Insight into the morphological instability of metallic nanowires under thermal stress.

HYPOTHESIS: Metallic nanowires, particularly polyol-grown silver nanowires, exhibit a morphological instability at temperatures significantly lower than their bulk melting point. This instability is commonly named after Rayleigh's description of the morphological instability of liquid jets, even though it has been shown that its quantitative predictions are not consistent with experimental measurements. In 1996, McCallum et al. proposed a description of the phenomenon assuming a solid wire lying on a substrate. It is assumed that the latter description depicts more accurately the reality. EXPERIMENTS: Nanowires with varying diameters have been deposited on silicon wafers. Statistical analysis of their radius and the wavelength of their periodical instability have been performed. FINDINGS: McCallum et al.'s model better aligns with experimental observations compared to Rayleigh's description. This validation provides a robust theoretical framework for enhancing the stability of nanowires, addressing a crucial aspect of their development.

Organizational commitment and its impact on employee performance in the water supply industry: Dataset from Vietnamese state-owned enterprises.

This dataset delves into the intricate dynamics linking organizational commitment (OC) and job performance (JP) within the realm of State-Owned Enterprises (SOEs). Centering on the water supply industry, it seeks to unravel the nuances of organizational citizenship behavior (OCB) in an economy oriented by socialist values. The compilation of this dataset represents a balanced integration of qualitative and quantitative methodologies, incorporating insights from expert interviews alongside data gathered from employee surveys. It encompasses 336 valid responses, which have been meticulously analyzed through Partial Least Squares Structural Equation Modeling (PLS-SEM). This approach facilitates a deeper understanding of the interconnections between OC, OCB, and EP. The dataset is instrumental in highlighting the pivotal role of professional integrity and voluntary dedication within SOEs, underscoring their critical function in representing state interests and effectively serving the public.

Antibacterial Activity against Escherichia coli and Cytotoxicity of Maillard Reaction Product of Chitosan and Glucosamine Prepared by Gamma Co-60 Ray Irradiation.

In this study, the gamma ray-induced Maillard reaction method was carried out for chitosan (CTS) and glucosamine (GA) to improve the water solubility and antibacterial activity. The mixture solution of CTS and GA was exposed to gamma rays at a dose of 25 kGy and freeze-dried to obtain a Maillard reaction product (MRP) powder. The physicochemical and biological properties of the CTS-GA MRP powder were investigated. The CTS-GA MRP powder expressed good solubility at a concentration of 0.05 g/mL. In addition, the result of the antibacterial activity test against Escherichia coli revealed that the CTS-GA MRP powder exhibited highly antibacterial activity at pH 7; in particular, bacterial density was reduced by over 4 logs. Furthermore, the cytotoxicity test of the CTS-GA MRP powder on mouse fibroblast cells (L929) showed non-cytotoxicity with high cell viability (>90%) at concentrations of 0.1-1 mg/mL. Owing to the high antibacterial activity and low cytotoxicity, the water-soluble CTS-GA MRP powder can be used as a favorable natural preservative for food and cosmetics.

Fruit-CoV: An efficient vision-based framework for speedy detection and diagnosis of SARS-CoV-2 infections through recorded cough sounds.

COVID-19 is an infectious disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). This deadly virus has spread worldwide, leading to a global pandemic since March 2020. A recent variant of SARS-CoV-2 named Delta is intractably contagious and responsible for more than four million deaths globally. Therefore, developing an efficient self-testing service for SARS-CoV-2 at home is vital. In this study, a two-stage vision-based framework, namely Fruit-CoV, is introduced for detecting SARS-CoV-2 infections through recorded cough sounds. Specifically, audio signals are converted into Log-Mel spectrograms, and the EfficientNet-V2 network is used to extract their visual features in the first stage. In the second stage, 14 convolutional layers extracted from the large-scale Pretrained Audio Neural Networks for audio pattern recognition (PANNs) and the Wavegram-Log-Mel-CNN are employed to aggregate feature representations of the Log-Mel spectrograms and the waveform. Finally, the combined features are used to train a binary classifier. In this study, a dataset provided by the AICovidVN 115M Challenge is employed for evaluation. It includes 7,371 recorded cough sounds collected throughout Vietnam, India, and Switzerland. Experimental results indicate that the proposed model achieves an Area Under the Receiver Operating Characteristic Curve (AUC) score of 92.8% and ranks first on the final leaderboard of the AICovidVN 115M Challenge. Our code is publicly available.

