Colloidal copper nanospheres boost propanol electrosynthesis from CO

doi:10.21203/rs.3.rs-4544481/v1

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Colloidal copper nanospheres boost propanol electrosynthesis from CO

https://doi.org/10.21203/rs.3.rs-4544481/v1

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Achieving a carbon neutral manufacturing of chemicals is imperative to accelerate the transition towards a sustainable future. Propanol electrosynthesis from CO electroreduction represents a promising alternative to the current manufacturing of this chemical. Yet, the catalyst features driving propanol formation are poorly understood, which limits further advancement in the performance. Herein, we report on a comprehensive mapping of the sensitivity of the CO electroreduction to the catalyst structure exploiting well-defined copper nanocrystals (NCs) with tunable shape and size synthesized via colloidal chemistry. In addition to clarify the dependence from the exposed surfaces, we discover that spheres uniquely promote n-propanol selectivity, which we explain mostly with strain effects. Driven by this novel insight, we achieve unprecedent n-propanol production via electrosynthesis with a copper catalyst. We demonstrate that colloidal copper nanospheres with a diameter of 4 nm deliver n-propanol faradaic efficiency of 39.6±1.4% at 119±4.2 mA/cm2 production rate, the latter being ten times the current state of the art for copper catalysts.

Physical sciences/Chemistry/Catalysis/Electrocatalysis

Physical sciences/Chemistry/Chemical synthesis/Nanoparticle synthesis

Physical sciences/Chemistry/Green chemistry/Sustainability

Propanol is used in the food industry, in healthcare, in packaging, and is appealing as a transportation fuel additive.^1-3Today, the manufacturing of this C₃ alcohol is based on the hydrogenation of propionaldehyde, which is produced by hydroformylation of ethylene with a rhodium phosphine catalyst.⁴This process occurs at high temperature and pressure, is highly energy demanding, relies on cracking and petroleum, and emits greenhouse gases.^1-4

The electrochemical CO reduction reaction (CORR) is an appealing process to produce chemicals at room temperature and ambient pressure while storing excess renewable electricity.^5,6 Technoeconomic analysis and experimental evidences suggest that the two-step electrosynthesis CO₂ to CO followed by CO to multi-carbon products outperform the one-step process in terms of efficiency and stability.^2,3,7-11

This attractive scenario has fostered an increase effort to overcome the selectivity challenge of CORR and to improve its efficiency towards one single chemical product.^12-24 The achievement of a significant faradaic efficiency (FE, i.e. electrons converted into chemicals) for C₃ products is particularly interesting.^16-24 However, further performance enhancement is needed to render n-propanol electrosynthesis a valuable process which operates with high selectivity at hundreds of milliamperes per square centimeters.

A puzzling scenario currently exists in understanding how the structure of the catalyst impacts the selectivity of CORR under practical reaction conditions (i.e. high current densities). All the catalysts reported to produce n-propanol are Cu-based materials.^16-24 The presence of “adparticles” with low coordinated sites and combined strain with ligand effects have been used to explain the observed selectivity towards n-propanol in Cu only and in Cu doped with noble metals, respectively.^16-24 Studies on Cu single crystals have shown a structural sensitivity of CORR wherein (111) and (100) facets have a preference to form methane and ethylene, respectively.^25,26 Yet, such facet-dependent relationships have not been demonstrated at high current density. Furthermore, evidences indicate that CO adsorption is not sensitive to certain structural features of the catalyst (i.e. coordination numbers).²⁷ Overall, solving this puzzle is important to design catalysts which further increase selectivity in CORR, specifically for n-propanol electrosynthesis.

Here, we exploit well defined Cu nanocrystals (NCs) with different shapes and sizes to provide a comprehensive mapping of catalyst structure/selectivity relationships in CORR. We reveal that facet-dependent selectivity does exist in CORR under practical reaction conditions. Through the combination of various state of the art experimental and computational data, we propose the lattice strain of spherical Cu NCs as one of the key features to boost the CORR towards alcohols and, more specifically, n-propanol. Based on this idea, we design a catalyst which achieves a production rate for n-propanol which is ten times the current state of the art for copper catalysts.

