Nanonetworks Research Articles

Ion Diffusion Reveals Heterogeneous Viscosity in Nanostructured Ionic Liquids.

Many ionic liquids (ILs) are composed of interpenetrating polar and apolar networks. These nanoscale networks are sustained by different local intermolecular and electrostatic interactions and are predicted to differ in their physical properties by orders of magnitude. Nonetheless, it is commonplace for the physical properties of ILs to be described by bulk parameters, such as the bulk dynamic viscosity. This study addresses the limitations of using bulk parameter descriptions in nanostructured ILs by applying the Saffman-Delbrück model to interpret the self-diffusion coefficient of ions within the homologous series of [Cnmim][NTf2] ILs. We demonstrate that pulsed field gradient NMR spectroscopy can effectively probe the relative viscosities of polar/charged and apolar networks within these pure ILs. Our calculated polar viscosities show good agreement with literature simulations. Our approach provides valuable insights into the local viscoelastic environments within nanostructured media. This work not only contributes to the understanding of mass and charge transport in ILs but also offers a new experimental perspective for studying structured fluids more broadly.

Organic BODIPY based gels: Optical, electrochemical and self-assembly properties.

Two novel BODIPY dyes, BOC3 and BC12, were synthesized with variable alkyl chains at terminal amide functional units. BC12, featuring a longer alkyl chain (-C12H25), formed a gel compared to BOC3, which has a shorter alkyl chain (-CH2OCH3), due to supra molecular self-assembly in film. Both dyes exhibited absorption peaks around 530 nm in the visible region, with a red shift of about 30 nm in the film state, essential for organic electronic applications. Concentration variation studies revealed π-π stacking/aggregates in the solid state causing red shifts in absorption and emission. BC12 exhibited more significant red shifts in film compared to its solution state due to supra molecular self-assembly. Electronic structure analysis using density functional theories (BMK and O3LYP) showed better correlation with absorption using the O3LYP method. Both dyes displayed quasi-irreversible oxidation and reduction couples with suitable HOMO (5.46 eV) and LUMO (3.32 eV) energy levels for organic electronic applications. Transient photoluminescence studies indicated a longer lifetime for BC12 (5.28 ns) than BOC3 (4.50 ns), suggesting π-π aggregation and supra molecular self-assembly. BC12's gelation, attributed to its long alkyl chain and two-dimensional motifs of the BODIPY core, forms spherical-shaped nano networks.

Mixed metric dimension and exchange property of hexagonal nano-network

The mixed metric dimension of a graph is an important parameter in characterizing its structural complexity, specifically in nanoscale networks where precision is paramount. In this article, we calculate the mixed metric dimension of hexagonal nano-network, a modal with significant applications in nanotechnology and material science. Through rigorous analysis, we set up that the mixed metric dimension of the hexagonal nano-network is exactly three, highlighting its minimal but enough resolving set that uniquely identifies all vertices. Furthermore, we check out the exchange property within this context, demonstrating the robust adaptability of the hexagonal network’s resolving sets. Our findings display that the alternate assets aren’t the handiest preserved but stronger in these nano-networks, allowing for flexible adjustments in resolving sets without compromising the network’s integrity. This examination offers critical insights into the fundamental properties of hexagonal nano-networks, offering a theoretical foundation for future research in nanomaterial design and optimization. The results underscore the potential of leveraging mixed metric dimensions and exchange properties to achieve efficient and scalable solutions in nano-network applications.

Highly Reversible Conversion-Type CoSn2 Cathode for Fluoride-Ion Batteries.

An all-solid-state fluoride-ion battery (FIB) is one of the promising candidates for the next-generation battery owing to its high energy density and high safety. For the practical application of FIBs, it is an urgent task to operate FIBs at lower temperatures. However, there are still two major difficulties in conventional conversion-type pure metal cathodes: low F- ion conductivities and poor cycle stabilities. Here, the conversion-type Sn-based intermetallic alloy is proposed as a new cathode that can overcome the above issues. The present CoSn2 cathode retains the discharge capacity of 229 mAh g-1 after 250 cycles, even at 60°C. CoSn2 is decomposed into CoF2 and SnF2 nanocrystals in the charging process, and the nanoscale network structure of SnF2 provides the fast F- ion conduction path throughout the cathode, facilitating the battery operation at lower temperatures. Moreover, the formed CoF2 and SnF2 phases are merged into the original CoSn2 phase in the discharging process, leading to a highly reversible redox reaction and the high cycle stability of CoSn2. These findings should pave the way to enhance the performance of all-solid-state FIBs at lower temperatures.

