Mesoscopic 3D Charge Transport in Solution-Processed Graphene-Based Thin Films: A Multiscale Analysis.

Graphene and related 2D material (GRM) thin films consist of 3D assembly of billions of 2D nanosheets randomly distributed and interacting via van der Waals forces. Their complexity and the multiscale nature yield a wide variety of electrical characteristics ranging from doped semiconductor to glassy metals depending on the crystalline quality of the nanosheets, their specific structural organization ant the operating temperature. Here, the charge transport (CT) mechanisms are studied that are occurring in GRM thin films near the metal-insulator transition (MIT) highlighting the role of defect density and local arrangement of the nanosheets. Two prototypical nanosheet types are compared, i.e., 2D reduced graphene oxide and few-layer-thick electrochemically exfoliated graphene flakes, forming thin films with comparable composition, morphology and room temperature conductivity, but different defect density and crystallinity. By investigating their structure, morphology, and the dependence of their electrical conductivity on temperature, noise and magnetic-field, a general model is developed describing the multiscale nature of CT in GRM thin films in terms of hopping among mesoscopic bricks, i.e., grains. The results suggest a general approach to describe disordered van der Waals thin films.

Regeneration and Long-Term Stability of a Low-Power Eco-Friendly Temperature Sensor Based on a Hydrogel Nanocomposite.

A water-processable and low-cost nanocomposite material, based on gelatin and graphene, has been used to fabricate an environmentally friendly temperature sensor. Demonstrating a temperature-dependent open-circuit voltage between 260 and 310 K, the sensor effectively detects subzero ice formation. Notably, it maintains a constant temperature sensitivity of approximately -19 mV/K over two years, showcasing long-term stability. Experimental evidence demonstrates the efficient regeneration of aged sensors by injecting a few drops of water at a temperature higher than the gelation point of the hydrogel nanocomposite. The real-time monitoring of the electrical characteristics during the hydration reveals the initiation of the regeneration process at the gelation point (~306 K), resulting in a more conductive nanocomposite. These findings, together with a fast response and low power consumption in the range of microwatts, underscore the potential of the eco-friendly sensor for diverse practical applications in temperature monitoring and environmental sensing. Furthermore, the successful regeneration process significantly enhances its sustainability and reusability, making a valuable contribution to environmentally conscious technologies.

Network analysis of drug prescriptions.

PURPOSE: Networks exist in many different aspects of the world, at social, economical, biological, and molecular levels. Network science studies their parameters, or quantitative indicators; its instruments make it possible to draw and analyze networks from a mathematical perspective. The present study is an attempt to apply network science techniques to the drug prescription process, a typical subject of Epidemiology for Public Health studies. METHODS: A drug prescription network was created using the set of drug prescriptions written during a 6-month period by a group of 99 general practitioners (GPs) operating in Italy. In this network, named co-prescription network, each drug represented a node, and different drugs prescribed to the same patient at the same moment were considered linked together. Drug prescription data for a total of 42 965 patients and 631 232 drug packages were studied. A number of co-prescription networks were obtained and analyzed on the basis of different subsets of patients by age and gender. The network parameters were measured and compared for the various subsets. RESULTS: All the drug prescription networks studied showed scale invariance behavior. The age- and gender-related co-prescription networks showed different patterns, with different levels of complexity. CONCLUSIONS: The present study shows that the drug prescription process has specific network aspects and dynamics and, more generally, that it is possible to apply instruments of network science to study public health phenomena from a new, different perspective. Further studies should be encouraged and performed.

Editorial for Special Issue "Electric Transport and Magnetic Properties in Nanomaterials and Thin Films".

Several nanomaterials and thin films have recently attracted much attention due to their peculiar electric transport and magnetic properties, such as the so-called magnetoresistance effect and the interplay between spin, orbital, charge, and structural degrees of freedom [...].

Low-Power and Eco-Friendly Temperature Sensor Based on Gelatin Nanocomposite.

