Analysis of photoconductive mechanisms of organic-on-inorganic photodiodes

Author’s Accepted Manuscript Analysis of photoconductive mechanisms of organic-on-inorganic photodiodes R.O. Ocaya, A. Dere, Abdullah G. Al-Sehemi, Ahmed A. Al-Ghamdi, M. Soylu, F. Yakuphanoglu www.elsevier.com/locate/physe

PII: DOI: Reference:

S1386-9477(17)30606-9 http://dx.doi.org/10.1016/j.physe.2017.06.024 PHYSE12846

To appear in: Physica E: Low-dimensional Systems and Nanostructures Received date: 28 April 2017 Accepted date: 22 June 2017 Cite this article as: R.O. Ocaya, A. Dere, Abdullah G. Al-Sehemi, Ahmed A. AlGhamdi, M. Soylu and F. Yakuphanoglu, Analysis of photoconductive mechanisms of organic-on-inorganic photodiodes, Physica E: Low-dimensional Systems and Nanostructures, http://dx.doi.org/10.1016/j.physe.2017.06.024 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting galley proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

Analysis of photoconductive mechanisms of organic-oninorganic photodiodes R.O. Ocayaa, A.Dereb, Abdullah G. Al-Sehemic,d,e, Ahmed A. Al-Ghamdif, M. Soylug*, F. Yakuphanogluh a Department of Physics, University of the Free State, South Africa b Nanoscience and Nanotechnology LAboratory, Firat University, Elazıg, Turkey c Department of Chemistry, Faculty of Science, King Khalid University, Abha 61413, P.O. Box 9004, Saudi Arabia d Research Center for Advanced Materials Science, King Khalid University, Abha 61413, P.O. Box 9004, Saudi Arabia e Unit of Science and Technology, Faculty of Science, King Khalid University, Abha 61413, P.O. Box 9004, Saudi Arabia f Department of Physics, Faculty of Science, King Abdulaziz University, Jeddah, Saudi Arabia g Department of Physics, Faculty of Sciences and Arts, Bingol University, Bingol, Turkey h Department of Physics, Faculty of Sciences, Firat University, 23169 Elazig, Turkey [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] * Corresponding author.

Abstract In this work, it is shown that choosing an organic-on-inorganic Schottky diode for photoconductive sensing by a using a power law exponent (PLE or

determined at a single

bias point is a limited approach. The standard literature approach does not highlight any bias voltage effects on the distribution of interface state density and other operationally important parameters. In this paper we suggest a new empirical method that holistically highlights the variation of

with voltage, irradiance and temperature to reach a more informed choice of

photosensor for real applications. We obtain a simple, plausible relation of the variation of barrier height, Φ, with voltage, irradiance and temperature. The method is evaluated with data collected previously for Schottky diodes of structure Al/p-Si/organic-semiconductor (OSC)/Au, where OSC is Coumarin-doped with graphene oxide (GO), Cobalt Phthacyanine (CoPC) doped with GO or PCBM doped with GO, respectively. The method reproduces published data for the three diodes reported at specific bias and provides for the first time some qualitative evidence of barrier height variation with light intensity, for which a possible physical basis is also given. Typically, Schottky barrier height is characterized using dark current leading to an under reporting of the effect of illumination on barrier height. Finally,

1

since recombination mechanisms are gauged on the basis of the magnitude of PLE, the method facilitates the identification of the recombination mechanism at a given bias. Keywords: Power law exponent, barrier height, Schottky diodes

