Transparent Conducting Oxides of Relevance to ... - ACS Publications

Perspective pubs.acs.org/cm

Transparent Conducting Oxides of Relevance to Organic Electronics: Electronic Structures of Their Interfaces with Organic Layers Hong Li, Paul Winget, and Jean-Luc Brédas*,† School of Chemistry and Biochemistry & Center for Organic Photonics and Electronics, Georgia Institute of Technology, Atlanta, Georgia 30332-0400, United States ABSTRACT: Transparent conducting oxides (TCO) are a critical component of many organic electronic devices including organic solar cells and lightemitting diodes. In this Perspective, we discuss what we have learned from our theoretical investigations, at the density functional theory (DFT) level, of the electronic structures of several technologically relevant transparent conducting oxides and their interfaces with organic layers. In particular, we describe how DFT calculations can be used to provide a detailed understanding of (i) the impact of surface modification by an organic monolayer on the interfacial electronic structure and the work function; (ii) the electronic characteristics of TCO surfaces as a function of surface hydroxylation and the presence of various intrinsic and extrinsic defects; and (iii) the nature of the charge transfer taking place between an organic semiconducting layer and a TCO electrode when considering the physisorption of a monolayer of π-conjugated organic molecules on the TCO surfaces. KEYWORDS: organic electronics, density functional theory, transparent conducting oxides, surface modification, work-function modification, hybrid organic−inorganic interfaces

1. INTRODUCTION In organic electronic applications, the control of the interface between the organic materials and the metal or metal oxide electrodes is of critical importance to the overall device performance.1−12 This is particularly the case in organic lightemitting diodes (OLEDs) as well as in organic photovoltaics (OPV) where transparent conducting oxides (TCOs), such as indium−tin oxide (ITO), zinc oxide (ZnO), and its various ntype doped derivatives (e.g., aluminum zinc oxide, AZO, and gallium zinc oxide, GZO), molybdenum oxide (MoO3), and vanadium oxide (V2O5) have found numerous uses either as electrodes or as electron- or hole-selective interlayers. Understanding the nature of the hybrid interfaces between TCOs and organic layers, however, remains in its infancy due to the complexity of the metal oxides themselves; in comparison to metals, fewer experimental and theoretical investigations have been devoted to metal oxide surfaces and their interfaces with organic compounds. Metal oxide surfaces are indeed inherently complex systems that pose a number of challenges not present in the case of metal surfaces. For example, ZnO-based materials are known to assume a variety of stoichiometries and surface terminations, with multiple defects in various forms; ITO shows significantly different surface properties depending on the surface composition and surface pretreatment methods, such as O2 plasma or UV Ozone cleaning.13−19 In this Perspective, we highlight what we have learned from the quantum-chemical studies we have recently carried out on several TCO surfaces and their interfaces with organic active layers relevant to OPV applications. We address in particular © 2013 American Chemical Society

the DFT modeling of TCO surfaces where we consider surface hydroxylation and the presence of intrinsic and extrinsic defects and the theoretical description of interfaces between these TCO surfaces and chemisorbed or physisorbed organic molecular layers. This Perspective is structured as follows. After a brief introduction to the computational methodology, we will discuss our results on (i) indium−tin oxide; (ii) the polar and nonpolar surfaces of zinc oxide; and (iii) molybdenum oxide. The final Section will provide an outlook of where we believe the field should be expanding.

2. COMPUTATIONAL METHODOLOGY A well-established tool to investigate the electronic structure of surfaces and interfaces at the DFT level is the repeated slab approach that allows one to take easy account of the twodimensional periodic character of such systems. For most of the metal oxides we have studied (ITO, ZnO, GZO, and MoOx), the projector-augmented wave (PAW) method20 and the PBE exchange-correlation generalized gradient approximation (GGA) functional21 have been adopted for both geometry optimizations and self-consistent total-energy calculations. The PBE functional has also been used to evaluate the total densityof-states (DOS) and its projection onto different atoms Special Issue: Celebrating Twenty-Five Years of Chemistry of Materials Received: June 28, 2013 Revised: October 3, 2013 Published: October 4, 2013 631

dx.doi.org/10.1021/cm402113k | Chem. Mater. 2014, 26, 631−646

Chemistry of Materials

Perspective

(PDOS) on the basis of the optimized geometries. Unless noted otherwise, this is the methodology applied in the examples illustrated in this Perspective for systems with large surface unit cells (supercells) such as ITO, GZO, MoOx, and ZnO interacting with organic adsorbates. It is worth pointing out here that van der Waals interactions can play a significant role in determining the structure of physisorbed or even covalently bonded molecules on metal or metal oxide surfaces.22−24 Since most examples discussed here mainly involve covalently bonded systems at relatively low packing densities, ranging from ∼2.8 × 1013 to ∼2.7 × 1014 molecules/ cm2, the consideration of van der Waals interactions would not affect the adsorption geometries significantly in such instances. (Caution should also be taken as incorrect long-range behavior in several implementations can lead to spurious results for infinite systems.25) It must be borne in mind that local density approximation (LDA) and GGA functionals can fail to provide accurate energy-level alignments at interfaces since they provide too small bandgaps in the case of semiconductors. However, they remain the method of choice for large-scale calculations as approaches based on hybrid or range-separated functionals or the GW approximation quickly become computationally intractable. Much care then has to be exercised when analyzing at the GGA level the energy-level alignments between a TCO surface and an organic semiconductor overlayer. In a number of cases, i.e., ZnO with small supercells, we have been able to verify the results from the GGA PBE functional calculations by considering as well the short-range hybrid HSE06 functional.26−28 We note that a drawback of the repeated-slab approach is the spurious dipole−dipole interactions that can take place between the repeated asymmetric slabs along the direction perpendicular to the surface. However, such interactions can be prevented by introducing a virtual dipole sheet in the middle of the vacuum gap between the slabs, as implemented in the Vienna Ab Initio Simulation Package (VASP).29,30 This “dipole-correction” procedure allows one to extract reliably the surface electrostatic potentials on both sides of asymmetric slabs. The work function of a surface is defined as

Φ = Vvac − E F

ΔVmol. =

eμz ε0A

(2)

where A denotes a unit area, e represents the electron charge, and ε0 the vacuum electric permittivity; and (ii) the electrostatic potential energy change induced by the charge redistribution at the very interface due to the chemisorption or physisorption of the organic layer on the surface; this is equivalent to the contribution of a dipole formed at the very interface (ΔVint.dip.). In the case of metal oxide surfaces, especially the ones modified by phosphonic acid (PA) molecules, a significant relaxation of the metal oxide surface geometry is observed upon chemisorption of the PA molecules.36,37 These geometry changes can themselves induce a modulation of the charge distribution of the modified metal oxide surface beyond the electron redistribution due to chemical bonding at the interface. As a result, we have introduced a third factor to the total workfunction change (ΔVgeom.rel.), defined as the work-function difference between a bare surface taking on the geometry it assumes upon chemisorption and the initially unmodified surface. Thus, the total work-function change can be decomposed into three contributing factors: ΔΦDFT ≈ ΔVmol. + ΔVint .dip. + ΔVgeom.rel. = ΔΦsum

(3)

The ΔVmol. and ΔVgeom.rel. terms in eq 3 can be obtained directly from DFT calculations for an isolated molecular layer and a bare surface, both at the geometries optimized when the molecular layer is adsorbed on the surface. The contribution of the interface dipole can be calculated by solving Poisson’s equation: d2V (z) 1 = − Δρ(z) 2 ε0 dz

(4)

where V(z) denotes the electrostatic potential energy, ε0 the vacuum permittivity, and Δρ(z) the plane-averaged charge density difference between the combined interface system and each isolated component.

3. INDIUM−TIN OXIDE (ITO) ITO is an ubiquitous electrode material in organic electronic devices and liquid-crystal displays due to its good transparency and low resistivity. However, control of its interface with organic layers has proven to be challenging due to the variations in its surface properties coming from differences in surface composition and/or surface pretreatments. As a result, modification of the ITO surface via chemisorption of selfassembled monolayers (SAMs) has been extensively investigated over the past few years in an effort to improve the stability and efficiency of OLED38−47 and OPV devices.19,48−51 These surface modifications have been shown to provide robust means of tuning the charge injection/collection barrier at the interface, enhancing the chemical and thermal stability of the device, and enhancing the mechanical adherence of the organic active layer on the oxide surface. Experimental characterizations of the SAM-modified ITO surfaces have also been carried out to understand the origin of these modifications.17,42,52−55 In parallel, our research group has pioneered the theoretical modeling of ITO at the DFT level to provide a firm theoretical basis to the chemical and physical processes occurring at the organic−oxide interface.

(1)

where Vvac is the plane-averaged electrostatic potential energy of an electron in the vacuum region away from the slab surface at the distance where the potential energy has reached its asymptotic value and EF denotes the Fermi energy of the system. The work-function change of the metal oxide surface upon adsorption of an organic layer can be directly evaluated based on the DFT results by comparing the work function of the modified and bare surfaces. Interestingly, a decomposition scheme, first proposed by Campbell and co-workers31 and discussed extensively in our earlier work32−34 and the work of De Renzi et al.35 on thiolate molecules chemisorbed on noble metal surfaces, can be used to gain a better understanding of the factors leading to the total work-function change. In this context, the total work-function change is generally associated to two major contributions: (i) the electrostatic potential energy change across the isolated molecular layer (ΔVmol.), which is a direct function of the molecular dipole moment within the layer projected along the surface normal direction (μZ) according to the Helmholz relation 632



Perspective

3.1. Surface Model. The first task on the theoretical side was to develop a reliable model for the ITO surface.56 X-ray diffraction (XRD) patterns on ITO films obtained by different methods, such as magnetron sputtering,57 molecular beam epitaxy,58 and chemical vapor deposition59 all point to ITO adopting the bixbyite In2O3 crystalline structure with the (222) surface as the most abundant face. An orthogonal supercell based on the bulk In2O3 crystal structure and oriented along the [222] direction was then used as the initial structure to build up the ITO surface slab model. The Sn:In ratio was chosen to be 0.14, which is right in the middle of the typical doping range of 10−20% observed in commercial ITO. Here, all the oxygen atoms located in the top In−O layer were initially saturated with hydrogen atoms to simulate a completely passivated ITO surface; the surface OH coverage density is then equivalent to 6.76 × 1014 OH groups per cm2. Experimental estimations of the OH coverage are highly dependent on the cleaning process,14,18 with the lowest OH coverage estimated around 1 × 1014 OH groups per cm2 for solvent precleaned and UV ozone treated ITO surfaces.18 This surface model is illustrated in Figure 1.

An interesting aspect to point out is that the work function for such a completely hydroxylated surface is calculated to be 3.18 eV,42 which is substantially smaller than the experimental results; these range from ∼4.0 to 5.2 eV, depending on the surface preparation conditions.60−62 The discrepancy can be related a priori to several reasons, such as the surface OH coverage density or the surface composition considered in our model. We have studied the effect of the surface OH coverage by gradually reducing the number of surface OH groups; we find that when the OH coverage is reduced to ∼1.1 × 1014 OH groups per cm2, the surface work function is very significantly increased to 4.24 eV,63 i.e., within the range of experimental values. In addition, the location of the Sn atoms within the slab is also found to affect the slab surface potential. In a following study,36 we simply modified the original ITO slab by moving one Sn atom from the bottom layer to the top layer in order to model an increased presence of Sn atoms on the surface, as reported experimentally.60 Having a Sn atom in the top layer also leads to an increase in the surface work function by 0.12 eV; thus, a higher concentration of Sn atoms on the surface can also contribute to an increased work function. These examples already underline the complexity inherent to the modeling of TCO surfaces. 3.2. Adsorption Sites and Binding Modes of Phosphonic Acids on the ITO Surface. A variety of organic surface modifiers, such as silanes,64−66 amines,67−69 carboxylic acids,70−76 and phosphonic acids,70,77,78 have been used to modify metal−oxide surfaces. In our work, we have extensively considered phosphonic acid (PA) molecules as surface modifiers (see their chemical structure in Figure 2) since they have been shown to be successful in promoting robust SAMs on the ITO surface and provide versatility in workfunction modification as a function of the nature of their substituent R.47 Figure 2 displays various possible mono-, bi-, or tridentate binding modes for PAs on a metal oxide surface such as ITO.

