Jesús Rafael Alcántara Avila

Ethanol derived from biomass is a promising renewable fuel; however, its long-term use as a gasoline additive is becoming increasingly uncertain due to the rise of electric vehicles and alternative propulsion technologies. This trend motivates the exploration of higher-value applications for ethanol, particularly in the food and pharmaceutical sectors, where product safety is critical. A key challenge in ethanol purification is breaking the ethanol–water azeotrope, as conventional entrainers such as ethylene glycol or glycerol can leave residual traces that limit ethanol’s use in sensitive markets. Magnesium chloride (MgCl2) offers an effective alternative, enabling high-purity ethanol without introducing hazardous organic residues, while exhibiting favorable hygroscopic properties and operational reliability. Simulating this system is challenging due to strong non-ideal and electrolyte interactions in phase equilibrium. Conducting a rigorous controllability analysis is also difficult; therefore, within an Integrated Design and Control (IDC) framework, accurate approximations are essential for successful implementation. This work presents a multi-objective optimization of a MgCl2-based ethanol dehydration column, simultaneously minimizing the Total Annual Cost (TAC) and the open-loop controllability criterion (A_gamma + gamma_sm). The optimization integrates Aspen Plus® with Python and employs validated surrogate cost models for the preconcentrator and salt concentrator processes. Dynamic boundaries ensure product purity by maintaining the ethanol/water feed below the salt feed. The ASF (Achievement Scalarizing Function) solution achieved a 64.33% improvement in controllability with a 13.37% increase in TAC relative to the reference case reported in the literature, illustrating the trade-off between economic and control objectives. This study demonstrates that incorporating simplified controllability metrics into multi-objective optimization enables the efficient and practical design of complex systems, providing a viable approach for managing cost–control trade-offs in processes with challenging dynamics.

Fine bubbles (FBs) are defined by the ISO/TC 281 as gas bubbles with a diameter of less than 100 μm, and they have interesting properties such as high surface-to-volume ratio, low buoyancy, long residence time, electric charge, and self-pressurization effect. Typically, FBs are characterized in terms of size distribution, concentration, and zeta potential through specialized microscopic and nanoscopic measuring devices. This work proposes a multi-objective optimization problem to find the optimal conditions to generate FBs from experimental macroscopic measurements in terms of dissolved oxygen (DO). Then, detailed microscopic measurements in terms of size distribution and zeta potential are conducted. Additionally, two venturi-type Fine Bubble Generators (FBGs) were 3D-printed in-house to evaluate the relationship between the internal structure and the generation of FBs. The best FBGs have an obstacle in the diverging section that promotes FB generation under the evaluated experimental conditions. Under the best operating conditions, FBs were stable over 7 days with a size distribution between 60 and 90 nm and with an average of −21 mV.

This Process Synthesis and Intensification (PS+I) framework uses a low-aggregation superstructure to solve the synthesis problem, and its solution is interpreted and translated into a task-integrated intensified process. Then, the process is post-optimized to find a better balance between operation and equipment costs. The solution leads to novel and counterintuitive intensified processes with low cost and energy requirements.

The generation of Fine Bubbles (FB) using Venturi-type nozzles has been researched experimentally and mathematically using CFD simulations. Nevertheless, little has been discussed about the addition of obstacles in the convergent or divergent parts of the nozzle. Therefore, this research evaluates the performance of six fine bubble generation nozzles that were designed using cloud-based 3D modeling software and 3D printing. The designed nozzles were evaluated in terms of macroscopic features measured through oxygen gas absorption experiments and microscopic features such as size distribution and zeta potential measurements. Moreover, two indexes were proposed based on the gas absorption dynamic responses. These indexes were included in three objective functions that can be solved as mono-objective or multi-objective optimization problems. The nozzles with the best performance were evaluated regarding size distribution and zeta-potential. The results showed that installing obstacles in the divergent part of the nozzle attained higher gas absorption, smaller size of ultra fine bubbles (UFB), and more negative zeta potential.

Typically, the synthesis problem starts from a set of preestablished connections between steams and unit operations resulting in distillation sequences, which can be included into superstructure representations and reformulated as mathematical programming problems. Nevertheless, in the last decades novel approaches to process synthesis that depart from the concept of unit operation and are based on phenomenological approaches have been proposed. This work decomposes distillation structures into distillation modules where a module is equivalent to a vapor-liquid equilibrium stage in which input and output material and heat flows connect modules. Also, a process synthesis an intensification (PS+I) framework is proposed for the synthesis of distillation structures separating ternary mixtures. The proposed framework has the following steps: database generation of distillation modules, optimization, solution interpretation, validation, and post-optimization. The separation of the BTX ternary mixture was taken as case study and several interpretation guidelines have been proposed.

Process Intensification (PI) is a vast and growing area in Chemical Engineering, which deals with the enhancement of current technology to enable improved efficiency; energy, cost, and environmental impact reduction; small size; and better integration with the other equipment. Since process intensification results in novel, but complex, systems, it is necessary to rely on optimization and control techniques that can cope with such new processes. Therefore, this review presents some advancements in the field of process intensification that are worthy of exploring in detail in the coming years. At the end, several important open questions that can be taken into consideration in the coming years are listed.