
==== Front
Heliyon
Heliyon
Heliyon
2405-8440
Elsevier

S2405-8440(24)13149-0
10.1016/j.heliyon.2024.e37118
e37118
Research Article
Development of Free Fatty Acid (FFA) monitoring device for evaluation of oil samples used for biodiesel production
Jayaprabakar J. jp21tn@gmail.com
a⁎⁎
Dawn S.S. dawnsudha@yahoo.com
bc
Anish M. anish.mech@sathyabama.ac.in
a
Giri Jayant jayantpgiri@gmail.com
de⁎
Sudhakar K. sudhakar@rmkcet.ac.in
f
Alarfaj Abdullah A. aalarfajj@ksu.edu.sa
g
Guru Ajay ajayguru.sdc@saveetha.com
h
a Department of Mechanical Engineering, Sathyabama Institute of Science & Technology, Chennai, India
b Centre of Excellence for Energy Research, Sathyabama Institute of Science & Technology, Chennai, India
c Centre for Waste Management, Sathyabama Institute of Science & Technology, Chennai, India
d Department of Mechanical Engineering, Yeshwantrao Chavan College of Engineering, Nagpur, India
e Department of VLSI Microelectronics, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences (SIMATS), Saveetha University, Chennai, 602105, TN, India
f Department of Chemistry, RMK College of Engineering and Technology, Puduvoyal, India
g Department of Botany and Microbiology, College of Science, King Saud University, P. O. Box.2455, Riyadh, 11451, Saudi Arabia
h Department of Cariology, Saveetha Dental College and Hospitals, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, 600077, India
⁎ Corresponding author. Department of Mechanical Engineering, Yeshwantrao Chavan College of Engineering, Nagpur, India. jayantpgiri@gmail.com
⁎⁎ Corresponding author. jp21tn@gmail.com
31 8 2024
15 9 2024
31 8 2024
10 17 e3711821 3 2024
20 7 2024
27 8 2024
© 2024 The Author(s)
2024
https://creativecommons.org/licenses/by-nc/4.0/ This is an open access article under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Diversion of oil sources for biodiesel production has been gaining importance to meet the environmental concerns and energy demand. The free fatty acid (FFA) content of the feedstock is a significant factor in biodiesel production. The FFA values determine the complexity of the biodiesel production. Until date, an experimental procedure has been used to determine the FFA concentration of an oil source; this method is dependent on titration, which is a laborious process involving significant volumes of chemicals. Hence, in the present study, an attempt was made to develop a device for the identification of FFA of the oils. Waste cooking oil samples subjected to wide range of cooking conditions like cooking time, temperature, type of food are collected from different food outlets. Subsequently, the composition of oil samples and the variation in their quality were analysed using gas chromatography flame ionization detector (GC – FID). Biodiesel is prepared from the oil samples through transesterification and the impact of FFA and their respective methyl esters in the quality and properties have been investigated. The properties of biodiesel were determined as per ASTM standards. The study was further extended to correlate the properties of biodiesel with the composition of the oil from which it was derived. The analysis evidently proved the dependence of biodiesel properties on the FFA percentage and the composition of the oil. The results have been further substantiated with the performance and emission characteristics of internal combustion engine fuelled with the prepared biodiesel samples.

Keywords

FFA
biodiesel
Transesterification
UV spectroscopy
GC-FID
Sensor
Arduino
==== Body
pmc NOMENCLATURE

GC	Gas Chromatography	
FID	Flame ionization detector	
WCO	Waste cooking oil	
WCOBD	Waste cooking oil biodiesel	
HC	Hydrocarbons	
NOx	Nitrogen oxides	
BTE	Brake Thermal Efficiency	
SFC	Specific fuel consumption	
FFA	Free fatty acid	
FAME	Fatty acid methyl ester	
CO	Carbon monoxide	
CO2	Carbon di oxide	
UV	Ultra violet	
ASTM	American standards for testing and materials	

1 Introduction

Fossil fuel energy has been a major source of power for the world since the 1700s, fuelling industrial production, automobiles, and contributing to the GDP growth of many nations. However, evidence emerged in the late 2000s that fossil fuel energy was linked to an increase in greenhouse gas emissions and climate change, which could have negative consequences for both human and animal life [1,2]. Many countries supported the efforts to achieve net-zero carbon emissions and to support the transition to renewable energy. Consequently, renewable energy has received more attention in recent times [3,4]. The renewable sources of energy have the capability to reduce greenhouse gas emission leading to change in climate and are much more sustainable and cleaner. Solar energy is one among and is a massive kind of energy [5]. Wind energy is anticipated to continue playing a significant role in the world's energy mix in the years to come [6].Hydro energy is a sustainable source of electricity because it doesn't emit any greenhouse gases. Hydroelectric facility construction and upkeep can be costly and challenging [7].Geothermal energy, which comes from the heat produced inside the earth's core, is an alternate source of energy. Due to its low carbon emissions and lack of resource depletion, it is regarded as a sustainable energy source [8].In rural areas, biomass is mostly utilised for cooking and heating and for industrial activities and energy production [9]. Nuclear fission and fusion reactors do not emit greenhouse gases into the atmosphere and, therefore, can play a significant role in mitigating climate change [10].Biomass-energy production is also a potential means of restoring degraded lands in some areas [11].Plant biomass serves as a key material for the synthesis of various biofuels such as bio alcohol, biodiesel, and bio hydrogen. Unlike other plants, algal-based biofuels production only requires sunlight, CO2, and water, resulting in a much higher production yield [12].

Biodiesel has gained global attention as an alternative to fossil fuels due to its renewable nature and potential to replace petroleum diesel. It is produced through trans-esterification of animal fats and vegetable oils using methanol or ethanol. The trans-esterification process reduces the molecular weight and viscosity of triglycerides while increasing their volatility. Biodiesel also has the potential to recycle carbon dioxide [13,14].The first generation of biodiesel primarily relies on edible feed stocks such as soybean oil, palm oil, and coconut oil, which were popular due to their availability and relatively simple conversion process [15].Second-generation biodiesel is produced from non-edible feed stocks such as neem oil, rubber seed oil, and jatropha oil, which offer several advantages over first-generation feed stocks. Nonetheless, second-generation biodiesel remains an important alternative to first-generation biodiesel for producing more sustainable and eco-friendly fuel [16,17].Biodiesel produced from microalgae and waste oils are categorized as third-generation biodiesel. Third-generation biodiesel offers several benefits such as reduced greenhouse effect, higher productivity, lower dependence on farming land, higher oil content, and reduced impact on the food chain [18,19]. Waste oils, including used cooking oil, waste fish oil, and waste animal tallow oil, are also potential sources of third-generation biodiesel, which reduces the burden on waste handling plants and decreases water pollution [20]. The fourth generation of biodiesel involves photo biological solar fuels and electro-fuels [21].The current topic of interest is biodiesel made from waste oils as the fourth generation is still in their research level. Biodiesel made from waste oilsis more likely to cause engine components to corrode or degrade, and it has undesirable weak cold flow qualities, high viscosity, and volatility [22]. Fuel users cannot obtain efficient engine performance since there are no correlations to forecast the features of biodiesels [23]. In compliance with ASTM guidelines, significant fuel characteristics are investigated [24]. It is always necessary to keep an eye on how the elements are affecting the yield percentage [25]. Blends made from waste cooking oil biodiesel perform well and showed comparatively decreased brake-specific fuel usage. Similarly, the rate of fuel consumption and brake thermal efficiency may be further stabilized by adding nano particles [26]. To get a robust study in the nearest future thermo physical properties of waste oil biodiesel-diesel blends and technical optimization of the trans-esterification reaction for biodiesel production is much needed [27,28].

