quantum chemical molecular modellingmichalak/mmod2008/l12.pdf · 2009. 1. 13. · quantum chemical...

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Quantum chemical molecular modelling Dr. hab. Artur Michalak Department of Theoretical Chemistry Faculty of Chemistry Jagiellonian University Kraków, Poland http://www.chemia.uj.edu.pl/~michalak/mmod/ http://www.chemia.uj.edu.pl/~michalak/mmod2008/ In Polish: http://www.chemia.uj.edu.pl/~michalak/mmod2007/ Ck08 Lecture 12

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Page 1: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

Quantum chemical molecular modelling

Dr. hab. Artur Michalak

Department of Theoretical Chemistry

Faculty of Chemistry

Jagiellonian University

Kraków, Poland

http://www.chemia.uj.edu.pl/~michalak/mmod/

http://www.chemia.uj.edu.pl/~michalak/mmod2008/

In Polish: http://www.chemia.uj.edu.pl/~michalak/mmod2007/

Ck08

Lecture 12

Page 2: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

• Basic ideas and methods of quantum chemistry:

Wave-function; Electron density; Schrodinger equation; Density Functional theory; Born-Oppenheimer

approximation; Variational principles in wave-function mechanics and DFT; One-electron approximation; HF

method; Electron correlation; KS method; Wave-function-based electron correlation methods;

• Input data for QM calculations, GAMESS:

Molecular geometry, Z-Matrix, Basis sets in ab initio calculations;, input, output;

Geometry of molecular systems:

Geometry optimization; Constrained optimization; Conformational analysis; Global minimum problem

Electronic structure of molecular systems:

Population analysis; Bond-orders; Molecular orbitals (KS orbitals); Chemical bond; Deformation density;

Localized orbitals;

•Molecular vibrations, Thermodynamics; Chemical Reactivity:

Vibrational analysis; Thermodynamic properties; Modeling chemical

reactions; Trantition state optimization and validation; Intrinsic Reaction

Coordinate; Chemical reactivity indices; Molecular Electrostatic Potential;

Fukui Functions; Single- and Two-Reactant Reactivity Indices

• Other Topics:Modelling of complex chemical processes – examples from catalysis; Molecular spectroscopy from ab initio calculations; Advanced

methods for electron correlation;Molecular dynamics; Modelling of large systems – hybrid approaches (QM/MM); Solvation

models

Page 3: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

Example:

Theoretical studies on the polymerisation

and co-polymerisation processes catalyzed

by the late-transition metal complexes

Example:

Theoretical studies on the polymerisation

and co-polymerisation processes catalyzed

by the late-transition metal complexes

Page 4: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

PolyethylenePolyethylene

Annual consumption (in 2000)

- 165 M tons

19 000 tons during 1 hour lecture

Page 5: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

PolyethylenePolyethylene

Annual consumption (in 2000)

- 165 M tons

Various classes of polyethylenes:

HDPE, LDPE, LLDPE

- size of macromolecules: molecular weight, molecular weight distribution

19 000 tons during 1 hour lecture

n

Etylene:

...

Page 6: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

PolyethylenePolyethylene

Annual consumption (in 2000)

- 165 M tons

Various classes of polyethylenes:

HDPE, LDPE, LLDPE

- size of macromolecules: molecular weight, molecular weight distribution

- architecture of macromolecules: degree of branching, topology of branches

19 000 tons during 1 hour lecture

Page 7: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

1) Influence of catalyst structure

and reaction conditions (T, p)

on the polyolefin mictrostructure

1) Influence of catalyst structure

and reaction conditions (T, p)

on the polyolefin mictrostructure

• Static DFT calculations; Ab initio MD (CP-MD); Stochastic simulations• Static DFT calculations; Ab initio MD (CP-MD); Stochastic simulations

Theoretical studies - methodology :

Page 8: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

1) Influence of catalyst structure

and reaction conditions (T, p)

on the polyolefin mictrostructure

1) Influence of catalyst structure

and reaction conditions (T, p)

on the polyolefin mictrostructure

2) Copolymerization of αααα-olefins

with polar monomers

– factors determining catalyst activity

2) Copolymerization of αααα-olefins

with polar monomers

– factors determining catalyst activity

Page 9: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

Ethylene polymerizationEthylene polymerization

n

n

TiCl4/MgCl2

• Ziegler, K.; Holtzkamp, E.; Martin, H.; Breil, H. Angew. Chem. 1955, 67, 541. (Das Mülheimer

Normaldruck-Polyäthylen-Verfahren)

• Ziegler, K.; Holtzkamp, E..; Breil, H.; Martin, H Angew. Chem. 1955, 67, 426. (Polymerisation

Äthylen und Anderen Olefinen)

• Natta, G. J. Polym. Sci. 1955, 16, 143. (Une Nouvelle Classe de Polymeres d’α-Olefines ayant

une Regularite de Structure Exceptionelle)

• Natta, G. Angew. Chem. 1956, 68, 393. (Stereospezifische Katalysen und isotaktische

Polymere)

1950’s : K. Ziegler, G. Natta

-heterogenous catalyst

Page 10: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

Ethylene polymerizationEthylene polymerization

• Sinn, H.; Kaminsky, W.; Vollmer H.J.; Woldt, R. Angew. Chem. Int. Ed. Engl. 1980, 19, 380. (“Living Polymers”:

On Polymerization with Extremely Productive Zigler Catalysts)

• Sinn, H.; Kaminsky, W. Adv. Organomet. Chem. 1980, 18, 99. (Ziegler-Natta Catalysis)

• Wild, F.R.W.P.; Zsolnai, L.; Huttner, G.; Brintzinger, H.H. J. Organomet. Chem. 1982, 232, 233. (ansa-Metallocene

Derivatives IV. Synthesis and Molecular Structures of Chiral ansa-Titanocene Derivatives with Bridged

Tetrahydroindenyl Ligands)

• Kaminsky, W.; Kulper, K.; Brintzinger, H.H.; Wild, F.R.W.P. Angew. Chem. Int. Ed. Engl. 1985, 24, 507.

(Polymerization of Propene and Butene with a Chiral Zirconocene and Methyl Aluminoxane as Cocatalyst)

1980:

‘Metallocene revolution’

homogeneous catalysts

- metallocenes (Zr, Ti)

Page 11: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

Ethylene polymerizationEthylene polymerization

1990’s:

Non-metallocene

homogeneous catalysts

(various metals and ligands)

ACS Symp.Ser. 857 (2003)

Page 12: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical
Page 13: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

AcAcRaRaFrFr7

RnRnAtAtPoPoBiBiPbPbTlTlHgHgAuAuPtPtIrIrOsOsReReWWTaTaHfHfLaLaBaBaCsCs6

XeXeIITeTeSbSbSnSnInInCdCdAgAgPdPdRhRhRuRuTcTcMoMoNbNbZrZrYYSrSrRbRb5

KrKrBrBrSeSeAsAsGeGeGaGaZnZnCuCuNiNiCoCoFeFeMnMnCrCrVVTiTiScScCaCaKK4

ArArClClSSPPSiSiAlAl

XIIXIVIII IX XVIIVIVIVIII

MgMgNaNa3

NeNeFFOONNCCBBBeBeLiLi2

HeHeHH1

XVIII

XVIIXVIXVXIVXIIIII

I

Ethylene polymerization catalystsEthylene polymerization catalysts

LuLuYbYbTmTmErErHoHoDyDyTbTbGdGdEuEuSmSmPmPmNdNdPrPrCeCe6

Page 14: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

Neutral ligands in the Ni (II) and Pd (II) complexes

Page 15: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

Anionic ligands in the Ni (II) and Pd (II) complexes

Page 16: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

CC

NN

Pd

R R

Ar Ar

+

CC

CC

C

CC

C

C

CC

C

CC

C

CC

C

C

CC

C

N CNC CC

C

C

CCC C

CC

Pd

CC

M. Brookhart, 1995

Diimine catalysts; Ni, PdDiimine catalysts; Ni, Pd

Page 17: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

CC

NN

Pd

R R

Ar Ar

+

CC

CC

C

CC

C

C

CC

C

CC

C

CC

C

C

CC

C

N CNC CC

C

C

CCC C

CC

Pd

CC

• Mw: 30 000 – 1 000 000;

controlled by catalyst, temperature and pressure;

