The oxygen reduction reaction (ORR) on platinum (Pt) electrodes in acidic electrolytes can occur via two pathways, with the four-electron (4e−) pathway predominantly prevailing. However, the research on the fundamental reasons for the switching of reaction pathways has largely focused on structure-activity relationships, while neglecting the impact of mass transport. The influence of macroscopic mass transport from the bulk to the diffusion layer has been studied by controlling the rotating speed. However, regulating mesoscopic transport by altering macroscopic hydrodynamics remains challenging. In this study, we varied the loading of Pt nanoparticles to produce Pt with nearly identical physicochemical properties but differing interparticle distances. Increasing the interparticle distance from 58.6 nm to 117.0 nm significantly enhanced the selectivity towards H2O2 in an acidic environment, with the selectivity increasing from 4.6% to 81.5%. Utilizing electrochemical im-pedance spectroscopy, we demonstrate that interparticle distance modulates the O2 diffusion field around Pt nanoparticles, consequently affecting H2O2 adsorption and determining the electron transfer numbers of the ORR. Our findings highlight that mesoscopic mass transport influences not only the total current but also the reaction pathways. These results emphasize the importance of the spatial distribution density of nanoparticles in regulating mesoscopic mass transport, thereby controlling the adsorption of intermediates and enhancing electrocatalytic performance.
Article
Interparticle Distance-Driven Diffusion Field Transforming Selectivity in Oxygen Reduction Reaction
https://doi.org/10.21203/rs.3.rs-4864770/v1
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The electrocatalytic oxygen reduction reaction (ORR) on Pt-based electrodes has grown significantly due to the increasingly demands of proton exchange fuel cells.1,2 Extensive experimental studies of the ORR on well-defined Pt metal surfaces in acidic media have established clear trends in their electrocatalytic activity across various well-defined facets.3,4 Nevertheless, H2O2 generation remains unclear, resulting in reduced electron transfer efficiency and degradation of the exchange membrane, posing safety and durability concerns in the practical application of fuel cells. On the Pt basal facets of single crystals, a minute amount of H2O2 was detected in the potentials above hydrogen deposition by applying the rotating ring-disk electrode,3 proving that direct pathway with 4e− transfer prevails without involving soluble H2O2. The slight difference in H2O2 selectivity results from the structure effect on reaction pathways. Much progress has been made in understanding the selectivity of 2e−-reduction to H2O2 versus 4e−-reduction to H2O on metal surfaces based on the assumption that catalytic rates are directly governed by the adsorption strength of the surface intermediates in the rate-limiting step.1,5–7 While the reaction pathway on isolated Pt atoms can be modulated toward 2e− pathway mostly by regulating its coordination environment.8,9
Unfortunately, the selectivity of H2O2 on Pt nanoparticles in practical applications varies in a broad range, which has been contributed to the effect of surface structure, particle size, interparticle distance and mass loading.10–15 While the effect of mass transport has been overlooked for a long time until Watanabe et al highlighted its importance.16 Chen et al. significantly increased the macroscopic mass transport coefficient to a level equivalent to that achieved on a Pt disk at over 108 rpm by using a Pt sub-micrometer electrode in H2SO4 electrolyte, resulting in an enhanced H2O2 selectivity of 25%.17 Behm et al regulated the mass transport conditions changing the loading of Pt nanoparticles, to increase the H2O2 yield.18 However, the particle size and interparticle distance were changed with Pt loading, increasing the difficulty and accuracy of mass transport effect.
