Aluminum alkoxide complexes (2) of salen ligands with a three-carbon linker and para substituents having variable electron-withdrawing capabilities (X = NO2, Br, OMe) were prepared, and the kinetics of their ring-opening polymerization (ROP) of ε-caprolactone (CL) were investigated as a function of temperature, with the aim of drawing comparisons to similar systems with two-carbon linkers investigated previously (1). While 1 and 2 exhibit saturation kinetics and similar dependences of their ROP rates on substituents X (invariant Keq, similar Hammett ρ = +1.4(1) and 1.2(1) for k2, respectively), ROP by 2 was significantly faster than for 1. Theoretical calculations confirm that, while the reactant structures differ, the transition state geometries are quite similar, and by analyzing the energetics of the involved distortions accompanying the structural changes, a significant contribution to the basis for the rate differences was identified. Using this knowledge, a simplified computational method for evaluating ligand structural influences on cyclic ester ROP rates is proposed that may have utility for future catalyst design.
Aluminum alkoxidecomplexes (2) of salen ligands with a three-carbon linker and para substituents having variable electron-withdrawing capabilities (X = NO2, Br, OMe) were prepared, and the kinetics of their ring-opening polymerization (ROP) of ε-caprolactone (CL) were investigated as a function of temperature, with the aim of drawing comparisons to similar systems with two-carbon linkers investigated previously (1). While 1 and 2 exhibit saturation kinetics and similar dependences of their ROP rates on substituents X (invariant Keq, similar Hammett ρ = +1.4(1) and 1.2(1) for k2, respectively), ROP by 2 was significantly faster than for 1. Theoreticalcalculations confirm that, while the reactant structures differ, the transition state geometries are quite similar, and by analyzing the energetics of the involved distortions accompanying the structuralchanges, a significant contribution to the basis for the rate differences was identified. Using this knowledge, a simplified computational method for evaluating ligand structural influences on cyclic ester ROP rates is proposed that may have utility for future catalyst design.
Through the conpan>trolled
rinpan>g-openinpan>g polymerization of cyclic esters,
a variety of useful and often renewable polymers may be synthesized.[1,2] Among the catalysts found to be effective in such polymerization
reactions, metal alkoxides are ubiquitous and in many cases operate
at high rates with excellent control of polymer molecular weight and
stereochemistry.[2b−2h] Further improvements in catalytic behavior by metal alkoxidecatalysts
are likely if the mechanism(s) of ROP is (are) understood and the
roles of supporting ligand structural variation on ROP rates and selectivities
are unraveled. Toward that end, numerous mechanistic studies have
been reported, leading to the hypothesis of the often used and generic
“coordination–insertion” pathway (Scheme ), wherein binding of the ester
to the metal (coordination) is followed by nucleophilic attack and
ring opening (insertion).[2,3] However, the involvement
of these two sequential independent steps has been difficult to confirm
and evaluation of the influences of ligand variation on them has been
impeded because comparisons are typically made on the basis of measured
pseudo-first-order rate constants (kapp) that are composites of equilibrium and/or rate constants for the
attendant elementary reaction steps. Nonetheless, intriguing effects
of changes in ligand structure on ROP kapp values have been seen. A notable example is a study of rac-lactide (LA) polymerization using aluminum alkoxidecatalysts derived
from treatment of (salen)AlMe complexes with benzyl alcohol (Figure , top);[4] such aluminum alkoxidecatalysts are known to
be mononuclear, single-site species that operate at rates convenient
for measurement by routine NMR methods. Rates of LA ROP increased
when R1 = R2 = Cl versus H or t-Bu (with identical linkers X), consistent with the enhanced electrophilicity
of the metalcenter underlying higher kapp values. The rates also increased as the linker was changed from
two to three carbons (X = −CH2C(Me)2–
vs −CH2C(Me)2CH2−),
but on the basis of the data available the only conclusion drawn was
that “the enhanced performance of the C3 linker
is more a function of the flexibility of the linking unit, which may
allow the complex to better access the key transition states involved
in the ROP process”.[4]
Scheme 1
Generalized
Coordination–Insertion Mechanism
Figure 1
Generalized structures of (salen)AlMe complexes studied as LA polymerization
precursors (top)[4] and catalysts 1 and 2 used in mechanistic studies of CL polymerization
(bottom).
Generalized structures of (salen)AlMe complexes studied as LA polymerization
precursors (top)[4] and catalysts 1 and 2 used in mechanistic studies of CL polymerization
(bottom).We have sought more detailed mechanistic
information for such cyclicesterpolymerizations by mononuclear aluminum alkoxidecomplexes through
dissection of composite kapp values into
kinetic/thermodynamicconstants associated with elementary reaction
steps.[5,6] Through such studies, we aim to better understand
the fundamental basis for ROP rate differences caused by catalyst
structure variation in compounds that are single-site catalysts, with
the ultimate goal of applying this knowledge to the design of more
effective catalysts. In previous work,[6] we examined the kinetics of ε-caprolactone (CL) polymerization
by mononuclear aluminum alkoxidecomplexes 1 (Figure ) using high monomer
concentrations ([CL]0 ≥ 2.0 M). Under these conditions,
saturation behavior was observed, and the data could be fit to the
rate law eq (PCL =
polycaprolactone) to provide values of the equilibrium constant for
monomer binding, Keq, and the rate constant
for monomer enchainment, k2, as a function
of temperature and remote substituent R. While Keq varied little as a function of the electron-withdrawing
properties of R (Hammett ρ = +0.16(8)), the k2 dependence was significantly larger (ρ = +1.4(1)),
supporting the hypothesis that differences in k2 underly observed overall rate differences and that k2 is enhanced by increased electrophilicity
of the metalcenter. Density functional theory (DFT) revealed transition state (TS) structures
featuring bond formation between the alkoxide and the incoming carbonyl
of CL, showing that greater electron withdrawal by the substituent
on the salen ligand results in greater bonding between the nucleophilicalkoxide and the lactonecarbonyl carbon in the TS to give enhanced
polymerization rates, and indicated that Keq was not appropriately assigned to formation of a CL adduct along
the reaction pathway; instead, Keq is
associated with “nonproductive” binding that inhibits
the ROP rate at high substrate concentrations.To dissect the inpan>triguinpan>g effect of linker length described
in
the previous studies,[4] we have now applied
our saturation kinetics approach to ROP by 2, comprising
the same substituents as 1 but with a longer ligand linker.
As described below, we observed saturation kinetics for CL polymerization
by 2 that were fit to eq to yield Keq and k2 values as a function of temperature. Comparison
of these values to those reported previously for 1,[6] in concert with evaluation of reactant and transition-state
structures via DFT, provided additional detailed insight into how
linker length affects ROP, with intriguing implications for future
ROP catalyst design.
