Investigating the optical and electrical performance of rod coated silver nanowire-based transparent conducting films.

Silver nanowires (Ag NWs) are highly promising building blocks for developing transparent conducting films (TCFs) due to their high electrical conductivity and good optical transparency. The large-scale production of Ag NW-based high-quality TCFs using low-cost processing methods can replace the traditional oxide based TCFs. Therefore, developing a reliable technique for large-scale fabrication of Ag NW-based TCFs is vital. This work involves the synthesis of Ag NWs, the fabrication of large-area Ag NW-based TCFs using a simple rod coating process, its optimization, and the performance analysis of the fabricated TCFs, including their demonstration as transparent heaters. The polyol synthesis method produces Ag NWs of lengths ranging from 25-110µm and diameters from 80-180 nm. The effect of Ag NW length, the number of coating passes, and the volume of the NW dispersion used per coating pass on the electrical and optical properties of the TCFs are studied by quantifying sheet resistance(Rs)and transmittance (T) of the film. The performance of the fabricated film is evaluated by estimating the figure of merit (FoM) in both percolative and bulk regimes. The TCF made with NWs of length 25.7µm and diameter 85.1 nm had the largest value of bulk FoM (101.3), percolative FoM (43.9), and, conductivity exponent (0.6). This elucidated the superior performance of the fabricated TCFs over those fabricated by other techniques. The critical thickness of the film (tmin), at the crossover between the percolation and bulk, scales with the shortest dimension of the NW, namely its diameter. The percolative FoM showed an increase, with a decrease in both sheet resistance and diameter of the NWs, with lowern. The fabricated TCF is tested as a transparent heater and the demonstration proves that rod coated Ag NW-based TCFs can be used for transparent electrode applications.

A Concept of Local Coordination Number for the Characterization of Solute Clusters within Atom Probe Tomography Data.

Identifying clusters of solute atoms in a matrix of solvent atoms helps to understand precipitation phenomena in alloys, for example, during the age hardening of certain aluminum alloys. Atom probe tomography datasets can deliver such information, provided that appropriate cluster identification routines are available. We investigate algorithms based on the local composition of the neighborhood of solute atoms and compare them with traditional approaches based on the local solute number density, such as the maximum separation distance method. For an ideal solid solution, the pair correlation functions of the kth nearest solute atom in the coordination number representation are derived, and the percolation threshold and the size distribution of clusters are studied. A criterion for selecting optimal control parameters based on maximizing the phase separation by the degree of clustering is proposed for a two-phase system. A map of phase compositions accessible for cluster analysis is constructed. The coordination number approach reduces the influence of density variations commonly observed in atom probe tomography data. Finally, a practical cluster analysis technique applied to the early stages of aluminum alloy aging is described.

Proximal High-Index Metamaterials based on a Superlattice of Gold Nanohexagons Targeting the Near-Infrared Band.

Plasmonic nanoparticles can be assembled into a superlattice, to form optical metamaterials, particularly targeting precise control of optical properties such as refractive index (RI). The superlattices exhibit enhanced near-field, given the sufficiently narrow gap between nanoparticles supporting multiple plasmonic resonance modes only realized in proximal environments. Herein, the planar superlattice of plasmonic Au nanohexagons (AuNHs) with precisely controlled geometries such as size, shape, and edge-gaps is reported. The proximal AuNHs superlattice realized over a large area with selective edge-to-edge assembly exhibited the highest-ever-recorded RI values in the near-infrared (NIR) band, surpassing the upper limit of the RI of the natural intrinsic materials (up to 10.04 at λ = 1.5 µm). The exceptionally enhanced RI is derived from intensified in-plane surface plasmon coupling across the superlattices. Precise control of the edge-gap of neighboring AuNHs systematically tuned the RI as confirmed by numerical analysis based on the plasmonic percolation model. Furthermore, a 1D photonic crystal, composed of alternating layers of AuNHs superlattices and low-index polymers, is constructed to enhance the selectivity of the reflectivity operating in the NIR band. It is expected that the proximal AuNHs superlattices can be used as new optical metamaterials that can be extended to the NIR range.