• Mw/ Mn: ca. 1.1-2.0;

• number of branches controlled by catalyst, temperature and pressure;

• microstructure controlled by catalyst, temperature and pressure;

• active in copolymerization of ethylene with polar monomers

• Mw: 30 000 – 1 000 000;

controlled by catalyst, temperature and pressure;

• Mw/ Mn: ca. 1.1-2.0;

• number of branches controlled by catalyst, temperature and pressure;

• microstructure controlled by catalyst, temperature and pressure;

• active in copolymerization of ethylene with polar monomers

Katalizatory diiminowe; Ni, PdKatalizatory diiminowe; Ni, Pd

Page 18: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

Diimine catalystsDiimine catalysts

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

n

Propylene:

n

Propylene:

n

Etylene:

n

Etylene:

333 methyl branches / 1000 C atoms

Linear chain

Observed: up to 130 branches / 1000 C

Observed: 210 - 333 branches / 1000 C

CC

CC

C

CC

C

C

CC

C

CC

C

CC

C

C

CC

C

N CNC CC

C

C

CCC C

CC

Pd

CC

Page 19: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

Diimine catalystsDiimine 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 branches influenced by p

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

n

Propylene:

n

Propylene:

n

Etylene:

n

Etylene:

333 methyl branches / 1000 C atoms

Linear chain

Observed: up to 130 branches / 1000 C

Observed: 210 - 333 branches / 1000 C

Page 20: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

β-agostic

π-complex

+ ethylene

β-agostic

γ-agostic

insertion

Ethylene polymerization mechanismEthylene polymerization mechanism

Page 21: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

n

Propylene:

n

Etylene:

333 methyl branches / 1000 C atoms

Linear chain

α-olefin polymerization mechanismα-olefin polymerization mechanism

Page 22: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

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

α-olefin polymerization mechanismα-olefin polymerization mechanism

Page 23: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

Chain isomerization

α-olefin polymerization mechanismα-olefin polymerization mechanism

Page 24: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

α-olefin polymerization mechanismα-olefin polymerization mechanism

Page 25: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

•Relative stability of isomeric alkyl complexes

•Relative stability of isomeric olefin ππππ-complexes

•Relative insertion barriers

•Relative rates of insertion vs. isomerization

•Relative stability of isomeric alkyl complexes

•Relative stability of isomeric olefin ππππ-complexes

•Relative insertion barriers

•Relative rates of insertion vs. isomerization

α-olefin polymerization mechanismα-olefin polymerization mechanism

Page 26: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

Theoretical modelingTheoretical modeling

• Schrödinger Equation →→→→ wave function; Kohn-Sham eq. →→→→ density

• Born-Oppenheimer approximation

• Potential energy surface (PES): reactants, products, TS

TS

minimum

reaction cooridinate

E

Page 27: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

Quantum chemical modelling of chemical processes

• Computational methods: ab initio and semi-empirical

• Reactions involving transition metals:

ab initio methods that account for electron correlation

- success of the density functional theory (DFT)

•DFT calculations possible for relatively large systems (up to 100-200

atoms; 1000 electrons)

Quantum-chemical modelling of TM-complexes and reactions:

•Niu, S.; Hall, M.B. Chem. Rev. 2000, 100, 353.

•Frenking G., Frohlich, N. Chem. Rev. 2000, 100, 717.

•Cundari, T.R. Chem. Rev. 2000, 100, 807.

•Dedieu, A. Chem. Rev. 2000, 100, 543.

polymerization processes:

•Rappe, A.K.; Skiff, W.M.; Casewit, C.J. Chem. Rev. 2000, 100, 1435.

•Angermund, K.; Fink, G.; Jensen, V.R.; Kleinschmidt, R. Chem.Rev.2000, 100, 1457.

Quantum-chemical modelling of TM-complexes and reactions:

•Niu, S.; Hall, M.B. Chem. Rev. 2000, 100, 353.

•Frenking G., Frohlich, N. Chem. Rev. 2000, 100, 717.

•Cundari, T.R. Chem. Rev. 2000, 100, 807.

•Dedieu, A. Chem. Rev. 2000, 100, 543.

polymerization processes:

•Rappe, A.K.; Skiff, W.M.; Casewit, C.J. Chem. Rev. 2000, 100, 1435.

•Angermund, K.; Fink, G.; Jensen, V.R.; Kleinschmidt, R. Chem.Rev.2000, 100, 1457.

Page 28: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

Theoretical modelingTheoretical modeling

Assumption: energetics independent of polymer length ( P )

6 propagation reactions

(2,1- i 1,2-; 1o, 2o, 3o)

3 termination reactions

(1o, 2o, 3o )

9 isomerizations

(from: 1o, 2o, 3o

to: 1o, 2o, 3o )

Page 29: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

DFT calculations:DFT calculations:

Chain growth:

Chain isomerization:

Page 30: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

Models for the catalyst:Models for the catalyst:

1) generic system: R = H; Ar = H1) 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

• R2 = An; Ar = H

• R2 = 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

• R2 = An; Ar = H

• R2 = An; Ar = Ph (i-Pr)2

CC

NN

Pd

R R

Ar Ar

+

CC

NN

Pd

Page 31: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

Models for the catalyst:Models for the catalyst:

1) generic system: R = H; Ar = H1) 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

• R2 = An; Ar = H

• R2 = 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

• R2 = An; Ar = H

• R2 = An; Ar = Ph (i-Pr)2

CC

NN

Pd

R R

Ar Ar

+

CC

CCCC

CNN CCC

CCC C

Pd

Page 32: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

Models for the catalyst:Models for the catalyst:

1) generic system: R = H; Ar = H1) 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

• R2 = An; Ar = H

• R2 = 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

• R2 = An; Ar = H

• R2 = An; Ar = Ph (i-Pr)2

CC

NN

Pd

R R

Ar Ar

+

C

CC

C

CCCC

CNN CCC

CCC C

C

Pd

C

Page 33: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

Models for the catalyst:Models for the catalyst:

1) generic system: R = H; Ar = H1) 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

• R2 = An; Ar = H

• R2 = 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

• R2 = An; Ar = H

• R2 = An; Ar = Ph (i-Pr)2

CC

NN

Pd

R R

Ar Ar

+

CC

C

CC

C

CC

C

CC

C

C

CNN CCC

CC

C

C C

CC

Pd

CC

Page 34: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

Models for the catalyst:Models for the catalyst:

1) generic system: R = H; Ar = H1) 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

• R2 = An; Ar = H

• R2 = 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

• R2 = An; Ar = H

• R2 = An; Ar = Ph (i-Pr)2

CC

NN

Pd

R R

Ar Ar

+

CC

CC

NN

Pd

Page 35: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

Models for the catalyst:Models for the catalyst:

1) generic system: R = H; Ar = H1) 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

• R2 = An; Ar = H

• R2 = 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

• R2 = An; Ar = H

• R2 = An; Ar = Ph (i-Pr)2

CC

NN

Pd

R R

Ar Ar

+

CC

C

CC

C

CC

CC

CNN CCC

CCC C

C

Pd

C

Page 36: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

Models for the catalyst:Models for the catalyst:

1) generic system: R = H; Ar = H1) 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

• R2 = An; Ar = H

• R2 = 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

• R2 = An; Ar = H

• R2 = An; Ar = Ph (i-Pr)2

CC

NN

Pd

R R

Ar Ar

+

C

CC

C

C

CC

C

CC

C

CC

C

C

N CNC CC

CC

C

C C

CC

Pd

CC

Page 37: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

Models for the catalyst:Models for the catalyst:

1) generic system: R = H; Ar = H1) 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

• R2 = An; Ar = H

• R2 = 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

• R2 = An; Ar = H

• R2 = An; Ar = Ph (i-Pr)2

CC

NN

Pd

R R

Ar Ar

+

CC

CC

C

CC

C

CC

CC

NN

Pd

Page 38: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

Models for the catalyst:Models for the catalyst:

1) generic system: R = H; Ar = H1) 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

• R2 = An; Ar = H

• R2 = 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

• R2 = An; Ar = H

• R2 = An; Ar = Ph (i-Pr)2

CC

NN

Pd

R R

Ar Ar

+

CC

CC

C

CC

C

C

CC

C

CC

C

CC

C

C

CC

C

N CNC CC

C

C

CCC C

CC

Pd

CC

Page 39: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

DFT calculations: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/molC

CC

C

C

CC

C

CC

C

CC

C

C

N CNC CC

CC

C

C C

CC

Pd

CC

Page 40: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

DFT calculations (ethylene):DFT calculations (ethylene):

���� 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.

C

CC

C

C

CC

C

CC

C

CC

C

C

N CNC CC

CC

C

C C

CC

Pd

CC

Exp.

(theoret.)

Page 41: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

Isomerization reactionsIsomerization reactions

0.000.00

+4.56+4.56

-3.42-3.42

0.000.00+5.84+5.84

+1.59+1.59

following

1,2-insertion

following

2,1-insertion

Page 42: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

Isomerization reactionsIsomerization reactions

0.000.00

+4.56+4.56

-3.42-3.42

0.000.00+5.84+5.84

+1.59+1.59

following

1,2-insertion

following

2,1-insertion

Page 43: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

Isomerization reactionsIsomerization reactions

0.000.00

+4.56+4.56

-3.42-3.42

0.000.00+5.84+5.84

+1.59+1.59

following

1,2-insertion

following

2,1-insertion

Page 44: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

1 C atom attached to the catalyst:

olefin capture

followed by

1,2- or 2,1-

insertion

Stochastic simulation - how it worksStochastic simulation - how it works

���� A. Michalak, T. Ziegler, „Stochastic modelling of the propylene polymerization catalyzed by thePd-based diimine catalyst: influence of the catalyst structure and the reaction conditions on the polymermicrostructure”, J. Am. Chem. Soc, 2002, 124, 7519-7528.

Page 45: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

1 C atom attached to the catalyst:

olefin capture

followed by

1,2- or 2,1-

insertion

Stochastic simulation - how it worksStochastic simulation - how it works

Page 46: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

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 worksStochastic simulation - how it works

1

2

3

4

Page 47: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

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 worksStochastic simulation - how it works

Page 48: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

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 worksStochastic simulation - how it works

Page 49: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

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 worksStochastic simulation - how it works

Page 50: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

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 worksStochastic simulation - how it works

Page 51: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

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 worksStochastic simulation - how it works

Page 52: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

Stochastic simulation - how it worksStochastic simulation - how it works

Page 53: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

Stochastic simulation - how it worksStochastic simulation - how it works

Page 54: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

Stochastic simulation - how it worksStochastic simulation - how it works

Page 55: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

Stochastic simulation - how it worksStochastic simulation - how it works

Page 56: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

ProbabilitiesProbabilities

][ 01,1 βisokr =

][ 02,2 βisokr =

β0 , β1 , β2 β-agostic complexes

Basic assumption:

Relative probabilities (microscopic)

= relative reaction rates (macroscopic)

Basic assumption:

Relative probabilities (microscopic)

= relative reaction rates (macroscopic)

π i

π j

=r i

r j

πiso.1

π iso.2

=r iso.1

r iso.2

=k iso.1

kiso.2

≈ exp(∆∆G 1 , 2

kT)

πi

i

∑ = 1

Two isomerization

reactions:

Page 57: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

β0 , β1 , β2 β-agostic complexes;

π0- olefin π complexes

Insertion vs.

isomerization:

Basic assumption:

Relative probabilities (microscopic)

= relative reaction rates (macroscopic)

Basic assumption:

Relative probabilities (microscopic)

= relative reaction rates (macroscopic)

π i

π j

=r i

r j

πi

i

∑ = 1

πiso.1

π ins. 1, 2

=riso.1

r ins.1, 2

≈kiso.1

k ins.1, 2 Kcompl. polefin

olefincomplins

insins

pKk

kr

][

][

0..

0..

β

π

=

==

][ 01,1 βisokr =

ProbabilitiesProbabilities

Page 58: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

R=H; Ar= Ph

CC

CCCC

CNN CCC

CCC C

Pd

Propylene polymerization (theoretical data)Propylene polymerization (theoretical data)

Page 59: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

R=An; Ar= Ph(i-Pr)2

CC

CC

C

CC

C

C

CC

C

CC

C

CC

C

C

CC

C

N CNC CC

C

C

CCC C

CC

Pd

CC

Propylene polymerization (theoretical data)Propylene polymerization (theoretical data)

Page 60: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

Propylene polymerization (theoretical data)Propylene polymerization (theoretical data)

R = H; Ar = H

CC

NN

Pd

���� A. Michalak, T. Ziegler, „Stochastic modelling of the propylene polymerization catalyzed by thePd-based diimine catalyst: influence of the catalyst structure and the reaction conditions on the polymermicrostructure”, J. Am. Chem. Soc, 2002, 124, 7519-7528.

Page 61: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

Propylene polymerization - effect of the catalystPropylene 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.).

61

Page 62: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

0

30

60

90

120

150

180

0 100 200 300 400 500

T [K]

No. of

bra

nch

es

Ethylene polymerization by Pd-based diimine catalyst

Simulations from experimental data

Ethylene polymerization by Pd-based diimine catalyst

Simulations from experimental data

62

CC

CC

C

CC

C

C

CC

C

CC

C

CC

C

C

CC

C

N CNC CC

C

C

CCC C

CC

Pd

CC

Ethylene polymerization by Pd-based diimine catalyst

Simulations from theoretical and experimental data

Ethylene polymerization by Pd-based diimine catalyst

Simulations from theoretical and experimental data

Page 63: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

0

30

60

90

120

150

180

0 100 200 300 400 500

T [K]

No. of

bra

nch

es

Ethylene polymerization by Pd-based diimine catalyst

Simulations from experimental data

Ethylene polymerization by Pd-based diimine catalyst

Simulations from experimental data

63

CC

CC

C

CC

C

C

CC

C

CC

C

CC

C

C

CC

C

N CNC CC

C

C

CCC C

CC

Pd

CC

Ethylene polymerization by Pd-based diimine catalyst

Simulations from theoretical data

Ethylene polymerization by Pd-based diimine catalyst

Simulations from theoretical data

Page 64: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

220

240

260

280

300

320

0 100 200 300 400 500

T [K]

