A multi-layered view of chemical and biochemical engineering

Catalytic confinement effects in nanochannels: from biological synthesis to chemical engineering

Catalytic reactions within nanochannels are of significant importance in disclosing the mechanisms of catalytic confinement effects and developing novel reaction systems for scientific and industrial demands. Interestingly, catalytic confinement effects exist in both biological and artificial nanochannels, which enhance the reaction performance of various chemical reactions. In this minireview, we investigate the recent advances on catalytic confinement effects in terms of the reactants, reaction processes, catalysts, and products in nanochannels. A systematic discussion of catalytic confinement effects associated with biological synthesis in bio-nanochannels and catalytic reactions in artificial nanochannels in chemical engineering is presented. Furthermore, we summarize the properties of reactions both in nature and chemical engineering and provide a brief overlook of this research field.

A machine-learning reduced kinetic model for H2S thermal conversion process

H2S is becoming more and more appealing as a source for hydrogen and syngas generation. Its hydrogen production potential is studied by several research groups by means of catalytic and thermal conversions. While the characterization of catalytic processes is strictly dependent on the catalyst adopted and difficult to be generalized, the characterization of thermal processes can be brought back to wide-range validity kinetic models thanks to their homogeneous reaction environments. The present paper is aimed at providing a reduced kinetic scheme for reliable thermal conversion of H2S molecule in pyrolysis and partial oxidation thermal processes. The proposed model consists of 10 reactions and 12 molecular species. Its validation is performed by numerical comparisons with a detailed kinetic model already validated by literature/industrial data at the operating conditions of interest. The validated reduced model could be easily adopted in commercial process simulators for the flow sheeting of H2S conversion processes.

A systematic techno-economic approach to decide between continuous and batch operation modes for injectable manufacturing

A comprehensive approach is proposed to systematically determine the optimal mode of operation between continuous and batch injectable manufacturing considering product and market conditions. At the core of this approach are two integrated complete mathematical modules for discrete and continuous injectable manufacturing, which are supplemented with an economic evaluation module that can then be used to explore the impact of all relevant process parameters (e.g., lot-size, number of operators, solubility, product demand, raw material costs). When the developed approach was applied to two case studies, it was found that batch production was preferred at low to moderate solution (raw material) costs. In contrast, at higher solution costs, the preference for batch and continuous production processes changed back and forth as the annual product demand changed. The study also found that continuous production processes became increasingly preferred at medium to large final dosage volumes and a competitive alternative even at moderate solution costs. From a decision-making point of view, batch injectable manufacturing will be preferred over the novel continuous manufacturing technology unless there is a significant economic incentive to overcome the perceived technology risk. The proposed approach is intended as a decision-support tool for pharmaceutical process engineers.

Modeling and Control of COVID-19 Transmission from a Perspective of Polymerization Reaction Dynamics

Due to the serious economic losses and deaths caused by COVID-19, the modeling and control of such a pandemic has become a hot research topic. This paper finds an analogy between a polymerization reaction and COVID-19 transmission dynamics, which will provide a novel perspective to optimal control measures. Susceptible individuals, exposed people, infected cases, recovered population, and the dead can be assumed to be specific molecules in the polymerization system. In this paper, a hypothetical polymerization reactor is constructed to describe the transmission of an epidemic, and its kinetic parameters are regressed by the least-squares method. The intensity of social distancing u is considered to the mixing degree of the reaction system, and contact tracing and isolation ρ can be regarded as an external circulation in the main reactor to reduce the concentration of active species. Through these analogies, this model can predict the peak infection, deaths, and end time of the epidemic under different control measures to support the decision-making process. Without any measures (u = 1.0 and ρ = 0), more than 90% of the population would be infected. It takes several years to complete herd immunity by nonpharmacological intervention when the proportion of deaths is limited to less than 5%. However, vaccination can reduce the time to tens to hundreds of days, which is related to the maximum number of vaccines per day.

Optimized design of obstacle sequences for microfluidic mixing in an inertial regime

Mixing is a basic but challenging step to achieve in high throughput microfluidic applications such as organic synthesis or production of particles. A common approach to improve micromixer performance is to devise a single component that enhances mixing through optimal convection, and then sequence multiple such units back-to-back to enhance overall mixing at the end of the sequence. However, the mixing units are often optimized only for the initial non-mixed fluid composition, which is no longer the input condition for each subsequent unit. Thus, there is no guarantee that simply repeating a single mixing unit will achieve optimally mixed fluid flow at the end of the sequence. In this work, we analyzed sequences of 20 cylindrical obstacles, or pillars, to optimize the mixing in the inertial regime (where mixing is more difficult due to higher Péclet number) by managing their interdependent convection operations on the composition of the fluid. Exploiting a software for microfluidic design optimization called FlowSculpt, we predicted and optimized the interfacial stretching of two co-flowing fluids, neglecting diffusive effects. We were able to quickly design three different optimal pillar sequences through a space of 32²⁰ possible combinations of pillars. As proof of concept, we tested the new passive mixer designs using confocal microscopy and full 3D CFD simulations for high Péclet numbers (Pe ≈ O(10^5-6)), observing fluid flow shape and mixing index at several cross-sections, reaching mixing efficiencies around 80%. Furthermore, we investigated the effect of the inter-pillar spacing on the most optimal design, quantifying the tradeoff between mixing performance and hydraulic resistance. These micromixer designs and the framework for the design in inertial regimes can be used for various applications, such as lipid nanoparticle fabrication which has been of great importance in vaccine scale up during the pandemic.

