Aluminum-based alloys have been considered candidate materials for cathodic protection anodes. However, the Al-based alloys can form a layer of alumina, which is a drawback in a sacrificial anode. The anodes must exhibit uniform corrosion to achieve better performance. Aluminum can be alloyed with Zn to improve their performance. In this sense, in the present research, the electrochemical corrosion performance of Al-xZn alloys (x = 1.5, 3.5, and 5 at.% Zn) exposed to 3.5 wt.% NaCl for 24 h was evaluated. Polarization curves, linear polarization resistance (LPR), and electrochemical impedance spectroscopy (EIS) were used to identify the electrochemical behavior. The microstructure of the samples before the corrosion assessment was characterized by means of X-ray diffraction analyses (XRD) and scanning electron microscopy (SEM). In addition, microstructures of the corroded surfaces were characterized using X-ray mappings via SEM. Polarization curves indicated that Zn additions changed the pseudo-passivation behavior from what pure Al exhibited in a uniform dissolution regime. Furthermore, the addition of Zn shifted the corrosion potential to the active side and increased the corrosion rate. This behavior was consistent with the proportional decrease in polarization resistance (R_p) and charge transfer resistance (R_ct) in the EIS. The analysis of EIS was done using a mathematical model related to an adsorption electrochemical mechanism. The adsorption of chloride at the Al-Zn alloy surface formed aluminum chloride intermediates, which controlled the rate of the process. The rate constants of the reactions of a proposed chemical mechanism were evaluated.

Fe–Al intermetallic compounds have been considered excellent candidates as alternative alloys for various applications in corrosive environments compared to other Fe-based alloys. Their excellent corrosion resistance is due to the development of an Al-based passive layer. The performance of the passive layer can be improved by adding a third alloy element. Therefore, in this study the electrochemical performance of the Fe40Al intermetallic alloy modified by the addition of a third alloy element (Cr, Ti, Co, Ni) is evaluated. The corrosion resistance of intermetallic alloys has been evaluated by electrochemical tests (potentiodynamic polarization curves, and measurements of open circuit potential, linear polarization and electrochemical impedance) in artificial saliva. The performance of intermetallic alloys was compared with that of Ti. The results obtained showed that the addition of Ni and Ti substantially improves the corrosion resistance of the base intermetallic. The corrosion resistance shown is comparable or greater than that shown by Ti. However, the addition of Co reduces the corrosion resistance of the base intermetallic.

Supply chain echelons normally base their operational decisions on average values of the parameters that depend on other members. However, in real-life operation the variability of said parameters decreases the link profits. Thus, a cooperative arrangement may be devised in which a link agrees to reduce the variability of its behavior to enhance the performance of other links, receiving compensation in return. This work shows the application of simulation and decision trees to assess the feasibility of this cooperation scheme, from the perspective of the central link of a three member supply chain. First, the operational parameters of the link are optimized for mean values of the variables set by adjacent members. Then, by simulating the system for different probability distributions of these variables, graphs of the expected link gain versus the variances of the distributions are plotted. The results are incorporated to decision trees to evaluate the collaboration feasibility. It was found that the increased variability of the behavior of one neighboring member decreases the benefit of lowering the variability of the behavior of the other. The manuscript closes with a discussion of the practical viability of this collaboration scheme.

In this work, issues of water separation and purification are addressed, where, in order to achieve the desired results, it is necessary to use several disciplines such as classical physics, biotechnology, automatic control, automation, and applications of industry 4.0. Further, the need for comprehensive and automated solutions for rainwater treatment in the agricultural sector is addressed. This research focuses on designing and implementing a system adapted to these needs using Siemens technologies. The methodology ranges from the design of the Piping and Instrumentation Diagram (P&ID) to the implementation of the interface, incorporating Siemens technologies for data acquisition, electrical connections, treatment programming, and PID controller design. The results show significant advances in the development of the system, highlighting the effectiveness of automation and the HMI-PLC human–machine interface in process monitoring and control. These findings support the viability of a comprehensive rainwater treatment system for the agricultural sector, with important implications for water efficiency, environmental preservation, and increased productivity in agricultural and livestock activities. The contribution of this work is the relationship between engineering and research focused on industrial processes. The scientific contribution is to obtain the dynamic models and apply two strategies to obtain the gains of the PID controller. The first method is performed through the proposal of a Hurwitz polynomial, and the second is performed through genetic algorithms (GA), where they are implemented in a controller that is commonly used in the industry. The technological part includes the integration of work (schemes, programming, and communications) so that the result is as close to what was expected.

The recent emphasis on sustainability has forced supply chain (SC) management research to include social and environmental aspects. When modelling multi-criteria decisions, an analysis should be made on why the stakeholder cares about the objectives, as they can be inherently important (fundamental) or foment other objectives (means). The classification of objectives into fundamental and means, and the relations between one another define an 'objective structure'. This work discusses different relations that can arise between the sustainability and economic objectives of the SC members and their representation by influence diagrams, utility functions and probabilities. Then, decision trees are used to predict how the decisions of the SC members are affected by their view of sustainability as a fundamental or means objective. This approach can be useful for regulating agencies dealing with real supply chains, as it can be used to predict the performance of incentives for 'sustainability friendly' behaviour.