Cu NCs with different shapes and size were synthesized via colloidal methods (Fig. 1a, Supplementary Fig. 1, Methods). Cu cubes (Cu-Cube) and Cu octahedra (Cu-Octa) were chosen because they expose mostly (100) and (111) facets, respectively, whereas Cu sphere (Cu-Sph) exhibit a mixture of both facets on their surface.²⁸ Cu-Cube with edge length of ~40 nm, Cu-Octa with edge length of ~80 nm and Cu-Sph with diameter of ~80 nm (Cu-S80)have a comparable surface-to-volume ratio (Supplementary Table 1). Cu spheres with diameter of ~34 nm (Cu-S34) and of ~7 nm (Cu-S7) were chosen to investigate the effect of size.

All catalysts are mostly selective for C₂₊ products (Fig. 1b,c and Supplementary Table 2). The low C₁ production is in line with reported results under similar operating conditions.^12-24 The ethylene FE remains constant at ~20% for all catalysts. Cu-Cubeproduces the highest amount of acetate (FE ~ 40%). Acetate remains the main product for Cu-Octa, yet the selectivity towards this product drops (FE ~26%) and, concomitantly, methane appears (FE ~6%). An intriguing switch in selectivity from acetate to alcohols occurs when moving to the Cu-Sph. Cu-S80 shows high selectivity for C₂₊ alcohols (FE ~50%) with n-propanol FE ~20% and ethanol FE ~29%. Alcohols increase further while acetate gets reduced as the size of the spheres decreases, reaching C₂₊ alcohols (FE ~57%) with ~23% for n-propanol and ~34% for ethanol for the Cu-S7.

Potential dependent product selectivity does not explain the changes in selectivity as only minor variation of the electrode potential occurs among the different systems (Supplementary Table 2, Supplementary Fig. 2).³¹ pH effects were proposed to promote the switch in selectivity from acetate, at high pH, to n-propanol, at lower pH.¹⁰Our system operates at high pH; furthermore, the testing conditions are the same for all catalysts, thus pH effects are unlikely to play a role. CO coverage was shown to affect the CORR mechanism, and the selectivity of ethylene vs oxygenated (i.e. low CO coverage to ethylene and high CO coverage to oxygenated).^12,13,32,33 To explore eventual CO coverage effects,we tested our well-defined Cu NCs at different CO concentration in an inert N₂ carrier (Fig. 1d, Supplementary Fig. 3). The decrease of acetate at lower CO % in both Cu-Cube and Cu-Octa, is accompanied by the increase of ethylene and methane, respectively. No change of the product distribution is observed for the Cu-S7.

With regards to the preferential ethylene selectivity and the CO coverage product dependence/switch to acetate (Fig. 1, Supplementary Fig. 2,3), the behavior of Cu-Cube is consistent with what observed in the literature and is in line with the idea that most polycrystalline copper exposes (100) facets during CORR.^12,25,26 The observation that methane selectivity is higher on Cu-Octa exposing the (111) surface compared to the Cu-Cube also agrees with the structure-dependence observed on single crystal.^25,26 The fact that this structural sensitivity becomes more evident at lower CO coverage and that methane and acetate might share a reaction intermediate on the (111) surface in CORR are new insights.

A mixture of (111) and (100) facets was previously used to explain the propanol selectivity of Cu “adparticles”.¹⁷However, the insensitivity of the product distribution of the Cu-S7to the CO coverage highlights that structural effects other than the exposed facets must be considered to explain the unique nature of their propanol-selective active sites.

The formation of grain boundaries and possible residual oxide were previously proposed as catalyst features accounting for alcohol production in both CO₂RR and CORR.^34-37

X-Ray diffraction and electron microscopy reveal that the morphology of the catalysts does not change after the collected CORR data (Supplementary Fig. 4, Supplementary Note 1), thus the grain boundaries forming during operation can be excluded. We also excluded any major impact on selectivity of residual oxidized copper during CORR by performing operando X-ray absorption spectroscopy and other control experiments (Supplementary Fig. 5-8, Supplementary Note 1). Differences in local environment and/or mass transport among the samples can also generate different distribution of multi-carbon products.¹⁰A similar distribution of all the catalysts through the gas diffusion layer also excluded these factors as a major contributor (Supplementary Fig. 9). The native ligands used for the synthesis of the catalysts also do not appear to influence the product distribution (Supplementary Fig. 10).

