EDITORIAL

There is currently a strong UN and IPCC-led campaign promoting the rejection of oil-derived fuels because of the risk of global warming. However, global demand for oil does not decline, but tends to increase to 100 million barrels per day in 2018 according to the International Energy Agency (IEA). This clearly demonstrates that a speech is not enough, but new sources of energy are needed that can unequivocally replace oil from a technical and economic point of view. In this context, one of the possible solutions is the introduction of biorefineries, which have the capacity to process biomass from different sources, generating several products and fuels derived from biomass. An example of biorefinery is the production of ethanol from sugarcane bagasse, where all sugarcane biomass is harvested for ethanol generation. However, the processes involving biorefineries are still in laboratory or pilot scale, because these processes are not yet economically feasible. One of the crucial bottlenecks of a biorefinery is the energy cost of the processes involved, which is often greater than the energy gain obtained. One way to reduce the energy costs of these processes is thermodynamic optimization. For this, mathematical models are needed that are capable of describing all the processes that occur within a biorefinery. Unfortunately, there is no such tool available, which makes thermodynamic optimization of biorefinery impossible. However, for oil refining, this tool is already available even in the form of commercial software such as Aspen Plus, after all petroleum refining is an industry more than a hundred years old and so the exploitation of oil is so profitable. If biorefineries want to compete with the oil industry, it is necessary to develop simulation tools that can be used for thermodynamic optimization, so that the processes of a biorefinery become economically feasible

MODELING AND SIMULATION OF COMPRESSION-IGNITION INTERNAL COMBUSTION ENGINES’ EMISSIONS PRODUCED BY DIESEL AND BIODIESEL MIXTURES

Biofuels have been identified as possible solutions to the problems caused by the usage of fossil fuels in energy production. Although they generally produce fewer emissions, there are indications that engines powered with biodiesel mixtures emit pollutants such as nitrogen oxides in greater quantities than when powered by fossil diesel. So, further investigation on the emissions produced by these two fuels is needed, with the goal of best knowing what kind of harm to the environment each one of those is causing.  One of the best tools available for expanding any subject’s comprehension, without spending lots of resources, are mathematical models. In order to better understand the relations between the fuel used to power a compression-ignition internal combustion engine (ICO) and the emissions produced as subproducts of the thermodynamic process, this paper aims at developing a mathematical model of the production of emissions according to the fuel mixture used. The main goal is to develop a simple model, from the point of view of chemical kinetics, but with the support of well-collected experimental data, and methods of mathematical model adjustments and validations, to make the model describe the reality of the phenomena with satisfactory precision. This Mathematical Model is completely implemented using FORTRAN® Language. There are 2 sorts of data: one used to calibrate and adjust the model’s constants so the model can properly describe the reality of the events, and the other as the basis of comparison for the validation of the model after adjustments and calibrations. With this work, it is expected that the knowledge about how the use of these fuels impact global emissions, and how it is possible to optimize our energy production by using the best mixture of fuels at the optimal point between net power outtake and net emissions produced

SUSTAINABLE ALKALINE MEMBRANE FUEL CELL

This work proposes a sustainable alkaline membrane fuel cell (SAMFC) comprising a traditional AMFC coupled to a hydrogen generation reactor. The reactor uses recycled aluminum from soda cans to split the water molecule via oxidation catalyzed by NaOH, and an innovative cellulose membrane eliminates the undesirable characteristics of liquid electrolytes and asbestos or ammonia---common constituents of alkaline electrolyte membranes that are toxic and carcinogenic. Oxygen is supplied to the cell by first directing the ambient air through KOH aqueous solution to remove CO2 and thus to avoid the formation of K­2CO3. In this paper, an SAMFC system with one unitary cell, reactor, and CO2 purifier was designed, built, and tested in the laboratory, and the system was compared experimentally against traditional AMFCs driven by commercial hydrogen and by the hydrogen derived from commercial aluminum. According to experimental polarization and power curves, the SAMFC delivered 0.9V in open circuit and approximately 0.42W of maximum power with recycled aluminum. The study thereby demonstrates the economic potential and competitive performance of the proposed SAMFC against traditional fuel cells

Alkaline membrane fuel cell (AMFC) stack modeling and simulation

Paper presented to the 10th International Conference on Heat Transfer, Fluid Mechanics and Thermodynamics, Florida, 14-16 July 2014.This paper aims to produce a dynamic model that is computationally fast to predict the response of the AMFC stack according to variations of physical properties of the materials, and operating and design parameters. The model is based on electrochemical principles, and mass, momentum, energy and species conservation. It also takes into account pressure drop in the headers, single cells gas channels and the temperature gradient with respect to space in the flow direction. The simulation results comprise temperature distribution, net power, polarization and efficiency curves. Therefore, the model is expected to be a useful tool for AMFC stack control, design and optimization purposes after adjustment and experimental validation.cf201

