Nanoparticle Networks Research Articles

Deformation induced evolution of plasmonic responses in polymer grafted nanoparticle thin films.

Multi-functional nanoparticle thin films are being used in various applications ranging from biosensing to photo-voltaics. In this study, we integrate two different numerical approaches to understand the interplay between the mechanical deformation and optical response of polymer grafted plasmonic nanoparticle (PGPN) arrays. Using numerical simulations we examine the deformation of thin films formed by end-functionalised polymer grafted nanoparticles subject to uniaxial elongation. The induced deformation causes the particles in the thin film network to rearrange their positions by two different mechanisms viz. sliding and packing. In sliding, the particles move in the direction of induced deformation. On the other hand, in packing, the particles move in a direction normal to that of the induced deformation. By employing a Green's tensor formulation in polarizable backgrounds for evaluating the optical response of the nanoparticle network, we calculate the evolution of the plasmonic response of the structure as a function of strain. The results indicate that the evolution of plasmonic response closely follows the deformation. In particular, we show that the onset of relative electric field enhancement of the optical response occurs when there is significant rearrangement of the constituent PGPNs in the array. Furthermore, we show that depending on the local packing/sliding and the polarization of the incident light there can be both enhancement and suppression of the SERS response.

In-operando FTIR study of ligand-linked Pt nanoparticle networks employed as catalysts in hydrogen gas micro sensors.

Microporous networks of Pt nanoparticles (NP) interlinked by aromatic diamines have recently shown prospects of application as hydrogen combustion catalysts in H2 gas microsensors. In particular with respect to long-term sensor performance, they outperformed plain Pt NP as catalysts. In this paper, electron microscopy and Fourier transform infrared (FTIR) spectroscopy data on the stability of p-phenylene diamine (PDA) and of the PDA-linked Pt NP network structure during catalyst activation and long-term sensor operation at elevated temperature (up to 120-180 °C) will be presented. For the first time, all data were collected directly from microsensor catalysts, and FTIR was performed in operando, i.e., during activation and sensor operation. While the data confirm high long-term catalyst activity far superior to that of plain Pt NP over 5 days of testing, they reveal that PDA fully decomposed during long-term sensor operation and that the network of discrete Pt nanoparticles changed to a sponge-like Pt nanostructure already during catalyst activation. These findings are at variance with previous work which assumed that stability of the PDA-linked Pt NP network is prerequisite for catalyst stability and performance.

“Interface localization of reduced graphene oxide in polystyrene/polymethyl methacrylate blends with co-continuous morphology: Investigating the effects of polymer interface on nanoparticle network stabilization”

This study aimed to investigate the co-continuous morphology of polymer blends and determine whether nanoparticles can be localized at the interface of polymers to create a well-organized network and decrease the percolation threshold. The researchers chose solution-mixed polystyrene (PS)/polymethyl methacrylate (PMMA) blends containing reduced graphene oxide (rGO) for analysis of their rheological, electrical, dynamic-mechanic properties, topography, and morphology. Graphene oxide in varying degrees of thermal reduction was prepared, and surface tension measurements were used to detect the range at which the particles tend to reside at the interface. Based on electrical characterization, it was determined that the required amount of rGO to cover the total polymer interface in the co-continuous blend is approximately 0.1 wt% on a volume basis. The rheology time sweep revealed that, while the initial storage modulus of the nanocomposite containing interface-located particles is similar to that of the sample with randomly distributed particles, the increase in storage modulus over time is less steep, resulting in a lower final value. These findings confirm that the flocculation of rGO particles decreases when they are located at the interface.