Lattice strain can alter the binding energy of adsorbates and, thus, impact selectivity of a given catalytic reaction.^38,39 Convoluted strain and ligand effects were proposed to explain the n-propanol selectivity observed in Cu catalysts doped with Ag and Ag-Ru.^20,21Strain effect in Cu catalyst have been recently suggested as a mean to lower the activation barrier for CORR.⁴⁰ Size and shape dependence of strain in nanoparticles of noble metals more commonly used in catalysis, such as Pt, have been largely explored and different strategies implemented to modulate it, including doping/alloying and support epitaxial interactions.^{41- 43} Yet, how shape and size modify the strain in Cu NCs is an under investigated topic.

We used Neural Network potential⁴⁴ and Molecular Dynamics (NN-MD, NVT ensemble) to obtain the average strain of surface atoms from models of Cu cubes, octahedra and sphere at three different sizes (2.5 nm, 5.0 nm, 7.5 nm) (Fig. 2a,b, Methods and Supplementary Information). The spheres possess the highest average strain among the shapes at 5.0 nm and 7.5 nm (Fig. 2b), which results in a wider distribution of the Cu-Cu bond length histograms (Fig. 2c). The same trends were observed when testing effects of surface reconstruction (i.e. randomly removing 5% of total atoms and of surface atoms) and surface oxidation (i.e. replacing the removed 5% Cu atoms with oxygen atoms) (Supplementary Figs. 11-17), which corroborate the experimental conclusion that possible minor surface reconstruction and oxidation do not explain the observed CORR selectivity.

To investigate how the strain impacts the selectivity, we created computationally affordable active site models from the large NN-MD simulation (Fig. 2d, Supplementary Note 2 and Supplementary Figs. 18-20). These active site models allowed us to assess the adsorption energies of key reaction intermediates to acetate and to alcohols (Fig. 2e).^45,46 Thus, we compared the adsorption energies of intermediates of competing mechanisms (Fig. 2f,g), on 30 active site models extracted from the spheres (10 for each size) and on Cu(211) step sites, as representative of cubes and octahedra. All the active site models of the spheres show preference for alcohols over acetate compared to cubes and octahedra, which is indicated by the stronger binding towards *OCHCH compared to the step sites (Fig. 2f). Furthermore, 28 out of 30 active sites for the spheres exhibit stronger binding energy for *OCHCHCOH compared to step sites (Fig. 2g). Among these sites, most of those derived from the smaller spheres (5 nm and 2.5 nm) possess a similar (or even weaker) binding energy for *OCHCH₂ than Cu(211), which points at a higher boost of n-propanol selectivity over ethanol selectivity for these sizes which have the highest local strain (Supplementary Fig. 21 and Supplementary Table 3). In addition, the sites extracted from the spheres show a linear correlation between local strain and d-band center energy (Supplementary Fig. 22), which indicate that strain impacts both electronic and structural local properties on the active sites.

Following the insight from the theory, we analyzed eventual strain differences in the as-synthesized catalysts and during operation (Fig. 3, Supplementary Note 3). Two-dimensional strain maps based on the HR-TEM images of single particles (Fig. 3a and Supplementary Fig. 23) and X-Ray diffraction at the ensemble level (Supplementary Fig. 24) for the as-synthesized NCs indicate a higher degree of strain for the Cu-Sph catalysts, with the Cu-S7 showing a higher overall strain (higher density of strained regions in blue color). EXAFS analysis of the as-prepared Cu NCs (Supplementary Fig. S25) and during CORR (Fig. 3b-d, Supplementary Fig. S26, Supplementary Table 4) agree with this observation. All samples are metallic Cu during operation. A shift of the Cu-Cu bond length (R) is observed in the Cu-Sph compared to Cu-Cube and Cu-Octa (Fig. 3b). The Cu-Cu bond length of Cu-Cube and Cu-Octa closely matches the one of the bulk Cu foil (2.541 Å). A deviation from this value occurs for all the Cu-Sph samples with an elongated bond length of 2.545 Å for Cu-S80 and Cu-S34 and a contracted bond length of 2.533 Å for Cu-S7 (Fig. 3c, Supplementary Table 4). This change results in a bigger relative strain (DR/R) for the Cu-Sph compared to the Cu-Octa and Cu-Cube, with the highest value for Cu-S7 (Fig. 3d). The lowering intensity and increasing broadening of the signal in the k-R Wavelet transformed-EXAFS (WT-EXAFS) contour maps going from Cu-Octa and Cu-Cube to Cu-Sph7 indicates a larger distribution of the Cu-Cu bond length (Fig. 3e), in agreement with the histograms from NN-MD in Fig. 2c.

