Relation of defects and grain boundaries to transport and photo-transport: Solved and unsolved problems in microcrystalline silicon

Journal of Non-Crystalline Solids 358 (2012) 1946–1953

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Relation of defects and grain boundaries to transport and photo-transport: Solved and unsolved problems in microcrystalline silicon Jan Kočka ⁎ Institute of Physics, Academy of Sciences of the Czech Republic, v.v.i., Cukrovarnická 10, 160 00 Prague 6, Czech Republic

a r t i c l e

i n f o

Article history: Received 12 September 2011 Available online 24 October 2011 Keywords: Density of states; Micro-crystalline silicon; Transport

a b s t r a c t Defects and grain boundaries play a crucial role in the dark and photo-transport of charge carriers. Surprisingly, the transport (trapping and recombination) in microcrystalline silicon is better understood at low temperatures, while room-temperature operation is of interest for real-life devices. In the first part of this review, the advantages of photo-transport techniques, used for the defect density evaluation, will be recapitulated and commented on. The second part is devoted to the present understanding of the specific features of transport in microcrystalline silicon like anisotropy, dominant transport path and the role of H and O in the grain boundary formation. The results of macroscopic measurements on series of samples will be confronted with the results of local conductivity studies on a nanometer scale and finally, the influence of oxygen and the ability to explain it by our model of transport will be illustrated. © 2011 Elsevier B.V. All rights reserved.

1. Introduction Amorphous hydrogenated silicon (a-Si:H) [1] has been one of the most intensely studied amorphous semiconductors for last few decades (see for example Ref. [2,3]), namely due to many exciting practical applications like photovoltaic (PV) solar cells, field effect (FET) transistors and flat panel displays, to name just a few. Recently, new class of materials, called nano- or micro-crystalline silicon (μc-Si: H), gained importance [4] due to the fact that these materials do not suffer from light-induced degradation [5]. Disorder is a characteristic feature of all amorphous semiconductors, with a lot of consequences, for which the theoretical basis has been formulated by N.F. Mott [6]. Direct consequence of disorder is the formation of localized (defect) states within the so-called “mobility gap” [7]. An additional characteristic feature of μc-Si:H is the existence of grains and grain boundaries. Defects and grain boundaries play a crucial role in the dark and photo-transport of charged carriers, important for most of the practical applications. Surprisingly, the transport (trapping and recombination) in a-Si:H and μc-Si:H is better understood at low temperatures [8,9], while room-temperature operation is of interest for real-life devices. In order to photogenerate the carriers, a photon has to be absorbed first. The actual understanding of the optical absorption formed the necessary basis for the progress in the field of amorphous semiconductors. In the pioneering paper by Tauc, Grigorovici and

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Vancu [10] authors posed a question—what are the differences between the crystalline and amorphous state of elemental semiconductor like Ge? In this paper [10] the formula for absorption coefficient (α) in amorphous semiconductors, without long-range order, has been derived: 2

αð ω Þ≈ðh ω − E g Þ ; where Eg is the optical gap, often called the “Tauc” gap. In another paper [11] the characteristic features of absorption coefficient of amorphous semiconductors have been summarized. In the first part of this review, photo-transport techniques, often used for the low α region and consequently defect density evaluation, will be recapitulated and commented on, first for a-Si:H and then also for μc-Si:H. The important “reference point” for these techniques is the carrier transport path. The second part of this review is devoted to the present understanding of the specific features of transport in microcrystalline silicon like anisotropy, dominant transport path and the role of H and O in the grain boundary formation. The results of the macroscopic measurements on series of samples will be confronted with the results of local conductivity studies on a nanometer scale and finally, the influence of the oxygen and the ability to explain it by our model of transport will be illustrated on 3 series of samples. 2. Photo-transport techniques, used for α(E) and defect density evaluation In Fig. 1 the 3 characteristic regions for absorption coefficient (α) of amorphous semiconductors [11] are illustrated. Part C, high α

