Two-dimensional iron–tetracyanoquinodimethane (Fe–TCNQ) monolayer: an efficient electrocatalyst for the oxygen reduction reaction

Nan Wang a, Liyan Fenga, Yongchen Shanga, Jingxiang Zhao*a, Qinghai Caia and Peng Jin*b
aKey Laboratory of Photonic and Electronic Bandgap Materials, Ministry of Education, College of Chemistry and Chemical Engineering, Harbin Normal University, Harbin, 150025, China. E-mail: xjz_hmily@163.com
bSchool of Materials Science and Engineering, Hebei University of Technology, Tianjin, 300130, P. R. China. E-mail: china.peng.jin@gmail.com

Received 2nd June 2016 , Accepted 28th July 2016

First published on 28th July 2016


Abstract

Searching for efficient, cheap, and stable non-Pt electrocatalysts for the oxygen reduction reaction (ORR) has been a major challenge for the development of fuel cells. Herein, we systematically investigated the potential of the experimentally synthesized two-dimensional (2D) metal–tetracyanoquinodimethane (M–TCNQ, where M denotes Mn, Fe, and Co) monolayers as novel ORR catalysts by means of density functional theory (DFT) computations. Our results revealed that O2 molecules can be chemisorbed and efficiently activated on the M–TCNQ monolayers, and the subsequent oxygen reduction can readily proceed via a 4e pathway. Among the monolayers, the Fe–TCNQ monolayer exhibits the highest catalytic activity with onset potentials of 0.63 and −0.20 V in acidic and alkaline media, respectively. Remarkably, its electrocatalytic performance could be further enhanced by the attachment of axial halogen ligands. Therefore, the Fe–TCNQ monolayer might serve as a promising alternative to Pt-based catalysts for the ORR in fuel cells.


1. Introduction

Fuel cells have been hotly pursued in the past few decades as novel electrical energy conversion systems.1–3 However, their large-scale practical application is greatly limited by the sluggish kinetics of the oxygen reduction reaction (ORR) at the cathode. Although platinum (Pt) is the most effective catalyst for ORR thus far,4–12 the shortcomings such as high cost, limited supply, and poor durability severely hinder its wide commercialization.13 Therefore, the search for inexpensive, efficient and stable non-Pt ORR electrocatalysts is of great importance for fuel cell technology. Some promising alternative catalysts include transition metal macrocyclic compound-based catalysts, metal-free doped carbon materials, and transition metal oxides.14–37

One class of candidate materials to replace Pt is metal–organic frameworks (MOFs), which consist of metal ions or clusters coordinated to organic molecules to form one-, two-, or three-dimensional porous structures.38,39 MOFs feature high surface area, controllable porosity and diversity in metal and functional groups.40–42 These advantages render them very attractive materials for gas storage, gas purification, gas separation, and heterogeneous catalysis.43–52 Very recently, MOFs have begun to be used for electrocatalytic applications.53–57 For examples, Lin et al. reported that cobalt porphyrins-based MOFs exhibit outstanding catalytic activity for the CO2 reduction in water.55 Miner et al. demonstrated that Ni3(HITP)2 (HITP = 2,3,6,7,10,11-hexaiminotriphenylene) is a very promising electrocatalyst for ORR in alkaline solution.57

Despite these pioneering investigations on the MOF-based electrocatalysts, the theoretical studies on their potential as ORR catalysts are scarce.58,59 We note that, as new 2D MOFs, the experimentally available metal–tetracyanoquinodimethane (M–TCNQ) monolayers have manifested unique electronic, paramagnetic, and photoactive properties.60–62 To the best of our knowledge, however, their catalytic performance towards ORR has never been reported before, although the related studies may provide valuable insights into the development of novel non-Pt ORR catalysts.

In this work, the adsorption and reduction pathways of O2 molecules on the Mn–, Fe–, and Co–TCNQ monolayers in both acidic and alkaline environments were systematically studied by means of spin-polarized density functional theory (DFT) computations. Our calculations demonstrated that the Fe–TCNQ monolayer exhibits excellent ORR catalytic activity, and is thus a highly potential candidate for the next-generation low-cost ORR catalysts.

2. Computational methods

All the spin-polarized DFT computations were carried out by employing the PBE functional63 and the double numerical plus polarization (DNP) basis set, as implemented in the DMol3 code.64,65 The DNP basis set has an accuracy comparable to that of Pople's 6-31 G** basis set.66,67 The DFT semicore pseudopotential (DSPP) method,68 which replaces core electrons by a single effective potential to introduce some degree of relativistic corrections to the core, was used for the transition metals. To accurately describe the long-range electrostatic interactions between the ORR species and catalysts, the PBE-D2 method including Grimme's dispersion correction was adopted.69 The self-consistent field (SCF) calculations were performed with a convergence criterion of 10−6 a.u. on the total energy and electronic computations. The conductor-like screening model (COSMO)70 was used to simulate the water solvent environment (dielectric constant: 78.54).

