Chemical reactor | EPFL Graph Search

A chemical reactor is an enclosed volume in which a chemical reaction takes place. In chemical engineering, it is generally understood to be a process vessel used to carry out a chemical reaction, which is one of the classic unit operations in chemical process analysis. The design of a chemical reactor deals with multiple aspects of chemical engineering. Chemical engineers design reactors to maximize net present value for the given reaction. Designers ensure that the reaction proceeds with the highest efficiency towards the desired output product, producing the highest yield of product while requiring the least amount of money to purchase and operate. Normal operating expenses include energy input, energy removal, raw material costs, labor, etc. Energy changes can come in the form of heating or cooling, pumping to increase pressure, frictional pressure loss or agitation.Chemical reaction engineering is the branch of chemical engineering which deals with chemical reactors and their design, especially by application of chemical kinetics to industrial systems. The most common basic types of chemical reactors are tanks (where the reactants mix in the whole volume) and pipes or tubes (for laminar flow reactors and plug flow reactors) Both types can be used as continuous reactors or batch reactors, and either may accommodate one or more solids (reagents, catalysts, or inert materials), but the reagents and products are typically fluids (liquids or gases). Reactors in continuous processes are typically run at steady-state, whereas reactors in batch processes are necessarily operated in a transient state. When a reactor is brought into operation, either for the first time or after a shutdown, it is in a transient state, and key process variables change with time. There are three idealised models used to estimate the most important process variables of different chemical reactors: Batch reactor model, Continuous stirred-tank reactor model (CSTR), and Plug flow reactor model (PFR). Many real-world reactors can be modeled as a combination of these basic types.

Model-based scale-up of a continuously operated consolidated bioprocess based on a microbial consortium for the production of ethanol

David Beat Dempfle

This work demonstrated that consolidated bioprocessing is a promising concept for conversion of lignocellulose to ethanol at industrial scale. CBP offers great cost saving potential, is feasible to be operated continuously and may be scaled up due to extensive knowledge of the process from a chemical engineering point of view.Cost savings of up to 27.5% of the total costs compared to conventional bioethanol production from lignocellulose, as stated by a techno-economic assessment, make continuous CBP the strongest lever to reduce processing costs of lignocellulosic ethanol. A cost sensitivity analysis identified scale and yield as the main cost-pushers from a process point of view, whereas the price level of the plant location has the highest impact on the investment conditions.To prove the feasibility of continuous CBP, and therefore the mentioned cost savings, experiments with a maximum titer of 3.258±0.007 g/L, a productivity of 0.025 g/(Lh) and constant enzyme production over 750h were conducted. Furthermore, the continuous experiments showed that experiments with identical volumetric oxygen transfer rate k_L a, but different oxygen fluxes per membrane area, showed titer differences of ca. 80% (1.83 g/L vs 3.26 g/L) in favor of setups with the large membrane surface. A rigorous process model was developed for continuously operated CBP. 9 species were considered (oxygen, glucose, total concentration Trichoderma reesei, secondary mycelia concentration of T. reesei, enzymes, cellulose, cellobiose, yeast density and ethanol). 8 of these 9 species needed to be modelled spatially resolved to account properly for mass transfer limitations. The fungal biofilm thickness d_f was found to be a critical parameter with an optimum for every membrane configuration. Smaller d_f reduced the fungal biofilm volume and thus, the enzyme production and larger d_f increased the diffusion path length causing shortage in nutrient supply as well as lower enzyme concentrations in the bulk. The enzyme synthesis rate of the secondary mycelia was fitted by reducing it by ca. 40% (0.67 FPU/(mLd) vs 1.152 (FPU/(mL*d) compared to batch models.With the process model as centerpiece, a scale-up framework consisting of the model and a set of non-dimensional parameters was developed to scale CBP from 2.7L laboratory scale to 130L pilot scale. The majority of the non-dimensional parameters could be kept constant during scale-up as requested by the similarity paradigm. Necessary changes were simulated with the model. Again, the fungal biofilm thickness d_f proved to be a relevant parameter for scale-up considerations. In general, the relative loss of biofilm volume is compensated by longer residence times since the residence time has by far the least impact on the process economics.Finally, popular rate-controlled separation techniques were investigated regarding their potential with CBP, since they offer the potential to reduce yeast inhibition, to avoid separation limitations by the azeotrope and they are not bound to the vapor-liquid-equilibrium of highly diluted ethanol-water mixtures. However, most of the mechanisms fail to handle the solids of the fermentation broth. Pervaporation, being the most promising concept for in-situ product removal, would be a cost-saving alternative to distillation for batch operation, but is limited by an unfavorable vapor-liquid equilibrium due to low bulk concentrations during continuous operation.