J. Kočka / Journal of Non-Crystalline Solids 358 (2012) 1946–1953

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equilibrium and, moreover, the phase signal can be used to check whether the lifetime is really constant, as assumed. In a later paper we have suggested the so-called “Absolute” (A)-CPM [16](see top part of Fig. 2 for its experimental arrangement). A-CPM allows one to get from one set-up the α(E) in the absolute units(see Fig. 2—bottom part) without the need to move the sample and to do a separate measurement of transmission, which is necessary for Standard (S)-CPM. Moreover, the measured curve in A-CPM is almost free from interference fringes, the averaging of which for S-CPM is, mainly for very thin samples, rather difficult. 2.1. Amorphous silicon (a-Si:H)

Fig. 1. Characteristic regions of absorption coefficient (α) in amorphous semiconductors. See text. Reproduced with permission from Ref. [11].

region, is described by above mentioned Tauc formula, part B (“Urbach” edge) is exponentially decreasing and low α region A, which is controlled by defect absorption, is of the highest importance for material optimization. While for amorphous, so-called chalcogenide glasses, often prepared with a few millimeter thickness, it was relatively easy to measure absorption even for the low α part by traditional transmittance techniques, for the few micrometer thin films of amorphous Ge or Si the traditional techniques often failed. The great advantage of the photoconductivity related techniques, which are used to complement the direct optical absorption measurements in the low absorption region (α below ≈10 3 cm −1 down to ≈10 −1 cm −1), is their sensitivity. The photoconductivity can be expressed as: σ ph ð EÞ ¼ e⋅I0 ð EÞ⋅½ 1−R ð EÞ  ½ 1− exp ð−α ð EÞ⋅ d Þ ⋅ τ ð EÞμ ð EÞ

The measurement of α(E) is usually not the final target, it is the tool how to deduce the defect-related DOS (density of states). We have basically three possibilities. We can use [17] the deconvolution of the optical spectra α(E) or the “integrated excess absorption” approach or the absorption coefficient at a single, appropriately selected energy. All of these different procedures need some assumptions and/or calibration (usually by ESR—electron spin resonance [18]). It is important to know which transitions we observe with the used experimental method. Here it is the right place to remember that there is another unique technique, so called PDS (photothermal deflection spectroscopy) [19], based on a different principle, not related to photoconductivity. The PDS advantage is that all processes are detected and so PDS gives absolute absorption values and it was also used instead of transmission to put standard CPM into absolute scale. The negative side of this overall sensitivity of PDS is that it is sometimes difficult, namely for thin samples, to exclude the influence of the substrate. Moreover, the need to immerse the sample into a liquid deflection medium is another complicating factor [19]. CPM measures only transitions contributing to the photocurrent. When the coplanar geometry of (ohmic) contacts is used, the so-called “secondary photocurrent” is measured and we detect only transitions leading to majority photocarriers (electrons in undoped a-Si:H, see Fig. 3, transitions a) and d)). This and other assumptions

where I 0 ð E Þ−light intensity; R ð E Þ−reflectivity;α ð E Þ−abs : coef:; d− thickness;τðEÞ−lifetime; μ ðEÞ−mobility: For weak absorption and constant mobility αd b b 1, μ(E) ≈ μ0 we can write: σ ph ð E Þ ≈I 0 ð E Þ⋅½1−R ð E Þ⋅ α ð E Þ⋅τ ð E Þ: For known reflectivity when we change I 0 ð E Þto keepσ ph ¼ constant; τðEÞ is ð≈Þ stabilized and we can write: αðEÞ≈

1 I0 ðEÞ

This is the basic trick of the constant photocurrent method (CPM) [12]on how to overcome the fact that generally, with the change of E and Io(E) the lifetime can change, too. The introduction of CPM started the discussion about regions in which the assumptions may be violated (temperature and/or type of samples [13]), also the discussion whether d.c. or a.c. CPM is better, has continued [14]. However, due to its relative simplicity and reliability the CPM [12,15] has been widely used for the characterization and optimization of a-Si:H. We prefer the a.c. mode because in this case, due to very sensitive lock-in detection, low light intensity can be used, the small quasi-Fermi level splitting causes only a small deviation from the thermal

Fig. 2. Upper part: experimental set-up for Absolute (A)-CPM. Bottom part: resulting absorption coefficient (α) for a-Si:H sample in absolute units, measured by (A)-CPM (solid line), compared with the results deduced from standard (S)-CPM (circles) and transmission data (diamonds). For details see text. Reproduced with permission from Ref. [16].

