Manuel A Ortuño1,2, Marcos Rellán-Piñeiro1, Rafael Luque3,4. 1. Centro Singular de Investigación en Química Biolóxica e Materiais Moleculares (CIQUS), Universidade de Santiago de Compostela, 15782 Santiago de Compostela, Spain. 2. Institute of Chemical Research of Catalonia, ICIQ, and the Barcelona Institute of Science and Technology, BIST, Av. Països Catalans 16, 43007 Tarragona, Spain. 3. Departamento de Química Orgánica, Universidad de Córdoba, Campus de Rabanales, Edificio Marie Curie, E-14014 Córdoba, Spain. 4. Peoples Friendship University of Russia (RUDN University), 6 Miklukho Maklaya str., 117198 Moscow, Russian Federation.
Abstract
Metal-organic frameworks (MOFs) are gaining importance in the field of biomass conversion and valorization due to their porosity, well-defined active sites, and broad tunability. But for a proper catalyst design, we first need detailed insight of the system at the atomic level. Herein, we present the reaction mechanism of methyl levulinate to γ-valerolactone on Zr-based UiO-66 by means of periodic density functional theory (DFT). We demonstrate the role of Zr-based nodes in the catalytic transfer hydrogenation (CTH) and cyclization steps. From there, we perform a computational screening to reveal key catalyst modifications to improve the process, such as node doping and linker exchange.
Metal-organic frameworks (MOFs) are gaining importance in the field of biomass conversion and valorization due to their porosity, well-defined active sites, and broad tunability. But for a proper catalyst design, we first need detailed insight of the system at the atomic level. Herein, we present the reaction mechanism of methyl levulinate to γ-valerolactone on Zr-based UiO-66 by means of periodic density functional theory (DFT). We demonstrate the role of Zr-based nodes in the catalytic transfer hydrogenation (CTH) and cyclization steps. From there, we perform a computational screening to reveal key catalyst modifications to improve the process, such as node doping and linker exchange.
The current scenario
dominated by crude oil and natural gas is
no longer feasible, and our society needs to devise new sustainable
ways to fulfill the feedstock demand of an increasing world population.
We must abandon the limited supply of fossil fuels and turn to renewable
resources such as biomass. Indeed, the upgrading of readily available
lignin and (hemi)cellulose to high-value products is already leading
the way toward a sustainable economy.[1] In
that regard, several biobased molecules have been identified as promising
building blocks.[2] Among them, we here target
the transformation of methyl levulinate (ML), readily available from
lignocellulose, into γ-valerolactone (GVL), a platform molecule
used as solvent, fuel, and feedstock for high-value chemicals.[3]This reaction is typically catalyzed in
the heterogeneous phase
and entails a direct hydrogenation via precious metals.[4] Alternatively, amphoteric catalysts, such as
those based on Zr, can promote a catalytic transfer hydrogenation
(CTH) using alcohols as a hydrogen source (Scheme ),[5,6] thus avoiding the need
of hydrogen gas and expensive metals. Zr-based oxides can indeed promote
this process,[7,8] but the variety of active sites
on the catalyst surface may become detrimental due to undesired side
reactions.
Scheme 1
Conversion of Methyl Levulinate (ML) into γ-Valerolactone
(GVL)
via Catalytic Transfer Hydrogenation
To better control the design of catalytic sites, we turn to metal–organic
frameworks (MOFs), a family of porous materials that comprises inorganic
nodes connected through organic linkers.[9] Their high surface area, variable porosity, and well-defined coordination
modes make them very valuable for general catalytic applications.[10] This scope has been expanded to biomass conversion
in recent years.[11,12] Due to the thermal stability
and catalytic properties of MOFs containing Zr6O8 nodes (Figure ),[13] they were tested in the valorization of alkyl
levulinates to GVL via CTH. UiO-66 exhibited high activity and selectivity
toward GVL in both batch[14] and flow[15] setups. Interestingly, while NH2-
and COOH-functionalized linkers did not improve the catalytic performance,[14] the presence of SO3H groups had a
positive impact, presumably due to a cooperative effect between Lewis
base nodes and Brønsted acid linkers.[16] Other MOFs with similar Zr6O8 nodes (MOF-808,[14] DUT-52,[17] and ZrF[18]) can also catalyze this reaction with high conversion
and moderate-to-good selectivity, as well as some Hf-based analogues.[19] The improved catalytic activity obtained by
MOF tuning is general and can be extrapolated to other processes,
as recently demonstrated in UiO-66-catalyzed carbohydrate conversion.[20]
Figure 1
Representation of Zr-based nodes. Zr = dark green, O =
red, H =
white.