To date, the underlying mechanisms causing puzzled H2O2 selectivity on Pt nanoparticles are primarily attributed to two factors: reaction pathways and transport of the involved species. The former dictates whether *H2O2 functions as the intermediate on catalyst surfaces. Much progress has been made in understanding the selectivity of the 2e− reduction to H2O2 versus the 4e− reduction to H2O on metal surfaces based on the assumption that catalytic rates are directly governed by the adsorption strength of the surface intermediates in the rate-limiting step.1,5,6 Mass transport determines whether soluble H2O2 can migrate away from the catalyst layer into the bulk electrolyte without further 2e− transfer forming H2O during diffusion. If H2O2 was initially generated and subsequently released from the Pt surface, only to be recaptured by another Pt nanoparticle within the catalyst layer, it would undergo further reduction to H2O. Consequently, H2O2 would not be identified in the bulk electrolyte, supported by the desorption-re-adsorption-reaction mechanism.19,20 Assuming that the increased possibility of H2O2 re-adsorption results from the greater number of neighboring Pt nanoparticles, the total generation of H2O2 would also increase before being recaptured by the adjacent Pt nanoparticles. In this case, it cannot be directly concluded that selectivity in H2O2 must be correspondingly enhanced. Besides the mass transport of H2O2, the significant difference in diffusion field of O2 have been realized and modeled mathematically at the nanoparticle level between sparse and dense distribution of nanoparticles, agreeing well with the observed current density in fuel cells,21–24 which has not been discussed in affecting H2O2 selectivity.
To study the diffusion field effect caused by interparticle distance, in this work, we firstly synthesized colloid of Pt nanoparticles, and then mixed with different amount of carbon black to control the interparticle distance (IPD), namely the spatial distribution density as depicted in Figure 1a. In this manner, materials containing high or low mass loadings of Pt nanoparticles maintained identical particle size and morphology to the maximum extent possible, differing only in IPD.
The actual mass loadings of Pt/C materials with nominal Pt mass loadings of 0.1%, 0.5%, 2%, 5%, and 10% are 0.1%, 0.5%, 2.1%, 7.0%, and 8.9%, respectively, determined by the induced coupled plasma-optical emission spectroscopy (ICP-OES). The IPD can be calculated according to the formula proposed by Watanabe et al (seeing supporting information).16 Dark field transmission electron microscopy (TEM) images in Figure 1b-f show the particle sizes (IPD) of 2.2 nm (117.0 nm), 2.3 nm (58.6 nm), 2.2 nm (24.9 nm), 2.5 nm (16.5 nm), and 2.5 nm (15.2 nm), respectively, for Pt/C with mass loading of 0.1%, 0.5%, 2.1%, 7.0%, and 8.9%. Using the IPD normalized by the diameter of Pt nanoparticles as subscripts, the five materials above are denoted as Pt54, Pt25, Pt12, Pt6.6, and Pt5.9 in order of decreasing dimensionless IPD(δ). In addition, Brunauer-Emmett-Teller surface areas (Figure S1) of the materials varied in a narrow range of 174.9 ~222.7 m2 g−1. X-ray diffraction patterns (Figure S2) and X-ray photon spectra (Figure S3) show that Ptδ materials remained similar grain size and surface chemical states on the materials of interest, respectively. The cyclic voltametric curves of Ptδ materials in Ar-saturated electrolyte show that the typical hydrogen adsorption-desorption features became apparent with the decrease of IPD of Pt nanoparticles (Figure S4).
Figure 2a shows that Pt5.9 and Pt6.6 reached the limiting current of 6 mA cm−2, while the rest of materials did not even at rather negative potentials, suggesting that the effective geometric area of Pt NPs of the catalyst layer is smaller the area of the substrate of glassy carbon for Ptδ with large IPD. Notably, the ring-current normalized by electrochemical active surface area increased with the IPD, indicating that more amount of H2O2 was generated on the Pt/C with larger IPD. The number of electron transfer and H2O2 selectivity in Figure 2b, calculated from Figure 2a, show that the electron transfer number increased with the decrease of IPD and H2O2 selectivity decreased with the decrease of IPD. For example, the electron transfer number on Pt54 are in the range from 2.5 to 2.7 below 0.6 V, suggesting that the oxygen reduction occurred mainly through 2e− pathway. While for Pt5.9, the electron transfer number was nearly 4, indicative of 4e− pathway to form H2O.