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Fig. 3. Schematic illustration of possible optical (line with the arrow) and thermal (wave with the arrow) transitions in undoped a-Si:H [15].

allowed us to do a simple deconvolution [12,15] and present one of the first DOS pictures, based later(see Fig. 4) on the idea of dangling bond “intimate pairs” for doped a-Si:H [20]. The idea to use the absorption coefficient at a single, appropriately selected energy, say α(1.2 eV), for the estimate of the number of defects in a-Si:H, instead of a complicated deconvolution, is very attractive [17]. To substantiate it a careful calibration by other techniques is needed. The calibration has been done in Ref. [17] and within a factor of 2 it has been concluded that in a-Si:H α(1.2 eV) = 1 cm−1 is equivalent to 2.4–5.1016 cm−3 defects. The fact that many different techniques have been compared to give the reasonable average also indicates that, at least in undoped “device-grade” a-Si:H, the dominant deep defect is the Si dangling bond (Si-db), as generally agreed. As concerns the light-induced defects [5] it has been evident for a long time that hydrogen plays some role. Recently it has been demonstrated [8] that nearby “paired H” seems to be the stabilizing factor in a process of the formation of the additional Si-dbs. 2.2. Microcrystalline silicon (μc-Si:H) For μc-Si:H the situation is much more complicated, although many properties are similar to a-Si:H. The first complication is due to the heterogeneity of μc-Si:H, leading to strong scattering of light. Fortunately the complete theory has been developed [21,22], which allows the determination of the “true” α(E) from the measured CPM, known electrode spacing and RMS roughness(see also Fig. 5) [23]. An alternative, extremely simplified solution how to minimize the effect of light scattering has been demonstrated for μc-Si:H, the so-called 2-point CPM, leading to “Quality factor” Q = α(1.4 eV)/ α(1.0 eV) [24]. Recently the so-called Fourier transform photocurrent spectroscopy (FTPS), has been suggested [25] as the best method for μc-Si:H layers or solar cells [26]. Its large dynamic range is illustrated in Fig. 6; however, the main advantage of this technique is the speed

Fig. 4. The DOS (density of states) found by deconvolution of absorption coefficient α(E), measured by CPM, for differently doped a-Si:H. For details, see text [20]. Reproduced with permission from Ref. [20].

Fig. 5. Apparent optical absorption coefficients of the μc-Si:H sample measured by CPM from the film side with the different inter-electrode spacing and calculated from T/R measurements. Evaluated spectral dependence of the true absorption coefficient α(E) is shown as the main result by solid line; α(E) of c-Si is shown for the comparison. See text. Reproduced with permission from Ref. [23].

of the measurement (about 100× higher than for CPM), allowing one to do the DOS mapping on large area solar cells. The cost for speed is, however, the loss of the physical simplicity, characteristic for CPM, for comparison see [27]. Measurement of the density of defects directly on devices is very important; however, the specific features of junction techniques have to be taken into account. First of all contrary to the secondary photocurrent (with dominant transitions, leading to the photogeneration of majority carriers), in a primary photocurrent (reverse biased p-i-n junction for example) the situation is different. Both electron and hole transitions contribute. But, as it was illustrated for a-Si:H in a fundamental paper by Okamoto et al. [28], the different transitions can be distinguished by a phase shift, and the results finally lead to the similar DOS picture as from CPM. As for (junction) capacitance based techniques like deep level transient spectroscopy (DLTS) or transient photocapacitance (TPC) [29], their advantage is the selectivity, signal sign indicating different transitions, as has been convincingly demonstrated recently also for μc-Si:H [29]. Many experimental results, namely based on ESR [30,31], indicate that also in μc-Si:H the Si-db is the dominant deep defect; however, there is growing evidence that in μc-Si:H there is “something else”

Fig. 6. Normalized FTPS spectrum of μc-Si:H, measured without Si filter (open circles) and with Si filter (full diamonds). CPM spectrum (crosses) is shown for comparison. See text. Reproduced with permission from Ref. [25].