Rapid laser fabrication of indium tin oxide and polymer-derived ceramic composite thin films for high-temperature sensors

Thin-film sensors are essential for real-time monitoring of components in high-temperature environments. Traditional fabrication methods often involve complicated fabrication steps or require prolonged high-temperature annealing, limiting their practical applicability. Here, we present an approach using direct ink writing and laser scanning (DIW-LS) to fabricate high-temperature functional thin films. An indium tin oxide (ITO)/preceramic polymer (PP) ink suitable for DIW was developed. Under LS, the ITO/PP thin film shrank in volume. Meanwhile, the rapid pyrolysis of PP into amorphous precursor-derived ceramic (PDC) facilitated the faster sintering of ITO nanoparticles and improved the densification of the thin film. This process realized the formation of a conductive network of interconnected ITO nanoparticles. The results show that the ITO/PDC thin film exhibits excellent stability, with a drift rate of 4.7 % at 1000 °C for 25 h, and withstands temperatures up to 1250 °C in the ambient atmosphere. It is also sensitive to strain, with a maximum gauge factor of −6.0. As a proof of concept, we have used DIW-LS technology to fabricate a thin-film heat flux sensor on the surface of the turbine blade, capable of measuring heat flux densities over 1 MW/m2. This DIW-LS process provides a viable approach for the integrated, rapid, and flexible fabrication of thin film sensors for harsh environments.

Resistive Switching Effect in Ag‐poly(ethylene Glycol) Nanofluids: Novel Avenue Toward Neuromorphic Materials

AbstractConventional computation techniques face challenges of deviations in Moore's law and the high‐power consumption of data‐centric computation tasks. Neuromorphic engineering attempts to overcome these issues by taking inspiration from neuron assemblies, ranging from distributed synaptic plasticity through orchestration of oscillator‐like action potential toward avalanche dynamics. Although solid networks of nanoparticles (NPs) are proven to replicate fingerprints of criticality and brain‐like dynamics, the aspect of dynamic spatial reconfigurations in the connectivity of networks remains unexplored. In this work, Ag/poly(ethylene glycol) (PEG) nanofluids are demonstrated as potential systems to mimic the spatio‐temporal reconfiguration of network connections. The nanofluids are prepared by directly loading Ag NPs from the gas aggregation cluster source into liquid PEG. The NPs exhibit a negative zeta potential in PEG; if the potential difference is applied between two electrodes submerged in this nanofluid, the NPs migrate toward the anode, accumulate in its vicinity, and form a conductive path. Spikes of electric current passing through the path are detected, accompanied by resistive switching phenomena, similar to the random switching dynamics in solid NPs networks. The unique behavior of Ag/PEG nanofluids makes them promising for the realization of spatio‐temporal reconfigurations in network topologies with the potential to transition to 3D.

Computation via Neuron-like Spiking in Percolating Networks of Nanoparticles.

The biological brain is a highly efficient computational system in which information processing is performed via electrical spikes. Neuromorphic computing systems that work on similar principles could support the development of the next generation of artificial intelligence and, in particular, enable low-power edge computing. Percolating networks of nanoparticles (PNNs) have previously been shown to exhibit critical spiking behavior, with promise for highly efficient natural computation. Here we employ a rate coding scheme to show that PNNs can perform Boolean operations and image classification. Near perfect accuracy is achieved in both tasks by manipulating the spiking activity using certain control voltages. We demonstrate that the key to successful computation is that nanoscale tunnel gaps within the percolating networks transform input data through a powerful modulus-like nonlinearity. These results provide a basis for implementation of further computational schemes that exploit the brain-like criticality of these networks.

Enhanced Mitochondrial Targeting and Inhibition of Pyroptosis with Multifunctional Metallopolyphenol Nanoparticles in Intervertebral Disc Degeneration.