Figure 1. Side view of the ITO (222) surface slab optimized at the DFT/PBE level. A pink sphere represents In; gray, Sn; red, O; and light pink, H.

Figure 2. Sketch of possible binding modes for phosphonic acid molecules on metal oxide surfaces. 633



Perspective

Figure 3. Plots comparing the changes in work function measured by UPS (red) and evaluated by DFT (blue) as a function of the calculated μz values (reported in Table 1), for the six PA molecules depicted at the bottom, listed from left to right in the same sequence as the data points. Note that the calculated ΔΦ values are those very crudely extrapolated for a coverage of ∼8.4 × 1013 molecules/cm2 by tripling the ΔΦ values calculated for coverages of ∼2.8 × 1013 molecules/cm2 (see text).

3.3. Electronic Properties of PA-Modified Surfaces. 3.3.1. Work-Function Change and Dipole Moment of Surface Modifiers. In order to analyze the correlation between the work-function modification and the dipole moment of different surface modifiers (related to the Helmholz relation presented earlier), we considered six benzyl−PA molecules with different degrees of fluorination; see Figure 3.42 The binding geometries of the PA molecules on the (oxygen− plasma treated) ITO surface and the work-function modifications were also characterized experimentally via XPS and ultraviolet photoelectron spectroscopy (UPS) measurements. The chemical structures of the PA molecules ensure that significant modulations of the molecular dipole moment can be realized along the surface normal direction (μZ) when they are attached to the ITO surface.81 Among the six benzyl−PA molecules, the first five have negative μZ values (defined such that the negative pole points outward the surface) while the last one has a positive μZ; see Table 1. All the calculations were initially carried out for a surface coverage of ∼2.8 × 1013 molecules/cm2, equivalent to one PA

From a comparison of the DFT-calculated O(1s) core-level binding energy shifts (CLBES) with the experimental values obtained in X-ray photoelectron spectroscopy (XPS) measurements,36,56,79,80 binding modes (c), (d), and (e) of Figure 2 were found to be the predominant binding modes for PA molecules chemisorbed on the ITO surface. The binding geometries and binding energies corresponding to these three predominant binding modes have been compared as a function of surface coverage density for 3,4,5-trifluorophenyl-phosphonic acid molecules adsorbed on the ITO surface.36 The results are largely independent of surface coverage and indicate a lower binding energy for the bidentate binding mode (c) by about 0.5−0.7 eV with respect to the tridentate binding mode (d) and the bidentate binding mode (e) involving hydrogen bonding between the PO moiety and the surface hydroxyls. We need to keep in mind, however, that since the surface binding geometry can also depend on the kinetics of molecular adsorption, a higher binding energy may not necessarily lead to a dominant molecular binding geometry on the surface. 634



Perspective

electrode Fermi energy to the ionization potential (roughly speaking, “HOMO energy”) of the organic layer. 3.3.2. Work-Function Change and Surface Coverage. To study the impact of the SAM coverage on the surface work function, we turned to a model case where surface coverage is linearly increased for a given modifier, 3,4,5-trifluorophenyl-PA (F3PPA). Starting from a coverage of ∼2.8 × 1013 molecules/ cm2, we increased the PA density by factors of 2, 3, and 4, with the latter then corresponding to a coverage of ∼1.1 × 1014 molecules/cm2.36 This is achieved in the calculations by increasing the number of F3PPA molecules per surface unit cell, n, from 1 to 4; the adsorption locations were then randomly selected for the PA molecules in order for them to assume a relatively homogeneous distribution on the surface unit cell and for the phosphonate moieties to have direct access to the surface In/Sn atoms as well; see Figure 4. The binding geometries for all PA molecules involved in all possible combinations of the adsorption locations at each coverage density were optimized at the DFT level. The main results are displayed in Table 2 with the total work-function change and its components plotted in Figure 5.

Table 1. DFT Results for the Work-Function Change, the Contributions of the PA Monolayer and the Interface Dipole, the Perpendicular Dipole Moment for the PA Monolayer at a Coverage of ∼2.8 × 1013 molecules/cm2, and the UPS Work-Function Modifications81 BnPA

pCF3

mpF3

F5

mF2

pF

oF2

ΔΦDFT (eV) ΔVmol. (eV) ΔVint.dip. (eV) μz (Debye) ΔΦ (UPS)

0.38 0.24 0.11 −2.24 1.1

0.33 0.21 0.12 −1.95 0.8

0.29 0.19 0.12 −1.75 0.7

0.30 0.15 0.10 −1.41 0.7

0.24 0.13 0.09 −1.21 0.5

0.13 −0.01 0.11 0.11 −0.1

molecule per surface unit cell of our original ITO surface model. Such a coverage value is in fact rather low when compared to the experimental estimate reported by Koh and co-workers for aryl−PA molecules on the ITO surface, on the order of 1 × 1014 molecules/cm2.53 A point to be made from Table 1 is that, at low coverage, the interface dipoles and binding geometries are very similar for all six PA SAMs, which leaves the SAM molecular dipole as the main contributor to the work-function change (ΔΦ) of the ITO surface. In Figure 3, the ΔΦ values measured by UPS for the six PA surface modifiers are compared to the DFT values as a function of the calculated μz values. As a very crude first step to take into account the higher coverages expected in the experiments, we simply took the ΔΦ values of Table 1 calculated for a coverage of ∼2.8 × 1013 molecules/cm2 and tripled them to simulate a coverage of ∼8.4 × 1013 molecules/cm2. Both experimental and computed ΔΦ values evolve in an approximate linear fashion with μz. However, the slopes of these evolutions are rather different, which can be related to our very rough extrapolation procedure for the theoretical data; this prompted us to investigate in more detail the impact of surface coverage, which we consider in the next Subsection. An important message from the experimental data in Figure 3 is that the surface modification of ITO with fluorinated benzyl−PA SAMs leads to work-function modulations over a 1.3 eV range, depending on the number and location of the fluorine atoms on the phenyl ring. In particular, the ITO work function can be increased by over 1 eV; this can facilitate charge injection into or charge collection from an organic holetransport layer, since it is expected to better match the

Table 2. Averaged Work-Function Change of the ITO Surface and Contributing Factors Calculated for Adsorption of 3,4,5-Trifluorophenyl−PA Molecules at Different Coverage Densities coverage density n n n n

= = = =

1 2 3 4

|μz| (D)

ΔVmol. (eV)

ΔVint.dip. (eV)

ΔVgeom.rel. (eV)

ΔΦsum (eV)

ΔΦDFT (eV)

3.38 6.07 7.66 9.47

0.36 0.65 0.82 1.01

0.23 0.46 0.66 0.79

−0.09 −0.24 −0.35 −0.41

0.50 0.87 1.10 1.40

0.49 0.89 1.17 1.42

Note that for the n = 1−3 molecular coverages, each column of Table 2 gives the corresponding value averaged over all possible combinations of adsorption sites for each coverage. For the n = 4 coverage, the reported values are the direct DFT results, as there is just a single configuration in this case. The message Table 2 delivers is clear: Up to n = 3, i.e., a coverage of ∼8.4 × 1013 molecules/cm2, the contributions from the interface dipole and the surface geometry relaxations evolve in a nearly linear fashion; on the other hand, the contribution

Figure 4. Top view of the PA-modified ITO surface; each surface unit cell contains four PA molecules, representing the highest coverage density. 635



Perspective

nanostructures98,122−132 have been widely investigated, while surfaces133−154 overall have received less attention. ZnO crystallizes in the hexagonal wurtzite structure (space group P63mc) with four oxygen atoms surrounding each zinc atom; since the Zn−O bonds are partially ionized, intrinsically the valence band maximum (VBM) is mainly comprised of O 2p orbitals and the conduction band minimum (CBM) of Zn 4s orbitals. Understanding the origin of the (unintentional) n-type conductivity of the ZnO crystal has been a topic of intense debate both experimentally102,105,108,155,156 and theoretically.103,104,106,107,110,111,113,114,116,118,157−160 A variety of possibilities have been presented as the source of n-type dopants; these include zinc interstitials, oxygen vacancies, and hydrogen impurities. In general, again, less attention has been given to determining the nature of similar defects on the ZnO surfaces. Extrinsic doping has also been used to trigger n-type conductivity, in particular, by replacing a few % Zn atoms with trivalent metal atoms such as Al, Ga, or In.161 While the sheet resistivity of naturally doped ZnO is on the order of 10−3 Ω cm,8 sheet resistivities reaching 10−4−10−5 Ω cm are obtained in ZnO:Al or ZnO:Ga.162−165 In the case of ZnO surfaces, we have considered a specific computational methodology, which has been applied in all our calculations on ZnO polar and nonpolar surfaces and is detailed in ref 154. In order to describe the Coulomb interactions among the localized zinc 3d-electrons, we adopted a GGA+U approximation166 (PBE functional) where U is the on-site Hubbard parameter. In addition, in instances where the (smaller) size of the unit cell allowed it, we used the rangeseparated HSE06 functional, which has been exploited to calculate the band gap of ZnO crystals and provides very good agreement with experimental values.167 Note that, hereafter, since ZnO is an n-type semiconductor,92,135 the work function of the ZnO surface slab is usually defined as the energy difference between the CBM (taken as a “quasi-Fermi level” in this instance) and the electrostatic potential energy of an electron away from the surface. 4.1. Polar ZnO(0002) Surface. The growth direction of ZnO films is found experimentally to occur preferentially along the c-axis, which exposes the (0002) or (0001) surfaces, which are connected through a 6-fold screw axis; however, other orientations can also be observed depending on substrates and conditions.168−171 We note that the (0001) plane has the same C3 rotational symmetry as the (0002) plane and the properties obtained for the (0001) plane are applicable to the (0002) plane. Since in the ZnO crystal the dipole moment of the bulk unit cell is directed along the crystallographic [0001] direction, the (0002) or (0001) surfaces have a polar character. Much work has actually been devoted to understanding the stabilization of the zinc- or oxygen-terminated polar surfaces;124,142−145,147−149,172−178 for instance, the earlier DFT work on ZnO polar surfaces focused on modeling the stabilization mechanism of the zinc-terminated (0001) surface by considering oxygen adatoms, OH groups, zinc vacancies, and triangular-shaped surface reconstructions.143,144 4.1.1. Surface Defects and Termination. As mentioned above, ZnO is an n-type material due to unintentional ndoping, with zinc interstitials (Zni) and oxygen vacancies (VO) as well as hydrogen impurities proposed as possible dopants. In the absence of definite experimental data as to the actual chemical structure of the ZnO polar surface, we decided to carry out an extensive evaluation of a number of surface

Figure 5. Evolution of the work-function change and its three contributing factors vs the number of PA molecules per unit cell.

