The growing global population and heightened concern for climate change leads to increased interest in utilizing microbial fermentations to replace polluting production processes for e.g., plastics, fuels, and animal proteins. Computational fluid dynamics (CFD) is a valuable tool for accelerating the scale-up and optimization of large-scale bioprocesses. However, the design correlations underlying most of these CFD models are validated with air-water systems, not accounting for the distinct hydrodynamic properties of microbial fermentation broth. In this review, we provide an extensive overview of the current understanding of how various biotechnologically relevant solutes impact the hydrodynamics of bubble columns. We examine the effects of components found in fermentation broths, including salts, surfactants, viscoelastic solutes, alcohols, acids, ketones, sugars, biomass, and proteins, on mass transfer, bubble formation, bubble interactions, and flow regime transitions. These components all exhibit unique effects, yet their combined influences remain poorly understood. Future research should prioritize identifying the concentration at which coalescence inhibition occurs for different compounds, especially in mixtures, and exploring the role of proteins in bubble column hydrodynamics from micro- to macroscale.

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Gradients in dissolved gas concentrations are expected to affect the performance of large reactors for anaerobic gas (CO, H2, CO2) fermentation. To study how these gradients, and the dissolved gas concentration level itself, influence the productivity of the desired product ethanol and the product spectrum of C. autoethanogenum, we coupled a CFD model of an industrial-scale gas fermentor to a metabolic kinetic model for a wide range of metabolic regimes. Our model results, together with literature experimental data and a model with constant
dissolved gas concentrations, indicate high ethanol specificity at low dissolved CO concentrations, with acetate reduction to ethanol at very low dissolved CO concentrations and combined ethanol and acetate production at higher CO concentrations. The gradient was predicted to increase both the biomass-specific ethanol production rate and the electron-to-ethanol yield by ~25%. This might be due to intensified ferredoxin and NAD+ redox cycles, with the rate of the Rnf complex – a critical enzyme for energy conservation – as key driver towards
ethanol production, all at the expense of a reduced flux to acetate. We present improved mechanistic understanding of the gas fermentation process, and novel leads for optimization and fundamental research, by coupling observations from various down-scaled lab experiments to expected microbial lifelines in an industrial-scale reactor. @en

One of the major challenges mankind faces nowadays is combating climate change. A substantial fraction of greenhouse gases are released by industrial processes, as steelmaking, (oil)refinery and waste processing. Emissions from these processes can partly be prevented with a recently developed technology called gas fermentation. Within this process, synthesis gas – amixture containing CO, CO2 and H2 – is converted into ethanol and acetic acid by bacteria such as Clostridium autoethanogenum. These products could be used in a wide range of applications, like fuels, plastics and cosmetics. Whilst gas fermentation is already applied at commercial-scale, challenges in scale-up persists due to complex multi-scale interactions among the bioreactor, gas bubbles, and bacteria. The poor solubility of CO and H2 alongside gas bubble coalescence, leads to low gas-to-liquid mass transfer rates (typically denoted via kLa). Slow mixing in industrial bioreactors (500m3), and high gas conversion rates, result in large spatial variations in dissolved gas concentrations. Bacteria experiencing concentration fluctuations have often been related to decreased process performance...@en

The stability of our planet is threatened by climate change, necessitating a shift towards a circular economy in the (bio-)chemical industry to sustainably meet our increasing product demand. Syngas fermentation by acetogenic bacteria, such as Clostridium autoethanogenum, has been identified as a sustainable alternative for the production of biofuels and other chemicals. These bacteria harbour the Wood-Ljungdahl pathway (WLP), enabling them to convert carbon monoxide (CO), carbon dioxide (CO₂) and hydrogen (H₂) into acetate and ethanol. Several process parameters influence the outcome of syngas fermentation and their effects on the metabolic behaviour of syngas fermenting bacteria can be quantified through kinetic modelling.

This study aimed to build a simple quantitative model for steady-state CO fermentation by C. autoethanogenum using unstructured microbial kinetics and the current insights into the ATP production of the CO pathways to acetate and ethanol. To this aim, a dataset compromising 37 steady-state lab-scale syngas fermentations was compiled. Incomplete data was reconciled and recovery gaps were addressed through data reconciliation applied to the dataset. Furthermore, the growth kinetics of C. autoethanogenum was described by coupling ATP production in the catabolism to energy requirements for growth and maintenance through a modified Herbert-Pirt equation. Finally, a preliminary model for CO fermentation by C. autoethanogenum was presented, which given the gas inflow rate, gas inflow composition and liquid dilution rate should predict the consumption and production rates. Moreover, this study emphasizes the necessity for methodologies to measure dissolved gas concentrations and highlights the research gap concerning gas uptake kinetics in syngas fermentation.

In large-scale syngas fermentation, strong gradients in dissolved gas (CO, H₂) concentrations are very likely to occur due to locally varying mass transfer and convection rates. Using Euler-Lagrangian CFD simulations, we analyzed these gradients in an industrial-scale external-loop gas-lift reactor (EL-GLR) for a wide range of biomass concentrations, considering CO inhibition for both CO and H₂ uptake. Lifeline analyses showed that micro-organisms are likely to experience frequent (5 to 30 s) oscillations in dissolved gas concentrations with one order of magnitude. From the lifeline analyses, we developed a conceptual scale-down simulator (stirred-tank reactor with varying stirrer speed) to replicate industrial-scale environmental fluctuations at bench scale. The configuration of the scale-down simulator can be adjusted to match a broad range of environmental fluctuations. Our results suggest a preference for industrial operation at high biomass concentrations, as this would strongly reduce inhibitory effects, provide operational flexibility and enhance the product yield. The peaks in dissolved gas concentration were hypothesized to increase the syngas-to-ethanol yield due to the fast uptake mechanisms in C. autoethanogenum. The proposed scale-down simulator can be used to validate such results and to obtain data for parametrizing lumped kinetic metabolic models that describe such short-term responses.

