Stable Multicomponent Multiphase All Active Material Lithium-Ion Battery Anodes

Due to their high energy density, lithium-ion batteries have been the state-of-the-art energy storage technology for many applications. Energy density can be further improved by engineering of the electrode architecture and microstructure, in addition to more common improvements via materials chemistry. All active material (AAM) electrodes consist of only the electroactive material that stores energy, and such electrodes have advantages to conventional composite processing with regards to improved mechanical stability at increased thicknesses and ion transport properties. However, the absence of binders and composite processing makes the electrode more vulnerable to electroactive materials with volume change upon cycling. Also, the electroactive material must have sufficient electronic conductivity to avoid large matrix electronic overpotentials during electrochemical cycling. TiNb₂O₇ (TNO) and MoO₂ (MO) are electroactive materials with potential advantages as AAM electrodes due to relatively high volumetric energy density. TNO has higher energy density, and MO has much higher electronic conductivity, and thus a multicomponent blend of these materials was evaluated as an AAM anode. Herein, blends of TNO and MO as AAM anodes were investigated, where this is the first use of a multicomponent AAM anode. Electrodes that had both TNO and MO had the highest volumetric energy density, rate capability, and cycle life relative to single component TNO and MO anodes. Thus, using multicomponent materials provides a route to improve AAM electrochemical systems.

Self-Organized Memristive Ensembles of Nanoparticles Below the Percolation Threshold: Switching Dynamics and Phase Field Description

Percolative memristive networks based on self-organized ensembles of silver and gold nanoparticles are synthesized and investigated. Using cyclic voltammetry, pulse and step voltage excitations, we study switching between memristive and capacitive states below the percolation threshold. The resulting systems demonstrate scale-free (self-similar) temporal dynamics, long-term correlations, and synaptic plasticity. The observed plasticity can be manipulated in a controlled manner. The simplified stochastic model of resistance dynamics in memristive networks is testified. A phase field model based on the Cahn-Hilliard and Ginzburg-Landau equations is proposed to describe the dynamics of a self-organized network during the dissolution of filaments.

The spread of infectious diseases from a physics perspective

This article deals with the spread of infectious diseases from a physics perspective. It considers a population as a network of nodes representing the population members, linked by network edges representing the (social) contacts of the individual population members. Infections spread along these edges from one node (member) to another. This article presents a novel, modified version of the SIR compartmental model, able to account for typical network effects and percolation phenomena. The model is successfully tested against the results of simulations based on Monte-Carlo methods. Expressions for the (basic) reproduction numbers in terms of the model parameters are presented, and justify some mild criticisms on the widely spread interpretation of reproduction numbers as being the number of secondary infections due to a single active infection. Throughout the article, special emphasis is laid on understanding, and on the interpretation of phenomena in terms of concepts borrowed from condensed-matter and statistical physics, which reveals some interesting analogies. Percolation effects are of particular interest in this respect and they are the subject of a detailed investigation. The concept of herd immunity (its definition and nature) is intensively dealt with as well, also in the context of large-scale vaccination campaigns and waning immunity. This article elucidates how the onset of herd-immunity can be considered as a second-order phase transition in which percolation effects play a crucial role, thus corroborating, in a more pictorial/intuitive way, earlier viewpoints on this matter. An exact criterium for the most relevant form of herd-immunity to occur can be derived in terms of the model parameters. The analyses presented in this article provide insight in how various measures to prevent an epidemic spread of an infection work, how they can be optimized and what potentially deceptive issues have to be considered when such measures are either implemented or scaled down.

Criticality and Neuromorphic Sensing in a Single Memristor

Resistive random access memory (RRAM) is an important technology for both data storage and neuromorphic computation, where the dynamics of nanoscale conductive filaments lies at the core of the technology. Here, we analyze the current noise of various silicon-based memristors that involves the creation of a percolation path at the intermediate phase of filament growth. Remarkably, we find that these atomic switching events follow scale-free avalanche dynamics with exponents satisfying the criteria for criticality. We further prove that the switching dynamics are universal and show little dependence on device sizes or material features. Utilizing criticality in memristors, we simulate the functionality of hair cells in auditory sensory systems by observing the frequency selectivity of input stimuli with tunable characteristic frequency. We further demonstrate a single-memristor-based sensing primitive for representation of input stimuli that exceeds the theoretical limits dictated by the Nyquist-Shannon theorem.

