Ciência e Natura

Sustainable petrochemical plataform from Elephant Grass

Regiani Crystina Barbazelli — 2025-03-14

The objective of this research is to demonstrate the potential of elephant grass (Pennisetum purpureum Schum) as biomass for obtaining other value-added byproducts, such as biofuels, lignocellulosic ethanol, adsorbents, among others. Through the pyrolysis process, biochar and bio-oil with average yields of 24.45% and 4.92% were produced, respectively The main components found in the bio-oil were carboxylic acids (64.47%), followed by esters (19.74%). The carbohydrate adsorption percentage observed in the biochar was lower than that found in commercial activated carbon, which is desirable in the food industry. Through scanning electron microscopy (SEM), it was possible to observe that the biochar consists of non-uniform particles with numerous pores, suggesting its potential use as an adsorbent material. The (BET and LANGMUIR) surface area values did not yield significant results; however, there was an increase in pore size after the pyrolysis process. The glucose content found in this study was 70.33%, and the reducing sugar content was 14.24 g.L^-1. Based on the theoretical yield calculations for 2G ethanol, it is possible to infer a potential production of 0.88 tons of 2G ethanol per hectare of elephant grass planted per year. The calculated theoretical yield for levulinic acid (LA) was 35.16%, and for formic acid (FA), it was 14.07%. It is worth noting that the use of such waste for the production of biochar and bio-oil represents a promising and cost-effective alternative, as elephant grass is currently highlighted among the most exploited crops for energy purposes.

Enhanced antioxidant and antimicrobial properties of lyophilized vitamin c concentrates from Malpighia emarginata (acerola): a comparative study

Flavia Maria Comachio — 2024-11-01

Vitamin C (Vit C) plays beneficial roles in the human body and has been used as a natural preservative in foods. However, there are no technological prospecting studies aimed at producing Vit C concentrates from Malpighia emarginata (acerola) nor antioxidant and antimicrobial evaluations of these products. In this context, this study aimed to compare Vit C concentrates obtained from acerola through two different drying methods (spray drying and freeze-drying), evaluating these preparations’ antioxidant and antimicrobial activities. The concentration of Vit C and phytochemical analyses were performed using chromatographic (HPLC) and spectroscopic (ESI-IT-MSn) methods. The antimicrobial activity was evaluated by microdilution and diffusion in a solid medium. Chemical analyses revealed the presence of six compounds, including Vit C and anthocyanins, considered markers for this species. The Vit C content was higher for freeze-drying compared to spray drying (16.30% and 10.74%, respectively). In the Minimum Inhibitory Concentration (MIC) test, the freeze-dried product also showed better activity against Escherichia coli and Staphylococcus aureus compared to the spray-dried product (0.0078 and 0.0312 g/mL, respectively). In the solid medium, both concentrates were active. The concentrates also showed antioxidant effects by the DPPH method. The results of this study provide convincing evidence that freeze-drying M. emarginata results in a higher concentration of Vit C and has promising antioxidant and antimicrobial effects.

Inventory of greenhouse gas (GHG) emissions from the modal system on the port cargo route of Santa Catarina

Gabriela Lamim — 2025-03-14

Climate change has intensified in recent decades due to the increase in the concentration of greenhouse gases (GHG) arising mainly from human activities. The transport sector is one of those responsible for the increase in these concentrations, due to the incomplete burning of fossil fuels in the use of different modals, such as road and railway. However, these modals are very important for the Brazilian production flow, product imports, as well as other human needs and development. Considering these facts, the present study inventoried the greenhouse gas emissions of the modal system on the port cargo route of Santa Catarina. With this purpose, movement data of Santa Catarina´s ports, road and railway modals data were used, referring to 2020 year. The data were analyzed using the Brazilian greenhouse gas protocol tool - GHG Protocol (Scope 1), 2022 version. In addition to the base data, five other scenarios were analyzed, considering different increments that encourage the railway use expansion as a strategy to reduce emissions. As a result, a reduction in carbon dioxide equivalent (CO₂e) emissions was observed when using the rail modal compared to the road modal, since, when comparing scenario 5 (50% rail + 50% road) with the current scenario (12.1% rail + 87.9% road), there is a 43% reduction in emissions from the road sector. Such findings make clear the importance of encouraging strategic planning and investments to promote intermodality and optimize logistical efficiency in Santa Catarina through the transport matrix diversification as a way of promoting sustainability.

Mathematical modeling of monodisperse nanoparticle concentration in aerosols subject to electric field using the Poisson–Nernst–Planck equation

Fran Sérgio Lobato — 2025-03-14

In recent decades, the study of particulate materials has gained significant attention from the scientific community. This is due to applications that can be developed, among which we can cite the risks to human health and the environment. As a consequence of this concern, classifying nanoparticles is a topic of considerable interest. One of the most used devices to classify nanoparticles in aerosols is the Differential Mobility Analyzer. From a mathematical point of view, particle concentration profiles have been obtained, preferably, considering constitutive relationships. In this contribution, the Poisson–Nernst–Planck equation is used to determine the concentration of monodisperse nanoparticles in aerosols subjected to an electric field. For this purpose, an inverse problem is proposed and solved considering real data and the Differential Evolution algorithm as an optimization tool. The results demonstrate that the proposed methodology was able to obtain good estimates considering the phenomenological model in relation to experimental points, as well as accurate estimates for intermediate profiles considering the Kriging approach. Finally, it is important to mention that the novelty of this contribution lies in predicting the concentration of monodisperse nanoparticles in aerosols subjected to an electric field using the Poisson–Nernst–Planck equation.

