DFT and stochastic studies on the influence of the catalyst structure and the reaction conditions on the polyolefin microstructure Artur Michalak a,b and.

DFT and stochastic studies on the influence of the catalyst structure and the reaction conditions on the polyolefin microstructure Artur Michalak a,b and Tom Ziegler a a Department of Chemistry, University of Calgary, Calgary, Alberta, Canada b Department of Theoretical Chemistry Jagiellonian University Cracow, Poland Artur Michalak a,b and Tom Ziegler a a Department of Chemistry, University of Calgary, Calgary, Alberta, Canada b Department of Theoretical Chemistry Jagiellonian University Cracow, Poland June 2, 2015

Ethylene polymerization mechanism  -agostic  -complex + ethylene  -agostic  -agostic insertion

n Propylene: n Etylene: 333 methyl branches / 1000 C atoms Linear chain  -olefin polymerization mechanism

n Propylene: n Etylene: 333 methyl branches / 1000 C atoms Linear chain Observed: up to 130 branches / 1000 C Observed: 210 - 333 branches / 1000 C

Chain isomerization  -olefin polymerization mechanism

Diimine catalysts

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

 -olefin polymerization mechanism

Models for the catalyst: 1) generic system: R = H; Ar = H 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 R 2 = An; Ar = H R 2 = An; Ar = Ph (i-Pr) 2 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 R 2 = An; Ar = H R 2 = An; Ar = Ph (i-Pr) 2

DFT calculations: Chain growth: Chain isomerization:

DFT calculations:  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. Examples of results: Ethylene insertion barrier: DFT: 16.7 kcal/mol exp.: 17.4 kcal/mol Isomerization barrier: DFT: 5.8 (6.8) kcal/mol exp: 7.2 kcal/mol

Substituent effect in real systems Electronic preference Steric effect (generic system) (real systems) alkyl complexesiso-propyl iso-propyl olefin  -complexesiso-propyl alkyl n-propyl alkyl olefin  -complexespropene ethene propene insertion2,1- 1,2- Electronic preference Steric effect (generic system) (real systems) alkyl complexesiso-propyl iso-propyl olefin  -complexesiso-propyl alkyl n-propyl alkyl olefin  -complexespropene ethene propene insertion2,1- 1,2-

Isomerization reactions 0.00 +4.56 -3.42 0.00 +5.84 +1.59 following 1,2-insertion following 2,1-insertion

1 C atom attached to the catalyst: olefin capture followed by 1,2- or 2,1- insertion 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 Stochastic simulation - how it works 1 2 3 4

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

Probablities of the events Basic assumption: relative probabilities (microscopic) = relative rates (macroscopic): Basic assumption: relative probabilities (microscopic) = relative rates (macroscopic): 36 Macroscopic kinetic expressions with microscopic barriers for elementary reactions (calculated or experimental) 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) Use of macroscopic kinetic expressions allows us to discuss the effects of the reaction conditions (temperature and olefin pressure)

Probablities of the events Basic assumption: relative probabilities (microscopic) = relative rates (macroscopic): e.g. isomerization vs. isomerization: isomerization vs. insertion: etc. Basic assumption: relative probabilities (microscopic) = relative rates (macroscopic): e.g. isomerization vs. isomerization: isomerization vs. insertion: etc.          - alkyl  -agostic complexes;   - olefin  complex; 37

Simulations of polymer growth and isomerization Results: - Polymer chain; - Total No. of branches; - Classification of branches: no. of branches of a given type, and their length; - Molecular weight; 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) 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.

R=H; Ar= Ph Propylene polymerization (theoretical data)

R=An; Ar= Ph(i-Pr) 2 Propylene polymerization (theoretical data)

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(CH 3 ) 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=CH 3 ; Ar=Ph(CH 3 ) 2 : 251.0 br.; 59.7%; 38.7%; 0.93 R=CH 3 ; 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

Propylene polymerization - temperature effect T=98K T=198K T=298K T=398K T=498K 43

Propylene polymerization - temperature effect T=98K T=198K T=298K T=398K T=498K 44 Two insertion pathways: 1,2- i 2,1- Chain straightening follows 2,1-insertion only Lower barrier for the 1,2- insertion (by c.a. 0.6 kcal/mol) Practically each 2,1- insertion is followed by chain straighening

Propylene polymerization - pressure effect 45

Propylene polymerization - pressure effect 46 Exp.: 213br. / 1000 C „Ideal” – no chain straighening 333.3

Propylene polymerization - pressure effect p=0.1 p=0.01 p=0.001 p=0.0001 47

Ethylene polymerization by Pd-based diimine catalyst Simulations from experimental data (  G) Ethylene polymerization by Pd-based diimine catalyst Simulations from experimental data (  G) 48

Ethylene polymerization by Pd-based diimine catalyst Simulations from experimental data Ethylene polymerization by Pd-based diimine catalyst Simulations from experimental data 49

Ethylene polymerization by Pd-based diimine catalyst Simulations from experimental data Ethylene polymerization by Pd-based diimine catalyst Simulations from experimental data 50 Exp.

