Difference between revisions of "Diels-Alder Reaction Experimental Design"

Latest revision as of 15:17, 29 July 2016

The Diels-Alder Reaction is an organic chemical reaction. A conjugated diene and a substituted alkene react and form a substituted cyclohexene system. Stefan Körkel used this model in his PhD thesis to compute optimum experimental designs.

Model Formulation

The reactionkinetics can be modelled by the following differential equation system:

$\begin{array}{rcl} \dot{n_1}(t) &=& -k \cdot \frac{n_1(t) \ \cdot \ n_2(t)}{m_{tot}}, \\ & & \\ \dot{n_2}(t) &=& -k \cdot \frac{n_1(t) \ \cdot \ n_2(t)}{m_{tot}}, \\ & & \\ \dot{n_3}(t) &=& \ \ k \cdot \frac{n_1(t) \ \cdot \ n_2(t)}{m_{tot}} \\ & & \\ \dot{n_4}(t) &=& 0 \end{array}$

The reaction velocity constant $k$ consists of two parts. One part reflects the non-catalytic and the other the catalytic reaction. The velocity law follows the Arrhenius relation

$k = k_1 \ \cdot \ exp(- \frac{E_1}{R} \ \cdot \ (\frac{1}{T(t)} \ - \ \frac{1}{T_{ref}}) ) \ + \ k_{cat} \ \cdot \ c_{cat} \ \cdot \ exp(-\lambda \ \cdot \ t) \ \cdot \ exp( - \frac{E_{cat}}{R} \ \cdot \ (\ \frac{1}{T(t)} \ - \ \frac{1}{T_{ref}}) )$

Total mass:

$m_{tot} = n_1 \ \cdot \ M_1 \ + \ n_2 \ \cdot \ M_2 \ + \ n_3 \ \cdot \ M_3 \ + \ n_4 \ \cdot \ M_4$

Temperature in Kelvin:

$T(t) = \vartheta (t) + 273$

The ODE system is summarized to:

$\begin{array}{rcl} \dot{x}(t) &=& f(x(t), u(t), p) \end{array}$

Constraints

The control variables are constrained with respect to the mass of sample weights (initial mass):

$\begin{array}{cll} 0.1 & \le & n_{a1} \ \cdot \ M_1 \ + \ n_{a2} \ \cdot \ M_2 \ + \ n_{a4} \ \cdot \ M_4 \le 10 \end{array}$

and to the mass of active ingredient content (fraction of active substances):

$\begin{array}{cll} 0.1 & \le & \frac{ n_{a1} \ \cdot \ M_1 \ + \ n_{a2} \ \cdot \ M_2 }{ n_{a1} \ \cdot \ M_1 \ + \ n_{a2} \ \cdot \ M_2 \ + \ n_{a4} \ \cdot \ M_4 } \le 0.7 \end{array}$

Optimum Experimental Design Problem

The aim is to compute an optimal experimental design $\xi = (q,w)$ which minimizes the uncertainties of the parameters $k_1, k_{cat}, E_1, E_{cat}, \lambda$ . So, we have to solve the following optimum experimental design problem:

