Transcript Teoretyczne badania polimeryzacji a

DFT and stochastic studies on the influence
of the catalyst structure and the reaction conditions
on the polyolefin microstructure
Artur Michalaka,b and Tom Zieglera
aDepartment
of Chemistry,
University of Calgary,
Calgary, Alberta, Canada
bDepartment
of Theoretical Chemistry
Jagiellonian University
Cracow, Poland
July 17, 2015
Ethylene polymerization mechanism
b-agostic
+ ethylene
p-complex
insertion
g-agostic
b-agostic
a-olefin polymerization mechanism
Etylene:
n
Linear chain
Propylene:
n
333 methyl branches / 1000 C atoms
a-olefin polymerization mechanism
Etylene:
Observed: up to 130 branches / 1000 C
n
Linear chain
Propylene:
Observed: 210 - 333 branches / 1000 C
n
333 methyl branches / 1000 C atoms
a-olefin polymerization mechanism
Chain isomerization
Diimine catalysts
Etylene:
Observed: up to 130 branches / 1000 C
n
Linear chain
Observed: 210 - 333 branches / 1000 C
Propylene:
n
333 methyl branches / 1000 C atoms
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
N
N
C
C
Pd
C
C
C
C
C
C
C
C
C
C
Diimine catalysts
Etylene:
Observed: up to 130 branches / 1000 C
n
Linear chain
Propylene:
Observed: 210 - 333 branches / 1000 C
n
333 methyl branches / 1000 C atoms
Influence of olefin pressure on the polymer structure
high p - linear structures
low p - hyperbranched structures
Pd – No. of branches independent of p
Ni – No. of braches influenced by p
a-olefin polymerization mechanism
Models for the catalyst:
R
R
Ar
C
N
N
1) generic system:
Ar
C
R = H; Ar = H
Pd
+
2) a variety of systems with
different substituents:
• R = H; Ar = Ph
• R = H; Ar = Ph (Me)2
• R = H; Ar = Ph (i-Pr)2
• R = Me; Ar = H
• R = Me; Ar = Ph (Me)2
• R = Me; Ar = Ph (i-Pr)2
• R2 = An; Ar = H
• R2 = An; Ar = Ph (i-Pr)2
C
C
N
N
Pd
R
R
Models for the catalyst:
Ar
C
Ar
C
N
N
1) generic system:
R = H; Ar = H
Pd
+
2) a variety of systems with
different substituents:
• R = H; Ar = Ph
• R = H; Ar = Ph (Me)2
• R = H; Ar = Ph (i-Pr)2
• R = Me; Ar = H
• R = Me; Ar = Ph (Me)2
• R = Me; Ar = Ph (i-Pr)2
• R2 = An; Ar = H
• R2 = An; Ar = Ph (i-Pr)2
C
C
C
C
C
C
C
C
C
N
N
C
C
Pd
C
C
C
R
R
Models for the catalyst:
Ar
C
Ar
C
N
N
1) generic system:
R = H; Ar = H
Pd
+
2) a variety of systems with
different substituents:
• R = H; Ar = Ph
• R = H; Ar = Ph (Me)2
• R = H; Ar = Ph (i-Pr)2
• R = Me; Ar = H
• R = Me; Ar = Ph (Me)2
• R = Me; Ar = Ph (i-Pr)2
• R2 = An; Ar = H
• R2 = An; Ar = Ph (i-Pr)2
C
C
C
C
C
C
C
C
C
C
C
N
N
C
C
Pd
C
C
C
C
C
R
R
Models for the catalyst:
Ar
C
Ar
C
N
N
1) generic system:
R = H; Ar = H
Pd
+
2) a variety of systems with
different substituents:
• R = H; Ar = Ph
• R = H; Ar = Ph (Me)2
• R = H; Ar = Ph (i-Pr)2
• R = Me; Ar = H
• R = Me; Ar = Ph (Me)2
• R = Me; Ar = Ph (i-Pr)2
• R2 = An; Ar = H
• R2 = An; Ar = Ph (i-Pr)2
C
C
C
C
C
C
C
C
C
C
C
C
C
C
N
N
C
C
Pd
C
C
C
C
C
C
C
C
C
C
Models for the catalyst:
R
R
Ar
C
N
N
1) generic system:
R = H; Ar = H
Ar
C
Pd
+
2) a variety of systems with
different substituents:
• R = H; Ar = Ph
• R = H; Ar = Ph (Me)2
• R = H; Ar = Ph (i-Pr)2
• R = Me; Ar = H
• R = Me; Ar = Ph (Me)2
• R = Me; Ar = Ph (i-Pr)2
• R2 = An; Ar = H
• R2 = An; Ar = Ph (i-Pr)2
C
C
C
C
N
N
Pd
R
R
Models for the catalyst:
Ar
C
Ar
C
N
N
1) generic system:
R = H; Ar = H
Pd
+
2) a variety of systems with
different substituents:
• R = H; Ar = Ph
• R = H; Ar = Ph (Me)2
• R = H; Ar = Ph (i-Pr)2
• R = Me; Ar = H
• R = Me; Ar = Ph (Me)2
• R = Me; Ar = Ph (i-Pr)2
• R2 = An; Ar = H
• R2 = An; Ar = Ph (i-Pr)2
C
C
C
C
C
C
C
C
C
C
C
C
C
N
N
C
C
Pd
C
C
C
C
C
R
R
Models for the catalyst:
Ar
C
Ar
C
N
N
1) generic system:
R = H; Ar = H
Pd
+
2) a variety of systems with
different substituents:
• R = H; Ar = Ph
• R = H; Ar = Ph (Me)2
• R = H; Ar = Ph (i-Pr)2
• R = Me; Ar = H
• R = Me; Ar = Ph (Me)2
• R = Me; Ar = Ph (i-Pr)2
• R2 = An; Ar = H
• R2 = An; Ar = Ph (i-Pr)2
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
N
N
C
C
Pd
C
C
C
C
C
C
C
C
C
C
R
R
Models for the catalyst:
Ar
C
Ar
C
N
N
1) generic system:
R = H; Ar = H
Pd
+
2) a variety of systems with
different substituents:
• R = H; Ar = Ph
• R = H; Ar = Ph (Me)2
• R = H; Ar = Ph (i-Pr)2
• R = Me; Ar = H
• R = Me; Ar = Ph (Me)2
• R = Me; Ar = Ph (i-Pr)2
• R2 = An; Ar = H
• R2 = An; Ar = Ph (i-Pr)2
C
C
C
C
C
C
C
C
C
C
C
C
N
N
Pd
R
R
Models for the catalyst:
Ar
C
Ar
C
N
N
1) generic system:
R = H; Ar = H
Pd
+
2) a variety of systems with
different substituents:
• R = H; Ar = Ph
• R = H; Ar = Ph (Me)2
• R = H; Ar = Ph (i-Pr)2
• R = Me; Ar = H
• R = Me; Ar = Ph (Me)2
• R = Me; Ar = Ph (i-Pr)2
• R2 = An; Ar = H
• R2 = An; Ar = Ph (i-Pr)2
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
N
N
C
C
Pd
C
C
C
C
C
C
C
C
C
C
DFT calculations:
Chain growth:
Chain isomerization:
DFT calculations:
Examples of results:
Ethylene insertion barrier:
DFT: 16.7 kcal/mol
exp.: 17.4 kcal/mol
C
C
C
C
C
C
C
C
C
C
C
C
Isomerization barrier:
DFT: 5.8 (6.8) kcal/mol
exp: 7.2 kcal/mol
C
C
C
C
N
N
C
C
Pd
C
C
C
C
C
C
C
C
C
C
 A. Michalak, T. Ziegler, "Pd-catalyzed Polymerization of Propene - DFT Model
Studies", Organometallics, 18, 1999, 3998-4004.