1.1 Free fatty acid (FFA) content

One of the main ingredients in waste cooking oils is free fatty acids (FFAs). They are often eliminated from unrefined oils and fats since they might have detrimental effects on the oil's quality and stability. FFAs, however, can occasionally be useful when generating biodiesel from unrefined oil. FFAs in raw oil can generally be a problem for the manufacture of biodiesel due to the fact that they may react with alcohol during the trans-esterification process results soap formation, which can lower the yield of biodiesel and cause other problems.High FFA concentrations can also result in more acidity in the final biodiesel, which can contribute to corrosion in storage tanks and engines [29]. Based on FFA content the raw oil can be categorized as high and low FFA oils. It is often essential to remove the FFA before trans-esterification when making biodiesel from high-FFA oils to achieve the amount and quality of biodiesel [30]. The manufacture of biodiesel from waste oils or non-edible oils with a high FFA content may be improved with further study in this field, which could open up new opportunities for the production of sustainable energy [31]. Solid catalysts can be used to carry out the trans-esterification process with maximum oil conversion and free fatty acid (FFA) conversion at the same time [32]. Solid catalysts have a lot of promise for producing sustainable biodiesel from low-quantity oils because of their strong activity and favourable reusability [33].Because of their good recovery with only a small amount of catalytic activity lost and their insensitivity to moisture and FFAs found in feedstock, solid catalysts are advantageous from an economic and environmental standpoint when used in the production of biodiesel, particularly from low-quality oils [34].More successfully in the recent years intense research is being attempted to handle very high FFA oils by one-pot transformation process where heterogeneous catalyst 8 wt% Fe3O4 nano particles was used for the conversion high FFA soybean oil to biodiesel with 15:1–35:1, methanol and oil molar ratio. Maintaining 130oC for 8 h with stirring at 600 rpm the oil conversion of 94.2 % was reported [34]. In another study soybean oil with methanol to oil molar ratio, 15:1 to 35:1 and 28 wt%H6PV3MoW8O40/Fe3O4/ZIF-8 catalyst at 160oC with stirrer speed 600 rpm and reaction time 10 h resulted in higher biodiesel yields leaving huge scope for heterogeneous solid acid catalyst for high FFA oils [33].FFA content of a feedstock is commonly identifiedby standard titrimetric procedures recommendedbyAmerican Oil Chemists Society (AOCS), the American Society for Testing andMaterials (ASTM), the European Commission Regulation (EC) and the Associationof Official Analytical Chemists (AOAC). A variety of instrumental techniques like spectroscopic methods, chromatographic methods, and colorimetric techniques are followed for more precise measurement of FFA content [35].With genetic engineering of the feedstock oils, it may be possible in the future to supplement a specific fatty acid or (acids) with desirable attributes to get a fuel enriched with particular fatty acids in the biodiesel fuel to enhance its general fuel properties [36]. According to the European biodiesel standard EN 14214, biodiesel with a high amount of methyl oleate (or monounsaturated fatty acid) may have outstanding features in terms of ignition quality, fuel stability, flow qualities at low temperatures, and iodine number [37]. Esters with saturated medium chain acids, especially those of decanoic (capric) acidexhibit acceptable cold flow characteristics and provide an alternative to long-chain saturated fatty acid esters with high melting temperatures [38]. Moreover, they have great oxidative stability because there are no double bonds, which make them a better choice than those esters. In numerous researches it had been shown that the chemical structure of the fatty acid content affects the physical and chemical properties of biodiesel. Also, several studies demonstrate a connection between exhaust emissions and the chemical makeup of fatty acids [39,40].

1.2 Oil quality

Gas chromatography (GC) is used to separate fatty acids in oils [41]. To ensure reliable measurement and quantification, the flame ionization detector (FID) technique is unproblematic [42]. However, even though the use of GC-FID chromatograms demonstrated the analytical power of multidimensional GC technology, it also highlighted the need for detectors that could provide more information [41,43].The UV spectroscopy is other important technique for the measurement of fatty acids [44]. Oleic acid and other compounds with UV-absorbing chromophores can be examined using the straightforward and affordable method of UV spectroscopy. This method is frequently used for the investigation of chemicals and the observation of reactions in many different domains [45].Sensors play a vital role nowadays in oil quality assessment by providing real-time data on these parameters. Viscosity sensors are used to measure the viscosity of oil, which is an important parameter that affects the performance and efficiency. Micro-electro-mechanical systems (MEMS) based viscosity sensors for oil quality assessments have been developed and reported earlier [46]. Acidity sensors are used to monitor the acidity of oil, which can indicate the presence of contaminants or oxidation products. Acidity sensor based on a quartz crystal microbalance (QCM) utilizes a sensitive film made of polydopamine/Graphene Oxide (PDA/GO) nano composites, which show high sensitivity and selectivity towards acidic gases [47]. Water content sensors are used to monitor the water content in oil, capacitance-based sensor uses parallel-plate capacitor configuration and utilizes a thin film of water-sensitive polymer (polyvinyl alcohol) as the dielectric material [48].

Almost all the literatures published on biodiesel, highlights the significant influence of FAME composition on the properties of biodiesel fuel. Optimising FAME composition is crucial for improving fuel performance and reducing its impact on the environment. Particularly FFA content determines the complexity of the biodiesel production. The experimental procedure practiced for the identification of FFA is based on titration, which is a laborious process and involves large amounts of chemicals. Also, it depends on visual end points which in turn compromise the accuracy of the result. Since, variety of feedstock with varying structural compositions and properties being used to produce biodiesel, yields inconsistent quality of biodiesel, analysing the composition of the oil becomes essential to produce superior quality biodiesel. For the first time in the research of biodiesel, a simple mechanistic decision-making approach is attempted in simplifying the choice of the oil and grading it for its usage in biodiesel production. The present study's main goal was to create an FFA monitoring device for testing waste cooking oil samples used to generate biodiesel by analysing the properties of biodiesel. This was accomplished by the creation of a database listing the initial characteristics of a group of oil samples and the related biodiesel samples. The work comprises of building the sensor and evaluating the sensor's functionality by comparing the results with experimental findings. The percentage variation of free fatty acid is calculated by establishing a correlation between the concentrations of the free fatty acid as oleic acid with the determination of absorbance using UV Spectrometer. The gas chromatography flame ionization detector was also used to determine the varying composition of the methyl esters in the biodiesel for different waste cooking oil samples. Further the biodiesel obtained was tested for its performance and emissions.

