1. Introduction
A photoconductive device is a special type of photodetector that consists of a metal–semiconductor–metal (MSM) structure [
1,
2,
3,
4,
5]. The quantum efficiency
or gain
of a photoconductive device has been observed for over 150 years in a wide variety of materials [
6]; however, the photoconductive gain theory still exhibits considerable controversy and ambiguity in the literature. The quantum efficiency is defined as
, where
and
are the numbers of photogenerated carriers and absorbed photons per unit time, respectively. The gain is also commonly expressed as the ratio of the carrier recombination lifetime
to the carrier transit time
over the conductive channel [
2,
7,
8,
9,
10,
11,
12,
13,
14].
If both electrons and holes are considered,
is then given as [
2,
8,
12,
13].
where
and
are the electron and hole lifetimes, respectively, whilst
and
are their respective transit times from one electrode to another. This simplistic equation implies that
can be increased by increasing
and/or by decreasing
. Since its initial appearance [
11], Equation (1) has been widely used to explain the experimentally observed photoconductive gains for various devices: due to a long recombination lifetime [
8,
12,
13], a short transit time by having a high carrier mobility [
8,
12], by increasing applied voltage [
15], or by shortening channel length of the device [
7,
12,
15]. Additionally, carrier trapping within the photoconductive channel (e.g., on the surface), thought to increase
, is often used as the mechanism for the observed high gain [
8].
However, Equation (1) cannot be derived rigorously from the drift–diffusion equations with photoexcitation that govern the carrier motions. By adopting an ambipolar-transport approximation, approximate analytic solutions of the drift–diffusion equations can be obtained for cases with high background carriers from either doping or thermal excitation [
3,
16]. Furthermore, Equation (1) is obtained under two questionable assumptions: (1) when the detector is uniformly illuminated, the carrier distribution under an applied voltage remains uniform as in the zero bias; (2) all carriers, no matter where they are generated (i.e., at any location relative to the electrodes), contribute equally to the photocurrent. The first assumption is invalid when realistic boundary conditions (BCs), such as vanishing BCs, are applied to the MS contacts in solving the drift–diffusion equations [
3,
5,
16,
17]. More discussion on the BCs is given in the next section. The second assumption would be valid if the current of one carrier type alone could close the circuit without loss (e.g., all electrons exiting the anode return to the conduction band through the cathode). However, this assumption is inconsistent with the definition of primary photoconductivity [
1,
2,
18,
19], where one incident photon can create at most one electron–hole pair. In a steady state, an electron and a hole are needed together to close the circuit. This implicitly assumes that a conduction-band electron exiting from the anode can only return to the photoconductor through the cathode to the valence band, i.e., there is no carrier recycling within the same band. In this case, since electrons generated at a distance away from the collection electrode (i.e., anode) will decay in number while drifting toward the electrode, those generated at different distances from the electrode will contribute differently to the photocurrent. Specifically, for the carriers that either can or cannot reach the electrode, their contributions to the photocurrent are given by the ratio of their travel lengths toward collecting electrode to the channel length of the device [
1,
19,
20,
21].
To further understand the mechanism(s) of the photoconductive gain, we (re)examine a less well-studied case of the photoconductive gain theory of a MSM device, with an intrinsic or undoped semiconductor that has negligible equilibrium carrier densities, allowing for arbitrary drift and diffusion conditions [
1,
16,
17,
19]. On the one hand, this is the case closest to primary photoconductivity, but, perhaps surprisingly, has not been studied in a comprehensive manner. For instance, previous studies often neglected the effect of diffusion [
1,
17,
19,
21]. On the other hand, when diffusion was included, high equilibrium carrier densities were assumed, to adopt an ambipolar approximation [
16]. However, the minimal equilibrium carrier densities have some unique advantages for certain applications. High equilibrium carrier densities lead to a high dark current. Besides the well-known drawbacks such as reduced signal-to-noise ratio, increased power consumption, dynamic range limitation, and cooling requirements, the high dark current also prevents the utilization of some of the unique effects of a photodetector with an exceptionally low dark current, for instance, recently reported optical logic and amplification functions under the illumination of two or more light beams [
22,
23]. For a photoconductive device with minimal equilibrium carrier densities, the key assumption,
, of the ambipolar transport approximation [
24] is invalid, because the distributions of the excess electrons and holes can exhibit significant relative displacement, a polarization effect, under an external field. Thus, the treatment required for the device of interest to this work is distinctly different from the devices with high background carrier densities, because the ambipolar-transport approximation is not applicable for the former case. In fact, the theory for the intrinsic semiconductor with minimal equilibrium carrier densities has a few tricky aspects that have not been properly discussed. It could be viewed as a relaxation semiconductor with a very long dielectric relaxation time [
25].
