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Engineering of Carbon-Based Electrocatalysts for Emerging Energy Conversion: From Fundamentality to Functionality Yao Zheng, Yan Jiao, and Shi Zhang Qiao*
1. Introduction The rapid development of new clean energy technologies, such as fuel cells and water splitting may provide possible solutions for the continuously increasing global demand for energy over the last few decades.[1,2] The performances of these electrochemical energy-conversion devices strongly depend on the reaction rates of a series of electrochemical processes on their electrodes. The reactions include the electrocatalytic oxygen reduction reaction (ORR) and hydrogen oxidation reaction (HOR), which occur on the cathode and anode of a hydrogen fuel cell, and the hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) at the cathode and anode of a water splitting cell. Up to now, a variety of commercial high-performance electrocatalysts have been designed (mainly precious metals) to facilitate these reactions with favorable kinetics and therefore to achieve higher energy efficiency for a given device.[3,4] More strikingly, due to remarkable advances in density functional theory (DFT) and computing power, theoretical chemists have the capability to predict, screen, and design electrocatalysts with desirable activities, based on profound understanding of the nature of electrocatalytic processes.[5,6] At the same time, by Dr. Y. Zheng, Dr. Y. Jiao, Prof. S. Z. Qiao School of Chemical Engineering University of Adelaide Adelaide, SA 5005, Australia E-mail: [email protected] Prof. S. Z. Qiao School of Materials Science and Engineering Tianjin University Tianjin 300072, China
DOI: 10.1002/adma.201500821
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using state-of-the-art nanotechnology, such as nanostructuring, heteroatom doping, exfoliation, and hybridization, materials scientists can fabricate appropriate electrocatalysts with most exposed active sites to achieve maximal apparent activities on theoretically selected catalyst candidates.[7] Furthermore, advanced spectroscopic tools can facilitate the verification of theoretical predictions and reveal the origin of catalytic activity on selected catalysts. Technological breakthroughs in these three areas jointly promote the advancement of electrocatalyst design. In this Research News article, we present a universal process for carbon-based electrocatalyst design by linking computational quantum chemistry, surface electrochemistry, and material science.[5,6,8,9] We focus on how to implement the process for the engineering of highly efficient electrocatalysts from microscopic fundamentality to macroscopic functionality. By tailoring the chemical composition and physical structure of a catalyst, it is possible to achieve the best catalytic reactivity for a certain active site, and simultaneously attain the largest number of exposed active sites in a certain geometric electrode area. The entire process contains two major steps: i) computation-guided surface (electro-) chemical properties modification, and ii) nanotechnology-aided structure engineering. As presented in Figure 1, the process starts from analysis of the electronic structure of a solid catalyst (STEP 1), which directly influences its surface adsorption properties, as reflected by a relationship between the catalyst’s band structure and the intermediates’ adsorption strength on its surface (STEP 2).[10] The next step is the construction of a reaction’s free-energy diagram, constructed from each intermediate states’ Gibbs’ free-energy changes (ΔG) (STEP 3); the reaction step with the largest free-energy change (ΔGmax) should be considered as the rate-determination-step of the whole reaction. Therefore this ΔGmax can be used as the activity descriptor to build an “activityadsorption volcano plot” that links the electrocatalyst’s apparent activity, e.g., exchange current density (j0), and calculated ΔG through a microkinetic model (STEP 4 and STEP 5). The last, but most essential step is nanostructure engineering, which could physically extend the total number of exposed active sites for a bulk electrocatalyst identified by computation (STEP 6). Afterward, its apparent cathodic/anodic current density for a reduction/oxidation reaction can be largely increased due to both maximally exposed active sites and reduced resistance of the reactant’s mass transportation.[10–13] The whole process can serve as an “origin-design-engineering-validation” electrocatalyst
Over the past decade, developing advanced catalysts for clean and sustainable energy conversion has been subject to extensive study. Driven by great advances achieved in computational quantum chemistry, synthetic chemistry, and material characterization techniques, the preferential design of a mostappropriate catalyst for a specific electrochemical reaction is possible. Here a universal process for the design of high-performance carbon-based electrocatalysts, by engineering their intrinsic electronic structures and physical structures to promote their extrinsic activities for different energy conversion reactions, is presented and summarized. How such a powerful strategy may aid the discovery of more electrocatalysts for a sustainable and clean energy infrastructure is discussed.
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RESEARCH NEWS Figure 1. Design process of nanostructured electrocatalysts for energy-related reactions. STEP 1: Scheme of orbital hybridization of the carbon’s valance band and adsorbates bonding orbital. STEP 2: the relationship between the catalyst’s electronic structure and ΔGOH. STEP 3: a representative free-energy diagram for ORR on graphene surface. STEP 4: schematic activity–adsorption volcano plot linking j0 and ΔG. STEP 5: typical polarization curves (solid lines) and equilibrium potentials (dashed lines) of HER/HOR and ORR/OER couples. STEP 6: transmission electron microscopy (TEM) images of several nanostructured electrocatalysts with different morphologies. The schemes and plots in the top panels are reproduced with permission,[10] Copyright 2014, American Chemical Society. The TEM images in the bottom panel are reproduced with permission:[10–13] ref. [10]: Copyright 2014, American Chemical Society (top left); ref. [11]: Copyright 2010, American Chemical Society (top right); ref. [12]: Copyright 2011, Nature Publishing Group (bottom left); ref. [13]: Copyright 2011, American Chemical Society (bottom right).
discovery scheme from atomic-level theoretical predictions to experimental verification.
2. Computation-Guided Modification of Surface (Electro-)chemical Properties With the considerable improvement of computing power, DFT calculations can offer a precise description of the electronic structure of a solid catalyst. The famous “d-band center” theory, developed by Nørskov et al., sheds light on the relationship of a catalyst’s physical band structure with its chemical surface adsorption behavior.[5,14] Consequently, for a certain (electro-) catalysis process, one can optimize the chemisorption energies of reaction intermediates by tailoring a catalyst’s intrinsic electronic structure to achieve a favorable surface reaction rate.
2.1. Electronic-Structure Theories The variation in the adsorption energies of intermediate species is determined by the electronic structure of the catalyst surface; namely, the coupling between the adsorbate’s orbitals and the d-orbital of the metal catalyst or the valence orbital of the carbon. Taking the simplest HER process as an example, when a hydrogen atom (H*) adsorbs on a transition metal surface, the
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hybridization of the H* orbital with the metal d-orbital results in a fully filled bonding orbital (σ) and a partially filled antibonding orbital (σ*). According to the d-band center theory, the occupancy of σ* determines the metal–H bonding strength, and therefore influences the HER catalytic activity of a surface.[9,14] For example, if the d-band center is closer to the Fermi level of the metal (i.e., higher), the resulting σ* level is higher, corresponding to a lower σ* occupation and hence a stronger H* adsorption.[9,14] Such a correlation can also be found on the surfaces of non-metallic graphene materials for catalyzing the ORR process; the descriptor within this scheme is defined as Ediff, which is the difference between the lowest valence orbital energy of a catalytically active carbon atom and the highest valence orbital energy of the entire graphene cluster.[10] As shown in STEP 1 in Figure 1, when the valence band of the catalytically active carbon atom hybridizes with the bonding orbital of the adsorbed species (O* or OH* or OOH*), bonding (v–σ) and antibonding (v–σ)* states are formed, in which a lower valence band can induce an increased filling of the (v–σ)* state; this leads to a destabilization of the graphene–adsorbate interaction, and vice versa.[10] Consequently, a linear relationship between the values of Ediff and the reaction intermediate’s ΔG is presented. Thus, by computing the local electron orbital states (e.g., the d-band center or Ediff value) of a solid surface, it is accessible to qualitatively describe and predict its adsorbing ability toward specific reaction intermediates.
