Nature inspired chemical engineering learning from the fractal geometry of nature in sustainable chemical engineering

Abstract

Man can learn from nature to improve technology in a sustainable way. In recent years, scientific interest in nature, particularly in the field of the life sciences, has grown tremendously. Observing the fascinating developments in molecular and cell biology, biophysical chemistry and bioinformatics, I aim to extend this interest beyond the molecular or nano-scale by using a range of multi-disciplinary tools, from physical chemistry, statistical mechanics and thermodynamics to catalysis and reactor engineering. The principle vision expressed through the Nature Inspired Chemical Engineering (NICE) research program is that, to drastically increase the efficiency of processes and products, chemical engineering can greatly benefit from the study of how nature operates, not only at the nano- or molecular scale but also at the mesoscopic and all the way up to the macroscopic scale. Using a combination of analytical calculations, simulations and experiments, the NICE program focuses on the creation of efficient patterned reaction environments, and on the creative modeling, design and synthesis of efficient ways to link the building blocks or cells (e.g. active sites, capillaries, the nano-structured function) to the macroscopic world. To do so, lessons are drawn from the architecture of the efficient self-assembled patterns and the hierarchical networks that nature uses in its own operations and reactors, such as lungs, kidneys or the vascular network. During the next few years, the NICE program aims to demonstrate that similar architectures can be used, e.g. to design porous catalysts with an optimal hierarchical pore structure that reduces transport limitations, or to construct fractal, tree-shaped fluid injectors for multiphase reactors (U.S. patent). Research on the latter shows that such an injector, designed like an inverted tree, could inject fluid in a much more uniform way throughout a reactor vessel containing another fluid or fluidized medium. Because of its fractal nature, the fractal injector also leads to a much more facile scale-up, answering a very important challenge in multiphase chemical reaction engineering that is nicely solved in nature. The NICE program incorporates a significant analytical and computational sub-program, aiming to reveal how certain patterns emerge (e.g., through self-assembly or chaos-order transitions), and which patterns in a catalyst or multiphase reactor are optimal to efficiently produce a product. While the optimization will go over a variety of structures, not only those structures that appear in nature, the observation of nature should be extremely useful. Indeed, nature may not always be optimal, yet certain patterns, such as fractal branching occur so frequently and in so many different situations that this raises the fundamental question why this is so. A signature of a space-filling fractal network (such as the vascular network) is the famous allometric scaling law of biology, holding over many orders of magnitude: metabolic energy is proportional to the body mass to the exponent 3/4. The origin of this law was recently found to be a thermodynamic optimization, together with the useful properties of scalability and uniform accessibility, properties so interesting to chemical reaction engineering. Other trees, such as botanical lungs or kidneys, have different shapes. Optimal geometry depends to a large extent on the (bio)physico-chemical function of the unit The scaling laws will be different as well. I aim to search for these optimal shapes for various chemical processes, in particular in the fields of heterogeneous catalysis, fluidized beds, slurry reactors and fluid mixing. This program is closely linked to an experimental program: catalyst and materials design, and novel multiphase reactors with a structured, dynamic fluid injection. For catalysis, the hierarchical, regularly patterned pore structure of a porous catalyst is rationally designed. Although the NICE program is still in its infancy, preliminary results in my group show that this is feasible. For multiphase reaction engineering, the way fluids are injected is spatially (where are the injection points?) and temporally (how does the flow vary over time?) controlled to optimize the process. The injection can be uniform, through a fractal injector, but can also be oscillating, through the bottom of the reactor, for example - the latter was very recently shown in my group to lead to rising regular hexagonal bubble patterns. The desired efficient design, for an actual chemical process, should follow from the formerly described computational sub-program. By controlling the geometrical design from the nano- to the macroscale, multiphase processes can be better structured, chaos can be turned into order, and desirable properties like uniformity and scalability can be realized, typically in a nature inspired way, leading to a more efficient process operation.