EPFL2022

Developing structure-oriented models for enzymatic hydrolysis of lignocellulosic biomass

Jessica Charlène Rohrbach

With the unsustainable use of fossil fuels increasing strains on human institutions and ecosystems, the development of a renewable energy alternative is of paramount importance. Second generation biorefineries, based on the production of fuels and chemicals from lignocellulosic biomass, appear as attractive alternative to their non-renewable counterparts. Within the multiplicity of existing valorisation routes, enzymatic hydrolysis of lignocellulosic biomass into its constituent sugars has generated considerable interest, notably in the context of biofuels production. However, major hurdles stemming from the intricate structure of the lignocellulosic feedstocks still impede large-scale deployment of this process. The multiplicity of highly intertwined spatiotemporal factors impacting the enzymatic hydrolysis of lignocellulosic biomass represents a challenge to rationally design efficient hydrolysis process. Here, we propose a theory-based modelling framework relying on pore-diffusion and surface reaction to explore the effects of recognised bottlenecks on the enzymatic hydrolysis of lignocellulosic substrates. The model is based on a set of partial differential equations describing the evolution of the substrate morphology to investigate the interplay between experimental conditions and the physical characteristics of biomass particles as the reaction proceeds. The overall quantity of cellulase present in the hydrolysis mixture is carefully considered to investigate its interplay with the available accessible cellulose surface. Also, non-uniformity in terms of cellulose accessibility and cellulose digestibility are introduced in the model to weight their influence on observed hydrolysis rates. Finally, deactivation mechanisms are considered through unproductive adsorption of cellulases on both cellulose and lignin fractions, with the existence of such phenomena alleged to be critical in the efficiency of the hydrolysis process. Based on predictions of our model, we were able to confirm the critical role of cellulose accessibility, as defined by the combination of particle size, porosity and accessible cellulose surface, in dictating early reaction rates for a range of pretreated beech wood substrates. While high biomass loading should be favoured to improve enzyme penetration in the substrates, high enzyme loadings going beyond the initial number of cellulose adsorption appeared beneficial in notably two cases: (i) to promote internal diffusion in large particles and (ii) counteract undesired enzyme adsorption on lignin. For the latter, a relatively low increase in enzyme loading was sufficient to offset the resulting slowdown. We also showed that the existence of structural heterogeneities, and in particular non-uniform pore volume distribution within the lignocellulosic samples, contribute to the rate slowdown observed at later stage of the hydrolysis, while not explaining it in its entirety. Unproductive adsorption to cellulose, coupled to decrease in the cellulase efficiency at the cellulose surface, appeared as major contributor to the rate slowdown. Overall, we show how the use of a theory-based model can help decouple and evaluate the effects of key factors in the enzymatic hydrolysis of lignocellulosic biomass. As such, our model can help pave the way towards efficient integrated rational design strategies for enzyme process engineering for biomass conversion.

EPFL2021

Numerical characterization and engineering of transport in morphologically complex heterogeneous media

Xiaoyu Dai

A multi-scale numerical methodology for the assessment of radiation and optical characteristics of complex structured soot-contaminated snow layers was investigated first. The methodology accounted for the exact morphology at the various scales and utilizes volume-averaging approaches with the corresponding effective properties to couple the scales. At the continuum level, the volume-averaged coupled radiative transfer equations were solved utilizing i) effective radiative transport properties obtained by direct Monte Carlo simulations at the pore level, and ii) averaged bulk material properties obtained at particle level by discrete dipole approximation calculations. The contribution of soot additives to the radiative forcing was quantitatively estimated by numerical simulation and qualitatively validated with the published experimental data.Additional coupled heat and mass transfer phenomena were then investigated for a two-step solar thermochemical water/carbon dioxide splitting reactor. It was composed of two distinct scales: porous reacting materials at the mesoscale and a batch reactor at the macro-scale. A transient multi-physics volume-averaged model of the reactive porous media undergoing the reduction and oxidation steps was developed. The effective heat and mass transport properties of reticulated porous foams were incorporated through porosity-dependent empirical correlations. Porosity-dependent reduction, oxidation, and cyclic performance for a uniform and homogenous porous structure were assessed and followed by the investigation of diverse structures with non-uniform porosities along the reactor. Subsequently, the effect of structural anisotropy on the system performance was assessed by extending the previous model into 2-dimensions. The porous medium was assumed to exhibit anisotropic transport behaviors in terms of heat transfer (radiation, conduction, convection) and mass transfer. Additionally, two operational configurations were investigated: a conventional concurrent flow configuration of fluid and irradiation and a scenario where the principal flow axis was perpendicular to the irradiation direction. In terms of radiative properties, a structure with a complete forward scattering phase function and low scattering albedo ensured the largest absorption, increasing the production rate. Anisotropic structures with a higher degree of anisotropy in permeability were more favored when the incoming radiation was perpendicular to the fluid flow direction, where the interphase heat convection was enhanced.Lastly, the engineering of the porous structure was explored by establishing a direct relationship between the local morphological characteristics and the reduction performance. This was implemented by direct-pore simulations on the discrete scale that were directly coupled to the volume-averaged finite volume simulations on the continuum scale. A large number of porous structures were artificially generated and its transport characteristics calculated by the pore-levels simulations. These calculated results were used to train a machine-learning algorithm that predicted the oxygen yield solely from based on the morphology. The learning algorithm identified the most significant morphological descriptors for a specific performance target and provided guidelines for the optimal porous structure design.

EPFL2021