Tuning the thermodynamic ordering of strongly correlated protons in ice by angstrom-scale interface modification

The static and dynamic behaviour of strongly correlated many-body protons in nanoscale hydrogen-bond networks plays crucial roles in a wide range of physicochemical, biological and geological phenomena in nature. However, because of the difficulty of probing and manipulating the proton configuration in nanomaterials, controlling the cooperative behaviour of many-body protons remains challenging. By combining proton-order sensitive nonlinear optical spectroscopy and well-defined interface modification at molecular/atomic scale, we demonstrate the possibility of extensively tuning the emergent physical properties of strongly correlated protons beyond the thermodynamic constraints of bulk hydrogen bonds. Focusing on heteroepitaxially grown crystalline ice films as a model of a strongly correlated and frustrated proton system, we show that the emergence and disappearance of a high-Tc proton order on the nano- to mesoscale is readily switched by angstrom-scale interface engineering. These results pave a way to designing and controlling emergent properties of correlated proton systems.

Revealing nanoscale structure and interfaces of protein and polymer condensates via cryo-electron microscopy.

Liquid-liquid phase separation (LLPS) is a ubiquitous demixing phenomenon observed in various molecular solutions, including in polymer and protein solutions. Demixing of solutions results in condensed, phase separated droplets which exhibit a range of liquid-like properties driven by transient intermolecular interactions. Understanding the organization within these condensates is crucial for deciphering their material properties and functions. This study explores the distinct nanoscale networks and interfaces in the condensate samples using a modified cryo-electron microscopy (cryo-EM) method. The method involves initiating condensate formation on electron microscopy grids to limit droplet growth as large droplet sizes are not ideal for cryo-EM imaging. The versatility of this method is demonstrated by imaging three different classes of condensates. We further investigate the condensate structures using cryo-electron tomography which provides 3D reconstructions, uncovering porous internal structures, unique core-shell morphologies, and inhomogeneities within the nanoscale organization of protein condensates. Comparison with dry-state transmission electron microscopy emphasizes the importance of preserving the hydrated structure of condensates for accurate structural analysis. We correlate the internal structure of protein condensates with their amino acid sequences and material properties by performing viscosity measurements that support that more viscous condensates exhibit denser internal assemblies. Our findings contribute to a comprehensive understanding of nanoscale condensate structure and its material properties. Our approach here provides a versatile tool for exploring various phase-separated systems and their nanoscale structures for future studies.

Significantly improved thermal conductivity of C/C composite by constructing 3D SiC nanowires network in carbon felt via vacuum thermal evaporation

Developing a nanoscale secondary thermal conduction network within carbon fiber performs is a challenging yet effective method to substantially enhance the thermal conductivity of C/C composites. In this study, a strategy for creating a three-dimensional (3D) SiC nanowires (SiCNWs) thermal conductivity network in carbon felts (CFs) was implemented using vacuum thermal evaporation technology to fabricate SiCNWs modified C/C composites (SiCNW–C/C). The growth mechanism of SiC nanowires within CFs and their impact on the microstructure and thermal conductivity of the C/C composite were thoroughly investigated. The findings indicate that a SiC nanowires thermal conduction network can be successfully established within carbon felts without catalysts by initiating nucleation sites and managing reaction pressure. An appropriate reaction pressure is crucial not only for the uniform growth of SiC nanowires but also as a key factor in modulating the content and microstructure of the SiC nanowires. SiC nanowires prepared at 150 Pa exhibit minimal structural defects and are evenly distributed throughout the carbon felts, markedly enhancing the thermal response rate of the felts. The thermal conductivity of these SiCNW-modified C/C composites, both parallel and perpendicular to the carbon fibers, increased to 173 W/m•K and 112 W/m•K, respectively, approximately tripling that of the pure C/C composite. The exceptional thermal management capabilities of SiCNW–C/C were empirically validated through simulated operational chips and finite element simulation. This work presents an effective approach for producing C/C composite with high thermal conductivity particularly through the thickness, offering promising applications in the thermal management of advanced electronics.

