Revealing Energetics of Surface Oxygen Redox from Kinetic

Subscriber access provided by ECU Libraries

Article

Revealing Energetics of Surface Oxygen Redox from Kinetic Fingerprint in Oxygen Electrocatalysis Hua Bing Tao, Junming Zhang, Jiazang Chen, Liping Zhang, Yinghua Xu, Jingguang G Chen, and Bin Liu J. Am. Chem. Soc., Just Accepted Manuscript • DOI: 10.1021/jacs.9b01834 • Publication Date (Web): 19 Aug 2019 Downloaded from pubs.acs.org on August 19, 2019

Just Accepted “Just Accepted” manuscripts have been peer-reviewed and accepted for publication. They are posted online prior to technical editing, formatting for publication and author proofing. The American Chemical Society provides “Just Accepted” as a service to the research community to expedite the dissemination of scientific material as soon as possible after acceptance. “Just Accepted” manuscripts appear in full in PDF format accompanied by an HTML abstract. “Just Accepted” manuscripts have been fully peer reviewed, but should not be considered the official version of record. They are citable by the Digital Object Identifier (DOI®). “Just Accepted” is an optional service offered to authors. Therefore, the “Just Accepted” Web site may not include all articles that will be published in the journal. After a manuscript is technically edited and formatted, it will be removed from the “Just Accepted” Web site and published as an ASAP article. Note that technical editing may introduce minor changes to the manuscript text and/or graphics which could affect content, and all legal disclaimers and ethical guidelines that apply to the journal pertain. ACS cannot be held responsible for errors or consequences arising from the use of information contained in these “Just Accepted” manuscripts.

is published by the American Chemical Society. 1155 Sixteenth Street N.W., Washington, DC 20036 Published by American Chemical Society. Copyright © American Chemical Society. However, no copyright claim is made to original U.S. Government works, or works produced by employees of any Commonwealth realm Crown government in the course of their duties.

Page 1 of 40 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Journal of the American Chemical Society

Revealing Energetics of Surface Oxygen Redox from Kinetic Fingerprint in Oxygen Electrocatalysis Hua Bing Tao,a Junming Zhang,a Jiazang Chen,c Liping Zhang,a Yinghua Xu,d Jingguang G. Chen,b,* and Bin Liua,* a

School of Chemical and Biomedical Engineering, Nanyang Technological University, 62

Nanyang Drive, Singapore 637459, Singapore b

Department of Chemical Engineering, Columbia University, New York, NY 10027, United

States c

State Key Laboratory of Coal Conversion, Institute of Coal Chemistry, Chinese Academy of

Sciences, Taiyuan 030001, China d

State Key Laboratory Breeding Base of Green Chemistry-Synthesis Technology, College of

Chemical Engineering, Zhejiang University of Technology, Hangzhou 310032, China *

To whom correspondence should be addressed. Email: [email protected] (J.G. Chen)

[email protected] (B. Liu)

1

ACS Paragon Plus Environment

Journal of the American Chemical Society 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Abstract The key step for rational catalyst design in heterogeneous electrocatalysis is to reveal the distinctive energy profile of redox reactions of a catalyst that give rise to specific activity. However, it is challenging to experimentally obtain the energetics of oxygen redox in oxygen electrocatalysis because of liquid reaction environment. Here we develop a kinetic model, which constructs a quantitative relation between energy profile of oxygen redox and electrochemical kinetic fingerprints. The detailed study here demonstrates that the kinetic fingerprints observed from experiments can be well described by different energetics of oxygen redox. Based on the model, a feasible methodology is demonstrated to derive binding energies of the oxygen intermediates from electrochemical data. The surface property of different catalysts derived from our model well rationalises the experimental trends and predicts potential directions for catalyst design. Keywords: oxygen electrocatalysis, oxygen redox, reaction intermediates, binding energy, kinetic fingerprint.

2


Page 2 of 40

Page 3 of 40 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


1. INTRODUCTION The transformation between water and dioxygen, two of the most abundant chemicals on earth, plays a central role in clean energy conversion and storage.1 However, owing to the sluggish kinetics, oxygen evolution reaction (OER) and its reverse reaction – oxygen reduction reaction (ORR) badly limit the overall efficiency of this transformation.2-4 It is well recognized that the sluggish kinetics and instability of catalysts in oxygen electrocatalysis originate from non-ideal energetics of oxygen redox in the catalytic cycle.5-8 Oxygen electrocatalysis involves multi-step oxygen redox, wherein the elementary reaction with the highest overpotential determines the overall turnover frequency.8 Despite of abovementioned importance, experimental observation of oxygen redox in oxygen electrocatalysis is challenging in liquid environment,9,10 especially on oxide surface.11-13 So far, the energetic and molecular level understanding of oxygen intermediates highly relies on density functional theory (DFT) calculations, which perform well on well-defined catalyst surfaces.14 However, the mechanistic understanding of practical catalysts under real working conditions (high positive potential, solvation effect, strong electric field) in oxygen electrocatalysis requires methods to extract energetics of intermediates from experimental data. In principle, the influence of catalyst surface reactivity and electrolyte ions could result in distinctive kinetic fingerprints, which can be used to deduce the energetics of oxygen redox.15 Previous experiment-oriented kinetic study demonstrated that electrochemical methods are sensitive enough to observe adsorbed species on electrode surface.16 In particular, detailed kinetic study shows that many electrosorbed species are spectators toward blocking active sites, instead of real kinetic-relevant intermediates.17,18 Therefore, quantitative kinetic modeling of experimental data is necessary to distinguish the real intermediates from the electrosorbed spectators. However, the implicit treatment of the energetics of elementary oxygen redox reactions in classic kinetic model makes it difficult to well describe activity trend with surface 3



reactivity of catalysts. In contrast, the concept of describing overpotential with thermodynamics of elementary steps in first principle kinetic model well rationales experimental trends,5,19 which can be introduced to kinetic model to construct a quantitative relationship between energetics of oxygen redox and kinetic fingerprints. Based on the advancement in experiment and theory, here we attempt to develop an approach to extract energetics of oxygen redox from electrochemical kinetics. The ButlerVolmer equation in our kinetic model is modified with the concept of equilibrium potential of specific elementary step, rather than that of overall reaction in classic kinetic model. Moreover, based on scaling relation of the adsorption energy of multi-intermediates,8 we construct the activity volcano of OER and ORR with a same activity descriptor to make a clear comparison between the two reactions. The kinetic simulation of the points on activity volcano plot can well reproduce distinctive kinetic characteristics observed in experiments. Therefore, it offers a method to extract intermediates bonding energy from kinetic modeling of specific catalysts, which is performed on various catalysts from both our laboratory and literature. Based on the understanding of intermediates binding energy, we predict some potential directions for catalyst design and provide an example to optimize ORR activity with manganese oxide.

