On the anniversary of the launch of IChemE’s newest learned journals, their Editors in Chief look through a year’s worth of research papers and pick out their highlights.
Over the decades, one of the major challenges faced by chemical engineers is to find more efficient and easier-to-use ways to solve the Navier-Stokes equation so that we can better understand and predict the complex turbulent flow behaviours in various chemical equipment. Nowadays, we largely rely on computational fluid dynamics (CFD) to do this, despite its high computational cost – often taking days or weeks, if not months, for a single simulation to complete – which largely limits its engineering applications.
Now, a potential game-changer has been reported by a team at the Federal University of Rio de Janeiro, Brazil. In their paper, Physics-Informed Deep Learning to Predict Flow Fields in Cyclone Separators (https://doi.org/h6d3), a machine learning algorithm, named Physics-Informed Neural Networks, or PINNs, has been developed to solve the Navier-Stokes equation and predict complex flow fields in cyclone separators (key equipment in the chemical industry. They demonstrate that the algorithm is 200 times faster than the CFD simulation, and provides results with the same accuracy. Such PINNs could open up new possibilities in the future when it comes to designing chemical devices like safer reactors, more efficient heat exchangers, and more sustainable fluidised beds, to name a few.
Every chemical engineer will agree that the importance of process safety management can’t be over-emphasised. How can we build better process safety management, and what is the role of humans in Big Data and Industry 4.0? This is the question a group of chemical engineers from The University of Queensland address in their paper Information Needs and Challenges in Future Process Safety (https://doi.org/h6d5).
Via an industry case study on high temperature hydrogen attack, the authors make a strong case that a whole system approach is required where data and information needs to be considered within the plant, people and procedures. This work raises an important debate on the role of humans in the era of Big Data. While we can foresee future opportunities for more autonomous operation, there will always be human-machine interfaces associated with day-to-day operations, analysis conceptualisation and design for use-cases of unified data-sets. One of the recurring themes in this paper is that it is important that data is interconnected so that its true and complete meaning can be interpreted by both humans and machines.
An example of an exciting industry development in digital chemical engineering is revealed in The Digital Design Basis: Demonstrating a Framework to Reduce Costs and Improve Quality in Early-Phase Design (https://doi.org/h6d7). The paper reports on a joint initiative to develop and demonstrate a common digital model framework and workflow that can be used by a consortium of operators and competing EPC companies to capture and share data in early-phase design bases for the process engineering sector. The project has developed a proof of concept (the Digital Design Basis) which represents a paradigm shift towards data-centric engineering and design, rather than conventional document-based practices.
The project proved that recent advances in system modelling and ontologies could be applied to a real design basis problem in chemical and process engineering. It also showed that digitalisation is not only about technologies, but also about the business models for value creations and data sharing within the entire industrial ecosystems. We believe the chemical industry needs more projects like this.
Developing efficient techniques to capture CO2 is the first step in reducing our CO2 emissions, but what do you do with it after that? Currently, the most popular approaches are to store it in novel materials or, even better, use it by converting it into fuels and chemicals with the aid of metal catalysts. However, current methods for CO2 capture and utilisation (CCU) are still a long way removed from real-life applications since they involve multiple steps that significantly limit their efficiency and cost.
Recent Progress in Integrated CO2 Capture and Conversion Process Using Dual Function Materials: A State-of-the-Art Review (https://doi.org/h6d8) introduced the most recent progress made in integrated CO2 capture and utilisation (ICCU) technologies. Based on the development of novel materials which can act simultaneously as sorbents and catalysts, ICCU allows CO2 capture and utilisation in a single reactor in a one-pot fashion. This significantly cuts down the steps required for CCU and mitigates undesirable processes, such as the transportation of sorbents, which is a huge step forward in the development of feasible technologies to deal with CO2. Importantly, the paper also points out six key technological gaps in the current research surrounding ICCU, which I believe will act as an important guideline for future research in this important area.
Another significant challenge in combatting CO2 issues is the development of affordable and green materials which can act as efficient sorbents and catalysts, and CCST has published several exciting papers in this area. For example, Study on CO2 Sorption Performance and Sorption Kinetics of Ce- and Zr-doped CaO-based Sorbents (https://doi.org/h6fb) showed that doping Zr and Ce led to a significant increase in the CO2-capturing ability of CaO adsorbents.
Meanwhile, Understanding the Competition Between Carbonation and Sulfation of Li4SiO4-Based Sorbents for High-Temperature CO2 Capture (https://doi.org/h6fd) introduced a new class of K2CO3/Li4SiO4 adsorbents to enhance the stability of CO2 capture and also the SOx removal, which opens a new concept of integrating the capture of multiple pollutants and the conversion of captured pollutants.
Notably, Integrated CO2 Capture and Utilization with CaO-alone for High Purity Syngas Production (https://doi.org/g22w) showed that CaO alone could act as a dual-functional material for both carbon capture and utilisation. Using commercially-available crude CaO in ICCU, the final conversion rate of CO2 to CO can reach 75%, which is higher than the conversion rate of traditional catalytic CO2 hydrogenation processes. The clear economic benefits of this approach over conventional CCU technologies were demonstrated using simulations. Considering the cost-effectiveness, ease for potential scaleup of CaO, and the existence of mature technologies for syngas (CO and H2) conversion to liquid fuels, the method reported in this paper has particularly promising potential to be further developed into a feasible approach for upcycling CO2.
Digital Chemical Engineering, and Carbon Capture Science & Technology are gold open access journals. All papers are freely available. Furthermore, the APC (article publishing charge) for both journals is currently waived for all authors until mid-2023. To view published papers and find out more about submitting your papers to DChE and CCST please see https://www.journals.elsevier.com/digital-chemical-engineering and https://www.journals.elsevier.com/carbon-capture-science-and-technology
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