 A. Michalak, T. Ziegler, "DFT studies on substituent effects in Pd-catalyzed olefin
polymerization", Organometallics, 19, 2000, 1850-1858.
Substituent effect in real systems
Electronic preference Steric effect
(generic system)
(real systems)
alkyl complexes
iso-propyl
iso-propyl
olefin p-complexes
iso-propyl alkyl
n-propyl alkyl
olefin p-complexes
propene
ethene
propene insertion
2,1-
1,2-
Isomerization reactions
0.00
following
1,2-insertion
+4.56
-3.42
+5.84
0.00
following
2,1-insertion
+1.59
Isomerization reactions
0.00
following
1,2-insertion
+4.56
-3.42
+5.84
0.00
following
2,1-insertion
+1.59
Isomerization reactions
0.00
following
1,2-insertion
+4.56
-3.42
+5.84
0.00
following
2,1-insertion
+1.59
Stochastic simulation - how it works
1 C atom attached to the catalyst:
olefin capture
followed by
1,2- or 2,1insertion
Stochastic simulation - how it works
1 C atom attached to the catalyst:
olefin capture
followed by
1,2- or 2,1insertion
Stochastic simulation - how it works
Primary C attached to the catalyst:
1) 1 possible isomerization
2) olefin capture and 1,2- insertion
3) olefin capture and 2,1- insertion
4) termination
2
1
3
4
Stochastic simulation - how it works
Secondary C attached to the catalyst:
1) isomerization to primary C
2) isomerisation to secondary C
3) olefin capture and 1,2- insertion
4) olefin capture and 2,1- insertion
5) termination
Stochastic simulation - how it works
Secondary C attached to the catalyst:
1) isomerization to secondary C
2) isomerisation to secondary C
3) olefin capture and 1,2- insertion
4) olefin capture and 2,1- insertion
5) termination
Stochastic simulation - how it works
Secondary C attached to the catalyst:
1) isomerization to primary C
2) isomerisation to secondary C
3) olefin capture and 1,2- insertion
4) olefin capture and 2,1- insertion
5) termination
Stochastic simulation - how it works
Primary C attached to the catalyst:
1) isomerization to secondary C
2) olefin capture and 1,2- insertion
3) olefin capture and 2,1- insertion
4) termination
Stochastic simulation - how it works
Primary C attached to the catalyst:
1) isomerization to tertiary C
2) olefin capture and 1,2- insertion
3) olefin capture and 2,1- insertion
4) termination
Stochastic simulation - how it works
Stochastic simulation - how it works
Stochastic simulation - how it works
Stochastic simulation - how it works
Probablities of the events
Basic assumption:
relative probabilities (microscopic)
= relative rates (macroscopic):
pi ri

pj rj
p 1
i
i
Macroscopic kinetic expressions with
microscopic barriers for elementary reactions
(calculated or experimental)
Use of macroscopic kinetic expressions
allows us to discuss the effects of the reaction
conditions (temperature and olefin pressure)
36
Probablities of the events
r1  kiso ,1[ b 0 ]
Basic assumption:
relative probabilities (microscopic)
= relative rates (macroscopic):
pi ri

pj rj
r2  kiso,2[b0 ]
p 1
i
i
e.g. isomerization vs. isomerization:
piso.1 riso.1 k iso.1
G1, 2


 exp(
)
piso.2 riso.2 kiso.2
kT
isomerization vs. insertion:
r1  kiso ,1[ b 0 ]
rins.  kins.[p 0 ] 
 kins. K compl .[ b 0 ] polefin
b0 , b1 , b2 - alkyl b-agostic complexes;
p0- olefin p complex;
etc.
piso .1
riso .1
kiso .1


p ins . 1, 2 rins .1, 2 k ins .1, 2 Kco mpl. pole fin
37
Simulations of polymer growth and isomerization
main chain
primary branch
secondary branch
tertiary branch
etc.