Results
Synthesis and Characterization
of Ligands and Complexes
The proligands H2LR (R = OMe, Br, NO2) and their complexes 2 were prepared according to the
same procedures described previously for 1,[6] except using 2,2-dimethyl-1,3-propanediamine
in the condensations with the respective salicylaldehydes. The proligands
were isolated as bright yellow crystalline solids in good yields (70–91%)
and then heated with Al(O-i-Pr)3 in toluene
to afford the compounds 2, which were isolated as analytically
pure bright yellow, yellow, and light brown solids (R1 =
OMe, Br, NO2, respectively), also in good yields (72–90%).
The proligands and complexes were characterized by 1H,
{1H}13C, and 27Al NMR spectroscopy,
CHN analysis, and, for 2 (R = Br), X-ray crystallography.
The X-ray structure (Figure ) confirms the anticipated five-coordinate formulation with
a τ value of 0.84,[7] close to idealized
trigonal bipyramidal (τ =1) and similar to that of related complexes
of salen ligands also featuring the 2,2-dimethylpropyl linker.[4,8] The τ value differs from that previously determined for 1 (R = OMe; τ = 0.52)[6] and
other closely related congeners with a two-carbon linker (τ
= 0.48–0.56).[4,8a,8b] Density
functional theory optimization of 2 (R = H; see Density FunctionalCalculations for theoretical
details) provided a τ value of 0.85, which is in excellent agreement
with that determined from crystallography, suggesting that crystal
packing forces do not significantly influence the intrinsiccoordination
geometry at the aluminumcenter.
Figure 2
Representation of the X-ray crystal structure
of 2 (R = Br), showing all non-hydrogen atoms as 50%
thermal ellipsoids.
Selected interatomic distances (Å) and angles (deg): Al1–O1,
1.7803(17); Al1–O2, 1.8225(18); Al1–O3, 1.7345(19);
Al1–N1, 2.054(2); Al1–N2, 1.994(2); O3–Al1–O2,
95.76(9); O3–Al1–O1, 120.96(9); O2–Al1–O1,
91.22(8); O3–Al1–N1, 92.35(9); O2–Al1–N1,
171.10(9); O1–Al1–N1, 87.74(8); O3–Al1–N2,
118.71(9); O2–Al1–N2, 88.90(8); O1–Al1–N2,
119.98(9); N1–Al1–N2, 83.98(8).
Representation of the X-ray crystpan> class="Chemical">al structure
of 2 (R = Br), showing all non-hydrogen atoms as 50%
thermal ellipsoids.
Selected interatomic distances (Å) and angles (deg): Al1–O1,
1.7803(17); Al1–O2, 1.8225(18); Al1–O3, 1.7345(19);
Al1–N1, 2.054(2); Al1–N2, 1.994(2); O3–Al1–O2,
95.76(9); O3–Al1–O1, 120.96(9); O2–Al1–O1,
91.22(8); O3–Al1–N1, 92.35(9); O2–Al1–N1,
171.10(9); O1–Al1–N1, 87.74(8); O3–Al1–N2,
118.71(9); O2–Al1–N2, 88.90(8); O1–Al1–N2,
119.98(9); N1–Al1–N2, 83.98(8).The 1H NMR spectra for the complexes 2 (Figures S1–S6 in the Supporting
Information)
are consistent with monomeric structures and contain a single resonance
for the tert-butyl groups, indicating that the two
different chemical environments of the aryl groups in the experimentally
determined X-ray structure for 2 (R = Br) and calculated
gas-phase structures for 2 (R = H) are averaged in solution.
Such fluxionality was reported for other complexes of related salen
ligands with the 2,2-dimethylpropyl linker.[4,8] The
NMR spectra of the complexes 2 with different R groups
are generally similar, except for differences in the aryl region (iminehydrogens and two aromatichydrogens adjacent to R). The 27Al NMR spectra contain a single resonance at 35, 34, and 33 ppm for
the complexes with R = OMe, Br, NO2, respectively.
Kinetics
of CL Polymerizations
NMR-scale polymerization
reactions for each catalyst were run in triplicate at four different
temperatures ranging from 273 to 313 K. The reactions were performed
in toluene-d8 with a fixed initialconcentration
of monomer ([CL] = 2.0 M), catalyst ([cat] = 5.5–7.0 mM), and
internal standard ([1,4-bis(trimethylsilyl)benzene] = 4.0 mM), with
growth of polymer (PCL) and decay of monomer (CL) monitored throughout
the reaction by 1H NMR spectroscopy. Most polymerizations
achieved 99% conversion, except for those catalyzed by 2 (R = NO2) at 273 K, for which the loss of NMR shims only
allowed for analysis up to only about 84% conversion. Similarly to
previous work,[5,6] the concentrations of CL and PCL
(determined by integrations vs the standard) were plotted versus time
and fit to eq using
the global kinetics fitting program COPASI (Figures S7–S11 in the Supporting Information). A reaction progress
kinetic analysis (RPKA)[9] protocol was used
to analyze one polymerization run (R = Br, 273 K) and further supported
the appropriateness of eq (Figure S12 and Table S2 in the Supporting
Information), with fits to alternative first- and second-order rate
laws being notably inferior (Figure S13 in the Supporting Information). Average values from the triplicate
runs for the kinetic parameters Keq and k2 calculated from the COPASI fits to eq are compiled in Table ; the complete list
of parameters from both COPASI analysis and RPKA are provided in Table S1 in the Supporting Information.