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[30–32]. Two kinds of Si-dbs with different g-factors have been discovered [30,31] and as one of the few DOS pictures for μc-Si:H at least schematic DOS picture has been presented [31](see Fig. 7). Unfortunately in μc-Si:H the situation is still far from clear to allow to draw the commonly accepted picture of the DOS. An attempt to find “calibration constant” also for μc-Si:H [32] remains unsolved. One of the reasons is that μc-Si:H is actually a wide class of materials with very different crystallinities and microstructures. Moreover, one of the unsolved problems is how to include into the DOS picture(see Fig. 7) the tissue where most of defects are concentrated [30] and the mobility gap of which is larger than the gap of Si crystallites. For μc-Si:H we need the coordinated comparison and/or combination of the different techniques on well characterized μc-Si:H sample series (like it has been done for a-Si:H). For example the combination of CPM with the ESR, the measurement of the spectrally resolved spin dependent photocurrent, as has been done for a-Si:H [18]. 3. The specific features of transport in μc-Si:H 3.1. Anisotropy and superlattices Having the cross-TEM image of μc-Si:H [33] in mind, it is clear that anisotropy has to be assumed and checked. For the test of the transport anisotropy we have to measure transport in directions parallel (() and perpendicular (/) to the substrate [34]. For parallel direction coplanar contacts are used, contact barriers can usually be neglected and the room temperature d.c. conductivity σ(()dc can be deduced. The sandwich geometry is used in perpendicular direction; the a.c. conductivity has to be used to exclude the influence of the contact barriers to get the “true” conductivity σ(/)ac[34]. The technique suitable for the evaluation of the diffusion length in the parallel direction is the SSPG (steady state photocarrier grating), for perpendicular direction it is the SPV (surface photo voltage)(see Ref. [35]). Comparable values of both σ(()dc and σ(/)ac indicate isotropy, as for example observed for fine grained μc-Si:H without the large columns, whenever the large columns are observed, there is a difference between σ(()dc and σ(/)ac[34]. Similar behavior has been observed for superlattices [35], whenever the growth of the large columns has been interrupted by a-Si:H interlayers, not only the conductivity but also the diffusion length were isotropic, although changing with the crystallinity. Only for μc-Si:H with “100% crystallinity” clear anisotropy and large columnar structure are observed(see Fig. 8)[35].

Fig. 8. (a) Room temperature values of the dark DC and AC conductivities and (b) the diffusion lengths (L) deduced from SSPG and SPV [35] as a function of the projected μc portion (horizontal axis) for the superlattices(see text and Ref. [35]).

of the existence of the small GBs is the formation of localized tail states. We have studied the transition from a-Si:H to μc-Si:H on many series of thin silicon films [34,37,38]. The changes of the room temperature dark coplanar conductivity as a function of the crystallinity upon crossing the a-Si:H/μc-Si:H transition are illustrated in Fig. 9 for several of our thin film Si series [39]. Different effective medium models, with different mixing rules, may be used. Neither the Maxwell Garnett approximation [40] nor the Bruggeman approximations [41] represent suitable description. The Wood–Ashcroft formula [42]—the approximation with the partial correlation of the components, represents the best fit. The main message from Fig. 9 is that the random mixture of amorphous and crystalline components (Bruggeman approximation) does not fit either the 3-dimentional or