from the SAM dipole evolves in a marked sublinear fashion (with the difference between the n = 1 and 2 coverages amounting to 0.29 eV and that between the n = 2 and 3 coverages, to 0.17 eV), which explains the discrepancy found in Figure 3. The reason for this sublinear evolution is well documented and is related to the depolarization ef fect occurring when individual molecular dipole moments are placed in increasingly closer proximity.82−88 For n = 4 (coverage of ∼1.1 × 1014 molecules/cm2), all contributions show a marked saturation trend. We also note from Table 2 that the Helmholz linear relationship between ΔVmol. and μz, see eq 2, is perfectly followed (with the ΔVmol. (eV)/|μz| ratio for all four coverage densities found at 0.514 V/Å). Figure 5 illustrates the correlation between the work-function change and its components as a function of surface coverage. The evolutions can be very well fitted by a quadratic function.36 Interestingly, a maximum work-function increase can then be extrapolated from the quadratic fitting and would correspond to ΔΦ of +1.53 eV for a coverage density of ∼1.56 × 1014 molecules/cm2 (n = 5.54). What is confirmed by these results is that the work-function change is not a simple linear function of surface coverage and can be expected to saturate at high coverages. It is also useful to point out that, at low coverage (n = 1, 2), ΔVint.dip. displays large variations as a function of the exact binding sites and binding configurations of the PA molecules: The ΔVint.dip. values range from 0.11 to 0.37 eV for n = 1 and from 0.17 to 0.80 eV for n = 2 (see Table 1 of ref 32 for more detail). At n = 3, however, the differences become much smaller, with ΔVint.dip. varying between 0.59 to 0.73 eV. These results indicate that the charge redistribution at the PA/ITO interface tends to have a local character at low coverage densities; at high coverage, increased interactions between the molecular layer and the ITO surface and among the molecules lead to a more similar pattern. Similar trend can be observed for the contribution of ΔVgeom.rel., which is also related to more local effects at low coverage.

4. ZINC OXIDE Zinc oxide is an n-type conducting oxide that has attracted significant attention for use in organic electronic devices1−12,89−92 due to its wide band gap (Eg = 3.3−3.4 eV)93 and the possibility of growing ordered nanostructures.94−101 The electronic and optical properties of ZnO bulk93,102−121 and 636



Perspective

hydroxylated Model-1 is considered as a reference system to examine the electronic structure and work function change induced by other intrinsic structural defects. For Model-2 that includes zinc vacancies at very high densities, the charge distribution corresponding to the VBM is associated with the dangling bonds of the surface oxygens and shows a much higher localization within the first Zn−O layer than in Model-1. Interestingly, the work function of the surface dominated by zinc vacancies is calculated to be 3.91 eV, which is 1.26 eV larger than the calculated work function for the OHcovered surface. This is related to the potential energy change near the surface induced by the presence of the zinc vacancies, the charge rearrangement on the surface, and the reorganization of the surface geometry. Interestingly, more recent calculations we performed on surface models with VZn surface densities reduced to 1/4 and 1/8 that of Model-2 result in work-function increases of 0.66 and 0.25 eV, respectively, which points out that the work function can be significantly modulated by the defect surface density. In the case of Model-3 (presence of OH group and oxygen vacancies), the calculated PDOS shows a state crossing the Fermi level, corresponding to a Zn−Zn metallic-like state induced by the absence of oxygen atoms. We note that this situation is significantly different from that in the VO-containing bulk crystal, where the oxygen vacancies were identified as deep electron-donor states;110,111,114,116,158 here, analysis of the DOS suggests that oxygen vacancies on the surface behave rather as shallow electron donors. The work function is calculated to be 2.90 eV, which is 0.25 eV higher than the value obtained for the OH-terminated surface. Turning to Model-4 that includes hydroxyl groups and pairs of oxygen and zinc vacancies, the top of the VZn-related states is located 2.0 eV below the CBM. This result underlines that zinc vacancies can act as electron-acceptor states (this is the case as well for the isolated VZn-related states of Model-2). The implication is that, in terms of OPV applications where ZnO is used as an electron-selective layer, such zinc vacancies should be avoided since they would provide for electron traps (sometimes referred to as electron-“killer” states). Another interesting feature in this model is that, in the course of the geometry optimizations of the slab, the oxygen vacancies become filled by OH groups; as a result, there is no formation of Zn−Zn metallic bonds and the metal-like states of Model-3 are not present. The work function here is estimated to be 4.43 eV, which is in good agreement with the upper limit of the experimental values that vary between 3.5 and 4.3 eV.92,135,136,138,180 Finally, we also considered a model surface (Model-5) where, in addition to the hydroxyl groups and pairs of zinc and oxygen vacancies of Model-4, we introduced zinc interstitials (Zni) (with a surface density of 6.8 × 1013 Zni per cm2) that act as electron donors and explicitly provide n-type charge carriers to the surface. While a number of DFT calculations have found Zni’s to have highly positive formation energies,110,111,114,116,158 data coming from high-energy electron irradiation experiments on the Zn-terminated (0001) surface in fact suggest that Zni defects could represent the native shallow electron donors in ZnO.102 The PDOS for Model-5 shows that the Fermi level is located at about 0.8 eV above the original CBM of Model-4, which confirms the degenerate n-doping of the surface due to the high surface density of interstitial zinc atoms. As a result, the work function of Model-5 is evaluated to be 2.87 eV; this is 1.56 eV lower than the work function of Model-4, which is

models, the details of which can be found in ref 154. Below, we briefly discuss some of the main results of this work, with the goal of underlining the inherent chemical and electronic complexity of metal oxide surfaces. We have first considered model surfaces for which we did not attempt to take explicitly into account the n-type conductivity and thus the presence of charge carriers in the conduction band. These model surfaces, illustrated in Figure 6, include: (i) a surface terminated by OH-

Figure 6. Top view of the ZnO(0002) surface models: (a) represents the OH-terminated surface; (b) the surface with VZn; (c) the OHcovered surface with VO; and (d) the OH-covered surface with VZn and VO. The black dots indicate the locations of zinc or oxygen vacancies; the black rectangle represents the surface unit cell used in the calculations. [Figure reprinted with permission from ref 154. Copyright 2012 ACS.]

groups (Model-1); (ii) a nonhydroxylated surface containing zinc vacancies, VZn (Model-2); (iii) a hydroxylated surface containing both OH-groups and VO (Model-3); and (iv) a hydroxylated surface containing OH-groups and pairs of VO and VZn (Model-4). In all these models, to keep the surface unit cell to a reasonable size, we had to consider high surface defect densities, on the order of 2.7 × 1014/cm2 for zinc and oxygen vacancies. Thus, in comparison to experimental data, these models represent limit cases. We note that the energetic stability of the investigated structural defects was thoroughly analyzed as well.154 Using these model surfaces, we carried out HSE06 calculations to gain insight into the evolution of the electronic structure and work function as a function of the presence of a variety of surface defects and terminations. For Model-1, a band gap of 2.89 eV is obtained for the slab, which is 0.46 eV lower than the band gap calculated for bulk ZnO using the same functional. As in the crystal, the VBM is mainly composed of contributions from O 2p orbitals belonging to oxygen atoms within the top Zn−O layer, while the CBM is composed of the contributions from Zn 4s orbitals. The work function is calculated to be 2.65 eV, which is much lower than the minimum experimental value of 3.5 eV observed for a zincterminated polar surface in the case of high charge carrier density (∼8 × 1013 e/cm2).137,179 In this case, the fully 637



Perspective

between the component of the PA molecular dipole moment perpendicular to the surface and the modification of the surface work function is obtained. The most striking feature of Figure 7, however, is that the entire data set for the bidentate systems is shifted 2.1−2.3 eV downward with respect to the corresponding tridentate systems. To understand this result, we analyzed the charge density associated with the CBM and VBM for each system. For both bidentate and tridentate systems, the CBM level is mainly located within the bulk of ZnO, which indicates that the CBM of the ZnO surface is not affected by surface modification with PA-SAMs. However, a significant difference is obtained regarding the VBM for the two binding geometries. In the bidentate systems, the VBM essentially corresponds to O(2p) orbitals within the top two Zn−O layers; for the tridentate systems, it corresponds to contributions from the molecular SAM. The projected density of states shows that the energy level of the HOMO of the tridentate PA-SAM is right above the top of the ZnO valence band, which is consistent with the charge distribution. For the bidentate configuration, the HOMO level is significantly below the VBM of the ZnO surface. This difference can be rationalized by comparing the charge transferred from the ZnO surface to the molecules for the two binding modes. While in the bidentate case only about 0.2 e is transferred, about 0.5 e is transferred in the tridentate case from the ZnO surface to the PO3 group of the molecule, which results in a destabilization of the HOMO level. These results highlight that the binding mode can thus have a significant effect on the energy-level alignment of the molecular frontier orbitals with respect to the band edges of the metal oxide).36,37 Another interesting group of surface modifiers are amines. It was recently shown by Kippelen and co-workers that, when an ultrathin layer (1−10 nm) of a polymer containing simple aliphatic amine groups is physisorbed onto a conductor surface, a nearly universal decrease in work function of ∼1.5 eV is measured on a variety of surfaces including ITO, ZnO, gold, and graphene.184 To model the polyamines of ref 69, we considered a SAM of ethylamine (C2H5NH2) molecules adsorbed on the polar ZnO (0002) surface. In contrast to the phosphonic acids, physisorption of the ethylamine groups is calculated to be energetically favored over dissociative chemisorption, which is consistent with the experimental observations. The change in work function of the ZnO (0002) surface is calculated to be −1.7 eV, fully in line with the UPS and Kelvin probe data.69 The mechanism leading to ΔΦ has been analyzed as usual by decomposing it into contributions from (i) the ethylamine molecular dipole (μz) within the SAM along the direction perpendicular to the surface (ΔVmol) and (ii) the dipole formed at the interface between the molecular SAM and the electrode surface (ΔVint.dip.). In the present case, the contributions of ΔVmol and ΔVint.dip. to ΔΦ are of the same order of magnitude, −0.9 and −0.8 eV, respectively. The contribution to ΔΦ coming from the interface dipole is related to a slight electron transfer, 0.07 e, from the amine-containing molecules to the electrode surface, corresponding to a dativetype bond from the lone pair of the nitrogens to empty Zn(s) orbitals. 4.2. Non-Polar ZnO(101̅0) Surface. The ZnO(1010̅ ) nonpolar surface of zinc oxide is the energetically most favorable surface; since the electrostatic instabilities seen for the polar surfaces are no longer present, the geometric structure

partly due to the high surface charge carrier density. This trend is consistent with experimental observations that the work function of zinc-terminated polar surfaces can be reduced by as much as 0.75 eV when the charge carrier density is increased to about 8 × 1013 e/cm2.137,179 Our goal in discussing the main results of our investigations of ZnO(0002) surface models was mainly to underline the marked variations in surface electronic properties that occur as a function of the nature of surface defects. Some trends were established; for instance, it appears that the presence of zinc vacancies consistently leads to higher work functions, more in line with the experimental data, while the explicit consideration of high surface carrier densities lowers the work function. A clear implication of this work is that further joint experimental and computational studies are warranted to assess better the nature and density of surface defects and their impact on the surface electronic properties. 4.1.2. Monolayers. We now turn to a discussion of the adsorption of organic layers on the zinc oxide surface. As in the case of ITO described above,36,40,42,44,180−183 it is possible to tailor the ZnO/organic interface using surface modifiers. First, we investigated four benzylphosphonic acids with varying degrees of fluorination: benzyl-PA, oF2BnPA, pFBnPA, and F5BnPA (see Figure 3 for chemical structures); the calculations were performed with the PBE functional (in the GGA+U approximation) on a hydroxylated surface containing both zinc and oxygen vacancies, i.e., Model-4 (at the PBE level, the work function of the unmodified surface is 4.68 eV, only slightly higher than the HSE06 result of 4.43 eV).36,37 The calculated changes in work function for the PA-modified ZnO surface are given in Figure 7 in the case of both bidentate and tridentate bindings. In both instances, the work-function change ranges over some 1.3−1.5 eV as a function of the fluorination pattern; this is the same range as in previous studies using the fluorinated benzylphosphonic acids on the ITO surface36 we discussed in Section 3 or semifluorinated alkylthiols on gold surfaces.181 Again, a clear correlation

Figure 7. Plot comparing the changes in DFT-calculated work function as a function of the calculated dipole moments (μz) for four PA molecules adopting bidentate (green) or tridentate (blue) binding modes. 638



Perspective

Figure 8. Total density of states for the bare surface (red line) and projections onto the PTCDI fragment (blue line) and ZnO substrate (green line) for the (a,b) stoichiometric, (c,d) O-deficient, and (e,f) Zni-containing ZnO nonpolar surfaces.

