Enhancing Effect of Fullerene Guest and Counterion on the Structural Stability and Electrical Conductivity of Octahedral Metallo-Supramolecular Cages.

Metallo-supramolecular cages have garnered tremendous attention for their diverse yet molecular-level precision structures. However, physical properties of these supramolecular ensembles, which are of potential significance in molecular electronics, remain largely unexplored. We herein constructed a series of octahedral metallo-cages and cage-fullerene complexes with notably enhanced structural stability. As such, we could systematically evaluate the electrical conductivity of these ensembles at both single-molecule level and aggregated bulk state (as well-defined films). Our findings reveal that counteranions and fullerene guests play a pivotal role in determining the electrical conductivity of aggregated state, while such effects are less significant for single-molecule conductance. Both counteranions and fullerenes effectively tune the electronic structures and packing density of metallo-supramolecular assemblies, and facilitate efficient charge transfer between the cage hosts and fullerenes, resulting in a notable one order of magnitude increase in electrical conductivity of the aggregated state.

Multi-step ahead forecasting of electrical conductivity in rivers by using a hybrid Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM) model enhanced by Boruta-XGBoost feature selection algorithm.

Electrical conductivity (EC) is widely recognized as one of the most essential water quality metrics for predicting salinity and mineralization. In the current research, the EC of two Australian rivers (Albert River and Barratta Creek) was forecasted for up to 10 days using a novel deep learning algorithm (Convolutional Neural Network combined with Long Short-Term Memory Model, CNN-LSTM). The Boruta-XGBoost feature selection method was used to determine the significant inputs (time series lagged data) to the model. To compare the performance of Boruta-XGB-CNN-LSTM models, three machine learning approaches-multi-layer perceptron neural network (MLP), K-nearest neighbour (KNN), and extreme gradient boosting (XGBoost) were used. Different statistical metrics, such as correlation coefficient (R), root mean square error (RMSE), and mean absolute percentage error, were used to assess the models' performance. From 10 years of data in both rivers, 7 years (2012-2018) were used as a training set, and 3 years (2019-2021) were used for testing the models. Application of the Boruta-XGB-CNN-LSTM model in forecasting one day ahead of EC showed that in both stations, Boruta-XGB-CNN-LSTM can forecast the EC parameter better than other machine learning models for the test dataset (R = 0.9429, RMSE = 45.6896, MAPE = 5.9749 for Albert River, and R = 0.9215, RMSE = 43.8315, MAPE = 7.6029 for Barratta Creek). Considering the better performance of the Boruta-XGB-CNN-LSTM model in both rivers, this model was used to forecast 3-10 days ahead of EC. The results showed that the Boruta-XGB-CNN-LSTM model is very capable of forecasting the EC for the next 10 days. The results showed that by increasing the forecasting horizon from 3 to 10 days, the performance of the Boruta-XGB-CNN-LSTM model slightly decreased. The results of this study show that the Boruta-XGB-CNN-LSTM model can be used as a good soft computing method for accurately predicting how the EC will change in rivers.

Exploring keratin composition variability for sustainable thermal insulator design.

In pursuing sustainable thermal insulation solutions, this study explores the integration of human hair and feather keratin with alginate. The aim is to assess its potential in thermal insulation materials, focusing on the resultant composites' thermal and mechanical characteristics. The investigation uncovers that the type and proportion of keratin significantly influence the composites' porosity and thermal conductivity. Specifically, higher feather keratin content is associated with lesser sulfur and reduced crosslinking due to shorter amino acids, leading to increased porosity and pore sizes. This, in turn, results in a decrease in ß-structured hydrogen bond networks, raising non-ordered protein structures and diminishing thermal conductivity from 0.044 W/(m·K) for pure alginate matrices to between 0.033 and 0.038 W/(m·K) for keratin-alginate composites, contingent upon the specific ratio of feather to hair keratin used. Mechanical evaluations further indicate that composites with a higher ratio of hair keratin exhibit an enhanced compressive modulus, ranging from 60 to 77 kPa, demonstrating the potential for tailored mechanical properties to suit various applications. The research underscores the critical role of sulfur content and the crosslinking index within keratin's structures, significantly impacting the thermal and mechanical properties of the matrices. The findings position keratin-based composites as environmentally friendly alternatives to traditional insulation materials.