Table 1
Average Values for Kinetic Parameters Keq and k2 for Complexes 2
Keq (M–1)
entry
temp (K)
R
COPASI
NMR
k2 (s–1)
1
313
OMe
3.4(7)
0.65(9)
0.32(2)
2
298
OMe
3.8(7)
0.64(5)
0.147(5)
3
293
OMe
3.3(4)
0.69(4)
0.105(3)
4
283
OMe
4.0(5)
0.88(3)
0.048(3)
5
298
Br
1.4(3)
0.6(1)
0.67(6)
6
293
Br
1.3(2)
1.2(4)
0.53(4)
7
283
Br
1.5(2)
0.9(2)
0.27(2)
8
273
Br
1.7(2)
0.65(8)
0.106(6)
9
293
NO2
0.8(4)
1.9(5)
1.9(7)
10
288
NO2
0.5(2)
1.6(3)
1.9(6)
11
278
NO2
0.9(3)
1.9(2)
0.6(2)
12
273
NO2
0.7(5)
1.7(5)
0.5(2)
The presence of a substrate
binpan>dinpan>g equilibrium characterized by Keq was further confirmed by two independent
sets of experiments. First, we analyzed the chemical shifts of peaks
associated with the catalyst during the polymerization reaction. Changes
in the chemical shifts of the catalyst peaks as a function of [CL]
were observed, and we analyzed them as described previously,[5,6] working under the assumption that these changes arise from rapid
equilibration between complexes with and without bound monomer. Typical1H NMR spectra and plots of chemical shift vs [CL] are presented
in Figures S14–S17 in the Supporting
Information, and calculated average Keq values are given in Table (a full list is given in Table S3 in the Supporting Information). Although the Keq values independently determined from the catalyst NMR peak
analysis and those obtained from the kinetic fits (COPASI) of the
CL decay and PCL generation profiles to eq are not identical, we consider them to be
sufficiently similar to be consistent with the hypothesized substrate
binding equilibration, especially if one considers the narrow span
of derived ΔG° values (see below).In a seconpan>d set of experiments, complexes 2 were mixed
at 293 K with varying concentrations of γ-butyrolactone (BL),
a cyclic ester that is relatively unreactive toward ring-opening polymerization.[10] The chemical shifts of the ligand peaks in the
aromatic region were observed to change as a function of [BL], consistent
with a binding equilibrium. Fitting of the data accordingly yielded Keq values of 0.6(1), 0.5(2), and 0.9(2) for
R = OMe, Br, NO2, respectively (Figures S18 and S19 in the Supporting Information). The relatively
good agreement among the Keq values determined
from fitting of the kinetic profiles and analysis of the catalyst
NMR peaks during CL polymerization and in the presence of BL provides
strong experimental evidence for equilibrium binding of lactones to
the catalysts 2 (Table S4 in
the Supporting Information).Evaluationpan> of the variationpan> of
the experimentally determined kinetic
and thermodynamic parameters as a function of substituent R and temperature
provided important insights. A plot of ln Keq versus 1/T including values from both COPASI (circles)
and NMR analysis (squares) shows clustering of ln Keq values within a relatively narrow range (−0.5
to +1.5) and with minimal temperature dependences indicative of relatively
small ΔG° values of <2 kcal mol–1 for monomer binding (Figure ). The Keq values
determined by COPASI as a function of R are ordered OMe > Br >
NO2, but the differences are small and this ordering is
not followed
using the values determined by the NMR method. Thus, as reported previously
for 1,[6] we conclude that the
thermodynamics for binding of CL to 2 are relatively
insensitive to substituent R, consistent with differences in CL binding
not being an important basis for the differences in the observed polymerization
rates.
Figure 3
Plot of ln Keq versus 1/T for 2 (R = Br, black; R = OMe, blue; R = NO2, red), using Keq values determined via
kinetic fits (COPASI, circles) and via fits of catalyst peak chemical
shifts in NMR spectra (NMR, squares).
Plot of lnKeq versus 1/T for 2 (R = Br, black; R = OMe, blue; R = NO2, red), using Keq values determined via
kinetic fits (COPASI, circles) and via fits of catalyst peak chemical
shifts in NMR spectra (NMR, squares).The temperature dependences of the rate constants k2 for the polymerizations of CL by 2 (this
work, circles) and 1 (squares)[6] are shown in Figure , and activation parameters determined from linear fits to the Eyring
equation are given in Table . It is readily apparent from the Eyring plots in Figure and the derived
ΔG⧧298 values
that the polymerization rate constants are greater for 2 than for 1. From the activation parameters, we calculate
that the fastest catalyst 2 (R = NO2) and
the slowest catalyst 1 (R = OMe) have k2 values that differ by factors of ∼(1–5)
× 103 (350–273 K). Hammett plots of log k2 versus σp for 2 are linear at all temperatures with similar positive slopes (Figure ), yielding an average
ρ value of +1.2(1) that is similar to that reported previously
for 1 (+1.4(1)).[6] Thus, the
sensitivities of the rate constants to the electronic influences of
the ligand substituents R are similar for the two catalyst systems.
Figure 4
Eyring
plots of ln(k2/T) versus
1/T for 1 (squares, dashed
lines) and 2 (circles, solid lines) for R = OMe (black),
Br (blue), and NO2 (red).
Table 2
Activation Parameters (k2) for the Polymerization of CL
catalyst
R
ΔH⧧a
ΔS⧧b
ΔG⧧a (298 K)
2c
OMe
9.1 ± 0.3
–32 ± 1
18.6 ± 0.4
2c
Br
10.4 ± 0.4
–24 ± 1
17.6 ± 0.5
2c
NO2
10.0 ± 0.9
–23 ± 3
17 ± 1
1d
OMe
13.5 ± 0.5
–27 ± 2
21.5 ± 0.8
1d
Br
11.5 ± 0.3
–30 ± 2
20.4 ± 0.7
1d
NO2
10.8 ± 0.4
–27 ± 2
18.8 ± 0.7
In kcal mol–1.
In cal
mol–1 K–1.
Determined from the linear fits
in Figure using the
Eyring equation.
Reference (6).
Figure 5
Hammett plots of log(k2) versus σp for the polymerization of CL by 2 at the indicated
temperatures.
Eyring
plots of ln(k2/T) versus
1/T for 1 (squares, dashed
lines) and 2 (cirpan> class="Chemical">cles, solid lines) for R = OMe (black),
Br (blue), and NO2 (red).In kn class="Chemical">cn class="Chemical">al mol–1.
Inn class="Chemical">cn class="Chemical">al
mol–1 K–1.
Determined from the linear n class="Disease">fits
in Figure using the
Eyring equationpan>.
Referenn class="Chemical">ce (6).
Hammett plots of log(k2) versus σp for the polymerizationpan> of pan> class="Chemical">CL by 2 at the indicated
temperatures.
Theoretical Modeling
To gain additional inpan>sight inpan>to
the observed catalytic activities, and in particular to better understand
the rate accelerations observed relative to the first-generation catalyst 1, we undertook density functionalcharacterization of reaction
pathways associated with catalyst 2 (see the Experimental Section for full computational details).
For computational simplicity, we modeled the alkoxide in the precatalyst
as MeO instead of iPrO, and to differentiate this
we refer to the MeO-substituted precatalyst structures as 1′ and 2′ below.
Conformational Flexibility
of Catalyst
In comparisonpan>
to 1′ with its two-carbon backbone linker, a number
of alternative chair and twist-boat conformations of the three-carbon
backbone are available to the ligand in 2′. In
particular, for the precatalyst carrying no para substituents on the
aromatic rings, we identified four different conformations (three
twist-boats and one chair), spanning a range in electronic energy
of 2.2 kcal/mol. Both the lowest and highest energy conformations
were found to be twist boats (the lowest is shown in Figure ), with the chair conformation
being intermediate in energy. A Boltzmann average over all four conformers
leads to a reduction in the free energy of the population of free
catalyst structures of only 0.1 kcal/mol: i.e., the global minimum
sits reasonably far below the other conformers in energy. We applied
the same 0.1 kcal/mol correction to the energies of the global minimum
twist boats in the para-substituted cases, assuming the influence
of para substitution on the conformational energetics to be minimal.
