Quantifying defects in graphene via Raman spectroscopy at different excitation energies.

We present a Raman study of Ar(+)-bombarded graphene samples with increasing ion doses. This allows us to have a controlled, increasing, amount of defects. We find that the ratio between the D and G peak intensities, for a given defect density, strongly depends on the laser excitation energy. We quantify this effect and present a simple equation for the determination of the point defect density in graphene via Raman spectroscopy for any visible excitation energy. We note that, for all excitations, the D to G intensity ratio reaches a maximum for an interdefect distance ∼3 nm. Thus, a given ratio could correspond to two different defect densities, above or below the maximum. The analysis of the G peak width and its dispersion with excitation energy solves this ambiguity

Avaliação de parâmetros associados à qualidade e produtividade em cana-de-açúcar.

O objetivo do trabalho foi avaliar diversos parâmetros associados com a produtividade e qualidade da cana-de-açúcar e identificar quais são os mais importantes para explicar a variabilidade no conjunto de dados coletados a campo bem como, identificar a relação entre eles.Evento online. CIIC 2021

Optical-phonon resonances with saddle-point excitons in twisted-bilayer graphene

Twisted-bilayer graphene (tBLG) exhibits van Hove singularities in the density of states that can be tuned by changing the twisting angle $\theta$. A $\theta$-defined tBLG has been produced and characterized with optical reflectivity and resonance Raman scattering. The $\theta$-engineered optical response is shown to be consistent with persistent saddle-point excitons. Separate resonances with Stokes and anti-Stokes Raman scattering components can be achieved due to the sharpness of the two-dimensional saddle-point excitons, similar to what has been previously observed for one-dimensional carbon nanotubes. The excitation power dependence for the Stokes and anti-Stokes emissions indicate that the two processes are correlated and that they share the same phonon.Comment: 5 pages, 6 figure

Utilização de índices de vegetação espectrais na predição da produtividade em cana-de-açúcar.

O objetivo deste estudo foi verificar o efeito das variáveis preditoras do tipo índices de vegetação espectrais Normalized Difference Vegetation Index (NDVI) e Visible Atmospherically Resistant Index (VARI), calculados a partir de imagens de drones, sobre a variável de interesse (variável resposta) que no caso foi a produtividade final da lavoura de cana-de-açúcar

Development and validation of a model based on vegetation indices for the prediction of sugarcane yield.

This study aimed to develop a predictive model for sugarcane production based on data extracted from aerial imagery obtained from drones or satellites, allowing the precise tracking of plant development in the field

Clar's Theory, STM Images, and Geometry of Graphene Nanoribbons

We show that Clar's theory of the aromatic sextet is a simple and powerful tool to predict the stability, the \pi-electron distribution, the geometry, the electronic/magnetic structure of graphene nanoribbons with different hydrogen edge terminations. We use density functional theory to obtain the equilibrium atomic positions, simulated scanning tunneling microscopy (STM) images, edge energies, band gaps, and edge-induced strains of graphene ribbons that we analyze in terms of Clar formulas. Based on their Clar representation, we propose a classification scheme for graphene ribbons that groups configurations with similar bond length alternations, STM patterns, and Raman spectra. Our simulations show how STM images and Raman spectra can be used to identify the type of edge termination

Single-layer graphene modulates neuronal communication and augments membrane ion currents

The use of graphenebased materials to engineer sophisticated biosensing interfaces that can adapt to the central nervous system requires a detailed understanding of how such materials behave in a biological context. Graphene's peculiar properties can cause various cellular changes, but the underlying mechanisms remain unclear. Here, we show that singlelayer graphene increases neuronal firing by altering membraneassociated functions in cultured cells. Graphene tunes the distribution of extracellular ions at the interface with neurons, a key regulator of neuronal excitability. The resulting biophysical changes in the membrane include stronger potassium ion currents, with a shift in the fraction of neuronal firing phenotypes from adapting to tonically firing. By using experimental and theoretical approaches, we hypothesize that the graphene\u2013ion interactions that are maximized when singlelayer graphene is deposited on electrically insulating substrates are crucial to these effects