The effect of polycarboxylate superplasticizer on the strength and hydration performance of alkali slag building materials.

To explore the effect of polycarboxylate superplasticizers on the strength and hydration performance of alkali slag building materials, this study prepared cross-linked polycarboxylate superplasticizers with different ratios of hydrogen peroxide, methyl allyl alcohol polyoxyethylene ether, acrylic acid, polyethylene glycol diacrylate, monomer aqueous solution, reducing agent, chain transfer agent, etc. according to certain ratios, and tested their effects on the hydration performance and strength of alkali slag building materials. Through experimental analysis, it was found that the higher the proportion of cross-linked polycarboxylate based high-efficiency water-reducing agents, the lower the initial flowability of building material slurry; The addition of cross-linked polycarboxylate water-reducing agent will prolong the initial and final setting time of alkali slag building materials, delaying the hydration time of building materials; Cross linked polycarboxylate superplasticizers can reduce the electrical conductivity of alkali slag building material slurry, delaying its hydration rate; Different ratios of water-reducing agents have a significant impact on the water reduction rate of alkali slag building materials, with V2 water-reducing agent having the highest water-reduction rate of 28.6%; Cross linked polycarboxylate superplasticizers can increase the flexural and compressive strength of alkali slag building materials. Therefore, cross-linked polycarboxylate water-reducing agents have shown great potential in regulating the properties of alkali slag building materials.

0D/2D Co-Doping Network Enhancing Thermal Conductivity of Radiative Cooling Film for Electronic Device Thermal Management.

The radiative cooling has great potential for electronic device cooling without requiring any energy consumption. However, a low thermal conductivity of most radiative cooling materials limits their application. Herein, a multishape codoping strategy was proposed to achieve collaborative enhancement of thermal conductivity and radiative properties. The hBN-coated hollow SiO2 particles were prepared based on electrostatic self-assembly technology, which were then mixed with hBN platelets and doped into a poly(vinylidene fluoride-co-hexafluoropropylene) substrate. Discrete dipole approximation theory was employed to reveal the mechanism and optimize the particle size. The results showed that the multishape codoping method can significantly improve the radiative performance, with 94.9% reflectivity and 91.2% emissivity. In addition, this zero-dimensional and two-dimensional composite doping structure facilitated the formation of a thermal conduction network, which enhanced the thermal conductivity of the film up to 1.32 W m-1 K-1. The high thermal conductivity radiative cooling film can decrease the heater temperature from 58.8 to 31.3 °C, with a further reduction of temperature by 7.2 °C compared to the radiative cooling substrates with low thermal conductivity. The net cooling power of the film can reach 102.5 W m-2 under direct sunlight. This work provides a novel strategy for high-efficiency electronic device cooling.

Exploring surface charge dynamics: implications for AFM height measurements in 2D materials.

An often observed artifact in atomic force microscopy investigations of individual monolayer flakes of 2D materials is the inaccurate height derived from topography images, often attributed to capillary or electrostatic forces. Here, we show the existence of a Joule dissipative mechanism related to charge dynamics and supplementing the dissipation due to capillary forces. This particular mechanism arises from the surface conductivity and assumes significance specially in the context of 2D materials on insulating supports. In such scenarios, the oscillating tip induces in-plane charge currents that in many circumstances constitute the main dissipative contribution to amplitude reduction and, consequently, affect the measured height. To investigate this phenomenon, we conduct measurements on monolayer flakes of co-deposited graphene oxide and reduced graphene oxide. Subsequently, we introduce a general model that elucidates our observations. This approach offers valuable insights into the dynamics of surface charges and their intricate interaction with the tip.

Atomic layer deposition of Al-doped ZnO nanomembrane with in situ monitoring.

Due to shortcomings such as poor homogeneity of Al doping, precisely controlling the thickness, inability to conformally deposit on high aspect ratio devices and high pinhole rate, the applications of Al-doped ZnO (AZO) nanomembrane in integrated optoelectronic devices are remarkably influenced. Here, we report in situ monitoring during the atomic layer deposition (ALD) of AZO nanomembrane by using an integrated spectroscopic ellipsometer. AZO nanomembranes with different compositions were deposited with real-time and precise atomic level monitoring of the deposition process. We specifically investigate the half reaction and thickness evolution during the ALD processes and the influence of the chamber temperature is also disclosed. Structural characterizations demonstrate that the obtained AZO nanomembranes without any post-treatment are uniform, dense and pinhole-free. The transmittances of the nanomembranes in visible range are > 94%, and the optimal conductivity can reach up to 1210 S/cm. The output of current research may pave the way for AZO nanomembrane becoming promising in integrated optoelectronic devices.

Neural Tissue-Like, not Supraphysiological, Electrical Conductivity Stimulates Neuronal Lineage Specification through Calcium Signaling and Epigenetic Modification.

Electrical conductivity is a pivotal biophysical factor for neural interfaces, though optimal values remain controversial due to challenges isolating this cue. To address this issue, conductive substrates made of carbon nanotubes and graphene oxide nanoribbons, exhibiting a spectrum of conductivities from 0.02 to 3.2 S m-1, while controlling other surface properties is designed. The focus is to ascertain whether varying conductivity in isolation has any discernable impact on neural lineage specification. Remarkably, neural-tissue-like low conductivity (0.02-0.1 S m-1) prompted neural stem/progenitor cells to exhibit a greater propensity toward neuronal lineage specification (neurons and oligodendrocytes, not astrocytes) compared to high supraphysiological conductivity (3.2 S m-1). High conductivity instigated the apoptotic process, characterized by increased apoptotic fraction and decreased neurogenic morphological features, primarily due to calcium overload. Conversely, cells exposed to physiological conductivity displayed epigenetic changes, specifically increased chromatin openness with H3acetylation (H3ac) and neurogenic-transcription-factor activation, along with a more balanced intracellular calcium response. The pharmacological inhibition of H3ac further supported the idea that such epigenetic changes might play a key role in driving neuronal specification in response to neural-tissue-like, not supraphysiological, conductive cues. These findings underscore the necessity of optimal conductivity when designing neural interfaces and scaffolds to stimulate neuronal differentiation and facilitate the repair process.

Copper-Graphene Composite (CGC) Conductors: Synthesis, Microstructure, and Electrical Performance.

Improving the electrical performance of copper, the most widely used electrical conductor in the world is of vital importance to the progress of key technologies, including electric vehicles, portable devices, renewable energy, and power grids. Copper-graphene composite (CGC) stands out as the most promising candidate for high-performance electrical conductor applications. This can be attributed to the superior properties of graphene fillers embedded in CGC, including excellent electrical and thermal conductivity, corrosion resistance, and high mechanical strength. This review highlights the recent progress of CGC conductors, including their fabrication processes, electrical performances, mechanisms of copper-graphene interplay, and potential applications.

V-Doping Strategy Induces the Construction of the CoFe-LDHs/NF Electrodes with Higher Conductivity to Achieve Higher Energy Density for Advanced Energy Storage Devices.

Doping of metal ions shows promising potential in optimizing and modulating the electrical conductivity of layered double hydroxides (LDHs). However, there is still much room for improvement in common metal ions and conventional doping methods. In contrast to previous methodologies, a hollow triangular nanoflower structure of CoFeV-LDHs is devised, which is enriched with a greater number of oxygen vacancies. This resulted in a significant enhancement in the conductivity of the LDHs, leading to an increase in energy density following the appropriate doping of V. To investigate the impact of V-doping on the energy density of the LDHs, in situ XPS and in situ X-ray spectroscopy is employed. Regarding electrochemical performance, the CoFeV-LDHs/NF electrode with optimal doping ratio exhibited a specific capacitance of 881 F g-1 at a current density of 1 A g-1. The capacitance remained at 90.53% after 3000 cycles. In addition, the constructed battery-type supercapacitor CoFeV-LDHs/NF-2//AC exhibited an impressive energy density of 124.7 Wh kg-1 at a power density of 850 W kg-1 and capacitance remained almost unchanged at 95.2% after 3000 cycles. All the above demonstrates the great potential of V-doped LDHs and brings a new way for the subsequent research of LDHs.

Zwitterionic Eutectogels with High Ionic Conductivity for Environmentally Tolerant and Self-Healing Triboelectric Nanogenerators.