2 Materials and methods

2.1 Biodiesel production and property testing

Five different waste cooking oil (WCO) samples used in this study are collected from varied cooking circumstances, such as variable cooking times and food items prepared in it. The initial characteristics of the gathered oil samples, such as the density, kinematic viscosity, free fatty acid (FFA) percentages and moisture content are evaluated and presented in Table 1. After the assessment of the raw oil properties, trans-esterification of all samples using optimal conditions was done as reported earlier [[49], [50], [51], [52], [53]].Since all the 5 samples are having FFA concentrations of less than 1 %, single-stage trans-esterification is appropriate and was done. Fuel characteristics of biodiesel samples like density, kinematic viscosity, acid value, moisture content, and cold flow characteristics like cloud point and pour point, as well as combustion characteristics like calorific value, flash point, and fire point, were tested as per ASTM standards [54] and tabulated in Table 2.Table 1 Preliminary properties of the WCO samples.

Table 1	WCO 1	WCO 2	WCO 3	WCO4	WCO 5	
Density of oil sample (g/ml)	0.93	0.95	0.94	0.91	0.92	
Viscosity (cSt)	41.21	58.47	37.29	41.28	32.15	
Percentage of FFA (%)	0.337	0.417	0.613	0.787	0.451	
Moisture content (%)	0.049	0.057	0.026	0.019	0.069	

Table 2 Waste cooking oil biodiesel properties.

Table 2Qualities analysed		Biodiesel samples	
ASTM Standard	WCOBD 1	WCOBD 2	WCOBD 3	WCOBD 4	WCOBD 5	
Density (g/cc)	D 1298	0.877	0.903	0.895	0.875	0.882	
Kinematic Viscosity (cSt)	D 445	5.841	5.995	5.701	4.267	5.155	
Moisture content (%)	D 2709	0.084	1.225	0.321	0.017	0.310	
Acid value (%)	D 664	0.569	0.336	0.445	0.344	0.225	
Cloud point (°C)	D 2500	9	−4	6	10	5	
Pour point (°C)	D 97	0	−14	5	1	−10	
Calorific value (cal/g)	D 240	6562.3	6261.9	7764.0	4058.7	5661.0	
Flash point(°C)	D 93	213	217	195	197	137	
Fire point (°C)	D 93	235	237	215	219	159	

2.2 UV visible spectroscopy for FFA measurement

In 80 mL of distilled water, 5.5g of the copper-acetate monohydrate was dissolved. The initial pH of the solution was 5.08, using the addition of pyridine to the solution mixture it was raised to 6.06. Further this mixture of solution is diluted with distilled water to a volume of 100 mL. These steps are carried out for the preparation of the copper acetate pyridine reagent. By dissolving stock oleic acid in the non-polar solvent isooctane, the standard oleic acid solutions were made at 9 different concentrations (2–18 mol/mL) for the calibration curve.Each calibration solution received 2 mL of copper reagent, which was then added, stirred for 30 s, and left to settle and get separated in a 10 mL centrifuge tube. A graph was drawn between the calibration solution concentration and the value of peak absorbance is calculated based on the measurement of the top organic layer using a UV–visible spectrometer. The absorbance peak was attained at 708–709 nm. The linearity relation between the concentration of fatty acids and the absorbance was developed by an equation using the graph. In addition, isooctane, and copper acetate reagent of 2 mL were added to a 10 mL centrifuge tube containing 2g of the oil sample. The resulting mixture was subsequently centrifuged at 2000 rpm for 5 min in a centrifuge for bilayer separation. The top organic layer was then analysed under a UV–visible spectrometer, allowing the FFA content of the oil to be predicted in terms of oleic acid (μmol/mL) based on the equation obtained on linearity from the calibration graph.

2.3 Development of sensor module for FFA measurement

In the construction of sensor module, an Arduino UNO board was used to power the module and analyse the input signals from the module in order to get the output readings. The first assembly of the module was made by arranging the components on a breadboard. First the connecting wires are connected to the Arduino UNO board with the required input and output connections. The emitter and the receiver are the IR LED and the photo diodes respectively are placed on the breadboard on the required places accordingly. Resistors of 10k ohm and 1k ohm are introduced in this circuit that is connected in the breadboard. When the circuit is complete the Arduino UNO board is connected to a computer to operate the circuit. The intensity of the IR rays collected by the photodiode changes when samples are positioned between the IR LED (emitter) and photodiode (collector), allowing the IR rays to pass through the sample. As a result, the output voltage also changes. When the samples were initially examined, the readings were unstable. It was later discovered that the excess light exposure to the photodiode owing to the open arrangement was the reason that contributed to the unstable readings. Hence, the module was modified into a closed assembly, which produced stable readings. The circuit diagram for the sensor module is depicted in Fig. 1.Fig. 1 Circuit diagram for the developed sensor.

Fig. 1

2.3.1 Arduino code for the sensor

const int photo_diode = A0;

int input_val = 0;

float volt;

void setup(){

// put your setup code here, to run once:

Serial.begin(9600);

}

void loop(){

// put your main code here, to run repeatedly:

input_val = analogRead(photo_diode);

volt=((input_val*1.20)/1023.00)*1000;

Serial.println(volt,4);

delay(1000);

}

The IR LED continuously emits IR rays, which are detected by the photodiode as analog signals and then converted into voltage measurements using an Arduino Uno R3 microcontroller. The reading gets recorded in the computer, and the Arduino board is supplied with power and controlled by a computer using an OTG cable. When samples are positioned between the IR LED and photodiode, letting the infrared light to pass through the sample, the intensity of the IR rays captured by the photodiode varies. The output voltage also varies as a result. The findings were erratic when the samples were first inspected. Later, it was found that the unstable readings were caused by the photodiode being exposed to too much light because of the open design. In order to provide stable readings, the module was changed into a closed assembly. A correlation of the absorbance and the corresponding voltage detected was investigated as it is easily measurable. Similar to the UV visible calibration, the calibration data was collected by dissolving various mass percentages of oleic acid in isooctane, a non-polar solvent, and recording the resulting sensor outputs. The data obtained from the sensor readings and the variable concentrations were shown on the calibration graph. The oil samples were collected in vials that were similar to those used for calibration, the samples were examined by the sensor, and the corresponding FFA contents in terms of oleic acid % were determined using the linear equation between the readings of the output voltage and the oleic acid concentration.

2.4 Correlation of composition of oil with properties of biodiesel using GC FID analysis

Before being injected into the injection port of the YL 6500 GC equipped with a 0.53-mm TR-WAX capillary column intended to achieve from 140 °C to 260 °C at a rate of 10 °C per minute, the moisture-removed samples were diluted with hexane. The carrier gas, helium, was set to flow at a flow rate of 5 mL per minute prior to injecting the sample. One micro litre (1 μL) of the sample was injected into the split mode injection port in order to analyse the composition of the oil and biodiesel samples. The FID detector, which detects the amount of carbon atoms in the sample, is then used to identify the segregated components. On the detector, each component will provide a unique signal. The Flame Ionization Detector (FID)'s maximum and ignition temperatures were calibrated at 471 K and 513 K, respectively. The data gathered from the detector is analysed to determine the different components and their quantities. By analysing GC - FID data and comparing it to well-known GC standards of fatty acid methyl esters, the fundamental composition of the oil and biodiesel samples were obtained. The impact of the composition of the oil sample on the properties of biodiesel was studied by comparing the individual properties of selective FFAs with the properties of the biodiesel samples obtained.