Figure 6
DFT predicted
lowest-energy structures for p-H-substituted 1′ and 2′ (above) and for their
corresponding transition-state structures for ring opening of CL (below).
H atoms are omitted for clarity.
DFT predicted
lowest-energy strupan> class="Chemical">ctures for p-H-substituted 1′ and 2′ (above) and for their
corresponding transition-state structures for ring opening of CL (below).
H atoms are omitted for clarity.
Catalysis
To characterize the mechanism of ROP with
the catalyst 2′, we carried out an exhaustive
search over all of the pathways associated with the various possible
catalyst/CL stereochemical orientations analogous to a prior study
involving catalyst 1′.[6] We observed again that one particular orientation, which was referred
to as “pathway 6” in our prior work,[6] led to CL ring opening through a transition-state (TS)
structure having the lowest activation free energy of all those surveyed
(Figure ). Indeed,
for the model system lacking para substituents, ΔG⧧ along pathway 6 was predicted to be at least
4 kcal/mol lower than any other pathway investigated, suggesting that
Boltzmann averaging over alternative stereochemistries is not required
for the modeling of the transition state. The TS structures in 1′ and 2′ are overall quite similar:
in each case, there is roughly octahedral coordination about Al with
an O–Al–O angle involving the alkoxide and carbonyl
oxygen atoms of about 75° and with both Al–O bond lengths
being 1.92 ± 0.01 Å. Full details of all bond lengths and
angles are provided in Figure S20 in the
Supporting Information, and additional analysis of the similarity
of TS structure geometries across a wider range of Al-based catalysts
is provided below in the Discussion.
Rate
Acceleration in Catalyst 2′
Predicted
free energies of activation for the reaction of catalyst 2′ with CL are provided in Table for the cases of p-OMe, p-Br, and p-NO2 substitution
at 298 K. Also included in Table are the analogous predictions previously reported
for catalyst 1′. Experimentally, a rate acceleration
of about 3 orders of magnitude is observed on going from 1 to 2 with identical para substituents, which corresponds
to a lowering of the activation free energy by about 4 kcal/mol at
298 K. As can be seen in Table , we predict reductions in activation free energies of 2.7,
2.9, and 3.7 kcal/mol for the p-MeO-, p-Br-, and p-NO2-substituted cases of 2′, respectively. These reductions (in what is effectively Keq*k2, since we
compute activation free energies relative to infinitely separated
reactants) are in generally good agreement with experimental observations
(cf. Table , noting
that variations in k2 have a larger influence
on relative rates than Keq; cf. Table ), although the acceleration
predicted for the p-NO2-substituted system
is somewhat larger. Focusing only on para substitution effects in 2 itself, experiment shows an acceleration relative to R =
MeO of −1.1 and −1.5 kcal/mol for R = Br and R = NO2, respectively. Theory predicts values of −1.5 and
−3.8 kcal/mol for 2′, again in reasonably
good agreement with experiment, albeit with some overestimation of
the rate acceleration afforded for the p-NO2case.
Table 3
Predicted 298 K Activation Free Energies
(kcal/mol) for Reaction of 1′ and 2′ with CL
para substituent
1′
2′
MeO
12.4
9.7
Br
11.1
8.2
NO2
9.6
5.9
Saturation
Kinetics
Experimental measurements inpan>dicate
that there is a modest equilibrium constant for the complexation with
CL of all three para-substituted derivatives of 2 examined
here. This is similar to the situation previously described for 1,[6] where DFT identified many local
minimum structures corresponding to van der Waals complexes between
CL and 1′. In that case, the lowest energy such
structure involved CL binding trans to the methoxide ligand, generating
a structure that is necessarily incapable of ring opening; thus, the
saturation kinetics observed were interpreted as substrate inhibition.
In the case of 2′, on the other hand, no such
trans complexes with CL proved to be especially favorable—while
van der Waals structures having CL on the side of 2 opposite
MeO could be located, they were no lower in energy than alternative
structures with CL on the same face as MeO, likely owing to stericconstraints diminishing favorable interactions between Al and the
carbonyl oxygen of CL (the shortest distance found between these two
atoms for a trans complex was 2.26 Å; see Figure ). However, saturation kinetics is predicted
for reactions having a pre-equilibrium irrespective of whether that
equilibrium leads to unreactive or reactive structures, and in this
respect the kinetics of 2′ in comparison to those
of 1′ are rationalized as deriving from a still-sizable
population of prereactive complexes.
Figure 7
Representative M06-L same-face and opposite-face
van der Waals
complexes of CL with 1′ and 2′.
In the case of 1′, the trans complex is lower
in free energy than the same-face structure by 8.4 kcal/mol. In the
case of 2′, the trans complex is higher in free
energy by 7.0 kcal/mol.
Representative M06-L same-face and opposite-face
van der Waals
complexes of CL with 1′ and 2′.
In the case of 1′, the trans complex is lower
in free energy than the same-face structure by 8.4 kcal/mol. In the
case of 2′, the trans complex is higher in free
energy by 7.0 kcal/mol.