Molecular Filter Net Synergy with Regulation in Ion Percolation for High-Performance Zn Metal Batteries.

The uncontrollable dendrite growth and complex parasitic reactions of Zn metal anodes cause short cycle lives and low Coulombic efficiency, which seriously affect their applications. To address these issues, this research proposes an efficient ion percolating interface constituted by a hydrogen-bonded organic framework (HND) for a highly stable and reversible Zn anode. The hydrogen-bonded skeleton acts as a molecular filter net, capturing water molecules by forming targeted hydrogen-bonding systems with them, sufficiently inhibiting parasitic reactions. Additionally, the interaction of the rich-N and -O electrochemically active sites with Zn2+ effectively regulates its percolation, which greatly enhances the diffusion kinetics of Zn2+, thus facilitating rapid and uniform migration of Zn2+ at the anode surface. Through the above synergistic effect, dendrite-free anodes with highly reversible Zn plating/stripping behaviors can be achieved. Hence, the modified Zn anode (HND@Zn) performs a steady cycling time of more than 1700 h at 1 mA cm-2. Moreover, the HND@Cu||Zn asymmetric cell exhibits a stable charge/discharge process of over 1600 cycles with an average Coulombic efficiency of up to 99.6% at 5 mA cm-2. This work provides some conceptions for the evolution and application of high-performance Zn metal batteries.

Environmental assessment of alkali-activated materials based on agro-industrial waste as alkaline activators through leaching tests.

Global circular economy drives the development of sustainable alkali activated materials (AAM) for use as construction material from industrial by-products and wastes. The assessment of the potentially hazardous substances release of these new material combinations into the soil and groundwater over time is essential. In this study, the aim is the environmental assessment of three AAMs based on blast furnace slag (BFS), activated with almond shell biomass ash (ABA) as potassium source and three solid sources of silica from the agricultural industry, rice husk ash (RHA), spent diatomaceous earth (SDE) and bamboo leaf ash (BLA), using European horizontal leaching tests proposed for construction materials, for monolithic form, Dynamic Surface Leaching Test (DSLT) and for granular form, Up-flow Percolation Test and the Compliance leaching test, by simulating different scenarios of their entire life cycle. The leaching results of the AAM showed the effectiveness of the inertization of all the recycled materials studied, which exceeded some inert materials limits, by means of the activation process. Despite the absence of significant differences in the leaching mechanisms of the oxyanions As, Cr, Mo, Sb, Se and V between the three AAMs developed, they presented different long-term leaching behavior depending on their form, monolithic, or granular, and therefore in their different life cycle stages. Therefore, it is concluded that although the incorporation of agro-industrial waste as alternative activators in BFS based AAM according to the Dutch Soil Quality Decree (for unrestricted use of monolithic and granular materials) is an environmentally acceptable option, the design of waste derived AAMs should be assessed by means of a combination of leaching tests that cover their expected life cycle.

Distribution and propagation of stress and strain in cube honeycombs as trabecular bone substitutes: Finite element model analysis.