2. METHODS 2.1 Model construction First, we provide the definition of the thermodynamic treatment of intermediates binding strength in electrochemical kinetic model, which is the basis to describe activity with surface reactivity of catalysts. It should be noted that the oxygen intermediates in this work is strictly kinetic-relevant intermediates, instead of spectators.16,18,20 Therefore, the energetics and adsorption isotherm of intermediates are closely related with kinetics. The overall reaction (reaction (1) and (2)) of oxygen electrocatalysis consists of a sequence of elementary oxygen 4


Page 4 of 40

Page 5 of 40 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


redox steps as shown in Figure 1 A&B. Here we only show the most widely accepted mechanism for illustration of the oxygen redox. 4 OH − ⇄ O2 + 2 H2 O + 4 𝑒 − (alkaline)

(1)

2 H2 O ⇄ O2 + 4 H + + 4 𝑒 − (acidic)

(2)

The standard equilibrium potential of the overall reaction is 𝐸 0 = 1.23 V vs RHE (reversible hydrogen electrode). All potentials used in this work are referred to RHE and we will omit the notation in following descriptions. The binding energy of intermediates in the model is defined in equilibrium potential (𝐸𝑖0 ) of each elementary electron-transfer (ET) step.5 𝐸𝑖0 = ∆𝐺𝑖0 /𝑒

(3)

where i refers to sequence number of elementary ET steps, e is the elementary charge. ∆𝐺𝑖0 (in eV) is the reaction free energy of elementary ET step, which is determined by the binding energy of intermediates.5 The sum of 𝐸𝑖0 for four ET pathway should satisfy: ∑41 𝐸𝑖0 = 4 ∗ 𝐸 0

(4)

In this way, the origin of irreversibility of oxygen electrocatalysis is rationalized by the deviation of 𝐸𝑖0 from 1.23 V (𝐸 0 ). With equation (3) and (4) one can obtain the free energies of oxygen intermediates from 𝐸𝑖0 . However, the binding energy of intermediates may vary with coverage.21-22 To construct an explicit connection between these parameters with experimentally observed kinetics, the definition of intermediates binding energy here is based on low coverage energetics. Under this treatment, 𝐸𝑖0 is defined as the onset potential of the elementary ET step. The highest 𝐸𝑖0 of an OER catalyst, or the lowest 𝐸𝑖0 of an ORR catalyst, is called potential determining step (PDS), which is used to predict the theoretical overpotential of a catalyst.7 The thermodynamic concept is different from the rate determining step (RDS), the elementary step with the slowest reaction rate in experimental kinetics. Therefore, PDS is 5



Page 6 of 40

a concept more relevant to binding energy of reaction intermediates, while RDS is directly related to experimental kinetics.30 Then, we give our treatment of the two concepts in kinetic description. In order to focus on the energetics of oxygen intermediates, an assumption is made that the rates of elementary steps of a catalyst are mainly determined by the energetics rather than different standard rate constants. Since it is very challenging to obtain energy of transition states for electron transfer (ET) steps,25-27 even with DFT calculations, the Brønsted–Evans–Polanyi (BEP) relationship19, 28,29

is typically used to predict experimental kinetics.19 In this circumstance, the RDS is treated

the same as PDS. While this assumption is not strictly rigorous,30 it may apply to the catalysts that share similarity in structure or reaction mechanism.31 Here we first present a simulation of electrochemical kinetics based on BEP relation to discuss the distinctive kinetic features. As shown in Figure 1C, the equilibrium potential of RDS is defined by: 0 𝐸RDS,OER = Max(𝐸𝑖0 )

(5)

0 𝐸RDS,ORR = Min(𝐸𝑖0 )

(6)

The correlation between energetics of different intermediates is described by the scaling relation 5, 7, 23 to reduce difficulty in solving the equations (detailed explanation is provided in section 2.1 of the Supporting Information). ∆𝐺OOH∗ − ∆𝐺OH∗ = 2.8 eV

(7)

∆𝐺O∗ = 1.65 ∗ ∆𝐺OH∗ + 0.58 eV

(8)

Using ∆𝐺O∗ as an activity descriptor, the predicted activity trends are presented in Figure 1D. The different location in the activity volcano plot is used to describe the catalyst with specific surface property. For example, Figure 1C depicts the energy profile under RHE for a catalyst whose surface reactivity is too strong for OER while too weak for ORR. In this case, all steps in OER are uphill in free energy with the largest step being the RDS, whereas all steps 6


Page 7 of 40 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


in ORR are downhill and the smallest step is the RDS. As a result, the RDS of OER is the fastest step in ORR and vice versa. Therefore, to improve the catalytic activity, one should work on its own RDS to tune the reaction energy toward the optimum value in OER or ORR. Figure 1D provides an overview of the activity trends in both OER and ORR. The scaling relation results in a mismatch in oxygen adsorption energy for the optimal catalyst in OER and ORR and a gap between the best activity with reversible potential - E0. Therefore, the correlation of adsorption energy of intermediates not only reduces the difficulty in identifying the origin of activity, but also exerts a constraint for optimizing the catalytic activity.2, 8 To derive rate constant of RDS, 𝐸𝑖0 is used in Butler-Volmer equation in our kinetic model. The rate constant is described by: 𝑘𝑖 =

𝑘𝑖0

∗𝑒

𝛼𝐹(𝑬−𝑬𝒊 𝟎 ) 𝑅𝑇

(9)

where 𝑘𝑖0 is the standard rate constant under equilibrium potential. 𝛼 is the charge transfer coefficient, typically taken around 0.5, meaning that the fraction of overpotential goes toward reducing activation barrier.33 𝐹 is Faradic constant of 96485 C mol-1. R is gas constant of 8.314 J mol-1 K-1 and T is absolute temperature in K. The rest steps remain in quasi-equilibrium.32 This gives the basic difference in describing rate constant between our kinetic model and the classic model in literature, which is based on 𝐸 0 .32-34 An overview of the simulated LSV curves for OER and ORR is shown in Figure 2. The simulated kinetics well reproduce basic activity trends reported earlier that the lowest overpotential emerges at an intermediate surface reactivity, while optimum ORR activity requires higher O* binding strength.7, 35 Besides, the simulation also shows that the kinetic feature differs significantly for different surface reactivity, which is the basis for deriving intermediates binding energy from kinetic modeling. Detailed kinetic simulation is summarized in section 3 of the Supporting Information.

7



2.2 Kinetic simulations We start our analysis from OER. The OER catalysts with very low surface reactivity tend to show high Tafel slope and high overpotential (Figure S4) as OH* formation is the RDS, which means that the major species are empty surface sites. With increase in surface reactivity, OH* formation becomes easier and the following step starts to become RDS, which results in lower overpotential. As shown in Figure S5, this type of catalysts could exhibit the typical Tafel slope of 40 mV/dec or dual Tafel slope (from 40 to 120 mV/dec), which is influenced by coverage of OH*. Further increase in surface reactivity can no longer improve OER activity as step (3) limits overall kinetics due to the scaling relationship of oxygen intermediates. Our simulation in Figure S6 shows that only this kind of mechanism could result in low Tafel slope of about 24 mV/dec, which is likely to describe the kinetics of NiFe catalysts.36 For this type of catalysts, both OH* and O* could account for the major species on surface. However, the Tafel slope can also be 120 mV/dec if O* becomes saturated on surface, which can hardly be easily judged by the kinetic analysis of OER. Besides the RDS of ET steps, the simulation of pure chemical step as RDS is also summarized in Figure S7. In our simulated ORR kinetics, we consider two mechanisms as shown in Scheme S1, where in both mechanism, O2 hydrogenation and OH* reduction steps determine the overall kinetic fingerprint.27, 37-38 The simulated electrochemical data presented in Figure S5 show that the catalysts with low surface reactivity exhibit high Tafel slope of 120 mV/dec, while the catalysts on the other side of the activity volcano plot manifest lower Tafel slope, ranging from 40 to 60 mV/dec depending on the adsorption isotherm of OH*. The simulated results can well fit the typical kinetic feature for well-studied catalysts, such as Pt group catalysts,4 Ag39 and Au40-41.

