A current concern is the increase in greenhouse gas emissions, mainly CO₂, with anthropogenic sources being the main contributors. Microalgae have greater capacity than terrestrial plants to capture CO₂, with this being an attraction for using them as capture systems. This study aims at the techno-economic evaluation of microalgae biomass production, while only considering technologies with industrial scaling potential. Energy consumption and operating costs are considered as parameters for the evaluation. In addition, the capture of CO₂ from a thermoelectric plant is analyzed, as a carbon source for the cultivation of microalgae. 24 scenarios were evaluated while using process simulation tools (SuperPro Designer), being generated by the combination of cultivations in raceway pond, primary harvest with three types of flocculants, secondary harvest with centrifugation and three filtering technologies, and finally the drying evaluated with Spray and Drum Dryer. Low biomass productivity, 12.7 g/m²/day, was considered, achieving a capture of 102.13 tons of CO₂/year in 1 ha for the cultivation area. The scenarios that included centrifugation and vacuum filtration are the ones with the highest energy consumption. The operating costs range from US $ 4.75–6.55/kg of dry biomass. The choice of the best scenario depends on the final use of biomass.

Sweet bell peppers are a Solanaceous fruit belonging to the Capsicum annuum L. species whose consumption is popular in world gastronomy due to its wide variety of colors (ranging green, yellow, orange, red, and purple), shapes, and sizes and the absence of spicy flavor. In addition, these fruits have a characteristic flavor and nutritional attributes that include ascorbic acid, polyphenols, and carotenoids. A quality criterion for the harvest of this fruit is maturity; this attribute is visually determined by the consumer when verifying the color of the fruit’s pericarp. The present work proposes an artificial vision system that automatically describes ripeness levels of the bell pepper and compares the Fuzzy logic (FL) and Neuronal Networks for the classification stage. In this investigation, maturity stages of bell peppers were referenced by measuring total soluble solids (TSS), ° Brix, using refractometry. The proposed method was integrated in four stages. The first one consists in the image acquisition of five views using the Raspberry Pi 5 Megapixel camera. The second one is the segmentation of acquired image samples, where background and noise are removed from each image. The third phase is the segmentation of the regions of interest (green, yellow, orange and red) using the connect components algorithm to select areas. The last phase is the classification, which outputs the maturity stage. The classificatory was designed using Matlab’s Fuzzy Logic Toolbox and Deep Learning Toolbox. Its implementation was carried out onto Raspberry Pi platform. It tested the maturity classifier models using neural networks (RBF-ANN) and fuzzy logic models (ANFIS) with an accuracy of 100% and 88%, respectively. Finally, it was constructed with a content of ° Brix prediction model with small improvements regarding the state of art.

Microalgae have a high capacity to capture CO₂. Additionally, biomass contains lipids that can be used to produce biofuels, biolubricants, and other compounds of commercial interest. This study analyzed various scenarios for microalgae lipid production by simulation. These scenarios include cultivation in raceway ponds, primary harvest with three flocculants, secondary harvest with pressure filter (and drying if necessary), and three different technologies for the cell disruption step, which facilitates lipid extraction. The impact on energy consumption and production cost was analyzed. Both energy consumption and operating cost are higher in the scenarios that consider bead milling (8.79–8.88 kWh/kg and USD 41.06–41.41/kg), followed by those that consider high-pressure homogenization (HPH, 5.39–5.46 kWh/kg and USD 34.26–34.71/kg). For the scenarios that consider pressing, the energy consumption is 5.80–5.88 kWh/kg and the operating cost is USD 27.27–27.88/kg. The consumption of CO₂ in scenarios that consider pressing have a greater capture (11.23 kg of CO₂/kg of lipids). Meanwhile, scenarios that consider HPH are the lowest consumers of fresh water (5.3 m³ of water/kg of lipids). This study allowed us to develop a base of multiple comparative scenarios, evaluate different aspects involved in Chlorella vulgaris lipid production, and determine the impact of various technologies in the cell disruption stage.

The cultivation of microalgae has become a viable option to mitigate increase in CO₂ in the atmosphere generated by industrial activities since they can capture CO₂ as a carbon source for growth. Besides, they produce significant amounts of oils, carbohydrates, proteins, and other compounds of economic interest. There are several investigations related to the process, however, there is still no optimal scenario, since may depend on the final use of the biomass. The objective of this work was to develop a techno-economic evaluation of various technologies in harvesting and drying stages. The techno-economic estimation of these technologies provides a variety of production scenarios. Photobioreactors were used considering 1 ha as a cultivation area and a biomass production of 22.66 g/m²/day and a CO₂ capture of 148.4 tons/ha/year was estimated. The production scenarios considered in this study have high energy demand and high operating costs (12.09–12.51 kWh/kg and US $210.05–214.59/kg). These results are mainly a consequence of the use of tubular photobioreactors as a biomass culture system. However, the use of photobioreactors in the production of microalgal biomass allows it to be obtained in optimal conditions for its use in the food or pharmaceutical industry.

Although much has been learned and investigated about environmentally friendly lubricants in recent years, several issues remain critical to their use in specific applications. A key point that could be limiting their utilization is that the effect of green lubricants on the tribological and mechanical properties of the elements has not been thoroughly studied since such attributes determine their performance in industrial applications. For this reason, in this research, the effect of green lubrication on the tribological and hardness properties of AISI 4140 steel was studied. The performance of three bio-based lubricants was studied and compared to that of five of the most representative lubricants. First, the lubricants were chemically and physically characterized. Then, the effect of each lubricant on the friction and wear behavior of the system was analyzed by kinetic friction coefficient, wear rate calculations, and microhardness measurements. In general, the bio-based lubricants exhibited the lowest values of friction and wear. Further the mechanical properties of the systems lubricated by these lubricants were not affected or were affected to a lesser degree.

The hardware in the loop (HIL) technique allows you to reproduce the behavior of a dynamic system or part of it in real time. This quality makes HIL a useful tool in the controller validation process and is widely used in multiple areas including photovoltaic systems (PVSs). This study presents the development of an HIL system to emulate the behavior of a PVS that includes a photovoltaic panel (PVP) and a DC-DC boost converter connected in series. The emulator was embedded into an NI-myRIO development board that operates with an integration time of 10 µs and reproduces the behavior of the real system with a mean percent error of 2.0478%, compared to simulation results. The implemented emulator is proposed as a platform for the validation of control systems. With it, the experimental stage is carried out on two controllers connected to the PVS without having the real system and allowing to emulate different operating conditions. The first controller is based on the Hill Climbing algorithm for the maximum power point tracking (MPPT), the second is a proportional integral (PI) controller for voltage control. Both controllers generate settling times of less than 3 s; the MPPT controller generates variations in the output in steady state inherent to the algorithm used. For both cases, the comparison of the experimental results with those obtained through software simulation show that the platform fulfills its usefulness when evaluating control systems.