No

. o

f b

ran

ches

/ 1

00

0 C

Propylene polymerization - temperature effectPropylene polymerization - temperature effect

T=98K

T=198K

T=298K

T=398K

T=498K

64

C

CC

C

C

CC

C

CC

C

CC

C

C

N CNC CC

CC

C

C C

CC

Pd

CC

Page 65: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

220

240

260

280

300

320

0 100 200 300 400 500

T [K]

No

. o

f b

ran

ches

/ 1

00

0 C

Propylene polymerization - temperature effectPropylene polymerization - temperature effect

T=98K

T=198K

T=298K

T=398K

T=498K

65

C

CC

C

C

CC

C

CC

C

CC

C

C

N CNC CC

CC

C

C C

CC

Pd

CC

• 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

Page 66: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

220

240

260

280

300

320

0.001 0.01 0.1 1

p [ arbitrary units]

No. of

bra

nch

es

Propylene polymerization - pressure effectPropylene polymerization - pressure effect

66

C

CC

C

C

CC

C

CC

C

CC

C

C

N CNC CC

CC

C

C C

CC

Pd

CC

���� A. Michalak, T. Ziegler, „Stochastic modelling of the propylene polymerization catalyzed by thePd-based diimine catalyst: influence of the catalyst structure and the reaction conditions on the polymermicrostructure”, J. Am. Chem. Soc, 2002, 124, 7519-7528.

Page 67: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

220

240

260

280

300

320

0.001 0.01 0.1 1

p [ arbitrary units]

No. of

bra

nch

es

Propylene polymerization - pressure effectPropylene polymerization - pressure effect

67

C

CC

C

C

CC

C

CC

C

CC

C

C

N CNC CC

CC

C

C C

CC

Pd

CC

Exp.: 213br. / 1000 C

„Ideal” – no chain straighening333.3

���� A. Michalak, T. Ziegler, „Stochastic modelling of the propylene polymerization catalyzed by thePd-based diimine catalyst: influence of the catalyst structure and the reaction conditions on the polymermicrostructure”, J. Am. Chem. Soc, 2002, 124, 7519-7528.

Page 68: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

Ethylene polymerization by Pd-based diimine catalyst

Simulations from experimental data

Ethylene polymerization by Pd-based diimine catalyst

Simulations from experimental data

68

p

Ethylene polymerization by Pd-based diimine catalyst

Simulations from theoretical and experimental data

Ethylene polymerization by Pd-based diimine catalyst

Simulations from theoretical and experimental data

Page 69: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

Ethylene polymerization by Pd-based diimine catalyst

Simulations from experimental data

Ethylene polymerization by Pd-based diimine catalyst

Simulations from experimental data

69

p

Ethylene polymerization by Pd-based diimine catalyst

Simulations from theoretical and experimental data

Ethylene polymerization by Pd-based diimine catalyst

Simulations from theoretical and experimental data

Page 70: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

70

���� Michalak, A.; Ziegler, T.; Macromolecules 2003, 36, 928-933 („Exploring the Scope ofPossible Microstructures from Polymerization of Ethylene by Late Transition Metal Single-SiteCatalysts. A Theoretical Study.”)

Ethylene polymerization - model studies on the effects of catalyst

(elementary reaction barriers), temperature, and pressure on the

microstructure of polymers

Ethylene polymerization - model studies on the effects of catalyst

(elementary reaction barriers), temperature, and pressure on the

microstructure of polymers

Page 71: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

0

50

100

150

200

250

300

350

400

450

0.0001 0.001 0.01 0.1 1

∆∆∆∆E1=2.0 kcal/mol

0

50

100

150

200

250

300

350

400

450

500

0.0001 0.001 0.01 0.1 1

∆∆∆∆E1=3.0 kcal/mol

0

100

200

300

400

500

600

0.0001 0.001 0.01 0.1 1

∆∆∆∆E1=4.0 kcal/mol

0

100

200

300

400

500

600

0.0001 0.001 0.01 0.1 1

∆∆∆∆E1=6.0 kcal/mol

p

∆∆∆∆E2=1

∆∆∆∆E2=9

Page 72: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

∆∆∆∆E1 =1; ∆∆∆∆E2=2 kcal/mol

∆∆∆∆E1 =1; ∆∆∆∆E2=5 kcal/mol

∆∆∆∆E1 =1; ∆∆∆∆E2=7 kcal/mol

∆∆∆∆E1 =2; ∆∆∆∆E2=5 kcal/mol

∆∆∆∆E1 =4; ∆∆∆∆E2=5 kcal/mol

p=0.0001; T=298 K

The polyethylene galleryThe polyethylene gallery

Page 73: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

0

20

40

60

80

100

120

140

160

0 0.0038 0.0076 0.0114 0.0152 0.019 0.0228

p [arb.u.]

br./

10

00

C

14 50 100 200 400 600p [psig]

theor.

exp.

EthyleneEthylene polymerizationpolymerization catalyzedcatalyzed by by NiNi--basedbased BrookhartBrookhart--HicksHicks complexcomplex

� A. Michalak, T. Ziegler, Organometallics 2003, 22, 2069-2079 „Polymerization of

Ethylene Catalyzed by a Ni(+2) Anilinotropone-based catalyst: DFT and Stochastic Studies on the

Elementary Reactions and the Mechanism of Polyethylene Branching”

Experimental data: Hicks, F.A., Brookhart M.Organometallics 2001, 20, 3217.Experimental data: Hicks, F.A., Brookhart M.Organometallics 2001, 20, 3217.

NNi

O

P

Page 74: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

0

10

20

30

40

50

60

70

80

90

100

40 50 60 70 80 90 100

T [C]

br./

10

00

C

p = 0.011 arb.u. / p = 400 psig

theor.

exp.

EthyleneEthylene polymerizationpolymerization catalyzedcatalyzed by by NiNi--basedbased BrookhartBrookhart--HicksHicks complexcomplex

� A. Michalak, T. Ziegler, Organometallics 2003, 22, 2069-2079 „Polymerization of

Ethylene Catalyzed by a Ni(+2) Anilinotropone-based catalyst: DFT and Stochastic Studies on the

Elementary Reactions and the Mechanism of Polyethylene Branching”

Experimental data: Hicks, F.A., Brookhart M.Organometallics 2001, 20, 3217.Experimental data: Hicks, F.A., Brookhart M.Organometallics 2001, 20, 3217.

NNi

O

P

Page 75: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

p 600 psig

200 psig

50 psig

14 psig

EthyleneEthylene polymerizationpolymerization catalyzedcatalyzed by by NiNi--basedbased BrookhartBrookhart--HicksHicks complexcomplex

Page 76: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

0

20000

40000

60000

80000

100000

120000

140000

0 100 200 300 400 500 600 700

p

Mn

N O

Ni

Ph(iPr)2

P(Ph)3

Ph

0

50000

100000

150000

200000

250000

300000

350000

400000

450000

500000

0 200 400 600 800 1000

p

Mn

N O

Ni

Ph(iPr)2

P(Ph)3

Ph

Experimental data: Brookhart M. , Hicks F.A. Organometallics 2001, 20, 3218;

Brookhart, M., Jenkins J. C., J.Am.Chem.Soc., 2004, 126, 582.

