Experimental and Density Functional Theory Corroborated

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Surfaces, Interfaces, and Catalysis; Physical Properties of Nanomaterials and Materials

Experimental and DFT-corroborated Optimization of Durable Metal Embedded Carbon Nanofiber for Oxygen Electrocatalysis Yoonhoo Ha, Sinwoo Kang, Kahyun Ham, Jaeyoung Lee, and Hyungjun Kim J. Phys. Chem. Lett., Just Accepted Manuscript • Publication Date (Web): 22 May 2019 Downloaded from http://pubs.acs.org on May 22, 2019

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The Journal of Physical Chemistry Letters

Experimental and DFT-corroborated Optimization of Durable Metal Embedded Carbon Nanofiber for Oxygen Electrocatalysis Yoonhoo Ha,†,※ Sinwoo Kang,‡,※ Kahyun Ham,‡ Jaeyoung Lee,*,‡,§ and Hyungjun Kim*,† †Department of Chemistry, Korea Advanced Institute of Science and Technology (KAIST), 291 Daehak-Ro, Daejeon 34141, Republic of Korea ‡School of Earth Sciences and Environmental Engineering, Gwangju Institute of Science and Technology (GIST), 123 Cheomdangwagi-Ro, Gwangju 61005, Republic of Korea. §Ertl Center for Electrochemistry and Catalysis, Gwangju Institute of Science and Technology (GIST), 123 Cheomdangwagi-Ro, Gwangju 61005, Republic of Korea.

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ABSTRACT

There is a growing need for widespread deployment of hydrogen and fuel cell technology for the realization of a sustainable energy landscape. However, due to the high price of platinum (Pt) catalysts, it is necessary to develop highly active and stable non-Pt oxygen reduction reaction (ORR) catalysts. Here, we describe a rational design of nonnoble metal-embedding and nitrogencontaining carbon nanofibers (M-CNF) catalysts. Using a combined experimental and computational approach, we establish an ORR activity volcano of M-CNF using the work function of the embedded metal as the descriptor. Near the top of the activity volcano, the embedded metal is further optimized by tuning the Fe1-xCox alloy composition to simultaneously achieve high catalytic activity and durability. This work identifies the mechanistic importance of controlling the charge transfer between the metal and carbon layers, providing guidance for the design of non-Pt ORR catalysts using stable carbon-layer-protected metals.

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To date, platinum (Pt) or platinum-based alloys have demonstrated the highest catalytic activity toward oxygen reduction reaction (ORR) in fuel cells.1-5 Based on moderate oxygen binding strength on their surfaces, Pt and Pt alloys satisfy the Sabatier principle to accelerate the sluggish kinetics of ORR on fuel cell cathodes.6-8 However, the use of Pt also creates several critical drawbacks that limit the high durability and cost-effectiveness of the fuel cell catalyst, leading to a significant obstacle for the facile deployment of fuel cell technologies. Among the various attempts to overcome these hurdles by developing of non-Pt catalysts9-16, transition metal-nitrogen-carbon (Me-N-C) catalysts are considered to be one of the most promising alternatives reaching high ORR activity.17-21 A number of research efforts have been pursued to identify the chemical details of the catalytic active site in order to rationalize generalized design principles. Based on various spectroscopic measurements such as X-ray absorption and Mössbauer spectroscopies, the presence of N-doped carbon sites (CNx) and Ncoordinated Me centers (MeN4) has been suggested, both of which can catalyze ORR.22-25 However, the detailed roles of different catalytic active sites have been still not fully understood, and this problem is rendered even more challenging by the high chemical/structural heterogeneity of the Me-N-C catalysts prepared by different experimental fabrication techniques. Recently, our group has developed metal-embedded and nitrogen-containing carbon nanofibers (M-CNF) as non-Pt alkaline oxygen electrocatalysts.26-34 CNFs achieve a stable accommodation of the metal nanoparticles and disperse them homogenously with carbon layers surrounding the nanoparticles. This action contributes to stability by preventing direct contact with the electrolyte that induces chemical degradation.5, 35 The metal particles that support the N-doped carbon layer enhance graphitization and conductivity.32


