Nanonetworks Research Articles

Bioinspired Crowding Inhibits Explosive Ice Growth in Antifreeze Protein Solutions.

Antifreeze (glyco)proteins (AF(G)Ps) are naturally evolved ice inhibitors incomparable to any man-made materials, thus, they are gaining intensive interest for cryopreservation and beyond. AF(G)Ps depress the freezing temperature (Tf) noncolligatively below the melting temperature (Tm), generating a thermal hysteresis (TH) gap, within which the ice growth is arrested. However, the ice crystals have been reported to undergo a retaliatory and explosive growth beyond the TH gap, which is lethal to living organisms. Although intensive research has been carried to inhibit such an explosive ice growth, no satisfactory strategy has been discovered until now. Here, we report that crowded solutions mimicking an extracellular matrix (ECM), in which AF(G)Ps are located, can completely inhibit the explosive ice growth. The crowded solutions are the condensates of liquid-liquid phase separation consisting of polyethylene glycol (PEG) and sodium citrate (SC), which possess a nanoscale network and strong hydrogen bond (HB) forming ability, completely different to crowded solutions made of single components, that is, PEG or SC. Due to these unique features, the dynamics of the water is significantly slowed down, and the energy needed for breaking the HB between water molecules is distinctly increased; consequently, ice growth is inhibited as the rate of water molecules joining the ice is substantially reduced. The present work not only opens a new avenue for cryopreservation, but also suggests that the ECM of cold-hardy organisms, which also exhibit great water confining properties, may have a positive effect in protecting the living organisms from freezing damage.

Lignin-Based Porous Supraparticles for Carbon Capture.

Multiscale carbon supraparticles (SPs) are synthesized by soft-templating lignin nano- and microbeads bound with cellulose nanofibrils (CNFs). The interparticle connectivity and nanoscale network in the SPs are studied after oxidative thermostabilization of the lignin/CNF constructs. The carbon SPs are formed by controlled sintering during carbonization and develop high mechanical strength (58 N·mm–3) and surface area (1152 m2·g–1). Given their features, the carbon SPs offer hierarchical access to adsorption sites that are well suited for CO2 capture (77 mg CO2·g–1), while presenting a relatively low pressure drop (∼33 kPa·m–1 calculated for a packed fixed-bed column). The introduced lignin-derived SPs address the limitations associated with mass transport (diffusion of adsorbates within channels) and kinetics of systems that are otherwise based on nanoparticles. Moreover, the carbon SPs do not require doping with heteroatoms (as tested for N) for effective CO2 uptake (at 1 bar CO2 and 40 °C) and are suitable for regeneration, following multiple adsorption/desorption cycles. Overall, we demonstrate porous SP carbon systems of low cost (precursor, fabrication, and processing) and superior activity (gas sorption and capture).

Ultrahigh degradation efficiency of AB type in-plane reverse polarization WS2 nano sheets in dark by piezo-catalyst effect

In the past decades, organic pollutants have become an important issue affecting life. In previous works, despite the photocatalytic degradation of organic pollutants have been extensively studied and applied, the period of catalytic effect is too long and the catalytic efficiency is difficult to converge, due to the limitation of photocatalytic conditions. In this work, the WS2 piezoelectric catalytic materials were proved to be highly efficient and reusable. Herein, it is reported that a-WS2 (150 °C), b-WS2 (160 °C), and c-WS2 (180 °C) catalysts degrade MB, with efficiencies of 99.7%, 72.2%, and 49.3%, respectively. The results show that cyclic stretching and releasing of thin WS2 flakes with an odd number atomic layers, produces oscillating piezoelectric volt-age, resulting in ultra-high catalytic efficiency. When external mechanical stress is applied, the WS2 nanosheets structure can disperse a large amount of hydroxyl radicals (OH) and superoxide radicals (O2−) in the solution. The high repetition rate of WS2 was also proved by cyclic experiments. In this work, the shortcomings of conventional photocatalysis were overcome by employing a novel AB type in-plane reverse polarization WS2 nano network, which is activated through the application of an external force.