Computational Study on Filament Growth Dynamics in Microstructure-Controlled Storage Media of Resistive Switching Memories

The filament growth processes, crucial to the performance of nanodevices like resistive switching memories, have been widely investigated to realize the device optimization. With the combination of kinetic Monte Carlo (KMC) simulations and the restrictive percolation model, three different growth modes in electrochemical metallization (ECM) cells were dynamically reproduced, and an important parameter, the relative nucleation distance, was theoretically defined to measure different growth modes quantitatively; hence their transition can be well described. In our KMC simulations, the inhomogeneity of storage medium is realized through introducing evolutionary void versus non-void sites within it to mimic the real nucleation during filament growth. Finally, the renormalization group method was used in the percolation model to analytically illustrate void-concentration-dependent growth mode transition, fitting KMC simulation results quite well. Our study found that the nanostructure of the medium can dominate the filament growth dynamics, as the simulation images as well as the analytical results are consistent with experiments results. Our study spotlights a vital and intrinsic factor, void concentration (relative to defects, grains, or nanopores) of a storage medium, in inducing filament growth mode transition within ECM cells. This theoretically proves a mechanism to tune performance of ECM systems that controlling microstructures of the storage media can dominate the filament growth dynamics, indicating an accessible strategy, nanostructure processing, for device optimization of ECM memristors.

Possible new phase transition in the 3D Ising model associated with boundary percolation

In the ordered phase of the 3D Ising model, minority spin clusters are surrounded by a boundary of dual plaquettes. As the temperature is raised, these spin clusters become more numerous, and it is found that eventually their boundaries undergo a percolation transition when about 13% of spins are minority. Boundary percolation differs from the more commonly studied site and link percolation, although it is related to an unusual type of site percolation that includes next to nearest neighbor relationships. Because the Ising model can be reformulated in terms of the domain boundaries alone, there is reason to believe boundary percolation should be relevant here. A symmetry-breaking order parameter is found in the dual theory, the 3D gauge Ising model. It is seen to undergo a phase transition at a coupling close to that predicted by duality from the boundary percolation. This transition lies in the disordered phase of the gauge theory and has the nature of a spin-glass transition. Its critical exponentν∼1.3is seen to match the finite-size shift exponent of the percolation transition further cementing their connection. This predicts a very weak specific heat singularity with exponentα∼-1.9. The third energy cumulant fits well to the expected non-infinite critical behavior in a manner consistent with both the predicted exponent and critical point, indicating a true thermal phase transition. Unlike random boundary percolation, the Ising boundary percolation has two differentνexponents, one associated with largest-cluster scaling and the other with finite-size transition-point shift. This suggests there may be two different correlation lengths present.

Sorption-Deformation-Percolation Model for Diffusion in Nanoporous Media

Diffusion of molecules in porous media is a critical process that is fundamental to numerous chemical, physical, and biological applications. The prevailing theoretical frameworks are challenged when explaining the complex dynamics resulting from the highly tortuous host structure and strong guest-host interactions, especially when the pore size approximates the size of diffusing molecule. This study, using molecular dynamics, formulates a semiempirical model based on theoretical considerations and factorization that offer an alternative view of diffusion and its link with the structure and behavior (sorption and deformation) of material. By analyzing the intermittent dynamics of water, microscopic self-diffusion coefficients are predicted. The apparent tortuosity, defined as the ratio of the bulk to the confined self-diffusion coefficients, is found to depend quantitatively on a limited set of material parameters: heat of adsorption, elastic modulus, and percolation probability, all of which are experimentally accessible. The proposed sorption-deformation-percolation model provides guidance on the understanding and fine-tuning of diffusion.