1. Introduction There is at present significant theoretical and practical interest in photodiodes that are fabricated as hybrid structures of scaffolding organic compounds and inorganic substrates. The authors have previously investigated p-Si Schottky diodes based on graphene oxide (GO) doped organic nanocomposites (ONC) scaffolds of Coumarin, Cobalt phthalocyanine (CoPC), phenyl-C61-butyric acid methyl ester (PCBM) [1-5]. The final device structure and the illumination scheme are shown in Fig. 1. The top/bottom contacts have circular cross section. The illumination is directed into the top layer, which forms a low thickness (transparent) aluminium window. The usefulness of such a device depends on the exact charge carrier transfer mechanism at play and the resultant interlayer carrier mobility, particularly for high frequency applications. Such a device typically exhibits a much greater than unity ideality factor and large series resistance that limits maximum device current. Still, they hold promise for solid-state sensing and photovoltaic applications [6]. In this paper, we suggest a new, ratiometric method of analysis that leads to a more informed choice of photoconductive sensor for real applications by highlighting the linear and nonlinear reverse bias regions of method, a ratiometric treatment of the currents respectively allows a running estimate of

and

variation. In the

due to illuminations

and

over applied reverse bias voltage. In a typical

photodiode characterization the stimulating intensities are varied from about 10

to

100

is

. We show that by taking the maximum spread of intensity the estimate of

reasonably accurate because

and

differ by several orders of magnitude and localized 2

variations of the specific currents over such a spread of intensity are effectively eliminated. In a photovoltaic sensor, bimolecular recombination (BMR) of photo-generated charges can severely limit device efficiency. However, the precise mechanisms at play are not easily quantified using the currently reported methods. Experimental determination of the extent of BMR evaluates the intensity dependence of the photocurrent, with PLEs between 0.5 and 1.0 indicating that a continuous distribution of localized states exists in the mobility gap of composite organic semiconductors [7,8]. Linear photoconductivity versus intensity corresponds to

= 1 and indicates mononuclear recombination, while

= 0.5 suggests BMR.

In organic bulk heterojunctions photo generated excitons dissociate into free carriers at the blend interface causing an increase of quantum efficiency and a reduction of the recombination [8]. In such materials Langevin recombination is usually observed due to charge carriers traveling shorter distances than the Coulomb radius. Another recombination mechanism has been reported, namely nongerminate (or trimolecular) recombination. Although the phenomenon of recombination is well-studied, its precise forms and origins are not yet fully explained. Trimolecular recombination is currently thought to involve a three species polaron i.e. a bound exciton and a charged hole operating in an Auger-like process [8]. Koster et al. [9] reported an improved method to quantify the fraction of bimolecular recombinant charge carriers during device operation. They resolve nonlinear behaviors in the in spite of apparent linearity in the current-intensity behavior, in contrast to conventional analysis. Their approach includes the effect of charge carrier drift and diffusion in addition to BMR and show that the Langevin rate becomes important. However, they limit their analysis to short-circuit current density using photovoltaic mode devices measured in the weak BMR region where

is close to unity and only slowly varies with intensity [9-11]. Motivated by

reducing the typical noise in

values in such measurements, they model the effects of charge

carrier drift and diffusion on the differential current density, with the specific case of annealed

3

samples of P3HT:PCBM electron donor-acceptor composite. Our method suggests that

is

strongly influenced by applied field and doping concentration. Cola and Farella [12] have investigated the effect of optical perturbations on the electric field distribution and photoconductive current in Schottky x-ray detectors. They show that for sufficiently high reverse bias, no gain effects are observable because charge saturation occurs due to the complete collection of photo-generated carriers. Gain occurs because the contact forces the injection of negative secondary charge carriers with respect to photo generated carriers. The absence of other effects such as carrier velocity saturation at high reverse bias carrier injection would produce the expected linear photocurrent response [12]. For the first time, we present a empirically based method that allows rapid characterization of

as a function of bias and

irradiance. The method makes it easier to interpret the possible recombination modes at play through the material photo response. Using simple arguments that are supported by experimental data, we show how the resulting plots readily highlight differences in different bias and material doping. Koster et al [9] have also shown that intensity. A continuous characterization of

at

depends on

with bias is advantageous in the light of reported

empirical measurements on certain organic composites which show that

> 1 are possible.