Fabrication of injectable hydrogels from silk fibroin and angiogenic peptides for vascular growth and tissue regeneration

Development of new biomaterials which can structurally and functionally mimic natural cell environments is one major goal of tissue engineering. Recently, self-assembling peptides are attractive candidates to prepare biomimetic cellular niches, because their nanoscale network and biomechanical properties are similar to those of the natural extracellular matrix (ECM). Here, we describe the generation of a new bioactive hydrogel composed of silk fibroin (SF) and a self-assembling peptide NapFFSVVYGLR for tissue engineering. As a consequence of the cooperative assembling of silk fibroin and NapFFSVVYGLR and the functional role of the SVVYGLR epitope from the osteopontin protein, a bioactive hydrogel (e.g., SV-SF) is afforded, which exhibits good gel stabilities and high capacities to induce endothelial cell adhesion, growth and migration. After implantation into the defect area of mouse skin, the SV-SF hydrogel can promote vascularization and epidermization for epidermal repair, by stimulating collagen deposition and expression of angiogenesis-related genes/proteins. Altogether, these results suggest that the bioactive hydrogel can work as a promising material for vascular regeneration and wound healing applications.

Annual report of the EFSA Scientific Network of Risk Assessment of Nanotechnologies in Food and Feed for 2020

The Scientific Network of Risk Assessment of Nanotechnologies in Food and Feed (the Nano Network) was established in 2010 by the EFSA Advisory Forum, in accordance with EFSA's strategy for cooperation and networking with Member States. This Nano Network exchanges information and expertise between EFSA and Member States. It enhances dialogue among members, builds mutual understanding of risk assessment principles, improves knowledge and confidence in the scientific assessment carried out in the European Union, and increases the transparency of the process among Member States and EFSA. The annual reports of the Nano Network inform the public, stakeholders and research communities about the specific activities and achievements of the Nano Network. In 2020, the yearly meeting was held concomitantly with the 17th meeting of the EFSA cross-cutting Working Group on Nanotechnologies, and converted to virtual network meeting in line with the measures established by EFSA to reduce the risk of coronavirus infection. The purpose of this annual meeting was to ensure information and knowledge exchange with risk assessor delegates of European Member States on the ongoing activities and further research priorities. The Nano Network members were informed on the last updates of the Guidance documents produced by EFSA in the field of Nanotechnologies, which are currently under finalisation. The Network was asked to contribute to the finalisation of the Guidances as well as their further implementation and dissemination.

Kerogen nanoscale structure and CO2 adsorption in shale micropores

Gas storage and recovery processes in shales critically depend on nano-scale porosity and chemical composition, but information about the nanoscale pore geometry and connectivity of kerogen, insoluble organic shale matter, is largely unavailable. Using adsorption microcalorimetry, we show that once strong adsorption sites within nanoscale network are taken, gas adsorption even at very low pressure is governed by pore width rather than chemical composition. A combination of focused ion beam with scanning electron microscopy and transmission electron microscopy reveal the nanoscale structure of kerogen includes not only the ubiquitous amorphous phase but also highly graphitized sheets, fiber- and onion-like structures creating nanoscale voids accessible for gas sorption. Nanoscale structures bridge the current gap between molecular size and macropore scale in existing models for kerogen, thus allowing accurate prediction of gas sorption, storage and diffusion properties in shales.