Rational Design of Ti3C2Tx MXene Inks for Conductive, Transparent Films

Transparent conductive electrodes (TCEs) with a high figure of merit (FOM_e, defined as the ratio of transmittance to sheet resistance) are crucial for transparent electronic devices, such as touch screens, micro-supercapacitors, and transparent antennas. Two-dimensional (2D) titanium carbide (Ti₃C₂T_x), known as MXene, possesses metallic conductivity and a hydrophilic surface, suggesting dispersion stability of MXenes in aqueous media allowing the fabrication of MXene-based TCEs by solution processing. However, achieving high FOM_e MXene TCEs has been hindered mainly due to the low intrinsic conductivity caused by percolation problems. Here, we have managed to resolve these problems by (1) using large-sized Ti₃C₂T_x flakes (∼12.2 μm) to reduce interflake resistance and (2) constructing compact microstructures by blade coating. Consequently, excellent optoelectronic properties have been achieved in the blade-coated Ti₃C₂T_x films, i.e., a DC conductivity of 19 325 S cm^-1 at transmittances of 83.4% (≈6.7 nm) was obtained. We also demonstrate the applications of Ti₃C₂T_x TCEs in transparent Joule heaters and the field of supercapacitors, showing an outstanding Joule heating effect and high rate response, respectively, suggesting enormous potential applications in flexible, transparent electronic devices.

Effect of Fractal Topology on the Resistivity Response of Thin Film Sensors

We discuss the effect of topological inhomogeneity of very thin metallic conductometric sensors on their response to external stimuli, such as pressure, intercalation, or gas absorption, that modify the material's bulk conductivity. The classical percolation model was extended to the case in which several independent scattering mechanisms contribute to resistivity. The magnitude of each scattering term was predicted to grow with the total resistivity and diverge at the percolation threshold. We tested the model experimentally using thin films of hydrogenated palladium and CoPd alloys where absorbed hydrogen atoms occupying the interstitial lattice sites enhance the electron scattering. The hydrogen scattering resistivity was found to grow linearly with the total resistivity in the fractal topology range in agreement with the model. Enhancement of the absolute magnitude of the resistivity response in the fractal range thin film sensors can be particularly useful when the respective bulk material response is too small for reliable detection.

Molecular insights into alginate β-lactoglobulin A multivalencies-The foundation for their amorphous aggregates and coacervation

For improved control of biomaterial property design, a better understanding of complex coacervation involving anionic polysaccharides and proteins is needed. Here, we address the initial steps in condensate formation of β-lactoglobulin A (β-LgA) with nine defined alginate oligosaccharides (AOSs) and describe their multivalent interactions in structural detail. Binding of AOSs containing four, five, or six uronic acid residues (UARs), either all mannuronate (M), all guluronate (G), or alternating M and G embodying the block structural components of alginates, was characterized by isothermal titration calorimetry, nuclear magnetic resonance spectroscopy (NMR), and molecular docking. β-LgA was highly multivalent exhibiting binding stoichiometries decreasing from five to two AOSs with increasing degree of polymerization (DP) and similar affinities in the mid micromolar range. The different AOS binding sites on β-LgA were identified by NMR chemical shift perturbation analyses and showed diverse compositions of charged, polar and hydrophobic residues. Distinct sites for the shorter AOSs merged to accommodate longer AOSs. The AOSs bound dynamically to β-LgA, as concluded from saturation transfer difference and 1 H-ligand-targeted NMR analyses. Molecular docking using Glide within the Schrödinger suite 2016-1 revealed the orientation of AOSs to only vary slightly at the preferred β-LgA binding site resulting in similar XP glide scores. The multivalency coupled with highly dynamic AOS binding with lack of confined conformations in the β-LgA complexes may help explain the first steps toward disordered β-LgA alginate coacervate structures.

Predicting alveolar ventilation heterogeneity in pulmonary fibrosis using a non-uniform polyhedral spring network model

Pulmonary Fibrosis (PF) is a deadly disease that has limited treatment options and is caused by excessive deposition and cross-linking of collagen leading to stiffening of the lung parenchyma. The link between lung structure and function in PF remains poorly understood, although its spatially heterogeneous nature has important implications for alveolar ventilation. Computational models of lung parenchyma utilize uniform arrays of space-filling shapes to represent individual alveoli, but have inherent anisotropy, whereas actual lung tissue is isotropic on average. We developed a novel Voronoi-based 3D spring network model of the lung parenchyma, the Amorphous Network, that exhibits more 2D and 3D similarity to lung geometry than regular polyhedral networks. In contrast to regular networks that show anisotropic force transmission, the structural randomness in the Amorphous Network dissipates this anisotropy with important implications for mechanotransduction. We then added agents to the network that were allowed to carry out a random walk to mimic the migratory behavior of fibroblasts. To model progressive fibrosis, agents were moved around the network and increased the stiffness of springs along their path. Agents migrated at various path lengths until a certain percentage of the network was stiffened. Alveolar ventilation heterogeneity increased with both percent of the network stiffened, and walk length of the agents, until the percolation threshold was reached. The bulk modulus of the network also increased with both percent of network stiffened and path length. This model thus represents a step forward in the creation of physiologically accurate computational models of lung tissue disease.

