Step-Edge Directed Metal Oxidation - ACS Publications - American

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Step-Edge Directed Metal Oxidation Qing Zhu, Wissam A. Saidi, and Judith C Yang J. Phys. Chem. Lett., Just Accepted Manuscript • DOI: 10.1021/acs.jpclett.6b00895 • Publication Date (Web): 14 Jun 2016 Downloaded from http://pubs.acs.org on June 15, 2016

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The Journal of Physical Chemistry Letters

Step-Edge Directed Metal Oxidation Qing Zhu a, Wissam A. Saidi b*, Judith C. Yang a,c a Department of Chemical and Petroleum Engineering, University of Pittsburgh Pittsburgh, PA 15261, United States b Department of Materials Science and Engineering, University of Pittsburgh Pittsburgh, PA 15260, United States c Department of Physics and Astronomy, University of Pittsburgh Pittsburgh, PA 15260, United States

ABSTRACT Metal surface oxidation is governed by surface mass transport processes. Realistic surfaces have many defects such as step edges, which often dictate the oxide growth dynamics and result in novel oxide nanostructures. Here we present a comprehensive and systematic study of the oxidation of stepped (100), (110) and (111) Cu surfaces using a multiscale approach employing density functional theory (DFT) and molecular dynamics (MD) simulations. We show that the early stages of oxidation of these stepped surfaces can be qualitatively understood from the potential energy surface of single oxygen adatoms, namely adsorption energies and Ehrlich-Schwöbel barriers. These DFT predictions are then validated using classical MD simulations with a newly optimized ReaxFF force field. In turn, we show that the DFT results can be explained using a simple bond-counting argument that makes our results general and transferable to other metal surfaces.

Metal alloys and metal oxides are widely used in many fields of modern industry 1-3. Understanding the process of metal oxidation is crucial towards the production of advanced oxide-based materials and plays a key role in the future growth of materials industry. In addition, controlling undesired metal corrosion resulting from exposure to air or water is critical to today’s economy. The US spends more than 3% of its gross national

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product per year to address these corrosion issues 4-5. An estimated 137 quadrillion (1015) Joule of energy are lost yearly due to high-temperature corrosion problems 6. Although the oxidation reaction of metal surfaces is highly complicated, different elementary processes, many of which are coupled, are involved from the onset of reaction. One good example for the metal oxidation study is the low-miller index surfaces of copper 7-13. Recent studies using modern electron microscopy (EM) have revealed that the initial stages of Cu oxidation bear a striking resemblance to heteroepitaxial film growth where interfacial strain is the key factor in thin film growth and determines the shape of the oxide nano-island 14-19. Through Cu oxidation, the Cu and O adatom diffusion processes dominate the oxide nucleation and the growth of the oxide nucleus. It has been well recognized that the existence of surface defects such as step edges, kinks, vacancy pits can have a profound effect on the self-assembly of the oxide. Nevertheless, there is still a debate on the role of the step-edge defect in the initial nucleation of the metal oxide. The in situ transmission electron microscopy (TEM) experiments of the oxidation on Cu(100) surface have shown no oxide nucleation preference at the step edge 20 , while for Cu(110) and Ag(110), scanning tunneling microscopy (STM) experiments showed that the oxide growth starts from the step edge through the formation of added row metal-oxygen chain structures. When exposed to oxidation atmosphere of chalcogen (S, O) molecules, the step-edge facets of Ag (111) and Cu (111) surfaces first become saturated with oxygen or sulfur adatoms first, then coarsening of the islands are accelerated by the formation of metal-oxygen or metal-sulfur cluster complexes at the step-edge vicinity 21-23. Thus, there is no simple understanding of the step-edge role in oxide nucleation and growth. To better answer this question, it is necessary to look into the basic physics of step edge. During homoepitaxial film growth on metal surfaces, occurrence of adatom islands leads to the formation of step edges at the ledge of the islands. Experimentally, continuous film growth can either lead to the formation of a smooth two-dimensional (2D) film or a three-dimensional (3D) island structures 24-26. The off-balance between these two growth mechanisms is controlled by the Ehrlich-Schwöbel (ES) barrier at the step edge 27-28. Historically the ES barrier is explained using bond-counting arguments where an adatom diffusing towards the ledge of a step has fewer bonds compared to atoms on the terrace. Thus, adatoms at the ledge are expected to have weak adsorption energy and higher transition state energy compared to terrace adatoms. As a result, the adatoms often bounce back away from the ledge as if hitting a wall, subsequently demoting the adatom descending movement off a step edge. This explains why the ES barrier effect usually reduces the interlayer mass exchange, and promotes the formation of 3D island structure in homoepitaxial film growth. Despite the well-recognized notion that the ES barrier can reduce the adatom descending movement, recent experimental and theoretical works have revealed that the upward ascending diffusion of adatoms can also play an important role during film growth 26, 29-32. For example, atomic force microscopy (AFM) experiments have revealed that 3D Al nanoclusters on Al(110) can largely attribute to the ascending adatom flux during the Al deposition 26, 29.