Representation of Zr-based nodes. Zr = dark green, O =
red, H =
white.These promising results encourage
further mechanistic understanding
for catalyst optimization. Here is where computational chemistry comes
into play to provide quantum mechanical insight at the atomic level
of detail.[21] Despite the many computational
contributions on MOF catalysis,[22,23] the mechanistic features
of how these materials participate in biomass valorization are still
scarce. Most of these studies employ finite-size clusters,[24] which ignore the periodicity of the material
and cannot account for confinement effects within the pores. To address
this gap in knowledge, here we employ periodic density functional
theory (DFT) to create a more realistic environment. We compute the
reaction mechanism of ML to GVL at UiO-66 using isopropanol as a hydrogen
source. We identify the key steps of the catalytic cycle and evaluate
the impact of different catalyst modifications. Such mechanistic insight
would guide the rational design of catalysts to develop more efficient
and selective experimental systems.
Computational Section
Calculations were performed at the periodic Density Functional
Theory (DFT) level using the Vienna Ab-Initio Simulation Package (VASP).[25,26] The PBE density functional[27] was employed,
and dispersion interactions were considered with Grimme’s D2
scheme.[28] Core electrons were described
by projector augmented wave (PAW) pseudopotentials,[29] and valence electrons were represented by plane waves with
a kinetic energy cutoff of 450 eV. A Hubbard correction[30] of 4.5 eV was applied to Ce(4f) electrons as
suggested in the literature.[31,32] The simulation cell
of UiO-66 (14.737 × 20.840 × 14.737 Å3, Figure S1) was taken from previous DFT calculations.[33] The Brillouin zone was sampled at the Γ-point
via the Monkhorst–Pack method.[34] Transition state structures were located with the climbing image
nudged elastic band[35] and improved dimer[36] algorithms. Minima and transition states were
characterized by diagonalizing the numerical Hessian matrix (±0.015
Å displacements). Vibrational partition functions were computed
using numerical frequencies at 513 K as in experiments,[15] where only selected atoms were allowed to move.[37]Open access[38] to all inputs and outputs
reported herein, including raw energies and geometries, is provided
by the ioChem-BD platform[39] in the following
database.[40]
Results and Discussion
The UiO-66 MOF is formed by Zr6O4(OH)4 nodes connected to 12 1,4-benzenedicarboxylate linkers.[41] The pristine material does not have any open
metal sites, but the presence of defects, i.e., missing linkers, is
known to be responsible for catalytic activity.[42,43] Thus, we first need to propose a feasible active site where the
ML-to-GVL conversion may take place.The unit cell of UiO-66
contains four inorganic nodes.[41] To save
computational resources, we use a smaller
cell containing two inorganic nodes.[33] The
removal of one dicarboxylate linker creates two node defects with
four metal vacancies overall, which we then balance with OH/H2O groups.[44] Under reaction conditions,
we expect a displacement of H2O and exchange of [OH]− by [PrO]−, yielding the potential active species 1 (Figure ). We will use this
structure as a starting point for computing the reaction mechanism.
Figure 2
Computed
structure 1 at defective UiO-66 MOF. The
periodic structure was cropped for better visualization. The black
square indicates a Zr vacant site. Zr = dark green, O = red, H = white.
Computed
structure 1 at defective UiO-66 MOF. The
periodic structure was cropped for better visualization. The black
square indicates a Zr vacant site. Zr = dark green, O = red, H = white.