Intervertebral disc degeneration (IVDD) is a significant contributor to low back pain, characterized by excessive reactive oxygen species generation and inflammation-induced pyroptosis. Unfortunately, there are currently no specific molecules or materials available to effectively delay IVDD. This study develops a multifunctional full name of PG@Cu nanoparticle network (PG@Cu). A designed pentapeptide, bonded on PG@Cu nanoparticles via a Schiff base bond, imparts multifunctionality to the metal polyphenol particles (PG@Cu-FP). PG@Cu-FP exhibits enhanced escape from lysosomal capture, enabling efficient targeting of mitochondria to scavenge excess reactive oxygen species. The scavenging activity against reactive oxygen species originates from the polyphenol-based structures within the nanoparticles. Furthermore, Pyroptosis is effectively blocked by inhibiting Gasdermin mediated pore formation and membrane rupture. PG@Cu-FP successfully reduces the activation of the nucleotide-binding oligomerization domain-like receptor family pyrin domain-containing 3 inflammasome by inhibiting Gasdermin protein family (Gasdermin D, GSDMD) oligomerization, leading to reduced expression of Nod-like receptors. This multifaceted approach demonstrates higher efficiency in inhibiting Pyroptosis. Experimental results confirm that PG@Cu-FP preserves disc height, retains water content, and preserves tissue structure. These findings highlight the potential of PG@Cu-FP in improving IVDD and provide novel insights for future research in IVDD treatments.

Heat Transfer Enhancement in Tree-Structured Polymer Linked Gold Nanoparticle Networks.

Human brains use a tree-like neuron network for information processing at high efficiency and low energy consumption. Tree-like structures have also been engineered to enhance mass and heat transfer in various applications. In this work, we reveal the heat transfer mechanism in tree-structured polymer linked gold nanoparticle (AuNP) networks using atomistic simulations. We report both upward and downward heat fluxes between root and leaf nodes in tree-structured polyethylene (PE) and poly(p-phenylene) (PPP) linked AuNP networks at tree levels from 1 to 5. We found that the heat conductance increases with an increasing polymer tree level. The heat transfer enhancement is due to the resulting increase in the low-frequency vibrational modes. This and other thermal properties are affected by the location of the AuNPs in the tree. Moreover, complex tree structures with at least five levels were found to be robust in the sense that disabling half of the leaves did not change the overall heat conductance.

Influence of mechanical vibration actions on the memory effect of PDLC films doped with SiO<sub>2</sub> nanoparticles

The effect of mechanical vibration in the frequency range from 200 Hz to 2500 Hz on the memory effect in 5CB polymer dispersed liquid crystals doped with SiO2 nanoparticles has been studied. As a result of capacitance-voltage measurements, the dependences of the dielectric properties of liquid crystal cells with 0.1 wt% SiO2 on the bias voltage. It has been established that the memory effect detected by dielectric hysteresis in polymer dispersed liquid crystals with silicon dioxide nanoparticles monotonically decreases with increasing oscillation frequency and completely disappears at a frequency of 2000 Hz due to the destruction of the network of silica nanoparticles and, respectively, the appearance of an isotropic orientation liquid crystals molecules.

Extrusion 3D printing of carbon nanotube-assembled carbon aerogel nanocomposites with high electrical conductivity

Carbon nanotubes (CNTs) with high aspect ratio and excellent electrical conduction offer huge functional improvements for current carbon aerogels. However, there remains a major challenge for achieving the on-demand shaping of carbon aerogels with tailored micro-nano structural textures and geometric features. Herein, a facile extrusion 3D printing strategy has been proposed for fabricating CNT-assembled carbon (CNT/C) aerogel nanocomposites through the extrusion printing of pseudoplastic carbomer-based inks, in which the stable dispersion of CNT nanofibers has been achieved relying on the high viscosity of carbomer microgels. After extrusion printing, the chemical solidification through polymerizing RF sols enables 3D-printed aerogel nanocomposites to display high shape fidelity in macroscopic geometries. Benefiting from the micro-nano scale assembly of CNT nanofiber networks and carbon nanoparticle networks in composite phases, 3D-printed CNT/C aerogels exhibit enhanced mechanical strength (fracture strength, 0.79 ​MPa) and typical porous structure characteristics, including low density (0.220 ​g ​cm−3), high surface area (298.4 ​m2 ​g−1), and concentrated pore diameter distribution (∼32.8 ​nm). More importantly, CNT nanofibers provide an efficient electron transport pathway, imparting 3D-printed CNT/C aerogel composites with a high electrical conductivity of 1.49 ​S ​cm−1. Our work would offer feasible guidelines for the design and fabrication of shape-dominated functional materials by additive manufacturing.