Ethylene polymerization by Pd-based diimine catalyst Simulations from experimental data Ethylene polymerization by Pd-based diimine catalyst Simulations from experimental data 51 p

Ethylene polymerization by Pd-based diimine catalyst Simulations from experimental data Ethylene polymerization by Pd-based diimine catalyst Simulations from experimental data 52 p

Ethylene polymerization by Pd-based diimine catalyst Simulations from experimental data (  G) Ethylene polymerization by Pd-based diimine catalyst Simulations from experimental data (  G) 55  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

Ethylene polymerization - model studies on the effects of catalyst (elementary reaction barriers), temperature, and pressure on the microstructure of polymers 56

Ethylene polymerization - pressure / catalyst effects Ethylene polymerization - pressure / catalyst effects 0 50 100 150 200 250 300 350 0.00010.0010.010.11  E 2 =1  E 2 =2  E 2 =3  E 2 =4  E 2 =5  E 2 =6  E 2 =7  E 2 =8  E 2 =9 No. of branches / 1000 C p [arbitrary units]  E 1 =1.0 kcal/mol 57

Ethylene polymerization - pressure / catalyst effects Ethylene polymerization - pressure / catalyst effects 0 50 100 150 200 250 300 350 0.00010.0010.010.11  E 2 =1  E 2 =2  E 2 =3  E 2 =4  E 2 =5  E 2 =6  E 2 =7  E 2 =8  E 2 =9 No. of branches / 1000 C p [arbitrary units]  E 1 =1.0 kcal/mol 58 pressure independent region

 E 1 =2.0 kcal/mol  E 1 =3.0 kcal/mol  E 1 =4.0 kcal/mol  E 1 =6.0 kcal/mol 59 The faster is the isomerisation (compared to insertions), the more extended is the pressure independent region. For Ni-diimine catalyst the isomerisation is slower then for Pd i.e. for Pd the pressure independent region is more extended toward higher values of the pressure For Ni-diimine catalyst the isomerisation is slower then for Pd i.e. for Pd the pressure independent region is more extended toward higher values of the pressure

The polyethylene gallery  E 1  E 2 =2 kcal/mol  E 1  E 2 =5 kcal/mol  E 1  E 2 =7 kcal/mol  E 1  E 2 =5 kcal/mol  E 1  E 2 =5 kcal/mol p=0.0001; T=298 K 60

Ethylene polymerization with the neutral anilinotropone Ni-based catalyst Experimental data: Hiks, F.A., Brookhart M. Organometallics 2001, 20, 3217. Experimental data: Hiks, F.A., Brookhart M. Organometallics 2001, 20, 3217.

Ni-anilinotropone catalyst - cis/trans isomers Alkyl complexes: Ethylene  -complexes:

0 5 10 -5 -10 -15 -20 N-isomers O-isomers Alkyl -- -- -- -- ins. TS iso. TS 1.9 -12.9 -17.9 0.0 1.9 9.5 5.8 1.3 3.4 -17.5 -17.1 5.7 1.7 Secondary alkylPrimary alkyl Ni-anilinotropone catalyst – results for real catalyst

0 5 10 -5 -10 -15 -20 N-isomers O-isomers Alkyl -- -- -- -- ins. TS iso. TS 1.9 -12.9 -17.9 0.0 1.9 9.5 5.8 1.3 3.4 -17.5 -17.1 5.7 1.7 Secondary alkylPrimary alkyl Ni-anilinotropone catalyst – stochastic simulations

14 - 600 psig Ni-anilinotropone catalyst – stochastic simulations

14 50 100 200400 600 p [psig] Ni-anilinotropone catalyst – stochastic simulations Theoret. Exp.

p = 0.011 arb.u./ p = 400 psig Theoret. Exp. Ni-anilinotropone catalyst – stochastic simulations

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. 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 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

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.` 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.`

DFT and stochastic studies on the influence of the catalyst structure and the reaction conditions on the polyolefin microstructure Artur Michalak a,b and.

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DFT and stochastic studies on the influence of the catalyst structure and the reaction conditions on the polyolefin microstructure Artur Michalak a,b and.

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Presentation on theme: "DFT and stochastic studies on the influence of the catalyst structure and the reaction conditions on the polyolefin microstructure Artur Michalak a,b and."— Presentation transcript:

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