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2.2. Adsorption Free-Energy Optimization Here we present typical methods for modification of a solid catalyst’s electronic structure and the consequent optimization of the adsorption free-energy on metallic and non-metallic materials, respectively. For metals, alloying them with another element can fundamentally shift their d-band centers by either forming heteroatom bonds (ligand effect) or altering the average metal–metal bond length (strain or geometric effect). Individual or synergistic contributions from ligands and strain effects to the alloy’s activity change have been theoretically and/or experimentally studied.[15] For example, some Pt-based and Ir/Ru-based alloys show more-favorable electrocatalytic activities than elementary metals in all the discussed ORR/HER
and OER fields, respectively.[8,9,16,17] As a great number of detailed reviews are devoted to these studies (mainly focused on component and morphology control), a complete catalog is not presented here. For graphene-based materials, intermolecular doping with one or two heteroatom(s) such as N, B, P, F, S, or O is an effective way to engineer its electronic structure by both changing the electronic character of the nearby carbons and creating specific defect structures.[18] Either different kinds of dopants or the different doping sites of an element can significantly influence the electrocatalytic property of the entire graphene (Figure 2a).[19,20] For example, based on natural bond orbital (NBO) population analysis, N and O dopants are always negatively charged (and act as electron acceptors for the adjacent C),
Figure 2. Electronic-structure engineering of graphene by different elements doping. a) Typical different types of dopants and different doping sites for one certain element in graphene matrix. b) NBO population analysis of six different non-metallic heteroatoms in a graphene matrix. The inset shows the proposed doping sites for different elements. c–e) DFT-calculated free-energy diagram, experimentally measured polarization curves, and linear relationship of ΔGH* and j0 for the electrocatalytic HER on graphene doped with single- and dual-heteroatom. a–e) Reproduced with permission.[21] Copyright 2014, American Chemical Society. f–h) DFT-calculated free-energy diagram, volcano plot, and linear relationship of ΔGOH* and jk for electrocatalytic ORR on graphene samples doped with different single heteroatoms. f–h) Reproduced with permission.[10] Copyright 2014, American Chemical Society.
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2.3. Volcano-Plot Construction In a wide range of electrocatalysis and heterocatalysis processes, the quantitative relationship between an (electro-) catalyst’s surface adsorbing property and its apparent catalytic activity can be linked by a activity–adsorption volcano plot, in which the abscissa is the calculated adsorption free energy as an activity descriptor (ΔG or ΔE) and the ordinate is the experimentally measured catalytic activity in form of j0, the overpotential (η), or the turnover frequency (TOF).[5,22] The theoretical maximal activity of a catalytic reaction is given at the peak of the volcano, which is accompanied by the most-moderate intermediate ΔG or ΔE. For example, Nørskov et al. established an ORR volcano plot that links the oxygen adsorption energy for a wide variety of elementary metals with their measured j0 values.[23] According to this relationship, one can fundamentally explain why Pt catalyst show the best ORR performance by far: it is located closest to the top of the volcano with the most-moderate binding energy of oxygen-containing species. Beyond the ORR, the activity trends of more electrochemical processes can be also evaluated by analogous volcano-type plots with a respective active descriptor, such as OER (ΔGO* – ΔGHO*),[24] HER (ΔGH*),[9,25] and H2O2 production (ΔGHOO*).[26] With the development of computing power, the subjects in this scheme can cover many complex surfaces like metal alloys, metal oxides, carbons, and hybrids involved in all the discussed ORR, OER, and HER fields.[8] In summary, for a certain electrocatalytic reaction, the activity–adsorption volcano plot provides us with both the mostdesirable intermediate adsorption energy and corresponding theoretically maximal catalytic activity. Additionally, by combining the scale relationship between adsorption strength and a catalyst’s surface electronic structure, one can, in principle, predict the best performance of a catalyst for a specific reaction, as well as the most optimal value for the activity descriptor(s). At
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this point, the merging of electronic structure engineering, the adsorption scale relationship, and the volcano plot has paved the way to the first major step of performance-oriented solidcatalyst design for preferable catalytic activity (e.g., a high value of j0 or TOF).
3. Nanotechnology-Aided Physical Structure Engineering Although the identification of j0 by quantum-chemistry calculations acts as an important bridge between fundamental science and practical applications, it is not safe to say that the most-moderate reaction-intermediate adsorption behavior must result in the best electrode performance for a certain electrocatalyst. Experimentally, nanostructuring or surface functionalization for a selected candidate identified by DFT-calculation prediction is also an essential step to enhance its output performance. Namely, by fabricating an electrocatalyst with a welldeveloped nanostructure, its surface area can be significantly enlarged, which results in a larger number of exposed electrocatalytically active sites without altering its intrinsic electronic properties as guided by theoretical calculations.[8] Consequently, the extrinsic anodic or cathodic current density for a particular oxidation or reduction reaction can be increased. Using the recently developed and most-promising carbon-based materials as featured examples,[27–29] here we present three atomic-level nanostructure engineering strategies for the design of different types of ORR, OER, and HER electrocatalysts.
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while F, S, B, and P are positively charged (and act as electron donors for the adjacent C) in a graphene cluster (Figure 2b).[21] In principle, one can select a couple of heteroatoms with the most-noticeable differences in charge population (e.g., N and P) to maximally tailor electron donor–acceptor property and catalytic activity of adjacent C atoms (Figure 2c). Proof-of-concept studies showed that by downshifting the valance bands of electrocatalytically active carbon atoms in a graphene matrix, the N and P co-dopants indeed result in much lower HER overpotential and higher j0 than those of all investigated single and double dopants in graphene samples (Figure 2d,e).[21] Similarly, the functions of different dopants in graphene samples toward ORR performance enhancement have also been extensively studied by uncovering the origin of their ORR activities at the atomic level (Figure 2f). All key experimentally measured ORR parameters such as the onset potential, geometrically normalized j0, and kinetic current densities jk under certain overpotentials have been quantitatively linked with DFT-calculated specific ΔG.[10] For example, a volcano shape plot of j0 vs ΔGOOH* (Figure 2g) and the linear relation of jk with ΔGOH* (Figure 2h) are clearly presented;[10] the agreements of theoretical prediction and experimental validation are remarkably good.