Eutectogels have garnered considerable attention for the development of wearable devices, owing to their inherent mechanical elasticity, ionic conductivity, affordability, and environmental compatibility. However, the low conductivity of existing eutectogels has impeded their progression in electronic applications. Here, we report a zwitterionic eutectogel with an impressive ionic conductivity of up to 15.7 mS cm-1. The incorporation of zwitterionic groups into the eutectogel creates ample mobile charges by dissociating the cation and anion of solvents, thereby yielding exceptional ionic conductivity. Moreover, the abundant electrostatic and hydrogen bonding interactions within the eutectogel endow it with prominent self-healing and adhesive properties. By integrating the eutectogel with a roughly patterned polydimethylsiloxane film, we have successfully constructed a triboelectric nanogenerator (TENG) with a maximum output power density of 112 mW m-2. This TENG is capable of generating stable electrical signals even in extreme temperature conditions ranging from -80 to 100 °C and effectively powering electronic devices. Furthermore, the assembled TENG displays high sensitivity as a self-powered sensor, enabling real-time and precise monitoring of signals derived from human motions. This study establishes a promising approach for the development of sustainable and multifunctional flexible electronics that are resilient in extreme environments.

High-performance n-Type Organic Thermoelectrics with Exceptional Conductivity by Polymer-Dopant Matching.

Achieving high electrical conductivity (σ) and power factor (PF) simultaneously remains a significant challenge for n-type organic themoelectrics (OTEs). Herein, we demonstrate the state-of-the-art OTEs performance through blending a fused bithiophene imide dimer-based polymer f-BTI2g-SVSCN and its selenophene-substituted analogue f-BSeI2g-SVSCN with a julolidine-functionalized benzimidazoline n-dopant JLBI, vis-à-vis when blended with commercially available n-dopants TAM and N-DMBI. The advantages of introducing a more lipophilic julolidine group into the dopant structure of JLBI are evidenced by the enhanced OTEs performance that JLBI-doped films show when compared to those doped with N-DMBI or TAM. In fact, thanks to the enhanced intermolecular interactions and the lower-lying LUMO level enabled by the increase of selenophene content in polymer backbone, JLBI-doped films of f-BSeI2g-SVSCN exhibit a unprecedent σ of 206 S cm-1 and a PF of 114 µW m-1 K-2. Interestingly, σ can be further enhanced up to 326 S cm-1 by using TAM dopant as a consequence of its favorable diffusion behavior into densely packed crystalline domains. These values are the highest to date for solution-processed molecularly n-doped polymers, demonstrating the effectiveness of the polymer-dopant matching approach carried out in this work.

Anionic Hofmeister Effect Regulated Conductivity in Polyelectrolyte Hydrogels for High-Performance Supercapacitor.

The Hofmeister effect not only affects the stability and solubility of protein colloids but also has specific effects on the polymer molecules. Here, the impact of the Hofmeister effect on the electrochemical properties of polyelectrolyte hydrogels at room temperature and subzero temperature studied for the first time. Polyelectrolyte hydrogels exhibit an anti-polyelectrolyte effect in low concentrations of ammonium salt, while they exhibit an obvious Hofmeister effect in high concentrations of ammonium salt. Kosmotropic ions demonstrate strong interaction with water molecules or polymer chains, resulting in the reduction of conductivity of polyelectrolyte hydrogels. However, chaotropic ions exhibit weak interactions with water molecules or molecular chains, leading to an increase in conductivity. The Hofmeister effect has a more significant effect on the polyzwitterion electrolyte. The conductivity of polyzwitterion hydrogel soaked in chaotropic ion is up to 6.2 mS cm-1 at -40 °C. The supercapacitor assembled by polyzwitterion electrolytes maintains a capacitance retention rate of 85% and ≈100% coulomb efficiency after 15 000 cycles at -40 °C. This study elucidates the influence of the Hofmeister effect on conductivity in polyelectrolytes and expands the regulatory approach for improving the performance of energy storage devices.

In-Plane Overdamping and Out-Plane Localized Vibration Contribute to Ultralow Lattice Thermal Conductivity of Zintl Phase KCdSb.