Reaction Mechanism at Defective UiO-66
We start the
mechanistic study from the previously discussed structure 1 which contains one PrO group and one
Zr vacant site. We establish this stage as the zero of energies. The
following values correspond to Gibbs energies computed at 513 K in
eV. All species are denoted with numbers in bold, where transition
states include the prefix TS.The proposed reaction
mechanism is depicted in Figure and entails catalytic transfer hydrogenation of ML
followed by cyclization to GVL. First, species 1 binds
ML through its carbonyl group forming 2 (0.14 eV). The
hydrogen transfer from PrO to the activated
ML occurs via TS2–3 (0.61 eV) involving two Zr
centers[45] and yields intermediate 3 (0.39 eV). From there, acetone is released via 4 (−0.09 eV) and the alkoxide rearranges to form the bidentate
species 5 (−0.51 eV), where the ester carbonyl
group is also bound to Zr. An intramolecular nucleophilic attack via TS5–6 (0.13 eV) generates the intermediate 6 (−0.14 eV). The subsequent elimination of MeOH is assisted
by the μ3-OH group of the node.[46−48] It takes place
via TS6–7 (0.15 eV) and results in the formation
of bounded GVL in 7 (−0.35 eV). The nonassisted
elimination via TS6–8 (0.46 eV), which yields
the Zr–OMe intermediate 8, is less favored (Figure S2). Finally, an incoming PrOH reactant molecule releases the GVL product and
regenerates catalyst 1. The computed mechanism is in
line with the experimental proposal, which involves two Zr atoms from
the same node[14] (rather than two Zr atoms
from adjacent nodes[16]).
Figure 3
Reaction mechanism of
ML to GVL at defective UiO-66 with relative
Gibbs energies (in eV). R = (CH2)2CO2Me.
Reaction mechanism of
ML to GVL at defective UiO-66 with relative
Gibbs energies (in eV). R = (CH2)2CO2Me.The Gibbs energy profile of the
reaction mechanism catalyzed by
defective UiO-66 is displayed in Figure (the electronic energy profile can be found
in Figure S3). The coordination of ML to
the catalyst 1 is slightly uphill by 0.14 eV, but this
step is temperature-sensitive, and computed Gibbs energies typically
over stabilize separated reactants due to entropic contributions.
The hydrogen transfer TS2–3 has a barrier of 0.61
eV above 1 and a relative barrier of 0.47 eV above 2. Similar values were recently found in the CTH of furfural
to furfuryl alcohol using finite-size cluster models of UiO-66[49] and MOF-808.[50] The
release of acetone followed by the bidentate coordination of the substrate
is quite favored, with 5 at 0.51 eV below 1. Next, the cyclization takes place via nucleophilic attack and elimination
of MeOH, where both TS5–6 and TS6–7 present similar barriers of 0.64 and 0.66 eV above 5, respectively. The release of GVL and the addition of PrOH recover the catalyst 1 with global
exoergic thermodynamics of 0.49 eV.
Figure 4
Gibbs energy reaction profile (in eV)
at defective UiO-66 with
relative barriers for each step.
Gibbs energy reaction profile (in eV)
at defective UiO-66 with
relative barriers for each step.The structures of selected transition states confined within the
MOF pore are displayed in Figure . TS2–3 shows the hydrogen transfer;
also, the ester group of ML forms a H bond with the μ3-OH group. TS5–6 describes the intramolecular
attack of the alkoxy to the carbonyl group. Finally, TS6–7 represents the departure of the methoxy group and the concomitant
abstraction of a proton from the μ3-OH group of the
node. Further simulations at the PBE level with and without D2 dispersion
corrections demonstrate the importance of such confinement effects
(Figure S4), with TS2–3 (hydrogen transfer) more affected than TS5–6 and TS6–7 (cyclization).
Figure 5
DFT-optimized TS structures.
Relevant atoms are display in ball-and-stick
format, the rest of them in tube format. Selected distances are shown
in Å.
DFT-optimized TS structures.
Relevant atoms are display in ball-and-stick
format, the rest of them in tube format. Selected distances are shown
in Å.These simulations predict overall
Gibbs energy barriers of ca.