Advances in Flexible Metallic Transparent Electrodes.

Transparent electrodes (TEs) are pivotal components in many modern devices such as solar cells, light-emitting diodes, touch screens, wearable electronic devices, smart windows, and transparent heaters. Recently, the high demand for flexibility and low cost in TEs requires a new class of transparent conductive materials (TCMs), serving as substitutes for the conventional indium tin oxide (ITO). So far, ITO has been the most used TCM despite its brittleness and high cost. Among the different emerging alternative materials to ITO, metallic nanomaterials have received much interest due to their remarkable optical-electrical properties, low cost, ease of manufacturing, flexibility, and widespread applicability. These involve metal grids, thin oxide/metal/oxide multilayers, metal nanowire percolating networks, or nanocomposites based on metallic nanostructures. In this review, a comparison between TCMs based on metallic nanomaterials and other TCM technologies is discussed. Next, the different types of metal-based TCMs developed so far and the fabrication technologies used are presented. Then, the challenges that these TCMs face toward integration in functional devices are discussed. Finally, the various fields in which metal-based TCMs have been successfully applied, as well as emerging and potential applications, are summarized.

Grain-boundary segregation of magnesium in doped cuprous oxide and impact on electrical transport properties.

In this study, we report the segregation of magnesium in the grain boundaries of magnesium-doped cuprous oxide (Cu2O:Mg) thin films as revealed by atom probe tomography and the consequences of the dopant presence on the temperature-dependent Hall effect properties. The incorporation of magnesium as a divalent cation was achieved by aerosol-assisted metal organic chemical vapour deposition, followed by thermal treatments under oxidizing conditions. We observe that, in comparison with intrinsic cuprous oxide, the electronic transport is improved in Cu2O:Mg with a reduction of resistivity to 13.3 ± 0.1 Ω cm, despite the reduction of hole mobility in the doped films, due to higher grain-boundary scattering. The Hall carrier concentration dependence with temperature showed the presence of an acceptor level associated with an ionization energy of 125 ± 9 meV, similar to the energy value of a large size impurity-vacancy complex. Atom probe tomography shows a magnesium incorporation of 5%, which is substantially present at the grain boundaries of the Cu2O.

Genomic mutations and changes in protein secondary structure and solvent accessibility of SARS-CoV-2 (COVID-19 virus).

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a highly pathogenic virus that has caused the global COVID-19 pandemic. Tracing the evolution and transmission of the virus is crucial to respond to and control the pandemic through appropriate intervention strategies. This paper reports and analyses genomic mutations in the coding regions of SARS-CoV-2 and their probable protein secondary structure and solvent accessibility changes, which are predicted using deep learning models. Prediction results suggest that mutation D614G in the virus spike protein, which has attracted much attention from researchers, is unlikely to make changes in protein secondary structure and relative solvent accessibility. Based on 6324 viral genome sequences, we create a spreadsheet dataset of point mutations that can facilitate the investigation of SARS-CoV-2 in many perspectives, especially in tracing the evolution and worldwide spread of the virus. Our analysis results also show that coding genes E, M, ORF6, ORF7a, ORF7b and ORF10 are most stable, potentially suitable to be targeted for vaccine and drug development.

Deep Reinforcement Learning for Multiagent Systems: A Review of Challenges, Solutions, and Applications.

Reinforcement learning (RL) algorithms have been around for decades and employed to solve various sequential decision-making problems. These algorithms, however, have faced great challenges when dealing with high-dimensional environments. The recent development of deep learning has enabled RL methods to drive optimal policies for sophisticated and capable agents, which can perform efficiently in these challenging environments. This article addresses an important aspect of deep RL related to situations that require multiple agents to communicate and cooperate to solve complex tasks. A survey of different approaches to problems related to multiagent deep RL (MADRL) is presented, including nonstationarity, partial observability, continuous state and action spaces, multiagent training schemes, and multiagent transfer learning. The merits and demerits of the reviewed methods will be analyzed and discussed with their corresponding applications explored. It is envisaged that this review provides insights about various MADRL methods and can lead to the future development of more robust and highly useful multiagent learning methods for solving real-world problems.

Versatility of bilayer metal oxide coatings on silver nanowire networks for enhanced stability with minimal transparency loss.