Discussion
In delving into the detailed
effects of the change in ligand linker
from two carbons to three on the rate of CL polymerization by 1 and 2, respectively, we used a combination
of experimental and theoretical approaches to compare the structures
of the reactants, their saturation kinetics behavior as a function
of para substituent and temperature, and the nature of relevant ring-opening
transition states. X-ray crystallography and theory confirmed that
the longer linker in 2 results in a coordination geometry
closer to trigonal bipyramidal (τ = 0.84) in comparison to 1 (τ = 0.52). This structural effect had been noted
previously but discounted as a rationale for different LA polymerization
rates because rate accelerations did not occur with (salen)AlMe precatalysts
with similar τ values but with rigid rather than flexible linkers.[4] As seen for 1, we observed saturation
behavior in the kinetics of CL polymerization by 2, and
the combined evidence from kinetic fits and NMR data for 2 in the presence of γ-butyrolactone (BL), which does not polymerize
under the conditions explored, supports assignment of Keq to equilibrium monomer binding. For 1,
theory suggests that the lowest energy complex-binding monomer is
unable to proceed to polymerization (owing to trans binding) and is
thus inhibitory. For 2, theory predicts that trans binding
is not competitive with productive binding, and Keq instead is a measure of alternative prereactive
bound complexes. Nonetheless, the relevant kinetic behavior is the
same in these two situations: i.e., saturation kinetics is predicted
and observed. Importantly, we conclude that differences in CL polymerization
rates between 1 and 2 and among systems
with different para substituents R do not arise from differences in Keq because these values do not vary significantly
as a function of linker length (1 vs 2),
R (OMe, Br, or NO2), or temperature. Instead, the overall
rate differences arise from variations in k2. While the sensitivity of k2 to the
electron-withdrawing ability of substituent R is similar for systems 1 and 2 (Hammett ρ values of +1.4(1) and
+1.2(1), respectively), and this supports similar mechanisms for CL
polymerization by these two systems, at parity of R the rates of CL
polymerization by 2 are significantly faster.To
rationalize the rate acceleration observed with 2 in
comparison to 1, we focused more closely on the
geometric details associated with the ring-opening TS structures in
each instance.[11] As noted above and quantified
in Figure S20 in the Supporting Information,
for the two different TS structures the geometry about the catalyticAlcenter is predicted to be quite similar: the mean unsigned deviation
over all Al–X bond lengths is 0.01 Å and the mean unsigned
deviation over all (cis) X–Al–Y angles is 3.0°.
This observation suggests that each catalyst is able to achieve a
common geometry that is optimal for reducing the free energy of activation
of ring opening. It also raises the question, then, of what is required
in terms of distortion energy relative to the resting precatalyst
structure to arrive at this optimal geometry. Also
shown in Figure S20 are corresponding metrics
for the resting precatalysts 1′ and 2′, and it is clear that there are more substantial geometric
differences between these alkoxidecomplexes than there are between
the corresponding TS structures. The differences are primarily associated
with the degree of square-pyramidal vs trigonal-bipyramidalcharacter
imposed by the different ligands and are well captured by the different
τ values reported above (experimental and calculated).To address the question of the influence of required distortionpan>
from precatalyst to TS structure in more quantitative detail, for
both 1′ and 2′ we removed
the reacting partners and the MeO units from the optimized TS structures,
and we carried out single-point calculations on the resulting cationicconformers of the catalyst frameworks to determine their differences
in energy relative to the precatalyst from which the MeO unit had
been removed. This calculation thereby provides an approximation to
the distortion energy of the aluminum–ligand framework that
is associated with adoption of a geometry well suited to stabilize
the optimal TS structure. The framework of 1 requires
18.3 kcal/mol to distort from the precatalyst structure to the TS
structure, while the framework of 2 has a corresponding
distortion energy of only 6.8 kcal/mol. Clearly, then, the “resting”
framework of 2 is much closer to the optimalcatalytic
geometry than is that of 1. This computed difference
is considerably larger than the experimentally observed rate acceleration,
as might be expected insofar as differentialalkoxide interactions
with the catalyst resting geometries would be expected to act in some
way to reduce differential strain. Nevertheless, the striking difference
that is computed suggests that enhanced catalytic activity can be
engineered through the design of catalysts whose precomplexed structures
are already geometrically similar to the octahedral TS structures
determined from DFT to have the lowest activation free energies for
ring-opening polymerization.To assess further the relative
utility of this framework-strain
analysis for the prediction of catalyst activity, we examined another
six related ROP catalysts reported previously (structures in Figure ).[4] In each instance, we computed precatalyst and TS structures
analogous to those for 1′ and 2′.
In all eight TS structures, there was a remarkable uniformity in the
12 unique cis valence bond angles about Al. For example, for the O–Al–O
valence angle between the alkoxide and caprolactonecarbonyl oxygen
atoms, the average and standard deviation were found to be 74.8 ±
0.7° over all eight structures. The largest angular standard
deviation, 4.7°, was associated with the N–Al–N
valence angle, which is unsurprising given the variation in bridge
lengths in the various catalysts; for all remaining angles, the standard
deviations ranged from 0.6 to 2.3°.
Figure 8
Relationship between
ln kapp for a
series of ROP catalysts described by Gibson et al.[4] (but lacking the t-Bu groups para to the
phenolate donors) and computed activation free energies (black circles)
and framework distortion energies (blue squares) for corresponding
reactant and TS structures. The best-fit line to the activation free
energies has the Pearson correlation coefficient R = 0.947. The best-fit line to the framework distortion energies
(not shown) has R = 0.852.
Relationship between
ln kapp for a
series of ROPcatalysts described by Gibson et al.[4] (but lacking the t-Bu groups para to the
phenolate donors) and computed activation free energies (black circles)
and framework distortion energies (blue squares) for corresponding
reactant and TS structures. The best-fit line to the activation free
energies has the Pearson correlation coefficient R = 0.947. The best-fit line to the framework distortion energies
(not shown) has R = 0.852.This similarity in TS structures prompted us to explore further
the utility of our distortionpan> energy hypothesis. Thus, we removed
the same alkoxide and CL components and computed distortion energies
for the six additionalcompounds[4] analogous
to those already described for 1′ and 2′ (Figure ). These distortion energies, as well as the computed activation
free energies, are plotted vs the natural logarithm of the previously
reported[4] lactide ROP rate constants (for
catalysts that contain t-Bu groups para to the phenolate
donor) determined under equivalent conditions in Figure (together with the calculated
data for 1′ and 2′ already
described above).There is a good correlationpan> between the computed
activation free
energies and the observed ln kapp values,
providing further validation of the modeling protocol. Interestingly,
the correlation of the rate constant data with the framework distortion
energies is also fairly good. Indeed, if the data
point for catalyst G is removed, the Pearson correlation
coefficient for the latter correlation is predicted to be identical
with that for the activation free energies (R = 0.947).
For this outlier, a significantly lower distortion energy is predicted
than for catalysts A and B, even though
all three are found experimentally to catalyze ROP at essentially
identical rates. This suggests that there is an interaction in the
actual TS structure for G that destabilizes the structure
beyond distortion of the framework. Indeed, if one examines a space-filling
model of the TS structure for polymerization of CL by G (Figure ) it is
apparent that one phenyl ring associated with the backbone bridge
of the ligand is thrust into the space that the reacting alkoxide
and CL moieties (not present in the framework distortion calculation)
occupy and that there is a stericclash between a CL hydrogen and
that ring. Failure to account for such interactions is a drawback
of the simple framework distortion energy metric.
Figure 9
Optimized M06-L structure
for the TS for ROP of CL by compound G drawn as a space-filling
model (using CPK van der Waals
radii). The CL ring carbons are highlighted in black, with the key
destabilizing interaction of a CL hydrogen with the ligand aromatic
ring indicated by an arrow.
