enables them to capture prey and avoid natural enemies in dim light. Inspired by natural compound eyes, a curved artificial-compound-eye (cACE) photodetector for diffused light harvesting is proposed and fabricated, and its light-harvesting capability is systematically investigated. The cACE photodetector is fabricated by introducing a cACE as a light-harvesting layer on the surface of a silicon-based photodetector, with the cACE being prepared via planar artificial-compound-eye (pACE) template deformation. The distinctive geometric morphology of the as-prepared cACE effectively reduces its surface reflection and the dependence of the projected area on the incident light direction, thereby significantly improving the light-harvesting ability and output photocurrent of the silicon-based photodetector. Furthermore, the performances of cACE, pACE, and bare polydimethylsiloxane (PDMS)-attached photodetectors as diffused light detectors are investigated under different luminances. The cACE-photodetector output photocurrent is 1.395 and 1.29 times those of the bare PDMS-attached and pACE photodetectors, respectively. Moreover, this photodetector has a desirable geometric shape. Thus, the proposed cACE photodetector will facilitate development of high-performance photodetectors for luminance sensing.

SERS Tags for Biomedical Detection and Bioimaging.

Surface-enhanced Raman scattering (SERS) has emerged as a valuable technique for molecular identification. Due to the characteristics of high sensitivity, excellent signal specificity, and photobleaching resistance, SERS has been widely used in the fields of environmental monitoring, food safety, and disease diagnosis. By attaching the organic molecules to the surface of plasmonic nanoparticles, the obtained SERS tags show high-performance multiplexing capability for biosensing. The past decade has witnessed the progress of SERS tags for liquid biopsy, bioimaging, and theranostics applications. This review focuses on the advances of SERS tags in biomedical fields. We first introduce the building blocks of SERS tags, followed by the summarization of recent progress in SERS tags employed for detecting biomarkers, such as DNA, miRNA, and protein in biological fluids, as well as imaging from in vitro cell, bacteria, tissue to in vivo tumors. Further, we illustrate the appealing applications of SERS tags for delineating tumor margins and cancer diagnosis. In the end, perspectives of SERS tags projecting into the possible obstacles are deliberately proposed in future clinical translation.

Hundred-gram scale fabrication of few-layered silicene by a continuous vapor-dealloying strategy for high-performance lithium storage.

A continuous vapor de-alloying strategy for a hundred-gram scale fabrication of silicene is developed by etching CaSi2 using waste polyvinyl chloride (PVC). The as-obtained few-layered silicene can be readily assembled with carbon nanotubes into flexible electrodes for lithium storage with excellent performance, which stably deliver a high capacity and stability. This strategy can be extended to other silicon analogs with various structures by selecting precursors such as Mg2Si and Al/Si alloy.

Cross-linked copolymer-derived nitrogen-doped hierarchical porous carbon with high-performance lithium storage capability

A hierarchically porous carbon material with N-doping has been developed by a synchronous activation–carbonization tactic using a cross-linked N-containing copolymer as the precursor, demonstrating tremendous potential as an alternative LIBs anode.

Vacancy-engineered V2O5-x films for ultrastable electrochromic applications

In the present study, we prepared vacancy-engineered V2O5-x films for electrochromic (EC) applications. To investigate the vacancy effect of V2O5-x films with high EC performance capabilities, precursor concentrations of V-based sol solutions were varied at 1 wt%, 5 wt%, and 10 wt%. Among them, V2O5-x films with a precursor concentration of 5 wt% (V2O5-5wt%) showed superior EC performance outcomes due to the (001)-plane-oriented crystal structure, which provides high electrical conductivity with the oxygen vacancy (Vo). In addition, the gravel-like uniform surface morphology with the optimized film thickness provides a stable electrochemical reaction during the EC measurement. As a result, V2O5-5wt% exhibited fast switching speeds (2.1 s for coloration and 3.6 s for bleaching), high transmittance modulation (ΔT) (51.32%), high coloration efficiency (CE) (52.3 cm2/C), and excellent cycle stability (85.85% ΔT retention after 500 cycles). In addition, V2O5-5wt% showed energy storage capability of 443.7 F/g at a current density of 2 A/g, thus proving its potential for use in multi-functional applications. Therefore, these results provide valuable insight related to the engineering of vacancies in EC films to achieve high-performance EC devices and additional multi-functional applications.

DNA Genotyping Based on Isothermal Amplification and Colorimetric Detection by Consumer Electronics Devices.

The point-of-care testing of DNA biomarkers requires compact biosensing systems and consumer electronic technologies provide fascinating opportunities. Their portability, mass-produced components, and high-performance readout capabilities are the main advantages for the development of novel bioanalytical methods.This chapter describes the detection of single nucleotide polymorphisms (SNP) through methods based on user-friendly optical devices (e.g., USB digital microscope, flatbed scanner, smartphone, and DVD drive). Loop mediated isothermal amplification (LAMP) enables the required discrimination of each specific variant prior to the optical reading. In the first method, products are directly hybridized to the allele-specific probes attached to plastic chips in an array format. The second method, allele-specific primers are used, enabling the direct end-point detection based a colorimetric dyer and a microfluidic chamber chip. In both approaches, devices are employed for chip scanning.A representative application to the genotyping of a clinically relevant SNP from human samples is provided, showing the excellent features achieved. Consumer electronic devices are able to register sensitive precise measurements in terms of signal-to-noise ratios, image resolution, and scan-to-scan reproducibility. The integrated DNA-based method lead a low detection limit (100genomic DNA copies), reproducible (variation <15%), high specificity (genotypes validated by reference method), and cheap assays (<10€/test). The underlying challenge is the reliable implementation into minimal-specialized clinical laboratories, incorporating additional advantages, such as user-friendly interface, low cost, and connectivity for telemedicine needs.