Furthermore, we note that in the literature, two subtly different
definitions have been used, but without being explicitly distinguished. One definition, which we refer to as apparent quantum efficiency (
), evaluates the photocurrent collected at the anode or cathode that should correspond to what is actually measured experimentally [
19]. The other definition, which we refer to as accumulative quantum efficiency (
), considers all photocurrents that ever flow in the device, regardless of whether they reach the electrodes [
1,
3,
16,
17,
19,
21].
Assuming uniform illumination, uniform electric field, constant carrier lifetime, negligible carrier diffusion and a BC of
, the solution of the drift-only continuity equation for the excess distribution of holes (neglecting the label “p” in the subscripts of the parameters) is given below [
17]
where
is the photogeneration rate of electron–hole pairs,
the drift length or carrier mean free path,
the carrier mobility, and
the applied electric field. By evaluating the drift current at
, where
is the channel length of device, Equation (2) would lead to
, equivalent to
, given below
In the limit of
, one finds
; however, when
,
. Thus, if only the primary conductivity is considered, Equation (1a) appears to be an inappropriately generalized low-drift limit result of Equation (3). On the other hand, the carrier distribution given by Equation (2) can be used to calculate the photocurrent by averaging the carrier density over the channel length [
17,
21]. Based on this consideration,
for one type of carrier (e.g., holes), without considering carrier diffusion, is given below as [
17]
In fact, it can be shown that this spatial averaging scheme is equivalent to evaluate
[
1,
19] (see
Appendix A), which yields the
given by Equation (4). Only in the limiting case of
, one finds
. On the other hand, when
, one has
. Therefore, if only the primary conductivity is considered, Equation (1a) appears to be an inappropriately generalized low-drift limit result of Equation (4). If both types of carriers have the same mobility and lifetime, or a mobility–lifetime product, they will contribute equally to the total
, given as
, which is limited to unity when
. Consequently, Equation (1b) appears to be an inappropriately generalized low conductivity limit result of Equation (4) when both types of carriers are considered.
In this work, we adopt a few common approximations, such as uniform generation of electron–hole pairs, constant electric field, as well as constant carrier mobilities and lifetimes, independent of the electric field, carrier density, and position, as commonly adopted [
1,
16,
17,
19,
21]. By solving the drift–diffusion equations of electrons and holes, under arbitrary conditions of drift and diffusion, we find analytic distributions of excess electrons and holes, as well as photocurrent of an intrinsic photoconductive device with negligible equilibrium carrier densities. We further show that the gain formula given by Equation (1) is the low-drift limit result of the general expression, when the effect of diffusion is neglected. Additionally, we perform numerical simulations to examine the polarization effect, which confirms that the drift field, induced by the displaced electron and hole distributions, does not change the conclusions qualitatively. Our analytical and numerical results, consistent with the conclusion based on the simplified models in the literature [
1,
17,
19,
21,
26], show a unity gain limit within the framework of primary photoconductivity. Finally, we compare the analytic results, using both
definitions, with the results of numerical simulations and discuss the deficiency and consequences of the commonly adopted constant-carrier-lifetime approximation.
2. Analytic Model
Most MSM-type photoconductive devices adopt a lateral structure, where the device is uniformly illuminated from the side, such as those in early literature [
2,
17,
18,
19,
20], as well as in many recent publications using nanowire-type structures [
8,
27,
28]. In this work, we consider lateral photoconductive devices illuminated uniformly from the top.