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On the other hand, the film growth during metal oxidation is of the heteroepitaxial type. The deposition of nonmetallic oxygen in the oxidation process is different from the case of metal deposition on metal growth. Since the magnitude of the ES barrier is affected by the chemistry/electronic environment 24, the introduction of nonmetal adatoms such as oxygen might produce different ES barrier effect. Indeed, using density functional theory (DFT) calculations, Ogawa and collaborators have showed that the binding of O atoms to the ledge at the upper side of step is stronger than on the lower foot of the A-type stepped Pt(111) surface with {100} microfacet as well as the most stable face centered cubic (fcc) site on flat Pt(111) terrace, result in 0.15 eV decrease in descending diffusion energy compared to diffusion barrier on flat Pt(111) terrace 33. This is in contrast to the conventional ES barrier effect where the opposite energy preference holds. In our recent reactive force field molecular dynamics (MD) study on the oxidation of stepped Cu(100) surface with a {110} microfacet 34, we have found that the existence of step edge leads to reduced energy barrier for ascending diffusion compared to diffusion on flat terrace, resulting in the ascending diffusion flux of oxygen adatoms and potentially leading to faster oxide nucleation on the upper terrace. Limited by the quality of the force field employed in our study, a more accurate study at the quantum mechanical level is desirable to provide better understanding of the diffusion dynamics on stepped Cu surfaces. In this paper, we use DFT combined with nudged elastic band (NEB) 35-36 calculation to probe the energetic and kinetic preferences of the oxygen adatom diffusion across stepped Cu(100), Cu(110) and Cu(111) surface models. We show that the oxygen adatom diffusion trend varies by surface-step type, where some favor the ascending diffusion, some favor the descending diffusion, and some limit the interlayer diffusion. The various step edge models in our study (shown in Figure S1) can be considered as different combinations of the three different low miller-index surfaces placed as either the lower/higher terraces or the step-edge facet. We use the notation Cu(1AB)×{1MN} to represent a step edge with a {1MN} microfacet on Cu(1AB) terrace. We limit our study to the low Miller index cases with A, B, M and N being either 0 or 1. The step edge models in our DFT calculations are of 3-layer height, expect for the Cu(110)×{111} where only 2-layer high step is modeled due to computational limitation. The choice of this step edge height is motivated by previous DFT 37 and ReaxFF 34, 38 calculations, which showed that effect of the step edge converges for step heights equal or larger than 3 layers. Only hopping mechanism is considered for oxygen diffusion process since there has been no experimental evidence that oxygen atom can diffuse through place-exchange mechanism on metal surfaces. The potential energy surfaces for oxygen adatom diffusion across the stepped surfaces are obtained from the different binding sites, and the activation energies as the oxygen atom diffuses from the lower to upper surface. Here we ignore the dissociation of O2, as this is nearly a barrierless process on all pristine Cu surfaces 39. An example for



