Algae Growth Company Commercial Viability and Bioreactor Design Equations
Often it is not obvious to algae entrepreneurs that the commercial viability is directly dependent on the efficacy of the Bioreactor Design Equations set with respect to the predictivity of the equations. Designing intrinsically entails prediction of performance, absent of the accurate prediction of performance the entrepreneur might as well be jumping down a bridge and hoping for the best. The fact is, the evaluation of Commercial Viability entails the prediction of the performance of the algae growth process which is based on the Bioreactor Design Equations capacity to predict the growth rate.

The primary lack of awareness with the design of algae growth process technology is that the Algal Suspension Media is a Many Body Problem and must be tackled as such, albeit a case of Random Media Many Body problem, because each microbe in the suspension is described by the same set of Mathematical equations. So then for an algal suspension that starts off with, say, six million algae cells, the correct approach is to start off the analysis with six million descriptive mathematical equations subject to the set of microbe-specific boundary conditions, and the simultaneous collective analyses of these equations is the correct approach.

Analyzing these equations which, of course, vary as the algae replicate and or die is rather daunting, and so there is often used the "Averaged Method" including the Monod Model, but such methods blatantly ignore the particulate system character of the media and so warrants another approach which is aptly the "Aggregated Method", one such approach of which is documented in title Contents being advanced as the Point Sinks Sources Bioreactors Design Equations set, that is such as enable description of cellular reactions dynamics.

The Two Approaches to Bioreactors Designs and Analyses.
Bioreactor design and analysis can be simple and can be complex depending on which one of the two approaches of design and analysis is adopted.

One approach, of course, starts off with the assumption of simulation model, such as say the Monod Model, and so performs parameter estimation for the model, and afterwards then constructs the substrate depletion profile using Yield Coefficients and Cell yield, and other relationships as developed over the years. Of course, in this approach, the specific growth rate is assumed constant as is the Yield Coefficient, etc.

The other approach performs experiments and extracts the kinetic parameters and hence the rate equations guided by the science of Cellular Biochemistry. One constructs the rate equations, and then analyzes the performance of the bioreactors, computing predictive calculations of the substrate depletion profile, microbes growth profile, Specific growth Rate and what have you.

Of course, the first approach is more common and easier, and has been the method of choice for the past 60 yrs, and often is studied with a Chemostat; however, it is not predictive, though rather informative. The second approach is more involved, is relatively newer being co-opted from the Chemical Engineering discipline, and so not commonly used; however, it is predictive and perhaps even instructive, and often entails use of a Batch reactor for the kinetics studies.

Knowing the method being adopted or proffered in a particular text/book is quite helpful to understanding the type of knowledge being imparted in a given text/book.

Reconciliation of the Two Perspectives of Bioreactor Designs
Every keen bioreactor engineer or designer will have observed by now that designing bioreactors entails the adoption of one of two fundamental perspectives: Particulate System Perspective and the Macro Well-mixed Perspective. Each perspective, of course, has its advantages and disadvantages,

Consider that the Macro Well-mixed perspective is easier to use though less accurate, while the Particulate Systems perspective is more accurate but more difficult to use. So then a Hybrid or Integrated Perspective just might be better given the possibility of embodying all the advantages in the one, though also possibly of all the disadvantages.

But what if a Hybrid or Integrated Perspective embodies all the advantages but only some of the disadvantages? Such a perspective should give more reliable design with much better predictivity, and that is exactly what The Point Sinks Sources Design Equations are. The equations set, as conceptualized in "Designing Batch Fermentation Reactors" is a Macro well-mixed perspective that evaluates the reaction strength using particulate systems perspective. This approach when couple with the use of the Happel-Brenner Formula for computing the viscosity, gives the best of both perspective in allowing the incorporation of the heat transfer effect with macro-properties derived with particulate systems perspective.

Obviously, “The Point Sinks Sources Design Equations” perspective proffers the best approach to designing and analyzing both Fermentation and Biologics Bioreactors.

Using the Correct Cellular Reactions Set in Analyzing Bioreactions
Very often, the analysis of bioreactions has started out with substrate utilization rate equations of the form
dCs/dt = YkCsCx/(ks + Cs)
without consideration for the nutrients utilization rate equation. However, as had previously been observed even this representation is incorrect, and that a more rational representation should have the form
dCs/dt = kCx(Cs)pow(Y)
and although this form more represents the reaction of the direct utilization of the substrate, this rate expression is incomplete as it does to factor the damping effect of proteasome and autophagosome reactions resulting in the recycling of substrate metabolites. In order to account for that the rate expression will have to take the form
dCs/dt = kCx(Cs)pow(Y) + r(p) + r(a) + ... + ..
where the r(p) is the rate of proteasome reations and r(a) is the rate for autophagosome reactions to which other cellular reactions may be added as necessary. Interestingly though, this is exactly the consideration of the rate representation adopted for the analysis of substrate and nutrients utilization reactions in "Designing Batch Fermentation Reactors: Design Basics" making the book the must have and must read for better alignment conceptual approach to the analysis of the cellular reactions collective.