We set the x and y directions parallel and the z direction perpendicular to the planes of M–TCNQ monolayers, and adopted a supercell length of 10 Å in the z direction. The Brillouin zone was sampled with a 5 × 5 × 1 mesh in the geometry optimizations, whereas a 12 × 12 × 1 grid was used for the electronic structure computations. The charge transfer was calculated according to the Hirshfeld method.71

The adsorption energy (Ead) of an ORR species on a M–TCNQ monolayer was defined as Ead = Especies/M–TCNQEspeciesEM–TCNQ, where Especies/M–TCNQ, Especies, EM–TCNQ are the total energies of the adsorbed system, free ORR species, and bare M–TCNQ monolayer, respectively. With this definition, a negative value indicates an exothermic adsorption.

We evaluated the change in Gibbs free energy (ΔG) for all the ORR steps based on a computational hydrogen electrode (CHE) model suggested by Nøskov et al.:72–74

ΔG = ΔE + ΔEZPETΔS + ΔGpH + ΔGU

In the equation, ΔE is the reaction energy directly obtained from the DFT calculations. ΔEZPE and ΔS are the zero point energy change and entropy change upon adsorption. The system temperature T is 298.15 K. ΔGpH = 2.303kBT pH is the correction of the H+ free energy by concentration (kB is the Boltzmann constant, and pH = 0 and 14 in acidic and alkaline conditions, respectively). ΔGU = −neU, where n is the number of electrons transferred and U is the electrode potential. The entropies and vibrational frequencies of the gas-phase molecules are taken from the NIST database. The vibrational frequencies of the adsorbed ORR species were calculated explicitly to obtain ZPE contribution in the free energy expression, while the M–TCNQ monolayers are fixed by assuming that their vibrations are negligible.

3. Results and discussion

3.1. Structures and properties of the M–TCNQ monolayers

The Fe–TCNQ monolayer was selected as a representative of the M–TCNQ monolayers. Fig. 1 depicts its optimized structure in a 2 × 2 supercell, in which all the atoms are in a plane. The unit cell is rectangular (lattice parameters: 7.03 and 11.35 Å) and contains twelve C atoms, four H atoms, four N atoms, and one Fe atom. In the Fe–TCNQ monolayer, each TCNQ acts as a ligand and binds to the central Fe atom through N atoms, leading to a Fe–N4 moiety in the unit cell (Fe–N bond lengths: 1.91 Å).
image file: c6ra14339c-f1.tif
Fig. 1 (a) Optimized structure (in a 2 × 2 supercell) and (b) density of states of the Fe–TCNQ monolayer. The red dotted lines in (a) indicate a unit cell. The purple, gray, blue, and green balls represent Fe, C, N, and H atoms, respectively.

The binding energy of Fe with TCNQ monolayer was computed as high as −7.91 eV, which is much larger than the cohesive energy of bulk Fe, indicating the high stability of the Fe–TCNQ monolayer. The Fe–TCNQ monolayer exhibits a spin-polarized ground state with a magnetic moment of 1.70 μB, which is mainly on the Fe atom (1.51 μB) with negligible contribution from the adjacent N atoms (0.03 μB, Fig. S1 in ESI). According to the Hirshfeld population analysis, the Fe atom carries a positive charge of +0.21e, much larger than those of other atoms. Since the highly positive atomic charge density or high spin density of the catalyst plays a significant role in facilitating the ORR process,75 the Fe atom would be an ideal reactive site to catalyze the ORR. The optimized Mn– and Co–TCNQ nanosheets possess similar planar structures, in which the Mn and Co atoms coordinate with the TCNQ ligands and exhibit large binding energies of −7.13 and −7.89 eV, respectively. In addition, the magnetic moments also mainly localize on the metal atoms (2.91 and 0.78 μB for Mn and Co, respectively).

To get a deeper understanding on the electronic structure of the Fe–TCNQ monolayer, we computed its density of states (DOS). As shown in Fig. 1b, there are strong hybridizations between the N 2p orbitals and Fe 3d orbitals in both spin-up and spin-down channels. In particular, there are some high energy levels near the Fermi levels, indicating a high activity of the Fe–TCNQ monolayer toward the adsorbates.

