Solvation of furfural at metal–water interfaces: Implications for aqueous phase hydrogenation reactions

Metal-water interfaces are central to understanding aqueous-phase heterogeneous catalytic processes. However, the explicit modeling of the interface is still challenging as it necessitates extensive sampling of the interfaces' degrees of freedom. Herein, we use ab initio molecular dynamics (AIMD) simulations to study the adsorption of furfural, a platform biomass chemical on several catalytically relevant metal-water interfaces (Pt, Rh, Pd, Cu, and Au) at low coverages. We find that furfural adsorption is destabilized on all the metal-water interfaces compared to the metal-gas interfaces considered in this work. This destabilization is a result of the energetic penalty associated with the displacement of water molecules near the surface upon adsorption of furfural, further evidenced by a linear correlation between solvation energy and the change in surface water coverage. To predict solvation energies without the need for computationally expensive AIMD simulations, we demonstrate OH binding energy as a good descriptor to estimate the solvation energies of furfural. Using microkinetic modeling, we further explain the origin of the activity for furfural hydrogenation on intrinsically strong-binding metals under aqueous conditions, i.e., the endothermic solvation energies for furfural adsorption prevent surface poisoning. Our work sheds light on the development of active aqueous-phase catalytic systems via rationally tuning the solvation energies of reaction intermediates

Ab initio dynamics in catalysis

Recycling waste carbon (e.g. CO2, biomass) is a powerful strategy to address humanity’s longstanding challenges, including climate change and environmental degradation. Electrocatalysis is an efficient tool for converting waste carbon to value-added products and is an alternative approach for closing the carbon circle and achieving carbon neutrality. However, electrocatalysis faces many technical challenges, the most important of which is to have an atomic-scale understanding of the complex and highly dynamic electrochemical interfaces where chemical reactions take place. In this thesis, we applied ab initio methods to elucidate the water adsorption, solvation, thermal expansion, strain and dipole-field effect at the interfaces.We begin by benchmarking water adsorption on metal surfaces with ab initio molecular dynamics (AIMD). The water adsorption energy, a central quantity to our goal of understanding water at interfaces and the solvation effect, is directly compared with temperature-programmed desorption (TPD) and other experimental results. Our results show that both RPBED3 and BEEF-vdW lead to appropriate water binding strengths, while PBED3 clearly overbinds near-surface water relative to experiments. Our study gives atomistic insight into the complex equilibrium of water adsorption and represents a guideline for future DFT-based simulations of the water/metal interface within molecular dynamics studies.We then focus on the selectivity issue of glycerol electro-oxidation, which is an area of interest within biomass upcycling, because of the low overpotential and high feedstock availability. Inspired by our experimental collaborators, we study the limited selectivity toward lactic acid on Pt surface by DFT. We have formulated a theoretical descriptor that establishes a correlation between surface acidity and selectivity toward lactic acid. Furthermore, we investigate the solvation effect of glycerol and related intermediates via an AIMD approach, which is the key to understanding the selectivity to 2-electron products. A simple linear model was developed to estimate the solvation energy in glycerol oxidation.Further, we explore the trends in strain effects from thermal expansion via ab initio phonon dynamics. We developed a thermal expansion strain parameter for transition metals which can quantitatively describe the strain effect induced by thermal expansion. The results offer a simple and easy method to correct adsorption energies at specific temperatures and assist in the strain engineering for catalysts.Finally, we turn to studying CO2 activation on the Cu surface. We develop a computational method to determine the energetic contribution and binding motifs of CO2 adsorption at electrochemical interfaces. By splitting the energies into bending, interaction with surface, dipole field and solvation components, we find that the carbon and oxygen binding motif is the most feasible configuration. Employing ab initio electrochemistry methods, we also investigate the energy trend in CO2 adsorption. These results help us understand the CO2 activation and selectivity in CO2 reduction.In summary, we have used ab initio dynamics to explore the manifold aspects of catalysis. We investigate water adsorption, glycerol electro-oxidation, thermal expansion strain and CO2 activation as case studies for the key factors at interfaces. The results and the methods we developed in this thesis will influence the theoretical development of electrochemical interfaces, industrial applications, and better catalyst design for upcycling of waste carbon

Benchmarking water adsorption on metal surfaces with ab-initio molecular dynamics

Solid-water interfaces are ubiquitous in nature and technology. Particularly, in technologies evolving in the context of a green transition, such as electrochemistry, the junction of an electrolyte and an electrode is a central part of the device. Simulations based on density functional theory (DFT) have become de facto standard for both the understanding of atomistic processes at this interface and the screening for new materials. Thus, DFT\u27s ability to simulate the solid/water interaction needs to be benchmarked and ideal simulation setups need to be identified, in order to prevent systematic errors. Here, we developed a rigorous sampling protocol for benchmarking the adsorption/desorption strength of water on metallic surfaces against experimental temperature programmed desorption, single crystal adsorption calorimetry and thermal energy atom scattering. We screened DFT\u27s quality on a series of transition metal surfaces, applying three of the most common exchange correlation approximations; PBE-D3, RPBE-D3 and BEEF-vdW. We find that all three XC-functional reflect the pseudo-zeroth order desorption of water rooted in the combination of attractive adsorbate-adsorbate interactions at low coverages and their saturation at intermediate coverage. However, both RPBE-D3 and BEEF-vdW lead to more appropriate water binding strengths, while PBE-D3 clearly overbinds near-surface water. We are able to relate the variations in binding strength to specific variations in water-metal and water-water interactions, highlighting the structural consequences inherent in an uninformed choice of simulation parameters. Our study gives atomistic insight into the complex adsorption equilibrium of water and represents a guideline for future DFT-based simulations of the solvated solid interface within molecular dynamics studies by providing an assessment of systematic errors in specific setups

