Simulation of algal photobioreactors: recent developments and challenges

The Role of Light on the Microalgae Biotechnology: Fundamentals, Technological Approaches, and Sustainability Issues

Light energy directly affects microalgae growth and productivity. Microalgae in natural environments receive light through solar fluxes, and their duration and distribution are highly variable over time. Consequently, microalgae must adjust their photosynthetic processes to avoid photo limitation and photoinhibition and maximize yield. Considering these circumstances, adjusting light capture through artificial lighting in the main culture systems benefits microalgae growth and induces the production of commercially important compounds. In this sense, this review provides a comprehensive study of the role of light in microalgae biotechnology. For this, we present the main fundamentals and reactions of metabolism and metabolic alternatives to regulate photosynthetic conversion in microalgae cells. Light conversions based on natural and artificial systems are compared, mainly demonstrating the impact of solar radiation on natural systems and lighting devices, spectral compositions, periodic modulations, and light fluxes when using artificial lighting systems. The most commonly used photobioreactor design and performance are shown herein, in addition to a more detailed discussion of light-dependent approaches in these photobioreactors. In addition, we present the principal advances in photobioreactor projects, focusing on lighting, through a patent-based analysis to map technological trends. Lastly, sustainability and economic issues in commercializing microalgae products were presented.

Impact of 3D printing materials on mircoalga Chlorella vulgaris

3D printing represents a key enabling technology in designing photobioreactors. It allows rapid prototyping of complex geometries at an affordable price. Yet, no study dealt with the biocompatibility of 3D printing material with microalgae. Thus microalga Chlorella vulgaris was cultivated in contact with different 3D printing materials (Acrylonitrile Butadiene Styren - ABS, PolyCarbonate Blend - PC-Blend, PolyLactic acid - PLA, and acrylate methacrylate resin). Cell status was analyzed using flow cytometry, fluorometry, and pigment profiling. Results revealed that acrylate methacrylate resin material inhibits growth, a constant rise in intracellular reactive oxygen species, and a decrease in photosynthetic apparatus functioning. On the contrary, ABS, PC-Blend, and PLA led to nominal perfromances. Nevertheless, PLA was the only material that did not induce an early onset of intracellular reactive oxygen species. Therefore, resin can be ruled out as photobioreactor material, ABS and PC-Blend could be used after a curation period, and PLA induces no detectable perturbations by the means used in this study.

A biphasic photobioreactor system for consecutive extraction of lipids and carotenoids from pre-hydrolysed microalgae and evaluation of its biodiesel potential

A green extraction method is developed using partially hydrolysed microalgal cells grown in biocompatible solvent for simultaneous cultivation and extraction of bioproducts from a highly efficient permeabilized microalgal cell with enhanced biomass and lipid content for potential use in biodiesel production. Incomplete digestion of cell wall was achieved by regulating the incubation time of the enzymatic pretreatment of the microalgal cells. 15.77% increase in lipid content was seen when untreated cells were cultured with biocompatible solvent, while cultivation of these enzymatically pretreated cells with biocompatible solvent, the lipid content increased by 53.33% and 22% higher carotenoid content was observed as compared to conventional extraction. The total fatty acids obtained after 1st and 2nd extractions in untreated samples were 67.82%, while those in enzymatically partially digested samples were 91.94%. The untreated and partially enzymatically predigested strain showed suitable properties for quality biodiesel production as per international recommendations. The cost benefit analysis of the overall process showed the use of biocompatible solvent coupled to enzymatically predigested biomass was a favorable option as compared to conventional extraction.

Optimization and Scale-Up of Fermentation Processes Driven by Models

In the era of sustainable development, the use of cell factories to produce various compounds by fermentation has attracted extensive attention; however, industrial fermentation requires not only efficient production strains, but also suitable extracellular conditions and medium components, as well as scaling-up. In this regard, the use of biological models has received much attention, and this review will provide guidance for the rapid selection of biological models. This paper first introduces two mechanistic modeling methods, kinetic modeling and constraint-based modeling (CBM), and generalizes their applications in practice. Next, we review data-driven modeling based on machine learning (ML), and highlight the application scope of different learning algorithms. The combined use of ML and CBM for constructing hybrid models is further discussed. At the end, we also discuss the recent strategies for predicting bioreactor scale-up and culture behavior through a combination of biological models and computational fluid dynamics (CFD) models.

Hydrodynamics and mass transfer of concentric-tube internal loop airlift reactors: A review

The concentric-tube internal loop airlift reactor is a typical reactor configuration which has been adopted for a myriad of chemical and biological processes. The reactor hydrodynamics (including mixing) and the mass transfer between the gas and liquid phases remarkably affect the operational conditions and thus are crucial to the overall reactor performance. Hence, this study aims at providing a thorough description of the basic concepts and a comprehensive review of the relevant reported studies on the hydrodynamics and mass transfer of the concentric-tube internal loop airlift reactors, taking microalgae cultivation as an exemplary application. In particular, the reactor characteristics, geometry, CFD modeling, experimental characterization, and scale up considerations are elucidated. The research gaps for future research and development are also identified.

Modeling and Simulation of Photobioreactors with Computational Fluid Dynamics—A Comprehensive Review

Computational Fluid Dynamics (CFD) have been frequently applied to model the growth conditions in photobioreactors, which are affected in a complex way by multiple, interacting physical processes. We review common photobioreactor types and discuss the processes occurring therein as well as how these processes have been considered in previous CFD models. The analysis reveals that CFD models of photobioreactors do often not consider state-of-the-art modeling approaches. As a comprehensive photobioreactor model consists of several sub-models, we review the most relevant models for the simulation of fluid flows, light propagation, heat and mass transfer and growth kinetics as well as state-of-the-art models for turbulence and interphase forces, revealing their strength and deficiencies. In addition, we review the population balance equation, breakage and coalescence models and discretization methods since the predicted bubble size distribution critically depends on them. This comprehensive overview of the available models provides a unique toolbox for generating CFD models of photobioreactors. Directions future research should take are also discussed, mainly consisting of an extensive experimental validation of the single models for specific photobioreactor geometries, as well as more complete and sophisticated integrated models by virtue of the constant increase of the computational capacity.

