*3.2. Photoluminescent Quantum Yield*

The photoluminescent quantum yield (PLQY) of the CDs was ascertained by Equation (8) as in Section 2.3. Using quinine sulfate added to H2SO4 to form 0.1 M solution, optical density of 0.00, 0.02, 0.04, 0.06, 0.08, 0.1 were obtained; at absorption wavelength of 340 nm and dilution was made from the synthesized carbon dots solution. The procedure, is an established process of calculating quantum yields of photoluminescent substances. Quinine sulphate as reference quantum yield was held at 54.6 [22–26].

**Figure 4.** Experimental factors for 3D surface plots of tapioca powder conversion to fluorescent carbon dots.

#### *3.3. Evaluation Performance between Artificial Neural Network (ANN) and Response Surface Methodology (RSM) on the Yield of Photoluminescent Quantum Yield*

Artificial neural Network (ANN) is a system that mimics the naturally inspired computational model. Thus, it emulates the workings of the human brain to take in certain connections among information inputs and yield outputs through trained data [27–30].

From Table 7 below, it shows the relationship between the response surface methodology and the artificial neural network performance of the trained data (see Figure 5). The best output for photoluminescent quantum yield was obtained at No. 11 at actual experimental value of 27.75%, RSM predicted value of 27.38%, and ANN predicted value of 26.25%. The training of the data set was conducted by Matlab R2015a (8.5.0.197613), utilizing Lavenberg–Marquardt algorithm (LMA). The LMA is based on the training neural network through iteration and reiteration of data set weight and bias values as shown on Table 8 [31–33].


**Table 7.** Response surface methodology and artificial neural network.

Predicted Value = Pred. value, Study Type: Response Surface, Runs: 30, Initial Design: Central Composite, Design Model: Quadratic.

**Figure 5.** Parity plots; (**A**) Response Surface Methodology (RSM) predicted against experimental actual values. (**B**) Artificial Neural Network (ANN) predicted against experimental actual values. (**C**) RSM predicted values against ANN predicted values.

**Table 8.** Artificial neural network (ANN) optimum values for hidden layer sizes and corresponding transfer functions ('tansig' and 'logsig') for minimum error fittings for train, validation, and test of optimized RSM data.


\* 4-8 is the chosen model based on its comparative high R<sup>2</sup> value.

As shown in Figure 5 below, the R<sup>2</sup> value is a good revelation of the compatibility of each data set to each other.

The RSM values shows a high R<sup>2</sup> value of 0.9563 than the ANN R<sup>2</sup> of 0.944 with a negligible residual value of 0.0123 between the RSM and ANN. Hence, the ANN is a very good method of validating RSM data set [21]. The process of validating the Levenberg–Marquardt back propagation model for the response yield of photoluminescent quantum yield adopted in this study were done by deploying different adjustable topologies (see Table 8) in training of the network performance. From the 13 topologies deployed hidden layers between 4 and 20; the best hidden layer configuration with high coefficient of determination and low training error was gained at 4–8, as evident in Figure 6.

**Figure 6.** Artificial neural network model coefficient of determination and error relationship of data set of fluorescent carbon dots. (**a**) Trained R<sup>2</sup> output, (**b**) Validated R<sup>2</sup> output, (**c**) Test R<sup>2</sup> output, and (**d**) Overall R<sup>2</sup> output of data set.

Figure 6 below shows a high value of R<sup>2</sup> ≥ 95 for the output parameter of photoluminescent quantum yield which complies with the expected results from training of data set by the Levenberg–Marquardt algorithm [17,29].

#### *3.4. Characterization and Properties of Carbon Dots*

The need to analyze carbon dots for their characteristic attributes is very essential. These can be done by determining the particle sizes and morphological patterns using high resolution devices [34]. The atomic force microscopy (AFM), high resolution transmission electron microscopy (HrTEM), and field emission scanning emission microscopic (FESEM) techniques have been utilized for this purposes.

3.4.1. Atomic Force Microscopy (AFM) and High Resolution Transmission Electron Microscopy (HrTEM) of Carbon Dots (CDs)

CDs particle size distribution and morphology have been investigated (Figure 7). Figure 7a shows the three dimensional (3D) plot of the morphological pattern of carbon dots while Figure 7b depicts 62 counts of CDs with a mean height and diameter of 4.054 nm and 44.032 nm, respectively, which is a confirmation of the nano-dimension of CDs. Figure 7c represents the histogram of the 62 carbon dots count and Figure 7d is the HrTEM of carbon dots at less than 10 nm and a lattice spacing at 0.24 nm. HrTEM analysis for the carbon dots were investigated to determine the actual size and shape of the carbon dots. The image clearly depicts the synthesized CDs as well dispersed in water with a spherical petal shape and fine size distribution of about 3.0–5.0 nm in diameter shown in Figure 7.