3.2. Transport path and model of transport It is commonly observed and generally accepted that μc-Si:H is usually composed of two kinds of grains [34,36], the small crystalline Si grains (with the characteristic size 10–30 nm) and large grains (100–500 nm) in a form of the aggregates from the small grains (often in a form of columns). For the charge transport the grain boundaries (GB) are important. What do we know about them? The 10–30 nm typical size of the small grains is not sufficient for the formation of the space-charge regions and potential barriers, which could block the charge transport. Thus, the main consequence

Fig. 7. Qualitative density of states (DOS) diagram for paramagnetic states detected in doped and undoped μc-Si:H by ESR [31]. Note two types of dangling bonds (dbs). Reproduced with permission from Ref. [31].

Fig. 9. Dark conductivity versus crystallinity for a large number of samples from several series crossing the amorphous/microcrystalline silicon boundary [39]. Lines show the transition as predicted by the mixing rules of several EMAs (effective medium approximations), as schematically illustrated on the top: random mixture of the two components for Bruggeman theory (BR) [41] in 2D or 3D, correlated Maxwell–Garnett(MG) [40] or partially correlated Wood–Ashcroft (WA) [42] mixing rule.

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the 2-dimensional predicted percolation thresholds (33% and 50%) and that the grains, in our case the “large grains (LG),” have to be coated by a resistive layer—we call it large grain boundary (LGB). We prefer the term “LG” over the “columns,” because for example in superlattices we have LGs which are not columnar [35]. By comparison of AFM topography and dark conductivity (its prefactor σ0 and activation energy Ea) on many series of thin Si film samples [34,37,38], we have found the empirical rule that whenever the prefactor σ0 ≤ 100 Ω −1 cm −1 and the activation energy Ea ≤ 0.5 eV are detected, the LGBs are formed. A typical example of such changes is given in Fig. 10 for the thickness series [38]. The basic idea of our model of transport in μc-Si:H(see Fig. 11) is that LGBs consist of the modified a-Si:H into which most of the defects, H and possibly O atoms, concentrate [31,43], increasing the mobility gap of LGBs. The role of H in the formation of the tissue is crucial; increase of the mobility gap with increasing H content is well known in the field of a-Si:H. Oxygen can also increase the gap of the tissue (forming a-Si:H:O alloy); moreover, incorporation of O is often accompanied by defect formation [44–46], increasing the probability of hopping through the LGBs. The role of O is much more complex(for further discussion see below, Section 5). To explain the features shown in Fig. 10 we have used the DOS for the components present in the films and the transport path within the DOS, as illustrated in Fig. 11. The scheme on the left shows the commonly accepted DOS for a-Si:H, corresponding to the initial stage of growth. The DOS for the isolated LG of μc-Si:H in the center of Fig. 11 also shows the tail states due to the GB of the small grains. These two images are aligned according to the conduction band offset less or around 0.1 eV and the valence band edge offset around 0.2–0.6 eV, corresponding to the mobility gap of μc-Si:H fluctuating in the range 1.5–1.1 eV for different microstructures [47–49]. As we move from a-Si:H to a mixed material, the presence of small grains or isolated large grains and their smaller band gap represents the reason why the Fermi level (EF) increases, leading to the decrease of Ea seen in Fig. 10 for thicknesses smaller than 0.6 μm. At the same time, no changes are observed in the conductivity prefactor, which is an important confirmation that the transport path for electrons stays at the conduction band mobility edge. Finally, the scheme on the right part of Fig. 11 shows the μc-Si:H with the densely packed LG, connected by LGB. The drop of σ0 ≤ 100 Ω −1 cm −1and activation energy Ea ≤ 0.5 eV indicate the down shift of the electron transport path (see the right scheme in Fig. 11), which now takes place through the LG and by hopping or tunneling through the tail states of LGBs as a new transport channel. We have, however, never said that the conduction path is

Fig. 10. The dark conductivity prefactor σ0 (right axis) and activation energy Ea (left axis) for the thickness series of thin Si samples [34]. The full (red) line with the arrows marks the values of our empirical rule for detection of the presence of large grain boundaries (LGB).