To reduce the uncertainty in quantifying H2O2 on the RRDE electrode,25 a gas-diffusion electrode was utilized in an electrolysis cell to enhance the production of H2O2 (Figure S5a), which was determined by Ultraviolet-visible absorption spectroscopy (Figure S5b), ensuring more precise analysis. Figure 3a illustrates that the concentration of H2O2 can reach 0.40 mM, accompanied by a notably high Faradaic efficiency of 81.5%. The result underscores the dominance of 2e− transfer in H2O2 formation. On Pt25, the H2O2 concentration slightly surpasses that on Pt54, attributed to the substantially higher overall current on Pt25. However, as the IPD diminishes from 117.0 nm to 58.6 nm, the Faradaic efficiency of H2O2 sharply declines from 81.5% to 4.6%. Notably, undetectable H2O2 generation occurs on Pt/C materials with an IPD below 24.9 nm. These findings highlight the extreme sensitivity of H2O2 production to IPD. Thus, it can be inferred that a direct 4e− transfer process occurs naturally on a Pt electrode in an acidic electrolyte when employing the Pt/C catalyst with a dense particle distribution. Furthermore, as depicted in Figure 3b, the concentration of H2O2 diminished with rising potential owing to a reduction in overall current. However, the Faradaic efficiency of H2O2 remained stable at approximately 80%, suggesting that 2e− pathway occurs in a wide potential range on Pt54. Based on the aforementioned findings, it is possible to alternate between the 2e− pathway and the 4e− pathway on Pt NPs by merely adjusting the IPD. In order to delve deeper into the impact of IPD on switching pathways, we conducted electrochemical impedance spectroscopy tests to examine the mass transport effects of oxygen. The total resistance of charge transfer decreased as the IPD decreased (Figure 4a), the applied potential decreased (Figure 4b and Figure S6), the loading amount increased (Figure 4c and Figure S7), and the rotating speed increased (Figure 4d and Figure S8), agreeing well with the LSV results in Figure 2a. Let us focus our attention on the evolution of the shapes of the impedance curves. The Nyquist plot transformed from an arc into a semicircle at a relatively low potential of 0.26 V for Pt54 which can be assigned to the charge transfer at the interface of ORR, whereas it occurred at higher potentials of 0.71 V for Pt25, and 0.81 V for Pt12. Interestingly, two semi-circles appeared at 0.71 V for Pt6.6 and Pt5.9. To elucidate the origins of the semi-circles, the catalyst loading was systematically increased. It was observed that the radius of the semi-circle decreased with the catalyst loading ranging from 20 μg to 100 μg for Pt54, Pt25, and Pt12. Conversely, for Pt6.6 and Pt5.9, Nyquist plots revealed two semi-circles at higher catalyst loadings of 50 μg. Furthermore, the radius of the semi-circle in the high-frequency (HF) region exhibited slight changes with decreasing rotation rate for both Pt6.6 and Pt5.9, while in the low-frequency (LF) region, it increased significantly. These observations suggest that the HF semi-circle is associated with charge transfer, determined by the reaction rate at the interface, while the LF semi-circle is influenced by the rate of oxygen transport. Notably, for Pt54, Pt25, and Pt12, characterized by large Pt interparticle distances, only one semi-circle was observed, indicating that the oxygen mass transfer rate did not become the limiting factor of the current. Bultel et al. proposed that for catalysts with a dense particle distribution, the catalyst phase can be regarded as a network of nanoparticles where the O2 diffusion field can be considered planar (Figure 4g). In contrast, for a sparse nanoparticle distribution, the catalyst phase should be viewed as discrete rather than continuous, resulting in a spherical diffusion profile at the particle level for the O2 diffusion field (Figure 4g).23,24
In the planar diffusion model, the mass transfer coefficient is proportional to the diffusion layer thickness, which can be regulated by a rotating disk, while in the spherical diffusion model, it is inversely proportional to the radius of the individual particles, which can be regulated by particle size. The mass transfer coefficient in the planar diffusion model is much smaller than in the spherical diffusion model (Figure 4g). According to the EIS results, the diffusion field can be considered spherical due to the sufficiently large distance between two Pt nanoparticles for Pt54. Consequently, the oxygen concentration around Pt nanoparticles with larger interparticle distances is higher than around those with smaller interparticle distances. In that case (Figure 4g), the higher O2 coverage on the Pt NPs with larger interparticle distances will be obtained due to high O2 concentration around Pt NPs.