Results:
- Polymer chain;
- Total No. of branches;
- Classification of branches:
no. of branches of a given type,
and their length;
- Molecular weight;
Propylene polymerization (theoretical data)
C
C
N
N
Pd
R = H; Ar = H
 A. Michalak, T. Ziegler, „Stochastic modelling of the propylene polymerization catalyzed by the
Pd-based diimine catalyst: influence of the catalyst structure and the reaction conditions on the polymer
microstructure”, J. Am. Chem. Soc, 2002, in press.
Propylene polymerization (theoretical data)
C
C
C
C
C
C
C
C
C
N
N
C
C
Pd
C
C
R=H; Ar= Ph
C
Propylene polymerization (theoretical data)
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
N
N
C
C
Pd
C
C
C
C
C
C
C
C
C
C
R=An; Ar= Ph(i-Pr)2
Propylene polymerization - effect of the catalyst
R=H; Ar=H: 331.6 br.; 66.7% 33.3%; 0
R=H; Ar=Ph: 122.5 br.; 51.7%; 40.1%; 14.2
R=H; Ar=Ph(CH3)2:
269.6 br.;60.9%; 38.1%; 0.89
R=H; Ar=Ph(i-Pr)2:
269.6 br.; 60.9%; 38.1%; 1.37
R=CH3; Ar=Ph(CH3)2:
251.0 br.; 59.7%; 38.7%; 0.93
R=CH3; Ar=Ph(i-Pr)2:
238.2 br.;61.7%; 36.5%; 2.6
R=An; Ar=Ph(i-Pr)2:
255.6 br.; 59.9%; 38.5%; 1.35
The values above the plots denote:
the average number of branches / 1000 C, % of atoms in the
main chain and % in primary branches, and the ratio between
the isomerization and insertion steps.
Colors are used to mark different types of branches (primary,
secondary, etc.).
42
43
Propylene polymerization - temperature effect
No. of branches / 1000 C
T=98K
320
T=198K
300
280
T=298K
260
240
220
0
100
200
300
400
500
T=398K
T [K]
C
C
C
C
C
C
C
C
C
C
C
C
C
N
N
C
C
Pd
C
T=498K
C
C
C
C
C
C
C
C
C
C
C
C
44
Propylene polymerization - temperature effect
No. of branches / 1000 C
T=98K
• Two insertion pathways:
1,2i 2,1320
• Chain straightening follows
T=198K
2,1-insertion only
300
•Lower barrier for the 1,2insertion (by c.a. 0.6 kcal/mol)
280
• Practically each 2,1- T=298K
insertion is followed by chain
straighening
260
240
220
0
100
200
300
400
500
T=398K
T [K]
C
C
C
C
C
C
C
C
C
C
C
C
C
N
N
C
C
Pd
C
T=498K
C
C
C
C
C
C
C
C
C
C
C
C
45
Propylene polymerization - pressure effect
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
N
N
C
C
Pd
C
C
C
C
C
320
C
C
C
No. of branches
C
300
280
260
240
220
0.001
0.01
p [ arbitrary units]
0.1
1
C
46
Propylene polymerization - pressure effect
C
C
C
C
333.3
C
„Ideal” – no chain straighening
C
C
C
C
C
C
C
C
N
N
C
C
Pd
C
C
C
C
C
320
C
C
C
No. of branches
C
300
280
260
240
220
0.001
C
C
C
Exp.: 213br. / 1000 C
0.01
p [ arbitrary units]
0.1
1
C
47
Propylene polymerization - pressure effect
p=0.1
p=0.01
p=0.001
C
C
C
C
C
C
C
p=0.0001
C
C
C
C
C
C
C
C
C
N
N
C
C
Pd
C
C
C
C
C
C
C
C
C
C
48
Ethylene polymerization by Pd-based diimine catalyst
Simulations from experimental data (G)
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
N
N
C
C
Pd
C
C
C
C
C
C
C
C
C
C
49
Ethylene polymerization by Pd-based diimine catalyst
Simulations from experimental data
150
No. of branches
120
90
C
C
C
C
C
C
60
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
N
N
C
C
Pd
C
C
C
C
30
0
0.001
C
C
C
C
C
C
0.01
p [ arbitrary units]
0.1
1
50
Ethylene polymerization by Pd-based diimine catalyst
Simulations from experimental data
150
Exp.
