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As climate change continues to pose a threat to the Earth due to the disrupted carbon cycles and fossil fuel resources remain finite, new sources of sustainable hydrocarbons must be explored. 2,3-butanediol is a potential source to produce butene because of its sustainability as a biomass-derived sugar. Butene is an attractive product because it can be used as a precursor to jet fuel, categorizing this work in the alcohol-to-jet pathway. While studies have explored the conversion of 2,3-butanediol to butene, little is understood about the fundamental reaction itself. We quantify the energetics for three pathways that were reported in the literature in the absence of a catalyst. One of these pathways forms a 1,3-butadiene intermediate, which is a highly exothermic process and thus is unlikely to occur since 2,3-butanediol likely gets thermodynamically trapped at this intermediate. We further determined the corresponding energetics of 2,3-butanediol adsorption on an ensemble of predetermined binding sites when it interacts with a defect-free stoichiometric RuO2(110) surface. Within this ensemble of adsorption sites, the most favorable site has 2,3-butanediol covering a Ru 5–coordinated cation. This approach is compared to that obtained using the global optimization algorithm as implemented in the Northwest Potential Energy Surface Search Engine. When using such a global optimization algorithm, we determined a more favorable ground-state structure that was missed during the manual adsorption site testing, with an adsorption energy of −2.61 eV as compared to −2.34 eV when using the ensemble-based approach. We hypothesize that the dehydration reaction requires a stronger chemical bond, which could necessitate the formation of oxygen vacancies. As such, this study has taken the first step toward the utilization of a global optimization algorithm for the rational design of Ru-based catalysts toward the formation of butene from sustainable resources.
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The continual use of fossil fuels is contributing to the disruption of the Earth’s carbon cycle, resulting in global warming. A contributor to this is aviation fuel—a highly refined and strictly regulated product of the petroleum industry. Bio-jet fuel provides an alternative to petroleum-based aviation fuel as it maintains low weight and high-energy content that is necessary for air travel. The aviation industry recognizes the need for implementing renewable fuels and has committed to halving emissions by 2050. Sustainable aviation fuel has been projected to help in this endeavor as it can offer up to 80% reduction in emissions as compared to petroleum-based fuel, and as such it has been touted as the biggest opportunity in emission abatement within the aviation industry (
One way to upgrade biomass to usable aviation fuel is through the alcohol-to-jet pathway. In this pathway, a biomass-derived alcohol is dehydrated to butene. Butene is then able to undergo additional chemical processes such as oligomerization and hydrogenation to achieve the proper alkane conformation that is specified in the ASTM standards (
Dehydrating diols, such as 2,3-butanediol (BDO), have been demonstrated to be a more complex process than dehydrating alcohols with only one hydroxyl group. Often research exploring the dehydration of diols yields a mono-alcohol (
In this study, the adsorption mechanism of 2,3-butanediol on the RuO2 surface is tested with two separate methods: an ensemble-based approach with a predetermined set of possible adsorption sites and through a global optimization algorithm using the Northwest Potential Energy Surface Search Engine (NWPEsSe) (
The study presented is an A-type article and original research.
The calculations presented in this study were carried out using the Vienna
The rutile structure for RuO2 was chosen as it is the most stable under standard conditions (
A density of states analysis was carried out such that the Fermi level was set to zero. For the gas-phase BDO the Fermi level was taken to be halfway between the HOMO and LUMO states as was done by (
To determine the most favorable adsorption site with an ensemble of predetermined binding sites, an ensemble-based approach was performed so that “ensemble-based” refers to the process that was conducted without the aid of a global optimization algorithm. As such, it is based on chemical intuition. Within this framework, seven unique possible adsorption sites were determined and tested for two different ways: with the 2,3 C-C bond parallel to the
We employed the Northwest Potential Energy Surface Search Engine (NWPEsSe) software (
The first step in analyzing the dehydration of BDO is to determine the reaction pathways in the absence of a catalyst based on what is known in the literature. Dehydrating BDO can have a variety of different products such as 3-hydroxy-2-butanone and 2,3-butanedione, but there are three distinct products whose pathways lead to butene (
Reaction Pathways 1, 2, and 3 for 2,3-butanediol dehydration to butene at three levels of theory: PBE, van der Waals optB86b functional, and SCAN.
Comparing the three pathways, the SCAN functional produced the lowest energies out of the three levels of theory, two exceptions being the intermediary structures in Pathways 2 and 3—2-butanol and 2-methyl-1-propanol. The energetic difference is especially clear when looking at the relative reaction energies for the dehydration process which was 0.395, 0.058, and 0.012 eV for the PBE, VDW, and SCAN functionals, respectively. The SCAN functional improves upon GGA as it has a better capability to distinguish between covalent and metallic bonds, additionally describing them as semi-local (
To understand the bonding more accurately between BDO and RuO2(110), the electronic configuration of the gas phase BDO was analyzed through partial density of states (PDOS). We also analyzed the partial charge density distribution of its four highest occupied molecular orbitals (E1–E4) as well as its lowest unoccupied molecular orbital (E5). This information will later be used in the study to identify changes in the electronic configuration upon adsorption to the surface. The PDOS shown in
Partial density of states for 2,3-butanediol with accompanying partial charge density images; isosurface of 0.0075 electrons/Bohr3. The gray, red, brown, and pink spheres are Ru, O, C, and H atoms, respectively.