2.5 Engine testing of generated biodiesel

An eddy current loading-type dynamometer is attached to the single cylinder 4 stroke Kirloskar diesel engine (Fig. 2). The system has a number of interfaces for sensing torque, speed, temperature, fuel gas, airflow, and speed. A fuel measurement standby unit, manometer, fuel measuring device, air flow and petrol transmitter, and air container are also included. An exhaust gas analyser is used to monitor exhaust gasses and smoke meter for smoke density. B20 biodiesel blend from all the 5 samples are tested. This biodiesel blend is checked for performance characteristics such as brake thermal efficiency (BTE) and specific fuel consumption (SFC) and emission characteristics HC, CO, CO2, O2, NOx.Fig. 2 Engine Test Rig for performance and emission measurement.

Fig. 2

2.6 Uncertainty analysis

Eq. (1)uses the Gaussian distribution model to evaluate the uncertainty of the observed variables (ΔXi) [55,56]. The confidence intervals fall between ±2σ. Here, 2σ is the average limit on which 95 % of the observed data might be trusted.(1) ΔXi=2σiXi‾*100

Where Xi Xi‾ and σi represents number of readings, experimental readings and standard deviation respectively. Eq. (2) & Eq. (3) are used to evaluate the uncertainty of derived parameters [56].(2) R=f(X1,X2,X3,…………‥Xn)

Where X1,X2, … ….Xn indicates the number of readings and R represents the function of those. Finally errors associated with measured parameters (ΔR) is computed by RMS (root mean square) method.(3) WR=((∂R∂X1W1)2+(∂R∂X2W2)2+…+(∂R∂XnWn)2)

WR is the overall uncertainty of tested parameters and W1, W2 … Wn are uncertainty values for engine parameters, R is function of measured quantities X1, X2 …, Xn. Uncertainty value of the all engine performance and emission quantities like are calculated and the uncertainty value of engine emissions were within the limits. Table 3 presented an illustration of the uncertainties of instruments. The uncertainties in the different measured parameters were assessed using Eq. (3), and the results were tallied in Table 4.Table 3 Uncertainty of instruments.

Table 3Instruments	Range	Accuracy	% of uncertainty	
Manometer	0–200 mm	±1 mm	2	
Tachometer	0–10000 rev/min	±10 rpm	0.2	
Stopwatch	–	±0.5s	0.2	
Pressure transducer	0–110 bar	±0.1 bar	0.2	
Smoke meter	0-10 BSU	±0.1	2	
Exhaust gas temperature	0–900oC	±1oC	0.24	

Table 4 Uncertainties in measured parameters.

Table 4parameters	% of uncertainty	
Load	0.32	
BP	1.6	
Speed	0.10	
Air flow rate	0.30	
Fuel flow rate	0.50	
HC	0.20	
CO	0.20	
NOx	0.20	
Smoke opacity	0.70	

3 Results and discussion

The results obtained through measurements and calculations based on the procedure discussed in section 3 are presented in this section.

3.1 UV visible spectroscopy results

Fig. 3 displays the measurement of curves of calibration for the various oleic acid concentrations determined via absorbance measurements. The horizontal axis displays the wavelength of the calibration solution's absorbance in relation to that of the blank (i.e., isooctane and copper acetate reagent), while the vertical axis represents absorbance. The solution's peak absorbance was measured between 707 and 709 nm, and the absorbance ascended as solution concentration ascended. These values are being represented in a graphical format for the purpose of analysing the curves calibrated at various curves. Additionally, the data are solely provided in the context of oleic acid. Oleic acid was selected for calibration over other FFAs due to its higher solubility and ability to form complexes with ions of copper in non-polar solutions. Since only the FFAs in the mixture of isooctane and copper acetate pyridine form a cage-like complex with the copper reagent, mono acylglycerols, di acylglycerols, tri acylglycerols, or any other lipid does not interfere with the production of colour. Thus, this study was capable to determine the linearity among the absorbance and the concentrations using the measurement findings. Table 5 contains the calibration information from the spectrophotometer results.Fig. 3 Graph of absorbance.

Fig. 3

Table 5 Analysis of UV visible spectroscopy for oleic acid calibration.

Table 5Oleic acid concentration (μmol/mL)	Absorbance(%)	Wavelength (nm)	
2	0.4	707	
4	0.8	709	
6	0.9	708	
8	1.1	709	
10	1.5	708	
12	1.7	707	
14	1.6	708	
16	2.0	707	
18	2.5	709	

Since the absorbance at the corresponding concentration level is about 2, showing the fact that the Lambert and Beer rule no longer holds true, it was found that the solutions having concentrations in the range of 16 mmol/mL and beyond were not easily tractable to the spectroscopy experiments. The sample 2 oil was taken into consideration for the FFA evaluation. The FFA was predicted using the linearity equation y = 0.1167x + 0.2182 using the calibration chart shown in figure and was also comparable with the FFA value obtained by titration (Fig. 4).Fig. 4 UV visible spectroscopy calibration chart.

Fig. 4

3.2 Sensor based results

While the oleic acid that was in varying concentrations dissolved in the isooctane had first been evaluated by means of the sensor, the values obtained were seen to be linear because the construction of the sensor module relied upon the method used for UV visible spectro photometry. As a result, the calibration procedure of the sensor module was carried out at different concentrations of oleic acid in the isooctane. Pure isooctane solution sensor readings were treated as blank readings (Table 6).Table 6 Calibration of oleic acid for the purpose of measurement of sensor.

Table 6Oleic acid in percentage [%] (w/w) (approx.)	Output Voltage measured (mV)	
0 (blank solution)	31.65	
0.1	32.03	
0.2	28.47	
0.3	26.87	
0.4	25.91	
0.5	24.03	
0.6	19.85	
0.7	21.01	
0.8	19.02	
1	17.27	
1.2	14.35	
1.4	10.87	
1.6	9.79	
1.8	8.56	
2	10.40	

The output voltage was found to linearly decline as concentration values increased; this was because the output voltage was dependent on how much radiation the photodiode was able to collect. This leads us to assume that when the FFA concentration of the sample increases; the IR LED's infrared radiation light will be more completely absorbed, resulting in reduced transmission to the photodiode. The output voltage of the photodiode decreases as a result. The readings of the sensor were also found to be unstable since the voltages that are outputted decrease linearly when the concentration exceeds 2 %; in addition, the outcomes values of the sensor were affected by a number of variables, including the vial used to take the readings, the exposure to ambient light, and the temperature (Fig. 5).Fig. 5 Chart of calibration for the measurement of sensor reading.

