1. Introduction
As binding of the solute by adsorption is an exothermic process and desorption is an endothermic process, migration speeds in chromatographic columns depend on temperature. Thermal effects are widely considered for gas phase flows through solid packings [
1,
2,
3,
4,
5,
6]. However, such effects are usually neglected in the liquid chromatography process (a) by considering the heat capacities of the two phases larger than the adsorption enthalpies and (b) by assuming a sufficiently larger value of the thermal conductivity to maintain a uniform temperature inside the column. As a result, most of the chromatographers have assumed isothermal conditions during the operation of liquid chromatography processes. However, there is experimental evidence of temperature fluctuations inside liquid chromatographic columns [
7,
8]. It has been found that temperature gradients broadly influence the production rate, yield and efficiency of the column. While, some studies show that they can reduce viscosity and can improve solubility and diffusivity [
9,
10]. Both separation and reactions are significantly affected by temperature fluctuations. Only a few contributions are available in the literature dealing with segmented temperature gradients in liquid chromatography [
11,
12,
13,
14,
15,
16,
17,
18,
19]. One method implemented is temperature gradient interaction chromatography with triple detection (TGIC-TD). The method was suggested by Chang et al. to separate branched polymers according to their molecular weight with a high resolution [
20,
21,
22,
23].
In this study, a specific forced non-isothermal operation of a liquid chromatographic process is theoretically studied. Particularly, the internal temperature of the column is changed at a specific position through an external heating or cooling source fixed to the surface of the column wall. The heating accelerates and the cooling decelerates the migration speed of the fronts in specific regions of the column.
The current study is restricted to an equilibrium model, that is, axial dispersion of the concentration and temperature fronts are ignored. Equilibrium theory is very effective to design and analyze different complex processes. One of its powerful features is that it can successfully predict, tackle and explain the dynamic behavior of such complex processes. For comprehensive studies on equilibrium theory, see References [
24,
25,
26]. In addition, it is further assumed that temperature changes in a forced stepwise manner uniformly inside the cross-sectional area of the column and no radial gradients occur. Thus, no energy balance is needed for the transport of heat through the column; instead, we provide temperature inside the column as a piece-wise step function.
The method of characteristics is utilized to solve the current model equations analytically. The method changes the original coordinate system
to a new coordinate system
in order to reduce the given partial differential equation (PDE) to an ordinary differential equation (ODE) along certain curves in the
plane. Such curves, along which a given PDE reduces to an ODE, are called
characteristic curves or just characteristics, which carry some information [
27]. These curves are particularly relevant to the study of equilibrium theory discussed in this manuscript. Several case studies are conducted to quantify the influence of temperature gradients generated via an externally fixed source, production rate and yield of a chromatographic column.
The remaining parts of the paper are organized as follows. In
Section 2, the non-isothermal chromatographic concept and model are introduced. In
Section 3, the method of characteristic is applied to derive the solution trajectories and for performance evaluation, the production rate of the column is introduced. In
Section 4, various scenarios are analyzed for illustration. Materials and methods used are given in
Section 5 and conclusions are drawn in
Section 6.
2. Non-Isothermal Equilibrium Model
We consider multi-component mixtures which are injected in a chromatographic column. The column is packed with spherical adsorbent particles. It is assumed that the bed is homogeneous and both axial and radial dispersion of the profiles are negligible. Furthermore, there is no interaction between the carrier fluid or solvent, and the solid phase and the composite fluid is assumed incompressible.
The considered equilibrium model deals with a fast rate of mass transfer and, as the name represents, it neglects molecular diffusion, axial dispersion and mass transfer resistances.
Let us consider concentrations
for
components, that are the functions of the spatial variable
, which is taken as distance along the column of length
, and time
t. Here,
denotes the arbitrary number of components. The concentrations
are to be determined by mass balances. The concentrations
of the adsorbed stationary phases are functions of the respective concentrations
and the induced temperature
T which are generally expressed in the form of functions, known as adsorption isotherms. Further,
u represents the interstitial velocity which is assumed to be constant for all temperatures, and
symbolizes the porosity of the bed. Both are constants. The balance law for a multi-component mixture in a volume element of the column mass is expressed as
For illustration of the wider applicable principle of segmented thermal gradients, we divide the z-domain just in two equal segments, from to , segment I, and from to , segment II. We consider that each of the segments behaves like an individual column and that the overall column is described by connecting these two segments. The outlet concentration profiles of segment I are the inlet concentration profiles for segment II. Hence, we define separate initial and boundary conditions for each segment and take care of conservation of masses in each segment separately.