Overall, the differences among the samples are certainly subtle, due to the substantial contribution from the bulk in the size regime of the Cu NCs used in this work. In-situ and operando strain measurements are experimentally challenging, especially for nanomaterials.⁴¹ Yet, the experimental data corroborates the theory simulations pointing at a higher strain in the propanol-selective Cu-Sph catalysts compared to Cu-Cube and Cu-Octa even during CORR.

Inspired by this new insight, we hypothesized that smaller Cu NCs (i.e. more strained) would exhibit an even higher selectivity for n-propanol. Thus, we designed a synthesis for Cu sphereswith a diameter of ~4.0 nm in size (Cu-S4, Fig. 4a). Cu-S4 exhibited a FE for n-propanol of 34.8±1.42% stable for at least 12 hours (Fig. 4b, Supplementary Fig. 27). This FE for n-propanol is 1.5 times higher compared to Cu-S7 when tested under the same conditions at 100 mA/cm², which corroborates a clear trend of increasing selectivity towards n-propanol as the size decreases (Fig. 4b, Supplementary Table 4). Having excluded a major impact of other factors (i.e. catalyst reconstruction, surface oxidation, potential and mass transport effects), this size-dependent trend strengthens the hypothesis that strain effects are key in boosting n-propanol production in CORR. Comparison with commercial Cu NCs in a similar size regime indicates a unique behavior of the colloidally synthesized Cu NCs (Fig. 4b, Supplementary Fig. 28). Strain induced by the synthesis method itself or the wider size distribution mitigating size-dependent effects can both explain the lower n-propanol selectivity of the commercial Cu NCs.

The Cu-S4 exhibit an increase of the FE for n-propanol to 39.6±1.4 % with a corresponding partial current density of 118±4.2 mA/cm² when tested at 300 mA/cm² (Fig. 4c, Supplementary Fig. 27). This n-propanol production rate is ten times higher than the best reported Cu catalyst to date (Fig. 4c and Supplementary Table 5) and superior to some of those reported for Cu doped with noble metals (Supplementary Fig. 29, and Supplementary Table 5). Cu-S4 exhibits also the highest ratio between the FE of n-propanol and of C₂(Fig. 4d and Supplementary Fig. 29), further indicating that copper with the highest strain can promote the coupling reaction between C₁ and C₂ towards C₃ compounds. This insight might open new reactivity pathways towards other multi-carbon products in the future.

Overall, this work demonstrates that a precise control on the size and morphology of Cu nanostructures enables an enhanced n-propanol electrosynthesis without the use of noble metals. The results highlight the importance of catalyst design and inspire future work in catalyst engineering towards carbon neutral manufacturing of chemicals.

Synthesis of colloidal Cu NCs

Cu NCs were synthesized following reported protocols.^47,48

Cu-Cube: Tri-n-octylphosphine oxide (TOPO, 24 mmol, 9.37 g) was mixed with oleylamine (OLAM, 117 ml) in a 3-neck flask and degassed under vacuum at room temperature. Copper(I) bromide (CuBr, 5 mmol, 0.71 g) was then added to the solution under N₂ flow. The resulting solution was heated to 260 °C and held at this temperature for 1 h.