$\begin{array}{cll} \displaystyle \min_{x^i,\ G^i,\ F^i,\ Tc^i,\ n_{a1}^i,\ n_{a2}^i,\ n_{a4}^i,\ c_{kat}^i,\ \vartheta(t)^i} && trace(F^{-1} (t_{end})) \\[1.5ex] \mbox{s.t.} \\ \dot{x}^i(t) & = & f(x^i(t), u^i(t),p), \\ \\ h(t) & = & \frac{n_3(t) \ \cdot \ M_3}{m_{tot}} \ \cdot \ 100 \\ \\ \dot{G}^i(t) & = & f_x(x^i(t),u^i(t),p)G^i(t) \ + \ f_p(x^i(t),u^i(t),p) \\ \\ \dot{F}(t) & = & \sum\limits_{i=1}^{4} w^i(t) (h^i_x(x^i(t),u^i(t),p)G^i(t))^T (h^i_x(x^i(t),u(t),p)G^i(t)) \\ \\ 0.1 & \le & n_{a1} \ \cdot \ M_1 \ + \ n_{a2} \ \cdot \ M_2 \ + \ n_{a4} \ \cdot \ M_4 \\ \\ 10 & \ge & n_{a1} \ \cdot \ M_1 \ + \ n_{a2} \ \cdot \ M_2 \ + \ n_{a4} \ \cdot \ M_4 \\ \\ 0.1 & \le & \frac{ n_{a1} \ \cdot \ M_1 \ + \ n_{a2} \ \cdot \ M_2 }{ n_{a1} \ \cdot \ M_1 \ + \ n_{a2} \ \cdot \ M_2 \ + \ n_{a4} \ \cdot \ M_4 } \\ \\ 0.7 & \ge & \frac{ n_{a1} \ \cdot \ M_1 \ + \ n_{a2} \ \cdot \ M_2 }{ n_{a1} \ \cdot \ M_1 \ + \ n_{a2} \ \cdot \ M_2 \ + \ n_{a4} \ \cdot \ M_4 } \\ \\ \vartheta(t) & = & \left\{ \begin{array}{cl} \vartheta_{lo} + 273 & t \in [t_0,2] \\ \vartheta_{lo} + \frac{t-2}{6} ( \vartheta_{up} - \vartheta_{lo} ) + 273 & t \in [2,8] \\ \vartheta_{up} + 273 & t \in [8,t_{end}] \end{array} \right. \\ & & x \in \mathcal{X},\,u \in \mathcal{U},\, p \in P \\ \dot{z}^i(t) & = & w^i(t) \\ z(0) & = & 0 \\ w^i(t) &\in& [0,1] \\ 0 & \le & 4 - z^i(t_f). \\ \end{array}$

State variables
Name	Symbol	Initial value ( $t_0$ )
Molar number 1	$n_1(t)$	$n_1(t_0) = n_{a1}$
Molar number 2	$n_2(t)$	$n_2(t_0) = n_{a2}$
Molar number 3	$n_3(t)$	$n_3(t_0) = 0$
Solvent	$n_4(t)$	$n_4(t_0) = n_{a4}$

Constants
Name	Symbol	Value
Molar Mass	$M_1$	0.1362
Molar Mass	$M_2$	0.09806
Molar Mass	$M_3$	0.23426
Molar Mass	$M_4$	0.236
Universal gas constant	$R$	8.314
Reference temperature	$T_{ref}$	293
St.dev of measurement error	$\sigma$	1

Remember, in an optimum experimental design problem the parameters of the model are fixed. But, we minimize the parameter's uncertainties by optimizing over the control variables and functions.

Fixed parameters
Name	Symbol	Value
Steric factor	$k_1$	$p_1 \cdot 0.01$
Steric factor	$k_{kat}$	$p_2 \cdot 0.10$
Activation energie	$E_1$	$p_3 \cdot 60000$
Activation energie	$E_{kat}$	$p_4 \cdot 40000$
Catalyst deactivation coefficient	$\lambda$	$p_5 \cdot 0.25$

with $p_j = 1, \ j =1, \dots, 5$

Optimization/control variables
Name	Symbol	Interval	Initial value Exp 1	Initial value Exp 2	Initial value Exp 3	Initial value Exp 4
Initial molar number 1	$n_{a1}$	[0,10.0]	1.0	1.0	1.0	1.0
Initial molar number 2	$n_{a2}$	[0,10.0]	1.0	1.0	1.0	1.0
Initial molar number 4	$n_{a4}$	[0.4,9.0]	2.0	2.0	2.0	2.0
Concentration of the catalyst	$c_{kat}$	[0,10.0]	0.0	1.0	2.0	3.0

Control function
Name	Symbol	Time interval	Value interval	Initial value Exp 1	Initial value Exp 2	Initial value Exp 3	Initial value Exp 4
Initial molar number 1	$\vartheta(t)$	$[t_0,2]$	[20.0,100.0]	20.0	60.0	40.0	20.0
Initial molar number 1	$\vartheta(t)$	$[2,8]$	[20.0,100.0]	20.0	60.0	40.0	20.0
Initial molar number 1	$\vartheta(t)$	$[8,t_{end}]$	[20.0,100.0]	20.0	60.0	40.0	20.0

Measurement grid

$\begin{array}{llll} t_0 = 0 & & & \\ t_{end} = 20 & & & \\ t_j = j/3, & j = 1,\dots, 15, & t_j = j - 10, & j = 16, \dots, 20. \end{array}$

Source Code

The VPLAN code using VPLAN can be found in: Diels-Alder Reaction Experimental Design (VPLAN)

