**1. Introduction**

Amongst renewable energy technologies the current trend is technology which aims to optimally utilize clean and sustainable energy sources, based on current and future economic and societal needs. Social and economic development is always followed with an increase in energy demand. Currently, most of the energy demand is fulfilled by nonrenewable fossil fuels, including natural gas, coal, and petroleum. The formation of fossil fuels took hundreds of million years. It is predicted that with the current consumption rate, fossil fuel will deplete in the near future [1,2]. Furthermore, the burning of fossil fuels results in negative environmental impacts, such as global warming, acid rain, climate change, and others. Hence, it is crucial to look for alternative energy resources that are clean and sustainable to replace the non-renewable fossil fuel.

There are a series of studies that have been done in exploring renewable energy technologies, such as solar energy, wind energy, tidal energy, and biofuels [3–8]. Among the available renewable energy, liquid biofuel from biomass resources has received a lot of attention [9–11], especially in the transportation sector, as it offers an opportunity to replace petroleum in operating the combustion engine with little to no modification [12,13]. In fact, over 90% of transportation nowadays is still dependent on non-renewable fossil fuel [14]. Therefore, many works have been done to enhance and improve the biofuel production

**Citation:** Ong, M.Y.; Nomanbhay, S.; Kusumo, F.; Raja Shahruzzaman, R.M.H.; Shamsuddin, A.H. Modeling and Optimization of Microwave-Based Bio-Jet Fuel from Coconut Oil: Investigation of Response Surface Methodology (RSM) and Artificial Neural Network Methodology (ANN). *Energies* **2021**, *14*, 295. https://doi.org/10.3390/ en14020295

Received: 15 December 2020 Accepted: 5 January 2021 Published: 7 January 2021

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technologies, especially biodiesel, a renewable replacement of diesel fuel [15–18]. Nevertheless, there is only a little information about the production of bio-kerosene (bio-jet fuel). Bio-jet fuel is a promising alternative fuel for a jet engine. Other than the aviation sector, bio-jet fuel also can be used in the power generation sector to operate the gas turbine engine. Hence, the bio-jet fuel production technologies should be further explored and investigated in obtaining a comparable renewable replacement for petroleum-based kerosene at sufficient volume.

Based on the statistical report, flights produced 859 Mt of carbon dioxide (CO2) globally in 2017. In the other words, approximately 2% of the CO2 emitted through human activities is contributed by the global aviation sector. In addition, this 859 Mt of CO2 is responsible for 12% of CO2 emission from all transports sources [19,20]. CO2 is one of the greenhouse gases that will trap heat within the Earth's atmosphere, causing global warming and climate change. In order to mitigate the CO2 emissions from air transport and, at the same time, to address the global challenge of climate change, the International Air Transport Association (IATA) has adopted a set of targets and approaches. One of the ambitious targets is to achieve 50% reduction in net aviation carbon emissions by 2050 as compared to 2005, through the deployment of sustainable low-carbon fuels, such as bio-jet fuel [19].

Generally, aviation liquid fuel can be produced from different biomass feedstock with different methods [21–23]. Currently, transesterification and hydrotreating are the main production method of bio-jet fuel [24]. Unlike the hydrotreating process, transesterification requires an upgrading process to separate bio-jet fuel from the product of transesterification (biodiesel). Although an additional downstream process is required, however, the transesterification process operates under milder condition as compared to the hydrotreating process. Hence, its operating cost are relatively lower. The transesterification process involves three consecutive and reversible reactions (refer to Equations (1)–(3)) that react triglyceride with alcohol in the presence or absence of a catalyst and produce a mixture of fatty acid alkyl ester (FAAE or biodiesel) and glycerol as a by-product. In overall, transesterification requires 1 mole of triglyceride and 3 moles of alcohol to produce 3 moles of biodiesel, as shown in Equation (4). However, practically, the excess amount of alcohol is usually used to shift the equilibrium to the product side and allow the phase separation of biodiesel from the glycerol [25].