Ni(II)-anilinotropone

catalyst

Modelling molecular weight and termination mechanismsModelling molecular weight and termination mechanisms

Pressure dependence of molecular weight

Page 77: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

NiL L

R

H

CH2

CH2

NiL L

R

NiL L

R

+

kINS

K

TS

propagation:

Modelling molecular weight and termination mechanismsModelling molecular weight and termination mechanisms

Page 78: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

NiL L

R

H

CH2

CH2

NiL L

R

NiL L

R

+

kINS

K

TS

propagation:

BHT termination:Ni

L L

H

R

Ni

L L

H

R

NiL L

HR

Ni

L L

H

+

R

kBHT

Modelling molecular weight and termination mechanismsModelling molecular weight and termination mechanisms

Page 79: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

NiL L

R

H

CH2

CH2

NiL L

R

NiL L

R

+

kINS

K

TS

NiL L

H

R

Ni

L L

H

R

NiL L

HR

Ni

L L

H

+

R

kBHT

nterminatio

npropagatio

r

rR =

Molecular weight of polymer

can be estimated from

the average number of insertions

that happen before termination,

ie. relative rates

of propagarion and termination

propagation:

BHT termination:

Modelling molecular weight and termination mechanismsModelling molecular weight and termination mechanisms

Page 80: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

NiL L

R

H

CH2

CH2

NiL L

R

NiL L

R

+

kINS

K

TS

NiL L

H

R

Ni

L L

H

R

NiL L

HR

Ni

L L

H

+

R

kBHT

BHT

ins

BHT

ins

k

k

EtKk

EtKk

r

rR ===

]][[

]][[

nterminatio

npropagatio

β

β

No pressure dependence:

propagation:

BHT termination:

Modelling molecular weight and termination mechanismsModelling molecular weight and termination mechanisms

Page 81: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

NiL L

R

H

CH2

CH2

NiL L

R

NiL L

R

+

kINS

K

TSBHE

R+

Ni

L L

H

kBHE

NiL L

R

H

Ni

L L

H

R

propagation:BHE termination:

Modelling molecular weight and termination mechanismsModelling molecular weight and termination mechanisms

Page 82: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

NiL L

R

H

CH2

CH2

NiL L

R

NiL L

R

+

kINS

K

TSBHE

R+

Ni

L L

H

kBHE

NiL L

R

H

Ni

L L

H

R

pk

Kk

k

EtKk

r

rR

BHE

ins

BHE

ins ===][

]][[

nterminatio

npropagatio

β

β

Pressure dependence:

propagation:BHE termination:

Modelling molecular weight and termination mechanismsModelling molecular weight and termination mechanisms

Page 83: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

Rys. Regina Szeliga

NiL L

R

H

CH2

CH2

NiL L

R

NiL L

R

+

kINS

K

TSBHE

R+

Ni

L L

H

kBHE

NiL L

R

H

Ni

L L

H

R

JACS, 2004, 126, 5827JACS, 2004, 126, 5827

pk

Kk

k

EtKk

r

rR

BHE

ins

BHE

ins ===][

]][[

nterminatio

npropagatio

β

β

Pressure dependence:

propagation:BHE termination:

Modelling molecular weight and termination mechanismsModelling molecular weight and termination mechanisms

Page 84: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

NiL L

R

H

CH2

CH2

NiL L

R

NiL L

R

+

kINS

K

TSBHE

R+

Ni

L L

H

kBHE

NiL L

R

H

Ni

L L

H

R

∆∆∆∆EBHE≈≈≈≈ 40 kcal/mol

pk

Kk

k

EtKk

r

rR

BHE

ins

BHE

ins ===][

]][[

nterminatio

npropagatio

β

β

Pressure dependence:

propagation:BHE termination:

Modelling molecular weight and termination mechanismsModelling molecular weight and termination mechanisms

Page 85: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

NiL L

R

H

CH2

CH2

NiL L

R

NiL L

R

+

kINS

K

TS

propagation:

NiL L

H

R

isomerization:

Modelling molecular weight and termination mechanismsModelling molecular weight and termination mechanisms

Page 86: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

NiL L

R

H

CH2

CH2

NiL L

R

NiL L

R

+

kINS

K

TS

primary propagation

NiL L

H

R

isomerization:

NiL L

H

R

+

CH2

CH2

K’

NiL L

R

NiL L

R

k’INS

secondary propagation

TS

Modelling molecular weight and termination mechanismsModelling molecular weight and termination mechanisms

Page 87: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

NiL L

R

H

CH2

CH2

NiL L

R

NiL L

R

+

kINS

K

TSNi

L L

H

R

NiL L

H

R

+

CH2

CH2

K’

NiL L

R

NiL L

R

k’INSTS

BHT’ BHT

primary propagation

isomerization:

secondary propagation

Modelling molecular weight and termination mechanismsModelling molecular weight and termination mechanisms

Page 88: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

NiL L

R

H

CH2

CH2

NiL L

R

NiL L

R

+

kINS

K

TSNi

L L

H

R

NiL L

H

R

+

CH2

CH2

K’

NiL L

R

NiL L

R

k’INSTS

BHT’ BHT

NiL L

H

R

Ni

L L

H

R

NiL L

HR

Ni

L L

H

+

R

kBHT

primary propagation

isomerization:

secondary propagation

Modelling molecular weight and termination mechanismsModelling molecular weight and termination mechanisms

Page 89: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

NiL L

R

H

CH2

CH2

NiL L

R

NiL L

R

+

kINS

K

TSNi

L L

H

R

NiL L

H

R

+

CH2

CH2

K’

NiL L

R

NiL L

R

k’INSTS

BHT’ BHT

Ni

L L

H

+

R

NiL L

H

R

Ni

L L

H

R NiL L

H

R

k’BHT

primary propagation

isomerization:

secondary propagation

Modelling molecular weight and termination mechanismsModelling molecular weight and termination mechanisms

Page 90: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

NiL L

R

H

CH2

CH2

NiL L

R

NiL L

R

+

kINS

K

TSNi

L L

H

R

NiL L

H

R

+

CH2

CH2

K’

NiL L

R

NiL L

R

k’INSTS

BHT’ BHT

NiL L

H

R

Ni

L L

H

R

NiL L

HR

Ni

L L

H

+

R

kBHT

Ni

L L

H

+

R

NiL L

H

R

Ni

L L

H

R NiL L

H

R

k’BHT

primary propagation

isomerization:

secondary propagation

Modelling molecular weight and termination mechanismsModelling molecular weight and termination mechanisms

Page 91: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

NiL L

R

H

CH2

CH2

NiL L

R

NiL L

R

+

kINS

K

TSNi

L L

H

R

NiL L

H

R

+

CH2

CH2

K’

NiL L

R

NiL L

R

k’INSTS

BHT’ BHT

NiL L

H

R

Ni

L L

H

R

NiL L

HR

Ni

L L

H

+

R

kBHT

Ni

L L

H

+

R

NiL L

H

R

Ni

L L

H

R NiL L

H

R

k’BHT

Pressure

dependence:1

'

3

'

13

'

23

1

'

2

'

12

'

22

kkkkpkk

kkkkpkkR

++

++=

k1, k1’ - isomerizationk2, k2’ - propagationk3, k3’ - BHT

(primary and secondary)

k1, k1’ - isomerizationk2, k2’ - propagationk3, k3’ - BHT

(primary and secondary)

Modelling molecular weight and termination mechanismsModelling molecular weight and termination mechanisms

Page 92: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

1

'

3

'

13

'

23

1

'

2

'

12

'

22

kkkkpkk

kkkkpkkR

++

++=

3

1

'

3

'

1

'

3

'

2

3

1

'

3

'

2

'

3

'