3.1. Carbon Nanomaterials with Various Morphologies With the giant advance of nanotechnology, materials scientists can fabricate electrocatalysts at the nanoscale to physically increase the number of electrocatalytically active sites per unit geometric area. A striking example is the engineering of nanostructured carbon materials that have widely been studied as metal-free ORR electrocatalysts for alternatives to Pt in alkaline conditions.[30,31] One of the most-significant advantages of carbon-based electrocatalysts in comparison to their Pt counterpart is their abundant source and strong tolerance against anode reactant poison. In the early stages, studies focused on developing amorphous carbons with various morphologies to achieve high surface areas, mainly by self-assembly and hard template casting. Later on, (doped) carbon nanotubes or (doped) graphene with high electrical conduction, as well as unique chemical functional groups were developed as nonmetallic ORR electrocatalysts. Currently, the hybridization of nanoporous carbon with graphene and/or carbon nanotubes in a three-dimensional complex is the main method to promote ORR activity; some of them have shown very competitive performances in comparison to traditional metallic catalysts.[8,30–35] The nanostructuring method can be applied not only to changing the morphologies of electrocatalysts, but also to building novel electrode architectures for practical applications. Currently, most experimentally available electrocatalysts are prepared in the form of powders, which need to be loaded on conductive supports (e.g., carbon cloths, metal foils)
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Figure 3. Promoting the electrocatalytic activity of g-C3N4 by nanocarbon incorporation for electrocatalytic applications. a,d) Typical scanning electron microscopy (SEM) image showing a relatively oriented assembly structure and OER performance of the g-C3N4 NS–CNT nanocomposite. Reproduced with permission.[50] Copyright 2014, Wiley. b,e) Typical TEM image showing nanoporous structure and ORR performance of synthesized g-C3N4@ CMK-3 composite. Reproduced with permission.[13] Copyright 2011, American Chemical Society. c,f) Typical high-resolution TEM (HRTEM) image showing layered structures and HER performance of the synthesized C3N4@NG hybrid. Reproduced with permission.[52] Copyright 2014, Nature Publishing Group.
to make membrane electrode assemblies (MEAs). Alternatively, constructing a substrate-free film electrode directly for device utilization can considerably reduce the cost and simplify the manufacturing process of the whole system. Such a filmlike structure can also afford a robust mechanical stability for the resulting electrode. Recently, we successfully developed a series of carbon-based self-support hydrogel or aerogel films by a 3D macroscopic assembly technique.[36–39] The component can be either single (doped) graphene or hybridized graphenebased composites, which all possess unique microstructures for highly efficient OER and HER processes. The activity enhancement for such 3D structured electrodes may originate from the high electrical conductivity for fast charge transport, and hierarchical pores (macropores and micropores) for the facile reactant mass transportation.[36–40]
3.2. Carbon–Metal Hybrids with Synergistic Effects Besides the nanostructuring method, hybridizing the bulk materials with high-surface-area nanocarbons can also achieve highly distributed catalyst nanoparticles with extended active sites for electrocatalysis. The carbon substrates not only act as a conductive support but, more importantly, also interact with electrocatalytically active metallic nanoparticles through strong coupling effects between both components. Such a chemical interaction can modify the (electro-)chemical properties of both
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metals and carbons to induce new and more-favorable electrocatalytically active sites. For example, by well-designed twostep wet-chemical methods, Dai et al. and our group directly attached a wide variety of nanostructured metal oxides/hydroxides onto nanocarbons (doped graphene or carbon nanotubes) with synergistically enhanced electrocatalytic activities in ORR, HER and OER applications.[41–47] In these studies, the size and shape of the metal nanoparticles/nanocrystals can be tuned by adjusting the surface functional groups (–OH, –C=O, –COOH, –CN, and–NH2, etc.) of the underlying carbon substrates to optimize the size- or shape-selectivity of the resulting hybrids.
3.3. Carbon–Non-metallic Materials with Different Functions Recently, the aforementioned hybridization strategy has been expanded to hybridizing carbon with more non-metallic materials that are electrochemically non-active or less active to boost their specific reaction activities. With the availability of DFT calculations, the origin of such synergistic activity enhancement can be uncovered at the atomic level. Generally, the promotion of carbons toward a non-metal catalyst (host material) can be reflected in three forms: i) expanding the surface area to enlarge the active sites on the host material; ii) enhancing the electrical conductivity of the whole hybrid to facilitate electron/charge transfer on host material’s surface or interface; and iii) fundamentally altering the electronic structure of the host
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4. Conclusions and Perspectives The merging of quantum computational chemistry, surface electrochemistry, and materials science has stimulated the advance of clean energy-conversion technology.[8] A rational and feasible catalyst-design process has been proposed and verified for various types of surfaces ranging from precious metals to non-metallic carbons, and from single-crystalline metals to hybrids. Although such success has been applied in many industrial processes, there are still a number of gaps between linking fundamental DFT calculations and the utilization levels. For example, electronic-structure analysis is only accessible for single facets of solid bulk surfaces and cannot deal with nanostructured catalysts with polycrystalline phases. Additionally, uncertainties also depend strongly on the real reaction conditions, especially for a scaled-up system in fuelcell stacks or large-scale electrolytic cells. Besides the surface reaction rate described by various activity descriptors, the performance of a mature catalyst is also evaluated by several additional factors like long-term stability, tolerance to poisons, and by-products, which are difficult to assess at the current stage of computation-aided catalyst design.[5] Nevertheless, despite these shortcomings, the combination of DFT calculation and experimental validation could help to uncover the reactivity of
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specific solid catalysts at the atomic level, and also to identify the most-favorable activity, rather than using the traditional trial-and-error process for optimization. We hope this proposed strategy can be used in a broad range of applications in fields of catalysis and energy conversion, and storage.
Acknowledgements The authors gratefully acknowledge financial support by the Australian Research Council (ARC) through the Discovery Project programs (DP140104062 and DP130104459).
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material to modify its surface adsorbing property. All of these three ways, either individually or synergistically, can enhance the electrocatalytic activity of resulting hybrids. Here, we take graphitic carbon nitride (g-C3N4), which is known as a semiconductor and inert electrocatalyst,[48] as a featured example to present the promoting role of carbon hybridization. Due to the physical and/or chemical effect of the nanocarbons as mentioned above, the hybrids showed significantly increased electrocatalytic activity in comparison to pristine g-C3N4; the performances were close to or even higher than those of some classic metallic electrocatalysts in all the discussed OER, ORR, and HER processes.[13,39,49–52] In the first case (Figure 3a,d), we assembled exfoliated g-C3N4 nanosheets with carbon nanotubes to form a 3D interconnected network, which possessed a well-developed porous structure, high surface area, and high nitrogen content.[50] Attributed to these features, the hybrid displayed more-favorable kinetics and stronger durability than the nanosized commercial IrO2 catalyst for OER applications. In the second case (Figure 3b,e), to address the limited electron-transfer capability on g-C3N4 that results in a large accumulation of OOH* intermediate on its surface, we incorporated g-C3N4 into two types of carbon frameworks, such as mesoporous carbon (CMK-3) or ordered macroporous carbon, to promote the hybrid’s electrical conductivity.[13,49] The superior activity on the resulting nanocomposite originates from both its enlarged surface area with more exposed active sites and facile electron/charge transfer to reduce the reaction barrier. In the third case (Figure 3c,f), we chemically coupled g-C3N4 with nitrogen-doped graphene sheets (N-graphene) as an atomic-layered hybrid to adjust its adsorbing hydrogen capability.[52] As result, the hybrid’s HER activity largely surpassed that of bulk g-C3N4 and was also very close to the most-well-known nanostructured MoS2 catalysts.