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In this work, we investigate the ORR activity of various M-CNF catalysts using a combination of experimental and computational studies. We find that the activity of oxygen reduction at the MCNF catalysts shows a volcano-like relationship with the work function of the embedded metals as relevant descriptor. On the basis of this mechanistic understanding of the role of metals in MCNF catalysts and the volcano map of ORR activity, we tune the embedded metals to develop an optimal M-CNF catalyst with high activity and prolonged stability. To obtain a systematic understanding of ORR activity arising from the embedded metal core, we synthesized CNFs embedding various types of metals/alloys (M-CNFs, M = Ag, Fe, Co, Ni, AgFe alloy, and FeCo alloy) using electrospinning and ball-mixing processes. First, from the transmission electron microscope (TEM) images shown in the insets of Figures 1 and S1, we confirm that the core metal particles with sizes in the 12-20 nm range are well-dispersed in MCNF due to homogeneous mixing during the fabrication process and are also fully encapsulated

Figure 1. ORR polarization curve for different embedded metals in CNF in O2-saturated 0.1M KOH with the rotating speed of 1600 rpm; (inset) TEM image of encapsulated Co metal in several graphite layers on the surface of Co-CNF.


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by the graphitized carbon layers around the rim of the CNF. This clearly demonstrates that the metal nanoparticles are entirely embedded in the CNF, making a direct participation of metal nanoparticles in ORR likely, in agreement with a previous study.35 Secondly, we investigate the crystallinity of the M-CNFs by means of the X-ray diffraction (XRD) patterns (Figure S2). We find that face-centeterd cubic structures are dominant (Ni (JCPDS: 04-1027), Co (JCPDS: 89-4307), Ag (JCPDS: 04-0783)) while the Fe-CNF consists of mainly Fe3C (JCPDS:77-0255). Considering the catalytic graphitization in heat treatment, we assume that the three metals are dissolved in the amorphous carbon phase, then separated from carbon during cooling step. However, iron combined with carbon and transformed to carbide form.36 In case of AgFe and FeCo alloys, we find that there is a shift of main peak which is located at 43º compared to the Ag (111) peak and Co (111) peak, respectively. However, peaks from metal redox peak are not observed in cyclic voltamoggrams (CVs) except for Co-CNF (Figure S3). Most importantly, we observe a distinct dependence of the ORR activity on the embedded metal in CNF. Figure 1 shows the ORR polarization curves for the prepared M-CNFs that were obtained using linear sweep voltammetry (LSV) conducted in O2-saturated 0.1M KOH with rotating speed of 1600 rpm. The potential at a given current density of 0.3 mA/cm2 shows that the ORR activity follows the trend of Ni-CNF < Ag-CNF < Ag0.5Fe0.5-CNF < Co-CNF < Fe0.3Co0.7-CNF < Fe0.5Co0.5-CNF < Fe0.7Co0.3-CNF < Fe-CNF. We also find that this trend is consistent at different rotating speeds, 400, 900, 1600, and 2500 rpm (Figure S4). It was previously suggested that the metal nanoparticles influence the surrounding carbon layers by electron transfer (ET).37-38 The amount of ET between the graphitic layers and the embedded metal nanoparticle is primarily determined by the relative difference of their Fermi levels. As schematically shown in the level alignment plot of Figure 2a, when the work function (W) of the


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embedded metal nanoparticle decreases (i.e., when the Fermi level of the metal increases), more electrons are likely to be transferred to the surrounding graphitic layers.

Figure 2. (a) Schematic band alignments between the metal and nitrogen-doped graphene (N-Gr) of the M-CNF catalyst for different work functions. Direction and the amount of charge transfer can be determined in terms of the relative Fermi level between the metal surface and the N-Gr. (b) Volcano plot of the potential at a current density of 0.3 mA/cm2 as a function of the calculated work function (WDFT) using the density functional theory. The WDFT was obtained from the optimized close-packed surface models of the embedding metals, except for M = Fe case. For FeCNF, we calculated the WDFT of Fe3C based on the XRD result (Figures S2 and S8). Notably, that we find that the potential at 0.3 mA/cm2 and the current density measured at 0.85 VRHE follow a volcano-curve behavior with respect to WDFT, which is the W calculated from density functional theory (DFT) as shown in Figures 2b and S5, respectively. This suggests that the work funciton of the embedded metal can serve as a good ORR activity descriptor of M-CNF catalysts.