Liquid Metal Interface for Two-Precursor Autogenous Deposition of Metal Telluride-Tellurium Networks.

Liquid metal-electrolyte can offer electrochemically reducing interfaces for the self-deposition of low-dimensional nanomaterials. We show that implementing such interfaces from multiprecursors is a promising pathway for achieving nanostructured films with combinatory properties and functionalities. Here, we explored the liquid metal-driven interfacial growth of metal tellurides using eutectic gallium-indium (EGaIn) as the liquid metal and the cation pairs Ag+-HTeO2+ and Cu2+-HTeO2+ as the precursors. At the EGaIn-electrolyte interface, the precursors were reduced and self-deposited autogenously to form interconnected nanoparticle networks. The deposited materials consisted of metal telluride and tellurium with their relative abundance depending on the metal ion type (Ag+ and Cu2+) and the metal-to-tellurium ion ratios. When used as electrode modifiers, the synthesized materials increased the electroactive surface area of unmodified electrodes by over 10 times and demonstrated remarkable activity for model electrochemical reactions, including HexRu(III) responses and dopamine sensing. Our work reveals the promising potential of the liquid metal-templated deposition method for synthesizing complex material systems for electrochemical applications.

Reversible Change in Performances of Polymer Networks via Invertible Architecture-Transformation of Cross-Links.

A polymer nanoparticle network using single-chain nanoparticles (SCNPs) as cross-links is designed. The experimental and theoretical study shows that incorporating SCNPs in polymer networks leads to smaller mesh size, faster terminal relaxation time, and reduced fluctuation among cross-links, resulting in a significant increase in shear storage modulus, and enhancement in tensile stress. Notably, the reversible single-chain collapse of SCNPs under thermal stimulation enables the polymer network to undergo coherent changes between two topological states, thereby exhibiting reversible transformations between soft and stiff states. This approach and finding can effectively tailor the mechanical properties of polymer networks, potentially leading to the development of intelligent, responsive materials.

Brainlike Networks of Nanowires and Nanoparticles: A Change of Perspective

Brainlike Networks of Nanowires and Nanoparticles: A Change of Perspective

Electrohydrodynamic Printed Ultra-Micro AgNPs Thin Film Temperature Sensors Array for High-Resolution Sensing.

Current methods for thin film sensors preparation include screen printing, inkjet printing, and MEMS (microelectromechanical systems) techniques. However, their limitations in achieving sub-10 μm line widths hinder high-density sensors array fabrication. Electrohydrodynamic (EHD) printing is a promising alternative due to its ability to print multiple materials and multilayer structures with patterned films less than 10 μm width. In this paper, we innovatively proposed a method using only EHD printing to prepare ultra-micro thin film temperature sensors array. The sensitive layer of the four sensors was compactly integrated within an area measuring 450 μm × 450 μm, featuring a line width of less than 10 μm, and a film thickness ranging from 150 nm to 230 nm. The conductive network of silver nanoparticles exhibited a porosity of 0.86%. After a 17 h temperature-resistance test, significant differences in the performance of the four sensors were observed. Sensor 3 showcased relatively superior performance, boasting a fitted linearity of 0.99994 and a TCR of 937.8 ppm/°C within the temperature range of 20 °C to 120 °C. Moreover, after the 17 h test, a resistance change rate of 0.17% was recorded at 20 °C.