Biomimetic nanoporous aerogels from branched aramid nanofibers combining high heat insulation and compressive strength

AbstractMaterials combining efficient thermal insulation and high mechanical properties are needed in many areas of technology. Various aerogels provide a convenient design framework for thermal insulators, but they are often brittle. Furthermore, the spectrum of advanced properties is constantly expanding while requirements to the degree of control of the three‐dimensional gel‐forming network is constantly increasing. Here, we report on biomimetic aramid nanofibers aerogels with the structure replicating articular cartilage, prepared by supercritical drying of 3D networks held together by hydrogen bonds. Owing to the branching morphology of the nanofibers, the three‐dimensional nanoscale networks with extensive percolation and high interconnectivity can be obtained. The aerogels showed high porosity with an average open pore size of 21.5 nm and correspondingly low specific density of 0.0081 g/cm3. The aerogels also possess a high compressive strength of 825 kPa at a strain of 80%. Due to the unique aramid chemistry of the parent nanofibers, aramid aerogels combine low thermal conductivity of 0.026 W/m·K with high thermal stability up to 530°C, which is unusually high for polymeric and composite materials of any type, opening a broad range of applications from electronics to space travel.

Exploring the interstitial system in the brain: the last mile of drug delivery.

Brain interstitial system (ISS) is a nanoscale network of continuously connected tubes and sheets surrounding each neural cell in the central nervous system. ISS usually accounts for ∼20% of the brain volume, far more than the cerebral blood vessels, which account for 3%. The neuronal function, signaling pathways, and drug delivery are all closely related to the microenvironment provided by ISS. The objective of this paper is to give the readers a clear outline of detection, anatomy, function, and applications of ISS. This review describes the techniques propelling the exploration for ISS in chronological order, physiological function and pathological dysfunction of ISS, and strategies for drug delivery based on ISS. Biophysical features are the focus of ISS research, in which the diffusion characteristics have dominated. The various techniques that explore ISS take advantage of this feature. ISS provides an essential microenvironment for the health of cells and brain homeostasis, which plays an important functional role in brain health and disease. Direct intracranial administration allows the diffusion of drugs directly through ISS to successfully bypass the blood-brain barrier that prevents most drugs from reaching the brain. With the deepening of understanding of the brain ISS, the new research model that takes into account brain cells, cerebral vessels, and ISS will provide a new perspective and direction for understanding, utilizing, and protecting the brain.

EmotionNet Nano: An Efficient Deep Convolutional Neural Network Design for Real-Time Facial Expression Recognition.

While recent advances in deep learning have led to significant improvements in facial expression classification (FEC), a major challenge that remains a bottleneck for the widespread deployment of such systems is their high architectural and computational complexities. This is especially challenging given the operational requirements of various FEC applications, such as safety, marketing, learning, and assistive living, where real-time requirements on low-cost embedded devices is desired. Motivated by this need for a compact, low latency, yet accurate system capable of performing FEC in real-time on low-cost embedded devices, this study proposes EmotionNet Nano, an efficient deep convolutional neural network created through a human-machine collaborative design strategy, where human experience is combined with machine meticulousness and speed in order to craft a deep neural network design catered toward real-time embedded usage. To the best of the author’s knowledge, this is the very first deep neural network architecture for facial expression recognition leveraging machine-driven design exploration in its design process, and exhibits unique architectural characteristics such as high architectural heterogeneity and selective long-range connectivity not seen in previous FEC network architectures. Two different variants of EmotionNet Nano are presented, each with a different trade-off between architectural and computational complexity and accuracy. Experimental results using the CK + facial expression benchmark dataset demonstrate that the proposed EmotionNet Nano networks achieved accuracy comparable to state-of-the-art FEC networks, while requiring significantly fewer parameters. Furthermore, we demonstrate that the proposed EmotionNet Nano networks achieved real-time inference speeds (e.g., >25 FPS and >70 FPS at 15 and 30 W, respectively) and high energy efficiency (e.g., >1.7 images/sec/watt at 15 W) on an ARM embedded processor, thus further illustrating the efficacy of EmotionNet Nano for deployment on embedded devices.

Novel nano network trigonal prismatic Ba2CoO4-deficient BaCoO3 for high-affinity sorption of radiolanthanide elements of biomedical applications: synthesis and sorption studies.