3.2. O2 adsorption on the M–TCNQ monolayers

To serve as the ORR catalyst, a 2D material should first favor the O2 adsorption on its surface. To obtain the most stable adsorption configuration, different adsorption sites in each M–TCNQ monolayer were considered with the O2 molecule assuming an end-on or side-on orientation.

After the geometry optimizations, the most favorable O2 adsorption site in each M–TCNQ monolayer is found to be the central metal atom, which results are consistent with the aforementioned large positive charges and high spin densities of the metals. O2 energetically prefers the end-on configuration with a tilted O–O bond, and forms a chemical bond with the metal atom (bond lengths: 1.79, 1.82, and 1.95 Å for the Mn–, Fe–, and, Co–O bonds, respectively, Fig. 2). As a result, each metal atom was pulled out from the basal plane by about 0.30 Å. The O–O bond is elongated from 1.21 to ∼1.29 Å due to the charge transfer of ∼0.20e from the M–TCNQ monolayers to the half-filled O2–2π* orbitals. Clearly, the O2 molecule has been effectively activated.


image file: c6ra14339c-f2.tif
Fig. 2 Optimized structures of the O2 adsorbed-(a) Mn–, (b) Fe–, and (c) Co–TCNQ monolayers. The unit of bond length is Å.

The O2 adsorption energies on the Mn–, Fe–, and Co–TCNQ monolayers are −0.94, −0.94, and −0.64 eV, respectively, suggesting that the oxygen molecule is strongly chemisorbed. The corresponding ΔG values are −0.25, −0.24, and 0.04 eV, respectively. This elementary reaction step can be written as: O2(g) → image file: c6ra14339c-t1.tif, where the asterisk denotes an adsorption site. Notably, the adsorbed O2 molecule is unlikely to dissociate into two separated O atoms at room temperature. For example, the energy barrier for the reaction of image file: c6ra14339c-t2.tif → 2O* on the Fe–TCNQ monolayer is calculated as high as 2.99 eV.

3.3. ORR pathways in an acidic medium

After the O2 activation, we further studied the ORR steps on the surfaces of the three M–TCNQ monolayers in both acidic and alkaline media.

In an acidic solution, the complete 4e ORR would occur via the following pathway:

 
image file: c6ra14339c-t3.tif(1)
 
image file: c6ra14339c-t4.tif(2)
 
OOH* + 3(H+ + e) → O* + H2O + 2(H+ + e) (3a)
 
OOH* + 3(H+ + e) → H2O2 + 2(H+ + e) (3b)
 
O* + H2O + 2(H+ + e) → OH* + (H+ + e) (4)
 
OH* + (H+ + e) → H2O (5)

The optimized configurations of various ORR species-adsorbed M–TCNQ monolayers along the above reaction pathway are depicted in Fig. 3, and the corresponding free energy profiles are summarized in Fig. 4.


image file: c6ra14339c-f3.tif
Fig. 3 Optimized configurations of various ORR species, including OOH, O, OH, H2O, and H2O2, on (a) Mn–, (b) Fe–, and (c) Co–TCNQ monolayers (two views). The unit of bond length is Å.

image file: c6ra14339c-f4.tif
Fig. 4 Free energy profiles (at different electrode potentials) for the ORR on (a) Mn–, (b) Fe–, and (c) Co–TCNQ monolayers in an acidic medium.

By adsorbing a proton coupled with an electron transfer, the activated O2 might be first hydrogenated to an OOH group (eqn (2)). This process should be feasible, as indicated by the calculated ΔG values of −0.60, −0.63, and −0.47 eV for the Mn–, Fe– and Co–TCNQ monolayers, respectively (Fig. 4). In the OOH* configuration, the hydrogen atom binds to the upper O atom, and the O–O bonds are further elongated to 1.47, 1.45, and 1.42 Å for M = Mn, Fe and Co, respectively.

The as-formed OOH* species can be further hydrogenated by reacting with a second proton, which may attack either the pre-hydrogenated O site (O2 in Fig. 3) or the pre-unhydrogenated one (O1 in Fig. 3). Therefore, the ORR can further proceed via two different pathways: a 4e or a 2e process. Accordingly, O2 is reduced to two H2O molecules or a H2O2 molecule.