Segment I is maintained at a fixed reference temperature, , while the temperature of segment II is changed uniformly via a fixed source placed at the outer surface of the conducting wall providing instantaneous heating, or cooling, , to the whole segment.
To illustrate the effect of the forced periodic regime, we illustrate in
Figure 1 and
Figure 2 three different scenarios. In the first scenario, c.f.
Figure 1a, a single-solute pulse injection into the column is shown. Hereby, it is allowed to face, for example, a lower temperature in segment II. As the pulse starts crossing
, its right part in segment II decelerates and its left part in segment I is still moving at the larger reference speed. As a result, the profile becomes narrower and more concentrated in segment II. After completely entering into segment II, the whole pulse is migrating at uniform low speed and reaches the column outlet. The second possible scenario is similar to the first one but now the pulse faces a higher temperature in segment II, see
Figure 1b. As a result, an opposite effect is observed, that is, the pulse becomes broader and more diluted. A third possible scenario is more complicated and refers to the intrinsic goal of chromatography to separate components. For illustration, a three-component mixture is considered assuming that the first two components are migrating much faster than the third component (case “Late Eluter”), see
Figure 2. Then, depending on the individual speeds, each component of the mixture faces the temperature changes at different times in segment II. Suitable changes in the temperature of segment II can improve separation performance, for example, production rate. For illustration, the mixture is injected periodically to the column both under isothermal and then non-isothermal conditions.
Figure 2 reveals the potential to reduce the cycle time, that is, the time difference between two consecutive injections, in the non-isothermal case,
, compared to the isothermal case,
.
Note that, another possible case “Early Eluter”, in which the first component is migrating much faster than the last two components, also exists but it is not illustrated below.
We formulate now mathematically, the exploitation of the temperature manipulation in segment II. A change in the temperature is performed when a certain pulse, completely or partially, crosses the point
of the column. The resulting switching times for cooling or heating are denoted by
for
. Further let
be the initial time and
be the simulation time corresponding to each component
i. To each semi-open interval
for
and
, we associate a constant temperature for segment II of the column. We take a sequence
, where
are representing reference, low and high temperatures, respectively. With this, we define a first version of the temperature function for our theoretical experiment as
Note that in a general case, we will have to consider specific adjusted finite sequences of
for each component of a mixture considering the specific migration and separation properties. Also the sequence of the switching times
will depend on the specific migration speeds of the adsorption and desorption fronts.
The distribution equilibria of the components between the mobile phases and the solid phases under equilibrium conditions are described by a function, called, for a given constant temperature, adsorption isotherm. We apply a linear relation in concentration using temperature dependent Henry constants
. This temperature dependence is expressed via Arhennius function incorporating the enthalpy of adsorption
for each component
i and the universal gas constant
R. Thus the adsorption isotherm is linear in concentration and nonlinear in temperature, as expressed below
where
is the Arhennius function depending upon
T.