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oxygen diffusion on Cu(100)×{110} model is illustrated in Figure 1. Our results for the barriers of the different models are all summarized in Table 1, and the adsorption energies of the different adsorption configuration during diffusion process are listed in Table S1. We first describe the oxygen diffusion barrier ∆E on the flat defect-free surfaces. From Table 1, the diffusion barriers on the defect-free Cu(100) surface are in the range of 0.7-0.9 eV, consistent with 0.74 40 and 0.89 eV 41 values reported in previous DFT calculations. The oxygen diffusion barrier along the Cu(110) in-channel direction is smaller than 0.1 eV, while along Cu(110) cross-channel direction the barrier is no more than 0.3 eV, comparable to 0.07 and 0.36 eV respectively from previous DFT calculation 41 . Finally, the barriers for oxygen diffusion are ~0.4 eV on the Cu(111) surface, consistent with 0.45 eV reported in previous DFT calculations 41-42. Thus, the oxygen adatom diffusion difficulty on the three defect-free low-index surfaces are ranked as ∆E Cu(110) in-channel < ∆E Cu(110) cross-channel < ∆E Cu(111) < ∆E Cu(100). These barriers suggest that oxygen diffusion on the stepped surfaces with a Cu(100) step-edge facet is likely to be hindered in comparison to steps with (110) or (111) facets. We also notice that oxygen adatom is most stable on Cu(100) 4-fold hollow site, while the adsorption energy for oxygen adatom on Cu(110) and Cu(111) surfaces are about 0.4 and 0.6 eV less favorable, respectively (Table S1). Thus, the Cu(100) facet is very likely to trap diffusing oxygen adatoms both thermodynamically and kinetically. Because the lower and upper terrace of the step edge are of the same surface type, the oxygen adatom has very similar adsorption energy at both ends, as can be seen from comparing the adsorption values for T1/T2 and U1/U2 configurations in Table S1. This is also in agreement with previous study of aluminum adsorption on stepped Al(110)×{100}, where the adatom binding energy on the upper terrace is similar to that on the flat terrace to within 0.1 eV 26. Thus, we do not expect the thermodynamic factors of oxygen adatoms on Cu surfaces to play important role in the diffusion dynamics on the stepped surfaces. Examining the barriers of the first ascending (from L to H sites, see Figure 1) and descending diffusion steps (from H to L sites) in Table 1, it is seen that oxygen adatom has a lower ascending diffusion barrier than the descending diffusion for Cu(100) ×{1MN} and Cu(111) ×{1MN}. Compared to the oxygen diffusion barriers on the flat Cu(100) and Cu(111) surfaces, which are respectively 0.8 and 0.4 eV, the oxygen ascending diffusion barriers of less than 0.3 and 0.25 eV have been significantly lowered on the corresponding stepped models. These translate into ascending ES barriers of approximately -0.5 and -0.15 eV, respectively. Judging from the barrier at the first diffusion step, oxygen favors ascending diffusion on stepped Cu(100) and Cu(111) surfaces. For the Cu(110)×{100} surface, ascending oxygen adatom encounters significantly increased barrier of 0.49 eV compared to the diffusion on flat terrace, which is in contrast to all the Cu(100) and Cu(111) stepped models. On the other hand, the descending diffusion barrier is just as low as the diffusion barrier on flat Cu(110) surface at 0.05 eV (along the in-channel direction). At last, for the Cu(110)×{111} surface, the ascending and descending barriers are both about the same as the diffusion barrier on the


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flat terrace, and thus the ES barriers are close to zero for both diffusion directions. Thus, based on the first diffusion step barrier, oxygen adatom descending diffusion is favored on the Cu(110)×{100} surface, while no preference exists on the Cu(110)×{111} surface. After the first ascending/descending step, we see from Table 1, that oxygen diffusion on stepped surfaces with {100} microfacet show barriers larger than 0.75 eV, which is significantly higher than the diffusion barriers on flat surface or ascending/descending the step. Thus, oxygen adatom diffusion on {100} microfacet will be hindered. As a result, the Cu(110)×{100} and Cu(111)×{100} stepped surfaces are expected to show very weak oxygen diffusion flux across the step edge for both ascending and descending directions. Also, because of the higher adsorption energy on the {100} microfacet compared to the (110) or (111) terraces, oxygen atoms are more likely to be trapped on this microfacet. The stepped models with {111} microfacet show 0.3-0.4 eV barrier for oxygen diffusion along these microfacets. Models with {111} microfacet generally do not limit the oxygen diffusion flux except for Cu(110)×{111}, where the diffusion barrier on step-edge facet is 0.10-0.17 eV higher than the first step of ascending or descending diffusion. Thus, on Cu(110)×{111} surface, oxygen adatom flux across the step edge should still be feasible, but with no direction preference since it is limited by the diffusion on the {111} microfacet. At last, Cu(100)×{110} is the only stepped model with {110} microfacet. It shows less than 0.2 eV barrier for oxygen adatom diffusion along the {110} microfacet, and thus this step-edge facet does not influence the oxygen diffusion trend. Finally, we consider the last step of the diffusion away from the step-edge facet for the models with {111} or {110} microfacets (from H to U sites and vice versa, see Figure 1). Models with {100} microfacets are no longer discussed since oxygen diffusion is limited by the step-edge facet, as discussed before. For Cu(110)×{111} model, the barrier for last step of the ascending diffusion is slightly higher (0.04 eV) than the diffusion barrier on the {111} microfacet, while the last step of the descending diffusion is smaller than the diffusion barrier on the {111} microfacet. Thus, the overall expectation for the diffusion trend on this model should not be affected by the last diffusion step, and no diffusion direction preference is expected. For Cu(100)×{110}, Cu(100)×{111}, and Cu(111)×{111} models, while oxygen diffusion on the step-edge facet is not rate limiting, the final descending step have a smaller barrier than the first descending step, thus should not affect the descending diffusion flux. The last ascending step on the two stepped Cu(100) models encounters slightly larger barrier than the first ascending step, but not larger than the barrier on the step-edge facet, thus should not influence the ascending diffusion flux, and thus the oxygen diffusion still favors ascending direction on them. While oxygen on the Cu(111)×{111} model sees larger barrier for the last ascending step than the steps before, this barrier is almost as large as the initial descending step, which may cancel out the ascending diffusion preference built at the first step. However, we still predict a favored ascending flux on the Cu(111)×{111} model as the smaller initial ascending barrier allows more oxygen adatoms to accumulate