In a steady state, considering uniform generation, the total electron and hole carrier densities,
and
, respectively, can be obtained by solving the drift–diffusion equations and the associated Poisson’s equation given below [
12,
13,
16]
where
and
are the equilibrium carrier densities,
and
the photogenerated excess carrier densities,
and
the mobilities of electrons and holes,
and
their diffusion coefficients,
the magnitude of the carrier charge,
the Boltzmann’s constant,
the temperature, and
and
the generation and recombination rates of electron–hole pairs, respectively, whilst
and
are the relative dielectric constant of the semiconductor and the permittivity of the vacuum, respectively. For a particular case of interest to this work, we may assume
, and the corresponding photocurrent densities,
and
can be calculated, respectively, as below
If the carrier recombination rates can be described by constant electron and hole lifetimes (
and
, respectively), i.e.,
and
, one can write
and
, where
, whilst
is the equilibrium rate of electron–hole pairs, respectively. Although the constant lifetime approximation has a few drawbacks, as discussed later, this is the only case for which analytic solutions of Equation (5) are obtainable. With this approximation, Equation (5) can be simplified as
where
and
are the drift lengths of electrons and holes, respectively, whilst
and
are the corresponding diffusion lengths. The
term ∝
in the drift–diffusion equation describes a charge polarization effect associated with the relative displacement of the electron and hole distributions induced by the external bias. The relative displacement of the electron and hole distributions leads to a polarization effect that modifies the field within the channel, e.g., screening or weakening the field in the central part of the channel. However, it might enhance the field somewhere closer to the electrodes. It can be seen from Equation (7c) that the impact of the
term is inversely scaled by the square of a normalized Debye length
, where
and
. Qualitatively, for a small
value or a large
, the polarization effect is negligible.
Further, we assume
or the external field being much stronger than this perturbation [
1,
3,
5,
16,
17,
19,
27]. The impact of this assumption is later examined by numerical simulations. Under this approximation, Equation (7a,b) can be solved analytically and separately. However, despite that Equation (7a,b) can be solved independently for different mobilities and lifetimes of electrons and holes, i.e.,
and
, we note that the obtained solutions would be unphysical in two aspects: (1) the photocurrents at the anode (mostly the electron current) and the cathode (mostly the hole current) would be different, which disrupts the basic requirement of the current continuity in the external circuit and (2) the solutions for the carrier densities do not satisfy the overall charge neutrality within the photoconductive channel. These pitfalls have not been noticed previously in the literature. Since our focus is to determine the limiting value of the gain, we, therefore, first adopt additional assumptions of equal mobilities and equal lifetimes of electrons and holes, i.e.,
and
. Because
tends to reduce the gain compared to that with the equal product of the larger one, this additional constraint does not affect the conclusion regarding the maximum gain value. Nevertheless, we later examine effects by removing these assumptions.
Depending on the assumption of the nature of the MS contacts, different BCs have been used in the literature. Solving the drift–diffusion equation typically requires two BCs. Often, the carrier densities at the electrodes are assumed to be equal to the thermal equilibrium values or to be zero [
3,
5,
16,
27]. However, we adopt a different set of BCs by assuming perfect carrier extraction at the electrodes. Mathematically, the carrier extraction by the electrode can be treated as equivalent to the surface recombination at the MS interface, with standard BCs [
29]:
at
and
at
for the electrons (and similarly for the holes), where
is the electrode extraction velocity (resembling the surface recombination velocity). We take the limit of
for perfect extraction. These BCs are appropriate for a Schottky junction, with the metal work function
significantly larger than the semiconductor electron affinity
, i.e.,
, where the electrons encounter a “cliff” at the contacts [
1].
implies that the carrier density goes to zero at the boundary, but the gradient is expected to be finite there. Thus, the solution will be the same as simply applying the vanishing BCs.
The solution of Equation (7b) (neglecting the label “
p” in the subscripts of the parameters) is given below
where
,
,
[
5,
27]. The solution for electrons
can be obtained by substituting
with
in Equation (8). As
, Equation (8) recovers the drift-only result of Equation (2) in
[
17]. Note that
and
depend only on two parameters: normalized drift length
and normalized diffusion length
, when expressed as normalized densities
and
, where
is the normalized coordinate.
Figure 1 plots the normalized carrier density
for
Generally,
is highly nonuniform and asymmetric in the photoconductive channel and it is more symmetric as diffusion becomes more dominant. Evidently, only in the low-drift and low-diffusion case (e.g.,
in
Figure 1a),
(i.e.,
) on the cathode side. This is in stark contrast to the common assumption of
, which leads to highly questionable Equation (1).