Industrial Requirements for Thermodynamic and Transport Properties: 2020

This paper reports the results of an investigation of industrial requirements for thermodynamic and transport properties carried out during the years 2019-2020. It is a follow-up of a similar investigation performed and published 10 years ago by the Working Party (WP) of Thermodynamics and Transport Properties of European Federation of Chemical Engineering (EFCE).1 The main goal was to investigate the advances in this area over the past 10 years, to identify the limitations that still exist, and to propose future R&D directions that will address the industrial needs. An updated questionnaire, with two new categories, namely, digitalization and comparison to previous survey/changes over the past 10 years, was sent to a broad number of experts in companies with a diverse activity spectrum, in oil and gas, chemicals, pharmaceuticals/biotechnology, food, chemical/mechanical engineering, consultancy, and power generation, among others, and in software suppliers and contract research laboratories. Very comprehensive answers were received by 37 companies, mostly from Europe (operating globally), but answers were also provided by companies in the USA and Japan. The response rate was about 60%, compared to 47% in the year 2010. The paper is written in such a way that both the majority and minority points of view are presented, and although the discussion is focused on needs and challenges, the benefits of thermodynamics and success stories are also reported. The results of the survey are thematically structured and cover changes, challenges, and further needs for a number of areas of interest such as data, models, systems, properties, and computational aspects (molecular simulation, algorithms and standards, and digitalization). Education and collaboration are discussed and recommendations on the future research activities are also outlined. In addition, a few initiatives, books, and reviews published in the past decade are briefly discussed. It is a long paper and, to provide the reader with a more complete understanding of the survey, many (anonymous) quotations (indicated with "..." and italics) from the industrial colleagues who have participated in the survey are provided. To help disseminate the specific information of interest only to particular industrial sectors, the paper has been written in such a way that the individual sections can also be read independently of each other.

Nature-Inspired Chemical Engineering for Process Intensification

A nature-inspired solution (NIS) methodology is proposed as a systematic platform for innovation and to inform transformative technology required to address Grand Challenges, including sustainable development. Scalability, efficiency, and resilience are essential to nature, as they are to engineering processes. They are achieved through underpinning fundamental mechanisms, which are grouped as recurring themes in the NIS approach: hierarchical transport networks, force balancing, dynamic self-organization, and ecosystem properties. To leverage these universal mechanisms, and incorporate them effectively into engineering design, adaptations may be needed to accommodate the different contexts of nature and engineering applications. Nature-inspired chemical engineering takes advantage of the NIS methodology for process intensification, as demonstrated here in fluidization, catalysis, fuel cell engineering, and membrane separations, where much higher performance is achieved by rigorously employing concepts optimized in nature. The same approach lends itself to other applications, from biomedical engineering to information technology and architecture.

Carbon dioxide capture and use in photobioreactors: The role of the carbon dioxide loads in the carbon footprint

This research evaluated the carbon dioxide capture and use by Scenedesmus obliquus in a photobioreactor under different CO₂ loads. Performance indicators, carbon and energy balances, sustainability indicators, and carbon credits on the photobioreactor were assessed. The results expressed that the CO₂ loads of 384.9 kg/m³/d (15% CO₂) provide the best trade-off for the process. For this condition, maximum biomass productivities of 0.36 kg/m³/d, carbon dioxide conversion rates of 0.44 kgCO₂/m³/d, and oxygen release rates of 0.33 kgO₂/m³/d were observed, reaching maximum CO₂ removal efficiencies of 30.76%. Volatile organic compounds were the major products generated (>80%). However, only <3% was fixed in biomass. From the environmental and economic point of view, the net energy ratio was 3.44, while the potential carbon credit was of 0.04 USD per m³ of culture. Finally, the use of adequate CO₂ loads was also proven to be determinant to improve the global performance of the system.

Analogies between SARS-CoV-2 infection dynamics and batch chemical reactor behavior

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The batch reactor dynamics is used to predict SARS-CoV-2 spreading.

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The reactor model can phenomenologically explain the virus spreading.

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The model predicts the peak (day and entity) and the infection extinction.

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Initial Value Problem for ODE has been solved with an unknown initial condition.

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Algorithm robustness and convergence have been tested.

The pandemic infection of SARS-CoV-2 presents analogies with the behavior of chemical reactors. Susceptible population (A), active infected population (B), recovered cases (C) and deaths (D) can be assumed to be molecules of chemical compounds and their dynamics seem well aligned with those of composition and conversions in chemical syntheses. Thanks to these analogies, it is possible to generate pandemic predictive models based on chemical and physical considerations and regress their kinetic parameters, either globally or locally, to predict the peak time, entity and end of the infection with certain reliability. These predictions can strongly support the emergency plans decision making process. The model predictions have been validated with data from Chinese provinces that already underwent complete infection dynamics. For all the other countries, the evolution is re-regressed and re-predicted every day, updating a pandemic prediction database on Politecnico di Milano’s webpage based on the real-time available data.