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near the top of the step-edge facet, which thus create a concentration gradient that favors more ascending diffusion. How do we understand the diffusion barriers of oxygen on the different stepped surfaces? To address this, it is helpful to note that in copper oxide Cu2O, that is formed under most in situ experimental conditions 15, 17-20, the oxygen atoms are located in the fcc tetrahedral sites and are thus 4-fold coordinated. The stability of the various optimum/transition configurations can be gauged by comparing the oxygen bonding with copper to this optimum 4-fold bonding. Table 2 summarizes the different bonding configurations for the oxygen atoms on the different step models, and Figure 3 schematically shows these configurations for the first ascending and descending steps. For example on Cu(100), transition state for oxygen diffusion on the flat terrace is the "bridge" configuration which is only 2-fold coordinated between two Cu atoms, and is thus less stable than the favorable 4-fold coordinated hollow-site ground state configuration. This explains its large diffusion barrier. The transition states for ascending diffusion on Cu(100)×{110} and Cu(100)×{111} surface both have oxygen adatom 3fold coordinated to neighboring Cu atoms, and thus are much more stable than the transition state on flat Cu(100) terrace and leads to lower diffusion energy barrier. For Cu(110) surface, the transition state for in-channel diffusion is distorted 3-fold coordinated compared to the 3-fold ground adsorption configuration, thus shows minimum energy barrier of less than 0.1 eV. When oxygen adatom starts ascending on Cu(110)×{100} surface along the in-channel path, the transition state is only 2-fold coordinated, and is thus much less stable and leads to a higher diffusion energy barrier. On Cu(110)×{111} surface, oxygen diffusion is along the cross-channel direction before encountering the step edge, which is a migration between 3-fold coordinated sites through a 2-fold coordinated transition state. When oxygen adatom starts ascending on Cu(110)×{111} surface along the cross-channel path, the transition state is also 2-fold coordinated. Thus, the barrier for ascending on this surface is almost the same as crosschannel diffusion on flat Cu(110) terrace and results in a near zero ES barrier effect. As for Cu(111) surface, the transition state for diffusion on flat terrace is also 2-fold coordinated, which is higher in energy than the 3-fold coordinated fcc or hexagonal close packed (hcp) adsorption sites. When ascending Cu(111)×{100} and Cu(111)×{111} steps, the transition state for oxygen adatom diffusion are both partially 3-fold coordinated. Thus, the diffusion energy barrier for oxygen adatom ascending stepped Cu(111) surfaces are also lowered. For descending diffusion, similar arguments are also applicable for explaining the ES barrier effects on different surfaces. The transition states for the oxygen descending diffusion on stepped Cu(100) is partially 3-fold coordinated for Cu(100)×{110} and 2fold coordinated for Cu(100)×{111}, which is lower in energy than the transition state for diffusion on flat Cu(100) terrace. This leads to negative ES barrier where the diffusion barrier is reduced in comparison to the flat terrace. When descending Cu(110)×{100} upper terrace along the in-channel direction, the oxygen adatom moves from 3-fold coordinated adsorption configuration to distorted 3-fold transition sate, same as the one