Contiguous High-Mobility Interphase Surrounding Nano-Precipitates in Polymer Matrix Solid Electrolyte

We establish that an interfacial region develops around amorphous Li_1.3Al_0.3Ti_1.7(PO₄)₃ (LATP) nanoparticles in a poly(ethylene oxide) (PEO), which exhibits a 30 times higher Li⁺ mobility than the polymer matrix. To take advantage of this gain throughout the material, nanoparticles must be uniformly dispersed across the matrix, so that the interphase formation is minimally blocked by LATP particle agglomeration. This is achieved using a water-based in situ precipitation method, carefully controlling the temperature schedule during processing. A maximum conductivity of 3.80 × 10^-4 S cm^-1 at 20 °C for an ethylene oxide to Li ratio of 10 is observed at 25 wt % (12.5 vol %) particle loading, as predicted by our tri-phase model. Comparative infrared spectroscopy reveals softening and broadening of the C-O-C stretching modes, reflecting increased disorder in the polymer backbone that is consistent with opening passageways for cation migration. A transition state theory-based approach for analyzing the temperature dependence of the ionic conductivity reveals that thermally activated processes within the interphase benefit more from higher activation entropy than from the decrease in activation enthalpy. The lithium infusion from LATP particles is small, and the charge carriers tend to concentrate in a space-charge configuration near the particle/polymer interface.

Topological Considerations in Biomolecular Condensation

Biomolecular condensation and phase separation are increasingly understood to play crucial roles in cellular compartmentalization and spatiotemporal regulation of cell machinery implicated in function and pathology. A key aspect of current research is to gain insight into the underlying physical mechanisms of these processes. Accordingly, concepts of soft matter and polymer physics, the thermodynamics of mixing, and material science have been utilized for understanding condensation mechanisms of multivalent macromolecules resulting in viscoelastic mesoscopic supramolecular assemblies. Here, we focus on two topological concepts that have recently been providing key mechanistic understanding in the field. First, we will discuss how percolation provides a network-topology-related framework that offers an interesting paradigm to understand the complex networking of dense 'connected' condensate structures and, therefore, their phase behavior. Second, we will discuss the idea of entanglement as another topological concept that has deep roots in polymer physics and important implications for biomolecular condensates. We will first review some historical developments and fundamentals of these concepts, then we will discuss current advancements and recent examples. Our discussion ends with a few open questions and the challenges to address them, hinting at unveiling fresh possibilities for the modification of existing knowledge as well as the development of new concepts relevant to condensate science.

Wound Healing Properties of Pelargonium Graveolens L'Hér Extract Lipogel: In-Vivo Evaluation in an Animal Burn Model

BACKGROUND

Pelargonium graveolens L'Hér has traditionally been used to reduce skin inflammation, and recent studies have confirmed antioxidant compounds in the plant's extract. The present study aimed to prepare a lipogel formulation from P. graveolens hydroalcoholic extract and evaluate its efficacy on the wound healing process in an animal model.

MATERIAL AND METHODS

The aerial part extract of P. graveolens was prepared through percolation. Additionally, plastibase was prepared by mixing 5% of low-molecular-weight polyethylene with hot mineral oil (130°C). The extract (5%) was levigated in the mineral oil (5-15%) and dispersed in the cooled plastibase. The physical properties of the lipogel, thermal stability, and microbial limits were tested. Further, the effect of the lipogel in the wound healing rate was examined among male Wistar rats, and skin tissue samples were assessed histologically.

RESULTS AND DISCUSSION

The results represented the best rheological and thermal stability characteristics in the formulation with 5% mineral oil (as the levigator). The lipogel-treated group had the least burn area compared to the silver sulfadiazine and negative control groups (p<0.05). The microscopic examination of tissue samples revealed increased collagen fiber production and maturation and significantly also faster epithelial repair among lipogel-treated rats than in the other two groups(p<0.05).

CONCLUSION

The results indicated the significant therapeutic effects of P. graveolens lipogelon burn healing. The suitable physicochemical properties and the low lipogel production cost facilitate further scale-up studies.