For designing trabecular (Tb) bone substitutes suffering from osteoporosis, finite element model (FEM) simulations were conducted on honeycombs (HCs) of 8 × 8 × 1 (2D) and 8 × 8 × 8 (3D) assemblies of cube cellular units consisting of 0.9 mm long Nylon® 66 (PA, Young's modulus E: 2.83 GPa) and polyethylene (PE, E: 1.1 GPa) right square prisms. Osteoporotic damage to the Tb bone was simulated by removing the inner vertical struts (pillars; the number of removed pillars: Δn ≤ 300) and by thinning the strut (thickness, d: 0.4-0.1 mm), while the six facade lattices were kept flawless. Uniform and uniaxial compressive loads on the HCs induced elastic deformation of the struts. The pillars held almost all the load, while the horizontal struts (beams) shared little. E for PA 3D HCs of all d smoothly decreased with Δn. PA 3D HCs of 0.2 mm struts deserved to be the substitutes for Tb bone, while PE 3D HCs of 0.05 mm struts were only for the Tb bone of the poorest bone quality. For the PA 3D HCs, the maximum von Mises stress (σM) first rapidly increased with Δn and showed a break at Δñ50, then gradually approached the yield stress of PA (50 MPa). Moreover, small portions of the stress were transferred from the façade pillars to the adjacent inner beams, especially those near the lost-pillar sites, denoted as X defects. The floor beams of thinner struts associated with the X-defects were lifted, and similar lifting effects in smaller amounts were propagated to the other floors. The 3DHCs of the thicker struts showed no such flexural deformations. The concept of force percolation through the remaining struts was proposed to interpret those mechanical behaviors of the HCs.

Rigidity percolation and active advection synergize in the actomyosin cortex to drive amoeboid cell motility.

Spontaneous locomotion is a common feature of most metazoan cells, generally attributed to the properties of actomyosin networks. This force-producing machinery has been studied down to the most minute molecular details, especially in lamellipodium-driven migration. Nevertheless, how actomyosin networks work inside contraction-driven amoeboid cells still lacks unifying principles. Here, using stable motile blebs from HeLa cells as a model amoeboid motile system, we imaged the dynamics of the actin cortex at the single filament level and revealed the co-existence of three distinct rheological phases. We introduce "advected percolation," a process where rigidity percolation and active advection synergize, spatially organizing the actin network's mechanical properties into a minimal and generic locomotion mechanism. Expanding from our observations on simplified systems, we speculate that this model could explain, down to the single actin filament level, how amoeboid cells, such as cancer or immune cells, can propel efficiently through complex 3D environments.

Triadic percolation induces dynamical topological patterns in higher-order networks.

Triadic interactions are higher-order interactions which occur when a set of nodes affects the interaction between two other nodes. Examples of triadic interactions are present in the brain when glia modulate the synaptic signals among neuron pairs or when interneuron axo-axonic synapses enable presynaptic inhibition and facilitation, and in ecosystems when one or more species can affect the interaction among two other species. On random graphs, triadic percolation has been recently shown to turn percolation into a fully fledged dynamical process in which the size of the giant component undergoes a route to chaos. However, in many real cases, triadic interactions are local and occur on spatially embedded networks. Here, we show that triadic interactions in spatial networks induce a very complex spatio-temporal modulation of the giant component which gives rise to triadic percolation patterns with significantly different topology. We classify the observed patterns (stripes, octopus, and small clusters) with topological data analysis and we assess their information content (entropy and complexity). Moreover, we illustrate the multistability of the dynamics of the triadic percolation patterns, and we provide a comprehensive phase diagram of the model. These results open new perspectives in percolation as they demonstrate that in presence of spatial triadic interactions, the giant component can acquire a time-varying topology. Hence, this work provides a theoretical framework that can be applied to model realistic scenarios in which the giant component is time dependent as in neuroscience.

Effect of BaTiO3 Filler Modification with Multiwalled Carbon Nanotubes on Electric Properties of Polymer Nanocomposites.

Two ranges of dielectric permittivity (k) increase in polymer composites upon the modification of BaTiO3 filler with multiwalled carbon nanotubes (MWCNTs) are shown for the first time. The first increase in permittivity is observed at low MWCNT content in the composite (approximately 0.07 vol.%) without a considerable increase in dielectric loss tangent and electrical conductivity. This effect is determined by the intensification of filler-polymer interactions caused by the nanotubes, which introduce Brønsted acidic centers on the modified filler surface and thus promote interactions with the cyanoethyl ester of polyvinyl alcohol (CEPVA) polymer binder. Consequently, the structure of the composites becomes more uniform: the permittivity increase is accompanied by a decrease in the lacunarity (nonuniformity) of the structure and an increase in scale invariance, which characterizes the self-similarity of the composite structure. The permittivity of the composites in the first range follows a modified Lichtenecker equation, including the content of Brønsted acidic centers as a parameter. The second permittivity growth range features a drastic increase in the dielectric loss tangent and conductivity corresponding to the percolation effect with the threshold at 0.3 vol.% of MWCNTs.