Silver nanowire (AgNW) networks have been lately much investigated thanks to their physical properties and are therefore foreseen to play a key role in many industrial devices as transparent electrodes, but their stability can be an issue. Although it has been shown that thin metal oxide coatings enhance the stability of AgNW networks, such stabilization is achieved at the expense of transparency. We demonstrate that by depositing a second oxide coating, which acts as an antireflective layer, it is possible to obtain highly stable and transparent composite electrodes. AgNW networks were deposited by the airbrush method, and zinc oxide (ZnO) and aluminum oxide (Al2O3) coatings were deposited, by Atmospheric Pressure Spatial Atomic Layer Deposition (AP-SALD), using both glass and plastic substrates; therefore, the proposed fabrication method is low-cost and compatible with high-throughput scalable fabrication. The mechanical stability of bare, ZnO and ZnO/Al2O3-coated AgNWs upon bending is also presented. The obtained nanocomposites exhibit highly homogeneous and conformal oxide coatings with average thicknesses of a few tens of nanometers. Samples with bilayer coatings of 70 nm ZnO/70 nm Al2O3 still exhibit very good stability after annealing in air up to 450 °C for 6 repetitive cycles.

Stability Enhancement of Silver Nanowire Networks with Conformal ZnO Coatings Deposited by Atmospheric Pressure Spatial Atomic Layer Deposition.

Silver nanowire (AgNW) networks offer excellent electrical and optical properties and have emerged as one of the most attractive alternatives to transparent conductive oxides to be used in flexible optoelectronic applications. However, AgNW networks still suffer from chemical, thermal, and electrical instabilities, which in some cases can hinder their efficient integration as transparent electrodes in devices such as solar cells, transparent heaters, touch screens, and organic light emitting diodes. We have used atmospheric pressure spatial atomic layer deposition (AP-SALD) to fabricate hybrid transparent electrode materials in which the AgNW network is protected by a conformal thin layer of zinc oxide. The choice of AP-SALD allows us to maintain the low-cost and scalable processing of AgNW-based transparent electrodes. The effects of the ZnO coating thickness on the physical properties of AgNW networks are presented. The composite electrodes show a drastic enhancement of both thermal and electrical stabilities. We found that bare AgNWs were stable only up to 300 °C when subjected to thermal ramps, whereas the ZnO coating improved the stability up to 500 °C. Similarly, ZnO-coated AgNWs exhibited an increase of 100% in electrical stability with respect to bare networks, withstanding up to 18 V. A simple physical model shows that the origin of the stability improvement is the result of hindered silver atomic diffusion thanks to the presence of the thin oxide layer and the quality of the interfaces of hybrid electrodes. The effects of ZnO coating on both the network adhesion and optical transparency are also discussed. Finally, we show that the AP-SALD ZnO-coated AgNW networks can be effectively used as very stable transparent heaters.

Percolation in networks of 1-dimensional objects: comparison between Monte Carlo simulations and experimental observations.

Planar networks composed of 1-dimensional nanometer scale objects such as nanotubes or nanowires have been attracting growing interest in recent years. In this work we directly compare the percolation threshold of silver nanowire networks to predictions from Monte Carlo simulations, focusing particularly on understanding the impact of real world imperfections on the percolation onset in these systems. This work initially determines the percolation threshold as calculated from an ideal system using Monte Carlo methods. On this foundation we address the effects of perturbations in length, angular anisotropy and radius of curvature of the 1-dimensional objects, in line with those observed experimentally in purposely fabricated samples. This work explores why two-dimensional stick models in the literature currently underestimate the percolation onset in real systems and identifies which of the network's features play the most significant role in that deviation.

Transparent Electrodes Based on Silver Nanowire Networks: From Physical Considerations towards Device Integration.