Fig. 5

After creating the chart for calibration, the sensor module assessed the oil samples, and the FFA values were predicted based on the equation of linearity derived from the chart of calibration and then compared it with FFA results derived from the data obtained on titration (Table 7).Table 7 Comparison of FFA values from obtained titration and sensor.

Table 7Sample	FFA through titration	FFA through sensor	Percentage deviation	
WCO 1	0.337	0.25	−25.81	
WCO 2	0.417	0.35	−16.06	
WCO 3	0.613	0.76	23.98	
WCO 4	0.787	0.745	−5.33	
WCO 5	0.451	0.59	30.82	

3.3 Property correlation of oil composition with biodiesel composition using GC-FID

Fig. 6, Fig. 7 represents the GC analysis of the oil sample and a biodiesel sample. To interpret the GC FID results of the oil and biodiesel samples, it is necessary to examine the area of peak and retention times of the individual constituents in the sample. The peak area represents the concentration of every component in the sample. The retention time shows how long it takes for each component to move along the GC column and on to the detector. Every component has a unique retention period that can be used to separate them. For this study 5 samples of waste cooking oil and their corresponding biodiesel were analysed through GC-FID. The composition details of the tested samples are presented in Table 8. It is evident from Table 8, that there are seven main fatty acid compositions present in all the samples taken and were compared.Fig. 6 GC analysis of Oil sample.

Fig. 6

Fig. 7 GC analysis of Biodiesel sample.

Fig. 7

Table 8 Composition analysis of oil and biodiesel samples.

Table 8Compound	Composition %	
Number	Name	WCO 1	WCOBD 1	WCO 2	WCOBD 2	WCO 3	WCOBD 3	WCO 4	WCOBD 4	WCO 5	WCOBD 5	
C12:0	Lauric acid	0.15	0.1	0.31	0.23	0.19	0.12	0.13	0.9	0.11	0.82	
C14:0	Myristic acid	0.54	0.43	0.77	0.68	0.64	0.55	0.5	0.39	0.42	0.39	
C16:0	Palmitic acid	10.54	7.89	12.36	11.12	16.47	11.76	9.56	6.25	8.23	5.5	
C18:0	Stearic acid	8.5	6.13	5.6	3.7	10.54	7.39	9.5	8.2	7.5	5.6	
C18:1	Oleic acid	28.5	20.8	40.45	35.65	21.45	11.64	32.3	25.6	29.5	24.5	
C18:2	Linoleic acid	16.47	12.54	22.37	19.56	17.96	15.23	15.2	11.32	13.20	10.2	
C18:3	Linolenic acid	1.56	0.9	1.09	0.85	0.56	0.23	1.23	0.85	1.11	0.74	

From this analysis, the specific influence of the fatty acid compositions over the properties of biodiesel, such as kinematic viscosity, density, cloud point and pour point, calorific values, flash point, fire point etc.can be compared. Kinematic viscosity rises as the amount of fatty acid carbon atoms in oil grows and falls as the degree of unsaturation rises. As unsaturation grows, so does density, which explains why the more unsaturated fatty acids there are, the higher the fuel's density will be. Based on observation, the cloud and pour points are lower at the lower saturation. These points describe the fuel's low temperature behaviour. Calorific value increased as chain length increased, and the heat of combustion decreased when unsaturation increased for a given chain length because of the loss of hydrogen.

Oleic acid composition is found to be predominantly high in all the samples of waste cooking oil and the biodiesels derived from them subsequently. Hence, oleic acid was used to in different compositions to obtain the corresponding voltages using UV spectroscopy. The unknown biodiesel samples derived from the various waste cooking oil were also investigated in the UV spectrometer to record the absorbance to interpret the corresponding voltage as shown in Fig. 4 and Table 5. Further the calibration curve plotted as shown in Fig. 6 with voltage and oleic acid composition was used to determine the FFA percentage considering FFA % to be represented as oleic acid. Thus the investigation formed a basis to correlate the absorbance composition data acquired using UV spectroscopy, composition data acquired from GC -FID and voltage measurements recorded from the developed sensor module. The FFA percentage of oil samples determined by titrimetric method and using the developed sensor module have been compared have been validated and the percentage deviation from the experimental method has been reported in Table 7.

3.4 Engine performance

The sensor module's results were supported by the performance and emission characteristics of an internal combustion engine running on the produced biodiesel samples. The implementation sensor module has no direct effect on the engine performance; nonetheless, the attributes computed with the help of sensor module are used to assess the engine performance. The engine performance characteristics brake thermal efficiency (BTE and brake specific fuel consumption (BSFC) of biodiesel samples are examined and the findings are shown in Fig. 8, Fig. 9. The ratio of the engine's brake power output to its fuel energy input, stated as a percentage, is known as brake thermal efficiency. It is an indication of how effectively an engine transforms fuel energy into productive work. Using a B20 blend of biodiesel made from used cooking oil can improve the engine's brake thermal efficiency. This is because biodiesel burns better and increases engine efficiency than petroleum diesel due to its higher cetane number. However, certain research works have also discovered that using a B20 blend of biodiesel made from used cooking oil will reduce the engine's brake thermal efficiency. This is since biodiesel produces less energy per unit of fuel than petroleum diesel due to its lesser heating value. From the BTE curves (Fig. 9), it is evident that the esters of myristic acid, palmitic acid and linoleic acid should be sustained for better BTE. Since the blend WCOBD 5 has slightly higher myristic acid, palmitic acid and linoleic acid content than the other blends it's BTE values are closer to the diesel.Fig. 8 BTE of B20 blend of WCO biodiesel.

Fig. 8

Fig. 9 SFC of B20 blend of WCO biodiesel.

Fig. 9

Due to their higher viscosity and lower energy content, biodiesel blends were found to have a somewhat higher SFC than petroleum diesel in general. Fig. 10 shows that biodiesel blends produced 2–4% higher SFC than diesel. The fuels with highest BTE will have least SFC which is favourable for a better engine performance [57]. It may further be added that the biodiesel samples with lesser percentage of long chain saturated fatty acid esters including myristic acid, palmitic acid as in WCOBD 5 will have less SFC values. In all the WCO biodiesel samples polyunsaturated linoleic acid methyl ester percentage is higher than myristic and palmitic acid methyl esters. However, it is found the polyunsaturated linoleic acid methyl ester conent least in the WCOBD5 blend favoring lowest SFC comparable with conventional diesel.

3.5 Engine emissions

The engine performance characteristics of biodiesel samples are examined and the findings are shown in Fig. 10, Fig. 11, Fig. 12, Fig. 13. The emissions of CO (carbon monoxide) and Hydro carbon might differ based on a number of variables, including the engine classification, mix ratio, efficiency of combustion, and operating circumstances. However, in comparison to regular diesel fuel, biodiesel blends like B20 offer the ability to lower CO emissions. Compared to petroleum-based diesel fuels, biodiesel fuels contain more oxygen, which can increase combustion efficiency and lower the quantity of carbon monoxide (CO) released during combustion as evident in Fig. 11. Additionally, biodiesel fuels emit less carbon monoxide (CO) because they have less contaminants and aromatic compounds than petroleum-based diesel fuels. B20 blend of biodiesel possessed less CO emission than the conventional petroleum diesel in all the load conditions making it a better performer in the case of CO emissions while engine testing it [[44], [45], [46]]. The hydro carbon emissions are shown in Fig. 12.Fig. 10 Carbon Monoxide emissions.