Providing that the ORR follows the 4e pathway, the pre-hydrogenated O2 site of the OOH group will adsorb one proton coupled with one electron transfer to generate the first H2O molecule (eqn (3a)). As a result, the O1 atom will be left on the metal site with O–M bond lengths of 1.64, 1.68, and 1.78 Å for Mn, Fe, and Co, respectively (Fig. 3). The above processes on the Mn–, Fe– and Co–TCNQ monolayers are all downhill in the free energy profiles by 2.44, 1.77, and 1.18 eV, respectively (Fig. 4). Subsequently, the remaining O1 atom interacts with another proton upon one-electron reduction to yield an OH group (eqn (4)), which still resides on the metal site with O–M distances of 1.82, 1.87, and 1.87 Å for Mn, Fe, and Co, respectively. The corresponding Gibbs free energies decrease by 0.76, 1.34, and 1.89 eV, respectively (Fig. 4). Finally, the adsorbed OH group can form a new H2O molecule by reacting with one proton and undergoing one-electron reduction (eqn (5)). This final step is also downhill in the free energy profiles by 0.83, 0.90, and 1.38 eV on the three electrocatalysts, respectively (Fig. 4). Because of the weak interactions between H2O and the M–TCNQ monolayers (Ead is less negative than −0.30 eV), the water molecule can easily escape from the layer surfaces, leading to the recovery of the catalysts for the next cycle.

In the alternative 2e reduction pathway, the new coming proton interacts with the pre-unhydrogenated O1 site of the OOH group to yield a H2O2 molecule (eqn (3b)). The ΔG values of this process are −0.41, −0.38, and −0.82 eV on the Mn–, Fe–, and Co–TCNQ monolayers, respectively, much less than those of the step OOH* → O* + H2O (−2.44, −1.77, and −1.18 eV). Clearly, the ORR on the M–TCNQ monolayers energetically prefers the 4e reduction pathway rather than the 2e one. Therefore, the M–TCNQ monolayers may serve as potential ORR catalysts, since it is well known that H2O2 could greatly affect the durability of fuel cells and is a highly undesirable ORR product.

Fig. 4 also shows the effect of electrode potential on the ORR processes. At U = 0 V, most of the elementary steps are exothermic and can occur spontaneously with the only exception of the O2 adsorption on Co–TCNQ nanosheet (ΔG = 0.04 eV). With increased potentials, however, the energy profiles gradually turn to be uphill. On each M–TCNQ monolayer, the reaction of image file: c6ra14339c-t5.tif + H+ + e → OOH*exhibits the smallest ΔG value and is thus the rate-determining step. Remarkably, the maximum potentials at which all the reactions are still exothermic (i.e., the onset potentials) are 0.60, 0.63, and 0.47 V, respectively, for the Mn–, Fe–, and Co–TCNQ nanosheets. Thus, in acidic media, the Fe–TCNQ nanosheet may exhibit the best catalytic performance due to its largest onset potential (0.63 V), which is comparable to those of well-known electrocatalysts such as Pt (0.79 V),76 iron–phthalocyanine monolayer (0.68 V),59 and N-doped graphitic materials (0.50–0.80 V).77

3.4. ORR pathways in an alkaline medium

In an alkaline medium, the complete 4e ORR can proceed via the following steps:
 
image file: c6ra14339c-t6.tif(6)
 
image file: c6ra14339c-t7.tif(7)
 
OOH* + OH + H2O + 3e → O* + 2OH + H2O + 2e (8)
 
O* + 2OH + H2O + 2e → OH* + 3OH + e (9)
 
OH* + 3OH + e → 4OH (10)

In Fig. 5, we present the corresponding free energy profiles at different potentials. The reaction of image file: c6ra14339c-t8.tif → OOH* is uphill at U = 0 V on the three M–TCNQ nanosheets, suggesting that it is the rate-determining step. The onset potential for the Fe–TCNQ monolayer is 0.20 V, which is smaller than that on the Mn–(0.23 V) and Co–TCNQ sheets (0.36 eV). When an ideal electrode potential of 0.40 V is applied at pH = 14, the energy levels of every net coupled proton and electron transfer step are shifted up by 0.40 eV. In an alkaline environment, the free energies of the reactions between O2 and H2O (i.e., the rate-determining step) change to 0.63, 0.60, and 0.76 eV on the Mn–, Fe–, and Co–TCNQ monolayers, respectively. Generally, the ΔG value of the rate-determining step can be used as a measure of the whole ORR rate, and smaller ΔG indicates faster ORR process. Hence, in an alkaline medium, the Fe–TCNQ monolayer is a more efficient ORR catalyst than the other two candidates.


image file: c6ra14339c-f5.tif
Fig. 5 Free energy profiles (at different electrode potentials) for the ORR on (a) Mn–, (b) Fe–, and (c) Co–TCNQ monolayers in an alkaline medium.