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Using DFT calculations, we further elucidate a connection the metal work function and the amount of ET with the oxygen binding energy (EO) that is the most widely accepted ORR activity descriptor. From DFT calculations on the interfacial systems shown in Figure S6, we find that the magnitude of the surface area normalized ET from metal to N-doped graphene (QET) is strongly correlated with the change in WDFT (Figure 3a). Using Bader charge analysis39, we calculated the charge of the N-doped graphene layer, which is normalized by the metal-graphene interfacial area,

Figure 3. (a) Surface area normalized electron transfer amount (QET) as a function of the DFTcalculated work function (WDFT) of metal surfaces. QET is quantified using Bader charge analysis. DFT-optimized distances between the metal surface and the graphitic layer are shown in parenthesis. (b) Calculated oxygen binding energies (EO) at the N-doped carbon site of the graphene layer (see Figure S6 and Table S3) as a function of QET. EO is defined by the reaction energy of H2O + *  *O + H2.


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yielding QET. QET for Ni, Co, Fe0.3Co0.7, Fe0.5Co0.5, Fe0.7Co0.3, Fe and Ag0.5Fe0.5 show a linear correlation with WDFT. For Ag, which has relatively small WDFT values, DFT calculations show virtually no ET from the metal to the carbon layer (Table S2). This is attributed to the different nature of the chemical interaction between the surface and N-doped graphene. Less chemically active surfaces containing Ag yield larger separation distances of around 2.7 Å, and significantly suppress the ET due to the minimized orbital overlaps while in the other cases the separation distances are around 2 Å (Figure S6). Figure 3b also shows that the QET is correlated with the EO of the graphitic layers. Although the correlation is slightly rendered, which is presumably due to the strain imposed during the DFT simulation cell construction of interfacial systems, we find a trend of increasing EO with increasing QET. Therefore, we conclude that the embedded metal modulates (1) the oxophilicity, and thereby (2) the ORR activity of the carbon layers by transferring electrons. This explains why the W of the embedded metal is a suitable ORR activity descriptor for the M-CNF catalysts as well. With the activity volcano in hand, we now optimize the catalytic performance of the M-CNF catalysts. Since the top of the volcano is located at W  4.6 eV, we investigate the Fe1-xCox-CNF catalysts with x ranging from 0 to 1 in detail. Assuming for simplicity that W of FeCo alloy follows Vegard’s law, we find that the more Fe content results in a better ORR activity since Fe-Co alloys locate at the right leg of the volcano. Indeed, we find ORR activity to increase nearly monotonically with increasing Fe content (dark bars in Figure 4a and Figure S7). This finding implies that Fe-CNF is located at the top of the activity volcano. We further investigate the change in the ORR activity after 20,000 potential cycles in 0.6 V – 1.0 V range (open bars in Figure 4a). Fe-CNF showed the largest activity loss


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Figure 4. (a) Trends of the current density of Fe1-xCox-CNF @ 0.85 V with a number of potential cycles; (b) Change in the normalized ORR current density of Fe1-xCox-CNF with increasing Co content of x from 0 to 1. Comparison of the current densities before (●) and after 20,000 potential cycles in 0.6 V - 1.0 V ( ▽). The values before the current density line are the initial current densities of Fe1-xCox-CNF after a full cycling test despite its highest initial activity. Furthermore, we observed that the activity loss decreases in the presence of Co. Considering that carbon oxidation of Me-N-C catalysts occurs in the high potential range over 0.9 VRHE40, demetallation is considered to be more relevant to the observed activity loss. As such, the formation of carbide species, which will facilitate the metal diffusion into the carbon layers and obstruct the full chemical protection of the embedded metal, can be intimately related to the stability degradation of the M-CNF catalysts.


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However, when Co is added to the Fe lattice, the carbide formation tendency is noticeably suppressed (Figure S2b), resulting in enhanced stability. Considering the trade-off relation between the initial activity and the stability (Figure 4b), we thus conclude that the Co content of 10% is optimal for dramatically reducing the activity loss after 20,000 cycles from 63.4% (x = 0) to only 32.4% (x = 0.1), while showing a high initial activity of 1.293 mA/cm2 that is still 90% of the value at the top of the activity volcano. In summary, we elucidated the role of the embedded metal of M-CNF catalysts using a combined experimental and computational approach. We established a volcano-like correlation of ORR activity and the work function of the embedded metal. We find that the amount of the electron transfer between the metal and carbon layer is described by the metal work function of the metal that modulates the oxygen binding energy and ORR activity of the carbon layers. Using the activity volcano, we optimized the chemical composition of the M-CNF catalyst and found Fe0.9Co0.1-CNF be a suitable stable and active ORR catalyst. We expect that the current study will provide guidance for a rational design of nonnoble metal-based electrocatalysts to approach the high catalytic activity and product selectivity required for the commercialization of fuel-cell technology.41