8


Page 8 of 40

Page 9 of 40 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


3. RESULTS AND DISCUSSION 3.1 Study of OER catalysts Following the above kinetic simulation based on surface reactivity, we examine the validity of our kinetic model via modeling real catalysts. To make sure that the electrochemical data can reflect the intrinsic activity of the catalysts, electrochemical tests and preparation of catalysts should be conducted following the basic standard as required for mechanistic study.42 To reduces the error in obtaining energetic information, the influence of catalysts’ surface areas on kinetics is corrected with electrochemical active surface area (section 3.1 of Supporting Information). Figure 3A & B show clearly that the experimental kinetics of the representative OER catalysts can be well fitted by simulated electrochemical data from our kinetic model. Both LSV curves and Tafel plots show quantitative consistency between experimental and simulated data, which suggests that our kinetic model well describes the kinetics of OER catalysts with different activity and reaction mechanism. In the process of determining intermediates binding energy, the above kinetic simulations are able to provide valuable guidance. Our fitting results provide the detailed energetic information of the elementary reactions as shown in Figure 3B, where the RDS for the three catalysts are clearly shown. Compared with optimal OER catalyst, the surface reactivity of Fe2O3 and Co3O4 is too low: OH* adsorption is the RDS for Fe2O3 and OH* dehydrogenation to O* is the RDS for Co3O4. DFT calculations usually predict OH* dehydrogenation step as RDS for Fe2O343 and TiO244. So far, we cannot exclude the possibility that the second ET step in Fe2O3 and/or TiO2 is PDS as kinetic modeling is based on a crude BEP relationship. Nonetheless, based on above kinetic analysis, two direct methods can be used to distinguish RDS from PDS for this scenario. If second step is PDS, OH* could amount to a significant coverage under working condition of OER. Therefore, using our newly developed chemical method to probe OH* is able to identify the real mechanism.45 9



The results summarized in Figure S13 support our kinetic modeling results that the first ET step in Fe2O3 is both the RDS and PDS of OER. Moreover, a fast scan rate cyclic voltammetry (CV) is able to detect OH*. If OH* dehydrogenation is PDS, the OH* formed in the forward scan (positive potential direction) should result in a reduction peak in the reverse scan. Of course, the DFT calculations are performed on perfect crystal facets, which may be different from the nanostructured materials used in our kinetic modeling. Therefore, our kinetic model provides a method to study surface chemistry for real catalysts. Similarly, for Co3O4, our kinetic modeling results are well supported by our previous experimental results - the activity of Co3O4 in OER increases with enhanced binding energy of oxygen intermediates.12 Our kinetic modeling of optimized NiFe catalyst, the most active non-precious catalyst for OER in alkaline media, visualizes the energetic origin of its high activity. While third step is RDS, the deviation of intermediates binding energy from reversible value is rather small, thus the energetic barrier for OOH* formation is only slightly higher than the first two steps. Besides, our model can also well simulate the electrochemical kinetics for typical oxides and (oxy)hydroxides (the position in activity volcano plot shown in Figure 3C). In addition to the catalysts synthesised from our own laboratory, we also studied the surface chemistry of well-known catalysts such as perovskite oxides (ABO3) reported from literature.46 Kinetic modeling of electrochemical data is summarized in Figure S9, while the positions of the catalysts in activity volcano plot are shown in Figure 3C. It is worth noting that in assignment of surface reactivity for catalytic origin, we take into consideration of both the OER and ORR kinetics of a catalyst. Moreover, activity trend in modification with composition also helps us identify the exact location of the catalyst in activity volcano plot. 3.2 Study of ORR catalysts Based on previous kinetic simulation, in the following we provide our mechanistic study of typical ORR catalysts. We first verified the validity of our kinetic model using the most well 10


Page 10 of 40

Page 11 of 40 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


studied catalysts. As shown in Figure 4A, the good fitting of well-characterized Pt group catalysts shows that the catalysts lie on the strong binding leg of activity volcano plot. From our modeling, the improved activity of Pt skin alloys as compared with Pt originates from the weakened binding of OHad that blocks active surface, consistent with down-shift of d-band centre as characterized from experiments.4, 47 At the same time, our kinetic modeling shows that alloy catalysts such as Pt3Ni are already at the apex of activity volcano plot, which means that further improvement in activity needs to break the energetic scaling relation of oxygen intermediates. Besides verification of well-studied catalysts, we have also examined our kinetic model in studying challenging problems in ORR. As summarized in Figure 4B, while many catalysts especially the Fe/N/C catalysts have already shown good ORR performance in alkaline media, their activities in acid are significantly lower.49, 53 This problem has been a long-term bottleneck to further improve efficiency or reduce cost of proton exchange membrane fuel cells (PEMFCs), whereas the underlying mechanism is still not clear. As a typical example, the poor ORR activity of Au is consistent with its noble chemical property,54 while the relatively “good” ORR activity in basic environment is difficult to understand.41 Several mechanisms have been proposed to interpret this kinetic behaviour, such as the negative charged intermediates and different activity of reactant. However, these proposed mechanisms can not give satisfying explanation of the dramatic difference over some catalysts. For example, why the activities in acid and base are similar on some catalysts such as Pt, but are dramatically different on some catalysts such Au and Fe/N/C catalysts? Besides, a practical question remains: How to develop excellent ORR catalysts for acid environment with non-precious materials? The dependence of this kinetic behaviour on materials stimulates us to dig out the possibility of specific interaction between catalyst surface with electrolyte. Interestingly, our kinetic modeling with these catalysts (Figure 4C) implies that their surface reactivities differ greatly in different reaction 11



media: the binding energy in alkaline media is significantly higher than that in acid, especially for Fe/N/C, whose surface reactivity in alkaline media is almost near the optimum value for ORR. The result is out of expectation, but it can be rationalized with the electronic interaction of different adsorbates with surface.55 There exist strong electronic interactions between adsorbates and catalysts. For example, the presence of CO can significantly influence the binding strength of OHad on gold.56 A general rule is proposed that the binding strength of a Lewis acid on a surface would be enhanced by adsorption of a Lewis base on the same surface, and vice versa, whereas the presence of a Lewis acid (base) would reduce the binding energy of another Lewis acid (base) on the same surface.55 This rule may apply to oxygen electrocatalysis as discussed here. Inspired by these studies, we provide a general model to predict the effects of electronic interaction. As illustrated in Scheme 1, the binding energy of an adsorbate maybe significantly influenced by the presence of another one. Promotion effect can be observed between a Lewis acid with a Lewis base, while inhibition effect can be expected between Lewis acids or Lewis bases. Based on above model, the electronic interaction between adsorbates is depicted in Figure 4C. In our case, OH- is a strong Lewis base, while O2, oxygen intermediates and H+ are Lewis acids. Therefore, as depicted in Figure 4C, the electron donating from OH- to Au would enhance its binding strength of oxygen intermediates, thereby reducing the activation energy in ORR. This interpretation is consistent with the studies of Au catalytic ethanol oxidation in alkaline media, which supports that O2 hydrogenation step is promoted by OH-.57-58 For the case of N-doped graphene and Fe/N/C, N atom plays a key role in determining activity due to its higher electron density than C atom in the matrix, thus being a typical Lewis base site. 49, 52 Therefore, H+ would interact strongly with basic N sites by withdrawing electrons from catalyst surface, thus weakens the binding energy of another Lewis acid-OOH*. To verify this interpretation, we may predict a strategy to enhance ORR kinetics on weakly bonding catalysts 12