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**Figure 7.** Atomic force microscopy (AFM) and high resolution transmission electron microscopy (HrTEM) of carbon dots (CDs). (**a**) 3D CDs particles, (**b**) 2D CDs particles, (**c**) CDs particle distribution, and (**d**) CDs particle sizes and lattice space.

The HrTEM provides a validation of the nano dimensions present in the synthesized CDs via hydrothermal route which is in agreemen<sup>t</sup> with semiconductors synthesized at the nano scale [35,36].

The CDs lattice spacing of 0.24 nm renders it suitable in membrane filtration application. More so, the sizes of CDs are below 5 nm, which means there are numerous surface sites for adsorption application purposes in wastewater treatment.

In addition, Table 9 shows a detailed presentation of the size distribution of CDs obtained by measuring the heights, areas, and diameters of 62-single carbon dots observed under atomic force microscopy.


**Table 9.** Analysis of the atomic force microscopy of CDs.

As presented on Table 9. The CDs mean diameter of 44.034 nm and mean area of 2086.516 nm<sup>2</sup> possess the attributes of a suitable adsorbent for adsorbing environmental pollutants [13].

3.4.2. Field Emission Scanning Electron Microscopy (FESEM) and EDx of Tapioca-Derived Carbon Dots

From the conducted FESEM analysis, it is found that the actual shape of the CDs is in the form of a flower shaped petals, spherical in nature, as can be seen in Figure 8a,b. The EDX study determined the elemental compositions of carbon dots, and the results shows presence of C (31.64%), 0 (55.84%), Na (10.99%), Si (1.45%), and K (0.079%) as in Figure 8c. The Na signal in EDX spectrum is due to the sodium hydroxide constituent of carbon dots synthesis and silicon is as result of glass substrate for drying carbon dots during the sample preparation for FESEM.

**Figure 8.** FESEM at (**a**) 40 μm (**b**) 10 μm and (**c**) EDx of tapioca-derived carbon dots.

#### 3.4.3. Properties of Carbon Dots (CDs)

The use of UV lamp to assess the quality of fluorescent carbon dots have been applied as a source to obtain a blue/green color in the near visible region of color band group. The UV irradiations absorbed by the carbon dots and excited through absorbing the energy leading to an electron excited state. The molecules of carbon dots with extended Pi-electron provides the basics for the fluorescence emission of carbon dots. The tapioca-derived carbon dot is a wavelength dependent photoluminescent ionic solution in the visible range with a surface abundant with hydroxyl and carboxylic/carboxyl moieties [13].

CDs indicated a strong optical absorption in the UV region (230–340 nm) with a tail extending to the visible range as presented in Figure 9.

**Figure 9.** Optical properties of CDs. (**a**) UV-visible absorption and emission spectra of as prepared CDs dispersed in water. (**b**) Fluorescence emission spectra of carbon dots and reference material (Tapioca).

Absorption shoulders in the spectrum may be due to the π-π\* (pi to pi star transition) of C=C bonds or n-π\* (n to pi star transition) of C=O [37]. The uniqueness of CDs is the photoluminescence emitted by it. Based on past study, it shows the dependency of intensity and wavelength emission towards excitation wavelength [38]. This is due to the different size of particles and surface chemistry and different emissive traps on CDs surface that can be related by the synthesis method.

The wavelength dependence behavior makes CDs possible to be applied in multi-color imaging applications. It has been suggested that there are separate emissions by CDs core and surface states whereby size, surface, and defects are responsible for the emission properties [13]. The color of CDs most of the time is related to the surface groups which compares to particles size and normally CDs show strong photoluminescence from blue to green wavelength. In terms of chemical properties, different synthesis methods of CDs lead to different chemical structure, such as polymer chains, oxygen based and amino-based groups [39].

The main challenge with carbon dots is the agglomeration of the particles due to strong particle interactions. It can be postulated that the agglomeration of particles over time is the very reason that these CDs emit green fluorescence since it had been left for 3 months. The resultant change in colour due to agglomeration of carbon dot particle can be observed in Figure 10 (A and B) [40].

**Figure 10.** Tapioca powder as source of fluorescent carbon dots. (**A**) Carbon dots after synthesis emitting blue fluorescence. (**B**) Carbon dots emitting green fluorescence after 3 months of synthesis.

It is well-known that there is a relationship between emission wavelength of quantum dots and particle size, i.e., the smaller the particle size is, the shorter the emission wavelength [41]. It is reasonable to speculate that this law is also applicable to carbon dots. Strong green photoluminescence offers unique superiority, because most of the current carbon dots emit blue fluorescence under UV irradiation. This kind of carbon dots had been synthesized [42].