*Triglyceride* (*oil or f at*) + *ROH* (*alcohol*) ↔ *Diglyceride* + *RCOOR* (1)

*Diglyceride* + *ROH* ↔ *Monoglyceride* + *RCOOR* (2)

$$\text{Monoglyceride} + \text{ROH} \leftrightarrow \text{Glycerol} + \text{R\prime} \text{COOR} \tag{3}$$

#### *Triglyceride* (*oil or f at*) + 3*ROH* (*alcohol*) ↔ *Glycerol* + 3*R COOR* (*FAAE*) (4)

Commonly, methanol is used for biodiesel production via transesterification reactions. This is because methanol is cheaper, allows phase separation to be conducted more easily, and permits the transesterification process to be conducted under milder conditions [26]. However, methanol is very toxic to humans, as in the body methanol is metabolized into formaldehyde and then formic acid. Therefore, there is the scope of using ethanol for producing biodiesel. Ethanol has several advantages to methanol, such as offering better solvent properties and low toxicity relative to methanol [27,28] Furthermore, there is a study reported that the biodiesel formed using ethanol, the fatty acid ethyl ester (FAEE) present a higher cetane number, calorific value, oxidation stability, lubricant characteristics, lower cloud and pour points, and also have lower tailpipe emissions in comparison to the product collected using methanol, fatty acid methyl ester (FAME) [29,30].

In addition, microwave technology is deployed to replace conventional heating in this study. Microwave technology is a green processing method that offers several advantages, such as by being more environmental-friendly, in terms of lower energy consumption. Furthermore, the volumetric heating mechanism of microwave heating also allows rapid heating, enhances chemical reaction rate and selectivity, and improves the production quality and yield [25]. Microwave heating has received a lot of attention since the 1970s, especially in the chemical research. Conventional heating transfers heat into the reactant through the reactant vessel via conduction and convection (wall heating). However, microwave heating is highly dependent on the dielectric properties of the reactant [25,31]. It allows direct heating of the material without heat-up of the reactant vessel [32]. Hence, microwave heating allows selective and rapid heating, as mentioned previously.

Numerous studies have been done on the microwave-assisted transesterification process for biodiesel production [25,33,34]. Compared to other approaches, transesterification is the simplest and a widely-accepted method to reduce oil viscosity because it is costeffective. Therefore, modeling the process and optimizing the process input variables involved are important in order to save time, achieve high product yield and reduce the overall cost to produce biodiesel. Response surface methodology (RSM) and artificial neural network (ANN) are one of the mathematical methods for modeling transesterification processes [35–38]. Some of the advantages that RSM has are the durability under optimal setting conditions and the ability to minimize the number of trials required to provide sufficient evidence for statistically acceptable results [37].

Artificial neural network (ANN) is an information processing system that has characteristics such as biological neural networks that imitates the behaviour and learning process of the human brain. An interesting characteristic of this ANN is its ability to learn (learning and training). The training process at ANN aims to find convergent weights between layers so that the weights obtained to produce the desired output. ANNs are universal approximators and their predictions are based on prior available data, have shown great ability in solving complex nonlinear systems [39].

Ant colony optimization (ACO) is a swarm intelligence technique which is inspired by natural metaphors, namely communication and cooperation between ants to find the shortest path from the nest ants to the food. It is desirable to integrate ACO with ANN model since ACO is capable of optimizing complex process parameters [15,40]. Coupling ACO with the ANN is desirable since the ACO algorithm is capable of optimizing complex process parameters [41].

This study proposed the production of bio-jet fuel through microwave-assisted catalytic transesterification from coconut oil. Coconut oil was selected as the raw feedstock as it consists of a high percentage of medium-chain triglycerides, which made it suitable to be used for bio-jet fuel production [22,42]. An optimization study was conducted in this work based on three parameters, including oil to ethanol molar ratio, reaction time and microwave power, using response surface methodology (RSM) and artificial neural network (ANN) coupled with ant colony optimization (ACO) algorithm. Additionally, the relevant characterizations of coconut oil through the application of gas chromatographicmass spectrometry and Fourier transform infrared spectrometry analyses of the coconut oil, FAEE, and bio-jet fuel were conducted and reported. The physicochemical properties of the bio-jet fuel collected and their comparison with the ASTM standard are also reported in this paper.