3.5. Effect of the axial ligands

Due to their high activity, the central metal atoms in the M–TCNQ monolayers could be readily modulated from 4- to 5-coordination. Then, a question naturally arises: how will the coordination number of metal affect the catalytic performance of a M–TCNQ monolayer? To address this issue, we further studied the ORR on the Fe–TCNQ monolayer functionalized by some common axial ligands (R) such as F, Cl, Br, NO2 or CN group.

Our computations show that the Ead values for O2 are −0.58, −0.58, −0.60, −0.22, and −0.13 eV on the F, Cl, Br, NO2, and CN–Fe–TCNQ nanosheets, respectively. The less negative values than that on the Fe–TCNQ nanosheet (−0.94 eV) suggest less favorable O2 adsorption on the R–Fe–TCNQ monolayers. Especially, the NO2 and CN groups seriously reduce the chemical activity of the Fe–TCNQ monolayer due to their strong electron-withdrawing capability. Thus, the 5-coordination Fe in R–Fe–TCNQ monolayer is less effective in donating electrons to O2 than the one without axial ligand. Note that the halogen–Fe–TCNQ monolayers may be still feasible for O2 activation, since their ΔG values for the O2 adsorption are close to zero (0.08 eV). In contrast, the corresponding ΔG values are 0.42 and 0.55 eV for the NO2 and CN–Fe–TCNQ monolayers, respectively, indicating that the O2 activations on them are unlikely.

Since O2 molecule could be activated on the halogen–Fe–TCNQ nanosheets, we further computed the ΔG values of the subsequent ORR along the 4e reduction pathway by choosing the Br–Fe–TCNQ monolayer as an example (Fig. S2). The reduction of image file: c6ra14339c-t9.tif to OOH* is still the rate-determining step and has the ΔG value of about −0.70 eV in an acidic medium, which is slightly more negative than that of the Fe–TCNQ monolayer (−0.63 eV). In contrast, in an alkaline medium, the onset potential on the Br–Fe–TCNQ nanosheet (0.12 V) is smaller than that on the Fe–TCNQ monolayer (0.20 V). Thus, the Br addition could enhance the electrocatalytic performance of the Fe–TCNQ monolayer under both acidic and alkaline conditions, although the corresponding O2 adsorption is slightly endothermic (ΔG: 0.08 eV). Our results are consistent with the Sabatier principle,21,78 which states that an ideal catalyst should bind with the reaction species neither too strongly nor too weakly.

4. Conclusions

In summary, our spin-polarized DFT computations demonstrated that the 2D Fe–TCNQ monolayer exhibits superior catalytic performance for the ORR in both acidic and alkaline media. Its onset potentials are 0.63 and 0.20 V in acidic and alkaline media, respectively. Especially, attaching suitable axial ligands such as halogen to the Fe–TCNQ nanosheet would further improve its catalytic activity. Therefore, our theoretical results suggest a new class of quite promising non-Pt ORR catalyst for fuel cells. Recent studies have found that introducing active nonprecious transition metal (e.g., Fe, Co, and Ni) atoms into the organic polymers complexes could lead to electrocatalysts with high ORR activity and durability.79–81 More recently, the applicability of TCNQ-based nanomaterials has emerged in some important research areas including catalysis, sensing and biology.82 We thus believe that the metal–TCNQ monolayers will be employed by experimental peers for ORR applications in the quite near future. We also hope that the current work could inspire more experimental and theoretical studies on exploring the potential of 2D organometallic sheets as single-atom catalysts for ORR.

Acknowledgements

Support by NSFC (21203048 and 21103224), the Natural Science Foundation of Heilongjiang Province (B2015006), and the Excellent Young Foundation of Harbin Normal University (XKYQ201304) are gratefully acknowledged.