Double Percolation of Poly(lactic acid)/Low-Density Polyethylene/Carbon Nanotube (PLA/LDPE/CNT) Composites for Force-Sensor Application: Impact of Preferential Localization and Mixing Sequence.

This study explores the enhancement of electrical conductivity in polymer composites by incorporating carbon nanotubes (CNTs) into a co-continuous poly(lactic acid)/low-density polyethylene (PLA/LDPE) blend, creating a double percolation structure. Theoretical thermodynamic predictions indicate that CNTs preferentially localize in the LDPE phase. The percolation threshold of CNTs in the PLA/LDPE/CNT composites was 0.208 vol% (5.56 wt%), an 80% reduction compared to the LDPE/CNT composite, due to the double percolation structure. This thermodynamic migration of CNTs from PLA to LDPE significantly enhanced conductivity, achieving a 13.8-fold increase at a 7.5 wt% CNT loading compared to the LDPE/CNT composite. The localization of CNTs was driven by thermodynamic, kinetic, and rheological factors, with viscosity differences between PLA and LDPE causing dense CNT aggregation in LDPE. Initial contact of CNTs with PLA reduced aggregation, allowing PLA to infiltrate CNT aggregates during melt-mixing, which influenced the final morphology and electrical conductivity. These findings provide new insights into the fabrication of conductive polymer composites for force sensor applications.

Quasi-1D Conductive Network Composites for Ultra-Sensitive Strain Sensing.

Highly performance flexible strain sensor is a crucial component for wearable devices, human-machine interfaces, and e-skins. However, the sensitivity of the strain sensor is highly limited by the strain range for large destruction of the conductive network. Here the quasi-1D conductive network (QCN) is proposed for the design of an ultra-sensitive strain sensor. The orientation of the conductive particles can effectively reduce the number of redundant percolative pathways in the conductive composites. The maximum sensitivity will reach the upper limit when the whole composite remains only "one" percolation pathway. Besides, the QCN structure can also confine the tunnel electron spread through the rigid inclusions which significantly enlarges the strain-resistance effect along the tensile direction. The strain sensor exhibits state-of-art performance including large gauge factor (862227), fast response time (24 ms), good durability (cycled 1000 times), and multi-mechanical sensing ability (compression, bending, shearing, air flow vibration, etc.). Finally, the QCN sensor can be exploited to realize the human-machine interface (HMI) application of acoustic signal recognition (instrument calibration) and spectrum restoration (voice parsing).

A Macroscopic Interpretation of the Correlation between Electrical Percolation and Mechanical Properties of Poly-(Ethylene Vinyl Acetate)/Zn Composites.

Elastic composites were prepared using a procedure involving hot plates and zinc powder that was directly dispersed into an EVA matrix. The correlation between the zinc content and the conductive properties of the material was studied via impedance spectroscopy, the thermal properties of the material were studied via differential calorimetry and the mechanical properties of the composites were studied via tensile strength curves, representing an important advancement in the characterization of this type of composite material. The composites' tensile strength and elongation at break decrease with the addition of filler since zinc particles act as stress-concentrating centres, while the composites' hardness and Young's modulus increase because of an increase in the stiffness of the material. The AC perturbation across the EVA/Zn composites was characterized using an RC parallel equivalent circuit that allowed us to easily measure their resistivity (ρp) and permittivity (εp). The dependence of these electrical magnitudes on the zinc content is correlated with their mechanical properties across the characteristic time constant τp = ρp·Îµp of this equivalent circuit. The dependence of the mechanical and electrical magnitudes on the zinc content is consistent with the formation of percolation clusters. The addition of graphite particles increases their potential performance. Three possible mechanisms for the electrical transport of the ac-perturbation across the EVA/Zn composites have been identified. Chemical corrosion in acid media causes the loss of zinc surface particles, but their bulk physical properties practically remain constant.