METHODS Preparation of M-CNFs, Electrospinning and Ball-Milling Process 4 g of polyacrylonitrile (PAN, sigma-aldrich) and 1.2 g of metal precursor were mixed in N,N-dimethylformamide (DMF, Junsei) for 8 hrs until it formed the homogeneous polymer solution. Silver(I) nitrate (AgNO3, sigma-aldrich), Ni(II) acetylacetonate (Ni(Acac)2, sigma-aldrich), Co(III) acetylacetonate (Co(Acac)3, sigma-aldrich) and Fe(III) acetylacetonate (Fe(Acac)3, sigma-aldrich) were used as metal precursor. In the case of alloy M-CNFs, we controlled the metal ratio in M-CNF by the


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weight ratio of metal precursors. Then, high electric voltage (24 kV) was applied between a drumlike collector and a syringe which contained well-mixed polymer solution with metal precursor. The collector was rotated with 500 rpm of rotating speed to collect the electrospun nanofibers. All these steps were carried out at room temperature and relative humidity under 30%. The ascollected electrospun nanofiber was pyrolyzed under 280 ºC in air with 1 ºC/min of ramping rate and kept for 1 hr for stabilization. Continually, pyrolyzed electrospun nanofiber was carbonized in N2 atmosphere at 1000 ºC with 5 ºC/min of ramping rate and kept for 1 hr. To uniformize the length of M-CNF, the as-prepared M-CNF was pulverized using a ball mill with 5 mm diameter zirconia beads in a zirconia container. The ball-milling step was repeated 10 times with a set of 20 min for milling and 10 min for idle. Characterization of M-CNFs The morphologies of M-CNF were characterized by a transmission electron microscope (TEM; JEOL JEM-2100F). The crystal structures on the M-CNF were investigated with X-ray diffraction (XRD; Rigaku Miniflex II). Electrochemical measurements were evaluated using a three-electrode system connected to a potentiostat/galvanostat (Biologic, VSP). Pt wire was used as the counter electrode and Hg/HgO was used as reference electrode dipped into 1M KOH solution. The working electrode was prepared by the drop-coating method with catalyst ink. The ink was fabricated by dispersing 10 mg of M-CNF powder and 10 μL of 10wt.% nafion dispersion solution (Sigma-Aldrich) in 1.2 mL of deionized water and 0.8 mL of isopropyl alcohol (Junsei) in the sonication bath. After 30 minutes, 9.9 μL of catalyst ink was loaded on glassy carbon in a rotating disk electrode (loading amount = 0.2 mg/cm2, area = 0.2475 cm2). Cyclic voltammograms (CV) were obtained at scan rate of 20 mV/s from 1.2V to 0.2V versus reversible hydrogen electrode (RHE) in 0.1M KOH electrolyte deaerated with nitrogen gas for 30 min at 25 ºC. To evaluate ORR activity of M-CNF, linear sweep voltammetric (LSV) measurement


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was conducted in O2-saturated 0.1M KOH with rotating speed of 2500, 1600, 900 and 400 rpm. Then, we gained ORR polarization curve by subtracting from LSV performed in O2 to N2, eliminating the peaks of other reaction such as capacitance originated from carbon and metal redox reaction. To evaluate the durability of M-CNFs, we repeated potential cycling ranging from 0.6 V to 1.0 V (vs. RHE) with the 50 mV/s in N2-saturated 0.1M KOH. LSV for ORR polarization curve was measured after every 1, 100, 1k, 3k, 5k, 10k, 15k and 20k potential cycling. Computational Details We performed spin-polarized Density functional theory (DFT) calculations using a revised Perdew-Burke-Ernzerhof (RPBE)42 functional with D3 dispersion corrections43 as implemented in the Vienna ab-initio software package (VASP)44. We used projector-augmented-wave (PAW)45 method with a plane-wave cutoff energy of 450 eV. We prepared bulk unit cells of various metals (Ag, Co and Ni), iron carbide (Fe3C), body-centeredcubic based iron-cobalt alloys46 (Fe11Co5, FeCo, Fe5Co11) and Ag-Fe alloy with R-3M symmetry (Figure S8). For the optimizations of the bulk unit cells, the reciprocal spaces were sampled using the Monkhorst-Pack scheme by employing the k-mesh sizes summarized in Table S1. To verify the structure of the bulk unit cells, we carried out a powder XRD simulation of the optimized bulk unit cells. In case of the bulk unit cell of Ag-Fe alloy which has not been reported, we chose AgFe with R3M symmetry model as a Ag-Fe bulk unit cell after examining DFT energetics of the R3M model and three Ag16Fe16 random alloy models consisiting of 32 atoms in the face-centered cubic unit cell (Figure S9). Based on the optimized bulk structures, we prepared surface slab models consisting of three or four layers of close-packed surfaces with an additional vacuum layer of 25 Å along the c-axis. Then the slab models were optimized with applying dipole correction along the c-axis, and fixing atoms at their bulk structure positions except for the topmost two layers. In case of the Fe3C(001) surface, we allowed the top three Fe layer and three C layers to be relaxed.47-