Fig. 11. Schematic illustration of the components present in the undoped mixed-phase silicon films. The components are present in various concentrations at different film crystallinity, increasing from left to right (for example with the increasing thickness, see Fig. 10). Localized densities of states (DOS) are schematically marked and the transport paths through the transport-limiting step are marked by arrows [38].

fully and only through the LGB or a-Si:H tissue (see dashed line in Fig. 12b), as stated in Ref. [50]. The LGBs should be seen rather as the transport-limiting step on the path, labeled by solid curve in Fig. 12a), which determines the resulting thermal behavior of the conductivity. Here we have to mention that there is a well-known phenomenon, the so-called Meyer–Neldel rule (MNR) [51], which relates different parameters of the thermally activated processes in many areas of physics and chemistry, including the prefactor σ0 and the activation energy Ea of a-Si:H dark conductivity, as summarized for example in [52]. Successful application and clear interpretation of the MNR for a-Si:H (statistical shift of the Fermi level) have been based on the good knowledge of the DOS and the “structural invariance” of a-Si:H. After the first attempt to apply MNR to doped μc-Si:H [53] recently a detailed study has been presented for “100% crystalline” μc-Si:H [54]. However, because our and many other samples, used for example for μc-Si:H solar cells, represent the real “mixed-phase” material with crystallinity around 50% (for which the detail quantitative DOS model is missing), we intentionally do not interpret the MNR and use in our model of transport actually only one point of the MNR plot (σ0 ≤ 100 Ω−1 cm−1and Ea ≤ 0.5 eV) as an indicator of the LGs and LGBs formation. 4. Local conductivity studies on a nanometer scale How the study of the local conductivities, measured on the nm scale with the help of atomic force microscopy (AFM) can help us? In one of our thin Si film sample series we have observed [37,55] that for a sample prepared at Ts = 35 °C, conductivity has been very low (10 −11 Ω −1 cm −1), while crystallinity was still about 50%. The AFM local conductivity map(see Fig. 13[55]), measured in parallel with the topography for samples prepared at Ts = 200, 65 and 35 °C,

Fig. 12. Schematic picture of the different possible transport routes (see text and Ref. [38]).

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Fig. 13. (b) The UHV-AFM topography combined with the map of local currents (c) for 3 thin silicon samples deposited at 54 MHz, high dilution (rH = 134) and substrate temperatures Ts = 200 °C, 65 °C and 35 °C [55].

clearly explains it. While for Ts = 200 °C there is a lot of conductive (white) crystallites, for Ts = 65 °C more dark (low conductivity) regions appeared and at Ts = 35 °C most Si crystallites are surrounded by low conductivity a-Si:H tissue. The opposite conclusion [50] that the tissue and LGBs are conductive and dominate the transport (following the path b)(see dashed line in Fig. 12), was rather surprising and based on the observation of conductive rings at the grain boundaries [50]. This stimulated us to repeat the experiments and we have discovered that we also see the “conductive rings” at the grain boundaries, but only when we apply relatively large voltage (about +10 V, as in Ref. [50], see Fig. 14b), while when negative or small positive voltage is applied, we observe the usual maps of the conductive crystalline grains in the non-conductive a-Si:H tissue (see Fig. 14a). It has been demonstrated that the conductive rings are related to local anodic oxidation (LAO) [56]. The conductive rings disappeared by HF etching (see Fig. 14c) and during the measurements in vacuum the conductive rings have not been formed even for large positive voltage (see Fig. 14d).