After being normalized to the maximum photocurrent
and by introducing normalized coefficients,
and
, the photocurrent density of the holes can be calculated by using Equation (7b) as given below
where
is the drift current with diffusion, whilst
is the diffusion current with drift. As
, it recovers the drift-only result in
:
[
19]. Again, the electron photocurrent density
can be obtained by substituting
with
in Equation (9). Both
and
are, in general, highly nonuniform.
Figure 2 plots
using the same parameters (without
) as in
Figure 1.
Due to the bidirectional nature of the carrier diffusion, a diffusion typically results in reduction in the net photocurrent. As shown in
Figure 2a, with a fixed
while increasing
,
at the anode decreases (becoming more negative), whereas
at the cathode increases. For a small
and large
(e.g.,
and
in
Figure 2a),
is close to being anti-symmetric with respect to the center; thus, the average photocurrent is expected to be small (exactly zero for
), as expected for the diffusion dominating case. However, the diffusion effect is suppressed with increasing drift length
, i.e., for a fixed
,
increases with increasing
from
Figure 2a–d. For a large
and small
(e.g.,
.0 and
in
Figure 2d),
is positive in almost the whole channel and approaches unity at
, as expected for the drift-only case.
The total normalized photocurrent density,
, including the contributions of both electrons and holes, can be calculated as
With the drift term
and the diffusion term
. The photocurrent density,
or
, at the anode or cathode, respectively, represents the actual photocurrent that goes through the external circuit and can be directly measured. A short-circuit condition is implicitly assumed in the calculation. Thus,
or more generally
is expected, as indeed yielded by Equation (10), which further constrains the selection of the BCs at the electrodes.
We then calculate
as given below
where
and
. Note that Equation (10) yields
, as a direct result of adopting vanishing BCs. Thus,
. Although Equation (11) is from the “diffusion part” of Equation (6b) or
in Equation (10), it recovers the result of drift-only current given by Equation (3) when
. When
,
can be expanded to the first order in
When
and
,
, the same as Equation (1a). As
,
, as does Equation (3). By calculating the spatially averaged photocurrent density, we obtain the
for holes:
Note that the spatial average of the “diffusion term” in Equation (6b) is identically zero for any
and
; thus, only the “drift term” contributes to the photocurrent. For
,
becomes Equation (4); when
,
and when
,
. The total
is given by
, which is simply
or
, when
and
. Thus,
also has a unity limit. For a finite
, when
,
can be expanded to the first order in
, yielding:
This result is consistent with [
3], where the zero-field carrier density distribution is used for the calculation. When
and
,
, consistent with Equation (1b).
Figure 3a plots
and
vs.
for
, and
, showing
in general. Both
approach the unity limit as
, which is true even as
, as also shown in
Figure 3a. In the limit of
and
,
, whereas
. Here, a factor of 2 difference is because of
, but
or
and
, whereas both
and
are averaged to
. On the other hand, in the limit of
,
and
, whilst
and
, i.e., at each electrode only one type of carrier contributes to the photocurrent, which contradicts the commonly accepted Equation (1b), where both the electrons and holes contribute to the photocurrent at each electrode. The situation is like the short-circuit current calculation in a solar cell, where only one type of carrier is considered, even though a uniform carrier distribution is assumed [
30]. It can also be seen from
Figure 3a that the diffusion effect, which results in the bidirectional motion of the carriers, tends to reduce the photocurrent, compared to the drift-only case where the carrier motion is unidirectional under the applied field.
Figure 3b–d compare
,
, and
with the spatially averaged value
(equivalent to
) for three representative (
) combinations: low field
, medium field
, and high field
, respectively, and illustrate how each type of carrier contributes to the total photocurrent at different field strengths measured by
. When diffusion is significant, as in
Figure 3b,
and
tend to have opposite signs and partially cancel each other at the electrodes, yielding a smaller net photocurrent. However, when the drift is dominant, as in
Figure 3d, one of
and
diminishes at the respective electrode, yielding a larger net photocurrent, approaching
. Physically, the cancelation of the
and
can be understood as that some electrons reaching the anode may go back to the valence band directly, instead of flowing through the external circuit, which is equivalent to saying that some holes diffuse out from the anode. In the case with diminished diffusion,
, no empty state in the valance band is available for the electrons to fill. Thus, the whole electron current flows through the external circuit and is the total current at the anode.