Core-Shell Engineering of Conductive Fillers toward Enhanced Dielectric Properties: A Universal Polarization Mechanism in Polymer Conductor Composites

Flexible dielectric and electronic materials with high dielectric constant (k) and low loss are constantly pursued. Encapsulation of conductive fillers with insulating shells represents a promising approach, and has attracted substantial research efforts. However, progress is greatly impeded due to the lack of a fundamental understanding of the polarization mechanism. In this work, a series of core-shell polymer composites is studied, and the correlation between macroscopic dielectric properties (across entire composites) and microscopic polarization (around single fillers) is investigated. It is revealed that the polarization in polymer conductor composites is determined by electron transport across multiple neighboring conductive fillers-a domain-type polarization. The formation of a core-shell filler structure affects the dielectric properties of tpolymer composites by essentially modifying the filler-cluster size. Based on this understanding, a novel percolative composite is prepared with higher-than-normal filler concentration and optimized shell's electrical resistivity. The developed composite shows both high-k due to enlarged cluster size and low loss due to restrained charge transport simultaneously, which cannot be achieved in traditional percolative composites or via simple core-shell filler design. The revealed polarization mechanism and the optimization strategy for core-shell fillers provide critical guidance and a new paradigm, for developing advanced polymer dielectrics with promising property sets.

Dewetting Process of Silver Thin Films and Its Application on Percolative Pressure Sensors with High Sensitivity

This work reports on an innovative dewetting process of silver thin films to realize percolative nanoparticle arrays (NPAs) and demonstrates its application on highly sensitive pressure sensors. The dewetting process, which is a simple and promising technique, synthesizes NPAs by breaking the as-deposited metal film into randomly distributed islands. The NPA properties, such as the mean particle size and the spacing between adjacent particles, can be easily tailored by controlling the dewetting temperature, as well as the as-deposited metal-film thickness. The fabricated NPAs were employed to develop gauge pressure sensors with high sensitivity. The proposed sensor consists of a sealed reference-pressure cavity, a polyimide (PI) membrane patterned with an interdigital electrode pair (IEP), and a silver NPA deposited on the IEP and the PI membrane. The operational principle of the device is based on the NPA percolation effect with deformation-dependence. The fabricated sensors exhibit rapid responses and excellent linearity at around 1 atm. The maximum sensitivity is about 0.1 kPa-1. The advantages of the proposed devices include ultrahigh sensitivity, a reduced thermal disturbance, and a decreased power consumption. A practical application of this pressure sensor with high resolution was demonstrated by using it to measure the relative floor height of a building.

Computational Micromechanics Investigation of Percolation and Effective Electro-Mechanical Properties of Carbon Nanotube/Polymer Nanocomposites using Stochastically Generated Realizations: Effects of Orientation and Waviness

The electrical and mechanical properties of carbon nanotube/polymer nanocomposites depend strongly upon several factors such as CNT volume fraction, CNT alignment, CNT dispersion and CNT waviness among others. This work focuses on obtaining estimates and distribution for the effective electrical conductivity, elastic constants and piezoresistive properties as a function of these factors using a stochastic approach with numerous CNT/polymer realizations coupled with parallel computation. Additionally, electrical percolation volume fraction and percolation transitional behavior is also studied. The effective estimates and percolation values were found to be in good agreement with experimental works in the literature. It was found that with increasing CNT volume fraction, the mechanical properties improved. However, due to the interaction of CNTs with one another through electrical tunneling, the conductivity and piezoresistivity properties evolved in a more complex manner. While the degree of alignment played a strong role in the effective properties making them anisotropic, the effect of waviness was found to be insubstantial.