Received: February 16, 2015 Revised: April 12, 2015 Published online: July 14, 2015
[1] B. C. H. Steele, A. Heinzel, Nature 2001, 414, 345. [2] M. G. Walter, E. L. Warren, J. R. McKone, S. W. Boettcher, Q. Mi, E. A. Santori, N. S. Lewis, Chem. Rev. 2010, 110, 6446. [3] H. Wolfschmidt, O. Paschos, U. Stimming, Fuel Cell Science, John Wiley & Sons, Inc., Hoboken, NJ, USA 2010. [4] H. A. Gasteiger, S. S. Kocha, B. Sompalli, F. T. Wagner, Appl. Catal. B 2005, 56, 9. [5] J. K. Norskov, T. Bligaard, J. Rossmeisl, C. H. Christensen, Nat. Chem. 2009, 1, 37. [6] J. Greeley, N. M. Markovic, Energy Environ. Sci. 2012, 5, 9246. [7] S. E. F. Kleijn, S. C. S. Lai, M. T. M. Koper, P. R. Unwin, Angew. Chem. Int. Ed. 2014, 53, 3558. [8] Y. Jiao, Y. Zheng, M. Jaroniec, S. Z. Qiao, Chem. Soc. Rev. 2015, 44, 2060. [9] Y. Zheng, Y. Jiao, M. Jaroniec, S. Z. Qiao, Angew. Chem. Int. Ed. 2015, 54, 52. [10] Y. Jiao, Y. Zheng, M. Jaroniec, S. Z. Qiao, J. Am. Chem. Soc. 2014, 136, 4394. [11] W. Xiong, F. Du, Y. Liu, A. Perez, M. Supp, T. S. Ramakrishnan, L. Dai, L. Jiang, J. Am. Chem. Soc. 2010, 132, 15839. [12] Y. Liang, Y. Li, H. Wang, J. Zhou, J. Wang, T. Regier, H. Dai, Nat. Mater. 2011, 10, 780. [13] Y. Zheng, Y. Jiao, J. Chen, J. Liu, J. Liang, A. Du, W. Zhang, Z. Zhu, S. C. Smith, M. Jaroniec, G. Q. Lu, S. Z. Qiao, J. Am. Chem. Soc. 2011, 133, 20116. [14] B. Hammer, J. K. Nørskov, in Advances in Catalysis, Vol. 45: Impact of Surface Science on Catalysis, (Eds: B. C. Gates, H. Knozinger), Academic Press, Waltham, MA, USA 2000. [15] J. G. Chen, C. A. Menning, M. B. Zellner, Surf. Sci. Rep. 2008, 63, 201. [16] A. Morozan, B. Jousselme, S. Palacin, Energy Environ. Sci. 2011, 4, 1238. [17] S. Park, Y. Shao, J. Liu, Y. Wang, Energy Environ. Sci. 2012, 5, 9331. [18] D.-W. Wang, D. Su, Energy Environ. Sci. 2014, 7, 576. [19] Y. Zheng, Y. Jiao, L. Ge, M. Jaroniec, S. Z. Qiao, Angew. Chem. Int. Ed. 2013, 52, 3110. [20] J. Liang, Y. Jiao, M. Jaroniec, S. Z. Qiao, Angew. Chem. Int. Ed. 2012, 51, 11496. [21] Y. Zheng, Y. Jiao, L. H. Li, T. Xing, Y. Chen, M. Jaroniec, S. Z. Qiao, ACS Nano 2014, 8, 5290. [22] R. Parsons, Catalysis in Electrochemistry, John Wiley & Sons, Inc., Hoboken, NJ, USA 2011. [23] J. K. Nørskov, J. Rossmeisl, A. Logadottir, L. Lindqvist, J. R. Kitchin, T. Bligaard, H. Jónsson, J. Phys. Chem. B 2004, 108, 17886. [24] J. Rossmeisl, Z. W. Qu, H. Zhu, G. J. Kroes, J. K. Nørskov, J. Electroanal. Chem. 2007, 607, 83.
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www.MaterialsViews.com
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[25] J. K. Nørskov, T. Bligaard, A. Logadottir, J. R. Kitchin, J. G. Chen, S. Pandelov, U. Stimming, J. Electrochem. Soc. 2005, 152, J23. [26] A. Verdaguer-Casadevall, D. Deiana, M. Karamad, S. Siahrostami, P. Malacrida, T. W. Hansen, J. Rossmeisl, I. Chorkendorff, I. E. L. Stephens, Nano Lett. 2014, 14, 1603. [27] Y. Sun, Q. Wu, G. Shi, Energy Environ. Sci. 2011, 4, 1113. [28] P. V. Kamat, J. Phys. Chem. Lett. 2011, 2, 42. [29] D. S. Su, J. Zhang, B. Frank, A. Thomas, X. Wang, J. Paraknowitsch, R. Schlögl, ChemSusChem 2010, 3, 169. [30] Y. Zheng, Y. Jiao, M. Jaroniec, Y. Jin, S. Z. Qiao, Small 2012, 8, 3550. [31] L. Dai, D. W. Chang, J.-B. Baek, W. Lu, Small 2012, 8, 1130. [32] Y. Li, W. Zhou, H. Wang, L. Xie, Y. Liang, F. Wei, J.-C. Idrobo, S. J. Pennycook, H. Dai, Nat. Nano. 2012, 7, 394. [33] J. Liang, X. Du, C. Gibson, X. W. Du, S. Z. Qiao, Adv. Mater. 2013, 25, 6226. [34] X. Zhou, J. Qiao, L. Yang, J. Zhang, Adv. Energy Mater. 2014, 4, 1301523. [35] Y. Shao, J. Sui, G. Yin, Y. Gao, Appl. Catal. B 2008, 79, 89. [36] S. Chen, J. Duan, M. Jaroniec, S. Z. Qiao, Adv. Mater. 2014, 26, 2925. [37] S. Chen, J. Duan, M. Jaroniec, S. Z. Qiao, Angew. Chem. Int. Ed. 2013, 52, 13567. [38] S. Chen, S. Z. Qiao, ACS Nano 2013, 7, 10190.
wileyonlinelibrary.com
[39] [40] [41] [42] [43] [44] [45] [46] [47] [48] [49] [50] [51] [52]
J. Duan, S. Chen, M. Jaroniec, S. Z. Qiao, ACS Nano 2015, 9, 931. C. Cheng, D. Li, Adv. Mater. 2013, 25, 13. Y. Liang, Y. Li, H. Wang, H. Dai, J. Am. Chem. Soc. 2013, 135, 2013. H. Wang, H. Dai, Chem. Soc. Rev. 2013,42, 3088. J. Duan, Y. Zheng, S. Chen, Y. Tang, M. Jaroniec, S. Z. Qiao, Chem. Commun. 2013, 49, 7705. R. Zhou, S. Z. Qiao, Chem. Mater. 2014, 26, 5868. J. Duan, S. Chen, S. Dai, S. Z. Qiao, Adv. Funct. Mater. 2014, 24, 2072. T. Y. Ma, S. Dai, M. Jaroniec, S. Z. Qiao, J. Am. Chem. Soc. 2014, 136, 13925. J. Liang, R. F. Zhou, X. M. Chen, Y. H. Tang, S. Z. Qiao, Adv. Mater. 2014, 26, 6074. Y. Zheng, J. Liu, J. Liang, M. Jaroniec, S. Z. Qiao, Energy Environ. Sci. 2012, 5, 6717. J. Liang, Y. Zheng, J. Chen, J. Liu, D. Hulicova-Jurcakova, M. Jaroniec, S. Z. Qiao, Angew. Chem. Int. Ed. 2012, 51, 3892. T. Y. Ma, S. Dai, M. Jaroniec, S. Z. Qiao, Angew. Chem. Int. Ed. 2014, 53, 7281. T. Y. Ma, J. Ran, S. Dai, M. Jaroniec, S. Z. Qiao, Angew. Chem. Int. Ed. 2015, 54, 4646. Y. Zheng, Y. Jiao, Y. Zhu, L. H. Li, Y. Han, Y. Chen, A. Du, M. Jaroniec, S. Z. Qiao, Nat. Commun. 2014, 5, 3783.