Capillary‐Driven Self‐Assembled Microclusters for Highly Performing UV Photodetectors

AbstractSelf‐assembled nanoparticle networks have emerged as multifunctional building blocks for a new generation of highly sensitive sensing technologies that offer large surface‐to‐volume ratios and a range of associated benefits. Unfortunately, with nanoparticle networks often being held together by weak van der Waals forces, the development of useful commercial devices is slowed by the relatively low robustness and poor carrier transport characteristics. This study shows how the application of a single droplet of ethanol can induce capillary forces capability of delivering significant changes to the morphological, structural, optical, and electronic properties of ZnO nanoclusters. It demonstrates how ZnO nanocluster “dendrites” and nanoparticles are forced together to form micro‐scale islands and larger nanoparticles, and thereby improve the robustness of the layers and the quality of the junctions between the nanoparticles without significantly reducing the overall porosity of the layer or degrading the structural or optical properties in any way. The commensurate improvement in the electronic transport within the layers is found to greatly improve the photoresponse of UV detectors. It seems likely that the application of ethanol and the exploitation of capillary force can provide a technique that can greatly benefit any nanostructured, ultra‐porous device where poor charge transport currently limits performance.

Inorganic-Organic Double Network Ionogels Based on Silica Nanoparticles for High-Temperature Flexible Supercapacitors.

Herein, we demonstrate an inorganic-organic double network gel electrolyte consisting of a silica particle network and a poly-2-hydroxyethyl methacrylate network in which 1-butyl-3-methylimidazolium tetrafluoroborate ionic liquids are confined. The as-synthesized double network ionogel electrolytes exhibited high ion conductivity of 3.8 to 12.8 mS cm-1 over a wide temperature range of 30 to 150 °C and mechanical integrity with a maximum toughness of 1.8 MJ m-3 at 30 °C. These remarkable properties of the ionogel were associated with the formation of an optimal physical network of the silica nanoparticles in the colloidal dispersion. Accordingly, a flexible supercapacitor using ionogel electrolytes and reduced graphene oxide electrodes delivered energy and power densities of 48 Wh kg-1 and 4 kW kg-1, respectively, even at a high temperature of 120 °C, demonstrating excellent long-term stability that retains 93% of the initial capacitance even over 10,000 charge/discharge cycles at 120 °C.

Redox Homeostasis Disruptors Based on Metal-Phenolic Network Nanoparticles for Chemo/Chemodynamic Synergistic Tumor Therapy through Activating Apoptosis and Cuproptosis.

The combination of chemo/chemodynamic therapy is a promising strategy for improving antitumor efficacy. Herein, metal-phenolic network nanoparticles (NPs) self-assembled from copper ions and gallic acid (Cu-GA) are developed to evoke apoptosis and cuproptosis for synergistic chemo/chemodynamic therapy. The Cu-GA NPs are biodegraded in response to the highly expressed glutathione (GSH) in tumor cells, resulting in the simultaneous release of Cu+ and GA. The intracellular GSH content is dramatically reduced by the released GA, rendering the tumor cells incapable of scavenging reactive oxygen species (ROS) and more susceptible to cuproptosis. Meanwhile, ROS levels within the tumor cells are significantly increased by the Fenton-like reaction of released Cu+ , which disrupts redox homeostasis and achieves apoptosis-related chemodynamic therapy. Moreover, massive accumulation of Cu+ in the tumor cells further induces aggregation of lipoylated dihydrolipoamide S-acetyltransferase and downregulation of iron-sulfur cluster protein, activating cuproptosis to enhance the antitumor efficacy of Cu-GA NPs. The experiments in vivo further demonstrate that Cu-GA NPs exhibited the excellent biosafety and superior antitumor capacity, which can efficiently inhibit the growth of tumors due to the activation by the tumor specific GSH and hydrogen peroxide. TheseCu-based metal-phenolic network NPs provide a potential strategy to build up efficient and safe cancer therapy.

Hierarchical Synergistic Structure for High Resolution Strain Sensor with Wide Working Range.