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on flat Cu(110) terrace and leads to a near-zero ES barrier effect. On Cu(110)×{111} surface, the descending oxygen adatom diffuses from 3-fold adsorption configuration to 2-fold transition state, also the same as the one on flat Cu(110) terrace and also leads to near-zero ES barrier effect. As for two stepped Cu(111) models, the transition states are both 2-fold coordinated, and are the same as diffusion on flat Cu(111) terrace too. This leads to a nearly zero ES barrier for descending on stepped Cu(111) models. Overall, one can rationalize the different diffusion barriers at step edge using similar bond counting technique as the traditional ES barrier theory, except that in the case of O adatom on Cu surface, the large atomic radius difference between the two elements makes the bond counting more complex compared to homoepitaxy case. We expect that the early stages of Cu oxidation can be largely understood from the potential energy surface of a single oxygen atom. Because oxygen diffusion barrier generally decreases with increasing oxygen coverage 34, in real time dynamics with continuous oxygen exposure, the oxygen adatom diffusion rate may be faster than the result from our DFT NEB calculation at low surface coverage of oxygen. This is best validated by carrying simulations on large systems and for long times to allow enough time for the oxygen atom to diffuse and oxidize the surface and sub-surface layers. This is unfortunately not feasible using first principles methods due to stringent computational costs. To mitigate this challenge, we carry out MD simulations using a ReaxFF force field which we have recently optimized (unpublished work) using the current and previous DFT calculation results. Although quantitatively, this approach is not as accurate as ab initio MD (AIMD) simulation, we expect that the employed forcefield can provide results that are in agreement with the more expensive AIMD simulation qualitatively. Some details of this new force field are provided in the supporting information. The oxidation trend of the different slab models from the MD simulations can be discerned from analyzing the locations of the oxygen atoms on the lower or upper sides of the step edge. As shown in Figures 2a and 2b, for the two Cu(100) stepped models, Cu(100)×{110} and Cu(100)×{111}, oxygen adatoms tend to reside on the upper-step terraces. Given that the incident oxygen adatom at first is evenly distributed on the surface, the uneven distribution at the end of oxygen deposition after 250 ps is the result of surface diffusion. Thus, we predict from the MD simulations that the ascending oxygen diffusion is more favorable than the descending diffusion. This result is also consistent with the prediction from the DFT NEB calculations above. Notice that oxygen adatoms do not show a preference to reside at the step-edge facet, but rather reside on the upper terraces presumably because of the higher adsorption energy on the (100) terrace compared to {110} or {111} microfacets. This finding is in agreement with Yang’s in situ experimental findings that the nucleation of the oxide island does not initiate at the step-edge fact, but rather at the Cu(100) terrace distance away for the step edge on Cu(100) surface 20.



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For the Cu(110)×{100} model, the DFT NEB results would predict an even oxygen distribution on the upper and lower terraces because of the large oxygen diffusion barrier along the {100} step-edge facet. To our surprise, the ReaxFF MD simulations show that the oxygen adatom favors the upper terrace. However, upon careful examination (Figure 2c, right), we find that the majority of the oxygen adatoms on the upper terrace resides by the ledge, where the (110) terrace meets the {100} microfacet. This is attributed to the larger adsorption energy of oxygen adatom on the {100} microfacet compared to the (110) terrace, which also results in the adsorption energy on the ledge site being 0.4-0.6 eV lower than the (110) terrace sites (see Table S1). Thus, the oxygen adatoms that first landed on the upper terrace are thermodynamically trapped by the ledge, and attributes a larger amount of upper terrace oxygen counting. On the other hand, oxygen adatoms that first landed on the lower terrace are also trapped on the {100} microfacet when they attempt to diffuse up. Because theses trap sites are above the lower (110) terrace, there are less oxygen adatoms remaining on the lower (110) terrace and result in less lower terrace oxygen adatom counting. These factors also indicate that oxygen adatoms will first accumulate on the step edge on Cu(110)×{100}. Experimentally, it is observed that the oxidation on both Cu(110)×{100} 43 and Ag(110)×{100} 44 surfaces show the formation of metal-oxygen chain structures that propagates from the step edge. This is consistent with our MD simulation here that the {100} microfacet acts as oxygen adatom trapper on the Cu(110) terrace. On Cu(110)×{111} model, DFT NEB results show that oxygen has nearly the same barrier for ascending and descending diffusion, and thus it is expected that this would result in an even distribution on the upper and lower terraces. The ReaxFF MD simulations agree well with the DFT NEB calculations for this model, and indicate little discrepancy among the oxygen distribution on the upper terrace and the lower terrace. In this case, the {111} microfacet does not show apparent adsorption energy difference compared to the (110) terrace, and thus the oxygen adatom distribution is mainly governed by kinetic factors, which is consistent with the DFT NEB calculations. At last, for the stepped Cu(111) model, the A-type {100} and the B-type {111} microfacets exist on the same model simultaneously. Figure 2e shows that the oxygen adatom tends to reside more on the upper terrace on the Cu(111) model. However, the DFT NEB calculations suggest that for the A-type Cu(111)×{100} model, oxygen flux is limited for both ascending and descending directions due to the large diffusion barrier on {100} microfacet. Further for B-type Cu(111)×{111} model, oxygen adatom favors ascending diffusion. As a result, when both A and B-type microfacets exist on the stepped Cu(111) surface, the oxygen adatom favors ascending diffusion across the step edge because the ascending pathway through the B-type microfacet is kinetically favored. Also, the larger oxygen adsorption energy on the A-type {100} microfacet traps oxygen adatoms on this microfacet or along the ledge, similar to the case on the Cu(110)×{100} model. Both of these two factors enhance the oxygen adatom occupancy of the upper terrace, which is consistent with the ReaxFF MD results. This also indicates that oxygen adatom will accumulate along the A-type microfacet on the Cu(111) surface.