1

3

2

'

3

'

2

3

2

k

k

k

kp

k

k

k

k

k

k

k

k

k

kp

k

k

k

k

R

++

++

=

k1, k1’ - isomerizationk2, k2’ - propagationk3, k3’ - BHT

(primary and secondary)

k1, k1’ - isomerizationk2, k2’ - propagationk3, k3’ - BHT

(primary and secondary)

Modelling molecular weight and termination mechanismsModelling molecular weight and termination mechanisms

� R. Szeliga, A. Michalak, manuscript in preparation

Page 93: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

1

'

3

'

13

'

23

1

'

2

'

12

'

22

kkkkpkk

kkkkpkkR

++

++=

- no isomerization : k1 = k’1 = 0- no pressure dependence

3

2

k

kR =

k1, k1’ - isomerizationk2, k2’ - propagationk3, k3’ - BHT

(primary and secondary)

k1, k1’ - isomerizationk2, k2’ - propagationk3, k3’ - BHT

(primary and secondary)

Modelling molecular weight and termination mechanismsModelling molecular weight and termination mechanisms

Page 94: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

- very fast isomerization : k1 , k’1 >> k2 ,k3 , k’2 ,k’3

- no pressure dependence

'

3

1

'

13

1

'

23

'

2

1

'

12

1

'

22

kk

kkp

k

kk

kk

kkp

k

kk

R

++

++

=

'

33

'

22

kKk

kKkR

isom

isom

+

+=

k1, k1’ - isomerizationk2, k2’ - propagationk3, k3’ - BHT

(primary and secondary)

k1, k1’ - isomerizationk2, k2’ - propagationk3, k3’ - BHT

(primary and secondary)

Modelling molecular weight and termination mechanismsModelling molecular weight and termination mechanisms

Page 95: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

1

'

3

'

13

'

23

1

'

2

'

12

'

22

kkkkpkk

kkkkpkkR

++

++=

- only one propagation mechanism,

(no secondary propagation):

k’2 = 0- no pressure dependence

1

'

3

'

13

'

12

kkkk

kkR

+=

k1, k1’ - isomerizationk2, k2’ - propagationk3, k3’ - BHT

(primary and secondary)

k1, k1’ - isomerizationk2, k2’ - propagationk3, k3’ - BHT

(primary and secondary)

Modelling molecular weight and termination mechanismsModelling molecular weight and termination mechanisms

Page 96: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

- identical primary and secondary

insertion:termination relative rates: k2 /k3 = k’2 /k’3

- no pressure dependence

3

1

'

3

'

1

'

3

'

2

3

1

'

3

'

2

'

3

'

1

3

2

'

3

'

2

3

2

k

k

k

kp

k

k

k

k

k

k

k

k

k

kp

k

k

k

k

R

++

++

=

3

2

3

1

'

3

'

1

3

2

3

1

'

3

'

1

3

2

3

2

k

k

k

k

k

kp

k

k

k

k

k

kp

k

k

k

k

R =

++

++

=

∆∆∆∆E= ∆∆∆∆E’

E

TSins

TSterm

TSins

TStermI rz. II rz.

k1, k1’ - isomerizationk2, k2’ - propagationk3, k3’ - BHT

(primary and secondary)

k1, k1’ - isomerizationk2, k2’ - propagationk3, k3’ - BHT

(primary and secondary)

Modelling molecular weight and termination mechanismsModelling molecular weight and termination mechanisms

Page 97: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

1

'

3

'

13

'

23

1

'

2

'

12

'

22

kkkkpkk

kkkkpkkR

++

++=

k1, k1’ - isomerizationk2, k2’ - propagationk3, k3’ - BHT

(primary and secondary)

k1, k1’ - isomerizationk2, k2’ - propagationk3, k3’ - BHT

(primary and secondary)

Pressure dependence exist if:

-there are two propagation mechanisms (primary and secondary)

-the relative propagation/termination rates are different

for primary and secondary cycles: k2 /k3 ≠≠≠≠ k’2 /k’3

Modelling molecular weight and termination mechanismsModelling molecular weight and termination mechanisms

Page 98: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

0

20000

40000

60000

80000

100000

120000

140000

160000

0 100 200 300 400 500 600 700

p [psig]

Mn

iBHTiBHTINSBHT

iINSiINSINSINS

kkkkpkk

kkkkpkkR

'''

'''

++

++=

Pressure dependence of molecular weight:

kINS / kBHT → E#BHT - E#

INS = 6,1[kcal/mol]

k’INS / k’BHT → E#BHT’ - E#

INS’ = 5,0[kcal/mol]

ki / kBHT → E#BHT - E#

i = 6,1 [kcal/mol]

k’i / k’BHT → E#BHT’ - E#

i’ = 3,4 [kcal/mol]

experimental fitted

‘Experimental’ energy differences:

� R. Szeliga, A. Michalak, manuscript in preparation

Page 99: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

NiL L

R

H

CH2

CH2

NiL L

R

NiL L

R

+

NiL L

H

R

+CH2

CH2

NiL L

R

NiL L

R

BHTBHT

NiL L

H

R

Ni

L L

H

R

NiL L

HR

Ni

L L

H

+

R

NiL L

H

R

Ni

L L

H

R

NiL L

H

R

NiL L

R

H

Ni

L L

H

R

NiL L

HR

1a1b

2a

3a

2b

3b

5a

Propagation

6

9a

11a

13a14

9b

11b

13a

5b

R

+

Ni

L L

H

7

Propagation

Isomerization

CH2

CH2

CH2

CH2

++

BHE

BHTBHT

� R. Szeliga, A. Michalak, manuscript in preparation

Page 100: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

NiL L

R

H

CH2

CH2

NiL L

R

NiL L

R

+

NiL L

H

R

+CH2

CH2

NiL L

R

NiL L

R

BHTBHT

NiL L

H

R

Ni

L L

H

R

NiL L

HR

Ni

L L

H

+

R

NiL L

H

R

Ni

L L

H

R

NiL L

H

R

NiL L

R

H

Ni

L L

H

R

NiL L

HR

1a1b

2a

3a

2b

3b

5a6

9a

11a

13a14

9b

11b

13a

5b

R

+

Ni

L L

H

7

CH2

CH2

CH2

CH2

++

BHE

BHTBHT

PropagationPropagation

Isomerization

� R. Szeliga, A. Michalak, manuscript in preparation

Page 101: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

∆E

0

10

-10

-20,0

1,73

7,05

-20.89

0.65

TS

TSTS

TS

TSTS

n - propyl iso - propyl

β, n β, izoπ,ag, p

π,ag, et π,ag, et

π,ag, p π,2H

π,2H

π π

-5.01 -5.01

β, et β, et

Insertion, isomerization, BHT – real system:Insertion, isomerization, BHT – real system:

10.38

6.696,49

6.73

14.77

0.01,03

Isomerization

π,H -1,46

-2,54

TS

-19,03

Propagation

secondary

BHT

secondary

BHT

primary

Propagation

primary

TS

-1,7

-18,43

β β

∆E = 9,03

Mn= 10 900 000

highly

overestimated

4,73 3,37

Page 102: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

kINS / kBHT → E#BHT - E#

INS = 8,43 [kcal/mol]

k’INS / k’BHT → E#BHT’ - E#

INS’ = 9,03[kcal/mol]

ki / kBHT → E#BHT - E#

i = 2,07 [kcal/mol]

k’i / k’BHT → E#BHT’ - E#

i’ = 1,83 [kcal/mol]

Modelling molecular weight and termination mechanismsModelling molecular weight and termination mechanisms

Calculated energy differences:

kINS / kBHT → E#BHT - E#

INS = 6,1[kcal/mol]

k’INS / k’BHT → E#BHT’ - E#

INS’ = 5,0[kcal/mol]

ki / kBHT → E#BHT - E#

i = 6,1 [kcal/mol]

k’i / k’BHT → E#BHT’ - E#

i’ = 3,4 [kcal/mol]

‘Experimental’ energy differences:

Calculations prove the existence of two different

propagation and termination mechanisms

(qualitatively justify pressure dependence)

but the accuracy of the energy differences is insufficient to

quantitatively model the molecular weight

Page 103: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

Polar copolymerization – diimine catalysts

Page 104: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

Copolymerization of α-olefins with methyl acrylate

N^N-Pd+ - active

N^N-Ni+ - inactive

Diimine catalystsDiimine catalysts

Experimental data:

• Johnson, L. K.; Mecking, S.; Brookhart, M. J. Am. Chem. Soc. 1996, 118, 267.

