Ultrasonication Influence on the Morphological Characteristics of Graphene Nanoplatelet Nanocomposites and Their Electrical and Electromagnetic Interference Shielding Behavior

Graphene nanoplatelets (GNPs)/epoxy composites have been fabricated via gravity molding. The electrical and thermal properties of the composites have been studied with variable GNP type (C300, C500, and C750, whose surface areas are ~300, 500, and 750 m2/g, respectively), GNP loading (5, 10, 12, and 15 wt.%), and dispersion time via ultrasonication (0, 30, 60, and 120 min). By increasing the time of sonication of the GNP into the epoxy matrix, the electrical conductivity decreases, which is an effect of GNP fragmentation. The best results were observed with 10-12% loading and a higher surface area (C750), as they provide higher electrical conductivity, thereby preserving thermal conductivity. The influence of sonication over electrical conductivity was further analyzed via the study of the composite morphology by means of Raman spectroscopy and X-ray diffraction (XRD), providing information about the aspect ratio of GNPs. Moreover, electromagnetic shielding (EMI) has been studied up to 4 GHz. Composites with C750 and 120 min ultrasonication show the best performance in EMI shielding, influenced by their higher electrical conductivity.

Experimental Demonstration of Reservoir Computing with Self-Assembled Percolating Networks of Nanoparticles

The complex self-assembled network of neurons and synapses that comprises the biological brain enables natural information processing with remarkable efficiency. Percolating networks of nanoparticles (PNNs) are complex self-assembled nanoscale systems that have been shown to possess many promising brain-like attributes and which are therefore appealing systems for neuromorphic computation. Here experiments are performed that show that PNNs can be utilized as physical reservoirs within a nanoelectronic reservoir computing framework and demonstrate successful computation for several benchmark tasks (chaotic time series prediction, nonlinear transformation, and memory capacity). For each task, relevant literature results are compiled and it is shown that the performance of the PNNs compares favorably to that previously reported from nanoelectronic reservoirs. It is then demonstrated experimentally that PNNs can be used for spoken digit recognition with state-of-the-art accuracy. Finally, a parallel reservoir architecture is emulated, which increases the dimensionality and richness of the reservoir outputs and results in further improvements in performance across all tasks.

High Thermoelectric Performance in Solution-Processed Semicrystalline PEDOT:PSS Films by Strong Acid-Base Treatment: Limitations and Potential

Thermoelectric (TE) generation with solution-processable conducting polymers offers substantial potential in low-temperature energy harvesting based on high tunability in materials, processes, and form-factors. However, manipulating the TE and charge transport properties accompanies structural and energetic disorders, restricting the enhancement of thermoelectric power factor (PF). Here, solution-based strong acid-base treatment techniques are introduced to modulate the doping level of poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS) thin films with preserving its molecular orientation, enabling to achieve a remarkably high PF of 534.5 µW m-1  K-2 . Interestingly, theoretical modeling suggested that further de-doping can increase the PF beyond the experimental value. However, it is impossible to reach this value experimentally, even without any degradation of PEDOT crystallinity. Uncovering the underlying reason for the limitation, an analysis of the relationship among the microstructure-thermoelectric performance-charge transport property revealed that inter-domain connectivity via tie-chains and the resultant percolation for transport are crucial factors in achieving high TE performance, as in charge transport. It is believed that the methods and fundamental understandings in this work would contribute to the exploitation of conducting polymer-based low-temperature energy harvesting.

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.

Facile synthesis ofβ-Ga2O3based high-performance electronic devices via direct oxidation of solution-processed transition metal dichalcogenides

Gallium oxide (Ga2O3) is a promising wide bandgap semiconductor that is viewed as a contender for the next generation of high-power electronics due to its high theoretical breakdown electric field and large Baliga's figure of merit. Here, we report a facile route of synthesizingβ-Ga2O3via direct oxidation conversion using solution-processed two-dimensional (2D) GaS semiconducting nanomaterial. Higher order of crystallinity in x-ray diffraction patterns and full surface coverage formation in scanning electron microscopy images after annealing were achieved. A direct and wide bandgap of 5 eV was calculated, and the synthesizedβ-Ga2O3was fabricated as thin film transistors (TFT). Theβ-Ga2O3TFT fabricated exhibits remarkable electron mobility (1.28 cm2Vs-1) and a good current ratio (Ion/Ioff) of 2.06 × 105. To further boost the electrical performance and solve the structural imperfections resulting from the exfoliation process of the 2D nanoflakes, we also introduced and doped graphene inβ-Ga2O3TFT devices, increasing the electrical device mobility by ∼8-fold and thereby promoting percolation pathways for the charge transport. We found that electron mobility and conductivity increase directly with the graphene doping concentration. From these results, it can be proved that theβ-Ga2O3networks have excellent carrier transport properties. The facile and convenient synthesis method successfully developed in this paper makes an outstanding contribution to applying 2D oxide materials in different and emerging optoelectronic applications.

