Environmentally Friendly Graphene Inks for Touch Screen Sensors

Graphene-based materials have attracted significant attention in many technological fields, but scaling up graphene-based technologies still faces substantial challenges. High-throughput top-down methods generally require hazardous, toxic, and high-boiling-point solvents. Here, an efficient and inexpensive strategy is proposed to produce graphene dispersions by liquid-phase exfoliation (LPE) through a combination of shear-mixing (SM) and tip sonication (TS) techniques, yielding highly concentrated graphene inks compatible with spray coating. The quality of graphene flakes (e.g., lateral size and thickness) and their concentration in the dispersions are compared using different spectroscopic and microscopy techniques. Several approaches (individual SM and TS, and their combination) are tested in three solvents (N-methyl-2-pyrrolidone, dimethylformamide, and cyrene). Interestingly, the combination of SM and TS in cyrene yields high-quality graphene dispersions, overcoming the environmental issues linked to the other two solvents. Starting from the cyrene dispersion, a graphene-based ink is prepared to spray-coat flexible electrodes and assemble a touch screen prototype. The electrodes feature a low sheet resistance (290 Ω □⁻¹) and high optical transmittance (78%), which provide the prototype with a high signal-to-noise ratio (14 dB) and multi-touch functionality (up to four simultaneous touches). These results illustrate a potential pathway toward the integration of LPE-graphene in commercial flexible electronics.     

Development of a Topical Insulin Polymeric Nanoformulation for Skin Burn Regeneration: An Experimental Approach

Insulin is a peptide hormone with many physiological functions, besides its use in diabetes treatment. An important role of insulin is related to the wound healing process—however, insulin itself is too sensitive to the external environment requiring the protective of a nanocarrier. Polymer-based nanoparticles can protect, deliver, and retain the protein in the target area. This study aims to produce and characterize a topical treatment for wound healing consisting of insulin-loaded poly-DL-lactide/glycolide (PLGA) nanoparticles. Insulin-loaded nanoparticles present a mean size of approximately 500 nm and neutral surface charge. Spherical shaped nanoparticles are observed by scanning electron microscopy and confirmed by atomic force microscopy. SDS-PAGE and circular dichroism analysis demonstrated that insulin preserved its integrity and secondary structure after the encapsulation process. In vitro release studies suggested a controlled release profile. Safety of the formulation was confirmed using cell lines, and cell viability was concentration and time-dependent. Preliminary safety in vivo assays also revealed promising results.     

Monthly Streamflow Modeling Based on Self-Organizing Maps and Satellite-Estimated Rainfall Data

Hydrological data provide valuable information for the decision-making process in water resources management, where long and complete time series are always desired. However, it is common to deal with missing data when working on streamflow time series. Rainfall-streamflow modeling is an alternative to overcome such a difficulty. In this paper, self-organizing maps (SOM) were developed to simulate monthly inflows to a reservoir based on satellite-estimated gridded precipitation time series. Three different calibration datasets from Três Marias Reservoir, composed of inflows (targets) and 91 TRMM-estimated rainfall data (inputs), from 1998 to 2019, were used. The results showed that the inflow data homogeneity pattern influenced the rainfall-streamflow modeling. The models generally showed superior performance during the calibration phase, whereas the outcomes varied depending on the data homogeneity pattern and the chosen SOM structure in the testing phase. Regardless of the input data homogeneity, the SOM networks showed excellent results for the rainfall-runoff modeling, presenting Nash–Sutcliffe coefficients greater than 0.90.

Graphical Abstract

     

Methodology for Estimating Streamflow by Water Balance and Rating Curve Methods Based on Logistic Regression

Both water balance (WB) and rating curve (RC) are methods for estimating streamflow. The first is mostly used to estimate reservoir outflows, while the second is usually adopted in hydrometeorological network streamflow gauges. While WB uses hourly collected data, the RC estimates streamflow using current water level and extrapolation techniques. The objective of this study was to analyze variations in the reservoir’s hourly outflow at Queimado Hydroelectric Power Plant (HPP Queimado) and to propose a method to evaluate whether the estimate of the daily outflows, obtained by the WB method, is similar to the flow values obtained at a conventional station. The logistic regression (LR) model was used because it is a method that adopts binary, categorically dependent variables to identify the event of interest. The results showed that the values of streamflow, obtained from an average of two daily readings, were a good representation of the flows in the region. The LR was able to identify atypical data, especially in the rainy season. This means that data consistency analysis can be faster and safer, when adequately employed and considering the proposed conditions, contributing to both management policies and the management of water resources.