References

  1. G. J. K. Acres, J. Power Sources, 2001, 100, 60–66 CrossRef CAS.
  2. E. Antolini, J. Power Sources, 2007, 170, 1–12 CrossRef CAS.
  3. C. Lamy, A. Lima, V. LeRhun, F. Delime, C. Coutanceau and J.-M. Léger, J. Power Sources, 2002, 105, 283–296 CrossRef CAS.
  4. B. C. H. Steele and A. Heinzel, Nature, 2001, 414, 345–352 CrossRef CAS PubMed.
  5. M. K. Debe, Nature, 2012, 486, 43–51 CrossRef CAS PubMed.
  6. N. P. Brandon, S. Skinner and B. C. H. Steele, Annu. Rev. Mater. Res., 2003, 33, 183–213 CrossRef CAS.
  7. J. Qu, F. Ye, D. Chen, Y. Feng, Q. Yao, H. Liu, J. Xie and J. Yang, Adv. Colloid Interface Sci., 2016, 230, 29–53 CrossRef CAS PubMed.
  8. Y. Bing, H. Liu, L. Zhang, D. Ghosh and J. Zhang, Chem. Soc. Rev., 2010, 39, 2184–2202 RSC.
  9. A. Chen and P. Holt-Hindle, Chem. Rev., 2010, 110, 3767–3804 CrossRef CAS PubMed.
  10. J. Wu and H. Yang, Acc. Chem. Res., 2013, 46, 1848–1857 CrossRef CAS PubMed.
  11. L. Xiao, L. Zhuang, Y. Liu, J. Lu and H. D. Abruna, J. Am. Chem. Soc., 2009, 131, 602–608 CrossRef CAS PubMed.
  12. S. Zhang, X.-Z. Yuan, J. N. C. Hin, H. Wang, K. A. Friedrich and M. Schulze, J. Power Sources, 2009, 194, 588–600 CrossRef CAS.
  13. P. C. K. Vesborg and T. F. Jaramillo, RSC Adv., 2012, 2, 7933–7947 RSC.
  14. D. Banham, S. Ye, K. Pei, J.-i. Ozaki, T. Kishimoto and Y. Imashiro, J. Power Sources, 2015, 285, 334–348 CrossRef CAS.
  15. L. Dai, Y. Xue, L. Qu, H.-J. Choi and J.-B. Baek, Chem. Rev., 2015, 115, 4823–4892 CrossRef CAS PubMed.
  16. D. Deng, K. S. Novoselov, Q. Fu, N. Zheng, Z. Tian and X. Bao, Nat. Nanotechnol., 2016, 11, 218–230 CrossRef CAS PubMed.
  17. J. K. Dombrovskis and A. E. C. Palmqvist, Fuel Cells, 2016, 16, 4–22 CrossRef CAS.
  18. J. Duan, S. Chen, M. Jaroniec and S. Z. Qiao, ACS Catal., 2015, 5, 5207–5234 CrossRef CAS.
  19. X. Ge, A. Sumboja, D. Wuu, T. An, B. Li, F. W. T. Goh, T. S. A. Hor, Y. Zong and Z. Liu, ACS Catal., 2015, 5, 4643–4667 CrossRef CAS.
  20. D. Higgins, P. Zamani, A. Yu and Z. Chen, Energy Environ. Sci., 2016, 9, 357–390 CAS.
  21. Y. Jiao, Y. Zheng, M. Jaroniec and S. Z. Qiao, J. Am. Chem. Soc., 2014, 136, 4394–4403 CrossRef CAS PubMed.
  22. Y. Jiao, Y. Zheng, M. Jaroniec and S. Z. Qiao, Chem. Soc. Rev., 2015, 44, 2060–2086 RSC.
  23. A. Jun, J. Kim, J. Shin and G. Kim, ChemElectroChem, 2016, 3, 511–530 CrossRef CAS.
  24. J. Liu, E. Li, M. Ruan, P. Song and W. Xu, Catalysis, 2015, 5, 1167–1192 CAS.
  25. Y. Liu, X. Yue, K. Li, J. Qiao, D. P. Wilkinson and J. Zhang, Coord. Chem. Rev., 2016, 315, 153–177 CrossRef CAS.
  26. H. Miao, Y. Xue, X. Zhou and Z. Liu, Prog. Chem., 2015, 27, 935–944 Search PubMed.
  27. Y. Nie, L. Li and Z. Wei, Chem. Soc. Rev., 2015, 44, 2168–2201 RSC.
  28. R. Ramachandran, S.-M. Chen and G. P. G. Kumar, Int. J. Electrochem. Sci., 2015, 10, 8581–8606 CAS.
  29. M. Shao, Q. Chang, J.-P. Dodelet and R. Chenitz, Chem. Rev., 2016, 116, 3594–3657 CrossRef CAS PubMed.
  30. K. A. Stoerzinger, M. Risch, B. Han and Y. Shao-Horn, ACS Catal., 2015, 5, 6021–6031 CrossRef CAS.