Zintl phases typically exhibit low lattice thermal conductivity, which are extensively investigated as promising thermoelectric candidates. While the significance of Zintl anionic frameworks in electronic transport properties is widely recognized, their roles in thermal transport properties have often been overlooked. This study delves into KCdSb as a representative case, where the [CdSb4/4]- tetrahedrons not only impact charge transfer but also phonon transport. The phonon velocity and mean free path, are heavily influenced by the bonding distance and strength of the Zintl anions Cd and Sb, considering the three acoustic branches arising from their vibrations. Furthermore, the weakly bound Zintl cation K exhibits localized vibration behaviors, resulting in strong coupling between the high-lying acoustic branch and the low-lying optical branch, further impeding phonon diffusion. The calculations reveal that grain boundaries also contribute to the low lattice thermal conductivity of KCdSb through medium-frequency phonon scattering. These combined factors create a glass-like thermal transport behavior, which is advantageous for improving the thermoelectric merit of zT. Notably, a maximum zT of 0.6 is achieved for K0.84Na0.16CdSb at 712 K. The study offers both intrinsic and extrinsic strategies for developing high-efficiency thermoelectric Zintl materials with extremely low lattice thermal conductivity.

Mechanism of high sensitivity proton acids doped polypyrrole molecularly imprinted electrochemical sensor and its application in urea detection.

Molecularly imprinted electrochemical sensor is a kind of convenient, fast, and stable analyzer, but the conductivity of electrode materials and their affinity with the analyte affect its performance. A proton acid (PSS, SA, SSA) doping method was proposed to improve the electrochemical performance of the polypyrrole molecularly imprinted polymer (PPy-MIP), which promoted the electropolymerization of pyrrole, reduced the charge transfer resistance, and increased the electrochemical surface area. In terms of both improving conductivity and affinity, the response of the proton acids doped the polypyrrole molecularly imprinted electrochemical sensors (PPy-MIECS) to urea was improved by 25-fold (PSS), 5-fold (SA), and 3-fold (SSA) over that of PPy-MIECS. In addition, the PSS-PPy-MIECS was validated for the practical application with a linear detection range from 0.1 mM to 100 mM, high selectivity (α = 39.73), reusability (RSD% = 4.54 %), reproducibility (RSD% = 0.93 %), and stability (11 days). The advantage of proton acid doping method in PSS-PEDOT-MIECS to urea and PSS-PPy-MIECS to glucose extended its application in the performance enhancement of MIECS design.

A DFT study of the adsorption behavior and sensing properties of CO gas on monolayer MoSe2 in CO2-rich environment.

CONTEXT: Carbon monoxide, also known as the "silent killer," is a colorless, odorless, tasteless, and non-irritable gas that, when inhaled, enters the bloodstream and lungs, binds with the hemoglobin, and blocks oxygen from reaching tissues and cells. In this work, the monolayer MoSe2-based CO gas sensors were designed using density functional theory calculation with several dopants including Al, Au, Pd, Ni, Cu, and P. Here, Cu and P were found to be the best dopants, with adsorption energies of -0.67 eV (Cu) and -0.54 eV (P) and recovery times of 1.66 s and 13.8 ms respectively. Cu conductivity for CO adsorption was found to be 2.74 times that of CO2 adsorption in the 1.0-2.26 eV range. P displayed the highest selectivity, followed by Pd and Ni. The dopants, Pd and Ni, were found suitable for building CO gas scavengers due to their high recovery times of 9.76 × 1020 s and 2.47 × 1011 s. Similarly, the adsorption of CO2 on doped monolayer MoSe2 was also investigated. In this study, it is found that monolayer MoSe2 could be employed to create high-performance CO sensors in a CO2-rich environment. METHOD: The electrical characteristics of all doped MoSe2 monolayers are obtained using a DFT calculation with the PBE-GGA method from the Quantum ESPRESSO package. The self-consistent field (SCF) computations were performed using a 7 × 7 × 1 k-point grid and a norm-conserving pseudo potential (NCPP) file. To determine electrical conductivity, the semi-classical version of Boltzmann transport theory, implemented in the Boltz Trap code, was used.

"Machine learning assisted understanding of the layer-thickness dependent thermal conductivity in fluorinated graphene".