Optimized M06-L structure
for the TS for ROP of CL by compound G drawn as a space-filling
model (using CPK van der Waals
radii). The CL ring carbons are highlighted in black, with the key
destabilizing interaction of a CL hydrogen with the ligand aromatic
ring indicated by an arrow.Nevertheless, in addition to being of interest from a fundamental
mechanistic standpoint, the relationship between framework distortion
energy and apparent rate constants we have discovered suggests a strategy
for in silico catalyst design. To the extent that
all of the various TS structures are geometrically similar to one
another about aluminum, one could use the “average”
set of TS bond angles described above for framework distortion calculations
with arbitrary ligands without the added expense of actually finding
a true TS structure. That is, one could compute a resting catalyst
structure for a given ligand of choice, remove the alkoxide, and then
compute the energy to distort the resulting structure to a pseudo-TS
structure having the fixed “average” angles about Al,
but all other degrees of freedom relaxed. While one might expect correlation
with the proper free energies of activation to degrade with such limited
relaxation, certainly ligands predicted to lead to very small framework
distortion energies by this rapid computational screening technique
would be higher priorities for initial experimental discovery efforts.
Conclusions
With the aim of understanding how linker length influences the
ROP of lactones by single-site (salen)AlOR catalysts, we evaluated
the kinetics for ROP of CL by 2 under conditions that
enabled determination of Keq and k2 (eq ) as a function of temperature and electron-withdrawing capabilities
of remote substituents. Comparison of these and derived thermodynamic
parameters for ROP by 2 to those previously reported
for 1, which features a shorter linker, revealed similar
dependences of Keq and k2 on the substituents (little variation of Keq, similar Hammett parameters for k2 of +1.4(1) and +1.2(1) for 1 and 2, respectively). However, an overall significant increase in rate
(k2 values) was observed for 2 relative to 1. Theoreticalcalculations accurately
replicated the different reactant geometries for analogues 1′ and 2′ but showed that the ROP transition
state structures were very similar, thus raising the possibility that
the differing activation energies for the two catalysts arise from
differences in the energies required to distort the ligand framework
to adopt the requisite TS geometries. Support for this notion was
obtained by approximating the energy cost of distorting the ligand
framework from its reactant geometry to that of the TS for 1′ and 2′ through single-point calculations.
Extension of this method to a previously reported series of catalysts
with varying ligand linkers yielded a good correlation between the
distortion energy and the rate of ROP of LA. We suggest that this
relatively simple method for
evaluating the ligand framework distortion energy may have even broader
utility for predicting the reactivity of metal alkoxidecatalysts
for cyclic ester ROP reactions and is therefore a potentially useful
tool for future catalyst design.
Experimental
Section
Materials and Methods. General Considerations
Experiments
were conpan>ducted under an inert atmosphere using a drybox or Schlenk
line unless otherwise indicated. Reagents were purchased commercially
and used without further purification unless otherwise stated. CL
was purified by distillation from CaH2 and stored under
N2. Deuterated solvents were dried over CaH2 or sodium metal, distilled under vacuum, and stored under N2. Protiated solvents were degassed and passed through a solvent
purification system (Glass Contour, Laguna, CA) prior to use. 1H and 13C NMR spectra were recorded on a Bruker
Avance III HD 500 MHz spectrometer equipped with a Prodigy TCIcryoprobe.
Chemical shifts for 1H and 13C NMR spectra were
referenced to residualprotium in the deuterated solvent and deuterated
solvent itself, respectively. 1H NMR spectra for the kinetic
runs were recorded on a Bruker Avance III 500 MHz spectrometer equipped
with either a BBFO SmartProbe or a TBO triple-resonance PFG probe. 27Al NMR spectra were recorded on a Bruker Avance III 500 MHz
spectrometer equipped with a TBO triple-resonance PFG probe. Chemical
shifts for 27Al NMR spectra were externally referenced
to aluminum tris(acetylacetonate) in toluene-d8. 2-Hydroxy-3-(tert-butyl)-5-methoxybenzaldehyde,[12] 2-hydroxy-3-(tert-butyl)-5-bromobenzaldehyde,[13] and 2-hydroxy-3-(tert-butyl)-5-nitrobenzaldehyde[14] were synthesized according to literature procedures.
Elemental analyses were performed by Robertson Microlit Laboratory
(Ledgewood, NJ).
Syntheses of Proligands H2LOMe, H2LBr, and H2LNO2
In an oven-dried round-bottom flask equipped with a reflux
conpan>denser,
the salicylaldehyde (H2LOMe, 1.583 g, 7.6 mmol;
H2LBr, 1.311 g, 5.1 mmol; H2LNO2, 1.473 g, 6.6 mmol) was dissolved in absolute ethanol to
give an approximate 0.64 M concentration. To this mixture 2,2-dimethyl-1,3-propanediamine
(H2LOMe, 0.388 g, 3.8 mmol; H2LBr, 0.266 g, 2.6 mmol; H2LNO2, 0.337
g, 3.3 mmol) was added with stirring, and the solution was heated
to reflux for 2 h. The reaction mixture was cooled to ambient temperature
and left to sit overnight at −30 °C, yielding a precipitate.
The crude precipitate was isolated by vacuum filtration and washed
with hexanes (40 mL) before recrystallization from minimaldichloromethane
(approximately 5 mL) layered with an equal volume of hexanes at −30
°C overnight. The purified product was isolated by vacuum filtration,
dried overnight in a vacuum oven at ambient temperature, and stored
under N2 in a drybox as a bright yellow, crystalline solid.