• Mecking, S.; Johnson, L. K.; Wang, L.; Brookhart, M. J. Am. Chem. Soc. 1998, 120, 888.

Experimental data:

• Johnson, L. K.; Mecking, S.; Brookhart, M. J. Am. Chem. Soc. 1996, 118, 267.

• Mecking, S.; Johnson, L. K.; Wang, L.; Brookhart, M. J. Am. Chem. Soc. 1998, 120, 888.

Page 105: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

Copolymerization of ethylene with methyl acrylate

N^N-Pd+ - active

N^N-Ni+ - inactive

(active in higher T)

Diimine catalystsDiimine catalysts

Experimental data:

• Johnson, L. K.; Mecking, S.; Brookhart, M. J. Am. Chem. Soc. 1996, 118, 267.

• Mecking, S.; Johnson, L. K.; Wang, L.; Brookhart, M. J. Am. Chem. Soc. 1998, 120, 888.

Experimental data:

• Johnson, L. K.; Mecking, S.; Brookhart, M. J. Am. Chem. Soc. 1996, 118, 267.

• Mecking, S.; Johnson, L. K.; Wang, L.; Brookhart, M. J. Am. Chem. Soc. 1998, 120, 888.

O OMe

MeO O

OMeO

MeO

O

OMeO

Ni-diimine catalyst:

Pd-diimine catalyst:

Page 106: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

Copolymerization mechanism – acrylate insertionCopolymerization mechanism – acrylate insertion

� A. Michalak, T. Ziegler, „DFT Studies on the Copolymerization of a-Olefins with Polar Monomers: Ethylene-Methyl Acrylate Copolymerization Catalyzed by a Pd-based Diimine Catalyst”,

J. Am. Chem. Soc, 123, 2001, 12266-12278.

Page 107: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

0

-10

-5

-15

-20

-25

-30

-35

-40

alkyl agostic

+acrylate

acrylate

ππππ complex

insertion TS

γγγγ−−−−agostic

ββββ-agostic

-20.7

+19.4

-18.5

-5.3

-20.7

CC

C

NN

O

O

C

Pd

C

CC

C

C

C C

N N

Pd

C

C

O

C

C

C

C

C

O

C C

N N

Pd

O

C

C

C

C

C

O

C

C

CC

NN

Pd

C C

C

O

CC

C

C

O

kcal/mol

Acrylate insertion (2,1-) – Pd catalystAcrylate insertion (2,1-) – Pd catalyst

� A. Michalak, T. Ziegler, J. Am. Chem. Soc, 123, 2001, 12266-12278.

Page 108: Quantum chemical molecular modellingmichalak/mmod2008/L12.pdf · 2009. 1. 13. · Quantum chemical modelling of chemical processes • Computational methods: ab initio and semi-empirical

0

-10

-5

-15

-20

-25

-30

-35

-40

alkyl agostic

+acrylate

acrylate

ππππ complex

insertion TS

γγγγ−−−−agostic

ββββ-agostic

-20.7

+19.4

-18.5

-5.3

-20.7

CC

C

NN

O

O

C

Pd

C

CC

C

C

C C

N N

Pd

C

C

O

C

C

C

C

C

O

C C

N N

Pd

O

C

C

C

C

C

O

C

C

CC

NN

Pd

C C

C

O

CC

C

C

O

kcal/mol

Acrylate insertion (2,1-) – Pd catalystAcrylate insertion (2,1-) – Pd catalyst

� A. Michalak, T. Ziegler, J. Am. Chem. Soc, 123, 2001, 12266-12278.

Real catalyst:

insertion barrier 12.4 kcal/mol

exp. ins. barrier 12.1 ± 1.4

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0

-10

-5

-15

-20

-25

-30

-35

-40

alkyl agostic

+acrylate

acrylate

ππππ complex

insertion TS

γγγγ−−−−agostic

ββββ-agostic

4-memb.

chelate

5-memb.

chelate6-memb.

chelate

-20.7

+19.4

-18.5

-5.3

-8.5

-6.1

-1.1

-20.7

CC

C

NN

O

O

C

Pd

C

CC

C

C

C C

N N

Pd

CO

C

C

C

C

C

O

C

C C

C

N N

C

Pd

C

CO

C

C

C

O

C C

N N

Pd

CO

C

C

C

C

C

C

O

C C

N N

Pd

C

C

O

C

C

C

C

C

O

C C

N N

Pd

O

C

C

C

C

C

O

C

C

CC

NN

Pd

C C

C

O

CC

C

C

O

kcal/mol

Acrylate insertion (2,1-) – Pd catalystAcrylate insertion (2,1-) – Pd catalyst

� A. Michalak, T. Ziegler, J. Am. Chem. Soc, 123, 2001, 12266-12278.

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0

-10

-5

-15

-20

-25

-30

-35

-40

alkyl agostic+acrylate

acrylate

ππππ complex

insertion TS

γγγγ-agostic

ββββ-agostic

4-memb. chelate

5-memb. chelate

6-memb. chelate

CC

C

NN

O

O

C

Pd

C

CC

C

C

C C

N N

Pd

CO

C

C

C

C

C

OC

C C

C

N N

C

Pd

C

CO

C

C

C

O

C C

N N

Pd

CO

C

C

C

C

C

C

O

C C

N N

Pd

C

C

O

C

C

C

C

C

O

C C

N N

Pd

O

C

C

C

CC

O

C

C

CC

NN

Pd

C C

C

O

CC

C

C

O

kcal/mol

Acrylate insertion (2,1-) - Pd and Ni catalystsAcrylate insertion (2,1-) - Pd and Ni catalysts

� A. Michalak, T. Ziegler, J. Am. Chem. Soc, 123, 2001, 12266-12278; Organometallics, 22 (2003), 2660-2669.

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Two-step chelate openingTwo-step chelate opening

very high insertion barriers

lower for Ni-catalyst

low insertion barriers,

lower for Ni-catalyst

� A. Michalak, T. Ziegler, Organometallics, 22, 2003, 2660-2669. „A comparison of Ni- and Pd-diimine complexes as catalysts for Et / MA copolymerization. A static and dynamic density functional theory study”

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Two-step chelate openingTwo-step chelate opening

very high insertion barriers

lower for Ni-catalyst

� A. Michalak, T. Ziegler, „DFT Studies on the Copolymerization of a-Olefins with Polar Monomers: Ethylene-Methyl Acrylate Copolymerization Catalyzed by a Pd-based Diimine Catalyst”,

J. Am. Chem. Soc, 123, 2001, 12266-12278.

� A. Michalak, T. Ziegler, „A comparison of Ni- and Pd-diimine complexes as catalysts for ethylene / methyl acrylate copolymerization. A static and dynamic density functional theory study”,

Organometallics, 22, 2003, 2660-2669.