Discernible interindividual patterns of global efficiency decline during theoretical brain surgery.

The concept of functional localization within the brain and the associated risk of resecting these areas during removal of infiltrating tumors, such as diffuse gliomas, are well established in neurosurgery. Global efficiency (GE) is a graph theory concept that can be used to simulate connectome disruption following tumor resection. Structural connectivity graphs were created from diffusion tractography obtained from the brains of 80 healthy adults. These graphs were then used to simulate parcellation resection in every gross anatomical region of the cerebrum by identifying every possible combination of adjacent nodes in a graph and then measuring the drop in GE following nodal deletion. Progressive removal of brain parcellations led to patterns of GE decline that were reasonably predictable but had inter-subject differences. Additionally, as expected, there were deletion of some nodes that were worse than others. However, in each lobe examined in every subject, some deletion combinations were worse for GE than removing a greater number of nodes in a different region of the brain. Among certain patients, patterns of common nodes which exhibited worst GE upon removal were identified as "connectotypes". Given some evidence in the literature linking GE to certain aspects of neuro-cognitive abilities, investigating these connectotypes could potentially mitigate the impact of brain surgery on cognition.

Surface Modification of Copper-Based Flakes for Conductive Polymer Composites.

The physical properties as well as thermal and electrical stability of copper particles can be improved by surface protection, which mainly depends on the coating material. Our study was, therefore, focused on the rheological, thermal, mechanical and electrical characterization of polymer composites by comparing uncoated (Cu), silver-coated (Cu@Ag) and silica-coated (Cu@Si) copper flakes in low-density polyethylene at various volume concentrations (up to 40%). Interactions among particles were investigated by rheological properties, as these indicate network formation (geometrical entanglement), which is important for mechanical reinforcement as well as establishing an electric pathway (electrical percolation). The results showed that geometrical and electrical percolation were the same for Cu and Cu@Si, ~15%, while, surprisingly, Cu@Ag exhibited much lower percolation, ~7.5%, indicating the fusion of the Ag coating material, which also decreased crystal growth (degree of crystallinity). Furthermore, the magnitude of the rheological and mechanical response remained the same for all investigated materials, indicating that the coating materials do not provide any load transfer capabilities. However, they profoundly affect electron transfer, in that, Cu@Ag exhibited superior conductivity (74.4 S/m) compared to Cu (1.7 × 10-4 S/m) and Cu@Si (1.5 × 10-10 S/m). The results obtained are important for the design of advanced polymer composites for various applications, particularly in electronics where enhanced electrical conductivity is desired.

Self-inhibiting percolation and viral spreading in epithelial tissue.

SARS-CoV-2 induces delayed type-I/III interferon production, allowing it to escape the early innate immune response. The delay has been attributed to a deficiency in the ability of cells to sense viral replication upon infection, which in turn hampers activation of the antiviral state in bystander cells. Here, we introduce a cellular automaton model to investigate the spatiotemporal spreading of viral infection as a function of virus and host-dependent parameters. The model suggests that the considerable person-to-person heterogeneity in SARS-CoV-2 infections is a consequence of high sensitivity to slight variations in biological parameters near a critical threshold. It further suggests that within-host viral proliferation can be curtailed by the presence of remarkably few cells that are primed for IFN production. Thus, the observed heterogeneity in defense readiness of cells reflects a remarkably cost-efficient strategy for protection.

Investigation on the leaching behavior of natural aggregates using percolation test and total content.

