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Batch Chromatography

Revision as of 15:45, 21 November 2012 by Zhangy (talk | contribs)


Description of the process

Preparative liquid chromatography as a crucial separation and purification tool has been widely employed in food, fine chemical and pharmaceutical industries. Chromatographic separation at industry scale can be operated either discontinuously or in a continuous mode. The continuous case will be addressed in the benchmark SMB, and here we focus on the discontinuous mode -- batch chromatography.

The dynamics of the batch chromatographics column can be described precisely by an axially dispersed plug-flow model with a limited mass-transfer rate characterized by a linear driving force (LDF) approximation. In this model the differential mass balance of component i (i=A,B,) in the liquid phase can be written as:


\frac{\partial c_i}{\partial t}+\frac{1-\epsilon}{\epsilon}\frac{\partial q_i}{\partial t}+u\frac{\partial c_i}{\partial z}-D_i\frac{\partial^2 c_i}{\partial z^2}=0, \qquad z\in(0,\;L), \qquad [1]

where c_i and q_i are the concentrations of solute i in the liquid and solid phases, respectively, u the interstitial liquid velocity, \epsilon the column porosity, t the time coordinate, z the axial coordinate along the column, L the column length, D_i=\frac{uL}{Pe} the axial dispersion coefficient and Pe the Péclet number. The adsorption rate is modeled by the LDF approximation:


\frac{\partial q_i}{\partial t} = K_{m,i}\,(q^{Eq}_i-q_i), \qquad z\in[0,\;L], \qquad [2]

where K_{m,i} is the mass-transfer coefficient of component i and q^{Eq}_i is the adsorption equilibrium concentration calculated by the isotherm equation for component i. Here the bi-Langmuir isotherm model is used to describe the adsorption equilibrium:


q^{Eq}_i=\frac{H_{i,1}\,c_i}{1+\sum_{j=A,B}K_{j,1}\,c_j}+\frac{H_{i,2}\,c_i}{1+\sum_{j=A,B}K_{j,2}\,c_j},\; i=A,B,  \qquad [3]

where H_{i,1} and H_{i,2} are the Henry constants, and K_{j,1} and K_{j,2} the thermodynamic coefficients.

The boundary conditions for Eq. [1] are specified by the Danckwerts relations:


D_i\left.\frac{\partial c_i}{\partial z}\right|_{z=0} = u\,(\left.c_i\right|_{z=0}-c^{in}_i), \quad\quad \left.\frac{\partial c_i}{\partial z}\right|_{z=L}=0,  \qquad [4]

where c^{in}_i is the concentration of component i at the inlet of the column. A rectangular injection is assumed for the system and thus


c^{in}_i=\left \{ \begin{array}{cc}  c^F_i,  &\text{if } t \le t_{inj};\\
      0,  &\text{if } t >   t_{inj}.

\end{array}
\right .

where c^F_i is the feed concentration for component i and t_{inj} is the injection period. In addition, the column is assumed unloaded initially:


c_i(t=0,z)=q_i(t=0,z)=0,\quad z\in[0,\;L],\;i=A,B.  \qquad [5]

Discretization

In this model, the feed flow-rate Q and injection period t_{inj} are often considered as the operating variables, and will be parametrized as \mu=(Q,\,t_{inj}). Using the finite volume discretization, we can get the full order model,


\left\{
\begin{array}{ll}
\mathbf{ A c}_i^{k+1} = \mathbf{Bc}_i^{k} + \mathbf b_i^k 
- \frac{1-\epsilon}{\epsilon} \Delta t \mathbf h_i^k,\\
\mathbf{q}_i^{k+1} = \mathbf{q}_i^{k} + \Delta t \mathbf h_i^k,
\end{array}
\right .

with \mathbf h_i^k = K_{m,i} (\mathbf q^{Eq}_i - \mathbf q_i^k),\; i=A,B, k\in \mathbb K = \{0,1,\cdots,K\}, the index for the time instance, and \Delta t is the time step determined by the stability condition. Here, the bold capital \mathbf {A,B} are constant matrices, and the bold \mathbf {c} and  \mathbf{q} are the solution vector in the high  \mathcal N-dimensional space.