Some Properties of (NiO)1-x(Co3O4)x Nano Composite Thin Films Prepared by Chemical Spray Pyrolysis for Photodetector Application

Figure 3. Reflectance spectrum for composite thin films of at varying volumes of (x)

3.1.4 The real and imaginary dielectric constant's

According to the dielectric constant's real (ε1) and imaginary (ε2) components are written as follows [18]:

${{\varepsilon }_{1}}={{\text{n}}^{2}}-{{\text{k}}^{2}}$         (2)

${{\varepsilon }_{2}}=2\text{nk}$                 (3)

where,

(k): is the extinction coefficient and;

(n): is the refractive index.

The imaginary part quantifies the rate of wave dissipation in the medium, whereas the real (ε₁) component is associated with dispersion. Figures 4 and 5 show the real and imaginary dielectric constants. Based on these figures, the values of ε₁ and ε₂ increase with increasing wavelength [19].

Figure 4. The dielectric constant spectrum's real component for composite thin films at varying voltage percentages of (x)

Figure 5. The dielectric constant spectrum's imaginary component for composite thin films at various vol.% of (x)

3.2 Electrical properties

3.2.1 D.C conductivity

The D.C Conductivity (σ_d.c) of the film depends upon several factors such as the preparation method, and the preparation environments. It has been studying the dependence of D.C conductivity (σ_d.c) on different ratio.

In the semiconductor granular borders are of great importance in the mobility of charge carriers because grain boundaries are high-density areas of defects, it's possible to be centers for scattering (scattering centers), centers for capture or trapping centers or centers for the union of charge carriers (recombination centers). In all these cases, the defects and impurities and grain boundaries have a direct impact on the mobility of charge carriers, then on conductivity [20].

Figure 6. The variation of Lnσ with 1000/T for the prepared thin films

Figure 6 shows the variation of Lnσ with inverted absolute temperature 1000/T, the electrical activation energy Ea₁ and Ea₂ for the (NiO)_1-x(Co₃O₄)_x films was calculated. The results of Ea₁ and Ea₂ listed in Table 2 show that the activation energy (Ea₁ and Ea₂) decreases with increasing Co₃O₄ ratios and this corresponds with the results of the optical properties as impurities increase, leading to a decrease in the optical energy gap [21].

The plot displays how the DC conductivity (ln σ) of different compositions of thin films varies with temperature. This relationship helps in determining the activation energy Ea. All curves decrease with increasing 1000/T (i.e., with decreasing temperature), indicating typical semiconducting behavior. Activation energy can be calculated from the slope increasing Co₃O₄ content decreases the conductivity, possibly due to structural changes or increased grain boundary resistance.

3.2.2 Hall effect

The Hall coefficient (RH), carrier concentrations (n), electrical conductivity (σ), and Hall mobility (μH), have been determined in Table 3. Hall coefficient (RH) can be calculated from Eq. (4) [22].

${{\text{R}}_{\text{H}}}=\frac{{{\text{V}}_{\text{H}}}}·{\text{I}}\frac{\text{t}}{\text{B}}$                  (4)

It's important to know the electrical properties. From the measurements we find that the RH value is positive, that means all the films is p-type and the majority charge are holes.

Table 2. DC conductivity and activation energy for the prepared thin films

Table 3. Hall effect characterization for prepared thin films

Table 3 shows that the Hall coefficient decreases with increasing mixing ratios. We also note that conductivity and the concentration of charge carriers increase with increasing impurity ratios. This is attributed to the increased concentration of charge carriers, which leads to a shrinkage of the region between the Fermi level and the conductivity edge. This, in turn, leads to a decrease in activation energy with increasing mixing ratios. The concentration of charge carriers also depends on the crystalline microstructure and surface chemical interactions [23].

3.3 Photodetector

The sensitivity (S) is used to know the increase in the current in a sample under illumination. Conductivity rises when the light is turned on, and after it is turned off, the current returns to its original rate. This process is repeated many times [24, 25].

The current versus time (I-t) graph of the photodetector device is shown in Figures 7-10. Power intensities of 6.17, 5.61, 10.38, and 5.11 mW/cm² were used to evaluate the device at wavelengths of 380, 460, 520, and 620nm. There was no bias voltage applied during these experiments. The device showed outstanding repeatability and stability by maintaining a constant current throughout several cycles. The ratio of the incident optical power at a certain wavelength to the output electrical signal is known as photoresponsivity (R_λ) [26].