Nano trigonal prismatic Ba2CoO4 with hierarchical structure and deficient BaCoO3 with columnar structure have been prepared at low temperatures (400 [BC4] and 500 [BC5]) °C/3h using green method. X-ray diffraction (XRD) results demonstrate the presence of enriched Ba2CoO4 phase at 400 °C and multiphase structures: BaCoO3, BaCoO3-δ, and Co3O4 with a decrease in the amount of Ba2CoO4 at 500 °C. The prepared powders are characterized by a high specific surface area (SSA) values which are reflected to the mode of synthesis that leads to produce materials with massive active sites. The SSA of BC4 is higher than that of BC5 which can be correlated to the difference in the microstructure analysis of BC4 and BC5 as given from scanning electron microscope (SEM) and high-resolution transmission electron microscope (HRTEM) studies. Electron spin resonance (ESR) spectroscopy as an effective method for the characterization of vacancy-rich nanostructures indicates that the presence of oxygen vacancies is related mainly to BaCoO3, BaCoO3-δ, and Co3O4 phases while the effective oxygen vacancies is in BaCoO3 and BaCoO3-δ. The nanocrystalline structures of BC4 and BC5 as novel nano-adsorbents are the first time to be tested. Production of Gd radioisotopes through natGd(n,γ)153,159,161Gd and carrier-free 161Tb through 160Gd(n,γ,) 161Gd [Formula: see text] 161Tb are achieved at 2nd Egyptian nuclear research reactor (ETRR-2). Preliminary sorption study of Gd radioisotopes (represent the lanthanide elements) shows a promising material for the application in the separation and removal of lanthanide elements. The results demonstrated that the fast interaction and efficient sorption of lanthanides ions are based on the novel synthesized nanomaterial that can be considered for the upscale application in this field.

A 1D–3D interconnected δ-MnO2 nanowires network as high-performance and high energy efficiency cathode material for aqueous zinc-ion batteries

Aqueous zinc‐ion batteries (AZIBs) have received significant research attention and widely investigated because of their high intrinsic safety and cost effectiveness. Manganese dioxide has been regarded as a promising cathode material for AZIBs, attributed to its friendliness, abundant resources, high theoretical capacity, and high working voltage. Herein, a unique one-dimensional–three-dimensional (1D–3D) hybrid network with interconnected δ-MnO2 nanowires was reported as a cathode material for AZIBs. A distinctive 3D nano network structure resulted in enhancement of electrolyte osmosis and significant increase in contact between electrode and electrolyte, and also provided more active sites and convenient rapid ion transport routes. Moreover, the fine nanowire structure and the optimum layer spacing resulted in easier insertion/deinsertion of ion in the active material. Taking advantage of this feature, the δ-MnO2 cathode provides high reversible capacity, fast rate capability and good longevity for cycling. Further kinetic experiments revealed that Zn/δ‐MnO2 system constitutes an electrochemical reaction regulated by the combination of ionic diffusion and pseudo-capacitance; and shows high energy efficiency during the charge/discharge states. This research may provide an advanced cathode material for AZIB development.

Nanoscale decoupling of electronic nematicity and structural anisotropy in FeSe thin films

In a material prone to a nematic instability, anisotropic strain in principle provides a preferred symmetry-breaking direction for the electronic nematic state to follow. This is consistent with experimental observations, where electronic nematicity and structural anisotropy typically appear hand-in-hand. In this work, we discover that electronic nematicity can be locally decoupled from the underlying structural anisotropy in strain-engineered iron-selenide (FeSe) thin films. We use heteroepitaxial molecular beam epitaxy to grow FeSe with a nanoscale network of modulations that give rise to spatially varying strain. We map local anisotropic strain by analyzing scanning tunneling microscopy topographs, and visualize electronic nematic domains from concomitant spectroscopic maps. While the domains form so that the energy of nemato-elastic coupling is minimized, we observe distinct regions where electronic nematic ordering fails to flip direction, even though the underlying structural anisotropy is locally reversed. The findings point towards a nanometer-scale stiffness of the nematic order parameter.