(PTCDI) deposited on conductive ZnO surfaces used as electrodes in organic solar cells.182,186−188 We now briefly discuss the main results of our calculations on this model system as it captures many of the central issues present at the electron-collection interface in small-molecule based organic devices. In the case of PTCDI, the experimental solid-state values of electron affinity and ionization energy are measured to be 4.04 and 6.42 eV,189 respectively. From these data, if vacuum-level alignment were to be assumed, the PTCDI HOMO would be expected to lie inside the ZnO bandgap and the LUMO close to the conduction band edge. In our calculations, the adsorption geometry of the PTCDI molecules is largely insensitive to the molecular density and the presence and exact location of defects. On all surfaces, the molecular geometry distorts slightly relative to the gas-phase equilibrium structure and tilts away from a cofacial geometry. In the presence of Zni, PTCDI adsorbs slightly more closely to the surface, which is reflected in a larger adsorption energy, 2.3 vs 1.1 eV, for the Zni-containing vs the VO-containing surface. Adding an empirical dispersion term to the DFT functional as was done in a similar study of zinc phthalocyanine on ZnO23 does increase the adsorption energy and leads to a smaller intermolecular distance. Despite these differences in geometries, the resulting electronic structure remains similar. Upon PTCDI adsorption on the stoichiometric and oxygendeficient surfaces, the calculated work functions decrease to 3.81 and 3.95 eV, respectively. However, in the presence of Zni defects, the work function increases to 4.66 eV. While the electronic structures of the PTCDI−ZnO interfaces are very similar in the case of the stoichiometric and O-deficient surfaces, there is a major difference in the case of the Znicontaining ZnO surface due to substantial charge transfer from

near the surface is expected to be similar to that in the bulk. The nonpolar surface has been the subject of a number of calculations.37,53,55,56 As it avoids the ambiguities of surface termination and reconstruction problems inherent to the polar surface, the nonpolar surface can be advantageously used to try and better understand the role of surface defects in heterojunctions formed with organic layers. In our theoretical work on the nonpolar surface, we have considered the impact of the presence of a low concentration of either oxygen vacancies (one per 120 oxygen atoms) or zinc interstitials (one per 120 zinc atoms) introduced in the near-surface region; we recall that VO and Zni represent prototypical surface defects in ZnO films.110,136 Assuming that such defects contribute each two free electrons, the resulting free electron surface density is 1.0 × 1014 e/cm2, which is consistent with the experimentally determined values for both bulk and sheet concentrations.185 For the bare stoichiometric (101̅0) surface, we calculate a work function of 4.64 eV, which is in good agreement with the experimental value of 4.65 eV.92,135,136,138,180 While introduction of VO defects leads to a slightly lower work function of 4.54 eV, the calculated work function drops to 3.72 eV in the presence of Zni defects. This trend is consistent with the experimental observations that the work function of the zincterminated ZnO polar surface can be reduced by as much as 0.75 eV when the charge carrier density is increased to about 8 × 1013 e/cm2.137,179 It is important to note that VO defects result in the appearance of deep donor states while Zni defects lead to shallow donor states. We have been particularly interested in the interface formed between organic semiconductors physisorbed on metal oxides for which the frontier molecular orbitals are close to the CBM of the metal oxide. A first study was devoted to the prototypical electron acceptor 3,4,9,10-perylene-tetracarboxylicdiimide 639



Perspective

the same surface defects at the same defect density as in Model4. We considered a Ga doping ratio of ∼1.5% (well within the experimental doping levels of 1−5% for GZO thin films)192 and a surface coverage density for the PA molecules of 1.3 × 1014 molecules/cm2 (which is similar to the highest coverage density modeled for the PA-modified ITO surface, 1.1 × 10 14 molecules/cm2). A tridentate binding mode is preferentially obtained for all the PA molecules adsorbed on the GZO surface, which is consistent with the trends observed on the ZnO surface (where we recall that the tridentate binding mode is found energetically more favorable than the bidentate mode by ∼0.6 eV). GZO corresponds to a degenerately n-doped system, the bottom of the conduction band is occupied and the Fermi level located at ∼0.6 eV above the CBM (at the DFT/PBE level). The work function of the GZO surface model is calculated to be 3.28 eV, which is in excellent agreement with the UPS data.191 The work-function change upon deposition of the PA molecules amounts to some +1.6 eV for the surface modified with perfluorophenyl-PA and +0.4 eV for that modified with the 2,6-fluorobenzyl-PA SAM. Decomposition of the work-function change into its contributions (ΔVmol., ΔVgeom.rel., and ΔVint.dip.) points to an important dissimilarity between the GZO modified surface and the ZnO Model-4 surface. In fact, in the latter case and for a tridentate binding of PA surface modifiers, the magnitudes of the ΔVgeom.rel. and ΔVint.dip. components are much larger, on the order of −0.8 to −0.9 eV and +2.1 to +2.5 eV, respectively. These results underline the major qualitative differences that occur when considering a surface with no explicit charge carriers in the conduction band as in the ZnO Model-4 (corresponding to a large-gap intrinsic semiconductor) and a degenerately n-doped surface with high surface charge-carrier density such as the GZO surface.

the surface to the PTCDI layer. While less than 0.1 e is transferred across the interface to each PTCDI molecule for the stoichiometric and VO surfaces, almost a full electron is transferred from ZnO to PTCDI on the Zni surface. Thus, even in rather modest concentrations, shallow donor states such as those due to Zni act as strong electron donors in the presence of molecular acceptors such as PTCDI. Conversely, deep donor states such as VO require a stronger electron acceptor than PTCDI in order for the electronic structure to be significantly impacted. An illustration of the calculated electronic levels for the three types of nonpolar ZnO surfaces and interfaces with PTCDI is shown in Figure 8. For a stoichiometric surface, the calculations show that the HOMO is buried inside the valence band region and only a single unoccupied state (the molecular LUMO) appears at −0.72 eV with respect to the conduction band minimum. However, these results are in marked contrast to the experimental findings, where the HOMO lies inside the band gap and there appears an interface state very close to EF.185 For the O-deficient interface, both a dangling bond state and the LUMO are found around −0.6 eV with respect to the CBM, with the HOMO again buried inside the valence band. Thus, neither the calculated work-function changes nor the calculated electronic structures for both stoichiometric and O-deficient surfaces agree with the experimental data. For the Zni-containing surface, in contrast, the presence of the zinc vacancies near the surface leads to an occupied state at 0.1 eV above the valence band maximum (−1.27 eV) and a partially occupied set of states near the Fermi level, associated with both the molecule and the interstitial Zn atom. While we recall that the gaps of both ZnO and PTCDI are underestimated in PBE calculations, the qualitative agreement with experiment we obtain for this model interface is striking, with a PTCDI HOMO above the valence band maximum and a hybrid interface state near EF originating from substantial charge-transfer from ZnO to PTCDI. Thus, the presence of interfacial gap states due to partial charge transfer to low-lying acceptor levels of the molecule from shallow donors, i.e., Zni rather than deep donors such as VO, is accompanied by a large interface dipole and substantial increase in work function without major band bending. The results described in this Section provide another example of the sensitivity of the interfacial electronic structure to the details of the surface chemistry. While they both correspond to electron-donor states, oxygen vacancies and zinc interstitials have very different impacts on the electronic structure of interfaces with an organic semiconductor such as PTCDI. Also, exclusive consideration of the stoichiometric surface would not provide an interfacial electronic structure in agreement with experiment.185 4.3. Modification of the Gallium-Doped ZnO Surface. Previous sections have highlighted the role of intrinsic dopants in the electronic structure of ZnO surfaces and their heterojunctions. Over the past 10 years, ZnO films extrinsically doped with gallium, aluminum, or indium atoms (GZO/AZO/ IZO) has been extensively studied as transparent conducting oxides in both OPV and OLED applications.161,190 In a recent work,191 we have investigated the modification of the polar GZO(002) surface by a series of unsubstituted and fluorine-substituted phenyl and benzyl phosphonic acid SAMs. It is instructive to compare the results obtained for GZO with those described above for the modification of Model-4 of the ZnO(0002) surface. The GZO(002) surface was modeled with

5. MOLYBDENUM OXIDE Molybdenum oxide (MoO3), vanadium oxide (V2O5), and tungsten oxide (WO3) have been extensively used as holeinjection or hole-extraction layer in OLED and OPV devices due to their remarkably high work function, over 6 eV.193−198 Since films of these metal oxides operate as a hole injection/ extraction layer, it was generally assumed that charge transport was involving the top of the valence band of the metal oxide. However, the results of recent experiments based on UPS and inverse photoemission spectroscopy have implied rather the involvement of the metal oxide conduction band.195,199−205 It was thus of interest to gain a detailed theoretical understanding of the interfacial electronic structure between such metal oxides and organic semiconductors. In this context, we very recently carried out a computational study to examine the interface between a monolayer of 4,4′-N,N′-dicarbazole-biphenyl (CBP) molecules, representing a hole-transport layer, and the molybdenum oxide surface.206 We considered both stoichiometric MoO3(010) and understoichiometric MoOx(010) surfaces; see Figure 9. The understoichiometric surface, formally corresponding to MoO2.94, is modeled by creating an oxygen vacancy at various nonequivalent oxygen sites, labeled terminal (Ot), asymmetric (Oa), and symmetric (Os) sites in Figure 9.206 DFT/PBE calculations on MoO3 result in a band gap of 2.13 eV, which as expected is smaller than the experimental value, by about 0.9 eV.198,207 In the understoichiometric cases, new states appear in the gap, as illustrated by the plots of the densities-of640



Perspective

Figure 9. (a) Bilayer surface structure of MoO3(010) with the three different types of oxygen atoms indicated. (b) MoOx(010) with a terminal Ot vacancy site. Mo atoms are represented in purple and O atoms in red.