Evaluating Heat of [Cellular] Reactions
One of the challenges of bioreactor operation and analysis is the evaluation of the heat of reaction of the cellular reactions. The challenge stems from the circumstance that the cellular reactions form a massive complex network of reactions, some of which are exothermic and some endothermic, and with the reactions being internal, the heat generated by the exothermic reactions must diffuse out through the cell mass and therefore some of the heat get to be utilized for endothermic reactions. So then the enthalpic state of the reaction mixture is define by the net enthalpic state of the cell.

The cell reactions are either net producing heat or net absorbing heat. Heat is generated when the exothermic reactions generate net heat, and is absorbed when the endothermic reactions consume net heat.

Common to both the heat discharge to and heat absorption from the reaction media, is that the heat transport occurs as rather diffusive heat transfer out of the cells. Of course, the heat transferred from the reaction media diffuses through the cell matrix and effectively energizes all reactions of network.

Obviously, every analysis of the thermal dynamics of the bioreactor must necessarily calculate the net generation or absorption of thermal energy. Notably, while the former is useful during Thermal Sterilization analysis and reactor Start-up Heating, the latter is useful for Heat Load Analysis during reactor designs. Further the heat transport analysis needs factor the intra-cell diffusive transport. These aspects of thermal analysis of bio-reactions are often not recognized as critical in bioreactors operations and design, however, the general procedure for evaluating heat of reactions is constructed in "Designing Batch Fermentation Reactions" and should be applicable to all Biological cell reactions.

On the Stagnation Growth Phase
The Stagnation Phase is often described as that time-span in the growth cycle when the replication and death rates are equal. However, this description may not be quite apt for the simple reason that the asserted equality is not uniformly descriptive of that Phase because the growth process continuously evolves through that Phase which it should not be, were the assertion of equality between replication and death actually hold. However, allowance could be made that the onset of the Phase is marked by that equality in a dynamic state, but after which the equality fails incrementally through differentially increasing death rate until the end of the Phase that is marked by the complete ceasing of replication.

Rationally, by the onset of the Stagnation Phase there will have accumulated in the reaction medium sizable number of dead cells and even some necrosis. Also notable is that as of the onset, there is sharply reduced availability of feed-substrate for utilization, and therefore, biogenesis reactions should have become ignited. Therefore it follows that there exists the need to develop the complete Biochemistry of Biogenesis. Indeed, as the growth cycle evolves into the Stagnation Phase, the ignition of the Biogenesis reactions shifts the product concentration relatively unfavorably and therefore intensifies product-inhibition on the overall growth dynamics.

Therefore then the Stagnation Phase is also characterized with the differential increase through the Phase of product-inhibition. The net result of this impact on the reaction dynamics is the differential imbalance of the oft asserted equality of replication and death of microbes during the stagnation Phase. These concepts while implicitly noted in "Designing Batch Fermentation Reactors

Immobilizing Microbes for Continuous Flow Packed Bed Bioreactors
Admittedly, Packed Bed Bioreactors enable the continuous production operations of Fermentation Processes; however, the extent to which such continuous operation is truly productive depends on the method of immobilization. Indeed, the effectiveness of the Continuous Flow is intrinsically rooted in the method of immobilization adopted for implementing the Packed Bed Bioreactor(s).

There are, of course, about fourteen methods of immobilization as extensively delineated in "Designing Batch Fermentation Reactors each with its advantages and disadvantages which make it suited for different reactors such as Fluidized Bed Bioreactors or Packed Bed Bioreactors. So then selection of an immobilization method that is efficacious for packed bed bioreactors is critical in achieving the object of high productivity continuous operation.

In that regard, it is imperative to identify the crucial factors that need addressing within the criteria. Off-the-cuff to be included in the criteria are some of two crucial factors: Restrict the ability of the microbes to replicate so as not to require inclusion of additional Separation Process into the production process, Expose the microbes to fluid phase with such perspective that the manner of expulsion of products can be leveraged through reactor dynamics; and such others as the bioreactor engineer deems important.

Further consideration then centers on "what such other factors are there?" that bioreactor engineers deem worth being factored in the criteria.

The Immobilization Factor: Microbes Reactivity Immobilization-Impact Analysis
Agreed that packed Bed Bioreactors should proffer the highest productivity of all forms of bioreactors when design with application-specificity. However, the choice of utilizing Packed Bed Bioreactor also requires the use of immobilized microbes; and but for the case of self-immobilization, the act of immobilizing a microbe may have some impacts on the reactivity of the microbe relative to the reactivity in the free state. This situation then calls for a mechanism both for evaluating and choosing an immobilization method amongst many as well for performing a more reliable analysis of Packed Bed Bioreactor.

The Immobilization factor, developed in the title contents proffers that metric of immobilization. The value of the Immobilization Factor falls between 0 - 1, and therefore permits a very objective evaluation of methods. Even more significantly because of this range analysis of bioreactors could also be performed using the rate equations of the microbial reactions as determined with the Microbial Suspension Broth using a Batch reactor.

So then available as it were now to a Bioreaction Kineticist as well as Bioreactor Engineer is a tool for both selecting immobilization method and for evaluating with predictivity the performance of any Packed Bed Bioreactors.