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.
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