This suggests that mechanisms other than mononuclear or BMR may be at play. The exact reverse bias at which where threshold voltage depends on the specific organic composite and the extent of doping. This behavior could be explained by the Shockley-Ramo theorem [13,14], where induced electrode current is predominantly due to the instantaneous electrostatic flux terminating at the electrode than the net rate of charge arrival at the electrode. In addition, continuous photo-generation contributes to photocurrent saturation when transit time is shorter than trapping time. However, an imbalance in the electron-hole transport properties leaves a net positive charge in the material near an Ohmic contact. Assuming validity of thermionic emission theory, we obtain an expression barrier height (Φ)

4

variation as a function of voltage, irradiance, ideality factor and temperature. Finally, we evaluate using previously collected data for three graphene oxide (GO) doped Schottky diodes with structure Al/p-Si/ONC:GO/Au, where ONC is nanocomposite comprised of Coumarin, Cobalt Phthacyanine (CoPC) or PCBM, respectively. The results agree with the literature and appear to confirm the suggested effectiveness of the method.

2. Experimental analysis The photocurrent

flowing through a Schottky diode that is suitable for use as a

photoconductive sensor may be expressed in terms of increasing intensity

by the power law

(1) where current

is a scaling current constant [7],

The magnitude of

is a constant, power law exponent (PLE).

highlights the type of recombinative processes that make up the

photocurrent [7, 15-19]. Eq. (1) can be linearized to (2) where

is the gradient of the log-log plot of diode current versus irradiance. The literature

analysis of photodiodes in photoconductive mode requires application of Eq. (2) at a specific bias voltage, which limits the effectiveness because it provides no further information about possible variations of

2.1.

with voltage, illumination and other variables.

Estimation of voltage-dependent PLE

Consider the set of reverse bias I-V data typically represented by

. Typically, the

characterization of photodiodes is done at 10 mW/cm2, 30 mW/cm2, 60 mW/cm2, 80 mW/cm2 and 100 mW/cm2 illumination intensities. In the currents are spread out over several orders of magnitude for a 10-fold increase in irradiance. The data points A and B are applicable to 5

the present analysis, discussed in the text. The irradiance at A and B are

and

respectively. Suppose that at a given bias voltage and given concentration of dopant two experimental points A and B are identifiable with the current-intensity pairs ( (

) and

) as shown in . It follows from the conventional approach that (3)

and (4) The data pairs belong to the same set of curves for which the conventional approach determines the single current scaling constant. Therefore, without loss of generality, the constants

and

Furthermore, setting

can be written in the ratio where

=

where

is constant.

is also constant and then dividing Eq. (4) by Eq. (3) and

taking logarithms ⁄

(5a)

⁄

Fig. 3 shows the typical plots of experimentally obtained current versus illumination data using the conventional approach. The line labelled A is the experimental best line from which is calculated according to Eq. (2). Superimposed on the plot are the pairwise linear fits for adjacent points. For instance, the line (C) joining the points (

) and (

) in Fig. 3

) taken respectively at 30 mW/cm2 and 60 mW/cm2.

refers to the experimental pairs (

Consequently for that specific line, the PLE at arbitrary voltage

according to Eq. (5a)

becomes ⁄

(5b)

⁄

In Fig. 3, consider the line joining the experimental data endpoint pairs ( (

) and

) and its extrapolation (dotted). It is apparent that the line joining the pair is a very

6

close match to the experimental best line, differing in gradient by only 3%, suggesting that the end-points for which the currents differ by higher orders of magnitude (here to a more reliable estimation of

) lead

using Eq. (5). Maximum non-linearity in measurement

theory i.e. in the present illustration occurring in either current or intensity measurement, may be expressed as the greatest deviation from the best line, and is typically not measured at the endpoints of the data set. In Fig. 3, the data point ( sufficiently, which taken with the point ( maximum of 40%. The currents

and

half and order of magnitude i.e.