An environmentally-friendly temperature sensor has been fabricated by using a low-cost water-processable nanocomposite material based on gelatin and graphene. The temperature dependence of the electrochemical properties has been investigated by using cyclic voltammetry, chronopotentiometry and impedance spectroscopy measurements. The simple symmetric device, composed of a sandwich structure between two metal foils and a printable graphene-gelatin blend, exhibits a dependence on the open-circuit voltage in a range between 260 and 310 K. Additionally, at subzero temperature, the device is able to detect the ice/frost formation. The thermally-induced phenomena occur at the electrode/gel interface with a bias current of a few tens of µA. The occurrence of dissociation reactions within the sensor causes limiting-current phenomena in the gelatin electrolyte. A detailed model describing the charge carrier accumulation, the faradaic charge transfer and diffusion processes within the device under the current-controlled has been proposed. In order to increase the cycle stability of the temperature sensor and reduce its voltage drift and offset of the output electrical signal, a driving circuit has been designed. The eco-friendly sensor shows a temperature sensitivity of about -19 mV/K, long-term stability, fast response and low-power consumption in the range of microwatts suitable for environmental monitoring for indoor applications.

Electrical conduction and noise spectroscopy of sodium-alginate gold-covered ultrathin films for flexible green electronics.

Green electronics is an emerging topic that requires the exploration of new methodologies for the integration of green components into electronic devices. Therefore, the development of alternative and eco-friendly raw materials, biocompatible and biodegradable, is of great importance. Among these, sodium-alginate is a natural biopolymer extracted from marine algae having a great potential in terms of transparency, flexibility, and conductivity, when functionalized with a thin gold (Au) layer. The electrical transport of these flexible and conducting substrates has been studied, by DC measurements, from 300 to 10 K, to understand the interplay between the organic substrate and the metallic layer. The results were compared to reference bilayers based on polymethyl-methacrylate, a well-known polymer used in electronics. In addition, a detailed investigation of the electric noise properties was also performed. This analysis allows to study the effect of charge carriers fluctuations, providing important information to quantify the minimum metallic thickness required for electronic applications. In particular, the typical noise behavior of metallic compounds was observed in samples covered with 5 nm of Au, while noise levels related to a non-metallic conduction were found for a thickness of 4.5 nm, despite of the relatively good DC conductance of the bilayer.

Electric Transport in Gold-Covered Sodium-Alginate Free-Standing Foils.

The electric transport properties of flexible and transparent conducting bilayers, realized by sputtering ultrathin gold nanometric layers on sodium-alginate free-standing films, were studied. The reported results cover a range of temperatures from 3 to 300 K. In the case of gold layer thicknesses larger than 5 nm, a typical metallic behavior was observed. Conversely, for a gold thickness of 4.5 nm, an unusual resistance temperature dependence was found. The dominant transport mechanism below 70 K was identified as a fluctuation-induced tunneling process. This indicates that the conductive region is not continuous but is formed by gold clusters embedded in the polymeric matrix. Above 70 K, instead, the data can be interpreted using a phenomenological model, which assumes an anomalous expansion of the conductive region upon decreasing the temperature, in the range from 300 to 200 K. The approach herein adopted, complemented with other characterizations, can provide useful information for the development of innovative and green optoelectronics.

Texture Analysis in the Evaluation of COVID-19 Pneumonia in Chest X-Ray Images: A Proof of Concept Study.

BACKGROUND: One of the most challenging aspects related to Covid-19 is to establish the presence of infection in an early phase of the disease. Texture analysis might be an additional tool for the evaluation of Chest X-ray in patients with clinical suspicion of Covid-19 related pneumonia. OBJECTIVE: To evaluate the diagnostic performance of texture analysis and machine learning models for the diagnosis of Covid-19 interstitial pneumonia in Chest X-ray images. METHODS: Chest X-ray images were accessed from a publicly available repository(https://www.kaggle. com/tawsifurrahman/covid19-radiography-database). Lung areas were manually segmented using a polygonal region of interest covering both lung areas, using MaZda, a freely available software for texture analysis. A total of 308 features per ROI was extracted. One hundred-ten Covid-19 Chest X-ray images were selected for the final analysis. RESULTS: Six models, namely NB, GLM, DL, GBT, ANN, and PLS-DA were selected and ensembled. According to Youden's index, the Covid-19 Ensemble Machine Learning Score showing the highest area under the curve (0.971±0.015) was 132.57. Assuming this cut-off the Ensemble model performance was estimated by evaluating both true and false positive/negative, resulting in 91.8% accuracy with 93% sensitivity and 90% specificity. Moving the cut-off value to -100, although the accuracy resulted lower (90.6%), the Ensemble Machine Learning showed 100% sensitivity, with 80% specificity. CONCLUSION: Texture analysis of Chest X-ray images and machine learning algorithms may help in differentiating patients with Covid-19 pneumonia. Despite several limitations, this study can lay the ground for future research works in this field and help to develop more rapid and accurate screening tools for these patients.