Page 12 of 40

Page 13 of 40 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


in acid by introducing a suitable Lewis base. Like OH- in alkaline media, adsorption of the Lewis base could result in electron enrichment of the catalyst surface so as to enhance its reactivity in ORR. This approach is a similar but different strategy to modify electrochemical double layer other than introducing competing species to spectators.59-60 The difference is that this method introduces Lewis basic additive to enhance the interaction between catalyst surface and oxygen intermediates. Therefore, it shall also be applicable to acidic media for many catalysts whose activities are limited by weak adsorption of oxygen intermediates. 3.3 Design of a better ORR catalyst The above kinetic modeling results demonstrate the power of our kinetic model to uncover the energy profiles of oxygen electrocatalysis on different catalysts. Based on the energetic information, one can anticipate ways to reduce the overpotential for specific catalysts. After examining a series of manganese oxides, including -MnO2 and LaMnO3 based perovskites, we find that Mn is the key element that determines surface reactivity. Kinetic modeling reveals that these oxides show too strong binding of oxygen intermediates in OER(Figure 5A), thus they have the possibility to achieve good ORR activity. LaMnO3 based perovskite catalysts are too reactive in both OER and ORR, and the surface reactivity of α-MnO2 is too strong in OER but too weak in ORR. Therefore, based on a number of results from our work and literature, we predict that it should be possible to achieve good ORR activity with manganese oxides. In principle, higher ORR activity should be achieved with LaMnO3 by reducing surface reactivity, or with α-MnO2 by increasing surface reactivity. Although it has been reported that α-MnO2 is the most active crystal phase in ORR, its activity is still significantly lower than Pt/C.61 Our kinetic study predicts that the activity of MnO2 in ORR can be further improved by increasing its surface reactivity. Here we provide experimental results of the activity optimization on MnO2, whose activity in ORR is improved to a level comparable to Pt/C. 13



As shown in Figure 5B, our experimental results demonstrate that the ORR activity of αMnO2 can be improved by increasing the surface reactivity adopting the method reported by us before.12 Although the onset potential of α-MnO2 H-250 is still slightly lower than that of Pt/C, the half-wave potential is 0.86 V, the same as that of Pt/C. Moreover, the significantly lower Tafel slope (40.2 mV/dec), as compared to 68.5 mV/dec of Pt/C (Figure S15) indicates the good intrinsic activity of α-MnO2 H-250 for ORR. Additionally, rotating ring-disk electrode tests (Figure S15) show that only a small portion of reduction current is for the production of peroxide with ET number as high as 3.95 at 0.8 V, comparable to Pt/C. Such performance is superior to any reported activity of manganese oxides in ORR.62-65 Considering the large abundance of Mn, the optimized ORR catalysts with manganese oxides are very promising for scalable application in alkaline oxygen reduction devices. This study demonstrates the probability of making good ORR catalysts with manganese oxides by optimizing surface reactivity. However, manganese oxides usually have low electrical conductivity and surface area, which need to be increased for further improvement of ORR activity. 3.4 Discussion and outlook The quantitative relationship between kinetic fingerprint and the underneath elementary surface oxygen redox described in the model provides a method to understand the origin of the abundant kinetic features in electrochemical data of oxygen electrocatalysis. Compared with classic kinetic models and DFT calculations, the major advancement of our model is that we adopt the advantages of the two approaches to study the energetic origin of intrinsic activity over different catalysts. Therefore, one important application of our kinetic model is to extract intermediate bonding energies through modeling experimental kinetics. Although the main kinetic features considered in this work are observed from LSV curves and Tafel plots, other experimental data such as transient current/potential,16 redox peaks in CV curves45 and the participation of lattice oxygen in OER/ORR66,67 may also contain valuable kinetic features. 14


Page 14 of 40

Page 15 of 40 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


However, at present many kinetic features have not been well understood. More efforts are needed to connect the mechanism to other kinetic features in the future. The examples studied here are mainly to illustrate a general understanding of the relationship, thus special cases such as the participation of lattice oxygen redox

66,67

and the

hybrid catalysts consist of two phases68-70 have not been taken into consideration. All the kinetic analysis is based on the adsorbed intermediates. However, many new evidences show that there are some cases where lattice oxygen participates in oxygen evolution. The different configuration of oxygen intermediates may result in different energetics of oxygen redox. For example, the significantly higher OER activity for catalysts with the binding energy deviates from the optimal value according to the well-known adsorbed intermediates. This mechanism provides new possibilities to optimize the activity of oxide catalysts. But it should not be difficult to give new description of the special mechanism based on the prototype study in this work. We also note that the treatments of oxygen intermediates behaviours in this work are based on the mean-field approximation, which might fail to capture the kinetic fingerprints for the cases where heterogeneity of the catalyst surface is significant. This issue can be solved with more detailed catalyst characterization. In addition to above discussion on optimizing activity towards oxygen electrocatalysis,71-73 there are challenges and opportunities for the study of surface oxygen redox. First, the chemical nature of oxygen intermediates and oxygen redox are not clear. Although many in situ techniques have been employed to reveal the mechanism of oxygen electrocatalysis, very few of them are able to observe oxygen redox at catalyst surface. So far, the observation of electronic structure of oxygen still requires vacuum or low-pressure gas environment, which is difficult to be realized in liquid oxygen electrocatalysis. Therefore, the exact electronic structure and chemical reactivity of oxygen intermediates over different catalysts are still unknown. Whereas, new opportunities may be encountered with the electronic-level study of 15



surface oxygen redox. As an example, OER involves dehydrogenation and pure ET steps, which have similarity with dehydrogenation and selective oxidation in organic synthesis. Therefore, it might be possible to carry out dehydrogenation and selective oxidation on OER electrode. Although most of studies focus on improving the activity of oxygen electrocatalysis, the understanding of oxygen redox may also provide design principles for other reactions.

5. CONCLUSIONS This work constructs a quantitative relation between kinetic features in electrochemical data and the energetics of oxygen redox. The relation offers a methodology to extract energetics of oxygen redox via modeling of experimental kinetics. The surface coverage of oxygen intermediates as a function of potential can be determined from modeling of kinetic fingerprints, which forms the basis for developing new operando techniques to detect oxygen intermediates. Based on the energetics of oxygen redox, a general model is proposed to predict the experimental trends of different catalytic activities influenced by the chemisorption of species from reaction media. New strategies are proposed to develop active ORR catalysts in acid media for PEMFC. With such mechanistic information on hand, one is able to develop strategies in designing better oxygen electrocatalysts to meet the specific application requirements.

ASSOCIATED CONTENT Supporting Information Experimental details and kinetic analysis, Figure S1-S16. This material is available free of charge via the Internet at http://pubs.acs.org.

16


Page 16 of 40

Page 17 of 40 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


AUTHOR INFORMATION Corresponding Authors [email protected] (B. Liu) [email protected] (J.G. Chen) Notes The authors declare no competing financial interests.

ACKNOWLEDGMENTS This work was supported by the funds from the Singapore Ministry of Education Academic Research Fund (AcRF) Tier 1: RG111/15 and RG10/16, Tier 2: MOE2016-T2-2-004, the Foundation of State Key Laboratory of Coal Conversion (Grant No. J19-20-913-2), and the Nanyang Technological University internal fund. J.C. acknowledges National Natural Science Foundation of China (Nos.: 91545116, 21773285). Y.X. thanks the support from National Natural Science Foundation of China (21576238). J.G.C. acknowledges support by the US Department of Energy, Basic Energy Science, Catalysis Program (Grant No. DE-FG0213ER16381).