The plant cell wall: Biosynthesis, construction, and functions

The plant cell wall is composed of multiple biopolymers, representing one of the most complex structural networks in nature. Hundreds of genes are involved in building such a natural masterpiece. However, the plant cell wall is the least understood cellular structure in plants. Due to great progress in plant functional genomics, many achievements have been made in uncovering cell wall biosynthesis, assembly, and architecture, as well as cell wall regulation and signaling. Such information has significantly advanced our understanding of the roles of the cell wall in many biological and physiological processes and has enhanced our utilization of cell wall materials. The use of cutting-edge technologies such as single-molecule imaging, nuclear magnetic resonance spectroscopy, and atomic force microscopy has provided much insight into the plant cell wall as an intricate nanoscale network, opening up unprecedented possibilities for cell wall research. In this review, we summarize the major advances made in understanding the cell wall in this era of functional genomics, including the latest findings on the biosynthesis, construction, and functions of the cell wall.

Graphene characterization based nano dipole antennas design for nano network wireless communication applications

Graphene-enabled nano antennas constitute a novel paradigm which is a current trend of research among designers. Graphene-based nano-antennas with nanometer in size have shown to radiate electromagnetic waves at the terahertz (THz) frequency band. Proposed research activity is an attempt of Terahertz Nano dipole antenna design through the Finite Difference Time Domain (FDTD) based numerical simulation software, i.e. CST. Graphene material as adipole antenna has been explored to get a radiation performance. Before hand absorption, reflection and transmission characteristics of the grapheme layer has been explored. Designed antenna is analyzed in terms of the reflection coefficient, and radiation pattern etc. An attempt has been done for resonance study of graphene based nano dipole antennas, in that patch antenna length parameteris changed and performance is observed. The impact of most crucial parameter, i.e., chemical potential on the grapheme radiation performance has been analyzed in terms of reflection coefficient. Proposed antenna may be suitable for wireless nano communication applications.

Nano Network Formation of CNF and the Applications

Nano Network Formation of CNF and the Applications

The role of nano-communication in bio medical application and research

Nano-communication devices play the vital role in the medical field in order to improve the quality of human life. They can be widely used because it can access small and delicate body sites non-invasively, where traditional medical devices are inefficient. In this paper, a brief study about the current models, various communication paradigms, antenna design, radio channel models and nano network models of the nano technology is presented. Also, the open research areas are illustrated for future development in the field.

Machine Learning in Nano-Scale Biomedical Engineering

Machine learning (ML) empowers biomedical systems with the capability to optimize their performance through modeling of the available data extremely well, without using strong assumptions about the modeled system. Especially in nano-scale biosystems, where the generated data sets are too vast and complex to mentally parse without computational assist, ML is instrumental in analyzing and extracting new insights, accelerating material and structure discoveries and designing experience as well as supporting nano-scale communications and networks. However, despite these efforts, the use of ML in nano-scale biomedical engineering remains still under-explored in certain areas and research challenges are still open in fields such as structure and material design and simulations, communications and signal processing, and bio-medicine applications. In this article, we review the existing research regarding the use of ML in nano-scale biomedical engineering. In more detail, we first identify and discuss the main challenges that can be formulated as ML problems. These challenges are classified in three main categories: structure and material design and simulation, communications and signal processing and biomedicine applications. Next, we discuss the state of the art ML methodologies that are used to countermeasure the aforementioned challenges. For each of the presented methodologies, special emphasis is given to its principles, applications and limitations. Finally, we conclude the article with insightful discussions, that reveal research gaps and highlight possible future research directions.