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Experimentally, it is observed that on stepped Cu(111) and Ag(111) surfaces, the stepedge facet gets saturated with oxygen or sulfur adatoms first when exposed to oxidation atmosphere 21-23. Our calculation for the high oxygen affinity on the A-type microfacet of the Cu(111) surface supports and explains these observations. In conclusion, we studied the step-edge defects on the oxygen adatom diffusion on the three low-miller index Cu surfaces using DFT and ReaxFF MD simulations. As the stepped surfaces can be described by the combination of three low index surfaces, there are different preferences of the oxygen adatom flux direction due to ES barrier effect. We are able to rationalize to a large extent quantitatively the different diffusion barriers on the stepped models using a simple and intuitive bond-counting argument for Cu-O bonds. Our finding suggests that the early oxidation stage on stepped metal surfaces takes place at different rates among different regions depending on the facet orientation, which can be employed to control the growth of advanced oxide nano structures. ACKNOWLEDGEMENTS We are grateful for Dr. Matthew Curnan for his comments on the manuscript. This work is supported by the United States Department of Energy (#DOE BES-ER46446) and National Science Foundation (#NSF DMR-1410055). We are grateful for computing time provided in part by the University of Pittsburgh Center of Simulations and Modeling, and by the Extreme Science and Engineering Discovery Environment (XSEDE), which is supported by National Science Foundation (#NSF OCI-1053575). Supporting Information Available: Details of the DFT and ReaxFF MD calculation settings are presented. The DFT calculated adsorption energies for oxygen adatom on all stepped Cu models are provided. Benchmark results from different pseudopotentials, k-point mesh, slab thickness, and energy cutoff in DFT calculations are given. Information for the new ReaxFF force field is provided as well.



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(37) Xiang, S. K.; Huang, H. Ab initio determination of Ehrlich-Schwoebel barriers on Cu{111}. Appl. Phys. Lett. 2008, 92, 101923-1-3. (38) Jeon, B.; Sankaranarayanan, S. K. R. S.; van Duin, A. C. T.; Ramanathan, S. Influence of surface orientation and defects on early-stage oxidation and ultrathin oxide growth on pure copper. Phil. Mag. 2011, 91, 4073-4088. (39) Gattinoni, C.; Michaelides, A. Atomistic details of oxide surfaces and surface oxidation: the example of copper and its oxides. Surf. Sci. Rep. 2015, 70, 424-447. (40) Alatalo, M.; Jaatinen, S.; Salo, P.; Laasonen, K. Oxygen adsorption on Cu(100): first-principles pseudopotential calculations. Phys. Rev. B 2004, 70, 245417-1-6. (41) Pang, X. Y.; Xue, L. Q.; Wang, G. C. Adsorption of atoms on Cu surfaces: a density functional theory study. Langmuir. 2007, 23, 4910-4917. (42) Xu, Y.; Mavrikakis, M. Adsorption and dissociation of O2 on Cu(111): thermochemistry, reaction barrier and the effect of strain. Surf. Sci. 2001, 494, 131-144. (43) Coulman, D. J.; Wintterlin, J.; Behm, R. J.; Ertl, G. Novel mechanism for the formation of chemisorption phases - the (2×1)O-Cu(110) added-row reconstruction. Phys. Rev. Lett. 1990, 64, 1761-1764. (44) Pai, W. W.; ReuttRobey, J. E. Formation of (n×1)-O/Ag(110) overlayers and the role of step-edge atoms. Phys. Rev. B 1996, 53, 15997-16005.