REFERENCES (1) Lewis, N. S.; Nocera, D. G., Powering the planet: Chemical challenges in solar energy utilization. Proc. Natl Acad. Sci. USA 2006, 103, 15729. (2) Seh, Z. W.; Kibsgaard, J.; Dickens, C. F.; Chorkendorff, I.; Nørskov, J. K.; Jaramillo, T. F., Combining theory and experiment in electrocatalysis: Insights into materials design. Science 2017, 355. 17



(3) Katsounaros, I.; Cherevko, S.; Zeradjanin, A. R.; Mayrhofer, K. J. J., Oxygen electrochemistry as a cornerstone for sustainable energy conversion. Angew. Chem. Int. Ed. 2014, 53, 102. (4) Stamenkovic, V. R.; Fowler, B.; Mun, B. S.; Wang, G.; Ross, P. N.; Lucas, C. A.; Marković, N. M., Improved oxygen reduction activity on Pt3Ni(111) via increased surface site availability. Science 2007, 315, 493. (5) Nørskov, J. K.; Rossmeisl, J.; Logadottir, A.; Lindqvist, L.; Kitchin, J. R.; Bligaard, T.; Jónsson, H., Origin of the overpotential for oxygen reduction at a fuel-cell cathode. J. Phys. Chem. B 2004, 108, 17886. (6) Rossmeisl, J.; Qu, Z. W.; Zhu, H.; Kroes, G. J.; Nørskov, J. K., Electrolysis of water on oxide surfaces. J. Electroanal. Chem. 2007, 607, 83. (7) Man, I. C.; Su, H.-Y.; Calle-Vallejo, F.; Hansen, H. A.; Martínez, J. I.; Inoglu, N. G.; Kitchin, J.; Jaramillo, T. F.; Nørskov, J. K.; Rossmeisl, J., Universality in oxygen evolution electrocatalysis on oxide surfaces. ChemCatChem 2011, 3, 1159. (8) Koper, M. T. M., Thermodynamic theory of multi-electron transfer reactions: Implications for electrocatalysis. J. Electroanal. Chem. 2011, 660, 254. (9) Zaera, F., Probing liquid/solid interfaces at the molecular level. Chem. Rev. 2012, 112, 2920. (10) Mueller, D. N.; Machala, M. L.; Bluhm, H.; Chueh, W. C., Redox activity of surface oxygen anions in oxygen-deficient perovskite oxides during electrochemical reactions. Nature Commun. 2015, 6, 6097. (11) Kuo, D.-Y.; Kawasaki, J. K.; Nelson, J. N.; Kloppenburg, J.; Hautier, G.; Shen, K. M.; Schlom, D. G.; Suntivich, J., Influence of surface adsorption on the oxygen evolution reaction on IrO2(110). J. Am. Chem. Soc. 2017, 139, 3473.

18


Page 18 of 40

Page 19 of 40 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


(12) Tao, H. B.; Fang, L.; Chen, J.; Yang, H. B.; Gao, J.; Miao, J.; Chen, S.; Liu, B., Identification of surface reactivity descriptor for transition metal oxides in oxygen evolution reaction. J. Am. Chem. Soc. 2016, 138, 9978. (13) Wang, H.-Y.; Hung, S.-F.; Hsu, Y.-Y.; Zhang, L.; Miao, J.; Chan, T.-S.; Xiong, Q.; Liu, B., In situ spectroscopic identification of μ-OO bridging on spinel Co3O4 water oxidation electrocatalyst. J. Phys. Chem. Lett. 2016, 7, 4847. (14) Norskov, J. K.; Bligaard, T.; Rossmeisl, J.; Christensen, C. H., Towards the computational design of solid catalysts. Nature Chem. 2009, 1, 37. (15) Subbaraman, R.; Tripkovic, D.; Chang, K.-C.; Strmcnik, D.; Paulikas, A. P.; Hirunsit, P.; Chan, M.; Greeley, J.; Stamenkovic, V.; Markovic, N. M., Trends in activity for the water electrolyser reactions on 3d M(Ni,Co,Fe,Mn) hydr(oxy)oxide catalysts. Nature Mater. 2012, 11, 550. (16) Conway, B. E.; Tilak, B. V., Behavior and characterization of kinetically involved chemisorbed intermediates in electrocatalysis of gas evolution reactions. Adv. Catal. 1992, 38, 1. (17) Schmidt, T. J.; Ross Jr, P. N.; Markovic, N. M., Temperature dependent surface electrochemistry on Pt single crystals in alkaline electrolytes: Part 2. The hydrogen evolution/oxidation reaction. J. Electroanal. Chem. 2002, 524–525, 252. (18) Conway, B. E.; Jerkiewicz, G., Nature of electrosorbed H and its relation to metal dependence of catalysis in cathodic H2 evolution. Solid State Ionics 2002, 150, 93. (19) Hansen, H. A.; Viswanathan, V.; Nørskov, J. K., Unifying kinetic and thermodynamic analysis of 2 e– and 4 e– reduction of oxygen on metal surfaces. J. Phys. Chem. C 2014, 118, 6706.

19



(20) Conway, B.; Jerkiewicz, G., Relation of energies and coverages of underpotential and overpotential deposited H at Pt and other metals to the ‘volcano curve’for cathodic H2 evolution kinetics. Electrochim. Acta 2000, 45, 4075. (21) Miller, S.; Dsilva, C.; Kitchin, J. R., Coverage dependent adsorption properties of atomic adsorbates on late transition metal surfaces. In Catalysis, Spivey J. J.; Gupta M. Eds, The Royal Society of Chemistry: 2012; Vol. 24, p 83. (22) Ertl, G. Reactions at Solid Surfaces, Wiley: 2010; p 5. (23) Abild-Pedersen, F.; Greeley, J.; Studt, F.; Rossmeisl, J.; Munter, T. R.; Moses, P. G.; Skúlason, E.; Bligaard, T.; Nørskov, J. K., Scaling properties of adsorption energies for hydrogen-containing molecules on transition-metal surfaces. Phys. Rev. Lett. 2007, 99, 016105. (24) Borden, W. T.; Hoffmann, R.; Stuyver, T.; Chen, B., Dioxygen: What makes this triplet diradical kinetically persistent? J. Am. Chem. Soc. 2017, 139, 9010. (25) Rostamikia, G.; Mendoza, A. J.; Hickner, M. A.; Janik, M. J., First-principles based microkinetic modeling of borohydride oxidation on a Au(111) electrode. J. Power Sources 2011, 196, 9228. (26) Filhol, J. S.; Neurock, M., Elucidation of the electrochemical activation of water over Pd by first principles. Angew. Chem. Int. Ed. Engl. 2006, 45, 402. (27) Janik, M. J.; Taylor, C. D.; Neurock, M., First-principles analysis of the initial electroreduction steps of oxygen over Pt(111). J. Electrochem. Soc. 2009, 156. (28) Bligaard, T.; Nørskov, J. K.; Dahl, S.; Matthiesen, J.; Christensen, C. H.; Sehested, J., The Brønsted–Evans–Polanyi relation and the volcano curve in heterogeneous catalysis. J. Catal. 2004, 224, 206. (29) Nørskov, J. K.; Bligaard, T.; Logadottir, A.; Bahn, S.; Hansen, L. B.; Bollinger, M.; Bengaard, H.; Hammer, B.; Sljivancanin, Z.; Mavrikakis, M., Universality in heterogeneous catalysis. J. Catal. 2002, 209, 275. 20