� A. Michalak, T. Ziegler, „DFT Studies on the Copolymerization of a-Olefins with Polar Monomers: Ethylene-Methyl Acrylate Copolymerization Catalyzed by a Pd-based Diimine Catalyst”,

J. Am. Chem. Soc, 123, 2001, 12266-12278.

� A. Michalak, T. Ziegler, „A comparison of Ni- and Pd-diimine complexes as catalysts for ethylene / methyl acrylate copolymerization. A static and dynamic density functional theory study”,

Organometallics, 22, 2003, 2660-2669.

low insertion barriers,

lower for Ni-catalyst

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Copolymerization mechanism

– catalyst-monomer complexes

Copolymerization mechanism

– catalyst-monomer complexes

� A. Michalak, T. Ziegler, „DFT Studies on the Copolymerization of a-Olefins with Polar Monomers: Comonomer Binding by Nickel- and Palladium-Based Catalysts with Brookhart and GrubbsLigands”, Organometallics, 20, 2001, 1521-1532.

� A. Michalak “Two-reactant Fukui function and molecular electrostatic potential analysis of the methyl acrylate binding mode in the complexes with the Ni- and Pd-diimine catalysts”, Chem. Phys.

Lett., 386, 2004, 346-350.

� A. Michalak, T. Ziegler, „DFT Studies on the Copolymerization of a-Olefins with Polar Monomers: Comonomer Binding by Nickel- and Palladium-Based Catalysts with Brookhart and GrubbsLigands”, Organometallics, 20, 2001, 1521-1532.

� A. Michalak “Two-reactant Fukui function and molecular electrostatic potential analysis of the methyl acrylate binding mode in the complexes with the Ni- and Pd-diimine catalysts”, Chem. Phys.

Lett., 386, 2004, 346-350.

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Ni- (inactive):

σ−complex preferred

Pd- (active)

π−complex preferred

Preference of the π− / σ− complex

- theoretical catalyst screening test

π− / σ− complexesπ− / σ− complexes

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ππππ−−−− / σ/ σ/ σ/ σ−−−− complexes: two reactant Fukui functionππππ−−−− / σ/ σ/ σ/ σ−−−− complexes: two reactant Fukui function

� A. Michalak „“Two-reactant Fukui function and molecular electrostatic potential analysis of the methyl acrylate binding mode in the complexes with the Ni- and Pd-diimine catalysts”, Chem. Phys.

Lett., 386, 2004, 346-350.

� A. Michalak „“Two-reactant Fukui function and molecular electrostatic potential analysis of the methyl acrylate binding mode in the complexes with the Ni- and Pd-diimine catalysts”, Chem. Phys.

Lett., 386, 2004, 346-350.

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π− / σ− complexesπ− / σ− complexes

Methyl acrylate: molecular electrostatic potential

Electrostatic origin of the σσσσ−−−−complex preference for Ni-system

� A. Michalak „“Two-reactant Fukui function and molecular electrostatic potential analysis of the methyl acrylate binding mode in the complexes with the Ni- and Pd-diimine catalysts”, Chem. Phys.

Lett., 386, 2004, 346-350.

� A. Michalak „“Two-reactant Fukui function and molecular electrostatic potential analysis of the methyl acrylate binding mode in the complexes with the Ni- and Pd-diimine catalysts”, Chem. Phys.

Lett., 386, 2004, 346-350.

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π− / σ− complexesπ− / σ− complexes

� A. Michalak „“Two-reactant Fukui function and molecular electrostatic potential analysis of the methyl acrylate binding mode in the complexes with the Ni- and Pd-diimine catalysts”, Chem. Phys.

Lett., 386, 2004, 346-350.

� A. Michalak „“Two-reactant Fukui function and molecular electrostatic potential analysis of the methyl acrylate binding mode in the complexes with the Ni- and Pd-diimine catalysts”, Chem. Phys.

Lett., 386, 2004, 346-350.

Electrostatic origin of the σσσσ−−−−complex preference for Ni-system

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Copolymerization of ethylene with methyl acrylate

N^N-Pd+ - active

N^N-Ni+ - inactive

(active in higher T)

Diimine catalystsDiimine catalysts

Experimental data:

• Johnson, L. K.; Mecking, S.; Brookhart, M. J. Am. Chem. Soc. 1996, 118, 267.

• Mecking, S.; Johnson, L. K.; Wang, L.; Brookhart, M. J. Am. Chem. Soc. 1998, 120, 888.

Experimental data:

• Johnson, L. K.; Mecking, S.; Brookhart, M. J. Am. Chem. Soc. 1996, 118, 267.

• Mecking, S.; Johnson, L. K.; Wang, L.; Brookhart, M. J. Am. Chem. Soc. 1998, 120, 888.

O OMe

MeO O

OMeO

MeO

O

OMeO

Ni-diimine catalyst:

Pd-diimine catalyst:

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Chain isomerization

α−olefin polymerization mechanismα−olefin polymerization mechanism

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Isomerization reactions in polar copolymerizationIsomerization reactions in polar copolymerization

O OMe

MeO O

influence on microstructure:

no isomerizations

O OMe

MeO Oisomerizations

after ethylene insertion

OMeO

MeO

O

isomerizations

after acrylate insertion

OMeO

MeO

O

OMeO

isomerizations after both, MA and Et insertion

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RC

7.8

12.9

E [kcal/mol]

14A-Pd

14A-Ni

6A,6E-Ni, Pd Pd

Ni

non-polarpolar

10.4

14E-Pd

4.2

14E-Ni

8A,8E-Ni, Pd

The energy of hydride olefin complexes (isomerization’s intermediates)

with Pd- and Ni-catalysts.

Mariusz Mitoraj, Artur Michalak, J. Mol. Model. , 2005, published on web, May 2005Mariusz Mitoraj, Artur Michalak, J. Mol. Model. , 2005, published on web, May 2005

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TheThe profile profile ofof isomerizationisomerization for for NiNi--catalystcatalyst::

Mariusz Mitoraj, Artur Michalak, J. Mol. Model. , 2005, published on web, May 2005Mariusz Mitoraj, Artur Michalak, J. Mol. Model. , 2005, published on web, May 2005

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TheThe profile profile ofof isomerizationisomerization for for PdPd--catalystcatalyst::

Mariusz Mitoraj, Artur Michalak, J. Mol. Model. , 2005, published on web, May 2005Mariusz Mitoraj, Artur Michalak, J. Mol. Model. , 2005, published on web, May 2005

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ConclusionsConclusions

DFT:• understanding mechanistic details of the process;

• energetics in reasonable agreement with experimental data;

• understanding of the electronic and steric influence of the

catalysts substituents;

• relationship between the catalyst structure and the energetics

of the process

Stochastic (mesoscopic) simulations:• provide a link between the microscopic and macroscopic level

• identify 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

• relationship between the energetics of the process, p, T, and

the polymer branching and microstructure

DFT:• understanding mechanistic details of the process;

• energetics in reasonable agreement with experimental data;

• understanding of the electronic and steric influence of the

catalysts substituents;

• relationship between the catalyst structure and the energetics

of the process

Stochastic (mesoscopic) simulations:• provide a link between the microscopic and macroscopic level

• identify 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

• relationship between the energetics of the process, p, T, and

the polymer branching and microstructure

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To be continued…