) expresses non-linearity

) gives an estimate of

that is off by a

for this set differ by a factor of 3 which is only . This further supports the assertion that for the

method to be accurate, both currents and intensities must differ by a substantial order of magnitude or conversely, a prerequisite that is generally met in practically feasible photodiodes. The plots are actual data for the Al/p-Si/Coumarin:GO/Au Schottky diode doped at 0.01 GO. The labels on the points refer to the irradiance at which the data pair of the point is measured. The dotted lines are extrapolations of the line joining the corresponding experimental points. Applying Eq. (2) on the set of five current versus intensity pairs at -3V reverse bias gave

= 1.302. Table 1 summarizes the results of Eq. (5a) on the same data. Using the

method on the endpoint pairs give

=1.318, which differs by only 0.46% with the value

calculated using the conventional method. Table 1 shows that when responses to spread out intensities are considered, then Eq. (5a) is in good agreement with Eq. (2) of the conventional method. The column labeled

lists the percent error difference in

between the two

methods. The new method has no clear precedent in the literature and introduces the advantage of reduced computational complexity. This makes it easier to compute

over a

wider bias. The reduction in complexity can be appreciated by considering a typical characterization with N=250 bias points and P=5 intensities, which generate I=1250 measured 7

currents. A precise knowledge of the PLE value at each bias voltage (N=1) requires linearly regressing of each set of currents and intensities, resulting in a computational complexity i.e.

. By comparison, the new method requires only P=2, hence a much smaller

complexity. Since the data is typically stored in a spreadsheet file, it is much easier to estimate PLE from the set of 2 points for all N data in the spreadsheet, than to linearly fit all P points, without resorting to complicated programming. Fig. 4 shows the plots of PLE versus voltage showing the conventional voltage specific plot alongside the new method. When interpreted in the context of recombination mechanisms, the dotted trace shows three distinct regions in PLE in its variation with bias. Above a bias of about -1.0V, 0.25

0.5. In this region, mononuclear recombination is

likely dominates. Between -2.0V and -1.0V, it can be seen that 0.5 2.0V, it can be seen that

1.0. Below about -

. This data representation could make it easier to deduce the

recombination mechanism for a given device through . The highest ratio produces the closest match to the photosensor equation. The dotted line is in close agreement with

calculated

using the conventional method. The endpoint pairs also match the value of

using the conventional method at -3V

applied bias. The additional information that is apparent in the plot is the onset of rapid fluctuations in

as the magnitude of the applied reverse voltage exceeds about 3V, for

intensity levels with small ratios. Photodiode noise is a collective term for separate independent mechanisms that are additive to the diode. They are thermal (Johnson), shot and flicker (also known as 1/f or contact) noise. The total diode noise current is the root of the sum of the square of each of these noise sources. Shot noise is due to the random current fluctuations through the P-N junction some randomness is unavoidable due to the discreteness of the electron charge carrier. It is well known that flicker noise has a dependence on the actual dc current flowing and is affected by manufacturing peculiarities and interface states

8

present in the device [20]. This observation of

data has not to the best of our knowledge

been reported previously. For instance, the trace labeled A shows a maximum change of 0.61 at a reverse bias of -3.5V from its near constant value of about 1.516 at -4.6V taken for the (

) and (

). The estimate of the change in current producing the observed

could be made by considering the infinitesimals of Eq. (1). In general, given infinitesimal of

Putting

,

for independent variables

and

and

, the

is

and carrying out partial derivatives leads to [

]

(6)

Eq. (6) suggests that the amplitude of the fluctuation depends on the actual current flowing and in the event that the illumination condition is fixed then Eq. (6) reduces to . Alternatively, it may be written in an illumination independent form by replacing using Eq. (2), i.e. ( where

)

(7)

was defined previously as a scaling current for the set of curves. For the set of data

curves given in Fig. 4, the estimated value of (1) is application of

using the intercept of the best line plot of Eq.

A. Hence for the point A in and

gives

at which the current is A or

A,

A. Since the

illumination conditions are fixed, the change in the exponent of the power law in the method is independent of irradiance and depends only on the voltage for the specific current ratio. One possible explanation of this fluctuation is that higher reverse bias influences recombination and interface states density in the nanocomposites leading to spurious recombination and larger noise currents. Fig. 5 shows the generality of the new method, which accurately reproduces the voltage specific results of the conventional method. 9

The data in Figs. 3 and 4 aptly show empirical measurements on actual organic composite semiconductors for which larger than unity PLE values at reverse bias voltages were observed. The unique data presentation of the present method clearly shows the regions for which the response would conform to mononuclear recombination, BMR and electric field dependent effects. It also shows the dependence on composite type and its extent of doping.