Yields: H2LOMe, 0.197 g, (70%); H2LBr, 1.355 g (91%); H2LNO2, 1.246
g, (73%).H2LOMe: pan> class="Chemical">1H NMR (500
MHz, toluene-d8) δ 13.82 (s, 2H,
OH), 7.78 (s, 2H, CH=N),
7.16 (d, J = 3.0 Hz, 2H, ArH), 6.41
(d, J = 3.0 Hz, 2H, ArH), 3.49 (s,
6H, ArOCH3), 3.10 (s, 4H, NCH2C(CH3)2CH2N), 1.57 (s, 18H, Ar-), 0.89 (s, 6H, NCH2C(CH3)2CH2N); 13C NMR (125 MHz, toluene-d8) δ 166.76, 155.52, 152.06, 139.20, 118.66,
118.56, 111.97, 68.30, 55.25, 35.98, 35.34, 29.57, 24.45. Anal. Calcd
for C29H42N2O4: C, 72.17;
H, 8.77; N, 5.80. Found: C, 72.09; H, 8.69; N, 5.73.H2LBr: pan> class="Chemical">1H NMR (500 MHz, toluene-d8) δ 14.21 (s, 2H, OH), 7.51 (d, J = 2.3 Hz, 2H, ArH), 7.47 (s, 2H, CH=N), 6.94 (d, J = 2.3 Hz, 2H, ArH), 2.98 (s, 4H, NCH2C(CH3)2CH2N), 1.43 (s, 18H,
Ar-), 0.79 (s, 6H, NCH2C(CH3)2CH2N); 13C NMR (125 MHz, toluene-d8) δ
165.80, 160.08, 140.47, 132.78, 132.23,
120.43, 110.44, 68.06, 35.90, 35.30, 29.25, 24.18. Anal. Calcd for
C27H36Br2N2O2: C, 55.87; H, 6.25; N, 4.83. Found: C, 55.90; H, 6.28; N, 4.83.H2LNO2: pan> class="Chemical">1H NMR (500 MHz, toluene-d8) δ 15.27 (s, 2H, OH), 8.29 (d, J = 3.0 Hz, 2H, ArH), 7.79 (d, J = 3.0 Hz, 2H, ArH), 7.38 (s, 2H, CH=N), 2.93 (s, 4H, NCH2C(CH3)2CH2N), 1.42 (s, 18H, Ar-), 0.74 (s, 6H, NCH2C(CH3)2CH2N); 13C NMR (125 MHz, toluene-d8) δ 167.16, 166.14, 139.61, 139.53, 126.40,
125.21, 117.34, 66.98, 35.82, 35.36, 28.98, 23.88. Anal. Calcd for
C27H36N4O6: C, 63.26;
H, 7.08; N, 10.93. Found: C, 62.64; H, 6.91; N, 10.79.
Syntheses of
Complexes 2
In a glovebox,
in an oven-dried 25 mL screw cap bomb flask equipped with a stirbar,
equimolar amounts of proligand (H2LOMe, 0.241
g, 0.5 mmol; H2LBr, 0.290 g, 0.5 mmol; H2LNO2, 0.256 g, 0.5 mmol) and aluminum tris(isopropoxide)
(0.010 g, 0.5 mmol) were dissolved in toluene (3 mL). The sealed vessel
was removed from the glovebox and heated to 90 °C, and the mixture
was stirred at this temperature for 3 days. After being cooled to
ambient temperature, the reaction mixture was returned to the glovebox
and solvent was removed in vacuo. The crude solid was purified by
trituration with pentane (5 mL) and then recrystallized from minimaltoluene (approximately 4 mL) layered with an equal volume of pentane
at −40 °C overnight. The purified product was isolated
by vacuum filtration, dried overnight on a vacuum line, and stored
under N2 in the glovebox at −40 °C as a bright
yellow (R = OMe), yellow (R = Br), or light brown (R = NO2) solid. Yields: R = OMe, 0.230 g; (81%); R = Br, 0.184 g (72%);
R = NO2, 0.263 g, (90%).2 (R = OMe): 1H NMR (500 MHz, pan> class="Chemical">toluene-d8) δ
7.48 (s, 2H, CH=N), 7.36 (d, J = 3.2 Hz, 2H, ArH), 6.30 (d, J = 3.2 Hz, 2H, ArH), 4.13 (septet, J = 5.2 Hz, 1H, OCH(CH3)2),
3.50 (s, 6H, ArOCH3), 3.38 (d, J = 12.1 Hz, 2H, NCH′HC(CH3)2CH′HN), 2.73 (d, J = 12.1 Hz, 2H, NCH′HC(CH3)2CH′HN), 1.72 (s, 18H, Ar-), 1.17 (d, 5.2 Hz, 6H, OCH(CH3)2), 0.80 (s, 3H, NCH2C(CH3)′(CH3)CH2N),
0.54 (s, 3H, NCH2C(CH3)′(CH3)CH2N); 13C NMR (125 MHz, toluene-d8) δ 169.35, 161.44, 150.33, 143.24, 123.17,
118.37, 111.30, 68.09, 62.95, 55.25, 35.95, 35.65, 30.17, 29.98, 25.62,
25.21; 27Al NMR (130 MHz, toluene-d8) δ 35.33. Anal. Calcd for C32H47AlN2O5: C, 67.82; H, 8.36; N, 4.94. Found:
C, 67.81; H, 8.32; N, 4.89.2 (R = Br): pan> class="Chemical">1H NMR (500 MHz, toluene-d8) δ 7.63
(d, J = 2.6
Hz, 2H, ArH), 7.17 (s, 2H, CH=N),
6.89 (d, J = 2.6 Hz, 2H, ArH), 3.97
(septet, J = 5.9 Hz, 1H, OCH(CH3)2), 3.25 (d, J = 12.1 Hz, 2H,
NCH′HC(CH3)2CH’HN), 2.59 (d, J = 12.1 Hz, 2H, NCH′HC(CH3)2CH’HN), 1.56 (s, 18H, Ar-), 1.08
(d, 6.0 Hz, 6H, OCH(CH3)2),
0.72 (s, 3H, NCH2C(CH3)′(CH3)CH2N), 0.47 (s, 3H, NCH2C(CH3)′(CH3)CH2N); 13C NMR (125 MHz, toluene-d8) δ
168.85, 164.63, 144.34, 135.59, 133.47, 120.92, 108.07, 67.89, 63.10,
35.91, 35.50, 29.66, 28.20, 25.55, 25.07; 27Al NMR (130
MHz, toluene-d8) δ 33.63. Anal.
Calcd for C30H41AlBr2N2O3: C, 54.23; H, 6.22; N, 4.22. Found: C, 54.29; H, 6.27;
N, 4.22.2 (R = NO2): pan> class="Chemical">1H
NMR (500 MHz,
toluene-d8) δ 8.43 (d, J = 3.0 Hz, 2H, ArH), 7.81 (d, J = 3.0 Hz, 2H, ArH), 7.14 (s, 2H, CH=N), 3.85 (septet, J = 6.0 Hz, 1H, OCH(CH3)2), 3.21 (d, J = 12.1 Hz, 2H, NCH′HC(CH3)2CH′HN), 2.59 (d, J = 12.1 Hz, 2H, NCH′HC(CH3)2CH′HN), 1.53 (s, 18H, Ar-), 1.04 (d, 6.0 Hz, 6H, OCH(CH3)2), 0.71 (s, 3H, NCH2C(CH3)′(CH3)CH2N),
0.50 (s, 3H, NCH2C(CH3)′(CH3)CH2N); 13C NMR (125 MHz, toluene-d8) δ 169.70, 169.48, 142.80, 138.23, 129.18,
127.39, 118.22, 67.80, 63.28, 35.91, 35.42, 29.41, 27.98, 25.56, 25.01; 27Al NMR (130 MHz, toluene-d8)
δ 33.40. Anal. Calcd for C30H41AlN4O7: C, 60.39; H, 6.93; N, 9.39. Found: C, 60.15;
H, 6.55; N, 8.71.