A Novel Framework for Capacity Analysis of Diffusion-Based Molecular Communication Incorporating Chemical Reactions

In recent years, molecular communication (MC) is considered as a transformative paradigm in the communication theory and a promising solution to future nanoscale communication networks. In this article, a novel framework is introduced for diffusion-based MC and is shown how its capacity is impacted by the effects of chemical reactions which were neglected in the existing literature. Particularly, the chemical reactions corresponding to complex balanced chemical reaction networks are studied in this work. With an information-theoretic approach, the capacity is introduced where the effects of chemical reactions are taken into account. Then, the individual entropy derivations are addressed where the chemical reactions at the transmitter are considered with the chemical reaction network theory. Finally, the mutual information is derived based on these entropy derivations and the analytical capacity expressions are introduced accordingly. Numerical results exhibit the interactions between different parameters and show that the capacity actually decreases when the effects of chemical reactions are considered, implying that the capacity derived without chemical reactions was overestimated in previous studies. Consequently, the proposed framework analyzes the fundamental limits of diffusion-based MC and provides a more realistic capacity derivation comprising limitations imposed by chemical reactions, hence applicable to various more realistic MC scenarios.

Development and evaluation of nanostructured palladium thin film prepared by dealloying using dilute citric acid for hydrogen gas sensing application

The safe application of H2 gas requires a high-performance H2 gas sensing system. An attractive H2 gas sensor for industrial application which has H2 gas selectivity, high sensitivity, high response, high durability, small size, and low cost has not been developed yet. Durability is one of the most important problems in H2 gas sensors using Pd. This study focused on electric resistivity changes in metallic Pd with hydrogen gas absorption. Nanostructured palladium (NSPd) films for a hydrogen gas sensing material were fabricated by a dealloying method using dilute citric acid. Fabricated NSPd films exhibited a nanoscaled network structure or aggregated particle structure, a linear electric resistance change with hydrogen gas concentration, and high sensitivity compared to flat pure Pd films. Therefore, NSPd film is useful for hydrogen gas sensing applications and has both high sensitivity and low usage of the noble metal. Furthermore, we also revealed a degradation mechanism of pure Pd film due to repeated H2 gas exposure, and this phenomenon did not appear in the NSPd film. NSPd also showed a higher durability with repeated H2 gas exposure compared to pure Pd film. We concluded that NSPd is suitable for use as a practical H2 gas sensor due to its cost effectiveness and high sensing ability.

Curvature effects of electron-donating polymers on the device performance of non-fullerene organic solar cells

In this study, we investigate the effects of polymer backbone curvature on the performance of non-fullerene organic solar cells (NFA-OSCs) fabricated using an electron-donating π-conjugated polymer and a non-fullerene electron-acceptor (NFA), 3,9-bis[2-methylene(3-(1,1-dicyanomethylene)-indanone)]-5,5,11,11-tetrakis(4-hexylphenyl)-dithieno[2,3-d:2ʹ,3ʹ-dʹ]-s-indaceno[1,2-b:5,6-bʹ]dithiophene (ITIC). The NFA-OSCs are fabricated using structurally similar bis(pyrrolo[3,4-c]pyrrole-1,3(2H,5H)-dione) (BPPD)-based π–conjugated polymers, i.e., P1 and P2, and they indicate almost identical absorption and energy levels but dissimilar backbone curvatures. P1 comprises two-dimensional conjugated benzodithiophene (BDTT) and thiophene π-bridged BPPD derivatives, and P2 comprises BDTT and thieno[3,2-b]thiophene π-bridged BPPD derivatives. The absorption maximum and highest occupied/lowest unoccupied molecular orbital levels of P1 and P2 are ~505 nm and ~˗5.4/˗3.4 eV, respectively. However, P1 shows a twisted backbone, whereas P2 exhibits a well-controlled wavy backbone owing to the presence of slightly different-structured π-bridges, such as thiophene and thieno[3,2-b]thiophene, on their backbones. The NFA-OSCs are fabricated with the structures of glass-ITO/PEDOT:PSS/P1 and P2:ITIC+0.5 vol% 1,8-diiodoctane (DIO)/PFN-Br/Al provide quite different device performances with power conversion efficiency of 0.88% and 6.25%, respectively. In general, the curvature of the polymer backbone significantly affects the nanoscale network formation between the polymer and ITIC, thereby resulting in a significant difference in the carrier transport and photovoltaic performances of the NFA-OSCs.