Page 20 of 40

Page 21 of 40 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


(30) Koper, M. T., Analysis of electrocatalytic reaction schemes: Distinction between ratedetermining and potential-determining steps. J. Solid State Electr. 2013, 17, 339. (31) Exner, K. S.; Over, H., Kinetics of electrocatalytic reactions from first-principles: A critical comparison with the ab initio thermodynamics approach. Acc. Chem. Res. 2017, 50, 1240. (32) Doyle, R. L.; Lyons, M. E. G., The oxygen evolution reaction: mechanistic concepts and catalyst design. In Photoelectrochemical Solar Fuel Production: From Basic Principles to Advanced Devices, Giménez, S.; Bisquert, J., Eds. Springer: 2016; p 54. (33) Surendranath, Y.; Nocera, D. G., Oxygen evolution reaction chemistry of oxide-based electrodes. In Prog. Inorg. Chem., Karlin K. D.; Lippard S. J. Eds. Wiley: 2011; Vol. 57, p 539. (34) Strmcnik, D.; Uchimura, M.; Wang, C.; Subbaraman, R.; Danilovic, N.; van der, V.; Paulikas, A. P.; Stamenkovic, V. R.; Markovic, N. M., Improving the hydrogen oxidation reaction rate by promotion of hydroxyl adsorption. Nature Chem. 2013, 5, 300. (35) Trasatti, S., Electrocatalysis in the anodic evolution of oxygen and chlorine. Electrochim. Acta 1984, 29, 1503. (36) Chen, R.; Sun, G.; Yang, C.; Zhang, L.; Miao, J.; Tao, H.; Yang, H.; Chen, J.; Chen, P.; Liu, B., Achieving stable and efficient water oxidation by incorporating NiFe layered double hydroxide nanoparticles into aligned carbon nanotubes. Nanoscale Horizons 2016, 1, 156. (37) Stamenkovic, V.; Markovic, N. Oxygen reduction on platinum bimetallic alloy catalysts. In Handbook of Fuel cells Wiley: 2009; Vol. 5, p18. (38) Holewinski, A.; Linic, S., Elementary mechanisms in electrocatalysis: Revisiting the ORR tafel slope. J. Electrochem. Soc. 2012, 159, H864. (39) Blizanac, B. B.; Ross, P. N.; Marković, N. M., Oxygen reduction on silver low-index single-crystal surfaces in alkaline solution: Rotating ring disk Ag(hkl) studies. J. Phys. Chem. B 2006, 110, 4735. 21



(40) Sarapuu, A.; Tammeveski, K.; Tenno, T. T.; Sammelselg, V.; Kontturi, K.; Schiffrin, D. J., Electrochemical reduction of oxygen on thin-film Au electrodes in acid solution. Electrochem. Commun. 2001, 3, 446. (41) Zurilla, R. W., The Kinetics of the oxygen reduction reaction on gold in alkaline solution. J. Electrochem. Soc. 1978, 125. (42) McCrory, C. C. L.; Jung, S.; Peters, J. C.; Jaramillo, T. F., Benchmarking heterogeneous electrocatalysts for the oxygen evolution reaction. J. Am. Chem. Soc. 2013, 135, 16977. (43) Liao, P.; Keith, J. A.; Carter, E. A., Water oxidation on pure and doped hematite (0001) surfaces: Prediction of Co and Ni as effective dopants for electrocatalysis. J. Am. Chem. Soc. 2012, 134, 13296. (44) García-Mota, M.; Vojvodic, A.; Metiu, H.; Man, I. C.; Su, H.-Y.; Rossmeisl, J.; Nørskov, J. K., Tailoring the activity for oxygen evolution electrocatalysis on rutile TiO2(110) by transition-metal substitution. ChemCatChem 2011, 3, 1607. (45) Tao, H. B.; Xu, Y.; Huang, X.; Chen, J.; Pei, L.; Zhang, J.; Chen, J.G.; Liu, B., A general method to probe oxygen evolution intermediates at operating conditions. Joule 2019, 3, 1. (46) Bockris, J. O. M.; Otagawa, T., Mechanism of oxygen evolution on perovskites. J. Phys. Chem. 2002, 87, 2960. (47) Stamenkovic, V. R.; Mun, B. S.; Arenz, M.; Mayrhofer, K. J. J.; Lucas, C. A.; Wang, G.; Ross, P. N.; Markovic, N. M., Trends in electrocatalysis on extended and nanoscale Ptbimetallic alloy surfaces. Nature Mater. 2007, 6, 241. (48) Greeley J.; Stephens, I. E. L.; Bondarenko, A. S.; Johansson, T. P.; Hansen, H. A.; Jaramillo, T. F.; Rossmeisl J.; Chorkendorff I.; Nørskov, J. K., Alloys of platinum and early transition metals as oxygen reduction electrocatalysts. Nature Chem. 2009, 1, 552.

22


Page 22 of 40

Page 23 of 40 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


(49) Rauf, M.; Zhao, Y.-D.; Wang, Y.-C.; Zheng, Y.-P.; Chen, C.; Yang, X.-D.; Zhou, Z.-Y.; Sun, S.-G., Insight into the different ORR catalytic activity of Fe/N/C between acidic and alkaline media: Protonation of pyridinic nitrogen. Electrochem. Commun. 2016, 73, 71. (50) Wu, G.; More, K. L.; Johnston, C. M.; Zelenay, P., High-performance electrocatalysts for oxygen reduction derived from polyaniline, iron, and cobalt. Science 2011, 332, 443. (51) Shui, J.; Wang, M.; Du, F.; Dai, L., N-doped carbon nanomaterials are durable catalysts for oxygen reduction reaction in acidic fuel cells. Sci. Adv. 2015, 1. (52) Yang, H. B.; Miao, J.; Hung, S.-F.; Chen, J.; Tao, H. B.; Wang, X.; Zhang, L.; Chen, R.; Gao, J.; Chen, H. M.; Dai, L.; Liu, B., Identification of catalytic sites for oxygen reduction and oxygen evolution in N-doped graphene materials: Development of highly efficient metal-free bifunctional electrocatalyst. Sci. Adv. 2016, 2. (53) Zhang, X.; Chen, C.; Dong, J.; Wang, R.-X.; Wang, Q.; Zhou, Z.-Y.; Sun, S.-G., Comparative study of the oxygen reduction reaction on pyrolyzed FePc in acidic and alkaline media. ChemElectroChem 2018, 5, 1. (54) Hammer, B.; Norskov, J., Why gold is the noblest of all the metals. Nature 1995, 376, 238. (55) Metiu, H.; Chrétien, S.; Hu, Z.; Li, B.; Sun, X., Chemistry of lewis acid–base pairs on oxide surfaces. J. Phys. Chem. C 2012, 116, 10439. (56) Angelucci, C. A.; Ambrosio, R. C.; Gewirth, A. A., Origins of less noble behavior by Au during CO adsorption. ACS Catal. 2018, 8, 2247. (57) Zope, B. N.; Hibbitts, D. D.; Neurock, M.; Davis, R. J., Reactivity of the gold/water interface during selective oxidation catalysis. Science 2010, 330, 74. (58) Gu, Q.; Sautet, P.; Michel, C., Unraveling the role of base and catalyst polarization in alcohol oxidation on Au and Pt in water. ACS Catal. 2018, 8, 11716.

23



Page 24 of 40

(59) Strmcnik, D.; Escudero-Escribano, M.; Kodama, K.; Stamenkovic, V. R.; Cuesta, A.; Markovic, N. M., Enhanced electrocatalysis of the oxygen reduction reaction based on patterning of platinum surfaces with cyanide. Nature Chem. 2010, 2, 880. (60) Ciapina, E. G.; Lopes, P. P.; Subbaraman, R.; Ticianelli, E. A.; Stamenkovic, V.; Strmcnik, D.; Markovic, N. M., Surface spectators and their role in relationships between activity and selectivity of the oxygen reduction reaction in acid environments. Electrochem. Commun. 2015, 60, 30. (61) Meng, Y.; Song, W.; Huang, H.; Ren, Z.; Chen, S.-Y.; Suib, S. L., Structure–property relationship

of

bifunctional

MnO2

Nanostructures:

Highly

efficient,

ultra-stable

electrochemical water oxidation and oxygen reduction reaction catalysts identified in alkaline media. J. Am. Chem. Soc. 2014, 136, 11452. (62) Ng, J. W. D.; Gorlin, Y.; Nordlund, D.; Jaramillo, T. F., Nanostructured manganese oxide supported onto particulate glassy carbon as an active and stable oxygen reduction catalyst in alkaline-based fuel cells. J. Electrochem. Soc. 2014, 161, D3105. (63) Lambert, T. N.; Vigil, J. A.; White, S. E.; Delker, C. J.; Davis, D. J.; Kelly, M.; Brumbach, M. T.; Rodriguez, M. A.; Swartzentruber, B. S., Understanding the effects of cationic dopants on α-MnO2 oxygen reduction reaction electrocatalysis. J. Phys. Chem. C 2017, 121, 2789. (64) Cheng, F.; Zhang, T.; Zhang, Y.; Du, J.; Han, X.; Chen, J., Enhancing electrocatalytic oxygen reduction on MnO2 with vacancies. Angew. Chem. Int. Ed. 2013, 52, 2474. (65) Liu, X.; Gong, H.; Wang, T.; Guo, H.; Song, L.; Xia, W.; Gao, B.; Jiang, Z.; Feng, L.; He, J., Cobalt-doped perovskite-type oxide LaMnO3 as bifunctional oxygen catalysts for hybrid lithium-oxygen batteries. Chem Asian J 2018, 13, 528. (66) Bockris, J. O. M.; Otagawa, T., Mechanism of oxygen evolution on perovskites. J. Phys. Chem. 1983, 87, 2960.