The density functional theory calculations (DFT) in Figure 4f demonstrate that higher O2 coverage on the Pt(111) surface weakens the adsorption of H2O2, thereby facilitating its desorption. In other words, a high O2 concentration promotes O2 adsorption, which competes with H2O2 adsorption, causing more H2O2 to be expelled into the electrolyte. Consequently, the escaped H2O2 cannot be recaptured by the Pt surface, leading to the 2e−-reduction of O2 to H2O2 rather than the 4e−-reduction to H2O. Thus, it can be inferred that the high efficiency of H2O2 production for Pt54 can be attributed to the high concentration of O2 around the Pt surface caused by the spherical diffusion field of O2.
In summary, we disclose a particle proximity effect on the ORR: densely dispersed Pt nanoparticles achieve nearly 100% H2O selectivity, while sparsely dispersed Pt nanoparticles achieve the highest selectivity of 81.5% towards H2O2 via a 2e− electron transfer. This observed selectivity inversion can be attributed to variations in oxygen diffusion field influenced by the spatial distribution density of Pt nanoparticles. EIS results suggest that oxygen transport rate is not the limiting factor for materials with super large interparticle distance (IPD), but it is for materials with small IPD. DFT modeling indicates that increased O2 coverage affects the adsorption of the *H2O2 intermediate, reducing its adsorption and thus promoting H2O2 desorption from the Pt surface, explaining well that significantly increased H2O2 selectivity on the sparsely dispersed Pt nanoparticles.
Synthesis of Pt nanoparticles
0.52 g NaOH (98 %, Aladdin) and 1.04 g H₂PtCl₆ (Shanghai Jiuyue Chemicals, 99.9 %) were dissolved separately in 50 mL ethylene glycol (99 %, Aladdin), after stirring for 30 minutes. The two solutions were put into a three-neck flask, and stirring for about 5 minutes until thoroughly mixed. The mixture was heated at 160 ℃ for 3 hours in Ar with a flow rate of 120 mL min−1 with the stirring rate of 800 rpm. And the carbon black (Vulcan XC-72R) was mixed with the colloid solution under intense stirring of 24 h (the required amount of conductive carbon black was calculated by desired Pt mass fractions of 0.1%, 0.5, 2%, 5%, and 10%). Finally, the product was washed by centrifugation with deionized water more than 10 times, and dried in a vacuum oven at 60 oC for 48 h to obtain the home-made catalyst.
Characterizations
The powder X-ray diffraction (XRD) patterns were collected on a PANalytical Empyrean instrument (operated at 40 kV and 45 mA) with Cu Kα radiation with a wavelength of 1.5418 Å. X-ray photoelectron spectra (XPS) were collected on an X-ray photoelectron spectrometer (Thermo Scientific K-Alpha) using Al Kα. All experiments were performed under ultrahigh vacuum conditions with a beam size of 400 um, an operating voltage of 12 kV, and a filament current of 6 mA. Binding energies were calibrated by assigning the C 1s peak to 284.8 eV. High resolution transmission electron microscopy (HRTEM) images were acquired on a FEI-Talosf 200x microscope operating at 200 kV and equipped with a Ceta CMOS camera. Brunauer–Emmett–Teller (BET) surface area measurement was conducted on a Micromeritics instrument (Tristar II 3020). After vacuum degassing the catalyst at 250°C for 5 h, reversible physical adsorption of the adsorbate (N2) was performed at ultra-low temperatures. The Pt content of the catalyst was determined by the inductively coupled plasma optical emission spectrometer (ICP OES, ICAP 7000) from Thermo Fisher Scientific.
Electrochemical test
All glassware, including the electrochemical cells, were subjected to overnight soaking in aqua regia and subsequent cleaning before the electrochemical experiments. The glassware was boiled in DI water five times to thoroughly clean the glassware of residual aqua regia and other trace impurities. All electrochemical measurements were conducted at room temperature in the 5-neck flask (volume of 250 mL) with three-electrode by an electrochemical workstation (CHI760e, Shanghai Chenhua Co., Ltd.). ORR performance test was conducted on a Pine rotating disk electrode (RDE) instrument. A rotating ring-disk electrode (RRDE) coated with catalyst ink was used as the working electrode (disk area of 0.2475 cm² and collection efficiency of 37%), an Ag/AgCl and a graphite rod were used as the reference and counter electrodes, respectively. The catalyst ink was prepared in a ratio of water: ethanol: 5 wt% Nafion = 1:9:0.06. The testing procedure is as follows. First, cyclic voltammetry (CV) was performed with a scan rate of 50 mV s−1 in an Ar-saturated 0.1 M HClO₄ electrolyte. Then, the atmosphere was switched to O2, and the solution was bubbled with O2 at a flow rate of 200 mL min−1 for 20 minutes until saturation. Subsequently, typical RRDE experiments were conducted at a scan rate of 10 mV s−1, sweeping from 1.00 V to 0.02 V (vs. RHE). Cyclic voltammetry (CV) testing was conducted after a few minutes of operation to ensure the stability of current. The electrochemical impedance spectroscopy (EIS) test was conducted over an alternating current frequency range of 1 MHz to 0.01 Hz with an amplitude of 5 mV to obtain the impedance spectra of the catalyst under O2-saturated 0.1 M HClO4 at 1600 rpm.