Percolation Effects in Mixed Matrix Membranes with Embedded Carbon Nanotubes

Polymeric membranes with embedded nanoparticles, e.g., nanotubes, show a significant increase in permeability of the target component while maintaining selectivity. However, the question of the reasons for this behavior of the composite membrane has not been unequivocally answered to date. In the present work, based on experimental data on the permeability of polymer membranes based on Poly(vinyl trimethylsilane) (PVTMS) with embedded CNTs, an approach to explain the abnormal behavior of such composite membranes is proposed. The presented model considered the mass transfer of gases and liquids through polymeric membranes with embedded CNTs as a parallel transport of gases through the polymeric matrix and a "percolation" cluster-bound regions around the embedded CNTs. The proposed algorithm for modeling parameters of a percolation cluster of embedded tubular particles takes into account an agglomeration and makes it possible to describe the threshold increase and subsequent decrease permeability with increasing concentration of embedded particles. The numerical simulation of such structures showed: an increase in the particle length leads to a decrease in the percolation concentration in a matrix of finite size, the power of the percolation cluster decreases significantly, but the combination of these effects leads to a decrease in the influence of the introduced particles on the properties of the matrix in the vicinity of the percolation threshold; an increase in the concentration of embedded particles leads to an increase in the probability of the formation of agglomerates and the characteristic size of the elements that make up the percolation cluster, the influence of individual particles decreases and the characteristics of the percolation transition determine the ratio of the sizes of agglomerates and matrix; and an increase in the lateral linear dimensions of the matrix leads to a nonlinear decrease in the proportion of the matrix, which is affected by the introduced particles, and the transport characteristics of such MMMs deteriorate.

Total cannabidiol (CBD) concentrations and yields from traditional extraction methods: Percolation vs. maceration

Medicinal plants have been valued for many generations due to their biosynthetic advantages generating pharmacologically active molecules. This is especially the case when it comes to cannabinoids from Cannabis. In these experiments we mimicked typical herbal home extractions and measured the yield of total decarboxylated CBD ("total CBD") from percolations and macerations done at the common duration of 2 weeks in duplicate independent extractions. Analysis was performed by GC-FID on triplicate samples from each extraction. Results demonstrated a significant extraction superiority of percolation over maceration. Percolation extracted 80.1% of the total CBD in the hemp biomass as compared to the 2-week time point at 63.5% recovery. Our results demonstrate a significant increase in total CBD yield from percolation, as compared to maceration. Highest solvent recovery was also through percolation, but overall solvent recovery was fairly consistent with the maceration method, after pressing. Under these conditions of extracting lipophilic cannabidiol in 95% ethanol, these data demonstrate that percolation is significantly superior to maceration in total CBD yield. These observations will likely apply to the extraction of lipophilic constituents from other herbs and botanical medicines.

Modeling of Electrical Conductivity for Polymer-Carbon Nanofiber Systems

There is not a simple model for predicting the electrical conductivity of carbon nanofiber (CNF)-polymer composites. In this manuscript, a model is proposed to predict the conductivity of CNF-filled composites. The developed model assumes the roles of CNF volume fraction, CNF dimensions, percolation onset, interphase thickness, CNF waviness, tunneling length among nanoparticles, and the fraction of the networked CNF. The outputs of the developed model correctly agree with the experimentally measured conductivity of several samples. Additionally, parametric analyses confirm the acceptable impacts of main factors on the conductivity of composites. A higher conductivity is achieved by smaller waviness and lower radius of CNFs, lower percolation onset, less tunnel distance, and higher levels of interphase depth and fraction of percolated CNFs in the nanocomposite. The maximum conductivity is obtained at 2.37 S/m by the highest volume fraction and length of CNFs.

Conformational Heterogeneity and Interchain Percolation Revealed in an Amorphous Conjugated Polymer

Conjugated polymers are employed in a variety of application areas due to their bright fluorescence and strong biocompatibility. However, understanding the structure of amorphous conjugated polymers on the nanoscale is extremely challenging compared to their related crystalline phases. Using a bespoke classical force field, we study amorphous poly(9,9-di-n-octylfluorene-alt-benzothiadiazole) (F8BT) with molecular dynamics simulations to investigate the role that its nanoscale structure plays in controlling its emergent (and all-important) optical properties. Notably, we show that a giant percolating cluster exists within amorphous F8BT, which has ramifications in understanding the nature of interchain species that drive the quantum yield reduction and bathochromic shift observed in conjugated polymer-based devices and nanostructures. We also show that distinct conformations can be unravelled from within the disordered structure of amorphous F8BT using a two-stage machine learning protocol, highlighting a link between molecular conformation and ring stacking propensity. This work provides predictive understanding by which to enhance the optical properties of next-generation conjugated polymer-based devices and materials by rational, simulation-led design principles.