Interestingly, under the commonly adopted assumption of constant lifetimes, the total photocurrent
is typically nonuniform, as shown in
Figure 3b–d. The spatial modulation is more prominent in the case of low field or a small
as shown in
Figure 3b, but as the applied field increases,
, as shown in
Figure 3d. This spatial nonuniformity of the current is inconsistent with the conventional wisdom that the current should be constant throughout the circuit under continuous and uniform illumination [
31]. However, from Equations (6) and (7), one finds
. The inhomogeneity decreases with increasing
, since the significance of the recombination term diminishes. Fundamentally, this current inhomogeneity is caused by the deficiency of the constant-carrier-lifetime assumption for describing the carrier recombination. More generally, we should expect that
, since in the steady state, condition
is required. This equality is obvious for the inter-band radiative recombination, usually expressed as
, where
is the radiative recombination coefficient. For the recombination through trap states, the Shockley–Read–Hall (SRH) model [
32,
33] automatically ensures equality. If
is enforced in the drift–diffusion equations, we expect the two
definitions to be equivalent. Other non-desirable effects of the constant-carrier-lifetime approximation have also been discussed in the past [
31]. Thus, a more comprehensive model should be developed to eliminate this deficiency, as shown as necessary for other problems [
34,
35]. However, the drift–diffusion equations become nonlinear where analytic solutions are not obtainable and even numerical solutions are much more challenging [
31].
3. Numerical Solutions
To obtain the analytic solutions of drift–diffusion equations, we have assumed . When applying the commonly adopted vanishing BCs within the constant-lifetime approximation, we have further assumed and , to yield physically meaningful results. Here, we use numerical approaches to discuss the impacts of these approximations.
We first address the polarization effect, caused by the relative displacement of the electron and hole distributions, i.e.,
, and induced by the applied field
. The polarization effect is expected to be strong for small
(corresponding to a large
value) and
values. Either a large
or
diminishes the excess carrier densities in the channel, thus, the polarization field. If the total field is written as
, the change in the
field
can be expressed in terms of a potential
through
Besides the
term,
also affects the drift term, changing
to
, where
is the drift length determined solely by
. By defining
with
, one can write
with
. Equation (7) can be then modified as given below
where
and
are, respectively, the drift lengths for electrons and holes determined solely by the external applied field, whilst
or
indicates the absence or presence of the polarization effect, respectively.
Solving the coupled nonlinear equations numerically is challenging for an arbitrarily small
. Here, the goal is to qualitatively understand the potential impact of the polarization effect. For a not-too-small
(e.g.,
), Equation (15) can be solved numerically for
using an iterative method developed in this work. For simplicity, we still adopt
and
, while applying the same BCs:
and
. Explicitly, by setting
, we first obtain the 0-th order carrier concentrations
and
, by solving Equation (15a,b), then use the results in Equation (15c) to solve for the 0-th order potential
; next, using
, and setting
, to solve for
and
. This process is repeated until the results converge (typically within 10 iterations). The photocurrents at
i-th iteration are evaluated as
Figure 4 illustrates the impact of the polarization effect on different quantities, assuming
, (e.g., a possible combination of a moderately high excitation condition:
,
,
and
), for
and
after 10 iterations.
Figure 4a compares
and
, showing that the polarization effect makes the excess carrier distribution more uniform near the central region due to the depolarization field
.
Figure 4b compares
and
, showing reduced current near the central region, while increased toward the two electrodes. Reducing
from 0.5 to 0.1 leads to the stronger polarization effect, but the impact is relatively small: an increase in
from 0.196 to 0.206 and decrease in
from 0.289 to 0.276, as shown in
Figure 4c,d, respectively.
We next examine the possible impacts of non-equality in the mobility-lifetime product of electrons and holes. We assume but and neglect the polarization effect (). For the case of and , the charge neutrality condition is satisfied automatically. However, assuming , solving Equation (7) under the same BCs of would result in and , which violates the current continuity and charge neutrality conditions.
The physical explanation is that when electrons coming out of the anode cannot be accepted by the cathode at the same rate when
, an accumulation of electrons will occur at the boundary with the anode. From
, one can see that if
is satisfied,
will automatically be satisfied as well. Therefore, we need to find
that can satisfy
. One possible solution is to allow
, whilst other BCs are kept unchanged. Although an analytical solution can still be obtained, it is too complex to be shown here. Thus, only numerical results for
are given to illustrate the effects.