Manipulating thermal conductivity (k) plays vital role in high-performance thermoelectric conversion, thermal insulation and thermal management devices. In this work, we using the machine learning-based interatomic potential and the phonon Boltzmann transport equation to systematically investigate layer thickness dependent thermal conductivity of fluorinated graphene (FG). We show that the lattice of FG can be significantly decreased with Bernal bilayer stacking. Surprisingly, the further increasing of stacking layer can no longer affect the thermal conductivity, however, the is increased in the bulk configuration. The variation of thermal conductivity can be attributed to the crystal symmetry change from P-3m1 (164) at single layer to P3m1 (156) at multilayer. The decreasing crystal symmetry from single layer to bilayer resulting stronger phonon scattering and thus leading a lower thermal conductivity. Moreover, we also show that the contribution of acoustic mode to κ decreases with the increase of layers, while the contribution of optical mode to κ is increased with increasing layers. These results provide a further understanding for the phonon scattering mechanism of layer thickness dependent thermal conductivity.

Modulating Surface Architecture and Electronic Conductivity of Li-rich Manganese-Based Cathode.

Li-rich manganese-based cathode (LRMC) has attracted intense attention to developing advanced lithium-ion batteries with high energy density. However, LRMC is still plagued by poor cyclic stability, undesired rate capacity, and irreversible oxygen release. To address these issues, herein, a feasible polyvinylidene fluoride (PVDF)-assisted interface modification strategy is proposed for modulating the surface architecture and electronic conductivity of LRMC by intruding the F-doped carbon coating, spinel structure, and oxygen vacancy on the LRMC, which can greatly enhance the cyclic stability and rate capacity, and restrain the oxygen release for LRMC. As a result, the modified material delivers satisfactory cyclic performance with a capacity retention of 90.22% after 200 cycles at 1 C, an enhanced rate capacity of 153.58 mAh g-1 at 5 C and 126.32 mAh g-1 at 10 C, and an elevated initial Coulombic efficiency of 85.63%. Moreover, the thermal stability, electronic conductivity, and structure stability of LRMC are also significantly improved by the PVDF-assisted interface modification strategy. Therefore, the strategy of simultaneously modulating the surface architecture and the electronic conductivity of LRMC provides a valuable idea to improve the comprehensive electrochemical performance of LRMC, which offers a promising reference for designing LRMC with high electrochemical performance.

Quasistatic approximation in neuromodulation.

We define and explain the quasistatic approximation (QSA) as applied to field modeling for electrical and magnetic stimulation. Neuromodulation analysis pipelines include discrete stages, and QSA is applied specifically when calculating the electric and magnetic fields generated in tissues by a given stimulation dose. QSA simplifies the modeling equations to support tractable analysis, enhanced understanding, and computational efficiency. The application of QSA in neuro-modulation is based on four underlying assumptions: (A1) no wave propagation or self-induction in tissue, (A2) linear tissue properties, (A3) purely resistive tissue, and (A4) non-dispersive tissue. As a consequence of these assumptions, each tissue is assigned a fixed conductivity, and the simplified equations (e.g., Laplace's equation) are solved for the spatial distribution of the field, which is separated from the field's temporal waveform. Recognizing that electrical tissue properties may be more complex, we explain how QSA can be embedded in parallel or iterative pipelines to model frequency dependence or nonlinearity of conductivity. We survey the history and validity of QSA across specific applications, such as microstimulation, deep brain stimulation, spinal cord stimulation, transcranial electrical stimulation, and transcranial magnetic stimulation. The precise definition and explanation of QSA in neuromodulation are essential for rigor when using QSA models or testing their limits.

In Situ Polymerized Zwitterionic Copolymer Ionic Gel Electrolytes with High Performance for Lithium-Ion Batteries.

Gel electrolytes are a promising research direction due to their high safety. However, its poor room temperature conductivity along with complex preparation process hinder its practical application. In this article, a type of zwitterionic gel electrolyte is prepared by in situ polymerization. The introduction of charged but nonmigrating zwitterionic copolymer in the polymer chain is beneficial to the dissociation of the lithium salt, improving the ion transport of the electrolyte on this account. At room temperature, the conductivity of lithium ion reaches 9.1 × 10-4 S cm-1, which contributes to achieve excellent electrochemical performance at high rates. The assembled Li|LiFePO4 cell also shows a capacity retention rate of 90.5% after 150 cycles at 0.5 C at room temperature as well as remarkable cycle stability at 1 C. These offer a novel tactic for the efficient and safe commercial application of lithium-ion batteries.