Photobioreactors for cultivation and synthesis: Specifications, challenges, and perspectives

Due to their versatility and the high biomass yield produced, cultivation of phototrophic organisms is an increasingly important field. In general, open ponds are chosen to do it because of economic reasons; however, this strategy has several drawbacks such as poor control of culture conditions and a considerable risk of contamination. On the other hand, photobioreactors are an attractive choice to perform cultivation of phototrophic organisms, many times in a large scale and an efficient way. Furthermore, photobioreactors are being increasingly used in bioprocesses to obtain valuable chemical products. In this review, we briefly describe different photobioreactor set-ups, including some of the recent designs, and their characteristics. Additionally, we discuss the current challenges and advantages that each different type of photobioreactor presents, their applicability in biocatalysis and some modern modeling tools that can be applied to further enhance a certain process.

How Do Operational and Design Parameters Effect Biomass Productivity in a Flat-Panel Photo-Bioreactor? A Computational Analysis

Optimal production of microalgae in photo-bioreactors (PBRs) largely depends on the amount of light intensity received by individual algal cells, which is affected by several operational and design factors. A key question is: which process parameters have the highest potential for the optimization of biomass productivity? This can be analyzed by simulating the complex interplay of PBR design, hydrodynamics, dynamic light exposure, and growth of algal cells. A workflow was established comprising the simulation of hydrodynamics in a flat-panel PBR using computational fluid dynamics, calculation of light irradiation inside the PBR, tracing the light exposure of individual cells over time, and calculation the algal growth and biomass productivity based on this light exposure. Different PBR designs leading to different flow profiles were compared, and operational parameters such as air inlet flowrate, microalgal concentration, and incident light intensity were varied to investigate their effect on PBR productivity. The design of internal structures and lighting had a significant effect on biomass productivity, whereas air inlet flowrate had a minimal effect. Microalgal concentration and incident light intensity controlled the amount of light intensity inside the PBR, thereby significantly affecting the overall productivity. For detailed quantitative insight into these dependencies, better parameterization of algal growth models is required.

Enhancing microalgal biomass productivity with an optimized flow field generated by double paddlewheels in a flat plate photoreactor with CO2 aeration based on numerical simulation

Computational fluid dynamics were used to analyze the flash light effect and CO₂ bubble behavior in an optimized flow field generated by double paddlewheels in a flat plate photoreactor to enhance microalgal biomass productivity. The increased D/w ratio significantly enhanced the average turbulent kinetic energy and flash cycle frequency. However, the effects became weak when the D/w ratio was over 0.67. Appliance of double paddlewheels increased flash cycle frequency from 0.035 to 0.121 Hz and increased light time ratio from 8.3% to 31.5%. Meanwhile, the bubble dynamic behavior was characterized using population balance model. The average bubble size reduced by 24.4% and the bubble rising velocity reduced by 10.6%, which facilitated CO₂ mixing and mass transfer in microalgal solution. Therefore, biomass accumulation of microalgae Chlorella in the photoreactor with double paddlewheels increased by 62.3% under 15% CO₂.

Multiscale numerical workflow describing microalgae motion and light pattern incidence towards population growth in a photobioreactor

In this article, a numerical workflow describing the microalgal growth inside of a photobioreactor is proposed. CFD is used to compute reactor internal hydrodynamics taking into account marine impeller rotation and sparged bubbles motion. Lagrangian approach is used to track microalgae motion inside of the culture vessel. The illumination across the reactor is obtained using the classical Beer-Lambert's law. The combination of light field and cell motion allows to reconstruct the light history of each microalgae. These histories are then supplied to Han's model which predicts individual growth rate and experienced photodamages. Once computed, several thousands of trajectories are agglomerated at the population level yielding the photobioreactor performances. After having ensured properties convergence, this procedure is applied to a large range of optical density (0 to 4.0), i.e. cell concentration, and incident light intensities (0 to 2000 μmolPhoton/m2/s). From this exploration, it is possible to determine the photobioreactor response surfaces in terms of growth rate and photodamages. These are latter used to propose an optimal lighting strategy for biomass production - reducing photobioreactor operation time by 16% compared to classical two-step procedure - and assist light induced stress with the aim of triggering secondary metabolites production.

The potential of quantitative models to improve microalgae photosynthetic efficiency

The massive increase in carbon dioxide concentration in the atmosphere driven by human activities is causing huge negative consequences and new sustainable sources of energy, food and materials are highly needed. Algae are unicellular photosynthetic microorganisms that can provide a highly strategic contribution to this challenge as alternative source of biomass to complement crops cultivation. Algae industrial cultures are commonly limited by light availability, and biomass accumulation is strongly dependent on their photon-to-biomass conversion efficiency. Investigation of algae photosynthetic metabolism is thus strategic for the generation of more efficient strains with higher productivity. Algae are cultivated at industrial scale in conditions highly different from the natural niches they adapted to and strains development efforts must fully consider the seminal influence on productivity of regulatory mechanism of photosynthesis as well as of cultivation parameters like cells concentration, light distribution in the culture, mixing, nutrients and carbon dioxide availability. In this review we will focus in particular on how mathematical models can account for the complex influence of all environmental parameters and can be exploited for development of improved algae strains.