Cu-S80 and Cu-S34: TOPO was substituted by tri-n-octylphosphine (TOP) in the same synthetic protocol used for the Cu-Cube. For Cu-S34, TOP (0.450 mL) was added together with CuBr (86 mg) and OLAM (7 mL) in a 3-neck flask and the reaction mixture was degassed. The resulting solution was heated to 270 °C and held at this temperature for 1 h. By varying the amounts of the same reagents, Cu-S80 could be obtained. Specifically, TOP (3.5 mL), CuBr (0.92 mg) and OLAM (117 mL) were mixed in a 3-neck flask and the rest of the procedure was kept the same as described for Cu-S34.

Cu-Octa: TOP (0.450 mL), CuBr (116 mg) and OLAM (15 mL) were added to a 3-neck flask and degassed. The rest of the procedure is the same of the one reported for Cu-S34 and Cu-S80.

Cu-S7 and Cu-S4: trioctylamine (20 mL) was added to a 3-neck flask and degassed under vacuum at 130 ºC for 1 hour. The flask was then refilled with N₂ gas and cooled to 50 ºC. Tetradecylphosphonic acid (270 mg, 1 mmol) and copper(I) acetate (245 mg, 2 mmol) were added in the flask, and the mixture was heated to 180 °C and held for 30 minutes. After 30 minutes, the mixture was heated to 270 °C and held for 30 min to obtain Cu-S7. The temperature was set to 230 °C to obtain Cu-S4 and the reaction quenched by removing the heating mantle as soon as the set temperature was reached.

Additional details on the Cu NCs synthesis can be found in the Supplementary Information.

Electrochemical measurements

Electrodes were prepared by air brushing dispersions of Cu NCs in hexane solvent on gas diffusion layer (GDL) with area of 1.33 cm². Additional details on the electrode preparation are reported in the Supplementary Information. A flow cell electrolyzer was used for the electrocatalytic testing.²⁸ Ag/AgCl electrode (leak free series, Innovative Instruments, Inc.) were used as the reference electrode, and anionic exchange membrane (Fumasep FAB-PK-130) was interposed between the anolyte and the catholyte compartments, as counter electrode a nickel mesh (Mc Master–Carr, 100x100 mesh size) was used. Chronopotentiometry measurements were performed with a potentiostat Biologic SP-300. A typical experiment was run for around 75 min. A gas chromatograph (GC 8610C, SRI instruments) equipped with a HayeSep D porous polymer column, thermal conductivity detector, and flame ionization detector was used for the analysis of gaseous products. Gas sampling was performed at regular intervals of 10 minutes. High-performance liquid chromatography (HPLC) or NMR were used for the analysis of the liquid products. Further experimental details can be found in the Supplementary Information.

Material Characterization

Low resolution TEM images were acquired on a FEI Tecnai-Spirit at 120 kV. The as-synthesized materials were drop-casted on a copper TEM grid (Ted Pella, Inc.) prior to imaging. HRTEM images were acquired on a double Cs-corrected FEI Titan Themis 60 – 300 operated at 300 kV. GPA was performed in Digital Micrograph version 3.52 using a GPA plugin available at https://er-c.org/index.php/software/stem-data-analysis/gpa/.^49,50,51

XAS experiments were performed at the Swiss-Norwegian beamlines BM31 at the European Synchrotron Radiation Facility in Grenoble, France. The samples were prepared in the same way of the sample used for the electrocatalytic testing with a loading of 100 mg/cm² and with a similar cell. Only the gas compartment was modified so that a Kapton foil could be introduced to allow X-ray penetration. The standards Cu₂O and CuO were prepared by using pressed pellets with the sample diluted in a light matrix such as boron nitride or cellulose to obtain an appropriate thickness. The measurements were carried out in fluorescence mode at an incident angle of approximately 45°. A Si(111) double crystal monochromator was used to condition the beam from the bending magnet source to a size of 3 mm (horizonatal) and 300 mm (vertical). Fluorescence X-ray absorption near edge structure (XANES) spectra were acquired using a Vortex single-element silicon drift detector with XIA-Mercury digital electronics and a time resolution of 60 sec per spectrum. Cu foil standard XAS spectrum was collected in transmission using ionization chambers for transmission detection. The resulting XAS data were reduced and normalized using Athena and Larch package.^52,53