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Engineering of Carbon-Based Electrocatalysts for Emerging Energy Conversion: From Fundamentality to Functionality Yao Zheng, Yan Jiao, and Shi Zhang Qiao*
1. Introduction The rapid development of new clean energy technologies, such as fuel cells and water splitting may provide possible solutions for the continuously increasing global demand for energy over the last few decades.[1,2] The performances of these electrochemical energy-conversion devices strongly depend on the reaction rates of a series of electrochemical processes on their electrodes. The reactions include the electrocatalytic oxygen reduction reaction (ORR) and hydrogen oxidation reaction (HOR), which occur on the cathode and anode of a hydrogen fuel cell, and the hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) at the cathode and anode of a water splitting cell. Up to now, a variety of commercial high-performance electrocatalysts have been designed (mainly precious metals) to facilitate these reactions with favorable kinetics and therefore to achieve higher energy efficiency for a given device.[3,4] More strikingly, due to remarkable advances in density functional theory (DFT) and computing power, theoretical chemists have the capability to predict, screen, and design electrocatalysts with desirable activities, based on profound understanding of the nature of electrocatalytic processes.[5,6] At the same time, by Dr. Y. Zheng, Dr. Y. Jiao, Prof. S. Z. Qiao School of Chemical Engineering University of Adelaide Adelaide, SA 5005, Australia E-mail: [email protected] Prof. S. Z. Qiao School of Materials Science and Engineering Tianjin University Tianjin 300072, China
DOI: 10.1002/adma.201500821
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using state-of-the-art nanotechnology, such as nanostructuring, heteroatom doping, exfoliation, and hybridization, materials scientists can fabricate appropriate electrocatalysts with most exposed active sites to achieve maximal apparent activities on theoretically selected catalyst candidates.[7] Furthermore, advanced spectroscopic tools can facilitate the verification of theoretical predictions and reveal the origin of catalytic activity on selected catalysts. Technological breakthroughs in these three areas jointly promote the advancement of electrocatalyst design. In this Research News article, we present a universal process for carbon-based electrocatalyst design by linking computational quantum chemistry, surface electrochemistry, and material science.[5,6,8,9] We focus on how to implement the process for the engineering of highly efficient electrocatalysts from microscopic fundamentality to macroscopic functionality. By tailoring the chemical composition and physical structure of a catalyst, it is possible to achieve the best catalytic reactivity for a certain active site, and simultaneously attain the largest number of exposed active sites in a certain geometric electrode area. The entire process contains two major steps: i) computation-guided surface (electro-) chemical properties modification, and ii) nanotechnology-aided structure engineering. As presented in Figure 1, the process starts from analysis of the electronic structure of a solid catalyst (STEP 1), which directly influences its surface adsorption properties, as reflected by a relationship between the catalyst’s band structure and the intermediates’ adsorption strength on its surface (STEP 2).[10] The next step is the construction of a reaction’s free-energy diagram, constructed from each intermediate states’ Gibbs’ free-energy changes (ΔG) (STEP 3); the reaction step with the largest free-energy change (ΔGmax) should be considered as the rate-determination-step of the whole reaction. Therefore this ΔGmax can be used as the activity descriptor to build an “activityadsorption volcano plot” that links the electrocatalyst’s apparent activity, e.g., exchange current density (j0), and calculated ΔG through a microkinetic model (STEP 4 and STEP 5). The last, but most essential step is nanostructure engineering, which could physically extend the total number of exposed active sites for a bulk electrocatalyst identified by computation (STEP 6). Afterward, its apparent cathodic/anodic current density for a reduction/oxidation reaction can be largely increased due to both maximally exposed active sites and reduced resistance of the reactant’s mass transportation.[10–13] The whole process can serve as an “origin-design-engineering-validation” electrocatalyst
Over the past decade, developing advanced catalysts for clean and sustainable energy conversion has been subject to extensive study. Driven by great advances achieved in computational quantum chemistry, synthetic chemistry, and material characterization techniques, the preferential design of a mostappropriate catalyst for a specific electrochemical reaction is possible. Here a universal process for the design of high-performance carbon-based electrocatalysts, by engineering their intrinsic electronic structures and physical structures to promote their extrinsic activities for different energy conversion reactions, is presented and summarized. How such a powerful strategy may aid the discovery of more electrocatalysts for a sustainable and clean energy infrastructure is discussed.
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RESEARCH NEWS Figure 1. Design process of nanostructured electrocatalysts for energy-related reactions. STEP 1: Scheme of orbital hybridization of the carbon’s valance band and adsorbates bonding orbital. STEP 2: the relationship between the catalyst’s electronic structure and ΔGOH. STEP 3: a representative free-energy diagram for ORR on graphene surface. STEP 4: schematic activity–adsorption volcano plot linking j0 and ΔG. STEP 5: typical polarization curves (solid lines) and equilibrium potentials (dashed lines) of HER/HOR and ORR/OER couples. STEP 6: transmission electron microscopy (TEM) images of several nanostructured electrocatalysts with different morphologies. The schemes and plots in the top panels are reproduced with permission,[10] Copyright 2014, American Chemical Society. The TEM images in the bottom panel are reproduced with permission:[10–13] ref. [10]: Copyright 2014, American Chemical Society (top left); ref. [11]: Copyright 2010, American Chemical Society (top right); ref. [12]: Copyright 2011, Nature Publishing Group (bottom left); ref. [13]: Copyright 2011, American Chemical Society (bottom right).
discovery scheme from atomic-level theoretical predictions to experimental verification.
2. Computation-Guided Modification of Surface (Electro-)chemical Properties With the considerable improvement of computing power, DFT calculations can offer a precise description of the electronic structure of a solid catalyst. The famous “d-band center” theory, developed by Nørskov et al., sheds light on the relationship of a catalyst’s physical band structure with its chemical surface adsorption behavior.[5,14] Consequently, for a certain (electro-) catalysis process, one can optimize the chemisorption energies of reaction intermediates by tailoring a catalyst’s intrinsic electronic structure to achieve a favorable surface reaction rate.
2.1. Electronic-Structure Theories The variation in the adsorption energies of intermediate species is determined by the electronic structure of the catalyst surface; namely, the coupling between the adsorbate’s orbitals and the d-orbital of the metal catalyst or the valence orbital of the carbon. Taking the simplest HER process as an example, when a hydrogen atom (H*) adsorbs on a transition metal surface, the
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hybridization of the H* orbital with the metal d-orbital results in a fully filled bonding orbital (σ) and a partially filled antibonding orbital (σ*). According to the d-band center theory, the occupancy of σ* determines the metal–H bonding strength, and therefore influences the HER catalytic activity of a surface.[9,14] For example, if the d-band center is closer to the Fermi level of the metal (i.e., higher), the resulting σ* level is higher, corresponding to a lower σ* occupation and hence a stronger H* adsorption.[9,14] Such a correlation can also be found on the surfaces of non-metallic graphene materials for catalyzing the ORR process; the descriptor within this scheme is defined as Ediff, which is the difference between the lowest valence orbital energy of a catalytically active carbon atom and the highest valence orbital energy of the entire graphene cluster.[10] As shown in STEP 1 in Figure 1, when the valence band of the catalytically active carbon atom hybridizes with the bonding orbital of the adsorbed species (O* or OH* or OOH*), bonding (v–σ) and antibonding (v–σ)* states are formed, in which a lower valence band can induce an increased filling of the (v–σ)* state; this leads to a destabilization of the graphene–adsorbate interaction, and vice versa.[10] Consequently, a linear relationship between the values of Ediff and the reaction intermediate’s ΔG is presented. Thus, by computing the local electron orbital states (e.g., the d-band center or Ediff value) of a solid surface, it is accessible to qualitatively describe and predict its adsorbing ability toward specific reaction intermediates.