Actually the current at GBs is smaller after LAO than before LAO; however, the drop of the current in the middle of the grains is much larger than at GBs(see Fig. 15) so that the conductive rings at the GBs are artificially emphasized. It is known that oxidation of a-Si:H is slower than for crystalline Si; the same can be expected for a-Si:H based tissue. The conductive GBs cannot be excluded for example in nanocrystalline diamond, formed by sp2 graphitic form [57], or in the specific case of local defective (and/or doped) GBs in a sandwich geometry [58], but we do not think that LGBs represent the dominant transport path in μc-Si:H, namely in coplanar geometry. 5. Role of the oxygen The problems with the local anodic oxidation have been discussed in the previous paragraph. Clear correlation between the H stretching modes and the post-deposition oxidation with the efficiency of μc-Si:H solar cells has been demonstrated [59]. On the other hand oxygen incorporation markedly improved μc-Si1 − xGex:H solar cells [60]. These are just a few reasons for asking what the role of oxygen and

Fig. 14. Local current maps measured with the Conductive (C)-AFM on μc-Si:H sample: (a) with the non-oxidizing small negative voltage [conductive (white) crystalline Si grains are observed in non-conductive a-Si:H based tissue] [39] and (b) with the high positive, about + 10 V (oxidizing) voltage. The “conductive rings” at the grain boundaries are formed(see text and Ref. [56]). The conductive rings disappeared by HF etching (c) and during the measurements in vacuum the conductive rings have not been formed even for large positive voltage (d).

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Fig. 15. Current profiles measured with the Conductive (C)-AFM on one of the μc-Si:H grains first with the non-oxidizing small negative voltage and then with the high positive (oxidizing) voltage(see text and Ref. [56]).

its relation to transport in μc-Si:H is. Is the main role of O the formation of donors in Si crystallites, widening of the mobility gap of a-Si: H:O tissue in LGBs or the passivation of defects (dangling bonds), in analogy with H? The recent study of a-Si:Ox:H alloys [44] clearly indicated that the crystallinity decreases with the addition of O. It can be used as an argument supporting our opinion that O is predominantly built-in into the amorphous tissue. Moreover, the correlation between the number of defects and O content [44,46] or O/H ratio [45] has been found. The role of O is also influenced by the way how O is incorporated, during the deposition or by intake after deposition. To test the role of oxygen we have prepared and studied three dilution series of samples [61]. For the first series, prepared at Ts = 250 °C and 55 W VHF power there is the a-Si:H/μc-Si:H transition at the dilution rH = 12.5. At this transition the evaluated prefactor σ0 and activation energy Ea crossed our empirical rule; the columns (LG and LGBs) are formed. Few percent intake of oxygen is observed on the μc side of the series. All above mentioned results (see Ref. [61]) are relatively characteristic and often observed in μc-Si:H. For the second, “high power” series (Ts = 250 °C and 110 W VHF power) the a-Si:H/μc-Si:H transition decreased below rH ≤ 10; all prepared samples are highly crystalline and conductive. The evaluated prefactor σ0 and activation energy Ea are just above or around the values, given by our empirical rule(see Fig. 16) so the clear typical large grains are not formed. At the same time the observed high content of O, without formation of the LGB, can be explained by the large

Fig. 16. Upper part: dark conductivity prefactor σ0 (full squares) and activation energy Ea (open circles) for the sample, prepared at Ts = 250 °C and 110 W, as a function of the working gas dilution rH[61]. The dashed line marks the critical values of the prefactor and Ea, crossing of which indicate the presence of the large grain boundaries(see text). Lines are guides to the eye. Bottom part: the hydrogen (full circles) and oxygen (open circles) content for the same sample as in the upper part. The gray (yellow in color version) bands mark the transition region from amorphous to microcrystalline growth [61].