References

R. T. Morrison and R.N. Boyd. Organic Chemistry. Allyn and Bacon, Inc., 4th edition, 1983
S. Körkel. Numerische Methoden für Optimale Versuchsplanungsprobleme bei nichtlinearen DAE-Modellen.PhD thesis, Universität Heidelberg, Heidelber,2002

@@ Line 81: / Line 81: @@
   \dot{G}^i(t) & = & f_x(x^i(t),u^i(t),p)G^i(t) \ + \ f_p(x^i(t),u^i(t),p) \\
   \\
-  \dot{F}(t) & = & \sum_{i=1}^{4} w^i(t) (h^i_x(x^i(t),u^i(t),p)G^i(t))^T (h^i_x(x^i(t),u(t),p)G^i(t)) \\
+  \dot{F}(t) & = & \sum\limits_{i=1}^{4} w^i(t) (h^i_x(x^i(t),u^i(t),p)G^i(t))^T (h^i_x(x^i(t),u(t),p)G^i(t)) \\
   \\
- \dot{z}^i(t)   & = & w^i(t)  \\
-z(0) & = & 0 \\
-w^i(t) &\in& [0,1] \\
-&  \ge & 4 - z^i(t_f) \\
 .1 & \le & n_{a1} \ \cdot \ M_1 \ + \ n_{a2} \ \cdot \ M_2 \ + \ n_{a4} \ \cdot \ M_4    \\
   \\
@@ Line 99: / Line 95: @@
                                         \vartheta_{up} + 273  &  t \in [8,t_{end}]
                       \end{array} \right. \\
-& & x  \in  \mathcal{X},\,u \in \mathcal{U},\, p \in P .
+& & x  \in  \mathcal{X},\,u \in \mathcal{U},\, p \in P \\
+ \dot{z}^i(t)   & = & w^i(t)  \\
+z(0) & = & 0 \\
+w^i(t) &\in& [0,1] \\
+&  \le & 4 - z^i(t_f). \\
 \end{array}
 </math>
@@ Line 204: / Line 204: @@
 |Symbol
 |Interval
+|Initial value Exp 1
+|Initial value Exp 2
+|Initial value Exp 3
+|Initial value Exp 4
 |-
 |Initial molar number 1
 |<math>n_{a1}</math>
-|[0.4,9.0]
+|[0,10.0]
+|1.0
+|1.0
+|1.0
+|1.0
 |-
 |Initial molar number 2
 |<math>n_{a2}</math>
-|[0.4,9.0]
+|[0,10.0]
+|1.0
+|1.0
+|1.0
+|1.0
 |-
 |Initial molar number 4
 |<math>n_{a4}</math>
 |[0.4,9.0]
+|2.0
+|2.0
+|2.0
+|2.0
 |-
 |Concentration of the catalyst
 |<math>c_{kat}</math>
-|[0.0,6.0]
+|[0,10.0]
+|0.0
+|1.0
+|2.0
+|3.0
 |}
@@ Line 229: / Line 249: @@
 |Time interval
 |Value interval
-|Initial value
+|Initial value Exp 1
+|Initial value Exp 2
+|Initial value Exp 3
+|Initial value Exp 4
 |-
 |Initial molar number 1
@@ Line 235: / Line 258: @@
 |<math>[t_0,2]</math>
 |[20.0,100.0]
+|20.0
+|60.0
+|40.0
 |20.0
 |-
@@ Line 241: / Line 267: @@
 |<math>[2,8]</math>
 |[20.0,100.0]
+|20.0
+|60.0
+|40.0
 |20.0
 |-
@@ Line 247: / Line 276: @@
 |<math>[8,t_{end}]</math>
 |[20.0,100.0]
+|20.0
+|60.0
+|40.0
 |20.0
 |}
@@ Line 262: / Line 294: @@
 == Source Code ==
-* The VPLAN code using [[:Category: VPLAN | VPLAN code]] can be found in: [[Diels-Alder Reaction Experimental Design (VPLAN)]]
+* The VPLAN code using [[:Category: VPLAN | VPLAN]] can be found in: [[Diels-Alder Reaction Experimental Design (VPLAN)]]
 == References ==

Difference between revisions of "Diels-Alder Reaction Experimental Design"

Latest revision as of 15:17, 29 July 2016

Contents

Model Formulation

Constraints

Optimum Experimental Design Problem

Source Code

References

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