24


Page 25 of 40 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


(67) Fabbri, E.; Schmidt, T. J., Oxygen evolution reaction—The enigma in water electrolysis. ACS Catal. 2018, 8, 9765. (68) Liang, Y.; Li, Y.; Wang, H.; Zhou, J.; Wang, J.; Regier, T.; Dai, H., Co3O4 nanocrystals on graphene as a synergistic catalyst for oxygen reduction reaction. Nature Mater. 2011, 10, 780. (69) Wang, H.; Dai, H., Strongly coupled inorganic-nano-carbon hybrid materials for energy storage. Chem. Soc. Rev. 2013, 42, 3088. (70) Liang, Y.; Li, Y.; Wang, H.; Dai, H., Strongly coupled inorganic/nanocarbon hybrid materials for advanced electrocatalysis. J. Am. Chem. Soc. 2013, 135, 2013. (71) Shan, J.; Guo, C.; Zhu, Y.; Chen, S.; Song, L.; Jaroniec, M.; Zheng, Y.; Qiao, S.-Z., Charge-Redistribution-Enhanced Nanocrystalline Ru@IrOx Electrocatalysts for Oxygen Evolution in Acidic Media. Chem 2019, 5, 445. (72) Liu, J.; Zheng, Y.; Wang, Z.; Lu, Z.; Vasileff, A.; Qiao, S. Z., Free-standing singlecrystalline NiFe-hydroxide nanoflake arrays: a self-activated and robust electrocatalyst for oxygen evolution. Chem Commun (Camb) 2018, 54, 463. (73) Shan, J.; Ling, T.; Davey, K.; Zheng, Y.; Qiao, S. Z., Transition-Metal-Doped RuIr Bifunctional Nanocrystals for Overall Water Splitting in Acidic Environments. Adv. Mater. 2019, 31, e1900510.

25



A

B

-2

0

O2 + H2O + e-

OH-

M*

OH-

0

0 -1

M-OOH*

-

O H

e-

-1

0 -1

M-OOH*

OHOH-

OH-

M*

OH-

M-OH*

e-

-2

O2 + H2O + e-

e-

O

-1

O

M-OH*

OH-

e-

0

0

M-O*

M-O*

OH-

H2O + e-

C

D ERDS0 (V) vs RHE

H2O + e-

2.0 O*

Energy

ORR RDS

OER RDS

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 26 of 40

→O

OH *

1.5

*→

O*

- → OH

OH

*

OH

OER

E0

ORR

1.0 *→

0.5

O

OH

2

OH

1.5

2.0

2.5

→

OO H*

3.0

3.5

DG0O* (eV)

Figure 1. The catalytic cycle and energetics of oxygen redox intermediates in oxygen electrocatalysis. (A), (B) Elementary reactions (alkaline) involved in the catalytic cycle of OER and ORR, respectively, where M* refers to the adsorption site on catalyst surface. OOH* and OH* may present on surface as deprotonated form as O2- and O-, respectively (see the discussion in section 2.4 of revised Supporting Information). The formal oxidation state of oxygen atom is explicitly shown to give a general illustration of oxygen redox. However, it should be noted that the charge may not be so ideally localized. For example, surface bonded OH* is not identical to •OH radical. Lewis structure of reactants are shown in each figure. The kinetics of the reactions should be closely related to the electronic structure of reactants. (C) The potential energy diagram of a typical catalyst under applied potential E = 0 V vs RHE. The surface reactivity of the illustrated catalyst as shown here is too high for OER but too low for 26


Page 27 of 40 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


ORR. (D) Activity volcano plot for OER and ORR. The RDS that form the volcano plot are shown. The chemical property of H2O and O2 is determined by the typical electronic structure of each molecule as shown in inset figures. H2O has two lone pairs of electrons centred on oxygen atom, thus behaves as an electron donor in OER; O2 is electron acceptor in ORR but the triplet state of O2 is a stable diradical.24

27



A

B

Figure 2. Characteristic LSV curves simulated as a function of surface reactivity. The surface reactivity is described with the adsorption energy of O*. (A) OER, and (B) ORR.

28


Page 28 of 40

Page 29 of 40

A 20 15

1.2

1.4

1.6

1.8

2.0

5 Fe2O3

Fe2O3 Co3O4 NiFe

5 0

Coverage

0

OH*

Reaction coordinate 2.0 TiO2 Fe2O3 SrVO3

1.9

ERDS0 (V) vs RHE

0.0

Fe2O3 Co3O4 NiFe

-4

LaMnO3

1.8 1.7

1.2

1.4

1.6

1.8

2.0

MnOOH

La0.7Sr0.3FeO3

FeOOH La0.5Sr0.5FeO3 NiOOH

1.6

-MnO2

1.5

1.3

LaVO3

La0.6Sr0.4MnO3 La0.2Ca0.8MnO3

CoOOH

1.5

2.0

2.5

LaCoO3 Co3O4

La0.6Sr0.4CoO3

CoFe

IrO2 NiFe

1.4

-5 1.0

E = 0 V vs RHE

OH

O* (NiFe)

C

-3

O*

2

-

OH* (NiFe)

-2

3

1

OH* (Fe2O3) OH* (Co3O4)

0.5

OOH*

NiFe

10

1.0

O2

Co3O4

4

DG (eV)

J (mA cm-2)

B

E (V) vs RHE 1.0

Log(J/A cm-2)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


LaNiO3 RuO2

3.0

3.5

4.0

DG0O* (eV)

E (V) vs RHE

Figure 3. Study of OER catalysts. (A) Kinetic modeling of Fe2O3, Co3O4 and NiFe catalysts. Experimental data is shown with scatters while simulated data with solid lines. (B) Potential energy diagram derived from kinetic fitting. (C) The position of the catalysts in the activity volcano plot. Transition metal oxides, oxyhydroxides and NiFe, CoFe catalysts are prepared in our laboratory while perovskites are adapted from literature (Figure S9).41

29



A

B

E (V) vs RHE 0.4

0.6

0.8

C

1.0 1.1

Pt3Ni(111)

Pt(111)

-4

ERDS0 (V) vs RHE

J (mA cm-2)

-2

E1/2 (V) vs RHE

Pt(111)

Acid Base

Pt3Ni(111) Pt3Y

Acid Base

0.9

0.8

0.7

0.2

Pt3Sc

1.0

Fe/N/C

Pt(111) Fe/N/C

N-G

PANI-Fe-C N-GRW

0.9 0.7

Au

0.6

0.8

ERDS0 (V) vs RHE

0

N-G

-MnO2

0.5

Ag(110)

0.4 0.3

Au

0.2 0.1

-6 0.1

0.7

Au/C

Pt3Ni(111) Pt(111)

1.0

0

N-C

Fe/N/C

Au

0.4 0.2

Acid

-1

-2

3.3

3.6

3.9

DG0O* (eV)