High-resolution three-dimensional imaging of topological textures in nanoscale single-diamond networks.

Topological defects-extended lattice deformations that are robust against local defects and annealing-have been exploited to engineer novel properties in both hard and soft materials. Yet, their formation kinetics and nanoscale three-dimensional structure are poorly understood, impeding their benefits for nanofabrication. We describe the fabrication of a pair of topological defects in the volume of a single-diamond network (space group Fd m) templated into gold from a triblock terpolymer crystal. Using X-ray nanotomography, we resolve the three-dimensional structure of nearly 70,000 individual single-diamond unit cells with a spatial resolution of 11.2 nm, allowing analysis of the long-range order of the network. The defects observed morphologically resemble the comet and trefoil patterns of equal and opposite half-integer topological charges observed in liquid crystals. Yet our analysis of strain in the network suggests typical hard matter behaviour. Our analysis approach does not require a priori knowledge of the expected positions of the nodes in three-dimensional nanostructured systems, allowing the identification of distorted morphologies and defects in large samples.

Orthogonal DNA Self-Assembly-Based Expansion Microscopy Platform for Amplified, Multiplexed Biomarker Imaging.

Expansion microscopy (ExM) facilitates nanoscale imaging under conventional microscopes, but it frequently encounters challenges such as fluorescence losses, low signal-to-noise ratio (SNR), and limited detection throughput. To address these issues, a method of orthogonal DNA self-assembly-based ExM (o-DAExM) platform is developed, which employs hybridization chain reaction instead of conventional fluorescence labeling units, showcasing signal amplification efficacy, enhancement of SNR, and expandable multiplexing capability at any stage of the ExM process. In this work, o-DAExM has been applied to compare with immunofluorescence-based ExM for cellular cytoskeleton imaging, and the resolved nanoscale spatial distributions of cytoskeleton show outstanding performance and reliability of o-DAExM. Furthermore, the study demonstrates the utility of o-DAExM in accurately revealing exosome heterogeneous information and multiplexed analysis of protein targets in single cells, which provides infinite possibilities in super-resolution imaging of cells and other samples. Therefore, o-DAExM offers a straightforward expansion and signal labeling method, highlighting future prospects to study nanoscale structures and functional networks in biological systems.

High-speed terahertz communication with graphene-based time-modulated low-bit phase coding metasurfaces: A novel architecture for enhanced performance

Coding metasurfaces have revolutionized electromagnetic device development by enabling precise electromagnetic wave manipulation. While spatial phase modulation alone offers significant capabilities, its limitations to comprehensive control and optimal functionality are evident. As a result of recent advancements, joint amplitude-phase coding approaches have been explored using different techniques in order to enhance performance. However, such methods often result in complex structures due to the combining of various modulation techniques within meta-atoms. Addressing this challenge, this paper proposes a novel architecture for terahertz (THz) communication utilizing low-bit coding metasurfaces featuring simplified meta-atoms. Our approach introduces a coding unit cell based on graphene, combined with time-modulated coding, to enable phase and amplitude control for different harmonics. As a proof-of-concept application, we demonstrate the effectiveness of our technique in multimode vortex communication. Moreover, we show secure hologram communication by using our proposed design within the THz frequency regime. By enhancing wavefront shaping flexibility through a straightforward approach, this work lays the foundation for next-generation devices, particularly in high-speed macroscale and nanoscale communication networks.

Transparent Superhydrophobic and Self-Cleaning Coating.