Generation and measurement of H2O2
A gas diffusion electrode coated with catalyst ink was used as the working electrode, Ag/AgCl and a graphite rod served as the reference and counter electrode, respectively, to assemble the gas diffusion electrolysis cell (Figure S5a). 20 mL 0.1 M HClO4 as the electrolyte solution saturated through O2 at a flow rate of 40 mL min⁻¹ for 20 minutes, then an i-t test was conducted for 30 minutes. Afterwards 200 μL electrolyte solution was diluted by 4.8 mL 0.5 M H2SO4 and 5 mL 1 mM Ce(SO4)2. The absorbance of the diluted solution was measured by the UV-Vis spectrophotometer at a wavelength of 320 nm.
DFT calculations
A hemispherical cuboctahedral Pt37 nanoparticle with a Pt(111) facet was used as the theoretical computational model, with the cluster's size approaching 1 nm and its lattice strain resembling the bulk phase26. To simulate real bulk phase constraints, the model's outer atoms were immobilized, yielding seven accessible adsorption sites on the Pt(111) facet. Different quantities of O2 were adsorbed on the H2O2-precovered Pt(111) surface to investigate the impact of oxygen coverage on the adsorption of H2O2 on Pt surfaces.
Model geometry optimization and frequency calculations were performed using the ORCA 5.0.3 program package27, employing PBE0/def2-SV(P)28 for geometry optimization and PBE0/def2-QZVP28 for single-point energies calculations, with DFT-D329-30 dispersion correction and RIJCOSX acceleration via the def2/J auxiliary basis set31. Additionally, the SMD implicit solvent model (water)32 was used throughout to simulate solvent effects, reflecting the reaction's solvent environment.
The adsorption energy of H2O2 on the Pt(111) surface was calculated using the following formula:
References
(26) Wang, L.; Roudgar, A.; Eikerling, M., Ab initio study of stability and site-specific oxygen adsorption energies of Pt nanoparticles. J. Phys. Chem. C 2009, 113 (42), 17989-17996.
(27) Neese, F., Software update: The ORCA program system—Version 5.0. Wiley Interdiscip. Rev.: Comput. Mol. Sci. 2022, 12 (5), e1606.
(28) Weigend, F.; Ahlrichs, R., Balanced basis sets of split valence, triple zeta valence and quadruple zeta valence quality for H to Rn: Design and assessment of accuracy. Phys. Chem. Chem. Phys. 2005, 7 (18), 3297-3305.
(29) Grimme, S.; Antony, J.; Ehrlich, S.; Krieg, H., A consistent and accurate ab initio parametrization of density functional dispersion correction (DFT-D) for the 94 elements H-Pu. J. Chem. Phys. 2010, 132 (15).
(30) Grimme, S.; Ehrlich, S.; Goerigk, L., Effect of the damping function in dispersion corrected density functional theory. J. Comput. Chem. 2011, 32 (7), 1456-1465.
(31) Weigend, F., Accurate Coulomb-fitting basis sets for H to Rn. Phys. Chem. Chem. Phys. 2006, 8 (9), 1057-1065.
(32) Marenich, A. V.; Cramer, C. J.; Truhlar, D. G., Universal solvation model based on solute electron density and on a continuum model of the solvent defined by the bulk dielectric constant and atomic surface tensions. J. Phys. Chem. B 2009, 113 (18), 6378-6396.
ASSOCIATED CONTENT
Supporting Information.