0.65 eV for the UiO-66 catalyst. It demonstrates that the proposed
mechanism is feasible under the reported experimental conditions,
either in batch[14,16] or flow reactors.[15] They also predict that the cyclization process
is likely rate-determining, which is in line with the detection of
slight amounts of methyl 4-hydroxypentanoate.[15,16] Due to the importance of the node in the mechanism, we next evaluate
several MOF modifications that directly impact the Zr6O8 core: changing the nature of the metals (tuning the node)
and changing the ligands bound to them (tuning the linker).To facilitate future reading and comparison, from now on we will
label all species of the original unmodified UiO-66 with the prefix A (e.g., A-1). We will use letters in bold for
different modifications together with numbers in bold for intermediates
and transition states. The correspondence between letters and modifications
will be indicated in the following sections. The numeric notation
does not change, and the correspondence between numbers and structures
can be consulted in Figure .
Tuning the Node
The previous reaction mechanism shows
that Zr atoms efficiently act as Lewis acids for carbonyl groups.
We then consider whether other M(IV) atoms (Hf, Ti, and Ce) can facilitate
the reaction. Although such doping is not trivial from an experimental
point of view, mixed-metal nodes[51,52] and Ce-based
nodes[53] have been previously reported in
the literature.Considering the two Zr atoms involved in the
process (A), we exchange them by Hf, Ti, and Ce (B–J) as shown in Figure a. We then compute energy barriers for each
step: hydrogen transfer (from 1 to TS2–3), nucleophilic attack (from 5 to TS5–6), and elimination (from 5 to TS6–7). For the Hf derivatives B–D, the
differences in electronic energy with respect to A are
less than 0.05 eV (Figure S5), and we expect
similar Gibbs energy profiles for both Zr- and Hf-based nodes. However,
more changes are noted for Ti and Ce derivatives, and representative
systems are shown in Figure b. For F with one Ti, the hydrogen transfer is
significantly more demanding (F-TS2–3 at 1.14
eV) due to a weak adsorption of ML (F-2 at 0.50 eV),
while the nucleophilic attack remains roughly the same and the elimination
becomes easier (F-TS6–7 at 0.38 eV, 0.54 eV above F-5). For I with one Ce, the hydrogen transfer
and elimination steps are only marginally better, and the nucleophilic
attack does not change. Interestingly, for J, which includes
two Ce atoms, all barriers are reduced. The adsorption of ML is slightly
stronger (J-2 at −0.10 eV), and the hydrogen transfer
barrier is lower (J-TS2–3 at 0.41 eV, 0.51 eV
above J-2). Likewise, the alkoxy intermediate is more
stable and the cyclization process is overall faster.
Figure 6
(a) Hf-, Ti-, and Ce-doped
nodes and (b) relative Gibbs energy
barriers (in eV) for selected models. Barriers are computed from the
transition state to the previous most stable intermediate.
(a) Hf-, Ti-, and Ce-doped
nodes and (b) relative Gibbs energy
barriers (in eV) for selected models. Barriers are computed from the
transition state to the previous most stable intermediate.To sum up, the presence of Ti can speed up the cyclization
process
at the expense of slowing down the hydrogen transfer. Ce-containing
nodes provide a general decrease of barriers for all steps, in line
with simulations on chemical warfare decomposition.[54] With these results, we hypothesize that rare-earth-based
MOFs[55] could also exhibit similar or improved
catalytic activity for biomass-related processes.