No. of branches
120
90
C
C
C
C
C
C
60
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
N
N
C
C
Pd
C
C
C
C
30
0
0.001
C
C
C
C
C
C
0.01
p [ arbitrary units]
0.1
1
51
Ethylene polymerization by Pd-based diimine catalyst
Simulations from experimental data
p
52
Ethylene polymerization by Pd-based diimine catalyst
Simulations from experimental data
p
53
Ethylene polymerization by Pd-based diimine catalyst
Simulations from experimental data
180
No. of branches
150
120
90
C
C
60
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
N
N
C
C
Pd
C
C
C
30
C
C
C
C
C
C
C
0
0
100
200
300
T [K]
400
500
54
Ethylene polymerization by Pd-based diimine catalyst
Simulations from experimental data
180
No. of branches
150
120
90
C
C
60
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
N
N
C
C
Pd
C
C
C
30
C
C
C
C
C
C
C
0
0
100
200
300
T [K]
400
500
55
Ethylene polymerization by Pd-based diimine catalyst
Simulations from experimental data (G)
C
C
C
C
C
C
 A. Michalak, T. Ziegler, „DFT and stochastic studies on the
factors controlling branching and microstructure of polyethylenes in
the polymerization processes catalyzed by the late-transition metal
complexes”, in preparation
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
N
N
C
C
Pd
C
C
C
C
C
C
C
C
C
C
56
Ethylene polymerization - model studies on the effects of catalyst
(elementary reaction barriers), temperature, and pressure on the
microstructure of polymers
57
Ethylene polymerization
- pressure / catalyst effects
No. of branches / 1000 C
350
E1=1.0 kcal/mol
300
E2=1
E2=2
E2=3
E2=4
E2=5
E2=6
E2=7
E2=8
E2=9
250
200
150
100
50
0
0.0001
0.001
0.01
p [arbitrary units]
0.1
1
58
Ethylene polymerization
- pressure / catalyst effects
pressure independent region
No. of branches / 1000 C
350
E1=1.0 kcal/mol
300
E2=1
E2=2
E2=3
E2=4
E2=5
E2=6
E2=7
E2=8
E2=9
250
200
150
100
50
0
0.0001
0.001
0.01
0.1
p [arbitrary units]
1
E1=2.0 kcal/mol
450
400
350
300
250
200
150
100
50
0
0.0001
0.001
0.01
0.1
1
500
450
400
350
300
250
200
150
100
50
0
0.0001
E1=3.0 kcal/mol
0.001
0.01
0.1
59
1
For
TheNi-diimine
faster is the
catalyst
isomerisation
the isomerisation
(comparedistoslower
insertions),
then for
thePd
more extended is the
i.e.
pressure
for Pd independent
the pressure region.
independent region is more extended toward higher values of
the pressure
E1=4.0 kcal/mol
600
500
500
400
400
300
300
200
200
100
100
0
0.0001
E1=6.0 kcal/mol
600
0
0.0001
0.001
0.01
0.1
1
0.001
0.01
0.1
1
60
The polyethylene gallery
E1 1; E2=2 kcal/mol
E1 2; E2=5 kcal/mol
E1 1; E2=5 kcal/mol
E1 4; E2=5 kcal/mol
E1 1; E2=7 kcal/mol
p=0.0001; T=298 K
Ethylene polymerization with the neutral
anilinotropone Ni-based catalyst
N
O
Ni
P
Experimental data:
Hiks, F.A., Brookhart M.