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Details about the cell dimensions and -centered k-meshes employed in DFT calculations are

listed in Table S2. We further investigated the interaction between a metal slab and a nitrogendoped graphene (N-Gr) monolayer. To quantify an amount of charge transfer between the metal surface and the N-Gr, we performed Bader charge analysis.39 Detailed DFT results are fully tabulated in Tables S1-S5.

ASSOCIATED CONTENT Supporting Information. The Supporting Information is available free of charge on the ACS Publications website at http://pubs.acs.org. TEM, XRD images, Volcano plots as a function of DFT-calculated work function, DFT-optimized structures of bulk and interfacial models, Trends of the catalytic activity as a function of composition ration, and optimized xyz coordinates. AUTHOR INFORMATION Corresponding Author * [email protected] (J. Lee) * [email protected] (H. Kim) Author Contributions ※Y. H. and S. K. contributed equally to this work. ACKNOWLEDGMENT


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We acknowledge Dr. Stefan Ringe (KAIST) for his fruitful discussions and also for helping us to proofread the manuscript. We also acknowledge the support by the New & Renewable Energy Core Technology Program of the Korea Institute of Energy Technology Evaluation and Planning (KETEP) granted financial resource from the Ministry of Trade, Industry & Energy, Republic of Korea (20153030031720). This research was also supported by Technology Development Program to Solve Climate Changes through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT (2018M1A2A2063861). REFERENCES (1) Huang, J.; Sen, R.; Yeager, E. Oxygen reduction on platinum in 85% orthophosphoric acid. J. Electrochem. Soc. 1979, 126, 786-792. (2) Toda, T.; Igarashi, H.; Uchida, H.; Watanabe, M. Enhancement of the electroreduction of oxygen on Pt alloys with Fe, Ni, and Co. J. Electrochem. Soc. 1999, 146, 3750-3756. (3) Stamenkovic, V. R.; Fowler, B.; Mun, B. S.; Wang, G.; Ross, P. N.; Lucas, C. A.; Marković, N. M. Improved oxygen reduction activity on Pt3Ni (111) via increased surface site availability. Science 2007, 315, 493-497. (4) Greeley, J.; Stephens, I.; Bondarenko, A.; Johansson, T. P.; Hansen, H. A.; Jaramillo, T.; Rossmeisl, J.; Chorkendorff, I.; Nørskov, J. K. Alloys of platinum and early transition metals as oxygen reduction electrocatalysts. Nat. Chem. 2009, 1, 552. (5) Lee, J.; Jeong, B.; Ocon, J. D. Oxygen electrocatalysis in chemical energy conversion and storage technologies. Curr. Appl. Phys. 2013, 13, 309-321. (6) Nørskov, J. K.; Rossmeisl, J.; Logadottir, A.; Lindqvist, L.; Kitchin, J. R.; Bligaard, T.; Jonsson, H. Origin of the overpotential for oxygen reduction at a fuel-cell cathode. J. Phys. Chem. B 2004, 108, 17886-17892. (7) Xu, Y.; Ruban, A. V.; Mavrikakis, M. Adsorption and dissociation of O2 on Pt− Co and Pt− Fe alloys. J. Am. Chem. Soc. 2004, 126, 4717-4725. (8) Stephens, I. E.; Bondarenko, A. S.; Grønbjerg, U.; Rossmeisl, J.; Chorkendorff, I. Understanding the electrocatalysis of oxygen reduction on platinum and its alloys. Energ. Environ. Sci. 2012, 5, 6744-6762. (9) Wu, G.; More, K. L.; Johnston, C. M.; Zelenay, P. High-performance electrocatalysts for oxygen reduction derived from polyaniline, iron, and cobalt. Science 2011, 332, 443-447.


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Experimental and Density Functional Theory Corroborated

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