Surface roughness and low surface energy are key elements for the artificial preparation of biomimetic superhydrophobic materials. However, the presence of micro-/nanostructures and the corresponding increase in roughness can increase light scattering, thereby reducing the surface transparency. Therefore, designing and constructing superhydrophobic surfaces that combine superhydrophobicity with high transparency has been a continuous research focus for researchers and engineers. In this study, a transparent superhydrophobic coating was constructed on glass substrates using hydrophobic fumed silica (HF-SiO2) and waterborne polyurethane (WPU) as raw materials, combined with a simple spray-coating technique, resulting in a water contact angle (WCA) of 158.7 ± 1.5° and a sliding angle (SA) of 6.2 ± 1.8°. Characterization tests including SEM, EDS, LSCM, FTIR, and XPS revealed the presence of micron-scale protrusions and a nano-scale porous network composite structure on the surface. The presence of HF-SiO2 not only provided a certain roughness but also effectively reduced surface energy. More importantly, the coating exhibited excellent water-repellent properties, extremely low interfacial adhesion, self-cleaning ability, and high transparency, with the light transmittance of the coated glass substrate reaching 96.1% of that of the bare glass substrate. The series of functional characteristics demonstrated by the transparent superhydrophobic HF-SiO2@WPU coating designed and constructed in this study will play an important role in various applications such as underwater observation windows, building glass facades, automotive glass, and goggles.

Theoretical study on the effective thermal conductivity of silica aerogels based on a cross-aligned and cubic pore model

Abstract Aerogel nanoporous materials possess high porosity, high specific surface area, and extremely low density due to their unique nanoscale network structure. Moreover, their effective thermal conductivity is very l1ow, making them a new type of lightweight and highly efficient nanoscale super-insulating material. However, predicting their effective thermal conductivity is challenging due to their uneven pore size distribution. To investigate the internal heat transfer mechanism of aerogel nanoporous materials, this study constructed cross-aligned and cubic pore model (CACPM) based on the actual pore arrangement of SiO2 aerogel. Based on the established cross-aligned and cubic pore model (CACPM), the effective thermal conductivity expression for aerogel was derived by simultaneously considering gas-phase heat conduction, solid-phase heat conduction, and radiative heat transfer. The derived expression was then compared with available experimental data and the Wei structure model. The results indicate that, according to the model established in this study for the derived thermal conductivity formula of silica aerogel, for powdery silica aerogel under the conditions of T=298K, a 2=0.85, D 1=90μm, ρ=128kg/m3, within the pressure range of 0-105Pa, the average deviation between the calculated values and experimental values is 10.51%. In the pressure range of 103-104Pa, the deviation between calculated values and experimental values is within 4%. Under these conditions, the model has certain reference value in engineering verification. This study also makes a certain contribution to the research of aerogel thermal conductivity heat transfer model and calculation formula.

Detection Method for Rice Seedling Planting Conditions Based on Image Processing and an Improved YOLOv8n Model

In response to the need for precision and intelligence in the assessment of transplanting machine operation quality, this study addresses challenges such as low accuracy and efficiency associated with manual observation and random field sampling for the evaluation of rice seedling planting conditions. Therefore, in order to build a seedling insertion condition detection system, this study proposes an approach based on the combination of image processing and deep learning. The image processing stage is primarily applied to seedling absence detection, utilizing the centroid detection method to obtain precise coordinates of missing seedlings with an accuracy of 93.7%. In the target recognition stage, an improved YOLOv8 Nano network model is introduced, leveraging deep learning algorithms to detect qualified and misplaced seedlings. This model incorporates ASPP (atrous spatial pyramid pooling) to enhance the network’s multiscale feature extraction capabilities, integrates SimAM (Simple, Parameter-free Attention Module) to improve the model’s ability to extract detailed seedling features, and introduces AFPN (Asymptotic Feature Pyramid Network) to facilitate direct interaction between non-adjacent hierarchical levels, thereby enhancing feature fusion efficiency. Experimental results demonstrate that the enhanced YOLOv8n model achieves precision (P), recall (R), and mean average precision (mAP) of 95.5%, 92.7%, and 95.2%, respectively. Compared to the original YOLOv8n model, the enhanced model shows improvements of 3.6%, 0.9%, and 1.7% in P, R, and mAP, respectively. This research provides data support for the efficiency and quality of transplanting machine operations, contributing to the further development and application of unmanned field management in subsequent rice seedling cultivation.

