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.     

On the efficiency of quantization-based integration methods for building simulation

Models describing energy consumption, heating, and cooling of buildings usually impose difficulties to the numerical integration algorithms used to simulate them. Stiffness and the presence of frequent discontinuities are among the main causes of those difficulties, that become critical when the models grow in size. Quantized State Systems (QSS) methods are a family of numerical integration algorithms that can efficiently handle discontinuities and stiffness in large models. For this reason, they are promising candidates for overcoming the mentioned problems. Based on this observation, this article studies the performance of QSS methods in some systems that are relevant to the field of building simulation. The study includes a performance comparison of different QSS algorithms against state-of-the-art classic numerical solvers, showing that the former can be more than one order of magnitude faster.     

CNBP Binds and Unfolds In Vitro G-Quadruplexes Formed in the SARS-CoV-2 Positive and Negative Genome Strands

The Coronavirus Disease 2019 (COVID-19) pandemic has become a global health emergency with no effective medical treatment and with incipient vaccines. It is caused by a new positive-sense RNA virus called severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2). G-quadruplexes (G4s) are nucleic acid secondary structures involved in the control of a variety of biological processes including viral replication. Using several G4 prediction tools, we identified highly putative G4 sequences (PQSs) within the positive-sense (+gRNA) and negative-sense (−gRNA) RNA strands of SARS-CoV-2 conserved in related betacoronaviruses. By using multiple biophysical techniques, we confirmed the formation of two G4s in the +gRNA and provide the first evidence of G4 formation by two PQSs in the −gRNA of SARS-CoV-2. Finally, biophysical and molecular approaches were used to demonstrate for the first time that CNBP, the main human cellular protein bound to SARS-CoV-2 RNA genome, binds and promotes the unfolding of G4s formed by both strands of SARS-CoV-2 RNA genome. Our results suggest that G4s found in SARS-CoV-2 RNA genome and its negative-sense replicative intermediates, as well as the cellular proteins that interact with them, are relevant factors for viral genes expression and replication cycle, and may constitute interesting targets for antiviral drugs development.     

Deconvoluting Energy Transport Mechanisms in Metal Halide Perovskites Using CsPbBr3 Nanowires as a Model System

Understanding energy transport in metal halide perovskites is essential to effectively guide further optimization of materials and device designs. However, difficulties to disentangle charge carrier diffusion, photon recycling, and photon transport have led to contradicting reports and uncertainty regarding which mechanism dominates. In this study, monocrystalline CsPbBr₃ nanowires serve as 1D model systems to help unravel the respective contribution of energy transport processes in metal-halide perovskites. Spatially, temporally, and spectrally resolved photoluminescence (PL) microscopy reveals characteristic signatures of each transport mechanism from which a robust model describing the PL signal accounting for carrier diffusion, photon propagation, and photon recycling is developed. For the investigated CsPbBr₃ nanowires, an ambipolar carrier mobility of μ = 35 cm² V⁻¹ s⁻¹ is determined, and is found that charge carrier diffusion dominates the energy transport process over photon recycling. Moreover, the general applicability of the developed model is demonstrated on different perovskite compounds by applying it to data provided in previous related reports, from which clarity is gained as to why conflicting reports exist. These findings, therefore, serve as a useful tool to assist future studies aimed at characterizing energy transport mechanisms in semiconductor nanowires using PL.     

Highly Sensitive Sensors for the Detection of Nitro Compounds Based on Pyrene Labeled Dendrons

In this paper, we describe the synthesis and characterization of four novel pyrene labeled compounds, some of them dendritic, which can act as potential sensors for the detection of nitro compounds in methanol solution. Methanol was selected as solvent due to its polar properties, which provide similar characteristics to water. The obtained pyrene labeled molecules (PyOH, Pytb, PyNK1OH and PyNK1tb) were studied by UV–Vis and steady state fluorescence spectroscopy. Their application as sensors has been tested with three different nitro compounds: nitrobenzene, 1-chloro-2,4-dinitrobenzene and nitromethane. PyOH and Pytb showed a detection concentration limit for the analyzed quenchers in the order of nM, making these compounds suitable for high-sensitive sensoring. PyNK1OH and PyNK1tb displayed high sensibility at µM concentration. All the sensors showed an accurate response towards quencher analytes.     

Color evolution during a coating process of pharmaceutical tablet cores by random spraying

Placebo white tablet cores (lactose anhydrous [47.6%], corn starch [23.8%], microcrystalline cellulose [19.1%], polyvinylpyrrolidone [7.9%], magnesium stearate [0.8%], and talcum powder [0.8%]) were coated with a colorant (hydroxypropyl methylcellulose [8% w/v], titanium dioxide [0.2% w/v], FD&C yellow No. 6 with aluminum lacquer [0.8% w/v], polyethylene glycol 4000 [0.4% w/v], and purified water [q.s.p. 100 mL]) using a random spraying method during 130 minutes. During the coating process, batches of 21 samples were extracted every 10 minutes and measured with a DigiEye imaging system. The initial cores showed very similar and uniform colors (Mean Color Difference from the Mean [MCDM] of 0.8 CIELAB units), but partially coated tablets showed lower uniformity (MCDM below 2.0 CIELAB units). There was a high color variability (MCDM about 4.0 CIELAB units) among tablets of the same batch in the period between 10 and 30 minutes, which decreased as the coating process progressed, until achieving a final acceptable value (MCDM below 2.0 CIELAB units). During the coating process, L^* decreased, C^*_ab strongly increased, and h _ab remained nearly constant (disregarding results at 0 and 10 minutes). CIELAB and CIEDE2000 color differences (mainly chroma differences) with respect to the initial color of the tablets were modeled as a function of time by exponential functions with three coefficients. The color change in the interval from 90 to 130 minutes (4.3 CIELAB units, or 2.6 CIEDE2000 units), may be considered negligible bearing in mind the color variability in the batches of 21 samples and typical values of visual color thresholds.