Prescribing Behavior of General Practitioners for Generic Drugs.

The factors influencing General Practitioners' (GPs) prescribing behavior are diverse in terms of health care policies and regulations, GPs' education and experience, demographic trends and disease profiles. Thus, it can be useful to analyze the specific local patterns, as they affect the quality of healthcare and the stability of the healthcare market. The aim of the present longitudinal retrospective study is to investigate the prescription of generic drugs in a database of about 4.6 million prescriptions from a sample of 38 GPs practicing in Salerno, Italy, within a timeframe of 15 years, from 2001 to 2015. The GPs in our study show a general tendency to increase prescriptions of generic drugs during the studied time span, to fulfill regulatory obligations and with some differences in prescription behavior according to age, gender and experience. The generics prescription depends also on the different diagnoses, with some diagnostic areas showing a greater generic drug prescription rate. Expanding this research to larger datasets would allow deepening the knowledge of the patterns of GPs' prescribing decisions, to provide evidence to be used in comparison between different national settings.

Iron-Based Superconducting Nanowires: Electric Transport and Voltage-Noise Properties.

The discovery of iron-based superconductors paved the way for advanced possible applications, mostly in high magnetic fields, but also in electronics. Among superconductive devices, nanowire detectors have raised a large interest in recent years, due to their ability to detect a single photon in the visible and infrared (IR) spectral region. Although not yet optimal for single-photon detection, iron-based superconducting nanowire detectors would bring clear advantages due to their high operating temperature, also possibly profiting of other peculiar material properties. However, there are several challenges yet to be overcome, regarding mainly: fabrication of ultra-thin films, appropriate passivation techniques, optimization of nano-patterning, and high-quality electrical contacts. Test nanowire structures, made by ultra-thin films of Co-doped BaFe2As2, have been fabricated and characterized in their transport and intrinsic noise properties. The results on the realized nanostructures show good properties in terms of material resistivity and critical current. Details on the fabrication and low temperature characterization of the realized nanodevices are presented, together with a study of possible degradation phenomena induced by ageing effects.

Magnetotransport and magnetic properties of amorphous [Formula: see text] thin films.

[Formula: see text] is an intermetallic compound with a bulk Curie temperature ([Formula: see text]) of 6-13 K. While existing studies have focused on [Formula: see text] crystals, amorphous thin-films of [Formula: see text] are potentially important since they would be magnetically soft without magnetocrystalline anisotropy, meaning that small external magnetic fields could reverse the direction of their magnetization. Here, we report [Formula: see text] thin-films with a thickness in the 5-200 nm range, deposited by DC magnetron sputtering onto Si(100). Films are amorphous with a weak temperature-dependent resistivity with values ranging between 150 and 300 [Formula: see text] cm. By means of noise spectroscopy, by analyzing the time-dependence of fluctuation-induced voltages, it is found that at low temperatures the resistance fluctuations are due to the Kondo effect. Volume magnetometry indicates [Formula: see text] K with a magnetic coercive field of 30 mT at 5 K for a 125-nm-thick film. The results are promising for the development of Ferromagnet(F)/Superconductor(S)/Ferromagnet(F) pseudo spin-valve devices based on amorphous [Formula: see text] thin films.

Current-Resistance Effects Inducing Nonlinear Fluctuation Mechanisms in Granular Aluminum Oxide Nanowires.