Fig. 10

Fig. 11 Hydro carbon emissions.

Fig. 11

Fig. 12 CO2 emissions.

Fig. 12

Fig. 13 NOx emissions.

Fig. 13

Long-chain fatty acid methyl esters (FAMEs), which typically have 11–21 carbon atoms per molecule, make up the complicated mixture that makes up biodiesel. The origin of the feedstock and the extraction techniques will determine the precise content of the biodiesel blend. The atoms of carbon in the FAMEs are oxidised into CO2 and water vapour during burning. The carbon-to-hydrogen proportion of the fuel and the equilibrium state of the process of combustion dictate how much CO2 is released depending on the amount of fuel burned [58]. In this study, compared to diesel, B20 blends of biodiesel can cut CO2 emissions by about 20 % as evident in Fig. 13. This is caused by the decreased carbon percentage of the biodiesel in comparison to petroleum diesel and the regenerative quality of the material being used, which consumes CO2 from the environment during growth. However, the particular engine and operating circumstances will determine the precise reduction in CO2 emissions. This study also revealed that, biodiesel blends released slightly higher HC and CO2 emission except WCOBD 1. This may be because the both HC and CO2 emission characteristics are interlinked upon each other and the exact reason for this cause is yet unknown and also the difference in emission is also not too high than diesel [56]. To solve the problem of Hydro carbon emissions, it might be necessary to increase fuel quality, streamline the combustion process, or alter the combustion chamber or system for fuel injection to better handle the biodiesel blend [55,58]. Fig. 13 delineates the NOx emissions of the tested samples. The NOx emissions of biodiesel blends significantly dropped than Petro diesel [55,57,59]. The optimization of combustion process proposed to reduce the emission and for controlling various environmental parameters [[60], [61], [62], [63], [64]]. Various reasons of emissions in diversified conditions revealed the importance of study [[65], [66], [67], [68], [69]]. Overall, the CO, HC, CO2 and NOx emissions are quite within the range for all WCO biodiesel samples and observed to be least for WCOBD 1 blend which has least lauric (saturated) and highest linolenic (polyunsaturated) methyl ester composition.

4 Conclusion

In the current work, an attempt was made to build a device for identifying the FFA of oils. The composition of oil samples and the fluctuation in their quality were investigated using a gas chromatography flame ionization detector (GC-FID). Biodiesel is produced from oil samples by transesterification, and the effect of FFA and their corresponding methyl esters on quality and characteristics has been examined. The characteristics of biodiesel were established using ASTM standards. The study was expanded to compare the qualities of biodiesel to the composition of the oil from which it was generated. The results clearly shown that biodiesel qualities are dependent on FFA content and oil composition. The findings were supported by the performance and emission characteristics of an internal combustion engine running on the produced biodiesel samples. To conclude, free fatty acid content of feedstock is a significant parameter to be considered to produce biodiesel, a mechanistic approach for identification of FFA consent in the oil will improvise the analysing procedure of oil samples and biodiesel production.

CRediT authorship contribution statement

J. Jayaprabakar: Writing – review & editing, Writing – original draft, Methodology, Investigation. S.S. Dawn: Writing – review & editing, Visualization, Methodology, Investigation, Formal analysis, Conceptualization. M. Anish: Writing – review & editing, Visualization, Supervision, Methodology, Investigation. Jayant Giri: Writing – review & editing, Visualization, Validation, Supervision, Software. K. Sudhakar: Software, Resources, Project administration, Formal analysis, Data curation. Abdullah A. Alarfaj: Writing – review & editing, Supervision, Software, Resources, Project administration, Funding acquisition, Formal analysis, Data curation. Ajay Guru: Visualization, Validation, Supervision, Formal analysis, Data curation.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence to the work reported in this paper.

Acknowledgment

The authors extend their appreciation to the Researchers Supporting Project number (RSP2024R98 ), 10.13039/501100002383 King Saud University , Riyadh, Saudi Arabia, for financial support.
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References