Strain sensors have been attracting tremendous attention for the promising application of wearable devices in recent years. However, the trade-off between high resolution, high sensitivity, and broad detection range is a great challenge for the application of strain sensors. Herein, a novel design of hierarchical synergistic structure (HSS) of Au micro cracks and carbon black (CB) nanoparticles is reported to overcome this challenge. The strain sensor based on the designed HSS exhibit high sensitivity (GF>2400), high strain resolution (0.2%) even under large loading strain, broad detection range (>40%), outstanding stability (>12000 cycles), and fast response speed simultaneously. Further, the experiments and simulation results demonstrate that the carbon black layer greatly changed the morphology of Au micro-cracks, forming a hierarchical structure of micro-scale Au cracks and nano-scale carbon black particles, thus enabling synergistic effect and the double conductive network of Au micro-cracks and CB nanoparticles. Based on the excellent performance, the sensor is successfully applied to monitoring tiny signals of the carotid pulse during body movement, which illustrates the great potential in the application of health monitoring, human-machine interface, human motion detection, and electronic skin.

On the Importance of Nanoparticle Necks and Carbon Impurities for Charge Trapping in TiO2.

Particle attachment and neck formation inside TiO2 nanoparticle networks determine materials performance in sensing, photo-electrochemistry, and catalysis. Nanoparticle necks can feature point defects with potential impact on the separation and recombination of photogenerated charges. Here, we investigated with electron paramagnetic resonance a point defect that traps electrons and predominantly forms in aggregated TiO2 nanoparticle systems. The associated paramagnetic center resonates in the g factor range between g = 2.0018 and 2.0028. Structure characterization and electron paramagnetic resonance data suggest that during materials processing, the paramagnetic electron center accumulates in the region of nanoparticle necks, where O2 adsorption and condensation can occur at cryogenic temperatures. Complementary density functional theory calculations reveal that residual carbon atoms, which potentially originate from synthesis, can substitute oxygen ions in the anionic sublattice, where they trap one or two electrons that mainly localize at the carbon. Their emergence upon particle neck formation is explained by the synthesis- and/or processing-induced particle attachment and aggregation facilitating carbon atom incorporation into the lattice. This study represents a substantial advance in linking dopants, point defects, and their spectroscopic fingerprints to microstructural features of oxide nanomaterials.

Enhanced rheological and tribological properties of nanoenhanced greases by tuning interparticle contacts

HypothesisDespite the wide spectrum of available nanoparticles, their utilization in lubricant and grease formulations remains challenging. To enhance their performance, an improved link between the interparticle contacts, brittleness of the resulting particle network, time-dependent rheology and tribology is required. ExperimentsWe systematically changed interparticle contacts and examined their effect on the colloidal stability, microstructure, rheological and tribological behavior of model greases by investigating four types of nanoclays: montmorillonite (Cloisite Na+), oleic-acid functionalized Cloisite Na+ (OA-Cloisite Na+), organomodified montmorillonite (C20A) and oleic-acid functionalized C20A (C20A-OA). FindingsWe observed a range of behaviors, starting from the lack of colloidal stability in greases derived with Cloisite Na+ and OA-Cloisite Na+ to semi-solid type systems with C20A and C20A-OA. Consistent with previous studies, the rheological and tribological properties of C20A systems scale with nanoclay loadings. Surprisingly, the functionalized C20A-OA system exhibited a delayed transition towards hydrodynamic lubrication, and enhanced lubrication properties, both of which were largely independent of nanoclay loadings. Coupled microstructural investigation and time-dependent rheology reveal that this behavior is governed by increasing repulsive forces, decreasing inter-particle friction between C20A-OA nanoparticles, and faster reorganization of the C20A-OA nanoparticle network under shear. Increased interparticle repulsion enables C20A-OA nanoclays to pass each other under shear and align in direction of shear, which reduces the overall viscosity, while the presence of OA on nanoclays decreases inter-particle friction and particle-steel surface friction.