2.2.

An analytical simplification of the Schottky equation Here we presume that the barrier height, ideality factor and series resistance have

already been found using standard methods, such as the method of Cheung & Cheung [21,22]. Deviations from the ideal thermionic emission theory of the Schottky diode can be explained on the basis of series resistance. In reverse bias the maximum photocurrent is typically small and its combined contribution to Eq. (8) is

. An inspection of Figure 2, which depicts

actual data from one such device, shows a maximum current of 0.2 mA at -5.0V bias. For the maximum measured series resistance of the device of 750Ω (see Table 2 below), this amounts to

V below -2.0V for this device. The effect of series resistance (

) in the reverse

bias region is small and can be neglected because the device currents are also small. According to thermionic emission (TE) theory [23,24] the current flowing through a rectifying barrier diode as a function of applied bias voltage ( ) and temperature ( ( where

is the electronic charge,

equal to diode and

for p-Si and

Φ

)

[

is device area,

]

is

(8) is the effective Richardson’s constant

is the barrier height [25],

is the ideality factor of the

is Boltzmann constant. Barrier height inhomogeneities and the existence of

interface states give ideality factors greater than unity [16,23]. It is widely reported [15,26] that the barrier height in many heterojunction devices varies as

10

Φ Where

is irradiance and

(9) is the barrier height coefficient of illumination (

)

[1,2,27]. This is an approximation since it excludes any temperature sensitivities of the barrier height and factors due to the important interface chemistry [28-36]. The foregoing method offers a possible simplification of the standard TE model that highlights the role of temperature, applied voltage and non-ideality. The latter two either influence or are influenced by the interface chemistry. Therefore, the method may add insights from the point of view of the experimental characterization of devices intended for photoconductive, rather than photovoltaic, applications. In the suggested approach, suppose that at a given reverse bias voltage

and temperature

and specified irradiance

hold, and we assume that the barrier height

, where TE equations (8) and (9)

and ideality factor

illumination and temperature. The subscript

do actually depend on

denotes the specific point on the I-V

characteristic. Thus for the two points A and B in that have the same and

respectively, the TE equations at applied reverse bias

at irradiances of

are

(

)

(10)

(

)

(11)

and

where

is the diode area,

is the Richardson’s constant and

and

are the ideality

factors measured at points A and B respectively. For the same device, dividing Eq. (10) by Eq. (11) with

for simplicity, and simplifying under the assumption of the validity of

Eq. (1), then ( )

{

[

]}

11

(12)

Taking logarithms of both sides of Eq. (12) and rearranging gives Φ

[

Φ

Eq. (13) shows that the barrier height Φ

]

(13)

calculated at a higher intensity will depend on the

applied voltage, the change in the interface states (expressed in terms of the ideality factors and the voltage), temperature and illumination. The term

is expressed as a ratio of

intensities in Eq. (12) and therefore is constant over temperature at a given value of dark reverse current

is associated with some limiting intensity

are independent of intensity, then (1), it can be seen that

. If the

using Eq. (1) where

and

. In the ratio-based analysis developed from Eq.

is constant and subsequently for all measurements using non-dark

illumination . Eq. (13) then becomes Φ

Φ

(14)

where Φ

Φ

and Φ is the barrier height at intensity

(15)

at which the ideality factor is

conditions the barrier height and ideality factors are respectively Φ

and

. Under dark . To the best

of our knowledge, Eq. (14) and (15) suggest for the first time that at a specific reverse voltage, if the temperature is also kept constant, then the barrier height will be narrowed by a term that involves the logarithm of the incident intensity. The narrowing is expected to increase at even higher temperatures at a given intensity. This result supports the observations of Pitigala et al [30]. For very non-ideal diodes (i.e. larger ) at the typically low bias, the effect of this term is additive albeit small, implying a non-zero contribution of higher bias voltage to interface states. For instance for Al/p-Si/PCBM:GO/Au Schottky diodes doped to