Tuning the
Linker
Not only nodes but also linkers can
be fine-tuned in MOF catalysts. Therefore, we now consider changing
the groups around the metals through linker modifications. Previous
theoretical studies have pointed out that functionalizing the aromatic
linkers has little effect on computed energy barriers[46,56] and frequencies.[57] We thus take a different
approach and change the type of connectivity between the linker and
the node.As mentioned before, the unmodified MOF is labeled
with the prefix A, where L is the original benzenedicarboylate
(bdc). Considering the linkers bound to the participating Zr atoms,
we exchange them by La and Lb as shown in Figure a. In La, one bidentate carboxylate group is removed, and one monodentate
hydroxo is bound to Zr (K and L), thus formally
introducing a new vacant site at the node. In Lb, one carboxylate
group is substitute by one sulfonate group[58] (M and N). The relative Gibbs energy barriers
are summarized in Figure b. For K, the adsorption of ML does not change
much (K-2 at 0.25 eV) but the hydrogen transfer becomes
more difficult (K-TS2–3 at 1.03 eV). This is due
to a stronger interaction between the PrO and the unsaturated Zr, which decreases the nucleophilicity of
the former. On the other hand, for L, the adsorption
of ML is enhanced at the unsaturated Zr (L-2 at −0.39
eV), and the hydrogen transfer becomes faster (L-TS2–3 at 0.41 eV above L-2). Although an electron deficient
Zr is beneficial in the first step, it later binds to the alkoxy intermediate
strongly (L-5 at −1.57 eV), creating a thermodynamic
sink that hinders the cyclization process. For M and N, both systems behave the same, and only N is
discussed for simplicity. The sulfonate group in N does
not introduce large changes, cf. the carboxylate
group in A, and similar barriers are obtained in both
cases.
Figure 7
(a) Linker-modified nodes and (b) relative Gibbs energy barriers
(in eV) for selected models. Barriers are computed from the transition
state to the previous most stable intermediate.
(a) Linker-modified nodes and (b) relative Gibbs energy barriers
(in eV) for selected models. Barriers are computed from the transition
state to the previous most stable intermediate.Overall, these results indicate that the excess of vacancies at
Zr atoms is counterproductive for activity, which may relate to the
worse catalytic performance after losing organic linkers.[15] They also suggest that the reaction is feasible
with MOFs containing SO3-modified linkers. Although there
is no strong improvement in terms of computed reaction barriers, these
materials may present other advantages from a practical point of view,
such as higher number of defects along the framework (i.e., more catalytic
sites) while increasing the stability of the material, as reported
recently.[58]
Conclusions
In
this work, we study the role of UiO-66 in the conversion of
methyl levulinate to γ-valerolactone using isopropanol as a
hydrogen source. By means of periodic DFT simulations, we propose
a feasible reaction mechanism in agreement with experiments, which
consists of transfer hydrogenation and cyclization (nucleophilic attack
followed by elimination). We find similar Gibbs energy barriers for
all steps, thus no unique rate-determining step can be ascribed. Notably,
the μ3-OH group at the node actively participates
in the reaction by forming H-bonds with reactants and assisting in
the elimination process.As for design, we explore several catalysts
by systematically varying
the metal atoms in the node as well as the connecting group between
the linker and the node. Our computational approach provides a precise
control of MOF changes that allows us to inspect the impact of each
modification on each step of the mechanism. In this way, we demonstrate
that Ti (a hard Lewis acid) improves the hydrogen transfer but is
detrimental for the cyclization, while highly unsaturated Zr operates
the other way around. We also find that Ce-based nodes decrease all
three reaction barriers and exploring related MOFs containing rare-earth
elements would be interesting. Finally, Zr nodes with SO3-modified linkers are competitive, cf. the parent
material, and can improve the overall performance of the catalytic
system.
Authors: Martin Lammert; Michael T Wharmby; Simon Smolders; Bart Bueken; Alexandra Lieb; Kirill A Lomachenko; Dirk De Vos; Norbert Stock Journal: Chem Commun (Camb) Date: 2015-08-14 Impact factor: 6.222
Authors: Anastasiya Bavykina; Nikita Kolobov; Il Son Khan; Jeremy A Bau; Adrian Ramirez; Jorge Gascon Journal: Chem Rev Date: 2020-03-30 Impact factor: 60.622
Authors: S M J Rogge; A Bavykina; J Hajek; H Garcia; A I Olivos-Suarez; A Sepúlveda-Escribano; A Vimont; G Clet; P Bazin; F Kapteijn; M Daturi; E V Ramos-Fernandez; F X Llabrés I Xamena; V Van Speybroeck; J Gascon Journal: Chem Soc Rev Date: 2017-06-06 Impact factor: 54.564