Energy-efficient faradaic desalination with scalable MnOx-coated carbon nanofoam papers validated by automated batch testing

Electrochemical approaches to water desalination show promise for processing brackish water, but continued progress relies on developing scalable electrode architectures with competitive capacity and uptake dynamics for ion capture. Binder-free, device-ready carbon nanofoam papers (CNFPs) are one such candidate, where intermingled nanoscale networks of conductive carbon and pores balance the transport of electrons and ions throughout the electrified interior. Microwave-assisted electroless deposition of conformal nanoscale manganese oxide (MnOx) at the CNFP surface amplifies the ion-capture capacity to technologically relevant levels via faradaic pseudocapacitance. We take advantage of the design flexibility of these electrode architectures to vary CNFP pore size (5 to >100 nm) and thickness (100–300 μm), and then characterize the resulting MnOx@CNFP electrode series for their respective desalination performance in 20 mM NaCl using automated recirculating-batch protocols. The combination of CNFP conductivity and facile ion/electrolyte transport through the pore network with the faradaic ion-capture capability of the MnOx coating enables effective desalination. Using 0.3 mm-thick electrodes and MnOx loadings over 16 mg cm−2, we obtain desalination productivity of 6.8 L m−2 at 4.4 L m−2 h−1 for 90 % salt removal at only 0.13 Wh L−1 energy consumption.

Emerging Trends: Nano-Scale Wireless Sensor Networks and Applications

New Adaptive Nano-Scale Sensor Network (ANSN) can quickly feel nanoscale surroundings. ANSN uses data in many scenarios to improve networks, consume less energy, and gain more accurate data. ANSI essentials are covered in detail here. This group has numerous parts. Making service better, collecting data with less energy, sending data with Q-learning, merging sensor data to increase accuracy, controlling power dynamically, and protecting data using AES are examples. Energy collection and sensor use are key to this effort. Academic research has proven that ANSN outperforms other techniques in several areas. Improvements include speed, security, latency, sensor accuracy, and network stability. With these changes, ANSN may be suitable for small wireless sensor networks.

Surface modification of a biomass-derived self-supported carbon nano network as an emerging platform for advanced field emitter devices and supercapacitor applications.

Herein, a self-supported carbon network is designed through the sole pyrolysis of Carica papaya seeds (biomass) without any activation agent, demonstrating their field emission and supercapacitor applications. The pyrolysis of seeds in an argon atmosphere leads to the formation of interconnected, rod-like structures. Furthermore, the hydrofluoric acid treatment not only removed impurities, but also resulted in the formation of CaF2 nanocrystals with the addition of F-doping. From the field emission studies, the turn-on field values defined at an emission current density of ∼10 μA cm-2 were found to be ∼2.16 and 1.21 V μm-1 for the as-prepared carbon and F-doped carbon, respectively. Notably, F-doped carbon exhibits a high emission current density of ∼9.49 mA cm-2 and has been drawn at an applied electric field of ∼2.29 V μm-1. Supercapacitor studies were carried out to demonstrate the multi-functionality of the prepared materials. The F-doped carbon electrode material exhibits the highest specific capacitance of 234 F g-1 at 0.5 A g-1. To demonstrate the actual supercapacitor application, the HFC//HFC symmetric coin cell supercapacitor device was assembled. The overall multifunctional applicability of the fabricated hybrid structures provides a futuristic approach to field emission and energy storage applications.

Silver-Rich Clusters Reveal the Initial Size of Nanoscale Network during Dealloying Via Kinetic Monte Carlo Simulation