The past few years have seen a considerable amount of research devoted to nanostructured transparent conducting materials (TCM), which play a pivotal role in many modern devices such as solar cells, flexible light-emitting devices, touch screens, electromagnetic devices, and flexible transparent thin film heaters. Currently, the most commonly used TCM for such applications (ITO: Indium Tin oxide) suffers from two major drawbacks: brittleness and indium scarcity. Among emerging transparent electrodes, silver nanowire (AgNW) networks appear to be a promising substitute to ITO since such electrically percolating networks exhibit excellent properties with sheet resistance lower than 10 Ω/sq and optical transparency of 90%, fulfilling the requirements of most applications. In addition, AgNW networks also exhibit very good mechanical flexibility. The fabrication of these electrodes involves low-temperature processing steps and scalable methods, thus making them appropriate for future use as low-cost transparent electrodes in flexible electronic devices. This contribution aims to briefly present the main properties of AgNW based transparent electrodes as well as some considerations relating to their efficient integration in devices. The influence of network density, nanowire sizes, and post treatments on the properties of AgNW networks will also be evaluated. In addition to a general overview of AgNW networks, we focus on two important aspects: (i) network instabilities as well as an efficient Atomic Layer Deposition (ALD) coating which clearly enhances AgNW network stability and (ii) modelling to better understand the physical properties of these networks.

Effect of oligochitosan and oligo-ß-glucan supplementation on growth, innate immunity, and disease resistance of striped catfish (Pangasianodon hypophthalmus).

Oligochitosan (COS) and oligo-ß-glucan (ßOG) were prepared by gamma Co-60 irradiation of chitosan/H2 O2 and ß-glucan/H2 O2 solutions. The striped catfish (Pangasianodon hypophthalmus) was fed diets containing 0-200 mg COS, ßOG, and a mixture of COS/ßOG per kg feed for 45 days, and then challenged with Edwardsiella ictaluri bacterium. The effects of supplemented COS, ßOG, and a mixture of COS/ßOG on immune stimulation and growth performance in striped catfish were investigated. The results indicated that when striped catfish fed with 100-200 mg COS or ßOG/kg feed the growth performance was significantly improved and the mortality was considerably decreased. Furthermore, striped catfish fed with supplementation of 50 mg COS + 50 mg ßOG/kg feed was the best for increasing weight gain (∼26%) and for decreasing mortality (∼38%) compared with the control group. Moreover, phagocytic activity and lysozyme activity of fish were enhanced by feeding diet-supplemented COS and/or ßOG. Thus, COS and/or ßOG can be potentially utilized as the immunostimulants and growth promoters for aquaculture.

Direct Imaging of the Onset of Electrical Conduction in Silver Nanowire Networks by Infrared Thermography: Evidence of Geometrical Quantized Percolation.

Advancement in the science and technology of random metallic nanowire (MNW) networks is crucial for their appropriate integration in many applications including transparent electrodes for optoelectronics and transparent film heaters. We have recently highlighted the discontinuous activation of efficient percolating pathways (EPPs) for networks having densities slightly above the percolation threshold. Such networks exhibit abrupt drops of electrical resistance when thermal or electrical annealing is performed, which gives rise to a "geometrically quantized percolation". In this Letter, lock-in thermography (LiT) is used to provide visual evidence of geometrical quantized percolation: when low voltage is applied to the network, individual "illuminated pathways" can be detected, and new branches get highlighted as the voltage is incrementally increased. This experimental approach has allowed us to validate our original model and map the electrical and thermal distributions in silver nanowire (AgNW) networks. We also study the effects of electrode morphology and wire dimensions on quantized percolation. Furthermore, we demonstrate that the network failure at high temperature can also be governed by a quantized increase of the electrical resistance, which corresponds to the discontinuous destruction of individual pathways (antipercolation). More generally, we demonstrate that LiT is a promising tool for the detection of conductive subclusters as well as hot spots in AgNW networks.

Imprinting superconducting vortex footsteps in a magnetic layer.

Local polarization of a magnetic layer, a well-known method for storing information, has found its place in numerous applications such as the popular magnetic drawing board toy or the widespread credit cards and computer hard drives. Here we experimentally show that a similar principle can be applied for imprinting the trajectory of quantum units of flux (vortices), travelling in a superconducting film (Nb), into a soft magnetic layer of permalloy (Py). In full analogy with the magnetic drawing board, vortices act as tiny magnetic scribers leaving a wake of polarized magnetic media in the Py board. The mutual interaction between superconducting vortices and ferromagnetic domains has been investigated by the magneto-optical imaging technique. For thick Py layers, the stripe magnetic domain pattern guides both the smooth magnetic flux penetration as well as the abrupt vortex avalanches in the Nb film. It is however in thin Py layers without stripe domains where superconducting vortices leave the clearest imprints of locally polarized magnetic moment along their paths. In all cases, we observe that the flux is delayed at the border of the magnetic layer. Our findings open the quest for optimizing magnetic recording of superconducting vortex trajectories.