12

0.5GO, it was observed that the ideality factor changed from 13 to 19 over the irradiance change from 10 mW/cm2 to 100 mW/cm2. At a bias of -5V for the device, the bias term in Eq. (14) is approximately 0.12 eV. Such diodes exhibit large deviations from the thermionic emission model, i.e. abnormally low barrier heights and high ideality factors. A number of simulation-based approaches have been reported in the literature to account or correct for the abnormal increase in barrier height and ideality factor due to the spatial distribution of barrier inhomogeneity’s by assuming a Gaussian distribution of the mean of the barrier height ( ̅ ) and the standard deviation (̅ ). While some researchers like Dobrocka & Osvald [31] assume bias independence of these two variables, others like Chand & Kumar [39] assume bias dependence. The barrier height is, however, known to increase with increasing forward bias [40]. Chand & Kumar model the role of bias voltage and ̅

̅

, where ̅

standard deviations and

and

and ̅

in ̅ and ̅ in the form ̅

̅

are the zero bias mean barrier height and mean

their bias voltage coefficients respectively. Eq. (14) and (15)

imply the dependence of barrier height with applied bias and the approach of Chand & Kumar can therefore be followed. The accumulation of localized charges formed at the p-Si the ntype organic material interface leads to an increase in the Fermi level in the n-material and a reduction of the barrier height. The resulting stronger internal field widens the depletion layer and causes greater hole-electron separation and reduced recombination [41]. Organic semiconductors exhibit a large extent of disorder and low density of states. Therefore, both the Fermi level and the Schottky barrier height can be strongly modulated by external electric fields as well as through photoexcitation [42]. The excess electrons and holes generated by photo-excitation split up the Fermi level of the organic semiconductor into quasi-Fermi levels. With respect to the n-material, the dark Fermi level generated excess concentrations

, dark concentration

[23, 24] is given by (

) 13

(16)

and photo-

The corresponding reduction in the Schottky barrier height due to illumination is then (

)

(17)

This last equation does not take into account the effect of an applied field on charges at the interface. The Schottky barrier height is strongly dependent on electric field and is therefore bias-dependent. The dominant mechanism involving the electric field

is image force

lowering, which reduces the barrier height by [43] ( where

)

(18)

is the permittivity of the semiconductor for image force. By solving the Poisson

equation under depletion conditions,

can be expressed in terms of bias

concentration

[24, 43]

and built-in potential {

(

)}

and doping

(19)

For large reverse bias at typical characterization temperatures

and

, hence

(20) estimates the lowering of barrier height by the image-force, where

.

Although the effects of doping concentration and temperature on the band gaps of both n-type and p-type semiconductors have been well studied over the decades, a survey of the current literature reveals that almost no investigations have been done to ascertain the effects of incident light intensity on band gap. Two well-studied band gap effects due to heavy doping are the Burstein-Moss shift (BMS) and band gap narrowing (BN). In BMS, electrons in the lower levels prevent further occupation thereby leaving only higher levels available. The material then behaves as though it has a larger band gap [44]. BN arises from the presence of ionized and the effects of many-body interactions between conduction band carriers and valence band holes. BN has been observed in both n-Si and p-Si that are heavily doped [45, 46]. Pitigala et al [37] have reported the effects of incident light intensity on p-doped low14

barrier heterojunction devices with associated observed band gap reduction at temperatures above 50 K. They acknowledge the absence of similar studies in the literature. Table 2 shows typical results of barrier height, resistance, ideality factor under different conditions of illumination and graphene oxide doping content.

2.3.

Factors limiting the method

The preceding discussion and analysis highlight factors that potentially affect the accuracy. The input of the method is experimental current-intensity data and the presumption is made of measurement calibration, accuracy and precision. These are mostly measurement factors arising from instrumental resolution, non-linearity, instability and drift due to temperature and voltage, and so on. The characterization of the Schottky diodes are mostly done using automated instrumentation, specifically the KEITHLEY 4200 semiconductor characterization system for the I-V curves, and the TM-206 solar power meter for the intensity based measurements. Human error is therefore essentially eliminated. It is shown above how the presence of outlier data, here specifically the datum (

), can potentially affect the

results. However, this is not necessarily a fault with the method since the source of the error is external, and the method does suggest that the specific data points may be outliers. In any event, the use of endpoints appears to consistently reproduce the expected exponent of the power law since measurement instrument accuracy of the current-intensity pairs will affect all pairs equally and tend to cancel out in the final analysis.