Organometallics 2001, 20, 3217.
Ethylene polymerization with the neutral
anilinotropone Ni-based catalyst
120
br./1000C
100
80
60
40
20
0
0
100
200
300
400
500
600
700
p [psig]
Experimental data:
Hiks, F.A., Brookhart M.
Organometallics 2001, 20, 3217.
br./1000C
80
70
60
50
40
30
20
10
0
20
40
60
80
T [C]
100
120
Ni-anilinotropone catalyst - cis/trans isomers
Alkyl complexes:
Ethylene p-complexes:
Ni-anilinotropone catalyst – results for real catalyst
Secondary alkyl
10
Primary alkyl
9.5
iso. TS
ins. TS
iso. TS
5.8
5
ins. TS
0
ins. TS
1.9
1.9
0.0
Alkyl
Alkyl
3.4
ins. TS
1.3
1.7
Alkyl
Alkyl
-5
-10
p-12.9
-15
-17.9
-20
pN-isomers
O-isomers
-17.1
-17.5
p-
p-
5.7
Ni-anilinotropone catalyst – stochastic simulations
Secondary alkyl
10
Primary alkyl
9.5
iso. TS
ins. TS
iso. TS
5.8
5
ins. TS
0
ins. TS
1.9
1.9
0.0
Alkyl
Alkyl
3.4
ins. TS
1.3
1.7
Alkyl
Alkyl
-5
-10
p-12.9
-15
-17.9
-20
pN-isomers
O-isomers
-17.1
-17.5
p-
p-
5.7
br./1000C
Ni-anilinotropone catalyst – stochastic simulations
160
140
120
100
80
60
40
20
0
14 - 600 psig
0
0.02
0.04
0.06
p [arb.u.]
0.08
0.1
Ni-anilinotropone catalyst – stochastic simulations
br./1000C
160
140
Theoret.
120
100
80
60
Exp.
40
20
0
0
0.0038
0.0076
0.0114
0.0152
0.019
0.0228
p [arb.u.]
14 50 100
200
p [psig]
400
600
br./1000C
Ni-anilinotropone catalyst – stochastic simulations
100
90
80
70
60
50
40
30
20
10
0
Theoret.
Exp.
40
50
60
70
T [C]
p = 0.011 arb.u. / p = 400 psig
80
90
100
Conclusions
DFT:
• energetics of elementary reactions in a reasonable agreement with
experimental data
• understanding of the electronic and steric influence of the catalysts
substituents
Stochastic modelling:
• provides a link between the molecular modeling on the microscopic and
macroscopic level
•identifies the factors controlling of the polyolefin branching and their
microstructure
•demonstrates that a huge range of polyolefin materials with specific
microstructures can be rationally designed by modification of the catalysts
• can be also useful for interpretation of the experimental results
Acknowledgements. This work was supported by the National Sciences and Engineering Research
Council of Canada (NSERC), Nova Chemical Research and Technology Corporation as well as donors
of the Petroleum Research Fund, administered by the American Chemical Society (ACS-PRF No.
36543-AC3). A.M. acknowledges NATO Fellowship. Important parts of the calculations was performed
using the UofC MACI cluster.
DFT:
• energetics of elementary reactions in excellent agreement with
experimental data
• understanding of the electronic and steric influence of the catalysts
substituents
Stochastic modelling:
• provides a link between the molecular modeling on the microscopic and
macroscopic level
• allows one to identify the factors controlling of the polyolefin branching
and their microstructure as well as its dependence on the reaction
conditions
• demonstrates that a huge range of polyolefin materials with specific
microstructures can be rationally designed by modification of the catalysts
• can be also useful for interpretation of the experimental results.`