The unusual superconducting properties of granular aluminum oxide have been recently investigated for application in quantum circuits. However, the intrinsic irregular structure of this material requires a good understanding of the transport mechanisms and, in particular, the effect of disorder, especially when patterned at the nanoscale level. In view of these aspects, electric transport and voltage fluctuations have been investigated on thin-film based granular aluminum oxide nanowires, in the normal state and at temperatures between 8 and 300 K. The nonlinear resistivity and two-level tunneling fluctuators have been observed. Regarding the nature of the noise processes, the experimental findings give a clear indication in favor of a dynamic random resistor network model, rather than the possible existence of a local ordering of magnetic origin. The identification of the charge carrier fluctuations in the normal state of granular aluminum oxide nanowires is very useful for improving the fabrication process and, therefore, reducing the possible sources of decoherence in the superconducting state, where quantum technologies that are based on these nanostructures should work.

General Practitioners Records Are Epidemiological Predictors of Comorbidities: An Analytical Cross-Sectional 10-Year Retrospective Study.

BACKGROUND: Comorbidity represents the co-occurrence of pathological conditions in the same individual, and presents with very complex patterns. In most cases, reference data for the study of various types of comorbidities linked to complex diseases are those of hospitalized patients. Such patients may likely require cure due to acute conditions. We consider the emerging role of EHR (Electronic Healthcare Records), and study comorbidity patterns in a general population, focusing on diabetic and non-diabetic patients. METHODS: We propose a cross-sectional 10-year retrospective study of 14,958 patients and 1,728,736 prescriptions obtained from family doctors, and thus refer to these data as General Practitioner Records (GPR). We then choose networks as the tools to analyze the diabetes comorbidity patterns, distinguished by both prescription type and main patient characteristics (age, gender). RESULTS: As expected, comorbidity increases with patients' age, and the network representations allow the assessment of associations between morbidity groups. The specific morbidities present in the diabetic population justify the higher comorbidity patterns observed in the target group compared to the non-diabetic population. CONCLUSIONS: GPR are usually combined with other data types in EHR studies, but we have shown that prescription data have value as standalone predictive tools, useful to anticipate trends observed at epidemiological level on large populations. This study is thus relevant to policy makers seeking inference tools for an efficient use of massive administrative database resources, and suggests a strategy for detecting comorbidities and investigating their evolution.

Correlation between Electronic Defect States Distribution and Device Performance of Perovskite Solar Cells.

In the present study, random current fluctuations measured at different temperatures and for different illumination levels are used to understand the charge carrier kinetics in methylammonium lead iodide CH3NH3PbI3-based perovskite solar cells. A model, combining trapping/detrapping, recombination mechanisms, and electron-phonon scattering, is formulated evidencing how the presence of shallow and deeper band tail states influences the solar cell recombination losses. At low temperatures, the observed cascade capture process indicates that the trapping of the charge carriers by shallow defects is phonon assisted directly followed by their recombination. By increasing the temperature, a phase modification of the CH3NH3PbI3 absorber layer occurs and for temperatures above the phase transition at about 160 K the capture of the charge carrier takes place in two steps. The electron is first captured by a shallow defect and then it can be either emitted or thermalize down to a deeper band tail state and recombines subsequently. This result reveals that in perovskite solar cells the recombination kinetics is strongly influenced by the electron-phonon interactions. A clear correlation between the morphological structure of the perovskite grains, the energy disorder of the defect states, and the device performance is demonstrated.

Noise-induced dephasing of an ac-driven Josephson junction.

We consider the phase-locked dynamics of a Josephson junction driven by finite-spectral-linewidth ac current. By means of a transformation, the effect of frequency fluctuations is reduced to an effective additive noise, the corresponding (large) dephasing time being determined, in the logarithmic approximation, by the Kramers expression for the lifetime. For sufficiently small values of the drive's amplitude, direct numerical simulations show agreement of the dependence of the dephasing activation energy on the ac drive's spectral linewidth and amplitude with analytical predictions. Solving the corresponding Fokker-Planck equation analytically, we find a universal dependence of the critical value of the effective phase-diffusion parameter on the drive's amplitude at the point of sharp transition from the phase-locked state to an unlocked one. However, for large values of the drive amplitude, saturation and subsequent decrease of the activation energy are revealed by simulations, which cannot be accounted for by the perturbative analysis. The same effect is found for a previously studied case of ac-driven Josephson junctions with intrinsic thermal noise. The predicted effects are relevant to applications to voltage standards, as they determine the stability of the Josephson phase-locked state.