${{\text{R}}_{\lambda }}={{\text{I}}_{\text{photo }\!\!~\!\!\text{ }}}/{{\text{P}}_{\text{in }\!\!~\!\!\text{ }}}\text{S}$                  (5)

Iphoto stands for the generated photocurrent, S for the photodetector's active area, and Pin for the intensity of incident light or radiation. The ratio of the number of charge carriers a device produces to the number of phoor η. S is the active region of the photodetector, Pin is the intensity of the incident light or radiation, and Iphoto is the generated photocurrent. External quantum efficiency, or η, is the ratio of the number of charge carriers generated by a device to the number of photons striking it. It sheds light on how well photodetectors transform photons into different types of charge carriers. The phrase describes the percentage of holes or electrons that undergo transformation as a result of photons being stimulated by an energy source. The following equations are used to accomplish the evaluation [27, 28]:

$\text{EQE}\left( \eta  \right)={{\text{I}}_{\text{photo }\!\!~\!\!\text{ }}}/{{\text{P}}_{\text{in }\!\!~\!\!\text{ }}}\text{S}\times \text{hc}/\text{q}\lambda \times 100$%                  (6)

$\text{EQE}\left( \eta  \right)=\text{R}\times \text{hc}/\text{q}\lambda \times 100%$%                            (7)

where, q is the unit of electric charge, c is the velocity of light, and h is the Planck constant. The photosensitivity is calculated by dividing the dark current by the quotient of the current change (ΔI) [29]:

        $\xi ={{I}_{\text{photo }\!\!~\!\!\text{ }}}-{{I}_{\text{dark }\!\!~\!\!\text{ }}}/{{I}_{\text{dark }\!\!~\!\!\text{ }}}$                       (8)

Specific detectivity (D*) of photodetector refers to its capacity to detect low-intensity signals given by [30]:

${{\text{D}}^{*}}=\sqrt{sf}/\text{NEP}$                              (9)

where, f is the bandwidth, the acronym NEP stands for noise equivalent power. It is appraised.

$\text{NEP}={{\text{i}}_{\text{n}}}/\text{R}$                  (10)

where, in represents the dark current noise.

The table above shows the spectral measurements of thin films composed of NiO and Co₃O₄ with different compositions, when exposed to different wavelengths (380, 460, 520, and 620 nm). The table contains several important parameters for evaluating the performance of the films as photodetectors. Interpretation of the results by wavelength.

Figure 7. Photo response time of prepared for composite thin films at wavelength 620 nm (red light)

Figure 8. Photo response time of prepared for composite thin films at 460 nm (blue light)

Figure 9. Photo response time of the prepared for composite thin films at 520 nm (green light)

Figure 10. Photo response time of prepared for composite thin films at 380 nm (U.V light)

Table 4. Spectral measurements for composite thin films measured at (380, 460, 520 and 620) illumination

A-Under UV (380 nm), the highest efficiency (η) = 20.3% was for the 75% NiO - 25% Co₃O₄ sample. The highest spectral response (Rλ) = 6.23 A/W was for the same sample.This indicates that the introduction of 25% Co₃O₄ to NiO significantly improved the photoelectric performance in UV (Table 4).

B-Blue Light (460 nm), we observe that performance improves with increasing Co₃O₄, with the highest Rλ = 3.62 × 10⁻³ A/W and η = 9.77% for the pure Co₃O₄ sample. Co₃O₄ appears to be more suitable for blue light than NiO.

C-Green Light (520 nm), The 75% NiO - 25% Co₃O₄ sample showed the highest response (η = 23.55%, Rλ = 9.88 × 10⁻³ A/W). This indicates that this combination is very effective for green light.

D-Red Light (620 nm), We observe the best performance for the 25% Co₃O₄ - 75% NiO sample (Rλ = 8.74 × 10⁻³ A/W). While pure Co₃O₄ showed a weak response at this wavelength, we conclude that changing the ratio of NiO to Co₃O₄ allows the films to adjust their spectral response, making them suitable for various photodetection applications depending on the target wavelength.

The demonstrated effective charge separation capabilities, responsivity, and sensitivity make this heterostructure an exciting choice for detector applications. These results are promising for the development of next generation optoelectronic de-vices, such as hybrid or dye sensitized solar cells, ultra-violet and visible detectors.