APPLICATION OVERVIEW
MATERIALS SCIENCE SUITE
Catalysis and Chemical Reactivity
Schrödinger’s Materials Science Suite has unique model builders, an extremely
efficient DFT engine, Jaguar, automated DFT-based reactivity workflows, and
analysis tools for the simulation, optimization, and discovery of effective,
efficient, selective catalysts and reactive systems.
Keywords: quantum mechanics, density functional theory, DFT, reactivity, catalysis,
atomic layer deposition
BACKGROUND
Advances in the capability and efficiency of quantum mechanics programs and the
improvement in computer performance has pushed the applicability of first-principles
simulation from the small molecule domain to the study of chemically realistic systems
with high accuracy. In addition to furnishing atomistic details for reaction mechanisms,
quantum mechanics-based simulation (e.g. density functional theory, DFT) enables the
calculation of energetics and properties with an accuracy comparable to experiment.
APPLICATION: HOMOGENEOUS CATALYSIS
For homogeneous catalysis, DFT can provide the fundamental understanding needed
to enable the rational modification of a catalyst to achieve desired increases in reactivity
and chemo-, regio-, and stereo-selectivity. Despite their importance in a range of
applications, fluorinated aromatic molecules are difficult to synthesize; recently a
Pd-catalyst to convert aryl bromides and aryl triflates to aryl fluorides was reported.3
Room temperature reaction conditions can now be used due to a novel fluorinated
ligand, however the underlying rationale leading to the observed reactivity is not fully
understood.
The complete reaction pathway for the Pd-mediated fluorination of p-tolyl bromide
using the reference ligand 1 was investigated using Jaguar as shown in Figure 1.
The catalytic cycle for this process begins with the substrate-catalyst complex I.
Oxidative addition TS-II of the Pd center into the C-Br bond leads to the aryl-bromide
intermediate III. Transmetalation TS-IV replaces the Br for F to give the aryl fluoride
intermediate V. The rate determining reductive elimination TS-VI step releases the Pd
center and creates the C-F bond to afford the product-catalyst complex VII. Transfer of
the catalyst to another substrate releases the product and regenerates the catalyst.
Figure 1. Complete reaction pathway for the Pd-mediated fluorination of p-tolyl bromide, calculated using DFT.
The rate determining step is between the aryl fluoride intermediate V and the reductive elimination TS-VI. (∆G
in kcal/mol; computed using B3LYP/LACVP* at 298.15 K, 1 atm)
Once the reaction mechanism is fully elucidated and
rate determining TS identified, catalyst derivatives
can easily be evaluated for reactivity and selectivity.
As shown in Figure 2, the rate determining step was
computed for two ligands, 2 and 3, and their kinetic
barriers are presented in Figure 2. Addition of an aryl
group (2) in the 3` position is found to hinder activity
by increasing the internal barrier, whereas the electron
withdrawing effect of the perfluorinated 3` aryl group
(3) leads to more favorable kinetics with an activation
energy 2 kcal/mol lower than the aryl-substituted
catalyst; ranking catalyst candidates in agreement with
the experimental report by Buchwald and co-workers.3
Figure 2. Comparison of rate determining reductive
elimination TS barriers between three ligands, the reference
ligand 1, arylated ligand 2, and perfluoroarylated ligand 3.
(∆G in kcal/mol; computed with B3LYP/LACVP* at 298.15 K,
1 atm)
APPLICATION: ATOMIC LAYER DEPOSITION
Thin film deposition by atomic layer deposition (ALD) is under widespread development for
semiconductor device fabrication. ALD affords uniform, conformal thin films with thickness control at
the atomic level through the cycling of self-limiting surface reactions. The initial deposition of Al2O3
on hydrogen-terminated silicon by ALD could require nucleation through exposure to either the Al- or
O-precursor (Al(CH3)3 or H2O, respectively). To determine the differential reactivity for Al2O3 nucleation on
H/Si, the kinetic barrier for the initial reaction between Al(CH3)3 and H2O with H/Si was calculated with
DFT using Jaguar.
The calculated kinetic barriers for Al(CH3)3 and H2O
with H/Si indicate significant preference for Al(CH3)3.
The ∆G‡ for the Al-precursor reaction is predicted to
be lower than the O-precursor reaction by 7.7 kcal/mol
(using M06-L/6-31G** at 300 K and 1 atm). The kinetic
selectivity for the Al reaction over the O reaction
on H/Si is presented in Figure 3, over a range of
temperatures (1 atm); showing the kinetic preference
for Al(CH3)3 in excellent agreement with experimental
observations. Chabal and co-workers4 carried out an
Figure 3. Al(CH3)3:H2O relative kinetic selectivity for
reaction with H/Si(111) across a range of temperatures.
in situ infrared study of the ALD nucleation of Al2O3
H2O nucleation (top left) and TMA nucleation (bottom
in H/Si using Al(CH3)3 and H2O. They observed only
right) transition state geometries. (-∆∆G‡in kcal/mol;
reaction with Al(CH3)3 and not with H2O and the silicon
computed with M06-L/LACVP** at 100-500 K, 1 atm)
substrate, remarking, “Contrary to common belief, we
find that the metal precursor, not the oxidizing agent, is the key factor to control Al2O3 nucleation on
hydrogen-terminated silicon.”
SUMMARY
The rate of reaction, mechanistic path, and selectivities for a target reaction are directly determined
by the free-energies of the critical point structures defining a particular reaction pathway. Comparison
of competing reaction pathways reveals differential reactivity that can be exploited in reactive process
engineering. DFT simulation using Schrödinger’s Materials Science Suite is a powerful tool for analysis,
optimization, and discovery. Automated reactivity workflows, such as Reaction Energy Enumeration,
Reaction Channel Enumeration, and AutoTS strengthen and extend the role of quantum mechanicsbased simulation for the optimization and discovery of new metal-ligand architectures and functional
co-reactants with enhanced reactivity and selectivity, informing the development of enhanced catalysts
and reactive precursors and processes.
REFERENCES
1.
2.
3.
4.
B.H. Greeley, et al., J. Chem. Phys., 1994, 101, 4028.
A.D. Bochevarov, Int. J. Quantum Chem., 2013, 113, 2110.
A.C. Sather, J. Am. Chem. Soc., 2015, 137(41), 13433.
M.M Frank, Y.J. Chabal and G.D. Wilk, Appl. Phys. Lett., 2003, 82, 4758.
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APPLICATION OVERVIEW