ENERGY ANALYSIS OF LIPID EXTRACTION OF Scenedesmus sp. PRODUCED IN PILOT SCALE

he production of biodiesel from lipids extracted from microalgae biomass is a promising approach to biofuels. However, this approach is still not commercialized because of the high costs of processes associated with, for example, time consumption and / or biomass drying with intense energy usage. However, it was not possible to show extraction methods among the lipids existing in the literature, which could be applied specifically to the extraction of lipids from the microalgae Scenedesmus sp. from the large-scale wet biomass, which is the current challenge faced by the Center for Research and Development of Sustainable Energy Auto (NPDEAS). Therefore, in this study, the possibility of avoiding the drying process, and extracting lipids directly from humid biomass, using the saponification method, was tested and compared with conventional Bligh and Dyer extraction (B & D). This study introduced the cultivation of microalgae Scenedesmus sp. compact tubular photobioreactors 12 m3 in area 10 m2 (8 x 5 x 2 m). The classical method of lipid extraction from microalgae - B & D - brings many pigments and polar lipids that exist in the biomass and the conversion rate was only 65-66%, whereas the recovery of fatty material in the wet biomass by the saponification method showed high conversion rate (90-95%). Therefore, the saponification process showed a high recovery of fatty acids that can be easily converted into biodiesel by esterification, and it was shown that the stage of drying the biomass can be removed without losing the fatty acids. In relation to the energy usage in the process, it was shown that drying the biomass for extraction of fatty acids uses more energy than that produced in the final product, biodiesel, showing that the removal of fatty acids of the wet biomass is of strategic importance to the viability of microalgae biodiesel

EXERGETIC OPTIMIZATION OF AN ABSORPTION REFRIGERATION

Nowadays, several scientific studies aim to improve the refrigeration systems commonly used to reduce the consumption of electric energy as well as the environmental impact caused by this equipment. However, it is desired that this be done together with increased efficiency and reduced production cost of the system. Absorption refrigeration systems offer this opportunity to save energy, as they can use thermal energy to produce, residual heat and geothermal energy as primary energy. In addition, they use very ecological working fluids, drawing the attention of the scientific academic world in recent decades. Currently, thermodynamic analyzes based on exergy are increasingly being implemented to calculate the performance of thermodynamic systems, where just considering COP as an efficiency parameter is no longer sufficient. The exergetic analysis takes into account the irreversibility of the system and can indicate which components need to be improved to have a better system performance. Taking this into account, this paper presents the modeling and exergetic optimization of an absorption refrigeration system that uses ammonia and water as working fluids. The thermodynamic model of the refrigerator was developed based on the principles of mass and energy conservation under the steady-state, and was implemented using the Engineering Equation Solver (EES) software. Regarding the performance of the modeled refrigerator, a value of COP = 0.4571. A parametric analysis of the system was carried out with the results obtained numerically from the proposed model, where the relevance of some operating parameters for the performance coefficient and the exergetic efficiency of the system was evaluated. An exergetic analysis of the system was also carried out, where it was shown that the generator and the absorber are responsible for 56.4% and 29.2%, respectively of the total destroyed exergy. Moreover, based on the proposed thermodynamic model, an exergetic optimization of the cooling system was performed based on parameters such as generator temperature and absorber pressure. Thus, it can be concluded that the model developed can be used as a useful tool in the study of absorption chillers possible to predict the impact on the system performance, taking into account various operating conditions

MATHEMATICAL MODELING AND SIMULATION OF CO2 REMOVAL FROM AN ALKALINE SOLUTION FOR FUEL CELLS APPLICATIONS

In order to reduce oil dependency and reduce CO2 emissions stabilizing the greenhouse effect on the planet, the search for new renewable energy sources has been intensified, with a particular interest in hydrogen based solutions. Hydrogen can be used in fuel cells, which have several applications. Fuel Cells are among the environmentally friendly energy conversion systems for the 21st century with simple components such as membrane, catalyst, rearrangeable configurations that allow them to accommodate space limitations, and their use of hydrogen and oxygen. There are many types of fuel cells that are distinguished by the electrolyte type and their operating temperature. Alkaline Membrane Fuel Cells (AMFCs) and Proton-Exchange Membrane Fuel Cells (PEMFCs) are major types that work in low temperatures and produce only H2O and electricity as part of the electrochemical reaction. AMFC is a fuel cell that has more affordable membranes, when compared to the PEMFC that uses a polymeric membrane with high cost, making applications more expensive. In AMFCs, the alkaline membrane used, is a simple filter paper saturated with KOH solution that allows ions to pass through the membrane, however, suffers CO2 poisoning when it gets in contact to the carbon dioxide present in the air, reacting in the KOH and capturing hydroxyl ions. The poisoning will generate chemical compounds that will interfere with the energy generation and efficiency of the fuel cell. The main cause of the decreasing performance of carbonate formation is the precipitation of large metal carbonate crystals such as K2CO3 and the formation of H2O in the membrane, decreasing KOH concentration. If not addressed, this issue will limit the use of AMFC to pure oxygen applications only, instead of the air itself, which restricts the applicability of the technology. This study presents a mathematical model of a purifier that reduces the concentration of CO2 present in the air, improving conditions to be used in AMFC for mobile applications as automotive vehicles and without the need to use pure oxygen