states in Figure 10; surfaces with Ot and Oa oxygen vacancies lead to shallow electron donor states right below the CBM (Figure 10b,d) while Os vacancies result in deep donor states (Figure 10c). A combination of these different types of oxygen vacancies would lead to a broad density of states between the Fermi level and the VBM, which is consistent with the gap states observed in UPS experiments.198 Upon adsorption of the CBP monolayer, the density of gap states observed for the bare understoichiometric MoOx surfaces is calculated to be further enhanced by the frontier molecular orbitals associated with the CBP molecules (see Figure 11); this increase in the gap DOS is in excellent agreement with the UPS data.198,206 Importantly, for both stoichiometric and understoichiometric surfaces, our calculations indicate that there occurs partial electron transfer from the CBP molecules to the MoO3/MoOx surface, which leads to an overall alignment of the Fermi level of the complex, the CBP HOMO, and the CBM of the substrate. Such a level alignment leads to a vanishing

Figure 11. Total density of states (a) as well as projections to Mo, O, C, and N atoms (b) of the MoOx(010)−CBP interface. Electron charge densities corresponding to the HOMO aligned with the Fermi level (c) and HOMO-1 (d) of the CBP molecule are displayed.

barrier for hole-extraction or hole-injection for both MoO3 and MoOx surfaces through the bottom of the conduction band, regardless of the presence of gap states, confirming the

Figure 10. Total density of states (black line) as well as projections to Mo (blue line) and O (red line) atoms of (a) the MoO3 surface, (b) the MoOx surface with a terminal oxygen vacancy, (c) the MoOx surface with a symmetric oxygen vacancy, and (d) the MoOx surface with an asymmetric oxygen vacancy. 641



Perspective

reactive force fields that allow the investigation of processes where the bonding can change throughout the course of the simulation, such as in the case of diffusion of organic molecules at the interface with a metal or metal oxide.209−214 For instance, the dynamics of assemblies of organic modifiers such as phosphonic acids on metal-oxide surfaces under different conditions of surface coverage, temperature, and pressure is of considerable interest. Deposition of modifiers on an oxide surface can lead to very different properties depending on the molecular locations on the surface, e.g., whether the molecules form clusters or islands or distribute more or less evenly. Dynamics simulations could also determine the distributions of binding modes (mono-, bi-, or tridentate modes in the case of phosphonic acids) and the possible interconversions among these modes, as well as the distributions in the orientations of the molecules with respect to the surface normal (which defines the z-component of the molecular dipole moment and thus directly impacts the work-function modification). The data from reactive force-field simulations could then inform which quantum-mechanical calculations would be most appropriate. There is also a need to better articulate the correlation between the chemical nature of the surface and the morphology of the organic molecular layer that absorbs on the surface. Indeed, while we have shown above that the presence of dopants or defects near the surface cause a change in the surface electronic structure and work function, it remains to be seen whether the exact locations of these species also influence where the organic molecules absorb and their binding modes. The performance of an organic solar cell is directly related to the efficiency of the electron transfer processes at the organic/ inorganic interfaces. Thus, when going beyond a simple analysis of energy-level alignments, another dynamical aspect of importance is the determination of the rates of electron transfer across these interfaces. This requires using methodologies akin to those exploited in the description of dyesensitized solar cells, where photoinduced electron transfer dynamics from excited states of dye molecules to the conduction band of inorganic semiconductors such as TiO2 are investigated using cluster models of the metal oxide.215−219 Development of methodologies treating the interfacial charge transfer dynamics under periodic boundary conditions could also be of interest.220−226 Finally, we have also expressed in the Computational Methodology Section the limitations related to the use of generalized-gradient approximation (GGA) functionals, which for instance lead to too small energy gaps and make the analysis of energy-level alignments far from being straightforward. The large size of the unit cells that need to be taken into consideration currently makes the use of hybrid functionals already computationally very expensive and simply precludes the use of GW methodologies. In addition, given the intrinsic differences in the electronic structures of organic (πconjugated) molecules and oxide semiconductors, it remains to be established whether the DFT functionals applied to the interfaces between these two types of systems treat both on an equal footing. Thus, it will not come as a surprise at the end of this Perspective that major advances in methods, algorithms, and computer hardware are very much needed!

suitability of MoO3/MoOx as hole-injection/hole-extraction interlayer in organic electronic devices. As a final point worth noting, the partial electron transfer per CBP molecule to the molybdenum oxide surfaces is calculated as 0.39 e/molecule for the MoO3 surface and 0.28 e/molecule for the MoOx surface. The smaller charge transfer in the latter case is attributed to the electron-donor nature of the oxygen vacancy on the MoOx surface, which counteracts the electron transfer from the CBP molecules to the surface. This interfacial charge transfer upon deposition of the CBP monolayer leads to a significant interface dipole, which is the main origin of the calculated work-function decrease by 1.1−1.2 eV; this value is in good agreement with the UPS data pointing to a decrease of work function by 0.7−0.9 eV.198,206

6. OUTLOOK In this Perspective, we have described the results of some of our recent DFT-based electronic-structure calculations on transparent conducting oxide surfaces and their interfaces with chemisorbed or physisorbed organic layers, of relevance to organic electronic applications. We have taken advantage of this discussion to underline the inherent complexity of such interfaces, which is related to a number of factors including the following: the chemical nature and concentration of surface defects, the nature of surface termination, and the mode of binding and coverage density of surface modifiers and physisorbed layers. In spite of this complexity, DFT calculations can provide insight into the extent of charge redistribution and charge transfer taking place at the interfaces, the resulting modifications of the electrode work functions, and (upon careful examination) the trends in the energy-level alignments between the frontier molecular orbitals of the organic layer and the electrode Fermi energy. Much further theoretical work, however, is needed in order to increase our understanding of these systems and provide more quantitative assessments of their electronic properties. A first aspect is that, due to computational constraints, the unit cells under consideration are usually of minimum size and are treated in a static way (i.e., only the stationary configurations lowest in energy are examined in detail). The limitation of the size of the surface unit cell can have severe consequences. For instance, in a recent study of the aluminum/aluminum oxide interface,208 we found that the interface geometric structure generated when using initially a minimum surface unit cell becomes unstable when much larger unit cells are considered: A qualitatively different interfacial structure then emerges. This instability is caused by the fact that the spatial extent of the geometric relaxation involving the formation of the interface is significantly greater than the size of the initial surface unit cell. A static picture of the unit cell can also give a limited understanding of the problem. In general, it is desirable to survey the large number of configurations that are all close in energy, for instance, in relation to diffusion of surface defects or dopants within the oxide layers close to the surface or diffusion of adsorbed molecules on the surface. As dynamics simulations are required to sample all of these configurations, the limitations of quantum methods for large system sizes and time scales become serious. While classical empirical force-field methods can statistically sample appropriate regions of phase space, they generally lack the ability to study chemical reactions or, in general, any system where interatomic bonds are broken and new bonds are formed. A way out can be offered by

■

AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected] (J.-L.B.). 642



Perspective

Notes

(9) Hsu, J. W. P.; Lloyd, M. T. MRS Bull. 2010, 35, 422. (10) Yang, T. B.; Cai, W. Z.; Qin, D. H.; Wang, E. G.; Lan, L. F.; Gong, X.; Peng, J. B.; Cao, Y. J. Phys. Chem. C 2010, 114, 6849. (11) Gershon, T. Mater. Sci. Technol. 2011, 27, 1357. (12) Huang, J.; Yin, Z.; Zheng, Q. Energy Environ. Sci. 2011, 4, 3861. (13) Cui, J.; Huang, Q. L.; Veinot, J. G. C.; Yan, H.; Marks, T. J. Adv. Mater. 2002, 14, 565. (14) Donley, C.; Dunphy, D.; Paine, D.; Carter, C.; Nebesny, K.; Lee, P.; Alloway, D.; Armstrong, N. R. Langmuir 2002, 18, 450. (15) Yan, H.; Lee, P.; Armstrong, N. R.; Graham, A.; Evmenenko, G. A.; Dutta, P.; Marks, T. J. J. Am. Chem. Soc. 2005, 127, 3172. (16) Li, C. N.; Kwong, C. Y.; Djurisic, A. B.; Lai, P. T.; Chui, P. C.; Chan, W. K.; Liu, S. Y. Thin Solid Films 2005, 477, 57. (17) Carter, C.; Brumbach, M.; Donley, C.; Hreha, R. D.; Marder, S. R.; Domercq, B.; Yoo, S.; Kippelen, B.; Armstrong, N. R. J. Phys. Chem. B 2006, 110, 25191. (18) Bermudez, V. M.; Berry, A. D.; Kim, H.; Pique, A. Langmuir 2006, 22, 11113. (19) Hains, A. W.; Liu, J.; Martinson, A. B. F.; Irwin, M. D.; Marks, T. J. Adv. Funct. Mater. 2010, 20, 595. (20) Blöchl, P. E. Phys. Rev. B 1994, 50, 17953. (21) Perdew, J. P.; Burke, K.; Ernzerhof, M. Phys. Rev. Lett. 1996, 77, 3865. (22) Liu, W.; Carrasco, J.; Santra, B.; Michaelides, A.; Scheffler, M.; Tkatchenko, A. Phys. Rev. B 2012, 86, 245405. (23) Mattioli, G.; Filippone, F.; Alippi, P.; Giannozzi, P.; Bonapasta, A. A. J. Mater. Chem. 2012, 22, 440. (24) Toyoda, K.; Hamada, I.; Lee, K.; Yanagisawa, S.; Morikawa, Y. J. Chem. Phys. 2010, 132, 134703. (25) Grimme, S.; Antony, J.; Ehrlich, S.; Krieg, H. J. Chem. Phys. 2010, 132, 154104. (26) Heyd, J.; Scuseria, G. E.; Ernzerhof, M. J. Chem. Phys. 2003, 118, 8207. (27) Heyd, J.; Scuseria, G. E. J. Chem. Phys. 2004, 121, 1187. (28) Heyd, J.; Scuseria, G. E.; Ernzerhof, M. J. Chem. Phys. 2006, 124, 219906. (29) Kresse, G.; Furthmüller, J. Comput. Mater. Sci. 1996, 6, 15. (30) Kresse, G.; Furthmüller, J. Phys. Rev. B 1996, 54, 11169. (31) Campbell, I. H.; Rubin, S.; Zawodzinski, T. A.; Kress, J. D.; Martin, R. L.; Smith, D. L.; Barashkov, N. N.; Ferraris, J. P. Phys. Rev. B 1996, 54, 14321. (32) Heimel, G.; Romaner, L.; Brédas, J. L.; Zojer, E. Phys. Rev. Lett. 2006, 96, 196806. (33) Heimel, G.; Romaner, L.; Brédas, J. L.; Zojer, E. Surf. Sci. 2006, 600, 4548. (34) Heimel, G.; Romaner, L.; Zojer, E.; Brédas, J. L. Acc. Chem. Res. 2008, 41, 721. (35) De Renzi, V.; Rousseau, R.; Marchetto, D.; Biagi, R.; Scandolo, S.; del Pennino, U. Phys. Rev. Lett. 2005, 95, 046804. (36) Li, H.; Paramonov, P.; Brédas, J. L. J. Mater. Chem. 2010, 20, 2630. (37) Wood, C.; Li, H.; Winget, P.; Brédas, J. L. J. Phys. Chem. C 2012, 116, 19125. (38) Cui, J.; Huang, Q. L.; Veinot, J. C. G.; Yan, H.; Wang, Q. W.; Hutchison, G. R.; Richter, A. G.; Evmenenko, G.; Dutta, P.; Marks, T. J. Langmuir 2002, 18, 9958. (39) Huang, Q. L.; Li, J. F.; Evmenenko, G. A.; Dutta, P.; Marks, T. J. Chem. Mater. 2006, 18, 2431. (40) Sharma, A.; Kippelen, B.; Hotchkiss, P. J.; Marder, S. R. Appl. Phys. Lett. 2008, 93, 163308. (41) Bardecker, J. A.; Ma, H.; Kim, T.; Huang, F.; Liu, M. S.; Cheng, Y. J.; Ting, G.; Jen, A. K. Y. Adv. Funct. Mater. 2008, 18, 3964. (42) Hotchkiss, P. J.; Li, H.; Paramonov, P. B.; Paniagua, S. A.; Jones, S. C.; Armstrong, N. R.; Brédas, J. L.; Marder, S. R. Adv. Mater. 2009, 21, 4496. (43) Sharma, A.; Haldi, A.; Hotchkiss, P. J.; Marder, S. R.; Kippelen, B. J. Appl. Phys. 2009, 105, 074511. (44) Sharma, A.; Hotchkiss, P. J.; Marder, S. R.; Kippelen, B. J. Appl. Phys. 2009, 105, 084507.