Figure 5a,b plot the carrier distributions of the electrons and the hole,
and
, respectively, for two different combinations of
and
.
Figure 5c,d plot
,
, and
, respectively, for the same set of parameters. As expected, with increasing drift and diffusion parameters, both components tend to become linear; thus, the total photocurrent tends to become uniform.
4. Simulation Results
To examine how our analytic model compares to a commonly available device simulator, we perform numerical simulations using “Drift-Diffusion Lab” from nanoHub.org [
36]. Note that this simulation tool also assumes constant carrier lifetimes, but considers other effects, such as the field-dependent mobility, i.e.,
, that is not considered in our model. To make meaningful comparisons, we attempt to identify a material system (namely Ge) together with a set of material parameters that can minimize the additional complications. However, we would like to clarify that although Ge is used as a prototype material, we do not intend to investigate photodetectors based on Ge. To investigate a realistic photodetector, one would need to consider the specific band structure of the material, for instance, the proximity of the indirect and direct conduction-band edges in Ge [
37].
Firstly, by letting
and
, we compare the potential differences in the carrier distributions. Germanium (Ge) is selected as the active material, with the following parameters:
,
,
,
,
, and surface recombination velocity at the electrodes
, the largest allowed value in the simulator. Although
is meant to be the surface recombination velocity, we take it as the carrier extraction velocity that is assumed to be infinity in the analytic model.
Figure 6a plots
and
with
. The simulation results (solid curves) are compared to those obtained from the analytic model (dashed curves). As shown in the figures, for a small applied voltage (e.g.,
V or
), the simulation results are significantly different from those of the analytic model, but the difference diminishes for larger applied voltages (e.g.,
V or
).
Secondly, we examine the effect of polarization on the
J-V characteristics. For the same parameters,
Figure 6b plots the
J-V curves of the simulated results
(black solid curve) and compares them with the analytic results:
(red solid curve) and
(blue solid curve). We find
, but they all approach the unity limit for the strong drift.
Thirdly, we examine the differences in the spatial variation in the photocurrent. By using the simulated carrier densities from
Figure 6a, we calculate the spatial variations in the photocurrents by using Equation (7), in which the electric field
is obtained by integrating Equation (7c), while keeping same voltage difference between the electrodes as the applied voltage. The results are shown in
Figure 6c,d (solid curves), in comparison with the results of the analytic model (dashed curves) for 0.1 V, 1.0 V, and 2.0 V. Due to the singularity in taking a derivative using the numerical data, out of 150 data points, the last 2 data points closest to the respective electrode are found unreliable, and, thus, they have been omitted in the plots. However, the extrapolated values at the electrodes are close to the direct current outputs of the simulations. Thus, the values of the simulation current are used for the end points at
and
. Clearly, the total current remains nonuniform, with a maximum at the center, with comparable modulation amplitudes compared to the analytic results. The ratios between the maximum and minimum points are found to be 1.611, 1.205, and 1.108, from the analytic results, compared to 1.382, 1.099, and 1.050 from the simulation results, for 0.1 V, 1.0 V, and 2.0 V, respectively, and the photocurrents become more uniform under a larger applied electric field. In addition to the systematically larger
compared to that of the analytic model
, the simulated results show upward bending near the end points.
Furthermore, we would like to point out that the differences between analytic and simulation results are not simply due to whether the polarization effect is included or not. In fact, according to our numerical simulation results as described in the previous section, the polarization effect is expected to be minimal for
. However, the simulator considers other effects, such as the carrier density and field dependences of mobility. Therefore, even using the same mobility and lifetime parameters for the electrons and holes, the relationship of
, predicted by the analytic model, is often found invalid for the simulated results. Consequently, we found that the charge neutrality condition, i.e.,
, does not always hold true in the simulated results. However, we have made a concerted effort to identify the parameters, which ensures that the charge neutrality condition in the photoconductive channel is nearly satisfied, as shown in
Figure 6a. Overall, the numerical simulations, which include the polarization effect and beyond, do not result in qualitative differences from the analytic model, but do exhibit significant quantitative differences, particularly for the cases of small
values, for instance, in
Figure 6a,c when