MATHEMATICAL MODELING AND SIMULATION OF BATCH REGIME FOR IMMOBILIZED MICROALGAE PHOTOBIOREACTOR FOR EFFLUENT TREATMENT

The increase of wastewater follows the expansion of the world population generating a deficit in basic sanitation and in the sewage collection provided. It is widely known that the United Nations (UN) instituted the 2030 Agenda, a plan for the sustainability of the planet, improvement of people's lives and world prosperity. There are 17 Sustainable Development Goals (SDGs) in the 2030 Agenda. We highlight the SDG 6: “Clean water and sanitation”, which is aimed at basic sanitation and access to drinking water. Currently, the treatment system is divided into three stages: primary, secondary and tertiary. In the secondary stage, one makes use of microorganisms to remove organic matter from the medium, such as microalgae or bacteria. Preference has been given to the use of microalgae, classified as microorganisms of rapid cell growth with photoautotrophic capacity. However, the free state physical dimension of a microalgae makes the treatment process more expensive and potentially, impacts the treatment time, thus burdening the treatment. With that in mind, a method of immobilization of microalgae and the elaboration of a photobioreactor for the treatment of effluents was developed. Immobilization is a practice that consists of fixing algae within small spheres, which simplifies the separation methodology of microorganisms from the treated effluent. The immobilizing medium provides mechanical resistance and protects the culture from possible contamination. In order to demonstrate the functionality of the system, as a means of effluent treatment, a mathematical modeling of the effluent treatment was conceived. Fortran was the programming language used to solve nonlinear differential equations through temporal discretization. Runge-Kutta was the numerical method chosen to solve the equations of the model that are based on Monod’s model. Monod’s model predicts the growth parameters during the life cycle determining the amount of substrates and the number of microalgae along the lag phase, log phase and stabilization level. It also expresses the consumption of the substrates. Thus, the model allows the visualization of the biomass growth, consumption of inorganic substances and the treatment time under study

STUDY ON THE DISPOSAL OF WASTE FROM THE HYDROGEN GENERATION BY ALUMINUM OXIDATION IN ALKALINE SOLUTION

In face of the current high energy consumption and demand worldwide, a change to a sustainable energy matrix became one of the pillars for global sustainability. The use of renewable energy has been one of the most attractive subjects in recent years. Several public policies in this matter have been suggested and there are ongoing efforts toward their implementation. The United Nations (UN) proposed what is called the 2030 Agenda, which considers 17 Sustainable Development Goals (SDG) to be achieved by the year 2030. In support of the 2030 Agenda, research on the production of fuels from clean and sustainable sources is being conducted by the scientific community around the world. Fossil fuels are finite and also a major source of environmental pollutants, therefore the choice of using renewable sources of energy tends to be an increasingly growing and attractive alternative. Hydrogen is a fuel with a high heating value and is known as the most abundant gaseous element and simplest in chemical structure. The scientific community researching fuel cells has given much attention to the generation and storage of hydrogen. Besides the electrolytic hydrogen production and the reforming of fossil fuels (e.g., natural gas), hydrogen can be generated by metallic means, for example, by oxidation of aluminum in an alkaline solution. The use of recyclable metals, such as aluminum in this study, is an option for sustainable hydrogen generation processes. Nevertheless, like any chemical reaction, part of the products generated are waste, and some are even harmful to the environment, which makes the production of sustainable fuels unfeasible in case of not finding an appropriate technological industrial destination for such waste. The herein study comprises the investigation of the industrial and technological applications of the products of the hydrogen generation reaction from aluminum. Mastering the chemical reaction parameters of that reaction is paramount for the optimal design of a hydrogen generation system. The disposal of the waste is relevant since it makes the energy supply chain complete and sustainable

Asc-Seurat: analytical single-cell Seurat-based web application

Background: Single-cell RNA sequencing (scRNA-seq) has revolutionized the study of transcriptomes, arising as a powerful tool for discovering and characterizing cell types and their developmental trajectories. However, scRNA-seq analysis is complex, requiring a continuous, iterative process to refine the data and uncover relevant biological information. A diversity of tools has been developed to address the multiple aspects of scRNA-seq data analysis. However, an easy-to-use web application capable of conducting all critical steps of scRNA-seq data analysis is still lacking. We present Asc-Seurat, a feature-rich workbench, providing an user-friendly and easy-to-install web application encapsulating tools for an all-encompassing and fluid scRNA-seq data analysis. Asc-Seurat implements functions from the Seurat package for quality control, clustering, and genes differential expression. In addition, Asc-Seurat provides a pseudotime module containing dozens of models for the trajectory inference and a functional annotation module that allows recovering gene annotation and detecting gene ontology enriched terms. We showcase Asc-Seurat's capabilities by analyzing a peripheral blood mononuclear cell dataset. Conclusions: Asc-Seurat is a comprehensive workbench providing an accessible graphical interface for scRNA-seq analysis by biologists. Asc-Seurat significantly reduces the time and effort required to analyze and interpret the information in scRNA-seq datasets