Effect of Impurity Scattering on Percolation of Bosonic Islands and Superconductivity in Fe Implanted NbN Thin Films

A reentrant temperature dependence of the thermoresistivity ρxx(T) between an onset local superconducting ordering temperature Tloconset and a global superconducting transition at T=Tglooffset has been reported in disordered conventional 3-dimensional (3D) superconductors. The disorder of these superconductors is a result of either an extrinsic granularity due to grain boundaries, or of an intrinsic granularity ascribable to the electronic disorder originating from impurity dopants. Here, the effects of Fe doping on the electronic properties of sputtered NbN layers with a nominal thickness of 100 nm are studied by means of low-T/high-μ0H magnetotransport measurements. The doping of NbN is achieved via implantation of 35 keV Fe ions. In the as-grown NbN films, a local onset of superconductivity at Tloconset=15.72K is found, while the global superconducting ordering is achieved at Tglooffset=15.05K, with a normal state resistivity ρxx=22μΩ·cm. Moreover, upon Fe doping of NbN, ρxx=40μΩ·cm is estimated, while Tloconset and Tglooffset are measured to be 15.1 K and 13.5 K, respectively. In Fe:NbN, the intrinsic granularity leads to the emergence of a bosonic insulator state and the normal-metal-to-superconductor transition is accompanied by six different electronic phases characterized by a N-shaped T dependence of ρxx(T). The bosonic insulator state in a s-wave conventional superconductor doped with dilute magnetic impurities is predicted to represent a workbench for emergent phenomena, such as gapless superconductivity, triplet Cooper pairings and topological odd frequency superconductivity.

High conductivity Sepia melanin ink films for environmentally benign printed electronics

Melanins (from the Greek μέλας, mélas, black) are bio-pigments ubiquitous in flora and fauna. Eumelanin is an insoluble brown-black type of melanin, found in vertebrates and invertebrates alike, among which Sepia (cuttlefish) is noteworthy. Sepia melanin is a type of bio-sourced eumelanin that can readily be extracted from the ink sac of cuttlefish. Eumelanin features broadband optical absorption, metal-binding affinity and antioxidative and radical-scavenging properties. It is a prototype of benign material for sustainable organic electronics technologies. Here, we report on an electronic conductivity as high as 10^-3 S cm^-1 in flexographically printed Sepia melanin films; such values for the conductivity are typical for well-established high-performance organic electronic polymers but quite uncommon for bio-sourced organic materials. Our studies show the potential of bio-sourced materials for emerging electronic technologies with low human- and eco-toxicity.

Quantifying the environmental limits to fire spread in grassy ecosystems

Modeling fire spread as an infection process is intuitive: An ignition lights a patch of fuel, which infects its neighbor, and so on. Infection models produce nonlinear thresholds, whereby fire spreads only when fuel connectivity and infection probability are sufficiently high. These thresholds are fundamental both to managing fire and to theoretical models of fire spread, whereas applied fire models more often apply quasi-empirical approaches. Here, we resolve this tension by quantifying thresholds in fire spread locally, using field data from individual fires (n = 1,131) in grassy ecosystems across a precipitation gradient (496 to 1,442 mm mean annual precipitation) and evaluating how these scaled regionally (across 533 sites) and across time (1989 to 2012 and 2016 to 2018) using data from Kruger National Park in South Africa. An infection model captured observed patterns in individual fire spread better than competing models. The proportion of the landscape that burned was well described by measurements of grass biomass, fuel moisture, and vapor pressure deficit. Regionally, averaging across variability resulted in quasi-linear patterns. Altogether, results suggest that models aiming to capture fire responses to global change should incorporate nonlinear fire spread thresholds but that linear approximations may sufficiently capture medium-term trends under a stationary climate.

A conceptual framework for understanding phase separation and addressing open questions and challenges

Macromolecular phase separation is being recognized for its potential importance and relevance as a driver of spatial organization within cells. Here, we describe a framework based on synergies between networking (percolation or gelation) and density (phase separation) transitions. Accordingly, the phase transitions in question are referred to as phase separation coupled to percolation (PSCP). The condensates that result from PSCP are viscoelastic network fluids. Such systems have sequence-, composition-, and topology-specific internal network structures that give rise to time-dependent interplays between viscous and elastic properties. Unlike pure phase separation, the process of PSCP gives rise to sequence-, chemistry-, and structure-specific distributions of clusters that can form at concentrations that lie well below the threshold concentration for phase separation. PSCP, influenced by specific versus solubility-determining interactions, also provides a bridge between different observations and helps answer questions and address challenges that have arisen regarding the role of macromolecular phase separation in biology.