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2.2. Adsorption Free-Energy Optimization Here we present typical methods for modification of a solid catalyst’s electronic structure and the consequent optimization of the adsorption free-energy on metallic and non-metallic materials, respectively. For metals, alloying them with another element can fundamentally shift their d-band centers by either forming heteroatom bonds (ligand effect) or altering the average metal–metal bond length (strain or geometric effect). Individual or synergistic contributions from ligands and strain effects to the alloy’s activity change have been theoretically and/or experimentally studied.[15] For example, some Pt-based and Ir/Ru-based alloys show more-favorable electrocatalytic activities than elementary metals in all the discussed ORR/HER
and OER fields, respectively.[8,9,16,17] As a great number of detailed reviews are devoted to these studies (mainly focused on component and morphology control), a complete catalog is not presented here. For graphene-based materials, intermolecular doping with one or two heteroatom(s) such as N, B, P, F, S, or O is an effective way to engineer its electronic structure by both changing the electronic character of the nearby carbons and creating specific defect structures.[18] Either different kinds of dopants or the different doping sites of an element can significantly influence the electrocatalytic property of the entire graphene (Figure 2a).[19,20] For example, based on natural bond orbital (NBO) population analysis, N and O dopants are always negatively charged (and act as electron acceptors for the adjacent C),
Figure 2. Electronic-structure engineering of graphene by different elements doping. a) Typical different types of dopants and different doping sites for one certain element in graphene matrix. b) NBO population analysis of six different non-metallic heteroatoms in a graphene matrix. The inset shows the proposed doping sites for different elements. c–e) DFT-calculated free-energy diagram, experimentally measured polarization curves, and linear relationship of ΔGH* and j0 for the electrocatalytic HER on graphene doped with single- and dual-heteroatom. a–e) Reproduced with permission.[21] Copyright 2014, American Chemical Society. f–h) DFT-calculated free-energy diagram, volcano plot, and linear relationship of ΔGOH* and jk for electrocatalytic ORR on graphene samples doped with different single heteroatoms. f–h) Reproduced with permission.[10] Copyright 2014, American Chemical Society.
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2.3. Volcano-Plot Construction In a wide range of electrocatalysis and heterocatalysis processes, the quantitative relationship between an (electro-) catalyst’s surface adsorbing property and its apparent catalytic activity can be linked by a activity–adsorption volcano plot, in which the abscissa is the calculated adsorption free energy as an activity descriptor (ΔG or ΔE) and the ordinate is the experimentally measured catalytic activity in form of j0, the overpotential (η), or the turnover frequency (TOF).[5,22] The theoretical maximal activity of a catalytic reaction is given at the peak of the volcano, which is accompanied by the most-moderate intermediate ΔG or ΔE. For example, Nørskov et al. established an ORR volcano plot that links the oxygen adsorption energy for a wide variety of elementary metals with their measured j0 values.[23] According to this relationship, one can fundamentally explain why Pt catalyst show the best ORR performance by far: it is located closest to the top of the volcano with the most-moderate binding energy of oxygen-containing species. Beyond the ORR, the activity trends of more electrochemical processes can be also evaluated by analogous volcano-type plots with a respective active descriptor, such as OER (ΔGO* – ΔGHO*),[24] HER (ΔGH*),[9,25] and H2O2 production (ΔGHOO*).[26] With the development of computing power, the subjects in this scheme can cover many complex surfaces like metal alloys, metal oxides, carbons, and hybrids involved in all the discussed ORR, OER, and HER fields.[8] In summary, for a certain electrocatalytic reaction, the activity–adsorption volcano plot provides us with both the mostdesirable intermediate adsorption energy and corresponding theoretically maximal catalytic activity. Additionally, by combining the scale relationship between adsorption strength and a catalyst’s surface electronic structure, one can, in principle, predict the best performance of a catalyst for a specific reaction, as well as the most optimal value for the activity descriptor(s). At
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this point, the merging of electronic structure engineering, the adsorption scale relationship, and the volcano plot has paved the way to the first major step of performance-oriented solidcatalyst design for preferable catalytic activity (e.g., a high value of j0 or TOF).
3. Nanotechnology-Aided Physical Structure Engineering Although the identification of j0 by quantum-chemistry calculations acts as an important bridge between fundamental science and practical applications, it is not safe to say that the most-moderate reaction-intermediate adsorption behavior must result in the best electrode performance for a certain electrocatalyst. Experimentally, nanostructuring or surface functionalization for a selected candidate identified by DFT-calculation prediction is also an essential step to enhance its output performance. Namely, by fabricating an electrocatalyst with a welldeveloped nanostructure, its surface area can be significantly enlarged, which results in a larger number of exposed electrocatalytically active sites without altering its intrinsic electronic properties as guided by theoretical calculations.[8] Consequently, the extrinsic anodic or cathodic current density for a particular oxidation or reduction reaction can be increased. Using the recently developed and most-promising carbon-based materials as featured examples,[27–29] here we present three atomic-level nanostructure engineering strategies for the design of different types of ORR, OER, and HER electrocatalysts.
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while F, S, B, and P are positively charged (and act as electron donors for the adjacent C) in a graphene cluster (Figure 2b).[21] In principle, one can select a couple of heteroatoms with the most-noticeable differences in charge population (e.g., N and P) to maximally tailor electron donor–acceptor property and catalytic activity of adjacent C atoms (Figure 2c). Proof-of-concept studies showed that by downshifting the valance bands of electrocatalytically active carbon atoms in a graphene matrix, the N and P co-dopants indeed result in much lower HER overpotential and higher j0 than those of all investigated single and double dopants in graphene samples (Figure 2d,e).[21] Similarly, the functions of different dopants in graphene samples toward ORR performance enhancement have also been extensively studied by uncovering the origin of their ORR activities at the atomic level (Figure 2f). All key experimentally measured ORR parameters such as the onset potential, geometrically normalized j0, and kinetic current densities jk under certain overpotentials have been quantitatively linked with DFT-calculated specific ΔG.[10] For example, a volcano shape plot of j0 vs ΔGOOH* (Figure 2g) and the linear relation of jk with ΔGOH* (Figure 2h) are clearly presented;[10] the agreements of theoretical prediction and experimental validation are remarkably good.
3.1. Carbon Nanomaterials with Various Morphologies With the giant advance of nanotechnology, materials scientists can fabricate electrocatalysts at the nanoscale to physically increase the number of electrocatalytically active sites per unit geometric area. A striking example is the engineering of nanostructured carbon materials that have widely been studied as metal-free ORR electrocatalysts for alternatives to Pt in alkaline conditions.[30,31] One of the most-significant advantages of carbon-based electrocatalysts in comparison to their Pt counterpart is their abundant source and strong tolerance against anode reactant poison. In the early stages, studies focused on developing amorphous carbons with various morphologies to achieve high surface areas, mainly by self-assembly and hard template casting. Later on, (doped) carbon nanotubes or (doped) graphene with high electrical conduction, as well as unique chemical functional groups were developed as nonmetallic ORR electrocatalysts. Currently, the hybridization of nanoporous carbon with graphene and/or carbon nanotubes in a three-dimensional complex is the main method to promote ORR activity; some of them have shown very competitive performances in comparison to traditional metallic catalysts.[8,30–35] The nanostructuring method can be applied not only to changing the morphologies of electrocatalysts, but also to building novel electrode architectures for practical applications. Currently, most experimentally available electrocatalysts are prepared in the form of powders, which need to be loaded on conductive supports (e.g., carbon cloths, metal foils)
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Figure 3. Promoting the electrocatalytic activity of g-C3N4 by nanocarbon incorporation for electrocatalytic applications. a,d) Typical scanning electron microscopy (SEM) image showing a relatively oriented assembly structure and OER performance of the g-C3N4 NS–CNT nanocomposite. Reproduced with permission.[50] Copyright 2014, Wiley. b,e) Typical TEM image showing nanoporous structure and ORR performance of synthesized g-C3N4@ CMK-3 composite. Reproduced with permission.[13] Copyright 2011, American Chemical Society. c,f) Typical high-resolution TEM (HRTEM) image showing layered structures and HER performance of the synthesized C3N4@NG hybrid. Reproduced with permission.[52] Copyright 2014, Nature Publishing Group.
to make membrane electrode assemblies (MEAs). Alternatively, constructing a substrate-free film electrode directly for device utilization can considerably reduce the cost and simplify the manufacturing process of the whole system. Such a filmlike structure can also afford a robust mechanical stability for the resulting electrode. Recently, we successfully developed a series of carbon-based self-support hydrogel or aerogel films by a 3D macroscopic assembly technique.[36–39] The component can be either single (doped) graphene or hybridized graphenebased composites, which all possess unique microstructures for highly efficient OER and HER processes. The activity enhancement for such 3D structured electrodes may originate from the high electrical conductivity for fast charge transport, and hierarchical pores (macropores and micropores) for the facile reactant mass transportation.[36–40]
3.2. Carbon–Metal Hybrids with Synergistic Effects Besides the nanostructuring method, hybridizing the bulk materials with high-surface-area nanocarbons can also achieve highly distributed catalyst nanoparticles with extended active sites for electrocatalysis. The carbon substrates not only act as a conductive support but, more importantly, also interact with electrocatalytically active metallic nanoparticles through strong coupling effects between both components. Such a chemical interaction can modify the (electro-)chemical properties of both
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metals and carbons to induce new and more-favorable electrocatalytically active sites. For example, by well-designed twostep wet-chemical methods, Dai et al. and our group directly attached a wide variety of nanostructured metal oxides/hydroxides onto nanocarbons (doped graphene or carbon nanotubes) with synergistically enhanced electrocatalytic activities in ORR, HER and OER applications.[41–47] In these studies, the size and shape of the metal nanoparticles/nanocrystals can be tuned by adjusting the surface functional groups (–OH, –C=O, –COOH, –CN, and–NH2, etc.) of the underlying carbon substrates to optimize the size- or shape-selectivity of the resulting hybrids.
3.3. Carbon–Non-metallic Materials with Different Functions Recently, the aforementioned hybridization strategy has been expanded to hybridizing carbon with more non-metallic materials that are electrochemically non-active or less active to boost their specific reaction activities. With the availability of DFT calculations, the origin of such synergistic activity enhancement can be uncovered at the atomic level. Generally, the promotion of carbons toward a non-metal catalyst (host material) can be reflected in three forms: i) expanding the surface area to enlarge the active sites on the host material; ii) enhancing the electrical conductivity of the whole hybrid to facilitate electron/charge transfer on host material’s surface or interface; and iii) fundamentally altering the electronic structure of the host
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4. Conclusions and Perspectives The merging of quantum computational chemistry, surface electrochemistry, and materials science has stimulated the advance of clean energy-conversion technology.[8] A rational and feasible catalyst-design process has been proposed and verified for various types of surfaces ranging from precious metals to non-metallic carbons, and from single-crystalline metals to hybrids. Although such success has been applied in many industrial processes, there are still a number of gaps between linking fundamental DFT calculations and the utilization levels. For example, electronic-structure analysis is only accessible for single facets of solid bulk surfaces and cannot deal with nanostructured catalysts with polycrystalline phases. Additionally, uncertainties also depend strongly on the real reaction conditions, especially for a scaled-up system in fuelcell stacks or large-scale electrolytic cells. Besides the surface reaction rate described by various activity descriptors, the performance of a mature catalyst is also evaluated by several additional factors like long-term stability, tolerance to poisons, and by-products, which are difficult to assess at the current stage of computation-aided catalyst design.[5] Nevertheless, despite these shortcomings, the combination of DFT calculation and experimental validation could help to uncover the reactivity of
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specific solid catalysts at the atomic level, and also to identify the most-favorable activity, rather than using the traditional trial-and-error process for optimization. We hope this proposed strategy can be used in a broad range of applications in fields of catalysis and energy conversion, and storage.
Acknowledgements The authors gratefully acknowledge financial support by the Australian Research Council (ARC) through the Discovery Project programs (DP140104062 and DP130104459).
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material to modify its surface adsorbing property. All of these three ways, either individually or synergistically, can enhance the electrocatalytic activity of resulting hybrids. Here, we take graphitic carbon nitride (g-C3N4), which is known as a semiconductor and inert electrocatalyst,[48] as a featured example to present the promoting role of carbon hybridization. Due to the physical and/or chemical effect of the nanocarbons as mentioned above, the hybrids showed significantly increased electrocatalytic activity in comparison to pristine g-C3N4; the performances were close to or even higher than those of some classic metallic electrocatalysts in all the discussed OER, ORR, and HER processes.[13,39,49–52] In the first case (Figure 3a,d), we assembled exfoliated g-C3N4 nanosheets with carbon nanotubes to form a 3D interconnected network, which possessed a well-developed porous structure, high surface area, and high nitrogen content.[50] Attributed to these features, the hybrid displayed more-favorable kinetics and stronger durability than the nanosized commercial IrO2 catalyst for OER applications. In the second case (Figure 3b,e), to address the limited electron-transfer capability on g-C3N4 that results in a large accumulation of OOH* intermediate on its surface, we incorporated g-C3N4 into two types of carbon frameworks, such as mesoporous carbon (CMK-3) or ordered macroporous carbon, to promote the hybrid’s electrical conductivity.[13,49] The superior activity on the resulting nanocomposite originates from both its enlarged surface area with more exposed active sites and facile electron/charge transfer to reduce the reaction barrier. In the third case (Figure 3c,f), we chemically coupled g-C3N4 with nitrogen-doped graphene sheets (N-graphene) as an atomic-layered hybrid to adjust its adsorbing hydrogen capability.[52] As result, the hybrid’s HER activity largely surpassed that of bulk g-C3N4 and was also very close to the most-well-known nanostructured MoS2 catalysts.
Received: February 16, 2015 Revised: April 12, 2015 Published online: July 14, 2015
[1] B. C. H. Steele, A. Heinzel, Nature 2001, 414, 345. [2] M. G. Walter, E. L. Warren, J. R. McKone, S. W. Boettcher, Q. Mi, E. A. Santori, N. S. Lewis, Chem. Rev. 2010, 110, 6446. [3] H. Wolfschmidt, O. Paschos, U. Stimming, Fuel Cell Science, John Wiley & Sons, Inc., Hoboken, NJ, USA 2010. [4] H. A. Gasteiger, S. S. Kocha, B. Sompalli, F. T. Wagner, Appl. Catal. B 2005, 56, 9. [5] J. K. Norskov, T. Bligaard, J. Rossmeisl, C. H. Christensen, Nat. Chem. 2009, 1, 37. [6] J. Greeley, N. M. Markovic, Energy Environ. Sci. 2012, 5, 9246. [7] S. E. F. Kleijn, S. C. S. Lai, M. T. M. Koper, P. R. Unwin, Angew. Chem. Int. Ed. 2014, 53, 3558. [8] Y. Jiao, Y. Zheng, M. Jaroniec, S. Z. Qiao, Chem. Soc. Rev. 2015, 44, 2060. [9] Y. Zheng, Y. Jiao, M. Jaroniec, S. Z. Qiao, Angew. Chem. Int. Ed. 2015, 54, 52. [10] Y. Jiao, Y. Zheng, M. Jaroniec, S. Z. Qiao, J. Am. Chem. Soc. 2014, 136, 4394. [11] W. Xiong, F. Du, Y. Liu, A. Perez, M. Supp, T. S. Ramakrishnan, L. Dai, L. Jiang, J. Am. Chem. Soc. 2010, 132, 15839. [12] Y. Liang, Y. Li, H. Wang, J. Zhou, J. Wang, T. Regier, H. Dai, Nat. Mater. 2011, 10, 780. [13] Y. Zheng, Y. Jiao, J. Chen, J. Liu, J. Liang, A. Du, W. Zhang, Z. Zhu, S. C. Smith, M. Jaroniec, G. Q. Lu, S. Z. Qiao, J. Am. Chem. Soc. 2011, 133, 20116. [14] B. Hammer, J. K. Nørskov, in Advances in Catalysis, Vol. 45: Impact of Surface Science on Catalysis, (Eds: B. C. Gates, H. Knozinger), Academic Press, Waltham, MA, USA 2000. [15] J. G. Chen, C. A. Menning, M. B. Zellner, Surf. Sci. Rep. 2008, 63, 201. [16] A. Morozan, B. Jousselme, S. Palacin, Energy Environ. Sci. 2011, 4, 1238. [17] S. Park, Y. Shao, J. Liu, Y. Wang, Energy Environ. Sci. 2012, 5, 9331. [18] D.-W. Wang, D. Su, Energy Environ. Sci. 2014, 7, 576. [19] Y. Zheng, Y. Jiao, L. Ge, M. Jaroniec, S. Z. Qiao, Angew. Chem. Int. Ed. 2013, 52, 3110. [20] J. Liang, Y. Jiao, M. Jaroniec, S. Z. Qiao, Angew. Chem. Int. Ed. 2012, 51, 11496. [21] Y. Zheng, Y. Jiao, L. H. Li, T. Xing, Y. Chen, M. Jaroniec, S. Z. Qiao, ACS Nano 2014, 8, 5290. [22] R. Parsons, Catalysis in Electrochemistry, John Wiley & Sons, Inc., Hoboken, NJ, USA 2011. [23] J. K. Nørskov, J. Rossmeisl, A. Logadottir, L. Lindqvist, J. R. Kitchin, T. Bligaard, H. Jónsson, J. Phys. Chem. B 2004, 108, 17886. [24] J. Rossmeisl, Z. W. Qu, H. Zhu, G. J. Kroes, J. K. Nørskov, J. Electroanal. Chem. 2007, 607, 83.
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www.MaterialsViews.com
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[25] J. K. Nørskov, T. Bligaard, A. Logadottir, J. R. Kitchin, J. G. Chen, S. Pandelov, U. Stimming, J. Electrochem. Soc. 2005, 152, J23. [26] A. Verdaguer-Casadevall, D. Deiana, M. Karamad, S. Siahrostami, P. Malacrida, T. W. Hansen, J. Rossmeisl, I. Chorkendorff, I. E. L. Stephens, Nano Lett. 2014, 14, 1603. [27] Y. Sun, Q. Wu, G. Shi, Energy Environ. Sci. 2011, 4, 1113. [28] P. V. Kamat, J. Phys. Chem. Lett. 2011, 2, 42. [29] D. S. Su, J. Zhang, B. Frank, A. Thomas, X. Wang, J. Paraknowitsch, R. Schlögl, ChemSusChem 2010, 3, 169. [30] Y. Zheng, Y. Jiao, M. Jaroniec, Y. Jin, S. Z. Qiao, Small 2012, 8, 3550. [31] L. Dai, D. W. Chang, J.-B. Baek, W. Lu, Small 2012, 8, 1130. [32] Y. Li, W. Zhou, H. Wang, L. Xie, Y. Liang, F. Wei, J.-C. Idrobo, S. J. Pennycook, H. Dai, Nat. Nano. 2012, 7, 394. [33] J. Liang, X. Du, C. Gibson, X. W. Du, S. Z. Qiao, Adv. Mater. 2013, 25, 6226. [34] X. Zhou, J. Qiao, L. Yang, J. Zhang, Adv. Energy Mater. 2014, 4, 1301523. [35] Y. Shao, J. Sui, G. Yin, Y. Gao, Appl. Catal. B 2008, 79, 89. [36] S. Chen, J. Duan, M. Jaroniec, S. Z. Qiao, Adv. Mater. 2014, 26, 2925. [37] S. Chen, J. Duan, M. Jaroniec, S. Z. Qiao, Angew. Chem. Int. Ed. 2013, 52, 13567. [38] S. Chen, S. Z. Qiao, ACS Nano 2013, 7, 10190.
wileyonlinelibrary.com
[39] [40] [41] [42] [43] [44] [45] [46] [47] [48] [49] [50] [51] [52]
J. Duan, S. Chen, M. Jaroniec, S. Z. Qiao, ACS Nano 2015, 9, 931. C. Cheng, D. Li, Adv. Mater. 2013, 25, 13. Y. Liang, Y. Li, H. Wang, H. Dai, J. Am. Chem. Soc. 2013, 135, 2013. H. Wang, H. Dai, Chem. Soc. Rev. 2013,42, 3088. J. Duan, Y. Zheng, S. Chen, Y. Tang, M. Jaroniec, S. Z. Qiao, Chem. Commun. 2013, 49, 7705. R. Zhou, S. Z. Qiao, Chem. Mater. 2014, 26, 5868. J. Duan, S. Chen, S. Dai, S. Z. Qiao, Adv. Funct. Mater. 2014, 24, 2072. T. Y. Ma, S. Dai, M. Jaroniec, S. Z. Qiao, J. Am. Chem. Soc. 2014, 136, 13925. J. Liang, R. F. Zhou, X. M. Chen, Y. H. Tang, S. Z. Qiao, Adv. Mater. 2014, 26, 6074. Y. Zheng, J. Liu, J. Liang, M. Jaroniec, S. Z. Qiao, Energy Environ. Sci. 2012, 5, 6717. J. Liang, Y. Zheng, J. Chen, J. Liu, D. Hulicova-Jurcakova, M. Jaroniec, S. Z. Qiao, Angew. Chem. Int. Ed. 2012, 51, 3892. T. Y. Ma, S. Dai, M. Jaroniec, S. Z. Qiao, Angew. Chem. Int. Ed. 2014, 53, 7281. T. Y. Ma, J. Ran, S. Dai, M. Jaroniec, S. Z. Qiao, Angew. Chem. Int. Ed. 2015, 54, 4646. Y. Zheng, Y. Jiao, Y. Zhu, L. H. Li, Y. Han, Y. Chen, A. Du, M. Jaroniec, S. Z. Qiao, Nat. Commun. 2014, 5, 3783.
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