Computational details

Neutral-network potentials are employed in classical molecular dynamics (NN-MD) for Cu NCs of different shapes (cube, octahedra, sphere) and sizes (2.5, 5.0, and 7.6 nm) were performed using Large-scale Atomic/ Molecular Massively Parallel Simulator (LAMMPS) code⁵⁴ with the NN interface from a neural network potential package (n2p2).^55,56 The NN-MDs were run for 100 ps for reach equilibrium in the canonical ensemble (NVT) using our constructed Behler-Parrinello-type HDNNP.^44,57 The sites of interest for reactivity study were selected considering coordination number and strain analysis (see Supplementary Information), and cut from NN-MD final structure as a 12x12x6 Å³-edge cube with the active site centered on the top facet. They were further placed as adclusters on top of Cu(100) and Cu(111) 3-layer surfaces using DockOnSurf⁵⁸ to avoid electronic structure embedding instabilities. DFT simulations were carried out with Vienna Ab Initio Simulation Package (VASP 5.4.4)^59,60 to compute adsorption energies of key intermediates. The exchange functional used was the Perdew-Burke-Emzerhof (PBE).⁶¹ Dispersion was included though the DFT-D2 method^62,63with our reparametrized C₆ coefficients for Cu atoms.⁶⁴ Inner electrons were represented by Projector Augment Wave (PAW),^65,66while the valence monoelectronic states were expanded as plane waves with a kinetic energy cutoff of 450 eV. In the final slabs, the vacuum along the z direction was at least 10 Å. We sampled the Brillouin zone by a Γ-centered k-points mesh from the Monkhorst-Pack method⁶⁷ with a reciprocal grid size smaller than 0.03·2π Å^–1. The slab models were asymmetric, and thus the dipole correction was applied.⁶⁸For all the investigated systems, structures were relaxed using convergence criteria of 0.03 eV/Å and 10⁻⁵ eV for the ionic and electronic steps, respectively. Reported adsorption energies are obtained using CO₂(g), H₂(g), H₂O(g) and clean surfaces as energy references. The Computational Hydrogen Electrode (CHE) was used for obtaining the relative energy between H⁺ and gas-phase H₂ at U = 0.0 V and pH = 0.^69,70

Conflicts of interest

There are no conflicts to declare.

Acknowledgements

This publication was created as part of NCCR Catalysis (grant number 180544), a National Centre of Competence in Research funded by the Swiss National Science Foundation. E.I.A., Z.L. and N.L. acknowledge financial support from the Spanish Ministry of Science and Innovation (PRE2021-097615, PID2021-122516OB-I00, Severo Ochoa Centre of Excellence CEX2019-000925-S 10.13039/501100011033) and the Barcelona Supercomputing Centre-Mare Nostrum (BSC-RES) for providing generous computational resources. The authors thank Aurélien Bornet, Pascal A. Schouwink and Emad Oveisi for their help with the NMR, XRD and TEM measurements, respectively. The staff at the BM28 (XmaS) beamline at the European Synchrotron Radiation Facility (ESRF) in Grenoble are acknowledged for their support. Access to the beamline was granted through the ESRF under proposal a311213.

Data availability

All data are available in the main text or the Supplementary Information. The data of the main text will be available in Zenodo upon acceptance.

Supporting DFT datasets are available in ioChem-BD⁷¹at
https://iochem-bd.iciq.es/browse/review-collection/100/68301/2ee66f560d478ddb190e6e82. All other raw data are available from the corresponding author upon reasonable request.

Author contributions

M.W. and A.L. designed and performed the experiments related to catalyst synthesis and electrocatalysis. A.L performed all the material characterization, both ex-situ and operando. E.I.A, Z.L. and N.L. designed and carried out the theoretical part of the work. K.K. and D.S. provided assistance with the data collection and contributed to the analysis of electron microscopy and XAS, respectively. P.A, L.Z, J.L. helped with ICP, NC synthesis and NMR liquid product analysis respectively and contributed with daily discussions. R. B. conceived the idea and coordinated the project. All the authors contributed to discussions and the writing of the manuscript.

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Colloidal copper nanospheres boost propanol electrosynthesis from CO

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Colloidal copper nanospheres boost propanol electrosynthesis from CO

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