In the construction industry, environmental behavior of aggregates has been monitored thanks to leaching tests, especially for alternative aggregates obtained from waste (e.g., construction and demolition waste, MSWI). Few studies were carried on the leaching behavior of natural aggregates, which are often not regulated for their substance release in most EU member states (as France). Leachable content of some heavy metals, halides, and sulfates on natural aggregates was investigated using up-flow percolation test EN 16637-3 and compared to threshold values. Only three samples (NS2, NG1, and NG8) show one element which exceeded threshold values (As, Zn, As, respectively), among the 19 natural aggregates tested for leaching. In this study, three natural aggregates (NG1, NS1, NS2) have been chosen because of their measurable leaching values. Total content was obtained through acid digestion. Influence of grain size on leaching results was investigated. Predominant release mechanisms were determined using EN 16637-3 - Annex D, based on percolation results such as pH, electrical conductivity, and leached content, and were then discussed. Detailed results for releases of As, Ba, Ni, Zn, SO42-, and F- were investigated. EN 16637-3 - Annex D shows some limits, especially for trace elements. The pH was found to be one of the most important factors influencing leaching release of most elements, being more important than grain size. By comparing total content with released quantities, it has been shown that As and Mo in NS2 are easily leached, hence present in a very soluble chemical form. Determining release mechanisms accurately in this study seems only possible for elements present in significant amounts.

Asymmetric response emerges between creation and disintegration of force-bearing subcellular structures as revealed by percolation analysis.

Cells dynamically remodel their internal structures by modulating the arrangement of actin filaments (AFs). In this process, individual AFs exhibit stochastic behavior without knowing the macroscopic higher-order structures they are meant to create or disintegrate, but the mechanism allowing for such stochastic process-driven remodeling of subcellular structures remains incompletely understood. Here we employ percolation theory to explore how AFs interacting only with neighboring ones without recognizing the overall configuration can nonetheless create a substantial structure referred to as stress fibers (SFs) at particular locations. We determined the interaction probabilities of AFs undergoing cellular tensional homeostasis, a fundamental property maintaining intracellular tension. We showed that the duration required for the creation of SFs is shortened by the increased amount of preexisting actin meshwork, while the disintegration occurs independently of the presence of actin meshwork, suggesting that the coexistence of tension-bearing and non-bearing elements allows cells to promptly transition to new states in accordance with transient environmental changes. The origin of this asymmetry between creation and disintegration, consistently observed in actual cells, is elucidated through a minimal model analysis by examining the intrinsic nature of mechano-signal transmission. Specifically, unlike the symmetric case involving biochemical communication, physical communication to sense environmental changes is facilitated via AFs under tension, while other free AFs dissociated from tension-bearing structures exhibit stochastic behavior. Thus, both the numerical and minimal models demonstrate the essence of intracellular percolation, in which macroscopic asymmetry observed at the cellular level emerges not from microscopic asymmetry in the interaction probabilities of individual molecules, but rather only as a consequence of the manner of the mechano-signal transmission. These results provide novel insights into the role of the mutual interplay between distinct subcellular structures with and without tension-bearing capability. Insight: Cells continuously remodel their internal elements or structural proteins in response to environmental changes. Despite the stochastic behavior of individual structural proteins, which lack awareness of the larger subcellular structures they are meant to create or disintegrate, this self-assembly process somehow occurs to enable adaptation to the environment. Here we demonstrated through percolation simulations and minimal model analyses that there is an asymmetry in the response between the creation and disintegration of subcellular structures, which can aid environmental adaptation. This asymmetry inherently arises from the nature of mechano-signal transmission through structural proteins, namely tension-mediated information exchange within cells, despite the stochastic behavior of individual proteins lacking asymmetric characters in themselves.

Comparing the Clique Percolation algorithm to other overlapping community detection algorithms in psychological networks: A Monte Carlo simulation study.