  31. W. Xia, A. Mahmood, Z. Liang, R. Zou and S. Guo, Angew. Chem., Int. Ed., 2016, 55, 2650–2676 CrossRef CAS PubMed.
  32. J. Xie and Y. Xie, Chem. - Eur. J., 2016, 22, 3588–3598 CrossRef CAS PubMed.
  33. J. Zhang and L. Dai, ACS Catal., 2015, 5, 7244–7253 CrossRef CAS.
  34. Z. Zhao, M. Li, L. Zhang, L. Dai and Z. Xia, Adv. Mater., 2015, 27, 6834–6840 CrossRef CAS PubMed.
  35. M. Zhou, H.-L. Wang and S. Guo, Chem. Soc. Rev., 2016, 45, 1273–1307 RSC.
  36. R. Zhou, M. Jaroniec and S.-Z. Qiao, ChemCatChem, 2015, 7, 3808–3817 CrossRef CAS.
  37. C. Zhu, H. Li, S. Fu, D. Du and Y. Lin, Chem. Soc. Rev., 2016, 45, 517–531 RSC.
  38. S. Kitagawa, R. Kitaura and S. Noro, Angew. Chem., Int. Ed., 2004, 43, 2334–2375 CrossRef CAS PubMed.
  39. S. L. James, Chem. Soc. Rev., 2003, 32, 276–288 RSC.
  40. L. E. Kreno, K. Leong, O. K. Farha, M. Allendorf, R. P. Van Duyne and J. T. Hupp, Chem. Rev., 2012, 112, 1105–1125 CrossRef CAS PubMed.
  41. D. Wu, Z. Guo, X. Yin, Q. Pang, B. Tu, L. Zhang, Y.-G. Wang and Q. Li, Adv. Mater., 2014, 26, 3258–3262 CrossRef CAS PubMed.
  42. A. Bétard and R. A. Fischer, Chem. Rev., 2012, 112, 1055–1083 CrossRef PubMed.
  43. A. Corma, H. Garcia and F. X. L. I. Llabres i Xamena, Chem. Rev., 2010, 110, 4606–4655 CrossRef CAS PubMed.
  44. D. M. D'Alessandro, B. Smit and J. R. Long, Angew. Chem., Int. Ed., 2010, 49, 6058–6082 CrossRef PubMed.
  45. L. E. Kreno, K. Leong, O. K. Farha, M. Allendorf, R. P. Van Duyne and J. T. Hupp, Chem. Rev., 2012, 112, 1105–1125 CrossRef CAS PubMed.
  46. J. Lee, O. K. Farha, J. Roberts, K. A. Scheidt, S. T. Nguyen and J. T. Hupp, Chem. Soc. Rev., 2009, 38, 1450–1459 RSC.
  47. J.-R. Li, R. J. Kuppler and H.-C. Zhou, Chem. Soc. Rev., 2009, 38, 1477–1504 RSC.
  48. J.-R. Li, J. Sculley and H.-C. Zhou, Chem. Rev., 2012, 112, 869–932 CrossRef CAS PubMed.
  49. L. J. Murray, M. Dinca and J. R. Long, Chem. Soc. Rev., 2009, 38, 1294–1314 RSC.
  50. J. L. C. Rowsell and O. M. Yaghi, Angew. Chem., Int. Ed., 2005, 44, 4670–4679 CrossRef CAS PubMed.
  51. M. P. Suh, H. J. Park, T. K. Prasad and D.-W. Lim, Chem. Rev., 2012, 112, 782–835 CrossRef CAS PubMed.
  52. K. Sumida, D. L. Rogow, J. A. Mason, T. M. McDonald, E. D. Bloch, Z. R. Herm, T.-H. Bae and J. R. Long, Chem. Rev., 2012, 112, 724–781 CrossRef CAS PubMed.
  53. C.-W. Kung, J. E. Mondloch, T. C. Wang, W. Bury, W. Hoffeditz, B. M. Klahr, R. C. Klet, M. J. Pellin, O. K. Farha and J. T. Hupp, ACS Appl. Mater. Interfaces, 2015, 7, 28223–28230 Search PubMed.
  54. A. J. Clough, J. W. Yoo, M. H. Mecklenburg and S. C. Marinescu, J. Am. Chem. Soc., 2015, 137, 118–121 CrossRef CAS PubMed.
  55. S. Lin, C. S. Diercks, Y.-B. Zhang, N. Kornienko, E. M. Nichols, Y. Zhao, A. R. Paris, D. Kim, P. Yang, O. M. Yaghi and C. J. Chang, Science, 2015, 349, 1208–1213 CrossRef CAS PubMed.
  56. R. Dong, M. Pfeffermann, H. Liang, Z. Zheng, X. Zhu, J. Zhang and X. Feng, Angew. Chem., Int. Ed., 2015, 54, 12058–12063 CrossRef CAS PubMed.