The columns (segments) are assumed to be fully regenerated. We inject concentration
of component
i for the duration of time
. Let us denote the time in which the adsorption front of a pulse reaches
by
and the general cycle time between the injections by
. Both will be calculated in
Section 3. Then the initial and boundary conditions for segment I, processing
number of injections, are given as
While for segment II holds
3. Analytical Solution
In this section we derive analytical expressions to quantify the transient concentration profiles, generally denoted by
, under the influence of the described segmented temperature gradients. For this we first calculate the trajectories,
. After dividing both sides of Equation (
1) by
and introducing the phase ratio
, we obtain
By applying the chain rule over
, we obtain
Since the temperature is constant in each segment, so
and thus, the obtained value of
from the above equation, when plug into Equation (
6) yields
By Equation (
3),
. Plugging this value in Equation (
7), after simplification, yields
Now, the method of characteristic is applied to reduce the above PDE to an ODE. As a result, analytical expressions for solution trajectories (paths) are obtained. According to Equation (
8), the characteristic speed of the fronts corresponding to component
i, using
as a general time parameter, is given as
The solution of Equation (
9) provides the trajectories of the solutions. Since the temperature
is piece-wise constant, one can integrate this ODE easily. Further, we already know that
and
. For
, Equation (
9) gives
The above equation gives different space-time positions for each component. Using this equation, we can easily find the time
:
For
, we have
. Now, the characteristics speed is affected by the temperature change. This effect depends on the particular switching time
. Suppose that we have
for some
. This means that
are the exploitable switching times in the interval
. Note that these switching times may be different for different components
i. Then, Equation (
10) can be integrated as
The term
, by setting
, in the above equation tells that the temperature of the pulse stays still
until the whole pulse enters segment II. This is possible when both the segments are initially kept at the same temperature. Later, in the case studies, we will discuss this scenario as a special case, c.f.
Section 4.1, (Type II). We neglect this term for the case where both the segments are initially kept at different temperatures, c.f.
Section 4.1, (Type I).
We denote the time dependent position of the adsorption (ad) front of the pulse by
, while the position of the desorption (de) front by
for component
i. The adsorption front enters the column at
while the desorption front enters at
. With these initial times, the adsorption and desorption fronts can be explicitly determined. After a simple calculation, the characteristic curve or the space-time trajectory for
is obtained from Equation (
12) by taking
again as
Further, we set
and obtain
for
.
The above trajectories allow calculating the solution for the components’ concentration profiles as function of
z and
t. The solution consists of three parts divided in the time domain by a first state,
, controlled by the reference temperature, a third (final) state,
, controlled by a different temperature in segment II and an intermediate state,
, which is influenced by both the temperatures via changing migration velocities, c.f.
Figure 3. This later state gradually transforms the concentration in state
,
, to the concentration in state
,
, via the concentration in itself,
. The concentration in each state depends on the difference between the trajectories of the adsorption and desorption fronts (space-bandwidths) in each state because it varies from state to state. Let
be the space-bandwidth of the pulse in state
, and
be the space-bandwidth in state
. These space-bandwidths are certainly constant because both adsorption and desorption fronts are migrating with same speeds in the corresponding states. But, the space-bandwidth in state
is not constant because, in this state, the desorption front of the pulse is in segment I and the adsorption front is in segment II. So both are migrating with different speeds. As much as, the pulse enters segment II, the space-bandwidth in state
tends to that in state
. Let us denote this variable space-bandwidth by
, c.f.
Figure 4.
Figure 3 and
Figure 4 will be explained later to illustrate state
graphically. We denote the part of
in segment I, by
and its part in segment II, by
. Then
and hence, by the conservation of mass, the concentration solutions in the states
and
are given as
and
The main aim of the temperature gradients being analyzed in this article is to enhance the production rate,
, which is defined at the end of this section (Equations (
20) and (
21)). This can be achieved by reducing the cycle time, c.f.
Figure 2. In
Section 4.2, we particularly calculate a cycle time with a conservative limit. We consider that a new injection should be introduced in such a way that the adsorption front of its fastest component reaches the middle of the column,
, at the same time as the desorption front of the slowest component of the previous injection leaves the column. Exactly at this time we switch the temperature of segment II back to its initial value and repeat the same sequence shifted by the cycle time. To calculate the cycle time denoted generally by
, we use Equation (
13). Let
be the time taken by the desorption front of the slowest component of the previous injection having Henry constant, say
, to reach
. Then the expression for
in terms of
, taking
, is given as
After simplification, we get the value of the time
as
On the other hand, the time
, in which the adsorption front of the fastest component of the next injection, having Henry constant, say
, covers the distance
, is the same as for the fastest component of previous injection, and is given by Equation (
11) as
Then, the cycle time
is given as
Equation (
19) can be used to calculate the cycle times
and
for both isothermal and the more flexible non-isothermal conditions, respectively, because
.