Examining the
To determine the most favorable adsorption site of 2,3-butanediol, the orientation of the hydroxyl groups relative to the surface—the main interest in the eventual dehydration reaction—needs to be analyzed. Therefore, for 2,3-butanediol, two alternatives were considered: one with hydroxyl groups facing toward the surface (
Differential charge density analysis for
This differential charge analysis was based on placement at Site 1 in
Within the framework of the ensemble-based site testing approach, a horizontal and a vertical site were tested at each of the seven sites can be seen in
Ensemble-based adsorption site comparison; the site orientation is given in
Site # | 1 | 2 | 3 | 4 | 5 | 6 | 7 |
---|---|---|---|---|---|---|---|
Horizontal adsorption energy (eV) | −2.34 | −0.43 | −1.43 | −0.46 | −2.35 | −2.34 | −2.30 |
Vertical adsorption energy (eV) | −1.75 | −0.35 | −1.71 | −0.46 | −1.71 | −1.97 | −2.30 |
Furthermore, we analyzed snapshots of the adsorption configurations during our geometric search. The first step using NWPEsSe and GFN-FF generally screened a variety of BDO/RuO2(110) structures, found a large amount of adsorption configurations, and ruled out unfavorable structures. In the second step involving GFN2-xTB, we were able to refine the obtained structures from the first step and identify several adsorption configurations that were at local minima, as illustrated in
Once the final DFT calculations were done on the NWPEsSe-generated structures, we determined which ground-state structure was at the global minimum.
Comparison of the adsorption energies and specifics of the configurations between ensemble-based approach and the NWPEsSe-based approach in finding the global minimum.
Eads (eV) | Edist (eV) | dO1-Ru (Å) | dO2-Ru (Å) | Dihedral angle O1 ( |
Dihedral angle O2 ( |
|
---|---|---|---|---|---|---|
Manual | −2.34 | 0.24 | 2.20 | 2.20 | 71.07 | 70.67 |
NWPEsSe | −2.61 | 0.23 | 2.14 | 2.16 | 168.70 | 166.64 |
We compare the PDOS analyses of the most favorable adsorption sites resulting from the two methods in
PDOS comparing adsorption of BDO on RuO2.
Partial charge density distribution images associated with the PDOS peaks in
The
Looking at the
Ensemble-based structure | NWPEsSe-based structure | ||||
---|---|---|---|---|---|
Ruclean | Ru-O1 | Ru-O2 | Ru-O1 | Ru-O2 | |
Center (eV) | −4.10 | −4.21 | −4.19 | −4.26 | −4.29 |
Width (eV) | 6.09 | 6.28 | 6.25 | 6.47 | 6.50 |
Analyzing the three different reaction pathways toward butene formation, as shown in
The HOMO level being primarily occupied by the oxygen
The adsorption analysis of BDO on RuO2(110) began by understanding its surface orientation. As is evident by the differential charge analysis (
Further confirmation of the differential charge analysis at the surface can be obtained through a Bader charge analysis that is given in
Bader net atomic charge values for the Ru5c atoms and their respective bonded hydroxyl oxygens for the two ground-state structures in the case of the ensemble-based and the NWPEsSe-based site testing approaches with accompanying clean RuO2(110) surface and gas phase (BDO) Bader net atomic charges for comparison.
Ensemble-based structure | NWPEsSe-based structure | |||||||
---|---|---|---|---|---|---|---|---|
Ru-O1 | Ru-O2 | O1 | O2 | Ru-O1 | Ru-O2 | O1 | O2 | |
Bader net atomic charge of adsorbed structure ( |
1.64 | 1.64 | −1.17 | −1.21 | 1.66 | 1.68 | −1.18 | −1.16 |
Bader net atomic charge of clean surface/gas phase structure ( |
1.80 | 1.80 | −1.15 | −1.21 | 1.80 | 1.80 | −1.15 | −1.21 |
Electron behavior | loss | loss | gain | gain | loss | loss | gain | loss |
The electronic configuration of the two different systems is similar. The PDOS of the main species that are involved in the adsorption of BDO (
Between the two analyses, ensemble-based and NWPEsSe-based, the ground-state structure had the same placement on the lattice indicated as Site 1 in
We compare the 10 lowest structures from the GFN2-xTB run and their corresponding DFT-based optimizations in
Correlation plot between the relative adsorption energies generated from the 10 lowest structures of GFN2-xTB simulation and their corresponding DFT optimized relative adsorption energies (in eV); the color coding in the plot corresponds to the figure images that have their DFT calculated adsorption energies. The gray, red, brown, and pink spheres are Ru, O, C, and H atoms, respectively.
Analyzing the energetic pathways of BDO dehydration to butene (
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The raw data supporting the conclusion of this article will be made available by the authors, without undue reservation.
All authors listed have made a substantial, direct, and intellectual contribution to the manuscript and approved it for publication.
This work was funded by the WSU-PNNL Bioproducts Institute, which is a joint research collaboration of Washington State University and the U.S. Department of Energy’s Pacific Northwest National Laboratory. V-AG, RR, and DZ acknowledge funding from U.S. Department of Energy, Office of Basic Energy Sciences, Division of Chemical Sciences, Geosciences and Biosciences project number 47319. This work was also partially funded by the Joint Center for Deployment and Research in Earth Abundant Materials (JCDREAM) in Washington State. This research also used resources of the National Energy Research Scientific Computing Center (NERSC), a U.S. Department of Energy Office of Science User Facility operated under Contract No. DE-AC02-05CH11231. The Pacific Northwest National Laboratory is operated by Battelle for the U.S. DOE.
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors, and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
Part of the computational resources was also provided by the Kamiak HPC under the Center for Institutional Research Computing at Washington State University. We also thank Naseeha Cardwell and Nisa Ulumuddin for fruitful discussions.
The Supplementary Material for this article can be found online at: