Design of electrocatalysts for oxygen- and hydrogen-involving energy conversion reactions.

Volume 44 Number 8 21 April 2015 Pages 2023–2576

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REVIEW ARTICLE Shi Zhang Qiao et al. Design of electrocatalysts for oxygen- and hydrogen-involving energy conversion reactions

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Design of electrocatalysts for oxygen- and hydrogen-involving energy conversion reactions Yan Jiao,†a Yao Zheng,†a Mietek Jaroniecb and Shi Zhang Qiao*ac A fundamental change has been achieved in understanding surface electrochemistry due to the profound knowledge of the nature of electrocatalytic processes accumulated over the past several decades and to the recent technological advances in spectroscopy and high resolution imaging. Nowadays one can preferably design electrocatalysts based on the deep theoretical knowledge of electronic structures, via computerguided engineering of the surface and (electro)chemical properties of materials, followed by the synthesis of practical materials with high performance for specific reactions. This review provides insights into both theoretical and experimental electrochemistry toward a better understanding of a series of key clean energy conversion reactions including oxygen reduction reaction (ORR), oxygen evolution reaction (OER), and hydrogen evolution reaction (HER). The emphasis of this review is on the origin of the electrocatalytic activity

Received 10th December 2014 DOI: 10.1039/c4cs00470a

of nanostructured catalysts toward the aforementioned reactions by correlating the apparent electrode performance with their intrinsic electrochemical properties. Also, a rational design of electrocatalysts is proposed starting from the most fundamental aspects of the electronic structure engineering to a more

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practical level of nanotechnological fabrication.

1 Introduction Due to the climate change and depleting petroleum supplies, the research and development of clean energy is of vital importance in the coming decades. Many advanced technologies for clean a

School of Chemical Engineering, University of Adelaide, Adelaide, SA 5005, Australia. E-mail: [email protected] b Department of Chemistry and Biochemistry, Kent State University, Kent, OH 44240, USA c School of Materials Science and Engineering, Tianjin University, Tianjin, 300072, China † These authors contributed equally to this work.

energy conversion, for example fuel cells, water electrolysis, metal–air batteries, and CO2 to fuel conversion, are the subject of both extensive fundamental and utilitarian studies.1–5 These devices serve as key components for sustainable energy utilization infrastructure, as has been widely discussed by academia and government organizations.6,7 The core of these energy conversion technologies is a series of electrochemical processes, which include electrocatalytic oxygen reduction reaction (ORR) and hydrogen oxidation reaction (HOR) that occur on the cathode and anode of a hydrogen–oxygen fuel cell, respectively; and hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) at the cathode and the anode of an electrolytic cell

Yan Jiao received her PhD in 2012 from the University of Queensland. She is currently a postdoctoral researcher in the University of Adelaide working with Professor Shi Zhang Qiao. Her current research focuses on discovering the electronic structure origin of electrocatalytic activity possessed by nanomaterials, and engineering novel carbon-based catalysts for clean energy conversion reactions. Yan Jiao

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Yao Zheng

Yao Zheng received his PhD in 2014 from the University of Queensland (Australia). Currently he is a postdoctoral researcher in the University of Adelaide working with Professor Shi Zhang Qiao. His research focuses on developing cost effective counterparts as alternatives to precious catalysts for some key electrocatalysis processes like oxygen reduction, hydrogen evolution, and CO2 reduction reactions.

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producing gaseous molecular hydrogen and oxygen, respectively.8,9 Fig. 1 presents the half-cell reaction equations and typical steadystate polarization curves for the aforementioned processes. The four reactions shown in Fig. 1 can be grouped into two reversible reaction couples. One of them is hydrogen-involving HER and HOR illustrated by a red curve with the equilibrium potential (U0) of 0 V vs. reversible hydrogen electrode (RHE). The other one is oxygen-involving ORR and OER illustrated by a blue curve with the U0 of 1.23 vs. RHE. Although these reactions are reversible, the shapes of the polarization curves for four half-cell reactions away from the U0 are not the same: HER and OER generally obey the Butler–Volmer model even with very high overpotentials, while the apparent currents for HOR and ORR approach a constant value at high overpotentials due to the limitation in the mass transfer rate.

These reactions have been investigated extensively in recent years and can be considered as the cornerstone for exploring more complicated multi-electron transfer processes. HER–HOR could be viewed as the simplest reaction in electrocatalysis due to the simplicity of reactants, products and the definition of the standard hydrogen electrode (SHE), which causes the chemical potentials of the reactant and the product to be the same. This facilitates the theoretical investigation of the HER–HOR activity: the only parameter that needs to be determined is the hydrogen adsorption free energy (DGH*), and the number of free energy changes is only two.10 Experimentally, HER is also considered as one of the first adsorption systems studied by means of modern ultrahigh vacuum (UHV) surface science techniques.11,12 The other pair includes ORR and OER that are elementary steps for many oxygen-involving reactions such as electrocatalytic CO2 reduction, CO oxidation, methanation reaction, etc.13–16 Apparently, the kinetics of these four key electrochemical processes significantly influences the output performance of the aforementioned clean energy conversion devices. The most arguable critical problem is how to effectively catalyze these reactions on each electrode surface to achieve as low overpotential and high current density as possible. Generally, the kinetics of two-electron transfer in half-cell HER and HOR is facile, while a multistep proton-coupled electron transfer in ORR and OER is kinetically sluggish. For example, at present the poor catalytic performance of the cathodic ORR electrode is the major cause of efficiency reduction in the case of proton exchange membrane fuel cells (PEMFC).2,17 Therefore, these reactions are generally catalyzed by precious metals such as platinum (Pt), iridium (Ir) and ruthenium (Ru)-based catalysts, to achieve favorable reaction kinetics for practical applications.18–21 Besides the requirement for high catalytic activity, other issues related to these catalysts are their comparatively high cost and limited storage, which limit their large-scale applications in

Mietek Jaroniec received his PhD from M. Curie-Sklodowska University (Poland) in 1976; afterward, he was appointed as a faculty at the same University. Since 1991, he has been Professor of Chemistry at Kent State University, Kent, Ohio (USA). His research interests include interfacial chemistry and chemistry of materials, especially adsorption at the gas/solid and liquid/ solid interfaces and nanoporous Mietek Jaroniec materials. At Kent State University he has established a vigorous research program in the area of nanomaterials such as ordered mesoporous silicas, organosilicas, inorganic oxides, carbons, and nanostructured catalysts/ photocatalysts, focusing on their synthesis, characterization and environmental and energy-related applications.

Shi Zhang Qiao received his PhD degree in chemical engineering from the Hong Kong University of Science and Technology in 2000, and is currently a Chair Professor at the School of Chemical Engineering of The University of Adelaide, Australia. His research expertise is in nanomaterials and nanoporous materials for drug/gene delivery and new energy technologies. He has coauthored more than 200 Shi Zhang Qiao papers in refereed journals with over 10800 citations (h-index 51). In recognition of his achievements in research, he was honored with the prestigious ARC Discovery Outstanding Researcher Award (2013), the Emerging Researcher Award (2013, ENFL Division of the American Chemical Society), ARC ARF and APD Fellowships.

Fig. 1 The polarization curves for two pairs of the key energy-related electrochemical reactions and their overall reaction equations. Red and blue curves refer to the hydrogen-involving and oxygen-involving reactions, respectively. The lines are not drawn to scale.


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relevant clean energy technologies. In this regard, the development of novel electrocatalysts that exhibit higher catalytic activity, longer durability, as well as lower cost, could greatly facilitate the realization of clean energy infrastructure. In the past few years, thanks to the remarkable advances in nanotechnology and synthetic chemistry, many novel nanomaterials such as Pt-based alloys with low precious metal content, strongly coupled transition metals (oxides) and nanocarbon hybrids, and non-metal carbon-based materials have been explored as alternatives of precious metal catalysts. A broad spectrum of the available advanced characterization techniques also benefits research in this area, allowing researchers to gain new insights into the nature of the electrocatalytic activity of these new catalysts toward specific reactions. For example, the UHV surface spectroscopic tools like X-ray absorption spectroscopy (XAS) and surface X-ray scattering (SXS) can accurately resolve the chemical bonding structure of catalysts,11,22–24 while some cutting-edge imaging techniques like high angle annular dark-field scanning transmission electron microscopy (HAADF-STEM) and scanning tunneling microscopy (STM) can give more information about chemical components of these catalysts at the molecular/atomic level.25,26 On the other hand, theoretical studies of the energy-related electrocatalysis, initiated long time ago, were restrained by inadequate knowledge of accurate electronic structures.27 Due to the remarkable developments in the density functional theory (DFT) and the availability of powerful computing, nowadays the researchers are capable of investigating catalysts at the atomic level.28 Consequently, many topics in this area have been extensively studied, including the nature of active centers present on the surface of catalysts, the evaluation of the catalytic activity at the atomic level, and ultimately the design of better catalysts toward specific electrochemical processes.28–31 One of the most significant achievements in this field is the volcano-type plot that correlates the intrinsic surface adsorption properties and electronic structure (e.g. electron orbital levels or workfunctions) of a catalyst with its apparent catalytic activity.28,32,33 This relationship successfully explains the trend in the catalytic activity for different surfaces, and provides a guide for the development of catalysts with high catalytic activity. At present, there are tremendous opportunities in advancing electrochemical surface science at the atomic level by merging experimental and computational methodologies. In this review article we present recent achievements in both experimental and theoretical electrochemistry and address two major issues: (i) origin of the activity of various electrocatalysts toward specific reactions, and (ii) synergistic interaction between fundamental science and practical technology, which is the driving force toward molecular/structural design of electrocatalysts. The first part (Section 2) represents a brief review of electrocatalytic processes studied by means of classical thermodynamics and more advanced molecular-level theories such as DFT. The second part (Sections 3–5) presents a concise review of various electrocatalysts for ORR, OER and HER processes at the atomic level. This part contains some featured examples of molecular design of the state-of-the-art electrocatalysts for each reaction, emphasizing a

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successful merging of experimental electrochemistry, synthetic chemistry, and computational chemistry. The conclusion part (Section 6) summarizes the design process of electrocatalysts by taking advantage of the current theoretical capabilities in the electronic structure engineering and experimental methods in the fabrication of nanostructures.

2 Modeling of oxygen- and hydrogeninvolving electrocatalytic processes Usually, the most insightful knowledge of the mechanism of reactions has been inferred from rate measurements;34 with the development of computational power and techniques, the DFT calculations have the potential to provide more in-depth information on the electrochemical processes at the atomic/ molecular level.35–38 This section presents a brief description of the modeling of oxygen- and hydrogen-involving electrocatalytic processes, starting with the electrode dynamics investigated in early days, and finishing with computational chemistry methods currently available. The last part shows how the atomic-level calculations and experimentally obtained quantities are related in terms of the molecular orbital theory. 2.1

Electrode kinetics and activity measurements

2.1.1 Electrode kinetics. For a given electrode process at a certain potential E, the concentrations of reactant and product can be linked by the Nernst equation:39 RT CO 0 ln (2.1) E ¼ E0 þ nF CR where E0 0 is the formal potential of an overall reaction, R is the universal gas constant, T is the temperature, n is the electron transfer number, F is the Faraday constant, and CO/CR is the concentration of oxidized/reduced species in the system. The forward ( jf, i.e., cathodic current density) and backward ( jb, i.e., anodic current density) current densities for a specific reaction are: jf = nFkf CO

(2.2)

jb = nFkbCR

(2.3)

and

where kf and kb are the forward and backward reaction rate constants, respectively, that can be linked, via Arrhenius relationship, to a standard rate constant k0 by: 0

kf = k0 exp[af (E E0 )]

(2.4)

and 0

kb = k0 exp[(1 a) f (E E0 )]

(2.5)

where f is defined as F/RT, and a is the transfer coefficient (ranging from 0 to 1) that can be calculated by Markus theory.39,40 At the equilibrium potential of an electrode reaction step Eeq, the forward and backward reaction rates are the same, which leads to a zero net current, and the electrode adopts a


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potential based on the bulk concentrations of the oxidized and reduced species (i.e. CO* and CR*) that leads to: 0

0

nFk0CO* exp[af(Eeq E0 )] = nFk0CR* exp[(1 a) f (Eeq E0 )] (2.6)


hence the Nernst equation at Eeq is: h i C 1 0 O ¼ ¼ exp f Eeq E 0 CR K

(2.7)

where K is the equilibrium constant, assuming that the concentration of protons is unity.10 Even though the net current is zero at Eeq, there is still a balanced faradaic activity that can be expressed in terms of the exchange current density, j0, which is equal in magnitude to the forward and backward current density: 0

j0 = nFk0CO* exp[af(Eeq E0 )] = nFk0CO*1aCR*a (2.8) The current density j0 is therefore proportional to k0 and can be often substituted for k0 in kinetic equations. At a certain overpotential Z = E Eeq, the overall current density for a certain reaction step can be expressed as follows: j = jf + jb = j0[CO/CO* exp(af Z) CR/CR* exp((1 a)f Z)] (2.9) If the solution is well stirred, or currents are kept at a low level that the surface concentrations do not differ appreciably from the bulk values (i.e. CO = CO*, CR = CR*), then eqn (2.9) becomes the well-known Butler–Volmer equation: j = j0[exp(af Z) exp((1 a)f Z)]

(2.10)

This equation implies that the smaller the value of j0, the more sluggish the kinetics; hence larger activation overpotential is required to achieve the desired net current. 2.1.2 Exchange current density and tafel slope. The exchange current density j0 is one of the most important activity descriptors. Derivation of the overall current density from j0 is presented in Fig. 2a. The dashed lines represent the forward and backward components of the overall current density; their intersection with the Y axis denotes the value of j0. The influence of the transfer coefficient a is also presented in Fig. 2a: the green curve

represents a = 0, which corresponds to a steep oxidant potential energy surface with a flat reductant potential energy surface; and the blue curve represents a = 1, corresponding to a reverse condition (a flat oxidant potential energy surface with a steep reductant potential energy surface). As shown in Fig. 2b, if the current density j0 is large enough (e.g. the red curve), the system can supply large currents even at very low overpotential, which means the activation of the overall reaction is easy with fast electrode kinetics. With the decrease in j0, e.g., the green and blue curves, no significant current flow occurs unless large activation overpotential is applied. Thus, it is often useful to use a plot that relates Z with the logarithm of the current density to evaluate the electrode performance, named the Tafel plot. The Tafel plot for each of the polarization curves in Fig. 2a is presented in Fig. 2c. The cathodic current density is used as an example for showing the Tafel plot: the smaller the Tafel slope (e.g., the blue line), the better the performance. The Tafel plot is also useful for the determination of the reaction mechanism by relating the electron transfer number and the charge transfer coefficient.41 It should be noted that in some instances, at a sufficiently large overpotential, the heterogeneous process can be driven so fast that the mass transfer controls the current, and the limiting plateau is reached as in the case of ORR and HOR presented in Fig. 1. Experimentally, the current density without the effect of mass transfer can be derived through the Koutecky–Levich equation based on the rotating disk electrode’s (RDE) data: 1/jD = 1/jK + 1/Bo1/2

(2.11)

where jK is the kinetic current density, jD is the measured current density on the rotating disk electrode, o is the electrode rotating speed in rpm, and B, the reciprocal of the slope. 2.1.3 Evaluation of electrocatalytic activity. Performance of an electrocatalyst is usually evaluated by using two metrics: (i) apparent total electrode activity (e.g., current density expressed in mA cmgeometric2), which is the most important factor for device-oriented catalyst design, and (ii) the intrinsic activity of each catalytic site (e.g., turnover frequency, TOF expressed in s1), which is more useful for fundamental studies of the catalytic activity. Some electrochemically measurable parameters such as the area-normalized j0 and the number of active sites provide a

Fig. 2 (a) Electrode current density calculated based on a j0 of 103 A cm2. Red, green, and blue lines refer to a = 0.5, 0, 1, respectively. The red dashed lines denote the forward (cathodic) and backward (anodic) components of the current. (b) Influence of j0 on the activation overpotential required to deliver net current densities. Red, green, and blue lines refer to j0 = 103 A cm2, 106 A cm2, and 109 A cm2, respectively. a = 0.5. (c) Tafel slope related to each color polarization curve in panel (a).


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bridge between the intrinsic catalytic activity and the apparent current/overpotential. For example, ultimately, all electrodes’ performances are judged by the overpotential required to reach an operating current density (e.g. 10 mA cm2 for OER and HER to match the 12.3% efficiency for photoelectrochemical water splitting),42 which is determined by both Tafel slope and j0 by strictly following the Tafel equation. Therefore, lower Tafel slopes and higher j0 are desirable, especially for high current applications such as water electrolyzers. Experimentally, nanostructuring is a simple and effective strategy to enhance the apparent electrocatalytic activities for certain bulk electrodes.43 Namely, by fabricating an electrocatalyst with well-developed nanostructure its surface area can be significantly enlarged, which results in a higher number of exposed electrocatalytically active sites per unit geometric area without altering the inherent electronic properties of the electrode. Consequently, normalization of the measured activity of a nanostructured electrode by both surface area and mass loading is essential for evaluating its intrinsic activity. For example, the specific activity (mA cmmetal2) of Pt-based electrodes is the most important characteristic of their ORR performance evaluation, while TOF is always used to compare different HER and OER electrocatalysts.44 The key issue in obtaining these parameters is a precise measurement of the electrocatalytic active surface area (ECSA) reflecting the total number of active sites on a given surface for a certain reaction. Experimentally there are three main methods to determine the ECSA for both single component and hybrid materials: (i) underpotential deposition (upd) hydrogen (Hupd) adsorption voltammetry,45 (ii) CO stripping voltammetry,46 and (iii) Cu upd stripping voltammetry.47 The Hupd adsorption method is widely applicable for Pt and Pt-based alloys. Underpotential is defined as the potential less negative than the equilibrium potential, at which hydrogen can be deposited on the metal surface as a monolayer before bulk deposition and evolution at an overpotential (also named overpotential deposition, opd), as shown in Fig. 3a. This methodology is based on the presumption that each surface Pt atom has the capacity to adsorb one hydrogen atom with a charge of 210 mC cm2; therefore, by calculating the whole upd hydrogen charge in voltammetry (with the subtraction of double-layer capacitance), one can deduct the surface area of

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electrocatalytically active Pt atoms.45 Note that this method is not applicable to Ru and Pd-based materials since there is an overlap of adsorbed hydrogen oxidation and elemental Ru oxidation current at a certain potential (B0.2 V vs. RHE), while there is a bulk hydrogen storage capacitance in the Pd lattice.48 The ECSA of Ru and the Ru–Pt alloy are generally measured by CO-stripping voltammetry, which assumes that one CO molecule can be electrochemically adsorbed on the surface of each metal atom under a relative positive potential.46 Then, in the case of sequentially anodic scan, the adsorbed CO can be stripped and oxidized from the surface of metal at a certain (more positive) potential with a certain charge (e.g. 420 mC cm2 for poly-Pt surface). By comparing it with that of a clean surface (CO-free), one can calculate the total charge of CO adsorption simply from the difference of two voltammetry curves (Fig. 3b). The CO-stripping technique can be used for a wide range of different precious single metal surfaces like Pt, Ru, Pd, Ir, Re and their alloys. An alternative method, Cuupd or Pbupd stripping, can be used for a broader spectrum of surfaces like metal compounds such as a highly effective HER electrocatalyst, tungsten disulfide (WS2).49 As an example, we demonstrate the Cuupd stripping process on a poly-Pt surface, which first reduces (adsorbs) the copper cation from the electrolyte at a more positive potential than its thermodynamic potential to form upd adsorption species. During the sequential anodic scan, the upd Cu species (and also opd Cu if any) will be stripped and oxidized to the Cu cation again into the solution under relatively high potential, as indicated by a blue arrow in Fig. 3c.47 The key issue is a precise measurement of the demarcation point of Cuupd and Cuopd zones (which may be slightly different than its thermodynamic potential) to eliminate the contribution of opd-adsorbed species for stripping and charge calculation. Basically, the aforementioned three methods should give consistent results for a given material while they still depend on the experimental conditions and surface properties of the electrode.45,47 One should select the most suitable method to determine the ECSA of a specific surface. 2.2

Modeling the free energy landscape by DFT

2.2.1 Electrode potential-corrected free energy. The DFT was shown to be a powerful tool in (i) discovering the reaction

Fig. 3 Measurement of ECSA for commercial polycrystalline Pt/C by using three typical voltammetry techniques under different testing conditions (mass loading: 20 mg, scan rate: 10 mV s1). (a) Hupd adsorption voltammetry, (b) CO stripping voltammetry, and (c) Cuupd stripping voltammetry.

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mechanism of electrocatalysis,50–53 and (ii) revealing the active centers,51–55 and ultimately (iii) helping the design of better electrocatalysts.28,56,57 According to the DFT methodology, a chemical reaction process can be described through searching and calculating its reaction pathway.58 By identifying the specific ‘bottleneck’ points along the potential energy surface and then stochastically simulating the reaction rate performance, the DFT method is found to be advantageous as compared to the cumbersome and time consuming calculations based on the real time dynamics. In electrocatalytic processes, due to the inclusion of electrons on the electrode, the energy levels of adsorbed intermediates (as well as the initial and final states) are also functions of the electrode potential U. In addition to the normal free energy obtained by standard DFT calculations, the free energy change introduced by the change in the electrode potential can be realized through shifting the energy level by neU, where n is the electron transfer number for a given reaction.50 On this basis, thermodynamics of a given electrode reaction can be expressed as a function of voltage, and more importantly, the reaction under certain overpotential can be linked directly to the equilibrium status. Fig. 4 shows the free energy diagram for two pairs of reversible oxygen- and hydrogen-involving reactions, constructed as a function of the applied electrode potential bias (e.g. E1, E2, and E3).59 The major information provided by blue lines (real catalyst) in the diagrams (Fig. 4) is the identification of the rate-determining steps (RDS) for each redox couple, which is the formation of the OOH* state and the H* state, respectively. The ideal reaction pathways for each of the aforementioned reactions are also shown as red lines in Fig. 4. These pathways should possess the minimum overall reaction free energy change at the thermodynamic equilibrium potential. In this case, each of the reaction intermediate states should be at the same free energy level as that of the reactant and the product. This phenomenon reflects the Sabatier principle,60 a general explanatory paradigm in heterogeneous catalysis and electrocatalysis. According to this principle the ideal catalyst should bind the reaction intermediates not too weakly or too strongly. So, the overall maximum free energy difference can be lowered and the reaction kinetics can be faster by mediating the strength of adsorption of reaction intermediates.61

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Additional information that can be determined from the above free energy diagram is the reaction on-set potentials. Due to the existence of an energy difference for the RDS, the initialization of the reaction requires a potential bias to reduce this free energy difference to a value that could be overcome automatically. Taking OER as an example, under a more positive electrode potential than the equilibrium potential, the free energies of the product (O2 + 4H+ + 4e) and intermediates states shift downward as compared to those under the equilibrium potential (e.g. in Fig. 4a, data referring to potential E1). As a result, the free energy change for the RDS is reduced (as indicated by the blue dash line), and the whole reaction could proceed with a much faster rate. When the electrode potential becomes more positive and passes beyond E3, the free energy change for the RDS becomes negative and the whole OER process is ‘activated’. A similar phenomenon can also be applied to the cathodic ORR reaction, for which a more negative electrode potential is required. The key issue in constructing the reaction pathway is the calculation of the Gibbs free energy in comparison to the reference energy level (DG). For the reactant, product, and each intermediate state along the reaction pathway, their DG can be calculated using:50,62 DG = DE + DZPE TDS + DGU + DG(pH) + DGfield (2.12) ¨dinger where DE can be calculated directly by solving the Schro equation for a given system. During the calculation of DE, it is highly desirable to incorporate vdW corrections,63–65 since the reactive intermediates and the surface, although weak, determine relative stabilities and thereby dictate the conditions for optimum selectivity.66 The zero point energy correction (DZPE) and entropy terms (TDS) can be obtained by using commercial software packages or can be calculated by frequency calculations.67–69 DGU is the free energy term introduced by changing the electrode potential. DG(pH) is introduced by the pH value of the electrolyte, which can be corrected by the concentration dependence of the entropy as kBT ln 10 pH.70 DGfield originates from the electrical double layer effect, and is normally ignored due to its small value.50

Fig. 4 Gibbs free energy diagrams for chemisorption of intermediates versus the reaction pathways for (a) ORR–OER couple and (b) HER–HOR couple in acidic solutions. Blue and red refer to real and ideal reaction pathways at three different electrode potentials (E1, E2, E3), respectively; the ideal reaction pathway corresponds to an overpotential-free catalyst. Dashed lines indicate energetics at the electrode potential where all thermochemical barriers disappear. Reproduced with permission from ref. 59. Copyright r 2010 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.


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The solvent effects should also be considered in DG calculation in two ways according to the existing literature. One of the methods is the use of an explicit model for introduction of water molecules into the system. A typical set up is adding several water layers.53,71 The advantage of this method is its ability to account for the hydrogen bonding effect and to model surfaces under different electrode potentials by adding an additional H atom into the first water layer to form H3O+.53 Another method for modeling the water environment is by introducing the dielectric effect.72 It should be noted that for a specific reaction like oxygen-involving reaction, there is a requirement to calculate the free energy of O2. Due to the notoriously described triplet ground state, its free energy is normally obtained from the reaction:50,73 O2 + 2H2 - 2H2O

(2.13)

for which the free energy change is 4.92 eV at 298 K and a pressure of 0.035 bar.74 2.2.2 Reaction barriers. Besides DG, the reaction barriers between two states can also significantly influence the overall reaction rate and can be calculated by obtaining the minimum energy pathway (MEP). The usual method for obtaining the MEP with balanced electron numbers for the initial state and final state is by using transition state search algorithms, e.g. the nudged elastic band75,76 or the Linear Synchronous Transit method.77 During this process many different configurations might be identified, and screening them by frequency analysis and adsorption energy comparisons is important. A genuine transition state should possess only one imaginary frequency associated with motion along the reaction pathway.78 In some cases, the reaction barriers are correlated to the surface electrode potential due to the unbalance number of electrons being in two states that link the reaction barrier. Calculation of this kind of reaction barrier is quite difficult as can be seen elsewhere.79,80 2.3

Origin of electrocatalytic activity

2.3.1 Micro-kinetic model. The DFT computed Gibbs free energy values can be related to many kinetic parameters obtained by electrochemical measurements. As mentioned above, j0 for a certain electrocatalytic process can be theoretically calculated by eqn (2.8), in which the concentration of reductant depends on the type of adsorption isotherm. If the reactant coverage obeys the Langmuir adsorption isotherm, the coverage y for reductant R can be expressed by81 y¼

CR K ¼ Ctotal 1 þ K

(2.14)

because of the assumption of unity for proton concentration as shown by eqn (2.7), and Ctotal is the total number of active sites. In the case of a multi-electron transfer process, the overall electrode kinetics depends on the free energy difference of the RDS by assuming that all the other steps are faster than this RDS and do not affect the overall reaction rate. For this step, the left side could be considered as the reactant, i.e. CO in eqn (2.2), and the right side could be considered as a product,

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0

i.e. CR in eqn (2.3). In this way, the term Eeq E0 in eqn (2.7) becomes the corresponding free energy change for RDS:73 1 DGmax U 0 (2.15) K ¼ exp kB T where DGmax(U 0) is the free energy change for the RDS at equilibrium potential U 0.73 Therefore, the j0 can be calculated in the form of coverage y by: j0 = nFk0Ctotal[(1 y)1aya]

(2.16)

where the pre-factor ˆj0 = nFk Ctotal can be fitted from experimentally measured j0 data. Similar to this relationship that gives a comparatively precise information, Nørskov et al. proposed a simpler form for eqn (2.16), using exchange current ik0 and overall electrode current ik as quantities to evaluate activity under U 0 and Z as:50 0

ik0 = B ık exp[DG(U0)/kT]

(2.17)

ik(U) = ik0 exp(eZ/kT)

(2.18)

and

2.3.2 The activity volcano plots. When j0 (eqn (2.16)) is plotted versus DGmax(U 0), a volcano-shaped plot is obtained as shown in Fig. 5. Volcano plots play an important role in electrocatalysis, which can be traced back to seventy years ago.82 An early analytical HER rate expression showed a volcano-type plot based on Langmuir type of adsorption, with the maximum located near DGH* = 0 as shown in Fig. 5a. Although this is the most common shape of the volcano plots, other shapes of these plots are possible when different adsorption models are used, for instance the Temkin model.81 The volcano plot also reflects the Sabatier principle, which states that the optimal catalytic activity can be achieved for a catalyst surface with appropriate binding energies for reactive intermediates. In the case when the intermediates bind too weakly, their activation on the surface is difficult; however if they bind too strongly, all available surface sites are occupied (poisoning effect): as a result, moderate binding energies are a good compromise between these two extreme situations. When the Sabatier principle is used for different reactions, the forms of volcano plots are quite similar except the surface intermediates. For ORR as shown in Fig. 5b, the oxygen adsorption strength (DEO*) can serve as the atomic-level descriptor through which the activity obeys the volcano plot quite well.83 The pioneering work on the OER volcano plot was reported by Trasatti, who used the enthalpy of transition from the lower to higher oxidation state of metal in metal oxides as a descriptor to analyze the electrocatalytic activity of oxide electrodes.84 The reason for this is that OER can be viewed as a transition between two different configurations of the surface coordination complex. As a result, metal oxides that are oxidized with difficulty are not very active because intermediates are weakly adsorbed, and therefore water dissociation is the RDS in this case. On the other hand, oxides that are oxidized easily are also not very active because intermediates are strongly adsorbed,


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Fig. 5 Volcano plots for different surfaces. (a) Relationship between j0 and hydrogen adsorption free energy under the assumption of Langmuir adsorption model. Reproduced with permission from ref. 81. Copyright r 1969, Royal Society of Chemistry. (b) ORR activity for a range of pure metals plotted against O* adsorption energy. Reproduced with permission from ref. 50 Copyright r 2004, American Chemical Society. (c) Activity trends for OER as a function of DGO* DGOH* for rutile and anatase oxides. The activity is expressed by the value of overpotential to achieve a certain value of current density. Reproduced with permission from ref. 87 Copyright r 2011 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim. (d) HER j0 versus hydrogen adsorption free energy for the surfaces of various metals, alloy compounds, and non-metallic materials. Reproduced with permission from ref. 92 Copyright r 2014, Nature Publishing Group.

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and the removal of oxygenated species is the RDS for these electrodes. Later, the OER reactivity has been related to the oxygen adsorption free energy DGO*,85,86 as in the case of ORR. Recently, this activity has been related to a single descriptor (DGO* DGOH*) that is universal for various oxide surfaces including rutile, perovskite, spinel, rock salt, and bixbyite oxides (Fig. 5c).87 For HER, the experimentally derived metal–hydrogen bond energies (EM–H) have been used as the atomic-level activity descriptor.88,89 It was shown that the logarithm of the exchange current plotted against EM–H gives a volcano-type curve, with the value measured for Pt near the apex.90 In recent years the DFT calculated hydrogen binding energy/hydrogen adsorption free energy (DGH*) has been widely used as the activity descriptor.91–93 Fig. 5d shows the volcano plot for many traditional metals, recently studied metal composites/metal alloys, and non-metallic materials. 2.3.3 Origin of adsorbates scaling relationships. Usually, the free energy and related quantities for intermediates formed in oxygen-involving reactions on various surfaces change in the same direction. This phenomenon has been observed for different surfaces including metals, metal oxides, and carbons, and is known as a scaling relationship between the oxygen containing intermediates (Fig. 6).33,73,85–87,94–97 Specifically, in the case of metal surfaces and transition metals embedded in graphene, the lines referring to OOH* and OH* are almost parallel to each other with the slope of one, as shown in Fig. 6a and b. The same slope value has also been observed for metal oxide and graphene surfaces (Fig. 6c and d). The underlying principle for such behavior is the nature of binding of the pair

Fig. 6 Correlations for adsorption intermediates appearing in oxygen-involving reactions on: (a) metal surfaces. Horizontal lines for water and oxygen have been drawn at 0 eV and 4.92 eV, respectively. The optimal Gibbs free energy value for each intermediate is also shown in figure. Reproduced with permission from ref. 96. Copyright r 2012, Royal Society of Chemistry. (b) Transition metals embedded in graphene via nitrogen linking. Triangles and squares represent supercells with different nitrogen/transition metal configurations, shown as insets cell (A) and cell (B). Horizontal lines for water and oxygen have been drawn at 0 eV and 4.92 eV, respectively. Reproduced with permission from ref. 97. Copyright r 2011, Royal Society of Chemistry. (c) Metal-oxide surfaces. Reproduced with permission from ref. 87. Copyright r 2011 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim. (d) Graphene surfaces. Reproduced with permission from ref. 73. Copyright r 2014, American Chemical Society.


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of adsorbates, OOH* and OH*, to the surface through an oxygen atom via a single bond. In the case of O*, which usually forms two bonds with the surface, the slope of the O* vs. OH* dependence is normally two.87 Although volcano plot and surface adsorbate scaling relationships provide qualitative arguments for tuning catalytic activity by varying the bond strength between the catalyst surface and reaction intermediates, they do not have predictive power to guide the discovery of new catalysts with enhanced activity. In this regard, the relationship between the surface adsorbate binding strength and the electronic band structure has been investigated for engineering catalyst materials. The most commonly related band structure is the d-band for elemental-metal and metal alloys/oxides (Fig. 7a, b, d and e),10,98–101 and the valence band for non-metallic carbon materials (Fig. 7c and f).56,73 Additionally, the concept of work function has also been related to the surface adsorption energies in evaluating the ORR and HER activities on metal surfaces.89,102 It has been shown that the d-band model, developed by Hammer and Nørskov, can predict the trends in the behavior of chemisorption energies for various adsorbates on metalcontaining surfaces, and has great explanatory and predictive power.103–106 The model correlates the central moment of d-band projected on the surface atoms (d-band center referenced to the Fermi level, ed) with the surface reactivity for designing novel metal surfaces.28,35,107 The chief principle underlying the d-band center theory is that the binding energy of an adsorbate to a metal surface is largely dependent on the electronic structure of the surface itself. Taking into account adsorption of oxygencontaining intermediates as an example shown in Fig. 8a,35 the formation of bonds between oxygen orbitals and the metal

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surface d electrons result in the filled, bonding molecular orbital and a partly filled anti-bonding one. The overall interaction in the bonding formation is approximately the same for all transition metals, but the anti-bonding energy levels for various metals are different; an increased filling of the anti-bonding states, which is led by a deeper d-band, corresponds to some destabilization of the metal–adsorbate interaction, and hence weaker binding. Similar principles can also be applied to hydrogen adsorption on metal surfaces: an increased filling of the anti-bonding states corresponds to destabilization of the metal–H interaction (weaker binding).108 As shown in Fig. 8b, the filling of the antibonding state for Au(111) is the largest among four metals due to the low value of H 1s–d anti-bonding, hence the hydrogen adsorption energy on this surface is the weakest. A similar situation can be observed for Cu(111), for which the hydrogen binding strength is very weak. On the contrary, for Ni(111), the energy level of the anti-bonding state formed by the hydrogen 1s orbital and the metal d orbital is high, which leads to a low filling of this state and hence a strong hydrogen adsorption strength. Pt(111) possesses the most favorable ed value and its performance for HER is the best. In the experimental perspective, ed can be affected by the inter-atomic distance of the surface metal atoms; for example, stretching/compressing the surface Pt atoms by placing them on another layer of metals with different lattice constants.109 When metals with larger lattice constant are used, the parent metal Pt is under tensile strain, and its d-orbital overlapping decreases, resulting in a narrow d-band and an up-shifted ed. Conversely, if the second metal has a smaller lattice constant than Pt, the parent metal is under compressive strain, which leads to the increase of the d-orbital overlap. As a result, the d-band

Fig. 7 (upper panels) Relationship between specific bands in electronic structures and the oxygen binding strength for (a) elemental-metal surfaces. Reproduced with permission from ref. 98. Copyright r 2000, Elsevier Inc. (b) Metal oxides. Yellow band represents the experimentally measured occupation of d states with eg symmetry; purple band represents DFT calculations for t2g symmetry occupation versus the oxygen adsorption energy. Reproduced with permission from ref. 101. Copyright r 2011, American Association for the Advancement of Science. (c) Graphene surfaces. Reproduced with permission from ref. 73. Copyright r 2014, American Chemical Society. (bottom panels) Relations between specific bands and the hydrogen binding strength for (d) elemental-metals. d-band center values are obtained from ref. 98 and hydrogen binding energies are obtained from ref. 10. (e) Metal alloys. Reproduced with permission from ref. 100. Copyright r 2004, Nature Publishing Group. (f) Graphene surfaces. Reproduced with permission from ref. 56. Copyright r 2014, American Chemical Society.

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Fig. 8 Relationship between catalyst electronic structure and reaction intermediate adsorption energy. (a) Metal-oxygen bonding scheme. Reproduced with permission from ref. 29. Copyright r 2011, National Academy of Sciences, USA. (b) Metal–hydrogen bonding scheme. Reproduced with permission from ref. 103. Copyright r 1995, Nature Publishing Group. (c) Transition metal oxide–oxygen bonding scheme. Reproduced with permission from ref. 116. Copyright r 2013, Nature Publishing Group. Definition of eg and t2g in Fig. 7b is displayed on the right. Reproduced with permission from ref. 115. Copyright r 1962, American Chemical Society. (d) Graphene–oxygen bonding scheme. Reproduced with permission from ref. 73. Copyright r 2014, American Chemical Society.

orbitals become broader and the ed decreases.110–112 A subtle modification of the d-band center could be achieved by selecting an appropriate ligand. The d electrons in transition metals such as Ni, Co, Fe, and Ag tend to transfer to Pt or Pd, which consequently down-shifts the d-band of the latter.113,114 In the design of real catalysts, the two aforementioned effects are usually not well separated from each other so they should be considered simultaneously. In metal oxides, metal 3d-band splits into two: doubly degenerated eg symmetry and triply degenerated t2g symmetry as shown in Fig. 8c.115 Yang et al. firstly reported that the experimentally determined eg orbital filling of the transition metal ions shows a linear relationship with the surface oxygen binding energy,99 which has been confirmed by DFT calculations.101 In addition, theoretical studies also reveal that there is a similar correlation between the adsorption energy and the occupancy of the other d symmetry component of t2g orbital. Later, Yang et al. reported that the oxygen binding strength on the surface of metal oxides should be correlated to the oxygen ion’s p-band center of a metal oxide by showing that the p-band center position scales linearly with the energy of oxygen vacancy formation and the oxygen surface exchange kinetics.116 For non-metallic materials, a comparable method to that based on the d-band theory exists that could correlate the oxygen adsorption with that of the substrate’s valence band.73 The natural bond order (NBO) method117 has been used to investigate the valence orbitals for different graphene cluster models. The descriptor within this scheme is defined as Ediff, which is the difference between lowest and highest valence orbital energies as shown in Fig. 8d. The valence band (n) of the surface active sites hybridizes with the bonding (s) orbital of


the adsorbed species to form bonding (n–s) and antibonding (n–s)* states. For carbon models, the (n–s) state is full, while the filling of the (n–s)* state depends on the valence orbital levels. A lower valence band will induce an increased filling of the (n–s)* state, and leads to some destabilization of the graphene–adsorbate interaction. In contrast, a decreased filling of the (n–s)* state corresponds to enhanced binding for surface adsorbates. Due to the aforementioned bond formation scheme, the reaction intermediate’s adsorption generally follows a linear relationship with Ediff, as shown in Fig. 7c. Knowing how adsorption energies of different intermediates are related would be crucial for understanding activity trends, and may impose some important limitations on the design of catalysts. In the designing process of new catalysts, the availability of the volcano plot for a substrate for each reaction, in combination with the scale relationship between different adsorption strengths of adsorbates can be used to predict the best performance of each substrate for specific reactions, as well as to achieve the optimal adsorption energy of intermediates. The specific examples for the design of materials according to this principle will be further discussed in the following sections.

3 Atomic-level understanding of ORR catalysts The overall ORR equation, which involves either four-electron (4e) or two-step two-electron transfer (2e), is shown in Table 1.118 In fuel cell operations, a direct 4e pathway is highly preferred in order to get high efficiency, while selective 2e reduction is used in industrial H2O2 production.119 The detailed

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mechanisms of ORR are complicated and primarily depend on the surface properties of the electrode. For the 4e pathway, there are two possible mechanisms (i.e. dissociative and associative pathways) proposed in alkaline solution (there are also similar pathways in acidic solution, not shown here) as:51,120 Dissociative mechanism: O2 + 2* - 2O*

(3.1)

2O* + 2e + 2H2O - 2OH* + 2OH

(3.2)

2OH* + 2e - 2OH + 2*

(3.3)

where * denotes one catalytic active site on a certain surface. This mechanism can be described as the initial O2 adsorption, followed by O–O bond breaking and formation of two adsorbed atomic O* species, which further gain two electrons and two protons to form directly the final product OH without OOH generation. Therefore, this mechanism can be considered a direct 4e pathway. Alternatively, ORR can also proceed according to the following associative mechanism: the four-electron pathway: O2 + * - O2*

(3.4)

O2* + H2O + e - OOH* + OH

(3.5)

OOH* + e - O* + OH

(3.6)

O* + H2O + e - OH* + OH

(3.7)

OH* + e - OH + *

(3.8)

O2 + * - O2*

(3.9)

or the two-electron pathway:

O2* + H2O + e - OOH* + OH

(3.10)

OOH* + e - OOH + *

(3.11)

Whether the reaction takes a dissociative or an associative pathway depends mainly on the initial O2 dissociating energy barrier on a given surface.51 For example, several DFT calculation studies showed that this dissociation energy barrier value for carbon surfaces is normally very high,121 accordingly not favorable for the 4e dissociative pathway. Therefore, the experimentally measured electron transfer numbers on almost all carbon materials are smaller than four. In contrast, ORR on the most metal surfaces normally takes a dissociative pathway due to the strong adsorption of O2. For instance, the adsorption free energy of O2 on Pt(111) surface is around 0.6 eV with a very low O2 dissociation barrier being less than 0.3 eV.122,123

This theoretical result is also consistent with experimental finding that Pt-based materials always show perfect 4e reduction selectivity. One of the exceptional cases among metals is Ag(111), on which the O2 adsorption is weak, which results in high O2 dissociation barrier of 41 eV.124 For this reason the reaction pathway on the Ag surface obeys generally the associative mechanism with strong 2e pathway selectivity. 3.1

Pt has been the most well studied ORR electrode since the 1960’s and is still the most active one. Although the commercially used electrocatalysts in fuel cells are Pt nanoparticles (NP) supported on a conductive carbon black, researchers usually use single-crystalline Pt (sc-Pt) to investigate the nature of ORR since it is more homogeneous, representative and easier to model by computations than poly-crystalline one (poly-Pt).125 A lot of experimental and theoretical studies indicate that ORR on sc-Pt surface is a structure–sensitive process. Markovic et al. reported a series of ORR measurements on different low-index Pt planes in acidic solutions, finding that the activities of each plane appear to be totally different and obey the following order: (110) 4 (100) 4 (111).11 Electrochemical studies indicate that the sensitivity of the ORR activity is not only attributed to the geometric effect of different planes but also the effect associated with adsorption of electrolyte species.11 In addition, such differences are also visible in diffusion limiting zone at very high overpotential where current drops with H2O2 generation. Interestingly, the trend of H2O2 yield is the same with ORR activity in kinetic zones, mainly due to the formation of Hupd adsorption to block the surface sites or inhibit O–O bond scission to convert ORR into a two-electron pathway.11 On the molecular level, the structural sensitivity of ORR on low-index Pt surfaces can be also revealed by free energy diagram.50,126,127 The theoretical trend of ORR activity is (111) 4 (100) 4 (110) under 0.9 V vs. RHE, different with the experimentally measured sequence. This may be due to the changes in the surface coverage of O-containing species with the potential and may affect the free energy of the different reaction intermediates.126 Recently, the studies of structure sensitive catalytic activity for ORR have been extended to well-defined Pt NPs system. The different activities on shape-controlled Pt NPs (spherical, cubic, hexagonal, and tetrahedral–octahedral) can be directly imaged by scanning electrochemical microscopy.128 This study also indicates that preferentially oriented Pt NPs could significantly change their ORR activity due to the specific adsorption of anions in electrolyte, which agrees with the findings for sc-Pt systems. 3.2

Table 1

Overall reaction equations of ORR in acidic and alkaline solutions

Electrolyte

Reactions

Acidic solution

O2 + 4H+ + 4e - H2O O2 + 2H+ + 2e - H2O2 H2O2 + 2H+ + 2e - 2H2O

Alkaline solution

O2 + H2O + 4e - 4OH O2 + H2O + 2e - OOH + OH OOH + H2O + 2e - 3OH

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Single crystalline Pt

Pt alloys

It is widely realized that the surface structures of pure Pt NPs are unstable under fuel cell operating conditions, resulting in deactivated facets and degradation of catalytic activities.129 Alloying Pt with some secondary metals can enhance stability and increase activity as compared to that of pure Pt.96,130–134 The activities of Pt-alloy based NPs depend on both the composition and structure (ordering and morphology) and their interactions. With the help of HAADF-STEM and synchrotron


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spectroscopy like XAS and anomalous small-angle X-ray diffraction (ASAXS) etc., it was possible to find more details of the spatial elemental distribution and chemical interaction between primary and secondary metals. Experimentally, a wide variety of non-precious transition metals (Ni, Fe, Co, Cu etc.) has been incorporated into the Pt skeleton by carefully designed solution-based synthesis leading to uniformly shaped nanoparticles (Fig. 9a).135–142 For a certain composition of Pt-alloys, different synthetic methods, including metal precursor, solvent, reducing agent, capping agent and medium, can also significantly influence the activity of synthesized NPs as indicated in a recent review.143 In addition to expanding the variation of compositions, the architectural studies of Pt alloys have also been proposed to preferably expose the most electrocatalytically active facets and sites. Basically there are two approaches to construct the alloy nanostructures named ‘‘core–shell’’ and ‘‘skin–skeleton’’

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structures.143 The primary principle of the above strategies is controlling the surface composition to optimize the whole alloy’s activity. The core–shell NPs always contain a Pt-rich shell and Pt-deficient pure metal or alloy core (usually Fe, Co, Ni, and Cu).144–150 The origin of ORR activity enhancement of these materials is structure-induced strain effect (metal lattice mismatch) and unique electronic property (metal redox property differences) associated with beneficial chemisorption properties of surface atoms.96 Experimental evidence demonstrate that their (electro)catalytic properties can be easily tailored by Pt shell thickness, core composition, diameter and shape (Fig. 9b).151 Generally there are three strategies for controllable synthesis of these core–shell structures: (i) deposition of Pt followed by galvanic displacement, example: Pd/PtML, or PdAu/PtML;152 (ii) acidic and/or electrochemical leaching or dealloying, examples: Cu/Pt,153,154 Ni/Pt,149,155 Co/Pt,156–158 Fe/Pt; and (iii) adsorbate or thermal induced segregation, example: Co/Pt.159

Fig. 9 (a) Typical TEM images of Pt-based alloy NPs catalysts with various composition and shapes; insets show the ORR performance of the corresponding NPs as compared to pure Pt; images are reproduced with permission from ref. 135. Copyright r 2010, American Chemical Society. Ref. 137. Copyright r 2011, American Chemical Society. Ref. 140. Copyright r 2010, American Chemical Society. Ref. 141. Copyright r 2014, American Chemical Society. Ref. 142. Copyright r 2012, American Chemical Society, respectively. (b) HAADF-STEM images of Pt-based alloy NPs catalysts with core–shell structures. Insets show the overview or cross-section view of spatial Pt and secondary metal distribution. Images are reproduced with permission from ref. 144. Copyright r 2012, Nature Publishing Group. Ref. 145. Copyright r 2013, Nature Publishing Group. Ref. 146. Copyright r 2012, American Chemical Society. Ref. 147. Copyright r 2013, Nature Publishing Group. Ref. 148. Copyright r 2011, American Chemical Society, ref. 149. Copyright r 2012, American Chemical Society, respectively.


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Another remarkably high activity for ORR was observed on Pt skin–skeleton structure, in which the Pt skin was prepared through segregating a pure Pt atomic layer on the top of an alloyed second layer by thermal annealing. Stamenkovic et al. designed and prepared stoichiometric Pt3M (M = Co or Ni) alloy with three types of surfaces (i) random surface with non-uniform Pt and M distribution; (ii) Pt-skeleton surface and (iii) Pt-skin surface with pure Pt on the top of Pt3M sublayer.160–162 The electrochemical tests showed that Pt-skin structure has the most enhanced activity due to the formation of OHad at most positive potential (i.e. most active Pt sites). Inspired by this finding, they further developed this concept into low index Pt single crystal system, and found the following ORR activity order: Pt3Ni(100)-skin o Pt3Ni(110)-skin | Pt3Ni(111)-skin, in which Pt3Ni(111)-skin showed the specific activity near 10 times of that on pure Pt(111) (Fig. 10a).163 A significant activity enhancement is arising from a synergy between surface geometry and surface electronic structure as shown in Fig. 10b.163 Very recently, these ‘‘skin-type structures’’ have been further extended to the well-defined Pt-alloy NPs with a multilayered Pt-skin surface, which showed higher specific and mass activities than those of commercial poly-Pt catalyst.148 On the molecular level, the apparent ORR catalytic activity enhancement observed for Pt-alloys can be attributed to two aspects: ligand effect and strain effect, which may respectively or interactively change the d-band center and chemisorption properties of the surface as discussed in Section 2.3.3.96 On the basis of d-band center theory, the specific alloying can lead to a down shift of d-band center position and thus to a weakening of adsorption of OH* on Pt surface.35,164 As a result, the catalytic activities of Pt-alloy materials vs. the position of d-band center

Fig. 10 (a) In situ characterization and ORR performance of the Pt3Ni(111) surface in 0.1 M HClO4. (b) Influence of surface morphology and the d-band center on the ORR kinetics on different Pt3Ni(hkl) alloy surfaces. (c) Relationship between the catalytic properties and electronic structure of the Pt-skin surfaces. (a) and (b) are Reproduced with permission from ref. 163. Copyright r 2007, American Association for the Advancement of Science. (c) Is reproduced with permission from ref. 161. Copyright r 2007, Nature Publishing Group.

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form a classic volcano-type dependence as shown in Fig. 10c.161 The theory underlying the aforementioned dependence is that an appropriate electronic structure is needed to assure the best catalytic activity. If the d-band of a metal approaches the Fermi level, a stronger adsorption is observed, and hence the activity is on the right branch of the volcano plot, lower than the peak. On the other hand, if the d-band of a metal moves away from Fermi level, a weaker adsorption is observed, which leads to a decreased activity, located on the left branch of the volcano plot.35,98,161 3.3

Non-precious metals

Beside Pt-based materials and alloys, the most promising candidates for ORR electrocatalysts are non-precious metal compounds (NPMCs); some of them possess high ORR activity and stability, which approach or even surpass those of Pt-based counterparts in alkaline solutions, although their performance in acidic solutions are not so good.165 The most promising NPMCs investigated so far are: (i) metal–N4 organometallic complexes (M–N4, M = Co, Fe) with or without carbon support; and (ii) metals coupled with nitrogen-containing carbon materials (M–Nx/C, M = Co, Fe, Ni, Mn, and normally x = 2 or 4). The DFT studies of these nanostructured electrocatalysts can shade new light into nature of their high ORR activity. 3.3.1 Non-pyrolyzed macrocycles (M–N4). The study of NPMCs as potential ORR electrocatalysts began in 1960’s when Jasinski discovered a simple metal–phthalocyanine material (M–Pc, M = Co, Ni, Cu) that can catalyze ORR in alkaline media.166 The origin of high activity of these electrocatalysts is the presence of delocalized p-electrons in Pc, which assure the fast electron transfer in electrochemical reactions.167 Therefore, the reactivity of a macrocycle depends on the energy level of its highest occupied molecular orbital (HOMOmacrocycle) as compared to the lowest unoccupied molecular orbital of oxygen molecule (LUMOO2).168 In the next decades following the pioneering work of Jasinski,166 this kind of organometallic materials was largely extended to a wider spectrum of N4– macrocyclic components with different metals like Fe, Co, Ni, Mn, Cu, Zn and macrocycles like (tetraphenyl)porphyrins (TPP), phenanthroline (PHEN) etc.143,165,168–175 The best ORR performance was always found for Fe–N4 materials, following these based on Co and Ni, due to the most favorable electron occupation of 3d orbitals in Fe.176 Additionally, the ORR activities of all these materials strongly depend on the type of metal centers, metal–N2 edge defects, and the nature of macrocyclic ligand. The DFT calculations of ORR on FePc and CoPc show that the type of the central metal is the key factor influencing adsorption energies of initial O2 (affecting the overall ORR kinetics), intermediate OH (affecting the catalysts’ stability), and H2O2 species (affecting 2e or 4e pathway selectivity) on these macrocyclic complexes.177 Additionally, the molecule’s geometrical structure (e.g. the distance between metal and two N atoms in N–Fe–N cluster) may also affect the ORR activity and efficiency by influencing the initial O–O bond breaking.178,179 3.3.2 Pyrolyzed macrocycles (M–Nx/C). The most significant limitation of pristine M–N4 organometallic complexes is their


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dismal stability in acid solutions due to metal dissolution. Pyrolysis of M–N4 at a high temperature (4800 1C) to form M–Nx/C hybrids with strong covalent metal–nitrogen bond can greatly enhance their stability, and simultaneously their activity (Fig. 11a).143,165,180–183 During pyrolysis process, the nitrogencontaining peripheral ligands are converted to pyrrolic, pyridinic, and graphitic nitrogen species bonded to metal center, while the metal can catalyze the formation of graphitic carbon shell around nanoparticle formed to enhance its conductivity and protect the metal center (Fig. 11b).183 The M–Nx/C materials can also be chemically synthesized by pyrolysis of transition metals and nitrogen precursors adsorbed on carbon supports at high temperatures. A large variety of metal salts (e.g. iron acetate or cobalt chloride) or metallic complexes (e.g. ferrocene or Prussian blues) can be chosen as metal precursors, while the nitrogen sources may be either NH3, CH3CN, or other N-containing molecules like phthalocyanines, porphyrins, polyaniline, etc.143,165 Depending on the various precursor choices, the resulting materials may be structures with different coordination numbers, such as M–N4/C, M–N2/C and M–N2+2/C, etc. (Fig. 11c), which can be characterized by Time-of-Flight Secondary Ion Mass Spectrometry (ToF-SIMS), Mossbauer spectrum or XAS.184,185 There are extensive studies and several excellent review papers regarding the effects of various factors on the ORR performance of these NPMCs, including choosing metal–nitrogen precursors, heat-treatment temperature on nitrogen doping, and in situ formed graphitized carbon nanostructure, etc.186–188 The third method is based on the stabilization of transition metal atoms in nitrogen doped graphene (N-graphene) framework forming an in-plane M–Nx motif (x = 2 or 4), in which metal atom is bonded to four pyridinic nitrogen atoms.97,184,189,190 The number of active sites in such system

Fig. 11 (a) Polarization curves of the Fe-based NPMC cathode in a H2–O2 single fuel cell test at 80 1C and 100% relative humidity. Reproduced with permission from ref. 182. Copyright r 2009, American Association for the Advancement of Science. (b) Typical HRTEM image of a Fe-based NPMC with graphitic carbon shell. Reproduced with permission from ref. 183. Copyright r 2011, American Association for the Advancement of Science. (c) Representative molecular structures of M–N2/C, M–N4/C, M–N2+2/C, respectively. Green: carbon; blue: nitrogen; yellow: iron or cobalt.


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is limited by the total number of nitrogen doping sites in N-graphene. The computational prediction shows that an M–N4 defect motif in graphene matrix is energetically favorable for the formation of M–N2 counterparts; M–N4 structure shows stronger interaction with O2 reactant and better structural stability during the ORR process.62,191,192 Similarly, functional N-rich graphene can also attach, grow, and anchor metal salt precursors to grow metal (hydro)oxides NPs on its out-of-plane surface, to form a metal–nanocarbon hybrid with strong coupling effect between metal and N species.193 This coupling may induce chemical and/ or electrical attachment between catalytically active NPs and conductive nanocarbon substrates, leading to a synergistically enhanced electrocatalytic activity for ORR.194–197 3.4

Non-metallic catalysts

Besides as a support for some active metallic NPs, many nonmetallic materials also have considerable catalytic potential and the same functions as conventional metallic ones. The origin of their high activity may be their unique electronic structure for reactant/intermediate adsorption and variable nanostructure for enlarging the number of exposed active sites. There are two major classes of currently developed metal-free ORR catalysts: carbonbased materials,198–203 and nitride materials.57,204–207 Although their electrocatalytic activities are not comparable to precious metals, they all present considerable durability and cost-effective features as promising Pt alternatives. The most developed metal-fee catalysts toward ORR, both theoretically and experimentally, are carbon and its derivatives. Pure carbons (nanostructured carbons, CNT, and graphene sheets) generally show negligible electrocatalytic activities, while doping different non-metals heteroatoms (e.g., N, B, S, O, P) into their frameworks can significantly enhance their ORR activities by (i) changing the electronic character of the carbon and (ii) creating rational defect structures to enable a stronger oxygen adsorption.198,200 The ORR activity of doped carbons is strongly depended on the doping site and content of heteroatoms, which can be carefully controlled by designed doping procedure and precursor choice (Fig. 12a). Among all heteroatoms, nitrogen doped CNT and graphene are most widely studied due to their easier synthesis and relatively good performance. Generally, there are three types of nitrogen species in carbon matrix (i.e. pyridinic, pyrrolic, graphitic N) depending on their different positions and bonding configurations; the mechanism of different nitrogen functions toward ORR has recently been revealed by theoretical studies.73 Beyond single doped graphene, double or triple-doped graphene (e.g. B/N,207,208 S/N,54 P/N,209 and N/B/P210) show much higher ORR activity as compared to single-doped ones. The DFT calculations revealed that the origin of this enhancement is the inter-molecular synergistic catalysis. Although the experimental studies of ORR mechanism on metal-free materials are difficult, theoretical analysis indicates that dopant can tailor the electron–donor properties of nearby carbon atoms, which act as active sites to enhance intermediate OOH* adsorption. Extensive efforts have been undertaken to investigate the origin of ORR activity of graphene-based materials by performing

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Fig. 12 (a) Typical atomic configuration of different types of dopants at different doping sites in the graphene matrix. (b) Free energy diagram of different heteroatom-doped graphenes at the equilibrium potential U0. (c) Experimentally determined Tafel plots for different catalysts. (d) Free energy diagram and optimized configurations of adsorbed species on the g-C3N4 surface with zero, two and four electrons participation demonstrated as paths I–III. (e) Typical TEM image and (f) ORR performance of the synthesized g-C3N4@CMK-3 composite. (b) and (c) are reproduced with permission from ref. 73. Copyright r 2014, American Chemical Society. (d)–(f) are reproduced with permission from ref. 57. Copyright r 2011, American Chemical Society.

systematic experiments and calculations.73 It was shown that different types of dopants and different doping sites in graphene can alter the free energy diagram of the ORR reaction pathway as shown in Fig. 12b. Among various doped graphenes, N-graphene shows the lowest free energy change, indicating its possible highest ORR activity, which is consistent with many experimental works (Fig. 12c).199 Recent studies combining the DFT calculations and electrochemical measurements showed that an ideal doped graphene material has a potential to surpass the ORR performance of the state-ofthe-art Pt catalysts.73 As regards the most promising N-graphene, the limited N content (usually 2–5 atm%) and leaching of N active sites tend to result in low and unstable catalytic activity of these materials. Therefore, the recently developed nitride materials like graphiticcarbon nitride (g-C3N4) and hexagonal-boron nitride (h-BN) with high N content and stable molecular structure can be easily synthesized and used as feasible metal-free ORR electrocatalysts.204,206 Both g-C3N4 and h-BN are non-conductive in nature with band gap of B2.6 and 5.2 eV, respectively; as a result, they need to be combined with carbon or other metal supports to facilitate electron transfer.204 For example, theoretical analysis indicates that the limited electron transfer capability on g-C3N4 surface and bulk is the major reason for its low ORR activity due to the large accumulation of OOH*

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intermediate on the surface, leading to the blockage of active sites (Fig. 12d).57 By incorporating carbon framework like mesoporous carbon (CMK-3) or graphene as conductive supports, the resulting hybrid materials become highly active ORR electrocatalysts (Fig. 12e). Their superior activity originates from both enlarged surface area with more exposed active sites and facile electron transfer reducing the reaction barrier.57 Similarly, the DFT calculations predict that a suitable substrate like Au(111) or graphene can dramatically change the ability of h-BN monolayer to activate O2 and tailor OOH* adsorption properties.206,207 As the proof-of-concept a liquid exfoliated h-BN on Au(111) was examined to confirm that the interface between h-BN and Au plays a vital role in enhancing the ORR activity.206

4 Atomic-level understanding of OER catalysts As can be seen from the reaction diagram, the OER pathway is just a reverse version to of the ORR pathway (Fig. 4): in the ORR process O2 is reduced into H2O or OH, while in OER H2O is oxidized to O2. The mechanism of OER is very sensitive to the structure of electrode surface; different materials or one material with different facets can exhibit various reaction


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Overall reaction pathway for OER in acidic and alkaline solutions

Overall reaction (condition)

Reaction pathway

2H2O - O2 + 4H + 4e (Acidic solution)

* + H2O - *OH + H+ + e *OH - *O + H+ + e *O + H2O - OOH* + H+ + e *OOH - *O2 + H+ + e *O2 - * + O2

4OH - O2 + 2H2O + 4e (Alkaline solution)

* + OH - *OH + e *OH + OH - H2O + *O + e *O + OH - *OOH + e *OOH + OH - *O2 + e *O2 - * + O2


+

mechanisms.211,212 The generally accepted overall reaction pathways for OER involves four discrete electron transfer steps, which are listed in Table 2.59,87,213 4.1

Precious metals (oxides)

The first studies of OER electrocatalysts date back to the 1960s and were devoted to single metals. The experimentally established overpotential sequence for OER in acidic solutions is: Ru o Ir o Pd o Rh o Pt;214 interestingly a reversed trend is observed for ORR (this issue will be discussed in Section 4.4). At high anodic potentials, the single metals typically tend to be corroded to form metal oxide film on the surface during OER process (Fig. 13a);215 the stability trend for different metals is exactly reversed to the corresponding activity trend: among noble metals Pt is the most stable and Ru is the most unstable electrocatalyst. Metal oxide with the highest OER activity is rutile-type ruthenium oxide (r-RuO2) in both acidic and alkaline solutions (Fig. 13b and c).216 At present, the mechanism and OER pathway on the surface of RuO2 is well studied by DFT

calculations while its real performance is still strongly related to the surface chemical/physical properties like local electronic structure, crystallinity, roughness factors and porosity.85,217 A major drawback of the most active RuO2 is its weak stability under acidic conditions in the case of commercial water electrolysis; during oxygen evolution under high anodic potential (41.4 V), it can be oxidized to ruthenium tetroxide (RuO4) while the latter is dissolvable.215,218 As a result, the surface of RuO2 is irreversibly changed and its high activity is vanished. An alternative to RuO2 is iridium oxide (IrO2) that possesses an increased stability in OER processes for up to 2.0 V anodic potential, and only slightly higher overpotential than that of RuO2. Additionally, Ru–Ir alloys and oxides have been studied as OER electrocatalysts with enhanced electrochemical activity and thermodynamic stability.219–221 The electrochemical properties of the mixed oxides are determined by interaction between metal-containing sites and oxides’ surface charge. To further maintain mixed valences (III–IV) of Ru cations in RuOx and inhibit its anodic corrosion, ternary oxides containing tantalum and tin like RuIr0.5Ta0.5Ox and Sn0.5Ru0.25Ir0.25O2 have been proposed,222,223 which all showed significantly enhanced stabilities as well as considerable activities. 4.2

Transition metals (oxides)

Generally, there are three classes of non-precious metal OER catalysts for alkaline electrolytes. The firstly studied and still popular electrocatalysts are Ni- and Co-based oxides (both free standing and supported on carbon or other metals), although their activities still are not comparable to precious Ru and Ir based materials (Fig. 13b).224–227 Particularly for CoOx and CoOOH materials, the nature of their OER activities, stability in alkaline solutions and OER mechanism have been thoroughly

Fig. 13 (a) Relationship between potential-dependent variations in the oxidation state, stability, and activity for active Ru and Ir catalysts. Reproduced with permission from ref. 215. Copyright r 2014, American Chemical Society. (b and c) Overview of the state-of-the-art electrocatalysts for OER in either acidic or alkaline solutions. Reproduced with permission from ref. 216. Copyright r 2014, Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.


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investigated.228–230 Additionally, a series of manganese oxides (MnOx, Mn2O3, Mn3O4) was shown to have a certain degree of OER activity in alkaline and neutral solutions.231–233 The origin of their activities may arise from the presence of Mn III ions in a distorted lattice, structural disorder (e.g. oxygen point defects) and a high variety of Mn–O bond distances. Interestingly, the DFT calculation predicted that these materials can also act as ORR bi-functional electrocatalysts.233 Such unique behavior may be due to the phase changes under different potentials in ORR or OER region. Secondly, some mixed oxides like spinel (NiCo2O4, NiLa2O4)234–237 and perovskite (LaCoO3 and Ba0.5Sr0.5Co0.8Fe0.2O3d)99,236–238 showed also favorable OER activities as compared to pure metal oxides. The enhanced activity can be attributed to the changes in lower/higher oxide transition energies and the oxides’ work function after metal atom substitution.84 Although the catalogue of OER electrocatalysts is more complicated than those catalyzing ORR, based on DFT calculations Rossmeisl et al. found that there is universality in oxygen evolution electrocatalysis behavior on many types of oxide surfaces covering perovskite, rutile and anatase oxides (Fig. 14).87 The activity trend can be theoretically described by using a couple of simple but universal descriptors, i.e. the free energies of OOH* and OH* intermediates, as discussed in Section 2.3.2. In this fashion, a fundamental limitation, the maximum OER activity, can by predicted and identified. Importantly, the agreement between experimentally measured overpotentials and predicted ones for all investigated types of oxides is remarkably good (Fig. 14), which may pave the way for future molecular design of highly efficient candidates.87 Thirdly, a large number of molecular catalysts for OER half reaction and water splitting have been extensively studied. Most of them are Ru and Co containing complexes or macrocycles that have also been widely used in photocatalysis and artificial photosynthesis. The two obvious shortcomings of these materials are their weak stability under either strongly acidic or alkaline conditions (they are only generally stable under neutral conditions). As there is a huge number of detailed reviews devoted to these materials (mainly focused on synthetic chemistry and molecular design),59,236,237,239–243 a complete catalogue and review are not presented here.

Fig. 14 Theoretical overpotential vs. experimental overpotential for (a) rutile, anatase and (b) perovskite oxides in alkaline solutions. Reproduced with permission from ref. 87. Copyright r 2011, Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

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4.3

Non-metallic materials

Different from the case of ORR, for which metal-free catalysts have been widely investigated and shown to be competitive, the studies of non-metal materials for OER just begun. The currently available OER metal-free catalysts are analogous to those developed for ORR, namely single/double doped carbons with heteroatoms (graphene,244 CNT,245 nanographite246) and carbon-based hybrids (C3N4–CNT,247 graphene–CNT,248 C3N4– graphene249). Most of these materials can be obtained with high surface area to achieve apparently very high anodic current densities. However, the theoretical studies of OER on carbon surfaces regarding oxygen/hydroxide adsorption behavior and mechanism are very rare. Although various architectures, like non-metal 3D structures and film-like electrodes, are very promising OER catalysts, their TOF are still worse than that of traditional (non)precious metals and their (electro)chemical oxidation at higher potentials is also a big concern for their long time operation. 4.4

ORR–OER bifunctional electrocatalysts

The significance of non-metal electrocatalysts is in their favorable activity toward both OER and ORR processes.42,250,251 Some theoretical works predicted that N-graphene has the ability of facilitating ORR and OER simultaneously but at different active sites (zigzag carbon adjacent to nitrogen dopant favors ORR, while armchair carbon near nitrogen favors OER as shown in Fig. 15a). Besides, a wide variety of metal-containing materials like transition metal oxides, hydroxides, perovskites and macrocycles are also promising bifunctional catalysts in alkaline solutions.42,194,232,233,251–259 However, most of these catalysts are more likely ‘‘by-products’’ of ORR catalysts or have been firstly investigated as effective ORR catalysts. More importantly, considering that OER/ORR is a reverse reaction couple, they share the same free energy diagram; the only difference is the reaction direction. Therefore, for a given electrode surface, there might be a very small free energy difference for the system to overcome in one direction (for instance OER process), showing apparently fast reaction rate. However in the opposite direction (i.e. ORR process), the free energy difference might become very huge and hence thermodynamically difficult to be activated. This is the fundamental reason that why a practical catalyst is hardly to be, at the same time, a good OER catalyst while being a good ORR catalyst. For example, based on experimental evidence, the most active ORR catalyst Pt/C even shows much worse OER activity than most of the reported nonprecious metals while the ‘‘unbeatable’’ RuO2 used to catalyze OER shows negligible ORR activity (Fig. 15b).216,254 From the theoretical perspective, as shown in Fig. 15c the volcano plots for ORR (top one, which activity trend is limited by the blue and black lines) and OER (bottom one, which activity trend is limited by the green and red lines), the O* binding energies for the best ORR and OER catalysts are not the same, indicating the ORR catalyst does not possess the best OER activity, and vice versa.85 The theoretical best OER/ORR bi-functional catalyst should have the same O* binding energy and should


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electrode surface (named Volmer reaction). This reaction in alkaline media requires an additional previous step of water dissociation, which very likely, would introduce an additional energy barrier and may affect the whole reaction rate. For the second step, there are two possibilities: one is Heyrovsky reaction, in which the adsorbed hydrogen atom combines with an electron transferred from the electrode surface and a proton from the electrolyte to form one hydrogen molecule; the other one is Tafel reaction, in which two (adjacent) adsorbed hydrogen atoms combine to form one hydrogen molecule. The determination, which reaction(s) is the possible ratecontrolling step(s), can be simply discerned by Tafel slope value from polarization curves.261 5.1

Fig. 15 (a) Proposed active sites (red carbon atoms around nitrogen atoms) on armchair and zigzag edges of N-graphene for OER and ORR, respectively. Reproduced with permission from ref. 250. Copyright r 2014, Elsevier. (b) Experimental polarization curves for classic ORR (Pt/ C), OER (RuO2, IrO2), and bifunctional (MnxOy/NC) electrocatalysts in ORR/ OER full range potentials. Reproduced with permission from ref. 254. Copyright r 2014, Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim. (c) The activity volcano plots for ORR and OER; the theoretical activity is depicted as a function of the oxygen binding energy. Reproduced with permission from ref. 85. Copyright r 2007, Elsevier.

be located near the equilibrium potential (dotted line). Therefore, getting favorable or acceptable activities for both OER/ORR is a rational target for the molecular design of future bi-functional catalysts. For example, Schuhmann et al. identified the overvoltage between ORR and OER (EORR@1 mA cm2 EOER@10 mA cm2), which translates into the loss in efficiency, as a descriptor for evaluating the bi-functional activity of a catalyst.254

5 Atomic-level understanding of HER catalysts The HER’s total equation and detailed pathway are summarized in Table 3.260 The first step of HER, no matter how the consecutive reaction will proceed, is adsorption of H on the electrode surface by transferring a proton from the acid electrolyte that combines with an electron transferred through

Table 3

Overall reaction pathways for HER in acidic and alkaline solutions

Overall reaction (condition)

Reaction pathway

2H + 2e - H2 (Acidic solution)

H+ + e + * - H* (Volmer) H+ + e + H* - H2 (Heyrovsky) or 2H* - H2 (Tafel)

2H2O + 2e - H2 + 2OH (Alkaline solution)

H2O + e - H* + OH (Volmer) H2O + e + H* - H2 + OH (Heyrovsky) or 2H* - H2 (Tafel)

+


Precious metals (Pt and Pt alloys)

As can be seen from Fig. 5d, Pt family materials are located at the summit of HER activity volcano plot with the value of DGH* very close to zero and very high experimentally obtained j0. Like in the case of ORR, the HER activity on sc-Pt surfaces is also structure–sensitive with the activity trend of (111) o (100) o (110) planes in both acidic and alkaline solutions.11,262,263 This trend has the same order of different apparent activation energies discerned from Arrhenius plots.264 Moreover, the activation energy values in alkaline solutions are twice as those in acid solutions, making the HER activity (in terms of j0) significantly higher than the former, which has also been observed for Pd and Ir materials.265 The reason for such behavior are strong metal–OHad interactions or high water dissociation energy barriers in alkaline solutions.11 To reduce the usage of Pt and increase the specific activity of catalysts, alloying Pt with a secondary metal (generally 3d transition metal) to form 3d/Pt bimetallic surfaces is an effective method, similar to the strategy in ORR field. As shown in Fig. 16a, the cost of a bimetallic electrode depends on the amount Pt (thin film or even monolayer are preferred to achieve high active surface area and reduce the cost).266 Alloying thin layer Pt with another metal substrate can significantly reduce the cost of whole catalyst without compromising catalytic activity. Also, the secondary metal heteroatom can optimize d-band center and DGH* of host Pt to promote the whole bimetallic system’s performance. For example, the configuration with 3d metal on the top-most layer of Pt(111) surface, designated as 3d-Pt(111), shifts the d-band center closer to the Fermi level, while the configuration with 3d metal in the subsurface region, designated as Pt–3d-Pt(111), shifts the d-band center away from the Fermi level.266–269 Such strategy has been experimentally realized in either precious Pt or Pd monolayers by underpotential depositing methods on the substrates of secondary single crystalline metal surfaces (Fig. 16b).107,109 With the existence of either ligand or strain effect,112 the bimetal catalysts show much better performance than single metals. Recently, the choice of substrates has been extended to wider range of single- and poly-crystalline NPMC like conductive tungsten carbides (WC and W2C) or molybdenum carbide (Mo2C) etc.91,270,271 For UHV surface science experiments, the Pt overlayer can be deposited onto the surface of these carbide

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Fig. 16 (a) Relationship between cost of overall Pt and overlayer thickness for a planar catalyst. Reproduced with permission from ref. 266. Copyright r 2011, Royal Society of Chemistry. (b) Relationship of the hydrogen–desorption potentials vs. the shift of the d-band center for different monolayer Pd alloys. Reproduced with permission from ref. 109. Copyright r 2005, Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim. (c) Volcano relationship between HER activity ( j0) and hydrogen binding energy (HBE) for different metal-modified single crystals and polycrystalline tungsten carbide surfaces. Reproduced with permission from ref. 272. Copyright r 2013, Hydrogen Energy Publications.

substrates through a common physical vapor deposition (PVD) method with various architectures as sub-monolayer, monolayer, or layer-by-layer, which subsequently will induce different surface (electro)chemical properties.266,267 The whole morphology can be also controlled as 2-D thin film or 3-D high surface area core–shell structures for preferable exposure of the active sites.266,267 The DFT calculations predicted that a variety of metals (Cu, Rh, Pd, Ag, Pt, Au) can be deposited on WC(0001) surface as monolayer.272 With the engineered electronic structures, as shown in Fig. 16c, the WC foil supported precious metals possess comparable HER performance to that of pure clean metal surface (but with much lower metal loading);

in particular, WC(0001) supported non-precious Cu even match the performance of bulk Pt catalyst with good stability.272 5.2

Non-precious metals compounds

Besides as supporters for precious metals, nanostructured metal sulfides,273,274 carbides,275–277 nitrides,277–279 selenides,280,281 and phosphides282–285 themselves or supported on nanostructured conductive carbons have been synthesized and evaluated as competitive candidates to replace Pt (Fig. 17). Since these materials possess various surface properties and electronic structures, the universal HER evaluation principle e.g. on pure metal (alloy) counterparts such as the M–H bond strength or

Fig. 17 Experimental HER polarizations for various transition metal compounds. (a) Metal sulfides; reproduced with permission from ref. 274. Copyright r 2007, American Association for the Advancement of Science. (b) Metal carbides; reproduced with permission from ref. 275. Copyright r 2013, Royal Society of Chemistry. (c) Metal nitrides; reproduced with permission from ref. 278. Copyright r 2013, American Chemical Society. (d) Metal selenides; reproduced with permission from ref. 280. Copyright r 2014, American Chemical Society. (e) Metal phosphides; reproduced with permission from ref. 282. Copyright r 2013, American Chemical Society. Insets show the crystal structures of each typical electrocatalyst. Performances were measured in N2 or H2 saturated 0.5 M H2SO4. Note that the mass loading may be different in the case of different electrocatalysts.

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Fig. 18 (A) Aberration-corrected and monochromated HRTEM images and EELS mapping for C3N4@NG nanosheets. (B) The HER polarization curves and Tafel plots for four metal-free electrocatalysts and 20% Pt/C. (C) The calculated free-energy diagram for HER at the equilibrium potential for three metal-free catalysts and Pt reference. Reproduced with permission from ref. 92. Copyright 2014, Nature Publishing Group.

DGH* descriptors is still unavailable. Since 2005 the most extensively studied metal compounds for HER, both experimentally and theoretically, are metal sulfides (MoS2 and WS2) to confirm their electrocatalytically active sites.273,274,286 Inspired by the agreement of a series of calculations and experiments, researchers then artificially exposed/extended MoS2’s active edge sites by various physical or chemical strategies to promote their electrocatalytic activities.287–294 As regards other metal compounds, due to advances in nanotechnology, there is a huge interest in exploring different nanostructures with high ECSA as electrocatalysts. Most of them showed acceptable activity as Pt’s alternatives. However, contrary to MoS2, researchers are mainly focused on the architecture/ morphology control of these materials, and the lack of fundamental understanding of the nature of their activities limits the more advanced molecular design. For example, in theoretical aspects, although it is well known that the shift in the d-band center of a metal caused by the formation of metal–carbon/ nitrogen bonds correlates closely to the change in the hydrogen binding energy on a given compound surface,295 a systemic investigation of the HER trends for these systems is still under construction, mainly due to their various electronic structures. Only metal carbides have been studied in which the hybridization between metal d-orbitals and the carbon s- and p-orbitals brings a broadening in the d-band and affects the hydrogen adsorption.296

as confirmed by theoretical calculations), their corrosion resistance in both acidic and alkaline conditions make them promising as Pt’s alternatives. The availability of various carbon nanostructures with tunable composition may significantly enlarge the number of candidates for highly efficient HER. One featured example is the chemically coupled C3N4–Ngraphene hybrid (Fig. 18A), which showed a comparable activity with most popular MoS2 material in acid solutions, judged by both calculated DGH* and measured j0.92 Through coupling g-C3N4 with N-graphene sheets, a strong interaction between two sheets occurs with extra interlayered bond formation. From the perspective of HER free energy diagram, there is a synergistic effect between C3N4 (too strong adsorption) and N-graphene (too weak adsorption) to create a proper adsorption of hydrogen on hybrid’s surface close to that of Pt, which results in favorable HER activity apparently (Fig. 18B).92 Both experimental tests and theoretical analysis confirmed that such effect could largely boost the electrocatalytic activities of C3N4–Ngraphene hybrid toward HER (Fig. 18C). Very recently, the conductive support has been extended to graphene nanoribbon and the performance of the composite has been further enhanced.301 For many non-metallic systems (e.g. C3N4–N-graphene hybrid and N, P co-doped graphene), good linear trends between theoretical DGH* and measured j0 were clearly visible (not shown here), which also validates the predictive capability of the employed DFT model beyond metals in HER field.56,92

5.3

6 Conclusions and perspectives

Non-metallic materials

Currently, as metal-free catalysts, almost all types of carbon materials show certain activity toward HER including activated CNT,297,298 graphene doped with heteroatoms,56,299 and functionalized fullerenes.300 Although their performance is not as good as their metal counterparts (mainly due to lower activity


A major challenge in clean and sustainable energy conversion technology is the development of highly efficient, cost-effective, and robust electrocatalysts that can catalyze the elementary electrochemical reactions involved in many devices with a high

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rate over a sufficiently long period of time. The improvement of the catalysts’ performances depends initially on the fundamental understanding of the particularities of reactions for the electrodes and secondly, on capitalizing the insight gained on the design of catalysts with targeted functionalities. Identifying a catalyst design principle that links material’s surface chemical properties to the electrocatalytic activity can accelerate the search for highly active and efficient catalysts for desired applications. By performing a rational design of new generation electrode catalysts rather than the traditional trial-and-error process, here we present a performance-oriented design strategy for desirable electrocatalysts from the most fundamental level to the application level. The initial step contains two strategies: (i) the electronic structure engineering of existing catalysts to optimize their performance determining band position or (ii) discovering new materials that possess desirable adsorption of reaction intermediates represented by adsorption scaling relationships. The realization of these two strategies includes heteroatom doping, bi-metallic alloying, and interlayer compositing as illustrated by the aforementioned examples in Sections 3–5. The aims of these two strategies are to achieve the minimum free energy change for the reaction pathway on a given surface. In this way, the system can reach the top of the activity volcano plot due to the lowest DG of RDS, which from the experimental perspective is represented by the highest value of j0. To achieve high apparent output current of fundamentally designed electrocatalysts for practical applications, nanostructure engineering is a critical next step process, which generally contains the following strategies: (i) preferably enlarging the ECSA by fabricating nanoscale structures of the catalysts like mesostructures, nanoparticles, core–shell architectures, nanowires, nanosheets etc.; (ii) enhancing the electrical conductivity for facile electron/charge transfer process by introducing extra conductive substrates like carbon and metal into the composite; (iii) increasing reactant/ product mass transfer efficiency in the bulk of the electrode by casting meso- or macroporous objects. The merging of theoretical calculations and experimental characterization greatly accelerates the development of the aforementioned electrocatalysts’ molecular design and nanostructure engineering toward oxygen- and hydrogen-involving reactions. More noticeably, such success has been extended to much broader electrocatalysis and heterogeneous catalysis in industrial processes beyond aforementioned ORR, OER and HER like (electro)catalytic CO2 reduction to fuel (CCR),302,303 electrocatalytic methanol oxidation at the anode of a direct methanol fuel cell,304 preferential CO oxidation in hydrogen (PROX),305,306 methanation reaction,307,308 selective hydrogenation of acetylene,309 and industrial ammonia synthesis,310,311 etc. Although the DFT calculations are always based on some simplified models, they can give a high level of accuracy to favorably compare experimental results and do some feasible prediction. From the materials perspective, the DFT computation also showed powerful predicting capability for non-metallic carbon-based materials beyond traditional metal-containing ones. A combination of theoretical calculations and experimental data

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provides clear and solid evidence that the well-designed metal-free counterparts possess competitive properties as the next generation catalysts for highly efficient oxygen- and hydrogen-involving reactions, thus largely expanding the spectrum of electrocatalysts for more energy-related electrocatalytic reactions.

Acknowledgements We gratefully acknowledge the financial support from Australian Research Council (ARC) through the Discovery Project programs (DP140104062 and DP130104459).

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