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In gas fermentations (using O2, CO, H2, CH4 or CO2), gas-to-liquid mass transfer is often regarded as one of the limiting processes. However, it is widely known that components in fermentation broths (e.g., salts, biomass, proteins, antifoam, and organic products such as alcohols and acids) have tremendous impact on the volumetric mass transfer coefficient kLa. We studied the influence of ethanol on mass transfer in three fermentation broths derived from syngas fermentation. In demineralized water, we observed that the addition of ethanol, the expected product, increased kLa two-fold in the 0–5 g L−1 range, after which near-constant kLa values were obtained. In the fermentation broths, kLa was increased significantly (2–4 fold compared to water) by ethanol supplementation, and to be highly influenced by broth salinity. Our results indicate that kLa is a dynamic parameter in gas fermentation experiments and can be significantly increased due to broth components.@en

Mass transfer limitations in syngas fermentation processes are mostly attributed to poor solubility of CO and H₂ in water. Despite these assumed limitations, a syngas fermentation process has recently been commercialized. Using large-sale external-loop gas-lift reactors (EL-GLR), CO-rich off-gases are converted into ethanol, with high mass transfer performance (7–8.5 g.L^-1.h⁻¹). However, when applying established mass transfer correlations, a much poorer performance is predicted (0.3–2.7 g.L^-1.h⁻¹). We developed a CFD model, validated on pilot-scale data, to provide detailed insights on hydrodynamics and mass transfer in a large-scale EL-GLR. As produced ethanol could increase gas hold-up (+30%) and decrease the bubble diameter (≤2 mm) compared to air–water mixtures, we found with our model that a high volumetric mass transfer coefficient (650–750 h⁻¹) and mass transfer capacity (7.5–8 g.L^-1.h⁻¹) for CO are feasible. Thus, the typical mass transfer limitations encountered in air–water systems can be alleviated in the syngas-to-ethanol fermentation process.

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The use of syngas, a renewable energy source, has raised increasing interest for the production of chemicals. Syngas, a mixture containing CO, H2, and CO2, can be converted into hydrocarbons, such as ethanol and 2,3-butanediol, via biochemical conversion. In this process, the microorganism Clostridium auto ethanogenum (C. auto ethanogenum) converts syngas into these hydrocarbons under ambient conditions. Still, syngas fermentation has drawbacks which influence the commercialization and scale-up, including low mass transfer rates due to the low solubility of syngas and the slow growth rate of C. auto ethanogenum.

An external loop gas-lift reactor (ELGLR) was considered to potentially overcome the low mass transfer rates. The recirculation of liquid in the reactor induces pneumatic agitation and the recirculation of biomass, which can improve the mass transfer and growth of C. auto ethanogenum and is currently used at an industrial scale by the company LanzaTech.

A 1D model of an external loop gas-lift reactor can provide understanding of the hydrodynamics and syngas fermentation process with C. auto ethanogenum in an ELGLR. A 1D model has the advantage of being less computationally intensive compared to other dimensional models and can be solved dynamically, which is valuable for comprehending the phenomena of syngas fermentation over time in the reactor. The predictions obtained by this model can be used to roughly determine optimal ranges for syngas fermentation, which could be useful for higher dimensional models or experimental setups.

The model considered a continuous inflow and outflow as well as liquid recirculation between the riser and the downcomer. The hydrodynamics of the reactor were based on correlations and equations proposed in the literature, whereas the syngas conversion by C. autoethanogenum was described using a black-box approach.

The hydrodynamic parameters were validated with experimental data proposed in the literature and a CFD model, which was also used for comparison of the syngas fermentation parameters. Additionally, the syngas fermentation in the 1D model was further optimized by adjusting external variable parameters like the dilution rate, inlet biomass concentration, and the gas mass inflow rate.

The syngas fermentation parameters in terms of ethanol productivity and CO conversion yield were compared to the industrial syngas fermentation process operated by the company LanzaTech. The 1D model was found to predict the hydrodynamic parameters in the same order of magnitude as the experimental data. Yet, the hydrodynamic parameters predicted with the CFD and 1D model corresponded less. Additionally, the syngas fermentation parameters varied greatly between the 1D and CFD model, probably as a result of different hydrodynamic parameter estimations in both models.

Using an optimization procedure, a dilution rate of 3 × 10^-5 1/s, gas inflow rate of 2.5 kg/s, and a biomass inlet concentration of 10 g/L were found to be the most advantageous for syngas fermentation in the 1D ELGLR model, resulting in an ethanol productivity of 0.6 g/L/h and 24.9% conversion.

The comparison with the estimated industrial performance deviated by 75.5% and 4.3% in ethanol productivity and CO-to-ethanol conversion yield, respectively. Due to the rough estimations and calculations, the validity of the 1D model to predict the syngas fermentation in an industrial process could not be deduced.

In conclusion, the 1D model was considered to reasonably predict the hydrodynamics of an actual external loop gas-lift reactor and give a rough approximation of the syngas fermentation by C. auto ethanogen. However, more experimental data on the syngas fermentation process is necessary for a complete understanding of the syngas fermentation process within an ELGLR.