In psychological networks, one limitation of the most used community detection algorithms is that they can only assign each node (symptom) to a unique community, without being able to identify overlapping symptoms. The clique percolation (CP) is an algorithm that identifies overlapping symptoms but its performance has not been evaluated in psychological networks. In this study, we compare the CP with model parameters chosen based on fuzzy modularity (CPMod) with two other alternatives, the ratio of the two largest communities (CPRat), and entropy (CPEnt). We evaluate their performance to: (1) identify the correct number of latent factors (i.e., communities); and (2) identify the observed variables with substantive (and equally sized) cross-loadings (i.e., overlapping symptoms). We carried out simulations under 972 conditions (3x2x2x3x3x3x3): (1) data categories (continuous, polytomous and dichotomous); (2) number of factors (two and four); (3) number of observed variables per factor (four and eight); (4) factor correlations (0.0, 0.5, and 0.7); (5) size of primary factor loadings (0.40, 0.55, and 0.70); (6) proportion of observed variables with substantive cross-loadings (0.0%, 12.5%, and 25.0%); and (7) sample size (300, 500, and 1000). Performance was evaluated through the Omega index, Mean Bias Error (MBE), Mean Absolute Error (MAE), sensitivity, specificity, and mean number of isolated nodes. We also evaluated two other methods, Exploratory Factor Analysis and the Walktrap algorithm modified to consider overlap (EFA-Ov and Walk-Ov, respectively). The Walk-Ov displayed the best performance across most conditions and is the recommended option to identify communities with overlapping symptoms in psychological networks.

In-vivo blood pressure sensing with bi-filler nanocomposite.

Conductive elastomers present desirable qualities for sensing pressure in-vivo, such as high piezoresistance in tiny volumes, conformability and, biocompatibility. Many electrically conductive nanocomposites however, are susceptible to electrical drift following repeated stress cycles and chemical aging. Here we propose an innovative approach to stabilize nanocomposite percolation network against incomplete recovery to improve reproducibility and facilitate sensor calibration. We decouple the tunnelling-percolation network of highly-oriented pyrolytic graphite (HOPG) nanoparticles from the incomplete viscoelastic recovery of the polydimethylsiloxane (PDMS) matrix by inserting minute amounts of insulating SiO2 nanospheres. SiO2 nanospheres effectively reduce the number of nearest neighbours at each percolation node switching off the parallel electrical pathways that might become activated under incomplete viscoelastic relaxation. We varied the size of SiO2 nanospheres and their filling fraction to demonstrate nearly complete piezoresistance recovery when SiO2 and HOPG nanoparticles have equal diameters (≈400 nm) and SiO2 and HOPG volume fractions are 1 % and 29.5 % respectively. We demonstrate an in-vivo blood pressure sensor based on this bi-filler composite.

Specific surface area of mannitol rather than particle size dominant the dissolution rate of poorly water-soluble drug tablets: A study of binary mixture.

The dissolution behavior of tablets, particularly those containing poorly water-soluble drugs, is a critical factor in determining their absorption and therapeutic efficacy. Traditionally, the particle size of excipients has been considered a key property affecting tablet dissolution. However, lurasidone hydrochloride (LH) tablets prepared by similar particle size mannitol, namely M200 (D90 = 209.68 ± 1.42 µm) and 160C (D90 = 195.38 ± 6.87 µm), exhibiting significant differences in their dissolution behavior. In order to find the fundamental influential factors of mannitol influencing the dissolution of LH tablets, the properties (particle size, water content, true density, bulk density, tapped density, specific surface area, circularity, surface free energy, mechanical properties and flowability) of five grades mannitol including M200 and 160C were investigated. Principal component analysis (PCA) was used to establish a relationship between mannitol properties and the dissolution behavior of LH. The results demonstrated that specific surface area (SSA) emerged as the key property influencing the dissolution of LH tablets. Moreover, our investigation based on the percolation theory provided further insights that the SSA of mannitol influences the probability of LH-LH bonding and LH infinite cluster formation, resulting in the different percolation threshold states, then led to different dissolution behaviors. Importantly, it is worth noting that these findings do not invalidate previous conclusions, as reducing particle size generally increases SSA, thereby affecting the percolation threshold and dissolution behavior of LH. Instead, this study provides a deeper understanding of the underlying role played by excipient SSA in the dissolution of drug tablets. This study provides valuable guidance for the development of novel excipients aimed at improving drug dissolution functionality.