1 Ozili Peterson K. Ozen Ercan Global energy crisis: impact on the global economy The Impact of Climate Change and Sustainability Standards on the Insurance Market 2023 439 454
2 Awan Ahmad Bilal Ali Khan Zeeshan Recent progress in renewable energy–Remedy of energy crisis in Pakistan Renew. Sustain. Energy Rev. 33 2014 236 253
3 De Jong S. Sterkx S. The 2009 Russian-Ukrainian gas dispute: Lessons for European energy crisis management after Lisbon European Foreign Affairs Review 15 4 2010 10.54648/eerr201003710.54648/eerr2010037
4 Dietz T. Shwom R.L. Whitley C.T. Climate change and society Annu. Rev. Sociol. 46 1 2020 135 158
5 Breyer C. Bogdanov D. Aghahosseini A. Gulagi A. Child M. Oyewo A.S. …Vainikka P. Solar photovoltaics demand for the global energy transition in the power sector 10.1002/pip.2950 2018
6 Herberta G.M.J. Iniyanb S. S E. Rajapandian S. Review of wind energy technology developments and future trends n.d. Renew. Sustain. Energy Rev. 2007 10.1016/j.rser.2005.08.004
7 Kaunda C.S. Cuthbert Z. Kimambo K. N T. Hydropower in the context of sustainable energy supply A Review of Technologies and Challenges 2012 10.5402/2012/730631
8 Ruth Shortall Davidsdottir B. Axelsson G. Geothermal energy for sustainable development: a review of sustainability impacts and assessment frameworks 10.1016/j.rser.2014.12.020 2015
9 Toklu E. Biomass energy potential and utilization in Turkey 2017 10.1016/j.renene.2017.02.008
10 Mathew M.D. Nucl. Energy: A pathway towards mitigation of global warming 2022 10.1016/j.pnucene.2021.104080
11 Joshi G. Pandey J.K. Rana S. Rawat D.S. Challenges and opportunities for the application of biofuel Renew. Sustain. Energy Rev. 79 May 2017 850 866 10.1016/j.rser.2017.05.185
12 Rodionova M.V. Poudyal R.S. Tiwari I. Voloshin R.A. Zharmukhamedov S.K. Nam H.G. Zayadan B.K. Bruce B.D. Hou H.J.M. Allakhverdiev S.I. Biofuel production: challenges and opportunities Int. J. Hydrogen Energy 42 12 2017 8450 8461 10.1016/j.ijhydene.2016.11.125
13 Naik S.N. Goud V.V. Rout P.K. Dalai A.K. Production of first and second generation biofuels: a comprehensive review Renew. Sustain. Energy Rev. 14 2 2010 578 597 10.1016/j.rser.2009.10.003
14 Cadenas A. Cabezudo S. Biofuels as sustainable technologies: perspectives for less developed countries Technol. Forecast. Soc. Change 58 1–2 1998 83 103 10.1016/s0040-1625(97)00083-8
15 Tariq M. Ali S. Khalid N. Aransiola E.F. Ojumu T.V. Oyekola O.O. Madzimbamuto T.F. Ikhu-Omoregbe D.I.O. Singh D. Sharma D. Soni S.L. Sharma S. Kumar Sharma P. Jhalani A. A review of current technology for biodiesel production: state of the art Fuel 16 8 2014 116553 10.1016/j.fuel.2019.116553
16 Peer M.S. Kasimani R. Rajamohan S. Ramakrishnan P. Experimental evaluation on oxidation stability of biodiesel/diesel blends with alcohol addition by rancimat instrument and FTIR spectroscopy J. Mech. Sci. Technol. 31 1 2017 455 463 10.1007/s12206-016-1248-5
17 Shameer P.M. Ramesh K. Green technology and performance consequences of an eco-friendly substance on a 4-stroke diesel engine at standard injection timing and compression ratio J. Mech. Sci. Technol. 31 3 2017 1497 1507 10.1007/s12206-017-0249-3
18 Hannon M. Gimpel J. Tran M. Rasala B. Mayfield S. Biofuels from algae: challenges and potential Biofuels 1 5 2010 763 784 10.4155/bfs.10.44 21833344
19 Mata T.M. Martins A.A. Caetano N.S. Microalgae for biodiesel production and other applications: a review Renew. Sustain. Energy Rev. 14 1 2010 217 232 10.1016/j.rser.2009.07.020
20 Bhatti H.N. Hanif M.A. Qasim M. Rehman Ata-ur Biodiesel production from waste tallow Fuel 87 13–14 2008 2961 2966 10.1016/j.fuel.2008.04.016
21 Cameron D.E. Bashor C.J. Collins J.J. A brief history of synthetic biology Nat. Rev. Microbiol. 12 5 2014 381 390 10.1038/nrmicro3239 24686414
22 Samuel O.D. Okwu M.O. Varatharajulu M. Eseoghene I.D. Fayaz H. Adaptive neuro-fuzzy inference system for forecasting corrosion rates of automotive parts in biodiesel environment Heliyon 10 5 2024 e26395
23 Samuel O.D. Kaveh M. Oyejide O.J. Elumalai P.V. Verma T.N. Nisar K.S. …Enweremadu C.C. Performance comparison of empirical model and Particle Swarm Optimisation & its boiling point prediction models for waste sunflower oil biodiesel Case Stud. Therm. Eng. 33 2022 101947
24 Samuel O.D. Waheed M.A. Taheri-Garavand A. Verma T.N. Dairo O.U. Bolaji B.O. Afzal A. Prandtl number of optimum biodiesel from food industrial waste oil and diesel fuel blend for diesel engine Fuel 285 2021 119049
25 Kumar S. Bansal S. Performance evaluation of ANFIS and RSM in modeling biodiesel synthesis from soybean oil Biosens. Bioelectron. X 15 2023 100408
26 Soudagar M.E.M. Afzal A. Safaei M.R. Manokar A.M. EL-Seesy A.I. Mujtaba M.A. Goodarzi M. Investigation on the effect of cottonseed oil blended with different percentages of octanol and suspended MWCNT nano particles on diesel engine characteristics Journal of Thermal Analysis and Calorimetry 2020 1 18
27 Samuel O.D. Gulum M. Mechanical and corrosion properties of brass exposed to waste sunflower oil biodiesel-diesel fuel blends Chem. Eng. Commun. 206 5 2019 682 694
28 Samuel O.D. Okwu M.O. Amosun S.T. Verma T.N. Afolalu S.A. Production of fatty acid ethyl esters from rubber seed oil in hydrodynamic cavitation reactor: study of reaction parameters and some fuel properties Ind. Crop. Prod. 141 2019 111658
29 Elgharbawy A.S. Sadik W.A. Sadek O.M. Kasaby M.A. Maximizing biodiesel production from high free fatty acids feedstocks through glycerolysis treatment Biomass Bioenergy 146 February 2021 105997 10.1016/j.biombioe.2021.105997
30 Ribeiro A. Castro F. Carvalho J. Influence of free fatty acid content in Biodiesel production on non-edible oils In: 1st International Conference WASTES: Solutions, Treatments and Opportunities. Centro para a Valorização de Resíduos(CVR) 2011 425 430
31 Mićić R. Tomić M. Martinović F. Kiss F. Simikić M. Aleksic A. Reduction of free fatty acids in waste oil for biodiesel production by glycerolysis: investigation and optimisation of process parameters Green Process. Synth. 8 1 2019 15 23 10.1515/gps-2017-0118
32 Medeiros Vicentini-Polette C. Rodolfo Ramos P. Bernardo Gonçalves C. Lopes De Oliveira A. Determination of free fatty acids in crude vegetable oil samples obtained by high-pressure processes Food Chem. X 12 2021 100166 10.1016/j.fochx.2021.100166
33 Zhang G. Xie W. ZrMo oxides supported catalyst with hierarchical porous structure for cleaner and sustainable production of biodiesel using acidic oils as feedstocks J. Clean. Prod. 384 2023 135594
34 Xie W. Gao C. Li J. Sustainable biodiesel production from low-quantity oils utilizing H6PV3MoW8O40 supported on magnetic Fe3O4/ZIF-8 composites Renew. Energy 168 2021 927 937
35 Xie W. Wang H. Grafting copolymerization of dual acidic ionic liquid on core-shell structured magnetic silica: a magnetically recyclable Brönsted acid catalyst for biodiesel production by one-pot transformation of low-quality oils Fuel 283 2021 118893