Rigidity percolation in a random tensegrity via analytic graph theory

Functional structures from across the engineered and biological world combine rigid elements such as bones and columns with flexible ones such as cables, fibers, and membranes. These structures are known loosely as tensegrities, since these cable-like elements have the highly nonlinear property of supporting only extensile tension. Marginally rigid systems are of particular interest because the number of structural constraints permits both flexible deformation and the support of external loads. We present a model system in which tensegrity elements are added at random to a regular backbone. This system can be solved analytically via a directed graph theory, revealing a mechanical critical point generalizing that of Maxwell. We show that even the addition of a few cable-like elements fundamentally modifies the nature of this transition point, as well as the later transition to a fully rigid structure. Moreover, the tensegrity network displays a collective avalanche behavior, in which the addition of a single cable leads to the elimination of multiple floppy modes, a phenomenon that becomes dominant at the transition point. These phenomena have implications for systems with nonlinear mechanical constraints, from biopolymer networks to soft robots to jammed packings to origami sheets.

Percolation Theories for Quantum Networks

Quantum networks have experienced rapid advancements in both theoretical and experimental domains over the last decade, making it increasingly important to understand their large-scale features from the viewpoint of statistical physics. This review paper discusses a fundamental question: how can entanglement be effectively and indirectly (e.g., through intermediate nodes) distributed between distant nodes in an imperfect quantum network, where the connections are only partially entangled and subject to quantum noise? We survey recent studies addressing this issue by drawing exact or approximate mappings to percolation theory, a branch of statistical physics centered on network connectivity. Notably, we show that the classical percolation frameworks do not uniquely define the network's indirect connectivity. This realization leads to the emergence of an alternative theory called "concurrence percolation", which uncovers a previously unrecognized quantum advantage that emerges at large scales, suggesting that quantum networks are more resilient than initially assumed within classical percolation contexts, offering refreshing insights into future quantum network design.

A Study on Enhanced Electrorheological Performance of Plate-like Materials via Percolation Gel-like Effect

The use of plate-like materials to induce a percolation gel-like effect in electrorheological (ER) fluids is sparsely documented. Hence, we dispersed plate-like materials, namely natural mica, synthetic mica, and glass, as well as their pulverized particles, in various concentrations in silicone oil to form ER fluids. Subsequently, the rheological properties of the fluids were evaluated and compared to identify the threshold concentration for percolating a gel-like state. The shear stress and viscoelastic moduli under zero-field conditions confirmed that plate-like materials can be used to induce percolation gel-like effects in ER fluids. This is because of the high aspect ratio of the materials, which enhances their physical stability. In practical ER investigations, ER fluids based on synthetic mica (30.0 wt%) showed the highest yield stress of 516.2 Pa under an electric field strength of 3.0 kV mm-1. This was attributed to the formation of large-cluster networks and additional polarization induced by the ions. This study provides a practical approach for developing a new type of gel-like ER fluid.

Interdependence of cellular and network properties in respiratory rhythmogenesis

How breathing is generated by the preBötzinger Complex (preBötC) remains divided between two ideological frameworks, and the persistent sodium current (INaP) lies at the heart of this debate. Although INaP is widely expressed, the pacemaker hypothesis considers it essential because it endows a small subset of neurons with intrinsic bursting or "pacemaker" activity. In contrast, burstlet theory considers INaP dispensable because rhythm emerges from "pre-inspiratory" spiking activity driven by feed-forward network interactions. Using computational modeling, we discover that changes in spike shape can dissociate INaP from intrinsic bursting. Consistent with many experimental benchmarks, conditional effects on spike shape during simulated changes in oxygenation, development, extracellular potassium, and temperature alter the prevalence of intrinsic bursting and pre-inspiratory spiking without altering the role of INaP. Our results support a unifying hypothesis where INaP and excitatory network interactions, but not intrinsic bursting or pre-inspiratory spiking, are critical interdependent features of preBötC rhythmogenesis.

Grid cells, border cells, and discrete complex analysis

We propose a mechanism enabling the appearance of border cells-neurons firing at the boundaries of the navigated enclosures. The approach is based on the recent discovery of discrete complex analysis on a triangular lattice, which allows constructing discrete epitomes of complex-analytic functions and making use of their inherent ability to attain maximal values at the boundaries of generic lattice domains. As it turns out, certain elements of the discrete-complex framework readily appear in the oscillatory models of grid cells. We demonstrate that these models can extend further, producing cells that increase their activity toward the frontiers of the navigated environments. We also construct a network model of neurons with border-bound firing that conforms with the oscillatory models.