The authors declare no competing financial interest. † Also affiliated with Department of Chemistry, King Abdulaziz University, Jeddah 21589, Saudi Arabia (J.-L.B.). Biographies Hong Li is a Senior Research Scientist in the School of Chemistry and Biochemistry at the Georgia Institute of Technology. She received her Ph.D. degree in Particle and Statistical Physics from Nankai University of China in 1996. She joined the Bredas research group in 2005. Her present research interests include the investigation of the electronic properties of metal and metal oxide surfaces and their interfaces with organic molecular layers as well as the charge-transfer processes across such interfaces. Paul Winget obtained his Ph.D. from the University of Minnesota in 2001 and completed postdoctoral research at the Universität ErlangenNürnberg and the Environmental Protection Agency. In 2009 he joined the Bredas group at the Georgia Institute of Technology where he is currently a Senior Research Scientist. His present research interests include the structure and reactivity of organic molecules on metal oxide surfaces and luminescent organic and organometallic molecules. Jean-Luc Brédas is Regents’ Professor of Chemistry and Biochemistry and the Vasser-Woolley and Georgia Research Alliance Chair in Molecular Design at Georgia Tech. Since 2000, he has held an Extraordinary Professorship at the University of Mons, Belgium; he has also been Adjunct Professor of Chemistry at King Abdulaziz University in Jeddah since 2011. The research interests of his group focus on the computational characterization and design of novel organic materials of relevance for organic electronics and photonics.

■

ACKNOWLEDGMENTS The present work was supported as part of the Center for Interface Science: Solar Electric Materials (CISSEM), an Energy Frontier Research Center funded by the U.S. Department of Energy, Office of Science, Basic Energy Sciences, under Award Number DE-SC0001084. The authors are most grateful for stimulating discussions with our CISSEM colleagues Neal Armstrong, Steve Barlow, Joseph Berry, Veaceslav Coropceanu, David Ginger, David Ginley, Antoine Kahn, Eung-Gun Kim, Bernard Kippelen, Jingrui Li, Seth Marder, Oliver Monti, Dana Olson, Theodoros Papadopoulos, Jeanne Pemberton, Erin Ratcliff, and Scott Saavedra.

■

REFERENCES

(1) Peiro, A. M.; Ravirajan, P.; Govender, K.; Boyle, D. S.; O’Brien, P.; Bradley, D. D. C.; Nelson, J.; Durrant, J. R. J. Mater. Chem. 2006, 16, 2088. (2) Koster, L. J. A.; van Strien, W. J.; Beek, W. J. E.; Blom, P. W. M. Adv. Funct. Mater. 2007, 17, 1297. (3) Olson, D. C.; Shaheen, S. E.; Collins, R. T.; Ginley, D. S. J. Phys. Chem. C 2007, 111, 16670. (4) Hau, S. K.; Yip, H. L.; Baek, N. S.; Zou, J. Y.; O’Malley, K.; Jen, A. K. Y. Appl. Phys. Lett. 2008, 92, 253301. (5) Olson, D. C.; Lee, Y. J.; White, M. S.; Kopidakis, N.; Shaheen, S. E.; Ginley, D. S.; Voigt, J. A.; Hsu, J. W. P. J. Phys. Chem. C 2008, 112, 9544. (6) Briseno, A. L.; Holcombe, T. W.; Boukai, A. I.; Garnett, E. C.; Shelton, S. W.; Fréchet, J. J. M.; Yang, P. Nano Lett. 2009, 10, 334. (7) Liu, J. P.; Wang, S. S.; Bian, Z. Q.; Shan, M. N.; Huang, C. H. Chem. Phys. Lett. 2009, 470, 103. (8) Cheun, H.; Fuentes-Hernandez, C.; Zhou, Y.; Potscavage, W. J., Jr.; Kim, S.-J.; Shim, J.; Dindar, A.; Kippelen, B. J. Phys. Chem. C 2010, 114, 20713. 643



Perspective

(45) Wang, M. Q.; Hill, I. G. Org. Electron. 2012, 13, 498. (46) Knesting, K. M.; Hotchkiss, P. J.; MacLeod, B. A.; Marder, S. R.; Ginger, D. S. Adv. Mater. 2012, 24, 642. (47) Hotchkiss, P. J.; Jones, S. C.; Paniagua, S. A.; Sharma, A.; Kippelen, B.; Armstrong, N. R.; Marder, S. R. Acc. Chem. Res. 2012, 45, 337. (48) Bulliard, X.; Ihn, S. G.; Yun, S.; Kim, Y.; Choi, D.; Choi, J. Y.; Kim, M.; Sim, M.; Park, J. H.; Choi, W.; Cho, K. Adv. Funct. Mater. 2010, 20, 4381. (49) Beaumont, N.; Hancox, I.; Sullivan, P.; Hatton, R. A.; Jones, T. S. Energy Environ. Sci. 2011, 4, 1708. (50) Kouki, F.; Karsi, N.; Lang, P.; Horowitz, G.; Bouchriha, H. Synth. Met. 2012, 162, 1741. (51) MacLeod, B. A.; Horwitz, N. E.; Ratcliff, E. L.; Jenkins, J. L.; Armstrong, N. R.; Giordano, A. J.; Hotchkiss, P. J.; Marder, S. R.; Campbell, C. T.; Ginger, D. S. J. Phys. Chem. Lett. 2012, 3, 1202. (52) Karsi, N.; Lang, P.; Chehimi, M.; Delamar, M.; Horowitz, G. Langmuir 2006, 22, 3118. (53) Koh, S. E.; McDonald, K. D.; Holt, D. H.; Dulcey, C. S.; Chaney, J. A.; Pehrsson, P. E. Langmuir 2006, 22, 6249. (54) Cerruti, M.; Rhodes, C.; Losego, M.; Efremenko, A.; Maria, J. P.; Fischer, D.; Franzen, S.; Genzer, J. J. Phys. D: Appl. Phys. 2007, 40, 4212. (55) Paniagua, S. A.; Hotchkiss, P. J.; Jones, S. C.; Marder, S. R.; Mudalige, A.; Marrikar, F. S.; Pemberton, J. E.; Armstrong, N. R. J. Phys. Chem. C 2008, 112, 7809. (56) Paramonov, P. B.; Paniagua, S. A.; Hotchkiss, P. J.; Jones, S. C.; Armstrong, N. R.; Marder, S. R.; Brédas, J. L. Chem. Mater. 2008, 20, 5131. (57) Sato, Y.; Tokumaru, R.; Nishimura, E.; Song, P. K.; Shigesato, Y.; Utsumi, K.; Iigusa, H. J. Vac. Sci. Technol. A 2005, 23, 1167. (58) Mei, Z. X.; Wang, Y.; Du, X. L.; Zeng, Z. Q.; Ying, M. J.; Zheng, H.; Jia, J. F.; Xue, Q. K.; Zhang, Z. J. Cryst. Growth 2006, 289, 686. (59) Zhou, Z. B.; Cui, R. Q.; Pang, Q. J.; Wang, Y. D.; Meng, F. Y.; Sun, T. T.; Ding, Z. M.; Yu, X. B. Appl. Surf. Sci. 2001, 172, 245. (60) Gassenbauer, Y.; Klein, A. J. Phys. Chem. B 2006, 110, 4793. (61) Gassenbauer, Y.; Schafranek, R.; Klein, A. Phys. Rev. B 2006, 73, 245312. (62) Harvey, S. P.; Mason, T. O.; Gassenbauer, Y.; Schafranek, R.; Klein, A. J. Phys. D: Appl. Phys. 2006, 39, 3959. (63) Wang, H.; Li, H. Unpublished. (64) Jeon, N. L.; Nuzzo, R. G.; Xia, Y. N.; Mrksich, M.; Whitesides, G. M. Langmuir 1995, 11, 3024. (65) Koide, Y.; Wang, Q. W.; Cui, J.; Benson, D. D.; Marks, T. J. J. Am. Chem. Soc. 2000, 122, 11266. (66) Luscombe, C. K.; Li, H. W.; Huck, W. T. S.; Holmes, A. B. Langmuir 2003, 19, 5273. (67) Ozawa, K.; Hasegawa, T.; Edamoto, K.; Takahashi, K.; Kamada, M. J. Phys. Chem. B 2002, 106, 9380. (68) Thomsen, L.; Watts, B.; Dastoor, P. C. Surf. Interface Anal. 2006, 38, 1139. (69) Zhou, Y. H.; Fuentes-Hernandez, C.; Shim, J.; Meyer, J.; Giordano, A. J.; Li, H.; Winget, P.; Papadopoulos, T.; Cheun, H.; Kim, J.; Fenoll, M.; Dindar, A.; Haske, W.; Najafabadi, E.; Khan, T. M.; Sojoudi, H.; Barlow, S.; Graham, S.; Brédas, J. L.; Marder, S. R.; Kahn, A.; Kippelen, B. Science 2012, 336, 327. (70) Gardner, T. J.; Frisbie, C. D.; Wrighton, M. S. J. Am. Chem. Soc. 1995, 117, 6927. (71) Nüesch, F.; Si-Ahmed, L.; François, B.; Zuppiroli, L. Adv. Mater. 1997, 9, 222. (72) Yip, H. L.; Hau, S. K.; Baek, N. S.; Jen, A. K. Y. Appl. Phys. Lett. 2008, 92, 193313. (73) Moreira, N. H.; da, R. A. L.; Frauenheim, T. Appl. Phys. Lett. 2009, 94, 193109. (74) Tian, X.; Xu, J.; Xie, W. J. Phys. Chem. C 2010, 114, 3973. (75) Chen, L.-M.; Xu, Z.; Hong, Z.; Yang, Y. J. Mater. Chem. 2010, 20, 2575. (76) Domínguez, A.; Moreira, N. H.; Dolgonos, G.; Frauenheim, T.; da Rosa, A. L. J. Phys. Chem. C 2011, 115, 6491.