36 Knothe G. Dependence of biodiesel fuel properties on the structure of fatty acid alkyl esters Fuel Process. Technol. 86 10 2005 1059 1070 10.1016/j.fuproc.2004.11.002
37 Knothe G. “Designer” biodiesel: optimising fatty ester composition to improve fuel properties Energy & Fuels 22 2 2008 1358 1364
38 Knothe G. Sharp C.A. Ryan T.W. Knothe G. Sharp C.A. Ryan T.W. Exhaust emissions of biodiesel , petrodiesel , neat methyl esters , and alkanes in a new technology engine exhaust emissions of biodiesel , petrodiesel Neat Methyl Esters , and Alkanes in a New Technology Engine † 2006 10.1021/ef0502711
39 Gopinath A. Sairam K. Velraj R. Kumaresan G. Effects of the properties and the structural configurations of fatty acid methyl esters on the properties of biodiesel fuel: a review Proc. Inst. Mech. Eng. - Part D J. Automob. Eng. 229 3 2015 357 390 10.1177/0954407014541103
40 Nantha Gopal K. Pal A. Sharma S. Samanchi C. Sathyanarayanan K. Elango T. Investigation of emissions and combustion characteristics of a CI engine fueled with waste cooking oil methyl ester and diesel blends Alex. Eng. J. 53 2 2014 281 287 10.1016/j.aej.2014.02.003
41 Poole C.F. General concepts in column chromatography The Essence of Chromatography 1–78 2003 10.1016/b978-044450198-1/50014-8
42 Purcaro G. Tranchida P.Q. Ragonese C. Conte L. Dugo P. Dugo G. Mondello L. Evaluation of a rapid-scanning quadrupole mass spectrometer in an apolar × ionic-liquid comprehensive two-dimensional gas chromatography system Anal. Chem. 82 20 2010 8583 8590 10.1021/ac101678r 20873720
43 Tranchida P.Q. Mondello L. Detectors and basic data analysis Separ. Sci. Technol. 12 2020 205 227 10.1016/B978-0-12-813745-1.00006-4
44 Győrik M. Ajtony Z. Dóka O. Alebic‐Juretić A. Bicanic D. Koudijs A. Determination of free fatty acids in cooking oil: traditional spectrophotometry and optothermal window assay Instrum. Sci. Technol. 34 1–2 2006 119 128 10.1080/10739140500373999
45 Azeman N.H. Yusof N.A. Abdullah J. Yunus R. Hamidon M.N. Hajian R. Study on the spectrophotometric detection of free fatty acids in palm oil utilizing enzymatic reactions Molecules 20 7 2015 12328 12340 10.3390/molecules200712328 26198220
46 Singh P. Sharma K. Puchades I. Agarwal P.B. A comprehensive review on MEMS-based viscometers Sensor Actuator Phys. 338 January 2022 113456 10.1016/j.sna.2022.113456
47 Ahmed Abdulkareem Ugur Erturun K.M. Fluid viscosity Science 303 5657 2004 429n 429 10.1126/science.303.5657.429n
48 Patocka F. Schneidhofer C. Dörr N. Schneider M. Schmid U. Novel resonant MEMS sensor for the detection of particles with dielectric properties in aged lubricating oils Sens. Actuators, A 315 2020 10.1016/j.sna.2020.112290
49 Mahmood T. Hassan S. Sheikh A. Raheem A. Hameed A. Experimental investigations of diesel engine performance using blends of distilled waste cooking oil biodiesel with diesel and economic feasibility of the distilled biodiesel Energies 15 24 2022 10.3390/en15249534
50 Jayaprabakar J. Karthikeyan A. Gokula Kannan K. Ganesh A. Combustion characteristics of a CI engine fuelled with macro and micro algae biodiesel blends J. Chem. Pharmaceut. Sci. 7 2015 68 71
51 Jayaprabakar J. Karthikeyan A. Josiah A. Shajan A. Experimental investigation on the performance and emission characteristics of a CI engine with rice bran and micro algae biodiesel blends J. Chem. Pharmaceut. Sci. 7 2015 19 22
52 Prabhu A. Venkata Ramanan M. Jayaprabakar J. Production, properties and engine characteristics of Jatropha biodiesel–a review Int. J. Ambient Energy 42 15 2021 1810 1814
53 Jayaraman J. Appavu P. Mariadhas A. Jayaram P. Joy N. Production of rice bran methyl esters and their engine characteristics in a DI diesel engine Int. J. Ambient Energy 43 1 2022 78 86
54 Ibrahim S.M. Abed K.A. Gad M.S. Abu Hashish H.M. A semi-industrial reactor for producing biodiesel from waste cooking oil Biofuels 14 4 2023 393 403
55 Sudarsanam M. Jayaprabakar J. Effect of alumina and bio‐based calcium Oxide nanoadditives on reduction of emissions and performance improvement in a common rail direct injection diesel engine fueled with B20 blend of waste cooking oil biodiesel Energy Technol. 2024 2301107
56 Venu H. Appavu P. Al2O3 nano additives blended Polanga biodiesel as a potential alternative fuel for existing unmodified DI diesel engine Fuel 279 2020 118518
57 Ibrahim S.M. Abed K.A. Gad M.S. Hashish H.A. Performance and emissions of a diesel engine burning blends of Jatropha and waste cooking oil biodiesel Proc. IME C J. Mech. Eng. Sci. 238 4 2024 1157 1169
58 Abed K.A. El Morsi A.K. Sayed M.M. Shaib A.A.E. Gad M.S. Effect of waste cooking-oil biodiesel on performance and exhaust emissions of a diesel engine Egyptian Journal of Petroleum 27 4 2018 985 989 10.1016/j.ejpe.2018.02.008
59 Yaqoob H. Teoh Y.H. Sher F. Farooq M.U. Jamil M.A. Kausar Z. Sabah N.U. Shah M.F. Rehman H.Z.U. Rehman A.U. Potential of waste cooking oil biodiesel as renewable fuel in combustion engines: a review Energies 14 9 2021 10.3390/en14092565
60 Zhang L. Liu C. Jia Y. Mu Y. Yan Y. …Huang P. Pyrolytic modification of heavy coal tar by multi-polymer blending: preparation of ordered carbonaceous mesophase Polymers 16 1 2024 161 10.3390/polym16010161 38201826
61 Liu L. Mei Q. Jia W. A flexible diesel spray model for advanced injection strategy Fuel 314 2022 122784 10.1016/j.fuel.2021.122784
62 Liu L. Peng Y. Zhang W. Ma X. Concept of rapid and controllable combustion for high power-density diesel engines Energy Convers. Manag. 276 2023 116529 10.1016/j.enconman.2022.116529
63 Liu L. Wu J. Liu H. Wu Y. Wang Y. Investigation of combustion and emissions characteristics in a low-speed marine engine using ammonia under thermal and reactive atmospheres Int. J. Hydrogen Energy 63 2024 1237 1247 10.1016/j.ijhydene.2024.02.308
64 Lu G. Duan L. Meng S. Cai P. Ding S. …Wang X. Development of a colorimetric and turn-on fluorescent probe with large Stokes shift for H2S detection and its multiple applications in environmental, food analysis and biological imaging Dyes Pigments 220 2023 111687 10.1016/j.dyepig.2023.111687
65 Lu G. Yu S. Duan L. Meng S. Ding S. …Dong T. New 1,8-naphthalimide-based colorimetric fluorescent probe for specific detection of hydrazine and its multi-functional applications Spectrochim. Acta Mol. Biomol. Spectrosc. 305 2024 123450 10.1016/j.saa.2023.123450
66 Chen D. Serbin S. Burunsuz K. Features of a gas turbine combustion chamber in operation with gaseous ammonia Fuel 372 2024 132149 10.1016/j.fuel.2024.132149
67 Wu X. Liu Y. Zhang P. Zheng C. Han Y. Li D. …Ji R. Sustainable and green sinking electrical discharge machining utilizing foam water as working medium J. Clean. Prod. 452 2024 142150 10.1016/j.jclepro.2024.142150
68 Ji R. Zhao Q. Zhao L. Liu Y. Jin H. Wang L. …Xu Z. Study on high wear resistance surface texture of electrical discharge machining based on a new water-in-oil working fluid Tribol. Int. 180 2023 108218 10.1016/j.triboint.2023.108218
69 Yu H. Wang H. Lian Z. An assessment of seal ability of tubing threaded connections: a hybrid empirical-numerical method J. Energy Resour. Technol. 145 5 2022 10.1115/1.4056332