Physics of large thermoelectric power factors in SnSe nanoflakes in mid-temperature range

We have theoretically investigated the underlying physics of observed high electrical conductivity (σ), simultaneous increase of σ and Seebeck coefficient (S) with temperature, and large power factors (PFs) in nominally undoped SnSe nanoflakes sintered at different temperatures, reported recently in Mandavaet al(2022Nanotechnology33155710). Given the fact that S and σ show unusual temperature trends and that the undoped SnSe samples are highly porous and disordered, the conventional Boltzmann theory does not appear to be an appropriate model to describe their transport properties. We have, instead, used a strong disorder model based on percolation theory where charge and energy transport take place through hopping between localized states to understand these observations. Our model is able to explain the observed temperature dependence of σ and S with temperature. Large σ can be explained by a high density of localized states and a large hopping rate. The sample sintered at a higher temperature has lower disorder (σDOS) and higher hopping rate (1/τ0). We findσDOS= 0.151 eV and 1/τ0= 0.143 × 1015s-1for sample sintered at 673 K andσDOS= 0.044 eV and 1/τ0= 2.023 × 1015s-1for sample sintered at 703 K. These values are comparable to the reported values of transition frequencies, confirming that the dominant charge transport mechanism in these SnSe nanoflakes is hopping transport. Finally, we suggest that hopping transport via localized states can result in enhanced thermoelectric properties in disordered polycrystalline materials.

Properties of Packed Bed Structures Formed during Filtration: A Two and Three-Dimensional Model

Agglomeration is an issue that causes many problems during secondary processing for pharmaceutical companies, causing material to need further processing and costing additional time and resources to ensure a satisfactory outcome. A potential source of agglomeration arises from the particle contacts established during filtration that lead to robust agglomerates forming during drying, so that a necessary first step toward understanding agglomeration is to study the packing properties of filtration beds. Here, we present two and three-dimensional models simulating the formation of packed bed structures during filtration. The models use circular and spherical particles of different sizes, mimicking the bimodal particle size distributions sometimes encountered in industrial practice. The statistics of packing and void formation, along with the distribution of interparticle contacts and percolation structures, are presented and discussed in the context of filtration, drying, and agglomeration. The model paves the way for predictive capabilities that can lead to the rational design of processes to minimize the impact of agglomeration.

Theoretical Prediction of Electrical Conductivity Percolation of Poly(lactic acid)-Carbon Nanotube Composites in DC and RF Regime

Polymer composites based on polylactic acid (PLA) reinforced with 0.25-5 wt.% of carbon nanotubes (CNTs) were synthesized by melt blending. The static (DC) and microwave (RF) electrical conductivity have been investigated on the PLA-CNT composites. The electrical percolation threshold has been theoretically determined using classical models of percolation in order to predict the conductivity of the different nanocomposites. Through the fitting process, it has been found that the percolation threshold is obtained at 1 wt.% of CNTs in the DC regime and reached below 0.25 wt.% of CNTs in the microwave regime. Among the Mamunya, McLachlan, or GEM models, the McCullough model remarkably fits the experimental DC and RF electrical conductivities. The obtained results are correlated to the electrical properties of a range of CNT-based composites, corresponding to the percolation threshold required for a three-dimensional network of CNTs into the polymer matrix.

The Flow of Glasses and Glass-Liquid Transition under Electron Irradiation

Recent discovery and investigation of the flow of glasses under the electron beams of transmission electron microscopes raised the question of eventual occurrence of such type effects in the vitrified highly radioactive nuclear waste (HLW). In connection to this, we analyse here the flow of glasses and glass-liquid transition in conditions of continuous electron irradiation such as under the e-beam of transmission electron microscopes (TEM) utilising the configuron (broken chemical bond) concept and configuron percolation theory (CPT) methods. It is shown that in such conditions, the fluidity of glasses always increases with a substantial decrease in activation energy of flow at low temperatures and that the main parameter that controls this behaviour is the dose rate of absorbed radiation in the glass. It is revealed that at high dose rates, the temperature of glass-liquid transition sharply drops, and the glass is fully fluidised. Numerical estimations show that the dose rates of TEM e-beams where the silicate glasses were fluidised are many orders of magnitude higher compared to the dose rates characteristic for currently vitrified HLW.

Optical nonreciprocity in multilayer nanoisland systems of [Ag--Al2O3]N

We study the effect of optical nonreciprocity in [Ag--Al<sub>2<\sub>O<sub>3<\sub>]_{N<\sub> multilayer structures. The percolation threshold for Ag films was found to be d^*≈ 2 nm. An anomalously large optical nonreciprocity effect was found in the structures with Ag island layers. This effect appeared as a change in the reflected light polarization (Δω) when the sample was rotated around its axis from the initial position by 180°. The effect magnitude reached Δω}max<sub> ≈ 7°. We suggest that a possible mechanism for the optical nonreciprocity effect in these structures can be related to the excitation of localized plasmons in Ag islands. We show that Δω essentially depends on the interlayer and intralayer interaction between Ag layers in multilayer structures and is suppressed in the case of strong intralayer and interlayer interaction of plasma oscillations.

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.