volume of the tissue, which can absorb oxygen. What is also interesting is the anti-correlated concentration of the O and H. The value of Ea around 0.5 eV clearly indicates that O is not predominantly forming donors in Si crystallites (for which much lower Ea is expected). For the third (low Ts = 80 °C) series(see Fig. 17) the prefactor (σ0) and activation energy (Ea) crossed the critical values of our rule at the transition, the LGs (columns) are formed. However, also before the transition, where the samples are fully amorphous, there is a drop of σ0 and it correlates with the oxygen content. In our recent paper [61] we have suggested “the inhomogeneous distribution of O in a-Si:H and the O-induced long-range band gap fluctuations” as a solution. To test this idea and to distinguish the origin of O (built-in during the deposition or intake after preparation) we have prepared a new sample at Ts = 80 °C, 55 W and rH = 15,6 and studied carefully the time evolution of the conductivity prefactor and O content(see Fig. 18). The results clearly illustrate that the drop of the prefactor (σ0) is due to the intake of O after the preparation. Having in mind another recent observation – the columnar nature of some of a-Si:H samples, prepared at Ts ≤ 100 °C [62](see Fig. 19) – the most probable explanation of the prefactor (σ0) drop and the O intake after the preparation of this sample (prepared at Ts = 80 °C, 55 W and rH = 15,6) is the fact that “columnar a-Si:H” can be permeable for impurities. This is an important warning for those who use low Ts for example for the deposition of solar cells on plastic substrates. 6. Conclusions Although even a-Si:H (prepared at low Ts) can surprise us, it is, with the exception of light-induced degradation, a reasonably understood and industrially matured material. The μc-Si:H is in many aspects similar to a-Si:H but the detailed quantitative, generally accepted DOS picture is missing. We need coordinated comparison and/or a combination of different techniques on well characterized sample series (like for a-Si:H). Local conductivity measurements are very perspective for the detailed understanding of the transport and function of devices, but at the same time care has to be taken to exclude possible artifacts. The role of impurities like oxygen is of fundamental importance; correlation of the nanostructure and the number of defects with the type of bonding (forming alloy or donor states) is very important.

Fig. 17. Upper part: dark conductivity prefactor σ0 (full squares) and activation energy Ea (open circles) for the sample, prepared at Ts = 80 °C and 55 W, as a function of the working gas dilution rH[61]. The dashed line marks the critical values of the prefactor and Ea, crossing of which indicate the presence of the large grain boundaries(see text). Lines are guides to the eye. Bottom part: the oxygen content (open squares) for the same sample as in the upper part. The gray (yellow in color version) bands mark the transition region from amorphous to microcrystalline growth [61].

J. Kočka / Journal of Non-Crystalline Solids 358 (2012) 1946–1953

Fig. 18. Time evolution of the oxygen content (CO) and conductivity prefactor (σ0) after the preparation of a-Si:H sample at Ts = 80 °C, 55 W and rH = 15.6 (see text).

Fig. 19. Cross-sectional TEM (X-TEM) of a-Si:H sample, prepared at rH = 40 and substrate temperature Ts = 40 °C [62] with evident columnar structure(see text).

Acknowledgements This work has been supported by the Ministry of Education, Youth and Sports of the Czech Republic (projects LC510, LC06040) and the Institutional Research PlanAV0Z 10100521 of the Academy of Sciences of the Czech Republic. The author is grateful to many colleagues and friends for contributions to this research. In particular, the author would like to thank for a long fruitful collaboration to M. Vaněček, J. Stuchlík, A. Poruba, A. Fejfar and E. Šípek. References [1] W.E. Spear, P.G. LeComber, Solid State Commun. 17 (1975) 1193. [2] R.A. Street, Hydrogenated Amorphous Silicon, Cambridge University, 1991. [3] R.A. Street (Ed.), Technology and Applications of Amorphous Silicon, Springer, Heidelberg, 2000. [4] J. Meier, R. Fluckiger, H. Keppner, A. Shah, Appl. Phys. Lett. 65 (1994) 860. [5] D. Staebler, C.R. Wronski, Appl. Phys. Lett. 31 (1977) 292. [6] N.F. Mott, Adv. Phys. 16 (1967) 49. [7] M.H. Cohen, H. Fritzsche, S.R. Ovshinsky, Phys. Rev. Lett. 22 (1969) 1063. [8] P.C. Taylor, J. Non-Cryst. Solids 352 (2006) 839. [9] W. Fuhs, J. Non-Cryst. Solids 354 (2008) 2067.

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