  57. E. M. Miner, T. Fukushima, D. Sheberla, L. Sun, Y. Surendranath and M. Dinca, Nat. Commun., 2016, 7, 10942 CrossRef CAS PubMed.
  58. P. Zhang, X. Hou, L. Liu, J. Mi and M. Dong, J. Phys. Chem. C, 2015, 119, 28028–28037 CAS.
  59. Y. Wang, H. Yuan, Y. Li and Z. Chen, Nanoscale, 2015, 7, 11633–11641 RSC.
  60. A. Nafady, A. P. O'Mullane and A. M. Bond, Coord. Chem. Rev., 2014, 268, 101–142 CrossRef CAS.
  61. X. Zhang, M. R. Saber, A. P. Prosvirin, J. H. Reibenspies, L. Sun, M. Ballesteros-Rivas, H. Zhao and K. R. Dunbar, Inorg. Chem. Front., 2015, 2, 904–911 RSC.
  62. G. Zhu and Q. Sun, Comput. Mater. Sci., 2016, 112, 492–502 CrossRef CAS.
  63. B. Delley, J. Chem. Phys., 1990, 92, 508–517 CrossRef CAS.
  64. B. Delley, J. Chem. Phys., 2000, 113, 7756–7764 CrossRef CAS.
  65. J. P. Perdew, K. Burke and M. Ernzerhof, Phys. Rev. Lett., 1996, 77, 3865–3868 CrossRef CAS PubMed.
  66. J. A. Rodriguez, S. Ma, P. Liu, J. Hrbek, J. Evans and M. Pérez, Science, 2007, 318, 1757–1760 CrossRef CAS PubMed.
  67. Z. Wu, L. Xu, W. Zhang, Y. Ma, Q. Yuan, Y. Jin, J. Yang and W. Huang, J. Catal., 2013, 304, 112–122 CrossRef CAS.
  68. B. Delley, Phys. Rev. B: Condens. Matter Mater. Phys., 2002, 66, 155125 CrossRef.
  69. S. Grimme, J. Comput. Chem., 2006, 27, 1787–1799 CrossRef CAS PubMed.
  70. A. Klamt and G. Schuurmann, J. Chem. Soc., Perkin Trans. 2, 1993, 799–805 RSC.
  71. F. L. Hirshfeld, Theor. Chim. Acta, 1977, 44, 129–138 CrossRef CAS.
  72. J. K. Nørskov, J. Rossmeisl, A. Logadottir, L. Lindqvist, J. R. Kitchin, T. Bligaard and H. Jónsson, J. Phys. Chem. B, 2004, 108, 17886–17892 CrossRef.
  73. J. Rossmeisl, A. Logadottir and J. K. Nørskov, Chem. Phys., 2005, 319, 178–184 CrossRef CAS.
  74. A. A. Peterson, F. Abild-Pedersen, F. Studt, J. Rossmeisl and J. K. Norskov, Energy Environ. Sci., 2010, 3, 1311–1315 CAS.
  75. L. Zhang and Z. Xia, J. Phys. Chem. C, 2011, 115, 11170–11176 CAS.
  76. V. Tripković, E. Skúlason, S. Siahrostami, J. K. Nørskov and J. Rossmeisl, Electrochim. Acta, 2010, 55, 7975–7981 CrossRef.
  77. D. Yu, Q. Zhang and L. Dai, J. Am. Chem. Soc., 2010, 132, 15127–15129 CrossRef CAS PubMed.
  78. Y. Zheng, Y. Jiao, M. Jaroniec, Y. Jin and S. Z. Qiao, Small, 2012, 8, 3550–3566 CrossRef CAS PubMed.
  79. Z. Xiang, Y. Xue, D. Cao, L. Huang, J. F. Chen and L. Dai, Angew. Chem., Int. Ed., 2014, 53, 2433 CrossRef CAS PubMed.
  80. J.-Y. Choi, D. Higgins, G. Jiang, R. Hsu, J. Qiao and Z. Chen, Electrochim. Acta, 2015, 162, 224–229 CrossRef CAS.
  81. Z. Xiang, D. Cao and L. Dai, Polym. Chem., 2015, 6, 1896–1911 RSC.
  82. M. Mohammadtaheri, R. Ramanathan and V. Bansal, Catal. Today, 2016 DOI:10.1016/j.cattod.2015.11.017.

Footnotes

Electronic supplementary information (ESI) available: Spin charge density of the Fe–TCNQ monolayer, free energy profile for ORR on Br–Fe–TCNQ monolayers in acidic and alkaline media. See DOI: 10.1039/c6ra14339c
Nan Wang and Liyan Feng contributed equally.

This journal is © The Royal Society of Chemistry 2016
Click here to see how this site uses Cookies. View our privacy policy here.