TEM, electrochemistry, and calculations.
AUTHOR INFORMATION
Corresponding Author
F. Peng ([email protected])
Author Contributions
G. Yang designed electrochemical measurements and wrote the manuscript. J. Chen, D. Liu, Z. Wu and J. Yuan conducted the electrochemical measurements and calculations. F. Peng conceived and supervised the project and wrote the manuscript. Q. Zhang, H. Yu, and Z. Liu revised manuscript. All of the authors discussed the results and approved the manuscript
Notes
The authors declare no competing interests.
ACKNOWLEDGMENT
This work was supported by the National Natural Science Foundation of China (22008076 and 22272038). We extend our sincere gratitude to Dr Jun Huang at Forschungszentrum Jülich GmbH in Germany for his illuminating theoretical discussion on the concept of the EIS results.
- Kulkarni, A.; Siahrostami, S.; Patel, A.; Nørskov, J. K. Understanding Catalytic Activity Trends in the Oxygen Reduction Reaction. Chem. Rev. 2018, 118 (5), 2302–2312.
- Wu, Z.; Yang, G.; Zhang, Q.; Liu, Z.; Peng, F. Deciphering the High Overpotential of the Oxygen Reduction Reaction via Comprehensively Elucidating the Open Circuit Potential. Energy Environ. Sci. 2024, 17 (10), 3338–3346.
- Markovic, N. M.; Gasteiger, H. A.; Ross, P. N. Oxygen Reduction on Platinum Low-Index Single-Crystal Surfaces in Sulfuric Acid Solution: Rotating Ring-Pt(hkl) Disk Studies. J. Phys. Chem. 1995, 99 (11), 3411–3415.
- Gómez-Marín, A. Ma.; Rizo, R.; Feliu, J. M. Oxygen Reduction Reaction at Pt Single Crystals: A Critical Overview. Catal. Sci. Technol. 2014, 4 (6), 1685.
- Luo, M.; Koper, M. T. M. A Kinetic Descriptor for the Electrolyte Effect on the Oxygen Reduction Kinetics on Pt(111). Nat. Catal. 2022, 5 (7), 615–623.
- Greeley, J.; Stephens, I. E. L.; Bondarenko, A. S.; Johansson, T. P.; Hansen, H. A.; Jaramillo, T. F.; Rossmeisl, J.; Chorkendorff, I.; Nørskov, J. K. Alloys of Platinum and Early Transition Metals as Oxygen Reduction Electrocatalysts. Nat. Chem. 2009, 1 (7), 552–556.
- Exner, K. S. Steering Selectivity in the Four-Electron and Two-Electron Oxygen Reduction Reactions: On the Importance of the Volcano Slope. ACS Phys. Chem. Au 2023, 3(2), 190-198.
- Ni, B.; Shen, P.; Zhang, G.; Zhao, J.; Ding, H.; Ye, Y.; Yue, Z.; Yang, H.; Wei, H.; Jiang, K. Second-Shell N Dopants Regulate Acidic O2 Reduction Pathways on Isolated Pt Sites. J. Am. Chem. Soc. 2024, 146(16), 11181-11192
- Zhao, J.; Fu, C.; Ye, K.; Liang, Z.; Jiang, F.; Shen, S.; Zhao, X.; Ma, L.; Shadike, Z.; Wang, X.; Zhang, J.; Jiang, K. Manipulating the Oxygen Reduction Reaction Pathway on Pt-Coordinated Motifs. Nat. Commun. 2022, 13 (1), 685.
- Taylor, S.; Fabbri, E.; Levecque, P.; Schmidt, T. J.; Conrad, O. The Effect of Platinum Loading and Surface Morphology on Oxygen Reduction Activity. Electrocatal. 2016, 7 (4), 287–296.
- Inaba, M.; Yamada, H.; Tokunaga, J.; Tasaka, A. Effect of Agglomeration of Pt/C Catalyst on Hydrogen Peroxide Formation. Electrochem. Solid-State Lett. 2004, 7 (12), A474.