     

Foliar Spraying of Silicon Associated with Salicylic Acid Increases Silicon Absorption and Peanut Growth

Silicon - Silicon (Si) combined with foliar spraying of salicylic acid (SA) can affect the absorption of this beneficial element. A study with Si non-accumulators plants (soybean and bean) observed...     

Designing optical glasses by machine learning coupled with a genetic algorithm

Engineering new glass compositions have experienced a sturdy tendency to move forward from (educated) trial-and-error to data- and simulation-driven strategies. In this work, we developed a computer program that combines data-driven predictive models (in this case, neural networks) with a genetic algorithm to design glass compositions with desired combinations of properties. First, we induced predictive models for the glass transition temperature (T_g) using a dataset of 45,302 compositions with 39 different chemical elements, and for the refractive index (n_d) using a dataset of 41,225 compositions with 38 different chemical elements. Then, we searched for relevant glass compositions using a genetic algorithm informed by a design trend of glasses having high n_d (1.7 or more) and low T_g (500 °C or less). Two candidate compositions suggested by the combined algorithms were selected and produced in the laboratory. These compositions are significantly different from those in the datasets used to induce the predictive models, showing that the used method is indeed capable of exploration. Both glasses met the constraints of the work, which supports the proposed framework. Therefore, this new tool can be immediately used for accelerating the design of new glasses. These results are a stepping stone in the pathway of machine learning-guided design of novel glasses.     

Analysis of stepwise charging limits and its implementation for efficiency improvement in switched capacitor DC–DC converters

In this work we analysed the stepwise charging technique to find the limits from which it is beneficial in terms of load capacitance and charge–discharge frequency. We included in the analysis practical limitations such as the consumption of auxiliary logic needed to implement the technique and the minimum size of auxiliary switches imposed by the technology. We proposed an ultra-low-power logic block to push these limits and to obtain benefits from this technique in small capacitances. Finally, we proposed to use a stepwise driver in the driving of the gate capacitance of power switches in switched-capacitor (SC) DC–DC converters. We designed and manufactured, in a 130 nm process, a SC DC–DC converter and measured a 29% energy reduction in the gate-drive losses of the converter. This accounts for an improvement of 4% (from 69 to 73%) in the overall converter efficiency.

     

Microwave hybrid fast sintering of red clay ceramics

This work aimed to examine the performance of the hybrid sintering of clay ceramic in a microwave furnace, compared to the sintering process in a conventional furnace. The raw materials were subjected to X-ray fluorescence, loss on ignition (LOI), X-ray diffraction, particle size distribution, real specific mass, and thermogravimetric analyses. The red clay ceramic mass was prepared, extruded, pre-sintered in a conventional furnace at 600°C/60 min, and sintered at temperatures between 700 °C and 1100 °C. The sintering conventional (resistive oven) was carried out for 60 min with a heating rate of 10°C/min. In the microwave furnace, the sintering times were 5, 10, and 15 min, with a heating rate of 50°C/min, with a sintering chamber coated with silicon carbide (susceptor). The sintered specimens were characterized according to linear shrinkage, water absorption, apparent porosity, apparent specific mass, X-ray diffraction, Raman spectroscopy analysis, spectroscopy analysis in the ultraviolet and visible regions, microhardness, and scanning electron microscopy. The results showed that microwave sintering promoted an increase in the microhardness and apparent specific mass, and reduction in water absorption and apparent porosity values, due to greater densification in the microstructure. The best results occurred for specimens sintered at 1100°C.     

A multimode CMOS PA with a single propagation path

Analog Integrated Circuits and Signal Processing - In this paper a four mode 130 nm RF CMOS power amplifier (PA) in a single propagation path topology is presented and evaluated with IEEE...     

Eugenol,citral, and hexanal,alone or in combination with heat,affect viability,biofilm formation,and swarming on Shiga-toxin-producing Escherichia coli

Shiga-toxin-producing Escherichia coli strains are pathogenic for humans and cause mild to severe illnesses. In this study, the antimicrobial effect of citral, eugenol, and hexanal in combination with heat shock (HS) was evaluated in terms of the growth, biofilm formation, swarming, and expression of virulence genes of STEC serotypes (O157:H7, O103, O111, and O26). Eugenol was the most effective compound against the growth of E. coli strains (MBC = 0.58 to 0.73 mg/mL), followed by citral (MBC = 0.86 to 1.26 mg/mL) and hexanal (MBC = 2.24 to 2.52 mg/mL). Biofilm formation and swarming motility have great variability between STEC strains. Natural compounds—alone or combined with HS—inhibited biofilm formation; however, swarming motility was induced by most treatments. The expression of the studied genes during biofilm formation and swarming under natural antimicrobials was affected but not in a uniform pattern. These treatments could be used to control contamination of STEC and inhibit biofilm formation.