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Tables and Figures: Table 1. Calculated energy barriers (eV) for oxygen adatom diffusion at the stepped models. The models are shown in Figure S1.

Model

Cu(100)×{110} Cu(100)×{111} Cu(110)×{100} Cu(110)×{111} Cu(111)×{100} Cu(111)×{111}

On Terrace

0.69

0.83

0.05

0.27

0.37

0.44

Ascending Fist Step

0.07

0.28

0.49

0.23

0.10

0.23

Ascending on Facet

0.18

0.36

0.85

0.40

0.75

0.29

Ascending Last Step

0.09

0.36

0.40

0.44

0.58

0.48

Descending First Step

0.48

0.56

0.05

0.27

0.43

0.47

Descending on Facet

0.04

0.35

0.81

0.37

0.83

0.36

Descending Last Step

0.10

0.01

0.82

0.18

0.36

0.14



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Table 2. Coordination configuration for oxygen adatom diffusion on flat terrace, first ascending and descending steps on the stepped models. The italic d and p letters stands for “distorted” and “partial” coordination, as discussed in the text. Also, see Figure 3 for a schematic of these bonding configurations.

Model

Cu(100)×{110} Cu(100)×{111} Cu(110)×{100} Cu(110)×{111} Cu(111)×{100} Cu(111)×{111}

Flat Adsorption

4-fold

3-fold

3-fold

3-fold

TS

2-fold

d3-fold

2-fold

2-fold

Prior Ascending

4-fold

4-fold

3-fold

3-fold

3-fold

3-fold

TS

p3-fold

3-fold

2-fold

2-fold

p3-fold

p3-fold

Prior Descending

3-fold

4-fold

3-fold

3-fold

3-fold

3-fold

TS

p3-fold

2-fold

d3-fold

2-fold

2-fold

2-fold


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Figure 1. Illustration for oxygen adatom diffusion pathway on the Cu(100)×{110} model in DFT calculation. The grey spheres represent the Cu atoms and the red spheres represent the O atoms. The calculation follows the path where oxygen adatom ascending from the lower terrace 4-fold hollow site to the upper terrace 4-fold hollow site.



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Figure 2. Oxygen coverage during oxidation process of stepped Cu surfaces in the ReaxFF MD simulation: (a) Cu(100)×{110}, (b) Cu(100)×{111}, (c) Cu(110)×{100}, (d) Cu(110)×{111}, (e) Cu(111)×{100} and Cu(111)×{111}. The orange line corresponds to the oxygen coverage on the lower terrace, and the blue line corresponds to the coverage on the upper terrace. All atom counts are normalized with respect to the available adsorption sites. For example, for the stepped Cu(100)×{110} surface, the oxygen coverages at the upper and lower terraces are normalized to the 88 and 44 available hollow sites on the terrace, respectively. For each model, we also show a snapshot of the final configuration of the MD trajectory. The grey spheres represent the Cu atoms and the red spheres represent the O atoms.


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(a)

(b)

(c)

(d)



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(e)

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(f)

Figure 3. Schematics of the first step of oxygen adatom ascending and descending diffusion on (a) Cu(100)×{110}, (b) Cu(100)×{111}, (c) Cu(110)×{100}, (d) Cu(110)×{111}, (e) Cu(111)×{100}, and (f) Cu(111)×{111}models. The terrace atoms are represented by orange color, and those on step-edge facet are represented by blue color. The color depth is correlated with the height of the atoms along z-dimension, whereas darker (lighter) color indicates atoms are higher (lower). The initial configuration of the oxygen adatom before diffusion is shown as red solid circle, the green lines indicate the bonding configuration (4-fold, 3-fold and 2fold). The transition state is shown as dotted red circle, and the dotted green lines indicate the bonding configuration.


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155x155mm (120 x 120 DPI)


Step-Edge Directed Metal Oxidation - ACS Publications - American

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