(77) Hanson, E. L.; Guo, J.; Koch, N.; Schwartz, J.; Bernasek, S. L. J. Am. Chem. Soc. 2005, 127, 10058. (78) Appleyard, S. F. J.; Day, S. R.; Pickford, R. D.; Willis, M. R. J. Mater. Chem. 2000, 10, 169. (79) Pehlke, E.; Scheffler, M. Phys. Rev. Lett. 1993, 71, 2338. (80) Kohler, L.; Kresse, G. Phys. Rev. B 2004, 70, 165405. (81) Hotchkiss, P. J.; Li, H.; Paramonov, P. B.; Paniagua, S. A.; Jones, S. C.; Armstrong, N. R.; Brédas, J. L.; Marder, S. R. Adv. Mater. 2009, 21, 4496. (82) Topping, J. Proc. R. Soc. London, Ser. A 1927, 114, 67. (83) Natan, A.; Zidon, Y.; Shapira, Y.; Kronik, L. Phys. Rev. B 2006, 73, 193310. (84) Rusu, P. C.; Giovannetti, G.; Brocks, G. J. Phys. Chem. C 2007, 111, 14448. (85) Cornil, D.; Olivier, Y.; Geskin, V.; Cornil, J. Adv. Funct. Mater. 2007, 17, 1143. (86) Natan, A.; Kronik, L.; Haick, H.; Tung, R. T. Adv. Mater. 2007, 19, 4103. (87) Romaner, L.; Heimel, G.; Ambrosch-Draxl, C.; Zojer, E. Adv. Funct. Mater. 2008, 18, 3999. (88) Li, H.; Duan, Y. Q.; Paramonov, P.; Coropceanu, V.; Brédas, J. L. J. Electron Spectrosc. Relat. Phenom. 2009, 174, 70. (89) Bolink, H. J.; Coronado, E.; Repetto, D.; Sessolo, M. Appl. Phys. Lett. 2007, 91, 223501. (90) Bolink, H. J.; Coronado, E.; Repetto, D.; Sessolo, M.; Barea, E. M.; Bisquert, J.; Garcia-Belmonte, G.; Prochazka, J.; Kavan, L. Adv. Funct. Mater. 2008, 18, 145. (91) Bolink, H. J.; Coronado, E.; Sessolo, M. Chem. Mater. 2009, 21, 439. (92) Uhlrich, J. J.; Olson, D. C.; Hsu, J. W. P.; Kuech, T. F. J. Vac. Sci. Technol. A 2009, 27, 328. (93) Srikant, V.; Clarke, D. R. J. Appl. Phys. 1998, 83, 5447. (94) Ingham, B.; Illy, B. N.; Toney, M. F.; Howdyshell, M. L.; Ryan, M. P. J. Phys. Chem. C 2008, 112, 14863. (95) Singamaneni, S.; Gupta, M.; Yang, R.; Tomczak, M. M.; Naik, R. R.; Wang, Z. L.; Tsukruk, V. V. ACS Nano 2009, 3, 2593. (96) Premkumar, T.; Zhou, Y. S.; Lu, Y. F.; Baskar, K. ACS Appl. Mater. Interfaces 2010, 2, 2863. (97) Cruickshank, A. C.; Tay, S. E. R.; Illy, B. N.; Da Campo, R.; Schumann, S.; Jones, T. S.; Heutz, S.; McLachlan, M. A.; McComb, D. W.; Riley, D. J.; Ryan, M. P. Chem. Mater. 2011, 23, 3863. (98) Lockett, A. M.; Thomas, P. J.; O’Brien, P. J. Phys. Chem. C 2012, 116, 8089. (99) Kuo, C.-Y.; Ko, R.-M.; Tu, Y.-C.; Lin, Y.-R.; Lin, T.-H.; Wang, S.-J. Cryst. Growth Des. 2012, 12, 3849. (100) Clament Sagaya Selvam, N.; Vijaya, J. J.; Kennedy, L. J. Ind. Eng. Chem. Res. 2012, 51, 16333. (101) Chen, C.; Lan, Y.-T.; Chou, M. M. C.; Hang, D.-R.; Yan, T.; Feng, H.; Lee, C.-Y.; Chang, S.-Y.; Li, C.-A. Cryst. Growth Des. 2012, 12, 6208. (102) Look, D. C.; Hemsky, J. W.; Sizelove, J. R. Phys. Rev. Lett. 1999, 82, 2552. (103) Kohan, A. F.; Ceder, G.; Morgan, D.; Walle, C. G. V. d. Phys. Rev. B 2000, 61, 15019. (104) Oba, F.; Nishitani, S. R.; Isotani, S.; Adachi, H.; Tanaka, I. J. Appl. Phys. 2001, 90, 824. (105) Ozgur, U.; Alivov, Y. I.; Liu, C.; Teke, A.; Reshchikov, M. A.; Dogan, S.; Avrutin, V.; Cho, S. J.; Morkoc, H. J. Appl. Phys. 2005, 98, 041301. (106) Lany, S.; Zunger, A. Phys. Rev. B 2005, 72, 035215. (107) Janotti, A.; Van de Walle, C. G. Appl. Phys. Lett. 2005, 87, 122102. (108) Tuomisto, F.; Saarinen, K.; Look, D. C.; Farlow, G. C. Phys. Rev. B 2005, 72, 085206. (109) Klingshirn, C. ChemPhysChem 2007, 8, 782. (110) Janotti, A.; Van de Walle, C. G. Phys. Rev. B 2007, 76, 165202. (111) Lany, S.; Zunger, A. Phys. Rev. Lett. 2007, 98, 045501. (112) Sokol, A. A.; French, S. A.; Bromley, S. T.; Catlow, C. R. A.; Dam, H. J. J. v.; Sherwood, P. Faraday Discuss. 2007, 134, 267. 644



Perspective

(113) Lany, S.; Zunger, A. Phys. Rev. B 2008, 78, 235104. (114) Oba, F.; Togo, A.; Tanaka, I.; Paier, J.; Kresse, G. Phys. Rev. B 2008, 77, 245202. (115) Huang, G.-Y.; Wang, C.-Y.; Wan, J.-T. Solid State Commun. 2009, 149, 199. (116) Janotti, A.; Van de Walle, C. G. Rep. Prog. Phys. 2009, 72, 126501. (117) Palacios, P.; Sanchez, K.; Wahnon, P. Thin Solid Films 2009, 517, 2448. (118) Lany, S.; Zunger, A. Phys. Rev. B 2010, 81, 113201. (119) Oba, F.; Choi, M.; Togo, A.; Seko, A.; Tanaka, I. J. Phys.: Condens. Matter 2010, 22, 384211. (120) Oba, F.; Choi, M.; Togo, A.; Tanaka, I. Sci. Technol. Adv. Mater. 2011, 12, 034302. (121) Lim, L. Y.; Lany, S.; Chang, Y. J.; Rotenberg, E.; Zunger, A.; Toney, M. F. Phys. Rev. B 2012, 86, 235113. (122) Lee, Y. J.; Sounart, T. L.; Scrymgeour, D. A.; Voigt, J. A.; Hsu, J. W. P. J. Cryst. Growth 2007, 304, 80. (123) Al-Sunaidi, A. A.; Sokol, A. A.; Catlow, C. R. A.; Woodley, S. M. J. Phys. Chem. C 2008, 112, 18860. (124) Goniakowski, J.; Finocchi, F.; Noguera, C. Rep. Prog. Phys. 2008, 71, 016501. (125) Aguilar, C. A.; Haight, R.; Mavrokefalos, A.; Korgel, B. A.; Chen, S. ACS Nano 2009, 3, 3057. (126) Bie, X. F.; Wang, C. Z.; Ehrenberg, H.; Wei, Y. J.; Chen, G.; Meng, X.; Zou, G. T.; Du, F. Solid State Sci. 2010, 12, 1364. (127) Moreira, N. H.; Aradi, B.; da Rosa, A. L.; Frauenheim, T. J. Phys. Chem. C 2010, 114, 18860. (128) Caddeo, C.; Dessì, R.; Melis, C.; Colombo, L.; Mattoni, A. J. Phys. Chem. C 2011, 115, 16833. (129) Caddeo, C.; Malloci, G.; Rignanese, G.-M.; Colombo, L.; Mattoni, A. J. Phys. Chem. C 2012, 116, 8174. (130) Cohn, A. W.; Kittilstved, K. R.; Gamelin, D. R. J. Am. Chem. Soc. 2012, 134, 7937. (131) Teklemichael, S. T.; McCluskey, M. D. J. Phys. Chem. C 2012, 116, 17248. (132) Zhang, L.; Wang, J.-Q.; Li, J.; Zhang, S.; Jiang, Z.; Zhou, J.; Cheng, J.; Hu, T.; Yan, W.; Wei, X.; Wu, Z. Chem. Mater. 2012, 24, 1676. (133) Dorn, R.; Lüth, H.; Büchel, M. Phys. Rev. B 1977, 16, 4675. (134) Duke, C. B.; Meyer, R. J.; Paton, A.; Mark, P. Phys. Rev. B 1978, 18, 4225. (135) Moormann, H.; Kohl, D.; Heiland, G. Surf. Sci. 1979, 80, 261. (136) Göpel, W.; Brillson, L. J.; Brucker, C. F. J. Vac. Sci. Technol. 1980, 17, 894. (137) Moormann, H.; Kohl, D.; Heiland, G. Surf. Sci. 1980, 100, 302. (138) Jacobi, K.; Zwicker, G.; Gutmann, A. Surf. Sci. 1984, 141, 109. (139) Parker, T. M.; Condon, N. G.; Lindsay, R.; Leibsle, F. M.; Thornton, G. Surf. Sci. 1998, 415, L1046. (140) Chen, M.; Wang, X.; Yu, Y. H.; Pei, Z. L.; Bai, X. D.; Sun, C.; Huang, R. F.; Wen, L. S. Appl. Surf. Sci. 2000, 158, 134. (141) Jedrecy, N.; Gallini, S.; Sauvage-Simkin, M.; Pinchaux, R. Surf. Sci. 2000, 460, 136. (142) Dulub, O.; Boatner, L. A.; Diebold, U. Surf. Sci. 2002, 519, 201. (143) Dulub, O.; Diebold, U.; Kresse, G. Phys. Rev. Lett. 2003, 90, 016102. (144) Kresse, G.; Dulub, O.; Diebold, U. Phys. Rev. B 2003, 68, 245409. (145) Meyer, B.; Marx, D. Phys. Rev. B 2003, 67, 035403. (146) Diebold, U.; Koplitz, L. V.; Dulub, O. Appl. Surf. Sci. 2004, 237, 336. (147) Lindsay, R.; Muryn, C. A.; Michelangeli, E.; Thornton, G. Surf. Sci. 2004, 565, L283. (148) Meyer, B. Phys. Rev. B 2004, 69, 045416. (149) Du, M. H.; Zhang, S. B.; Northrup, J. E.; Erwin, S. C. Phys. Rev. B 2008, 78, 155424. (150) Marana, N. L.; Longo, V. M.; Longo, E.; Martins, J. B. L.; Sambrano, J. R. J. Phys. Chem. A 2008, 112, 8958.