2.4

2.7

3.0

DG0O* (eV) OH-

OOH*

OOH*

Electron H+ withdrawing

-3

Base

O2

0.0

3.0

2.1

Au

Energy

J (mA cm-2)

0.6

2.7

1.8

Electron donating

0.8

 OH *

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 30 of 40

OOH*

-4 0.4

0.6

0.8

E (V) vs RHE

1.0

0.0

0.2

0.4

0.6

0.8

Fe/N/C

E (V) vs RHE

Figure 4. Kinetic modeling of ORR catalysts and mechanistic analysis. (A) Kinetic modeling of Pt group catalysts in ORR. Experimental data are shown in scatters (adapted from ref.4), while simulated curves in solid lines. The simulated coverage of OHad is in qualitative consistency with experimental data, which is normalized to saturation coverage. (B) Exploration of origin of activity difference for typical catalysts (example shows kinetic fitting results of Au) in acid and base. Kinetic modeling results show that the binding energy in acid is dramatically lower than in alkaline media (shown in inset). (C) Activity volcano plot and proposed mechanism for different surface reactivity in acidic and alkaline media. Data adapted from literature for modeling: Pt3Sc and Pt3Y,48 Fe/N/C,49 PaNI-Fe-C,50 N-G,51 N-GRW,52 Ag(110).39

30


Page 31 of 40 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Scheme 1. Schematic illustration of electronic interaction between adsorbates. Lewis acid and base are denoted as “A” and “B”, respectively. Lewis acid drives electron away from substrate, while Lewis base donates electron towards substrate.

31



A

2.0

TiO2 Fe2O3 SrVO3 LaVO3 FeOOH

LaMnO3 La0.6Sr0.4MnO3 0.2 C MnOOH a 0.8 M nO 3 -MnO2 NiOOH

ERDS0 (V) vs RHE

La

1.5

La0.7Sr0.3FeO3 LaCoO3 CoOOH La Sr FeO3 Co3O4 0.5 0.5 CoFe La0.6Sr0.4CoO3 IrO2 LaNiO3 NiFe RuO2

Pt3Ni(111) Pt(111)

1.0

Fe/N/C N-G Au Ag(110) -MnO 2

N-G(acid)

0.5

1.5

2.0

2.5

3.0

3.5

4.0

DG O* (eV) 0

B

1 MnO2 0

J (mA cm-2)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 32 of 40

MnO2 H-230 MnO2 H-250

-1

Pt/C

-2

Increase surface reactivity

-3

0.2

0.4

0.6

0.8

1.0

E (V) vs RHE

Figure 5. Predictions towards designing optimum ORR catalysts with manganese oxides. Rationally optimizing ORR activity of α-MnO2. (A) Predictions for designing optimum ORR catalysts with manganese oxides. (B) Activity variation by increasing surface reactivity of αMnO2. The samples are named with treatment environment and temperature. Specifically, A and H represent the samples annealed in air and 5% H2/Ar, respectively, and numbers are the treatment temperature.

32


Page 33 of 40 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Table of contents

33



B

-2

0

O2 + H2O + e-

OH-

M*

OH-

0

M-OOH*

-

O H

-1

0 -1

M-OOH*

OHOH-

e-

M-OH*

e-

OH-

M*

OH-

e-

0 -1

-2

O2 + H2O + e-

O

-1

O

M-OH*

OH-

e-

0

0

M-O*

C

M-O*

OH-

H2O + e-

D

H2O + e-

2.0

Energy

ORR RDS

O*

ERDS0 (V) vs RHE

A

OER RDS

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 34 of 40

→O

1.5

OH *

*→

O*

- → OH

* OH

OH

OER

E0

ORR

1.0 *→

0.5

O

OH

2

OH

1.5

2.0

2.5

DG0O* (eV)


→

OO H*

3.0

3.5

Page 35 of 40 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


A

B



A 20 15

1.2

1.4

1.6

1.8

2.0

5 Fe2O3

Fe2O3 Co3O4 NiFe

5 0

Coverage

OH*

Reaction coordinate 2.0 TiO2 Fe2O3 SrVO3

1.9

ERDS0 (V) vs RHE

0.0

Fe2O3 Co3O4 NiFe

-4

LaMnO3

1.8 1.7

1.2

1.4

1.6

1.8

2.0

La0.2Ca0.8MnO3

MnOOH

La0.7Sr0.3FeO3

FeOOH La0.5Sr0.5FeO3 NiOOH

1.6

a-MnO2

1.5

1.3

LaVO3

La0.6Sr0.4MnO3

IrO2 NiFe

1.4

-5 1.0

E = 0 V vs RHE

OH-

O* (NiFe)

C

-3

O*

2

0

OH* (NiFe)

-2

3

1

OH* (Fe2O3) OH* (Co3O4)

0.5

OOH*

NiFe

10

1.0

O2

Co3O4

4

DG (eV)

J (mA cm-2)

B

E (V) vs RHE 1.0

Log(J/A cm-2)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 36 of 40

1.5

2.0

2.5

CoOOH

La0.6Sr0.4CoO3

CoFe

LaNiO3 RuO2

3.0

DG0O* (eV)

E (V) vs RHE


LaCoO3 Co3O4

3.5

4.0

Page 37 of 40

A

B

E (V) vs RHE 0.4

0.6

0.8

C

1.0 1.1

Pt3Ni(111)

Pt(111)

-4

ERDS0 (V) vs RHE

J (mA cm-2)

-2

E1/2 (V) vs RHE

Pt(111)

Acid Base

Pt3Ni(111) Pt3Y

Acid Base

0.9

0.8

0.7

0.2

Pt3Sc

1.0

Fe/N/C

Pt(111) Fe/N/C

N-G

PANI-Fe-C N-GRW

0.9 0.7

Au

0.6

0.8

ERDS0 (V) vs RHE

0

N-G

a-MnO2

0.5

Ag(110)

0.4 0.3

Au

0.2 0.1

-6 0.1

0.7

Au/C

Pt3Ni(111) Pt(111)

1.0

0

N-C

Fe/N/C

Au

0.4 0.2

Acid

-1

-2

3.3

3.6

3.9

DG0O* (eV)

2.4

2.7

3.0

DG0O* (eV) OH-

OOH*

OOH*

Electron H+ withdrawing

-3

Base

O2

0.0

3.0

2.1

Au

Energy

J (mA cm-2)

0.6

2.7

1.8

Electron donating

0.8

q OH *

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


OOH*

-4 0.4

0.6

0.8

E (V) vs RHE

1.0

0.0

0.2

0.4

0.6

0.8

E (V) vs RHE


Fe/N/C



Page 38 of 40

Page 39 of 40

A

2.0

TiO2 Fe2O3 SrVO3 LaVO3 FeOOH

LaMnO3 La0.6Sr0.4MnO3 0.2 C MnOOH a 0.8 M nO 3 a-MnO2 NiOOH

ERDS0 (V) vs RHE

La

1.5

La0.7Sr0.3FeO3 LaCoO3 CoOOH La Sr FeO3 Co3O4 0.5 0.5 CoFe La0.6Sr0.4CoO3 IrO2 LaNiO3 NiFe RuO2

Pt3Ni(111) Pt(111)

1.0

Fe/N/C N-G Au Ag(110) a-MnO 2

N-G(acid)

0.5

1.5

2.0

2.5

3.0

3.5

4.0

DG O* (eV) 0

B

1 MnO2 0

J (mA cm-2)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


MnO2 H-230 MnO2 H-250

-1

Pt/C

-2

Increase surface reactivity

-3

0.2

0.4

0.6

0.8

E (V) vs RHE


1.0


Table of contents

1


Page 40 of 40

Revealing Energetics of Surface Oxygen Redox from Kinetic

Recommend Documents