Kinetics Measurements and Analysis
A procedure for
a typical kinetic run is as follows. In a nitrogen-filled glovebox,
an NMR tube dried in a vacuum oven at ambient temperature was charged
with 500 μL of a stock solution of catalyst in toluene-d8 (0.0098 M) and 10 μL of the internal
standard 1,4-bis(trimethylsilyl)benzene in toluene-d8 (0.28 M). The NMR tube was capped with a septum and
wrapped with black electric tape. A gastight syringe was loaded with
190 μL of a stock solution of ε-caprolactone (CL) in toluene-d8 (7.4 M) and capped with a septum to prevent
air contamination during the experiment setup. The target concentrations
for the NMR reaction were 0.007 M catalyst, 0.004 M internal standard,
and 2.0 M CL. The NMR tube and loaded syringe were taken out of the
glovebox and brought to the spectrometer. A pure methanol standard
was used to calibrate the temperature of the spectrometer (500 MHz
Bruker Avance III). In order to accurately determine catalyst concentration,
a relaxation relay of 10 s was used to ensure complete relaxation
for quantification integrations. A 1H NMR spectrum of the
catalyst and internal standard was measured, and then the NMR tube
was ejected from the spectrometer and CL was injected through the
septum. The NMR tube was aggressively shaken and inverted before being
reinserted into the spectrometer. The time between the CL injection
and the start of 1H NMR data acquisition was recorded in
minutes. An array of spectra was taken every 48 s (four scans) for
most kinetic runs except for the runs with R = NO2 (288,
293 K) and R = Br (273 K), where a spectrum was taken every 24 s (two
scans) and 96 s (eight scans), respectively. The acquisition parameters
were as follows: relaxation delay 10 s, 30° pulse width 3.9,
gain of 10 or 16 depending on the NMR probe used, and acquisition
time 2 s. Samples were spun, and autoshim was employed to allow for
shimming during kinetic runs. The arrayed experiment was allowed to
proceed until the disappearance of the CL peaks, indicating complete
polymerization. For R = NO2 (273 K), the kinetic runs were
halted prior to the complete disappearance of CL peaks due to the
loss of shims by the spectrometer. For each catalyst, triplicate reactions
were performed at four different temperatures. The obtained arrayed
NMR data were phased and baseline corrected before being integrated,
using Mestrenova (http://mestrelab.com/). Using the peak
integrations, absolute concentrations of all species as a function
of time were calculated relative to the concentration of internal
standard. The reaction time was calculated in seconds from the known
duration of each spectrum and the time between the CL injection and
the start of the 1H NMR data acquisition. The concentration
vs time data were entered into the program COPASI and fit to eq S1 in the Supporting Information to obtain KM and Vmax values.
The reaction rates were calculated using eq S1 and plotted as a function of [CL]; full details of the fits and
results are provided as Supporting Information. All linear and nonlinear curve fits were performed using Origin
9.1 SR2 software (OriginLab, Northampton, MA).
Binding Study with γ-Butyrolactone
In a nitrogen-filled
glovebox, six NMR tubes dried inpan> a vacuum oven at ambient temperature
were each charged with 500 μL of a stock solution of catalyst 2 (R = OMe, Br, NO2) in toluene-d8 (0.0074–0.0078 M). Different amounts (10–190
μL) of a 7.38 M stock solution of γ-butyrolactone (BL)
were added to each tube. Toluene-d8 was
added to some of the tubes to achieve an overall volume of 690 μL.
The NMR tubes were capped and shaken. The finalconcentrations for
BL were 0.11, 0.25, 0.50, 0.75, 1.0, 1.5, and 2.0 M, while the catalyst
concentration ranged from 0.005 to 0.007 M. The reactions were monitored
at 293 K by 1H NMR spectroscopy (500 MHz Bruker Avance
III) using the same parameters as the kinetic runs. This experiment
was run in triplicate for each catalyst, and the spectra were processed
using Mestrenova and analyzed by NMR peak analysis using Origin 9.1
SR2 software.
Density Functional Calculations
Molecular structures
were optimized at the M06-L level[15] of
density functional theory employing the 6-31+G(d,p) basis set.[16] The nature of all stationary points was confirmed
by computation of analytic vibrational frequencies, which were also
employed to compute vibrationalcontributions to the molecular partition
function, replacing all vibrations below 50 cm–1 with values of 50 cm–1 in order to correct for
the well-known deficiency of the quantum mechanical harmonic oscillator
approximation when applied to very low frequency motions.[17] Improved free energies were computed by summing
thermalcontributions from this lower level of theory with single-point
electronic energies computed at the M06-2X level[18] of density functional theory employing the 6-311+G(d,p)
basis set.[16] Solvation effects for toluene
as solvent were included during single-point energy calculations employing
the SMD solvation model.[19]There
are a very large number of conpan>formationpan>al and configurational possibilities
associated with the binding of the catalyst with caprolactone. In
this work, we consider a limited number of structures, primarily to
compare with prior work involving a different, but analogous, catalyst.
A more exhaustive survey of the various possible complexes and reaction
paths undertaken for an analogue of the catalyst in this work from
which alkyl groups substituting the ligand were removed suggests that
the specific structures reported in this study are indeed relevant
as low-energy stationary points, and results from that work on the
reduced catalyst are summarized in the Supporting Information.Cpan> class="Chemical">alculations were carried out with the Gaussian
09 suite of electronic
structure programs.[20] CM5 charges were
computed using the auxiliary CM5PAC program.[21]
Authors: Aleksandr V Marenich; Steven V Jerome; Christopher J Cramer; Donald G Truhlar Journal: J Chem Theory Comput Date: 2012-02-03 Impact factor: 6.006
Authors: Andreas Sauer; Andreas Kapelski; Christophe Fliedel; Samuel Dagorne; Moshe Kol; Jun Okuda Journal: Dalton Trans Date: 2013-04-04 Impact factor: 4.390
Authors: Maria O Miranda; Yvonne DePorre; Hugo Vazquez-Lima; Michelle A Johnson; Daniel J Marell; Christopher J Cramer; William B Tolman Journal: Inorg Chem Date: 2013-11-12 Impact factor: 5.165
Authors: Peter T Altenbuchner; Alexander Kronast; Stefan Kissling; Sergei I Vagin; Eberhardt Herdtweck; Alexander Pöthig; Peter Deglmann; Robert Loos; Bernhard Rieger Journal: Chemistry Date: 2015-08-11 Impact factor: 5.236