3. Conclusions In this paper, we present a new empirical method that extends and simplifies the analysis of Schottky photodiodes that are intended to be used as photoconductive sensors. We start from the commonly used current versus incident intensity power law equation for a Schottky

15

diode operated in the photoconductive mode and deduce a relation that highlights barrier height variation with voltage, irradiance and temperature. The results agree well with published data on three different Schottky diodes consisting of metal-organic semiconductor composites on graphene. The method considers the PLE over the entire bias range, in contrast to the conventional method that only considers one bias point. We highlight for the first time some qualitative evidence of barrier height variation with light intensity and outline a possible physical basis for the behavior. The characterization of barrier height in the literature typically occurs under dark conditions and this may be the primary reason that the preceding effect of illumination on barrier height is under reported. Finally, we show one possible simplification of the thermionic emission equation that highlights the variation of the barrier height with applied voltage, temperature and ideality factor.

Acknowledgments Authors would like to acknowledge the support of the King Khalid University for this research through a grant RCAMS/KKU/002-16 under the (Research Center for Advanced Materials Science) at King Khalid University, Kingdom of Saudi Arabia.

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19

FIGURE CAPTION Fig. 1. A schematic diagram showing structure of the Al/p-Si/ONC:GO/Au Schottky diode.

Fig. 2. Typical I-V curves for the Al/p-Si/Composite/Au Schottky photodiodes studied. Fig. 3. Logarithmic plot of current versus intensity for k = 1 for five data pairs at a specific reverse bias of -3V typically used in PLE characterization of photodiodes. Fig. 4. Plot of

versus applied reverse bias calculated using four intensity ratios.

Fig. 5. Plots of PLE showing the conventional voltage specific plot alongside the new method, a) Conventional approach at -5V reverse bias – Coumarin b) This method – Coumarin c) Conventional approach at -10V reverse bias – CoPC d) New method – CoPC. e) Conventional approach at -5V reverse bias – PCBM f) New method – PCBM.

ILLUMINATION

TOP Al LUMO

ONC:GO (see text)

LUMO

EF

EF

p-Si HOMO

Au BOTTOM

Fig. 1.

20

HOMO

Fig. 2.

Fig. 3.

21

Fig. 4.

a)

b)

c)

d)

22

e)

f)

Fig. 5a-f.

Table 1. Calculated PLE using both conventional and new methods applied to the Au/pSi/Coumarin:GO/Al Schottky diode with 0.01GO concentration. The values are specified at -3V. Dataset

Power law exponent,

(%)

P30/P10

1.578

21.2

P60/P30

0.788

-39.5

P100/P10

1.318

0.46

Table 2. Al/p-Si/PCBM:GO/Au diode parameters using the dV/d(LnI) and H(I) current-voltage methods. 0.1GO

0.3GO

I-V Intensity 2 (mW/cm )

0.5GO

I-V

n

Rs (Ω)

Φ (eV)

n

Dark

9.75

369

0.760

10

10.25

313

30

9.86

60

I-V Rs (Ω)

Φ (eV)

n

Rs (Ω)

Φ (eV)

10.03

632

0.768

10.93

670

0.772

0.751

14.79

393

0.675

12.57

743

0.729

345

0.756

12.65

582

0.696

18.33

543

0.658

9.95

336

0.752

12.60

597

0.712

15.30

662

0.685

80

9.42

370

0.759

14.20

472

0.680

20.74

448

0.637

100

9.90

381

0.739

19.23

287

0.633

18.91

476

0.650

Highlights 23

    

New empirical method that highlights PLE over wider bias Improves PLE characterization of photoconductive sensor Reproduces published diode data Method is holistic and empirically based Evidences barrier height variation intensity



Highlights variation of

with bias and illumination

24