Pick's Theorem in two-dimensional lattices

Eleonesio Strey — 2025-03-14

In this article, a generalization of Pick's Theorem is presented, which establishes an expression for the area of simple polygons whose vertices are points of an arbitrary two-dimensional lattice, in terms of the determinant and the number of lattice points inside the polygon and on its boundary.

Geometry of a navigation problem: the $\lambda-$Funk Finsler Metrics

Newton Mayer Solórzano Chávez — 2025-03-14

We investigate the travel time in a navigation problem from a geometric perspective, with respect to a new class of Finsler metrics. We present the λ−Funk Finsler Metrics. The setting involves an open disk centered at the origin, representing a circular lake perturbed by a symmetric wind flow proportional to the distance from the origin with proportionality factor λ. The Randers metric, which is an important Finsler metric, derived from this physical problem, generalizes the well-known Euclidean metric (λ = 0) on the Cartesian plane and the Funk metric on the unit disk (λ = 1). We obtain the formula for distance, or travel
time, from point to point, and the circumference equations. In addition, we obtain the distance formulas from point to line and vice versa.

Cultivation of Tagetes patula L. in copper contaminated soils

Leandra de Carvalho Lacerda — 2025-03-14

Leaf quality is one of the most valued commercial parameters in the cultivation of flowers and ornamental plants in vases, with soil or substrate conditions playing a fundamental role in its successful practice. Thus, the objective of this study was to evaluate the vegetative development of marigold (Tagetes patula L.) cultivated in soils contaminated by Cu, seeking to verify its soil phytoremediation potential for an agriculture with low environmental impact. The experiment took place in a greenhouse, using a completely randomized, 5x2 factorial design (added levels of Cu in the soil: 0 (no addition: control), 250, 500, 750 and 1,000 mg kg^-1 of copper sulfate and soil pH corrections: 5.5 and 6.0, according to soil analysis report), with five replications. This work evaluated phytotechnical parameters and translocation factors, bioaccumulation, bioconcentration and Cu extraction rate in plants. It was observed that the development of marigold plants was similar on both soil pH corrections according to the addition of Cu, affecting the aesthetic quality of the plants. In this context, it is concluded that the marigold species is tolerant to the cultivation in soils with excess Cu and is characterized as a Cu extracting plant, with low soil phytoremediation potential.

Clustering of spatio-temporal precipitation patterns in the Legal Amazon using deep convolutional autoencoder

Vander Augusto Oliveira da Silva — 2025-03-14

Identifying patterns in precipitation time series in a given region is fundamental for its socioeconomic development. Many studies on this topic have been carried out in Brazil, mainly in the Amazon region. This research aimed at the development of a computational method for analyzing time series of precipitation using machine learning techniques, aiming at a method capable of extracting complex characteristics from the data, obtaining a map of attributes in low dimensionality for pattern recognition and discovery of homogeneous regions with respect to precipitation in the Legal Amazon. The proposed model is trained to learn the main and most complex characteristics of the original data and present them in low dimensionality in latent space. After training, the observations of the reconstructed data showed good performance as evaluated by the RMSE and NRMSE metric with resulting values equal to 0.06610 and 0.3355 respectively. The result of the low-dimensional representation of the data was analyzed by a clustering structure using hierarchical clustering with Ward's method. This methodology carried out consistent groupings characterizing homogeneous regions in relation to precipitation data. In this way, demonstrating that the representation in low dimensionality carried the main characteristics of the time series of the studied data.

Prediction of corn genetic bases grain productivity by phenological and meteorological variables

Murilo Vieira Loro — 2025-03-14

The objective of this study was to determine if it is possible to predict the grain yield of maize genotypes using phenological and meteorological variables. An experiment was conducted with maize genotypes at five sowing dates. On the first sowing date (September 21, 2021) 71 genotypes were sown (46 single hybrids, 14 triple hybrids, 3 double hybrids and 8 varieties). In the other four sowing dates (October 20, 2021, November 20, 2021, December 20, 2021 and January 30, 2022) 78 genotypes were sown (47 single hybrids, 15 triple hybrids, 8 double hybrids and 8 varieties). For each genotype and sowing date, the phenological variables, grain yield, accumulated global solar radiation and the thermal sum in the vegetative and reproductive stages were obtained. For each maize genetic base, principal component analysis was applied and the parameters of the regression tree algorithm for predicting grain yield as a function of phenological and meteorological variables were estimated. The global solar radiation accumulated in the vegetative and reproductive stages is the main variable that determines the grain yield of triple and double hybrids; and simple hybrids and maize varieties, respectively.

Making chocolate sweets and the statistical analysis of experimental data

Joyce Laura da Silva Gonçalves — 2024-04-26

This is a didactic proposal for the introduction of data processing concepts using typical Brazilian chocolate sweets, called brigadeiros. The methodology consisted of distributing a packaging of brigadeiro to each of the groups: blue, orange and green. The groups had to make the brigadeiros in the dimensions they wanted, proceeding with their quantification and weighing. Statistical analysis was based on hypothesis tests (p<0.05) in which the average mass of sweets obtained by the groups was compared in relation to the reference value and the performance of the groups among themselves. It was observed that 29, 20 and 16 sweets were made with average masses of 16.4±2.2; 24.6±4.5 and 28.5±8.7g for the blue, orange and green groups, respectively. The groups' precision and accuracy were blue>orange>green. The unpaired t-test, confidence interval for the mean and ANOVA suggested a significant difference between all groups. However, Tukey's test identified only the brigadeiros in the blue group as different from the other groups. In addition to the insertion of statistical concepts, carrying out this didactic proposal can stimulate teaching practice, involving the student and promoting meaningful learning. This experiment is fast, practical and inexpensive, and can be applied at any level and/or area of knowledge.