- Kluge, R. M.; Haid, R. W.; Riss, A.; Bao, Y.; Seufert, K.; Schmidt, T. O.; Watzele, S. A.; Barth, J. V.; Allegretti, F.; Auwärter, W.; Calle-Vallejo, F.; Bandarenka, A. S. A Trade-off between Ligand and Strain Effects Optimizes the Oxygen Reduction Activity of Pt Alloys. Energy Environ. Sci. 2022, 15 (12), 5181–5191.
- Inaba, M.; Zana, A.; Quinson, J.; Bizzotto, F.; Dosche, C.; Dworzak, A.; Oezaslan, M.; Simonsen, S. B.; Kuhn, L. T.; Arenz, M. The Oxygen Reduction Reaction on Pt: Why Particle Size and Interparticle Distance Matter. ACS Catal. 2021, 11 (12), 7144–7153.
- Perez‐Alonso, F. J.; McCarthy, D. N.; Nierhoff, A.; Hernandez‐Fernandez, P.; Strebel, C.; Stephens, I. E. L.; Nielsen, J. H.; Chorkendorff, I. The Effect of Size on the Oxygen Electroreduction Activity of Mass‐Selected Platinum Nanoparticles. Angew. Chem. Int. Ed. 2012, 51 (19), 4641–4643.
- Nesselberger, M.; Roefzaad, M.; Fayçal Hamou, R.; Ulrich Biedermann, P.; Schweinberger, F. F.; Kunz, S.; Schloegl, K.; Wiberg, G. K. H.; Ashton, S.; Heiz, U.; Mayrhofer, K. J. J.; Arenz, M. The Effect of Particle Proximity on the Oxygen Reduction Rate of Size-Selected Platinum Clusters. Nat. Mater. 2013, 12 (10), 919–924.
- Watanabe, M.; Sei, H.; Stonehart, P. The Influence of Platinum Crystallite Size on the Electroreduction of Oxygen. J. Electroanal. Chem. Interfacial Electrochem. 1989, 261 (2), 375–387.
- Chen, S.; Kucernak, A. Electrocatalysis under Conditions of High Mass Transport Rate: Oxygen Reduction on Single Submicrometer-Sized Pt Particles Supported on Carbon. J. Phys. Chem. B 2004, 108 (10), 3262–3276.
- Schneider, A.; Colmenares, L.; Seidel, Y. E.; Jusys, Z.; Wickman, B.; Kasemo, B.; Behm, R. J. Transport Effects in the Oxygen Reduction Reaction on Nanostructured, Planar Glassy Carbon Supported Pt/GC Model Electrodes. Phys. Chem. Chem. Phys. 2008, 10 (14), 1931.
- Heenen, H. H.; Pillai, H. S.; Reuter, K.; Bukas, V. J. Exploring Mesoscopic Mass Transport Effects on Electrocatalytic Selectivity. Nat. Catal. 2024.
- Lim, K. R. G.; Kaiser, S. K.; Wu, H.; Garg, S.; Perxés Perich, M.; Van Der Hoeven, J. E. S.; Aizenberg, M.; Aizenberg, J. Nanoparticle Proximity Controls Selectivity in Benzaldehyde Hydrogenation. Nat. Catal. 2024, 7 (2), 172–184.
- Bultel, Y. Study of Mass Transfer within the Active Layer of PEMFC. Electrodes at the Particle Level. ECS Proc. Vol. 1995, 1995–23 (1), 34–47.
- Bultel, Y. Concentration and Potential Distributions in the Active Layer of Proton Exchange Membrane Fuel Cell Electrodes. J. Appl. Electrochem. 2000, 30 (12), 1369–1376.
- Bultel, Y.; Ozil, P.; Durand, R. Modified Thin Film and Agglomerate Models for Active Layers of P.E. Fuel Cells. Electrochim. Acta 1998, 43 (9), 1077–1087.
- Bultel, Y.; Ozil, P.; Durand, R. Modelling of Mass Transfer within the PEM Fuel Cell Active Layer: Limitations at the Particle Level. J. Appl. Electrochem. 1999, 29 (9), 1025–1033.
- Zhou, R.; Zheng, Y.; Jaroniec, M.; Qiao, S.-Z. Determination of the Electron Transfer Number for the Oxygen Reduction Reaction: From Theory to Experiment. ACS Catal. 2016, 6 (7), 4720–4728.
There is NO Competing Interest.