(151) Brillson, L. J.; Dong, Y.; Tuomisto, F.; Svensson, B. G.; Kuznetsov, A. Y.; Doutt, D.; Mosbacker, H. L.; Cantwell, G.; Zhang, J.; Song, J. J.; Fang, Z. Q.; Look, D. C. Phys. Status Solidi C 2012, 9, 1566. (152) D’Amico, N. R.; Cantele, G.; Ninno, D. J. Phys. Chem. C 2012, 116, 21391. (153) Gutmann, S.; Conrad, M.; Wolak, M. A.; Beerbom, M. M.; Schlaf, R. J. Appl. Phys. 2012, 111, 123710. (154) Li, H.; Schirra, L. K.; Shim, J.; Cheun, H.; Kippelen, B.; Monti, O. L. A.; Brédas, J. L. Chem. Mater. 2012, 24, 3044. (155) Lavrov, E. V.; Weber, J.; Borrnert, F.; Van de Walle, C. G.; Helbig, R. Phys. Rev. B 2002, 66, 165205. (156) Tuomisto, F.; Ranki, V.; Saarinen, K.; Look, D. C. Phys. Rev. Lett. 2003, 91, 205502. (157) Van de Walle, C. G. Phys. Rev. Lett. 2000, 85, 1012. (158) Zhang, S. B.; Wei, S. H.; Zunger, A. Phys. Rev. B 2001, 63, 075205. (159) Patterson, C. H. Phys. Rev. B 2006, 74, 144432. (160) Clark, S. J.; Robertson, J.; Lany, S.; Zunger, A. Phys. Rev. B 2010, 81, 115311. (161) Fortunato, E.; Ginley, D.; Hosono, H.; Paine, D. C. MRS Bull. 2007, 32, 242. (162) Hiramatsu, M.; Imaeda, K.; Horio, N.; Nawata, M. J. Vac. Sci. Technol. A 1998, 16, 669. (163) Meyer, B. K.; Sann, J.; Hofmann, D. M.; Neumann, C.; Zenner, A. Semicond. Sci. Technol. 2005, 20, S62. (164) Bhosle, V.; Narayan, J. J. Appl. Phys. 2006, 100, 093519. (165) Bhosle, V.; Tiwari, A.; Narayan, J. J. Appl. Phys. 2006, 100, 033713. (166) Dudarev, S. L.; Botton, G. A.; Savrasov, S. Y.; Humphreys, C. J.; Sutton, A. P. Phys. Rev. B 1998, 57, 1505. (167) Walsh, A.; Da Silva, J. L. F.; Yan, Y. F.; Al-Jassim, M. M.; Wei, S. H. Phys. Rev. B 2009, 79, 073105. (168) Triboulet, R.; Perriere, J. Prog. Cryst. Growth Charact. Mater. 2003, 47, 65. (169) Zhang, C. Y.; Li, X. M.; Zhang, X.; Yu, W. D.; Zhao, J. L. J. Cryst. Growth 2006, 290, 67. (170) Zhang, J. P.; He, G.; Zhu, L. Q.; Liu, M.; Pan, S. S.; Zhang, L. D. Appl. Surf. Sci. 2007, 253, 9414. (171) Papadopoulou, E. L.; Varda, M.; Kouroupls-Agalou, K.; Androulidaki, M.; Chikoidze, E.; Galtier, P.; Huyberechts, G.; Aperathitis, E. Thin Solid Films 2008, 516, 8141. (172) Noguera, C. J. Phys.: Condens. Matter 2000, 12, R367. (173) Staemmler, V.; Fink, K.; Meyer, B.; Marx, D.; Kunat, M.; Girol, S. G.; Burghaus, U.; Wöll, C. Phys. Rev. Lett. 2003, 90, 106102. (174) Wöll, C. Prog. Surf. Sci. 2007, 82, 55. (175) Torbrugge, S.; Ostendorf, F.; Reichling, M. J. Phys. Chem. C 2009, 113, 4909. (176) Diebold, U.; Li, S. C.; Schmid, M. Annu. Rev. Phys. Chem. 2010, 61, 129. (177) Lauritsen, J. V.; Reichling, M. J. Phys.: Condens. Matter 2010, 22, 263001. (178) Onsten, A.; Stoltz, D.; Palmgren, P.; Yu, S.; Gothelid, M.; Karlsson, U. O. J. Phys. Chem. C 2010, 114, 11157. (179) Kohl, D.; Moorman, H.; Heiland, G. Surf. Sci. 1978, 73, 160. (180) Sundaram, K. B.; Khan, A. J. Vac. Sci. Technol., A 1997, 15, 428. (181) Alloway, D. M.; Hofmann, M.; Smith, D. L.; Gruhn, N. E.; Graham, A. L.; Colorado, R.; Wysocki, V. H.; Lee, T. R.; Lee, P. A.; Armstrong, N. R. J. Phys. Chem. B 2003, 107, 11690. (182) Peumans, P.; Uchida, S.; Forrest, S. R. Nature 2003, 425, 158. (183) Sharma, A.; Haldi, A.; Potscavage, W. J.; Hotchkiss, P. J.; Marder, S. R.; Kippelen, B. J. Mater. Chem. 2009, 19, 5298. (184) Zhou, Y.; Fuentes-Hernandez, C.; Shim, J.; Meyer, J.; Giordano, A. J.; Li, H.; Winget, P.; Papadopoulos, T.; Cheun, H.; Kim, J.; Fenoll, M.; Dindar, A.; Haske, W.; Najafabadi, E.; Khan, T. M.; Sojoudi, H.; Barlow, S.; Graham, S.; Brédas, J. L.; Marder, S. R.; Kahn, A.; Kippelen, B. Science 2012, 336, 327. (185) Winget, P.; Schirra, L. K.; Cornil, D.; Li, H.; Coropceanu, V.; Ndione, P. F.; Sigdel, A. K.; Ginley, D. S.; Berry, J. J.; Shim, J.; Kim, H.; Kippelen, B.; Monti, O. L. A.; Brédas, J. L. Submitted for publication. 645



Perspective

(186) Anthony, J. E. Chem. Mater. 2010, 23, 583. (187) Hesse, H. C.; Weickert, J.; Hundschell, C.; Feng, X.; Müllen, K.; Nickel, B.; Mozer, A. J.; Schmidt-Mende, L. Adv. Energy Mater. 2011, 1, 861. (188) Sonar, P.; Fong Lim, J. P.; Chan, K. L. Energy Environ. Sci. 2011, 4, 1558. (189) Zahn, D. R. T.; Gavrila, G. N.; Gorgoi, M. Chem. Phys. 2006, 325, 99. (190) Wang, L. A.; Swensen, J. S.; Polikarpov, E.; Matson, D. W.; Bonham, C. C.; Bennett, W.; Gaspar, D. J.; Padmaperuma, A. B. Org. Electron. 2010, 11, 1555. (191) Li, H.; Ratcliff, E. L.; Sigdel, A. K.; Giordano, A. J.; Marder, S. R.; Berry, J. J.; Brédas, J. L. 2013, to be submitted. (192) Ratcliff, E. L.; Sigdel, A. K.; Macech, M. R.; Nebesny, K.; Lee, P. A.; Ginley, D. S.; Armstrong, N. R.; Berry, J. J. Thin Solid Films 2012, 520, 5652. (193) Tokito, S.; Noda, K.; Taga, Y. J. Phys. D: Appl. Phys. 1996, 29, 2750. (194) Frey, G. L.; Reynolds, K. J.; Barker, J. A.; Greenham, N. C.; Friend, R. H. J. Appl. Phys. 2002, 92, 7556. (195) Chu, C. W.; Chen, C. W.; Li, S. H.; Wu, E. H. E.; Yang, Y. Appl. Phys. Lett. 2005, 86, 253503. (196) Meyer, J.; Hamwi, S.; Bulow, T.; Johannes, H. H.; Riedl, T.; Kowalsky, W. Appl. Phys. Lett. 2007, 91, 113506. (197) Chen, L. M.; Hong, Z. R.; Li, G.; Yang, Y. Adv. Mater. 2009, 21, 1434. (198) Meyer, J.; Hamwi, S.; Kröger, M.; Kowalsky, W.; Riedl, T.; Kahn, A. Adv. Mater. 2012, 24, 5408. (199) You, H.; Dai, Y. F.; Zhang, Z. Q.; Ma, D. G. J. Appl. Phys. 2007, 101, 026105. (200) Kröger, M.; Hamwi, S.; Meyer, J.; Riedl, T.; Kowalsky, W.; Kahn, A. Org. Electron. 2009, 10, 932. (201) Subbiah, J.; Sarasqueta, G.; So, F.; Ding, H. J.; Irfan; Gao, Y. L.; Kim, D. Y. Appl. Phys. Lett. 2009, 95, 093304. (202) Park, J. S.; Lee, B. R.; Lee, J. M.; Kim, J.-S.; Kim, S. O.; Song, M. H. Appl. Phys. Lett. 2010, 96, 243306. (203) Kanai, K.; Koizumi, K.; Ouchi, S.; Tsukamoto, Y.; Sakanoue, K.; Ouchi, Y.; Seki, K. Org. Electron. 2010, 11, 188. (204) Meyer, J.; Zilberberg, K.; Riedl, T.; Kahn, A. J. Appl. Phys. 2011, 110, 033710. (205) Greiner, M. T.; Helander, M. G.; Tang, W.-M.; Wang, Z.-B.; Qiu, J.; Lu, Z.-H. Nat. Mater. 2012, 11, 76. (206) Papadopoulos, T. A.; Meyer, J.; Li, H.; Guan, Z.; Kahn, A.; Brédas, J. L. Adv. Funct. Mater. 2013, DOI: 10.1002/adfm.201301466. (207) Meyer, J.; Shu, A.; Kröger, M.; Kahn, A. Appl. Phys. Lett. 2010, 96, 133308. (208) Kim, E.-G.; Brédas, J. L. Org. Electron. 2013, 14, 569. (209) Roy, S.; Asenov, A. Science 2005, 309, 388. (210) Raymand, D.; van Duin, A. C. T.; Baudin, M.; Hermansson, K. Surf. Sci. 2008, 602, 1020. (211) Koizumi, K.; Boero, M.; Shigeta, Y.; Oshiyama, A. Phys. Rev. B 2011, 84, 205203. (212) Russo, M. F., J.r; Li, R.; Mench, M.; van Duin, A. C. T. Int. J. Hydrogen Energy 2011, 36, 5828. (213) Lectez, S.; Roques, J.; Salanne, M.; Simoni, E. J. Chem. Phys. 2012, 137, 154705. (214) Jeon, B.; Ko, C.; van Duin, A. C. T.; Ramanathan, S. Surf. Sci. 2012, 606, 516. (215) Kondov, I.; Thoss, M.; Wang, H. J. Phys. Chem. A 2005, 110, 1364. (216) Persson, P.; Lundqvist, M. J.; Ernstorfer, R.; Goddard, W. A.; Willig, F. J. Chem. Theory Comput. 2006, 2, 441. (217) Kondov, I.; Wang, H.; Thoss, M. Int. J. Quantum Chem. 2006, 106, 1291. (218) Wang, L.; Willig, F.; May, V. J. Chem. Phys. 2007, 126, 134110. (219) Kondov, I.; Č ížek, M.; Benesch, C.; Wang, H.; Thoss, M. J. Phys. Chem. C 2007, 111, 11970. (220) Stier, W.; Prezhdo, O. V. J. Phys. Chem. B 2002, 106, 8047. (221) Rego, L. G. C.; Batista, V. S. J. Am. Chem. Soc. 2003, 125, 7989.

(222) Duncan, W. R.; Prezhdo, O. V. J. Phys. Chem. B 2004, 109, 365. (223) Duncan, W. R.; Stier, W. M.; Prezhdo, O. V. J. Am. Chem. Soc. 2005, 127, 7941. (224) Abuabara, S. G.; Rego, L. G. C.; Batista, V. S. J. Am. Chem. Soc. 2005, 127, 18234. (225) Rego, L. G. C.; Silva, R. d.; Freire, J. A.; Snoeberger, R. C.; Batista, V. S. J. Phys. Chem. C 2009, 114, 1317. (226) da Silva, R.; Rego, L. G. C.; Freire, J. A.; Rodriguez, J.; Laria, D.; Batista, V. S. J. Phys. Chem. C 2010, 114, 19433.

646


Transparent Conducting Oxides of Relevance to ... - ACS Publications

Recommend Documents