As residues of the master alloy that survived corrosion, the silver-rich clusters of nanoporous gold (NPG) fabricated by dealloying affect the functional properties of the material. Also, they are representative of the initial nanoscale network established at the beginning of dealloying. The evolution of silver-rich clusters during dealloying at different potentials is investigated via kinetic Monte Carlo simulations [1]. Our simulations show that the dealloying consists of two characteristic processes: (i) the primary process produces an initial three-dimensional bicontinuous network with silver-rich clusters embedded in the ligaments and pure gold covered on ligaments' surface. See Fig.1(a). (ii) the secondary process coarsens the ligaments and further dissolves silver from the ligaments. See Fig.1(b). The size of silver-rich clusters, L Ag, scales with that of ligaments, L lig, during primary dealloying for all studied potentials (Fig.1(c)). Both sizes decrease with increasing dealloying potential. The trends in size and potential are consistent with a Gibbs-Thompson-type relation (dash-dotted line in Fig.1(c)). Yet, the size of silver clusters remains invariant when the ligament size increases during secondary dealloying. Our simulations reveal that the survived clusters provided a way to measure the initial ligament size.Fig.1. Renderings of slicing the NPG structure at different dealloying time (a-b) and the size evolution during primary dealloying (c) (Ref.[1]): (a) the primary dealloying establishes the initial 3D nanoscale network, (b) the secondary dealloying dissolves Ag clusters and coarsens ligaments, (c) inverse of Ag cluster size, L Ag and of ligament size, L lig, during primary dealloying as a function of dealloying potential, Φ.Reference:[1] Y. Li, B.-N. D. Ngô, J. Markmann, J. Weissmüller. Evolution of length scales and of chemical heterogeneity during primary and secondary dealloying, Acta Materialia, (2021) 117424. Figure 1

(Invited) Tailor-Made Hierarchical Nested-Network Nanoporous Metals By Dealloying

Structural hierarchy is known to optimize functional and mechanical behaviors in deliberately designed structures and natural materials. The benefits of hierarchy implementing the high strength and the high surface-to-volume of nanoscale objects into hierarchical structures would lead to even more interesting mechanical characteristics and more opportunities for interface- or surface-controlled functional applications. This talk focuses on nested network random nanomaterials "hierarchical nanoporous gold" made by two-stage self-organization dealloying processes, which processes allow for large samples contained over trillions of struts to be synthesized. Both the strut size and porosity at each hierarchy level are tuned independently. The strut size can be controlled from 10 nm to 300 nm, and the porosity from 80% to 90%. Compression tests on these hierarchical nanoporous gold materials demonstrated that the structural hierarchy brings enhanced mechanics for truly nanoscale network materials. The experiments are well supported by our proposed scaling laws for the stiffness and strength for nested network with different numbers of hierarchy levels [1].[1] S. Shi, Y. Li, B.-N. Ngo-Dinh, J. Markmann and J. Weissmüller, Scaling behavior of stiffness and strength of hierarchical network nanomaterials, Science 371 (6533), 2021.

Effects of Argon Gas Plasma Treatment on Biocompatibility of Nanostructured Titanium.

In this study, we applied argon plasma treatment to titanium surfaces with nanostructures deposited by concentrated alkali treatment and investigated the effects on the surface of the material and the tissue surrounding an implant site. The results showed that the treatment with argon plasma removed carbon contaminants and increased the surface energy of the material while the nanoscale network structure deposited on the titanium surface remained in place. Reactive oxygen species reduced the oxidative stress of bone marrow cells on the treated titanium surface, creating a favorable environment for cell proliferation. Good results were observed in vitro evaluations using rat bone marrow cells. The group treated with argon plasma exhibited the highest apatite formation in experiments using simulated body fluids. The results of in vivo evaluation using rat femurs revealed that the treatment improved the amount of new bone formation around an implant. Thus, the results demonstrate that argon plasma treatment enhances the ability of nanostructured titanium surfaces to induce hard tissue differentiation and supports new bone formation around an implant site.

La-Al Intermetallic Alloy Anode for Realizing High-Energy Fluoride-Ion Battery

An all-solid-state fluoride-ion battery is one of the promising candidates for the next-generation high-energy batteries owing to the high theoretical energy density. However, the practical capacities of anodes are significantly low compared with cathodes, and therefore it is an urgent task to develop new anode materials for fluoride-ion batteries. Here, we show that the LaAl3 alloy anode delivers a reversible high capacity of 298 mAh g−1 with only 0.66% capacity fading per cycle. By using atomic-resolution scanning transmission electron microscopy combined with electron energy-loss spectroscopy, we investigate the structural and chemical evolution of LaAl3. We find that LaAl3 is firstly decomposed into LaF3 and AlF3 nanocrystals, forming the nanoscale network of the F– ion conduction path owing to the high ionic conductivity of LaF3. In the subsequent cycles, the redox reaction of Al/AlF3 nanocrystals solely proceeds, contributing to the reversible high capacity. Our findings should open new avenues for realizing high-energy fluoride-ion batteries.