Solvation of furfural at metal|water interfaces: Implications for aqueous phase hydrogenation reactions

Metal|water interfaces are central to understanding aqueous phase heterogeneous catalytic processes. However, it is challenging to model the interactions between metal surfaces, adsorbates and the solvent water molecules at the interface. Herein, we use ab-initio molecular dynamics (AIMD) simulations to study the adsorption of furfural, a platform biomass chemical on several catalytically relevant metal|water interfaces (Pt, Rh, Pd, Cu and Au) at low coverages. We find that furfural adsorption is destabilized on all the metal|water interfaces compared to the metal|vacuum interfaces considered in this work. This destabilization is a result of the energetic penalty associated with the displacement of water molecules near the surface upon adsorption of furfural. This is evidenced by a linear correlation between solvation energy and the change in surface water coverage. To predict solvation energies without the need for computationally expensive AIMD simulations, we demonstrate OH binding energy in vacuum to be a good descriptor to estimate the solvation energies of furfural on different metal|water interfaces. Using microkinetic modeling, we further explain the origin of the activity for furfural hydrogenation on intrinsically strong-binding metals, such as Rh and Pt, under aqueous conditions, i.e., the endothermic solvation energies for furfural adsorption helps prevent surface poisoning. Our work sheds light on the development of active aqueous-phase catalytic systems via rationally tuning the solvation energies of reaction intermediates

Solvation of furfural at metal-water interfaces:Implications for aqueous phase hydrogenation reactions

Metal-water interfaces are central to understanding aqueous-phase heterogeneous catalytic processes. However, the explicit modeling of the interface is still challenging as it necessitates extensive sampling of the interfaces' degrees of freedom. Herein, we use ab initio molecular dynamics (AIMD) simulations to study the adsorption of furfural, a platform biomass chemical on several catalytically relevant metal-water interfaces (Pt, Rh, Pd, Cu, and Au) at low coverages. We find that furfural adsorption is destabilized on all the metal-water interfaces compared to the metal-gas interfaces considered in this work. This destabilization is a result of the energetic penalty associated with the displacement of water molecules near the surface upon adsorption of furfural, further evidenced by a linear correlation between solvation energy and the change in surface water coverage. To predict solvation energies without the need for computationally expensive AIMD simulations, we demonstrate OH binding energy as a good descriptor to estimate the solvation energies of furfural. Using microkinetic modeling, we further explain the origin of the activity for furfural hydrogenation on intrinsically strong-binding metals under aqueous conditions, i.e., the endothermic solvation energies for furfural adsorption prevent surface poisoning. Our work sheds light on the development of active aqueous-phase catalytic systems via rationally tuning the solvation energies of reaction intermediates

Selective glycerol to lactic acid conversion via a tandem effect between platinum and metal oxides with abundant acid groups

Phasing out petrochemical-based thermoplastics with bio-plastics produced in an energy efficient and environmentally friendly way is of paramount interest. Among them, polylactic acid (PLA) is the flagship with its production accounting for 19% of the entire bioplastics industry. Glycerol electrolysis for producing the monomer lactic acid, while co-generating green H2, represents a promising approach to boost the production of PLA, yet the reaction selectivity has been a bottleneck. Here, we report a combined electrochemical and chemical route using a tandem Pt/C-γ-Al2O3 multicomponent catalyst which can achieve a glycerol-to-lactic acid selectivity of 60.2 ± 2.7%, among the highest performance reported so far. Combining an experimental and computational mechanistic analysis, we suggest that tuning the acidic sites on catalyst surface is crucial for shifting the reaction towards the dehydration pathway, occurring via dihydroxyacetone intermediate. Within the tandem effect, Pt is the active site to electrochemically catalyze glycerol to dihydroxyacetone and glyceraldehyde, while the γ-Al2O3 provides the required acidic sites for catalyzing dihydroxyacetone to the pyruvaldehyde intermediate, which will then go through Cannizzaro rearrangement, catalyzed by the OH- ions to form lactic acid. This catalytic synergy improves the selectivity towards lactic acid by nearly two-fold. A selectivity descriptor (ΔG_(GLAD^* )-ΔG_(DHA^* )) from density functional theory calculations was identified, which could be used to screen other materials in further research. Our findings highlight the promise of tandem electrolysis in the development of strategies for selective electrochemical production of high-value commodity chemicals from low value (waste) precursors