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The use of fuel consumption as a gauge of national economic growth is well documented, especially in regions with high petro-diesel demand (Ahmad et al., 2023; Munir, Ahmad, Mubashir, et al., 2021). Fossil fuels, the primary energy source, have been linked to severe environmental issues, including global climate change. Numerous studies advocate for sustainable energy alternatives to mitigate these problems (Chaudhry et al., 2022; Munir, Ahmad, Saeed, et al., 2019). Among these alternatives, bio-based diesel stands out as a viable substitute to reduce our dependence on fossil fuels. The demand for and consumption of fossil fuel-based oils continues to surge despite their non-renewable nature. In response to rising fossil fuel costs and growing environmental apprehensions, biodiesel production is projected to experience sustained growth (Hosseinzadeh-Bandbafha et al., 2024).
It is worth noting that nearly 95% of the world's biodiesel is currently produced from edible seed oils, and this heavy reliance on edible oils for biodiesel production has significant consequences, negatively impacting food supplies and market demands due to their large share (Dawood et al., 2021). To address these concerns, researchers have explored a variety of alternative biodiesel feedstocks, including nonedible sources (Chowdhury et al., 2024; Munir et al., 2023), animal fat, and used edible oils. These efforts are aimed at mitigating the potential food-versus-fuel conflict. The complex transesterification process required for converting these feedstocks into biodiesel has been a significant obstacle, often increasing the cost of biodiesel production (Dawood et al., 2022; Munir, Ahmad, Saeed, et al., 2019). However, the utilization of oils derived from nonedible and inedible sources represents a promising shift in the bio-based diesel industry, reducing production costs and alleviating concerns regarding food resources (Munir et al., 2023).
Madras Leaf Flower (Phyllanthus maderaspatensis), a plant belonging to the Phyllanthaceae family, is widely distributed in the sub-tropics and tropical regions. This plant has been studied for the very first in the current study owing to its high oil content of 35%. It's a characteristic monoecious perennial herb, typically reaching a height of 50–75 cm. The plant is known for its smooth, shiny leaves and trilobed fruit, each containing two seeds (Anonymous, 2023; Bhat et al., 2023). The plant grows abundantly in the wild, having small oil-rich seeds measuring 1–1.5 mm in length, and is brown with tiny, interconnected black granulations. In the current research, we harness the potential of novel inedible Madras Leaf Flower seed oil as a valuable biomass resource for the production of bio-based diesel.
The production of biodiesel commonly involves transesterification technology, a process that consists of three sequential reactions resulting in the generation of esters. These reactions occur in the presence of various catalysts, including chemical, biocatalysts, and nanocatalysts (Hamaidi et al., 2024; Munir, Ahmad, Saeed, et al., 2021). The process starts with the conversion of neutral fats (TAG) to diacylglycerol (DAG), followed by the conversion of DAG to monoacylglycerol, and ultimately to glycerol (Chowdhury et al., 2024). Traditional chemical catalysis routes for biodiesel production have drawbacks. They consume a significant amount of energy, produce unwanted byproducts such as soaps and polymeric colors, and make it challenging to separate the desired products from glycerine, DAG, and acylglycerol (Mandari & Devarai, 2022). These limitations have led to the exploration of alternative, more efficient methods for biodiesel synthesis (Maleki et al., 2024).
In biocatalysis, enzymes such as lipases have been employed for the transesterification of vegetable oils to produce biodiesel (Osman et al., 2023). These enzymes are favored for their specificity and high selectivity (Norjannah et al., 2016; Parandi et al., 2022). However, a drawback of enzymatic transesterification is its relatively slow reaction rate, and the cost of the catalyst, in this case, the enzyme, can be quite high (Da Silva et al., 2020). An additional challenge in enzymatic processes is the inhibition of lipases by methanol, which has been previously reported (Rizwanul Fattah et al., 2020). It's important to recognize that each type of catalytic system, be it enzymatic or chemical, has its own set of advantages and disadvantages (Mofijur et al., 2021). Homogeneous catalysts are practical, but only to a certain extent, especially for oils with low-free fatty acids. They can lead to poor glycerol recovery and are not cost-effective due to the formation of soaps during the refining process. On the other hand, heterogeneous catalysts, with their abundant active acidic or basic domains, offer high catalytic activity, specificity, and tolerance to water (Rizwanul Fattah et al., 2020). This makes them a more efficient choice for a wider range of feedstocks, especially those with a higher free fatty acid content.
Nanocatalysts have a profound impact on catalyst performance and specificity (Ingle et al., 2022). They enhance the interaction between catalysts and substrates due to their extraordinarily high surface areas, leading to significantly improved product quality (Mofijur et al., 2021). Additionally, nanocatalysts tend to have a longer lifespan and can continue working efficiently even after undergoing five cycles of use (Maleki et al., 2024). The design of nanoparticles typically involves either chemical-mediated synthesis or green-mediated synthesis. Green synthesis methods make use of safe and environmentally friendly resources, emphasizing the use of biodegradable phytoconstituents, enzymes, and microorganisms (Das & Chatterjee, 2019). Recent studies have delved into the environmental impacts of various nanomaterials in biodiesel production, employing life cycle assessment (LCA) methodologies to comprehensively analyze the ecological footprint of these processes (Ala'a et al., 2021, 2022; Al-Mawali et al., 2021).
Green metal oxide nanocatalysts have gained significant attention due to their potential in transesterification processes and unique properties, particularly in biodiesel production (Mofijur et al., 2021). Various environmentally friendly green nanocatalysts have been developed from plant materials (Saravanan et al., 2024). For example, CdO from Buxus papillosa leaf extract (Arshad et al., 2023), Ag2O from Monotheca buxifolia leaf extract (Dawood et al., 2022), CuO from Portulaca oleracea leaf extract (Chia et al., 2022), and WO3 from Cannabis sativa leaf extract have been studied for their catalytic potential (Abbasi et al., 2023).
Chromium oxide nanoparticles are gaining significant attention due to their versatility in various applications, including serving as chemical catalysts, eco-friendly pigments, materials with high wear resistance, and effective thermal protectants. The size of these nanoparticles varies depending on the specific preparation method employed, resulting in a range of particle sizes (Maleki et al., 2024; Sackey et al., 2021). In the current research, there is a focus on the production of green chromium oxide nanocatalysts using brinjil peel waste (Solanum melongena), commonly known as aubergine. Aubergine is a well-known and widely consumed edible fruit crop, with Pakistan alone producing approximately 88,148 tons of it, according to FAO data. However, the fruit stalks are typically discarded as waste, making them a valuable resource for sustainable nanoparticle synthesis. This innovative approach not only addresses waste management but also has the potential to enhance the production of green nanocatalysts for various applications (Brenes et al., 2020). Apart from this, these plant materials serve as natural reducing and capping agents and also increase the catalytic stability and reactivity (Siddiki et al., 2022).
Herein, the current study presents the synthesis of a green nanocatalyst of chromium oxide derived from waste stalk extract of brinjal for biodiesel production from the novel inedible seed oil of P. maderaspatensis. The Cr2O3 catalytic system was characterized via different analytical techniques to validate the properties of synthesized nanoparticles: crystallographic analysis (XRD), Fourier-transformed IR spectroscopic investigation (FTIR), scanning electron microscopic analysis (SEM), elemental composition analysis (EDX), diffused reflectance spectroscopy (DRS), and zeta analysis were carried out. Biodiesel was quantified by using the facilities of mass spectrometry, nuclear magnetic resonance spectroscopic analysis 1H-NMR and 13C-NMR, and Fourier-transformed IR spectroscopic techniques. Fuel properties were also checked and compared with the worldwide biodiesel standards (EN 14214, ASTM D 6571, and GB/T 20828-2007) to examine its suitability as an eco-friendly fuel. Additionally, the stability of the catalysts was also investigated to determine their potential for use in industrial biodiesel synthesis on a global scale. This novel comprehensive study aims to promote sustainable and environmentally friendly biodiesel production.
MATERIALS AND METHODS Chemicals and reagentsChromium nitrate nonahydrate [Cr (NO3)3·9H2O], deionized water (H2O), methanol (CH3OH), n-Hexane (C6H14), potassium hydroxide (KOH), phenolphthalein indicator (C20H14O4), isopropanol (C3H8O), chloroform (CHCl3), seeds of P. maderaspatensis were purchased from pansar shop Rawalpindi, and waste fruit material of Solanum melongena.
Extraction of phytoconstituentsThe green nanocatalyst was synthesized in an environmentally conscious manner, that is biological method, using waste brinjal stalks. This process is very efficient as it does not involve the use of chemical stabilizers, but special types of biomaterials present in plant extract serve as natural reducing and capping agents. Initially, the stalks were collected and subjected to a thorough cleaning process to remove any dust or contaminants. This cleaning involved rinsing the stalks with deionized water after an initial wash with tap water. Subsequently, approximately 50 g of these cleaned brinjal stalks were placed in a container with 500 mL of deionized water. The mixture was then heated on a hot plate, with boiling continuing until around half of the water had evaporated. This process aimed to extract valuable phytoconstituents from the stalks. After boiling, the resulting extract underwent filtration four times using Whatman filter paper. This filtration step was crucial in removing any solid particles or impurities, ensuring a clean extract. The filtered extract was then stored in an amber glass container and preserved in a refrigerator at 4°C to maintain its stability and prevent degradation (Jabeen et al., 2022). This green extract from brinjal stalks serves as an environmentally friendly precursor for the synthesis of the chromium oxide nanocatalyst.
Synthesis of nanoparticlesA solution of chromium nitrate nonahydrate (0.1 M) was prepared by mixing 10 g of Cr (NO3)3·9H2O in 250 mL of ions-free water and holding on mixing for 30 min on a 60°C hotplate for continuous stirring. Following this, the phytoconstituent extract, totaling 250 mL, was added drop by drop to the salt solution. The combined solution was then stirred continuously for a duration of 2 h to facilitate the reaction between the extract and the salt. Subsequently, the solution was carefully poured into Petri dishes and left to dry in an oven for a period of 48 h at a temperature of 60°C. The resultant dried material, in the form of crystals, underwent a crucial transformation into nanoparticles. To achieve this, the dried material was collected from the Petri dishes and transferred to crucibles. The crucibles containing the specimen were then placed in a furnace and subjected to a heating process lasting 3 h at a temperature of 600°C to convert the material into nanoparticles (Jabeen et al., 2022). The resulting nanoparticles exhibited a distinctive green color, signifying the successful synthesis of environmentally friendly chromium oxide nanocatalysts.
Characterization of nanocatalystThe newly synthesized green Cr2O3 nanocatalyst was characterized in several ways to understand its architectural states, chemical makeup, and interfacial texture. X-ray diffraction (XRD) was used to analyze a powdered sample of Cr2O3 from the Chemistry department at QAU Islamabad [Cu(K-alpha) radiation with a wavelength of 1.5406 Å]. The sample was measured at 2θ angle per minute with a scale of 2θ = 10–80°. The size of nanoparticles was measured by the Debye–Scherer Equation (Equation 1; Munir et al., 2022).[Image Omitted. See PDF]
A suspension of Cr2O3 nanoparticles was evaluated using the zeta potential to determine the durability and surface-charged density of the particles. Zetasizer was utilized to analyze the zeta potential of synthesized nanoparticles using Nano-ZS and Malvern Instruments from the Department of Pharmacy, Quaid-i-Azam University Islamabad. Diffuse reflectance spectroscopy (DRS) was performed to get the reflectance spectrum and bandgap energy calculation. Fourier-transform IR spectroscopy (FTIR) of the specimen was performed to identify functional groups in synthesized nanoparticles in the 4000–400 cm−1 IR wavelength range. The size and morphology of the powders were determined using a scanning electron microscope from the University of Peshawar (SEM, VEGA3 TESCAN). The elemental composition of a green synthesized Cr2O3 nanocatalyst was determined using an X-ray technique called energy-dispersive X-ray analysis (EDX), also known as EDS or EDAX. Through TGA, the thermal behavior of the synthesized Cr2O3 nanocatalyst was examined in a nitrogen environment utilizing a Perkin Elmer Simultaneous Thermal Analyzer (STA 6000).
Determination of oil proportion inA soxhlet instrument was employed to ascertain the amount of oil in seeds by using a 5 g coarse powder of P. maderaspatensis seeds in a soxhlet thimble. N-hexane (65 mL) with 99% purity was used as an extraction solvent in a 250 mL distillation flask. An electrical heat source (Isomantle) was set on the boiling point of n-hexane (69°C; Munir, Ahmad, Mubashir, et al., 2021) with continuous heating for a maximum of 6 h. A rotary evaporator was used to evaporate the extra n-hexane. The oven was used to dry the sample in a thimble at 55°C for 24 h. For the purpose of assessing oil yield, flask and thimble calculations were done.
The oil content of P. maderaspatensis seed using a flask was calculated using Equation (2) (Dawood et al., 2022).[Image Omitted. See PDF]
Equation (3) (Jabeen et al., 2022) was used for oil content from the thimble.[Image Omitted. See PDF]
Here, the mass of the empty thimble (g) = A, the mass of the thimble and sample (g) = B, and the mass of the thimble and sample after extracting (g) = C.
Oil extractionThe collected 5 kg seeds of P. maderaspatensis were cleaned to eliminate dust and other contaminants using tap water first, then deionized water, and then dried in an oven at 55°C to eliminate moisture for 4 h. An oil expeller was used to extract oil from seeds. The yield of P. maderaspatensis seed oil was calculated by Equation (4) (Munir, Ahmad, Saeed, et al., 2019).[Image Omitted. See PDF]
Determination ofJust before the synthesis of biodiesel, the FFA contents of P. maderaspatensis seed oil were ascertained using an acid-based titration technique for the determination of single or double-stepped reaction by using Equation (4). Briefly, a 0.025 M solution of KOH was impregnated dropwise in a flask containing 10 mL of isopropanol and a few drops of phenolphthalein as an indication for blank titration. When titrating a sample, a known quantity of PMSO was used with 9 mL of isopropanol and a few drops of phenolphthalein. This process was done thrice to calculate the mean FFA content of PMSO using Equation (5) (Ahmad et al., 2017).[Image Omitted. See PDF]
Protocol and chemistry behind the green catalytic synthesis of biodiesel usingTransesterification of PMSO was carried out by using green chromium oxide NPs. Filtered P. maderaspatensis seed oil was transesterified in a three-necked 250-mL round-bottom flask, in which reactions took place with a magnetic stirrer, reflux with a water condenser, and a digital thermostat. Primarily, methoxide was produced by methanol and the catalyst (0.03–0.15 g) on continuous stirring (600 rpm) at 65°C for 40 min. Second, the preheated 5 mL of P. maderaspatensis seed oil was mixed with the produced methoxide ions at a temperature of 70–110°C and a time varying from 60 to 210 min. After the reaction was finished, the catalyst, glycerol, and PMSO methyl esters (PMSOME) were removed from the mixture by spinning it for 10 min at 4000 rpm and stored for further characterization. The yield (%) was calculated using the given Equation (6) (Moreira et al., 2020).[Image Omitted. See PDF]
Characterization of biodieselThe P. maderaspatensis biodiesel was examined using a gas chromatography-mass spectrometer by making a dilution with n-hexane (1:3) to make sure that the oil had been converted to its fatty acid methyl esters and other contaminants. Using FTIR spectroscopy with a wavelength of 4000–400 cm−1, the functionalities present in PMSO as well as PMSOME were identified. For the conformation of effective biodiesel production from P. maderaspatensis seed oil, the NMR (1H and 13C) of P. maderaspatensis biodiesel was generated at 300 MHz and 75 MHz with the aid of a nuclear magnetic resonance spectrometer and deuterated chloroform solvent from Chemistry department, QAU. The PM fuel's physical qualities were ascertained, including color, flash point, pour point, density, cloud point, kinematic viscosity, cetane number, sulfur content, and acid number. The fuel properties of synthesized biodiesel (B100%) were ascertained using International biodiesel standards (American [ASTM D-6751], China [GB/T 20828], and European [EN-14214]).
Recyclability of nanocatalystRepetitive transesterification experiments were conducted under optimum experimental parameters, such as CH3OH: oil (9:1), nanocatalyst amount (0.135 wt.%), time set point (150 min), and temperature set point (80°C), to assess the capacity of chromium oxide nanoparticles. After the catalyst was separated from the reaction medium, 20 mL of C6H14 was added to the catalyst, and then centrifugation was done at 4000 rpm for 15 min. To completely separate non-polar or polar compounds from the upper layer of the separated nanomaterials, it was rinsed thrice and then evaporated overnight at 65°C in the oven. Nanoparticles were calcinated at 500°C for 3 h in a furnace. Thenceforth, the catalyst is utilized again in another process verification cycle, so a number of tests were run to look into how the previously used catalyst was activated.
RESULTS Scanning electron microscopy of seedsThe scanning electron microscopic investigation of P. maderaspatensis seeds is shown in Figure 1a–f. The seed size of P. maderaspatensis is 1.3 × 1 × 1 mm and has a spherical-shaped, smooth texture that is light to dark brown and is networked with 8–10 longitudinal lines of tiny black granulations (Le Bourgeois & Merlier, 1995). Surface sculpturing, as shown in Figure 1c,d, is rugose with thick wall ornamentation; the anticlinal wall is irregularly thickened (Figure 1e,f); and the concave periclinal wall and the hilum are absent. The apex and base are rounded with undulating wall forming a netted appearence (Figure 1f).
Enlarge this image.FIGURE 1. Seed morphology of Phyllanthus maderaspatensis (a) and (b) LM; (c) SEM at 200 μm; (d) SEM at 50 μm; (e) 20 μm; (f) 100 μm.
The most widely used method for characterizing NPs is X-ray diffraction (XRD). The obtained spectra of XRD are interpreted, and found 10 distinct peaks were recorded at 2θ angle: 24.596°, 33.6391°, 36.2854°, 41.5558°, 50.3441°, 54.9567°, 63.725°, 65.2611°, 73.1249°, and 76.9687°, as shown in Figure 2a. The size of the Cr2O3 nanocatalyst was determined by using the Scherer equation. The average size of the crystallite measured is 27 nm (13–55 nm).
Enlarge this image.FIGURE 2. (a) XRD of green chromium oxide; (b) EDX spectra of catalyst; (c) FTIR spectra of chromium oxide; (d) SEM of chromium oxide.
To ascertain the chemical components present in a compound or material, an analysis technique called EDX is utilized. The energy-dispersive X-ray spectrum of green synthetic chromium oxide nanoparticles can be seen in Figure 2b and demonstrates that our manufactured Cr2O3 NPs contain carbon, chromium, and oxygen. The energy levels of chromium are represented by peaks at 1.2, 8.5, and 7.9 keV, while the peak for oxygen was detected at 9.8 keV. The EDX spectra of synthesized nanoparticles revealed that they were primarily made of chromium (50.07%) and oxygen (37.47%). The EDX spectrum also shows an additional peak (12.46%) connected to carbon. The phytochemicals present in the phytoextract were absorbed by the surface of Cr2O3 nanoparticles, which could be the cause of the carbon peak.
Fourier-The FTIR spectrum of green Cr2O3 nanoparticles is displayed in Figure 2c. Within the extent of 4000–400 cm−1, the Fourier-transformed spectrum of Cr2O3 nanomaterial, the characteristic patterns were observable. The spectrum reveals the presence and stretching of hydroxyl groups (-OH), with a wide point at 3835–3780 cm−1. The point at 3463 cm−1 shows the occupancy of phenolic compounds. Split water molecules absorbance band at 1621.8 cm−1. The strongest peaks of crystalline chromium oxide were observed at 657.53 and 501.4 cm−1, thus confirming that the prepared material is the nanoparticles of chromium oxide.
Scanning electron microscopic analysis (The scanning electron microscopic studies of Cr2O3 nanoparticles appear agglomerated, irregular, and round with somewhat hexagonal crystals (Figure 2d).
DRSDiffused reflectance spectroscopic analysis of synthesized nanocatalysts was performed in the 200–1200 nm wavelength range, and band gap energy was calculated from DRS data. Band gap energy (Eg) is determined by using the Kubelka Munk function, and wide band gap is evaluated, which is Eg = 3.48 eV, as shown in Figure 3a.
Enlarge this image.FIGURE 3. (a) DRS spectrum of chromium oxide; (b) the representation of the size distribution; (c) zeta potential of chromium oxide; (d) TGA mass loss curves of prepared catalyst (upper) before catalytic reaction and (lower) after catalytic reaction recovered catalyst.
The zeta potential and size distribution of Cr2O3 nanoparticles were presented in Figure 3b,c. For the suspension of Cr2O3, the outcomes showed that 168.7 and 1045 nm bigger particles agglomerated. Cr2O3 NPs had a Zeta Potential of −15.5 m, respectively (Figure 3b,c). The nanoparticles are initially stable and anionic (negatively charged) in suspension, with a value of −15.5 mV.
TGAThe stability assessment of the synthesized material was conducted using a thermogravimetric analyzer (TGA) under inert conditions, monitoring weight loss (%) across a temperature range of 40–800°C, as depicted in Figure 3d. The analysis revealed that the chromium oxide-based material exhibited a transition solely within the temperature span of 100–300°C, which corresponds to the volatilization of surface-adsorbed water molecules and the de-hydroxylation of water molecules, resulting in mass loss. Two distinct thermal transition regions were identified in the material: (a) water volatilization (below 150°C, resulting in a 4.5% mass loss) and (b) evolution of carbonaceous substances (300–450°C, leading to an 8% mass loss). Comparatively, the TGA curve for the catalyst after the reaction did not show significant differences except for a slight increase in observed mass loss.
Synthesis of methyl esters using transesterification methodMember of the Phyllanthaceae family, P. maderaspatensis seeds have an oil proportion of 35% (w/w) from thimble calculations and 34% calculated with flask calculations, and the FFA content is calculated by the titration method (blank and sample), and the resultant FFA content is 0.8722 mg KOH g−1, which confirms single-step transesterification reaction. More than 3% of the FFA level in oil is regarded as unfavorable. They require an additional stage of the primary reaction of esterification by acids, followed by transesterification. It is possible to synthesize methyl esters from P. maderaspatensis seed oil without going through the requisite prior process of acid esterification. Green chromium oxide nanoparticles were used to perform the alcoholysis of P. maderaspatensis seed oil. The best yield result of 92% is attained by optimizing the four variables with the collective effect of the catalyst to be used, the required temperature, the oil-to-methanol ratio, and time because the reactive factors consistently have an impact on the process of transesterification. The schematic representation of green nanoCr2O3 during the transesterification reaction is shown in Figure 4.
Enlarge this image.FIGURE 4. Schematic representation of Cr2O3 nanocatalyst for transesterification reaction.
So, in order to achieve the maximum biodiesel yield, it is important to examine the ideal variables for the transesterification reaction. The current study project used a central composite design (CCD) to take four variables impacting the transesterification process into account. The maximum and minimum values for these variables were oil-to-methanol ratios 1:3 to 1:12, the concentration of catalyst 0.1%–0.7%w/w, time 60–150 min, and temperature 50–110°C, as depicted in Table 1. Thirty experimental trial reactions were carried out, and the results are shown in Table 2. Figure 5 compares the yield produced from transesterification to the anticipated yield. It is determined that the estimated figures and the experimental figures are dispersed over a linear fashion, providing proof of a strong relationship between them.
TABLE 1 Central composite design (CCD) for transesterification reactions.
| Process variables | Low | High |
| Methanol:oil | 3:1 | 12:1 |
| Catalyst amount (wt.%) | 0.1 | 0.7 |
| Reaction time (min) | 60 | 150 |
| Reaction temperature (°C) | 50 | 110 |
TABLE 2 Representation of results of experimental design of PMBD.
| S/N | Variable 1 | Variable 2 | Variable 3 | Variable 4 | Result |
| A: CH3OH:Oil molar ratio | B: Catalyst loading (wt.%) | C: Reaction time (min) | D: Reaction temperature (°C) | Yield (%) | |
| 1 | 3:1 | 0.2 | 60 | 110 | 66 |
| 2 | 12:1 | 0.2 | 105 | 80 | 69 |
| 3 | 12:1 | 0.135 | 105 | 80 | 77 |
| 4 | 12:1 | 0.135 | 150 | 110 | 67 |
| 5 | 12:1 | 0.07 | 105 | 80 | 67 |
| 6 | 9:1 | 0.135 | 105 | 110 | 70 |
| 7 | 3:1 | 0.135 | 105 | 80 | 87 |
| 8 | 9:1 | 0.135 | 150 | 110 | 74 |
| 9 | 9:1 | 0.135 | 150 | 80 | 92 |
| 10 | 12:1 | 0.2 | 105 | 110 | 56 |
| 11 | 9:1 | 0.2 | 60 | 80 | 60 |
| 12 | 9:1 | 0.135 | 150 | 50 | 65 |
| 13 | 12:1 | 0.135 | 60 | 80 | 68 |
| 14 | 9:1 | 0.07 | 60 | 80 | 64 |
| 15 | 12:1 | 0.135 | 105 | 50 | 65 |
| 16 | 9:1 | 0.135 | 60 | 50 | 56 |
| 17 | 12:1 | 0.135 | 150 | 80 | 88 |
| 18 | 3:1 | 0.2 | 150 | 80 | 66 |
| 19 | 9:1 | 0.07 | 105 | 80 | 85 |
| 20 | 3:1 | 0.2 | 105 | 80 | 65 |
| 21 | 9:1 | 150 | 50 | 60 | |
| 22 | 9:1 | 0.135 | 60 | 80 | 88 |
| 23 | 9:1 | 0.2 | 105 | 80 | 65 |
| 24 | 3:1 | 0.135 | 105 | 110 | 55 |
| 25 | 9:1 | 0.07 | 150 | 50 | 63 |
| 26 | 9:1 | 0.2 | 150 | 80 | 70 |
| 27 | 9:1 | 0.135 | 60 | 80 | 85 |
| 28 | 3:1 | 0.07 | 105 | 110 | 65 |
| 29 | 12:1 | 0.07 | 150 | 80 | 70 |
| 30 | 9:1 | 0.135 | 150 | 80 | 78 |
The test model underwent analysis of variance (ANOVA), and the findings are displayed in Table 3. p-test value and F-test value were used to evaluate the relevance of the experimentally induced model and the independent variables. The ANOVA Quadric exploratory model was proven to be statistically significant with the lowest p-test value of 0.0006 (<0.05), and with a value of 3.20, the F-test value is not significant. The lack of fit F-value of 3.20 implies that the lack of fit is not significant relative to the pure error. There is a 10.54% chance that a lack of fit F-value this large could occur due to noise. The most relevant quadratic factors were reaction time (D2), with a p-value of 0.0084 followed by D with a p-value of 0.0100, and methanol-to-oil molar ratio with the cumulative impact of reaction time (AB). The p-test type value is 0.0154, which is less than 0.05. The anticipated R2 value is 0.6369, which is pretty near to the adjusted R2 value of 0.6947 with a standard deviation of 0.05 and was used to assess the precision and accuracy. The signal-to-noise ratio is measured with enough precision. A ratio of at least 4 is preferred. Our signal is powerful enough based on the ratio of 5.546. To move around the design layout, this model can be utilized. The depiction of the polynomial function used for the quadric model is in Equation (7), adopted from Munir, Ahmad, Saeed, et al. (2021).[Image Omitted. See PDF]
TABLE 3 ANOVA for the response surface quadratic model.
| Source | Sum of squares | Df | Mean square | F-value | p-value | Remarks |
| Model | 2128.67 | 14 | 152.05 | 2.35 | 0.0060 | Significant |
| A-Methanol-to-oil molar ratio | 18.43 | 1 | 18.43 | 0.2850 | 0.0013 | |
| B-Catalyst loading | 26.11 | 1 | 26.11 | 0.4037 | 0.0348 | |
| C-Reaction time | 11.27 | 1 | 11.27 | 0.1742 | 0.0223 | |
| D-Reaction temperature | 5.23 | 1 | 5.23 | 0.0808 | 0.0100 | |
| AB | 14.25 | 1 | 14.25 | 0.2204 | 0.0455 | |
| AC | 138.54 | 1 | 138.54 | 2.14 | 0.0240 | |
| AD | 13.41 | 1 | 13.41 | 0.2073 | 0.0154 | |
| BC | 27.56 | 1 | 27.56 | 0.4260 | 0.0238 | |
| BD | 33.11 | 1 | 33.11 | 0.5119 | 0.0453 | |
| CD | 66.05 | 1 | 66.05 | 1.02 | 0.0283 | |
| A 2 | 104.53 | 1 | 104.53 | 1.62 | 0.0230 | |
| B 2 | 374.72 | 1 | 374.72 | 5.79 | 0.0294 | |
| C 2 | 97.63 | 1 | 97.63 | 1.51 | 0.0382 | |
| D 2 | 593.89 | 1 | 593.89 | 9.18 | 0.0084 | |
| Residual | 970.30 | 15 | 64.69 | |||
| Lack of fit | 839.30 | 10 | 83.93 | 3.20 | 0.1054 | Not significant |
| Pure error | 131.00 | 5 | 26.20 | |||
| Cor total | 3098.97 | 29 |
Note: R2 = 0.7869, SD = 8.04, C.V. % = 11.43, Adeq precision = 5.5460.
Impact of optimized parameters on transesterification3D response surface plots of the quadric model have been attained through response surface methodology (RSM) shown in Figure 6a–f. That supports the knowledge of how different factors interplay to establish the ideal proportions per each parameter for the best response. Six interactions were designed for the combined effect of variables.
Mutual effect of methanol-to-oil molar ratio and catalyst loading (wt.%)The combined effect of methanol:oil and catalyst loading is depicted in a 3D plot in Figure 6a and shows a significant influence on transesterification with a p-value of 0.0455 in ANOVA. The highest yield of 92% was attained at Run 9 (Table 2) on 9:1 methanol:oil and catalyst loading of 0.135 wt.% while the other two variables were kept constant (150 min and 80°C). Increasing the molar ratio up to 12:1 and decreasing the catalyst loading to 0.07 wt.% of the yield reduced to 70% in Run 29, as shown in Table 3. In Run 26, decrease in methanol:oil to 9:1 and increase the amount of catalyst loading to 0.2 wt.% keeping the other two variables constant, the yield was reduced from the optimized Run. On the further decrease in methanol:oil to 3:1, in Run 18, and increased catalyst loading of 0.2 wt.%, the yield was reduced to 66% (Table 3).
Enlarge this image.FIGURE 6. (a–f) A graphical representation of the mutual interactions of reaction parameters in PMBD.
A 3D graphic b in Figure 6b represents the relationship between the methanol-to-oil ratio and the reaction time. In the combined effect of methanol:oil ratio and reaction time, two factors were constant with 0.135 wt.% concentration of catalyst and Reaction temperature 80°C. The highest yield is attained at run 9 with a yield of 92% with optimized 9:1 methanol:oil and 150 min time. The biodiesel yield was reduced to 88% when the reaction time was reduced to 60 min with methanol:oil as depicted in Table 2 (Run 22). When the molar ratio reached its lowest value of 3:1 at 105 min, the yield in Run 7 would fall to 87%. Higher methanol:oil molar ratio (12:1) with a time of 60 min at Run 13 results in a reduced yield of 68 wt.% while keeping both other factors are held persistent. This interaction is found to be significant with a p-value of 0.0240 (<0.05) between methanol:oil ratio and reaction time (Table 3).
Mutual effect of methanol-to-oil molar ratio and reaction temperature (°C)The united effect of both methanol:oil and the reaction temperature is depicted in a 3D plot in Figure 6c and shows the significance of both these factors with the p-value of 0.0154 (Table 3). In run 17 Table 2, by increasing the methanol-to-oil ratio to 12:1 and temperature 80°C at a constant time of 150 min and catalyst loading of 0.135 wt.%, the yield of biodiesel was 88%. At the same methanol-to-oil molar ratio, the temperature was enhanced to 110°C temperature, and the catalyst concentration and the reaction time were constant; the yield was reduced to 67% (Run 4). The temperature was reduced to 50°C at a 9:1 methanol-to-oil ratio in run 12 (Table 2). Other variables were kept constant (catalyst loading 0.135 and reaction time 150 min) the product amount was reduced to 65%. It is concluded that the relationship between temperature and the oil-to-methanol ratio is significant.
Mutual effect of catalyst loading and reaction time (min)In transesterification, catalyst dosage and reaction time are both crucial. Figure 6d shows the interaction of catalyst amount and the reaction time in the form of a 3D plot. The influence of these varying parameters is comparable to the yield of biodiesel. The yield of biodiesel grew as reaction temperature and catalyst dosage increased until optimal parameters were achieved. The highest yield of 92% was achieved on catalyst loading of 0.135 wt.% and 150 min reaction time in Table 2, run 9. Methanol-to-oil molar ratio and temperature are kept static (9:1 and 80°C) in this combined relation of catalyst concentration and reaction time on transesterification. The quantity of catalyst was reduced to 0.07 wt.% in run 14 with the reduction of time to 1 h, and the achieved yield was 64%. By keeping the catalyst concentration the same and the time increased up to 105 min, the yield was enhanced to 85% (Run 19). In run 14, the reaction time was insufficient for the proper reaction to give a high yield. Run 11 was performed with an increasing quantity of catalyst to 0.2 wt.% with a reaction time of 1 h, resulting in a poor product yield of 60%. The reaction time was increased to 105 min in run 23, and the catalyst concentration was kept the same at 0.2 wt.%; the output was slightly enhanced to 65%. If we increase the catalyst amount from the optimal value, the yield will be reduced. ANOVA Table 3 confirms the significance of the combined interaction of catalyst loading and time for transesterification through p-value, which is 0.0238 and in the significance region.
Mutual effect of catalyst loading and reaction temperature (°C)A 3D graph plot of the relationship between catalyst loading and temperature on the transesterification reaction is shown in Figure 6e. With the constant methanol:oil (9:1) and time (150 min), the highest yield obtained was 92% with 0.135 wt.% catalyst concentration and 80°C temperature, as shown in Table 2, run 9. In run 8, the methanol-to-oil ratio (9:1), time (150 min), constant catalyst concentration, and temperature were optimized. The reaction temperature was enhanced to 110°C, and the catalyst was used at 0.135 wt.%; the product yield of biodiesel was reduced to 74%. In run 12, the catalyst concentration was the same as in run 8, and the reaction temperature was reduced to 50°C; the yield was further reduced to 65%. Both high and low temperatures from the optimal temperature reduced the experimental yield of biodiesel at a catalyst concentration of 0.135 wt.%. Decreasing the catalyst concentration to 0.07 wt.% and temperature at 50°C on constant time and methanol-to-oil ratio in run the yield achieved of 63%. In run 21, keeping the temperature same as run 25 and the amount of catalyst to 0.2 wt.% with constant time (150 min) and methanol-to-oil ratio (9:1), the yield further decreased to 60%. So, the mutual effect of catalyst loading and reaction temperature are both factors that affect the yield during the transesterification process, and hence, the relationship is significant, which is also proved by the p-value of 0.0453 in ANOVA Table 3.
Mutual effect of time (min) and reaction temperature (°C)The combined impact of the time period and the heating temperature is plotted in a 3D model in Figure 6f. The forward reaction takes place up to heating of 80°C and with a reaction period of 150 min, yielding the maximum amount of bio-based diesel of 92% with constant CH3OH:oil (9:1) and catalyst amount (0.135 wt.%) as mentioned in run 9, Table 2. In run 6, the hydrolytic chemical reaction of biodiesel, which is accelerated by elevated temperature (110°C) and reaction period (105 min) in the reaction mixture, acids and polar methanol are formed and results in an alleviation of biodiesel output up to 70% (with constant methanol:oil and catalyst concentrations of 9:1 and 0.135 wt.%, respectively). With the decrease in time to 60 min as well as heat to 50°C in run 16, a low yield of the CCD model design was attained of 56% with 9:1 and 0.135 wt.%, methanol:oil and catalyst concentration. In run 27 at the same time as in run 16 (60 min) with methanol:oil (9:1) and catalyst (0.135 wt.%) and the temperature of 80°C, the yield was enhanced to 85%. The ANOVA findings (Table 3) showed that the mutual impact of heat and time period (CD) on methyl esters yield has a p-value of 0.0283, which is less than 0.05 and is significant.
Characterization of biodiesel Nuclear magnetic resonance spectrometry (The illustrated 1H-NMR spectrum is shown in Figure 7. In this spectrum characteristic point of 3.61 ppm, singlet methoxy proton (-OCH3) is observed, which confirms that the sample of biodiesel exhibits ester formation. There are no undesired peaks for methanolic impurity that frequently showed up at 3.45 ppm, which shows the clarity of manufactured bio-based diesel. Triplet appeared at 1.55–1.99 ppm with a coupling constant 3J = 6.6 Hz, indicating the presence of alpha-methylene (-CH2-) protons. Triplet appeared at 0.87–0.93 ppm with a coupling constant 3J = 7.8 Hz, indicating the presence of methyl protons at the terminal (-CH3). The potent triplet visible at 2.23–2.28 ppm with a coupling constant 3J = 7.5 Hz indicates the presence of beta-methylene (-CH2-) protons. Multiplet appeared at 5.27 ppm, indicating the presence of olefinic protons (unsaturated moiety) in the FAME of P. maderaspatensis seed oil. The solvent (CDCl3) signal appeared in their respective region of 7.28 ppm, which is used in sample preparation. The production of FAME from P. maderaspatensis inedible oil-yielding seeds has been confirmed by examining the specifics of the described points in the spectrum of 1H-NMR. Measurement of the percent transformation of triacylglycerides into FAMES yielded a result of 92% by the given Equation (8) (Osman et al., 2023).[Image Omitted. See PDF]
Methylene and methoxy protons in methyl esters integration values are represented by the letters AMe and ACH2, respectively.
13C-NMRThe spectrum of 13C-NMR of P. maderaspatensis FAMES is illustrated in Figure 8. The structural characteristics of the synthesized biodiesel were investigated using 13C-NMR spectroscopy. In the 13C-NMR spectrum, a characteristic peak appeared at 174.0 ppm, indicating the presence of carbonyl carbon of ester (-COOCH3). The signal that appeared at 51.3 indicates the aliphatic carbon with a heteroatom, which is a methoxy carbon (-OCH3) present in the sample. The characteristic point at 127.8 ppm in the 13C-NMR spectrum represents the inside carbon atom of the unconjugated carbon and the degree of unsaturation (-CH=CH-) in methyl esters. The chemical shift of 129.6–129.8 ppm in the exterior unconjugated carbon atom (-CH=CH-) is noticeable. The characteristic signal that appeared at 14.0 ppm indicates terminal methyl carbon (-CH3). Signals appeared in the range of 22.55–33.97 ppm, representing the secondary carbon long chain of methylene carbon (-CH2-).
GC–MS
The total ion chromatogram (TIC) of FAMEs of PMBD produced using a Cr2O3 catalyst from a GC–MS study is displayed in (Figure 9). They were discovered as well as compared with reference data from the library using the NIST tool. A particular FAME is represented by each prominent peak and is confirmed via a standard library match (Table 4). The gas chromatogram of P. maderaspatensis biodiesel showed various FAME peaks. The major FAME was determined to be 9,12-octadecadienoic acid, methyl ester (18:2), with a maximum amount found with a retention period of 18.71 min. Saturated fragments in the spectrum are Octanoic acid, methyl ester (8:0), at 6.930 min; Decanoic acid methyl ester (10:0), at 10.003 min; Mistiric acid methyl ester (14:0), at 14.938 min; Hexadecanoic acid methyl ester (16:0); and Pentadecanoic acid methyl ester (15:0), at 17.066 min. Unsaturated methyl esters, including a peak of 9-Octadecenoic acid (Z)-methyl ester (18:1) at the retention time of 18.785 and 13-Docosenoic acid methyl ester (22:1) at 22.025 min, can be observed from the GC–MS spectrum.
TABLE 4 Representation of GC–MS spectrum of PMBD.
| Indication of methyl esters | Retention time | Chemical formula | Molecular weight |
| Octanoic acid, methyl ester | 6.930 min | C9H18O2 | 158.2380 |
| Decanoic acid, methyl ester | 10.003 min | C11H22O2 | 186.2912 |
| Mistiric acid methyl ester | 14.938 min | C15H30O2 | 242.3975 |
| Pentadecenoic acid, 13-methyl ester | 17.066 min | C16H32O2 | 256.42 |
| Hexadecanoic acid, methyl ester | 17.066 min | C17H34O2 | 270.4507 |
| 9,12-Octadecadienoic acid, methyl ester | 18.785 | C19H34O2 | 294.4721 |
| 9,12-Octadidecenoic acid, methyl ester | 18.711 | C19H34O2 | 294.4721 |
| 13-Docosenoic acid, methyl ester | 22.025 min | C23H44O2 | 352.5943 |
The Fourier-transform infrared spectroscopy of Phyllanthus L. seed oil and synthesized biodiesel in the infrared region (500–4000 cm−1) is shown in Figure 10a,b. Because there is no difference in the chemical composition of oils and biodiesel, the FTIR spectra of the two samples—understudy oil and synthetic biodiesel—show relatively similar band intensities and absorbance frequencies. With regard to oil, the most notable peaks were detected at 1743.23 cm−1 (C=O ester group stretch), 2853.22 cm−1 (sp3 C-H stretching), 2922.22 cm−1 (sp2 C-H stretching), 1454.63 cm−1 (scissoring bend of C-H), 1159.34 cm−1 (stretching vibration of C-O), and 721.83 cm−1 (rocking bend of C-H). In oils and biodiesel, the bending vibrational behavior of the CH2 and CH3 peaks can be seen at 1381.53, 1435.68, and 1483.58 cm−1. The oil (methyl ester group) conversion in biodiesel is shown by the most notable peak, which is absent in oil spectra and appears at 1435.68 cm−1.
Characterization of physical parameters of
Physical parameters of PMBD produced under ideal experimental variables are provided in Table 5, along with their relation to worldwide standards like American Standards, Chinese standards, and European Union Standards. PMBD fuel characteristics were discovered to be comparable to international norms. The pour and cloud points, acidic and sulfuric amounts, viscosity, fire point, and density of biodiesel fuel parameters were all examined. Biofuel made from P. maderaspatensis seed oil had a 90°C flash point with an acid value of 0.246 mg KOH g−1 (Table 5) (ASTM D-974) and is in good agreement with the values mandated by international biodiesel standards. The viscosity of PMBD is observed at 40°C, which is 5.45 (mm2 s−1), and the kinematic density of 0.8722 kg L−1 complies with international regulations, proving that using it for an engine won't have any negative effects on the ecosystem or engine efficiency. The examined value of the pour point °C of P. maderaspatensis bio-based diesel is −13°C, which lies in the worldwide standard norms. The cloud point of PMBD is −9°C, which lies within international standards. The sulfuric amount in PMBD is very less, that is, 0.00432 wt.%.
TABLE 5 Fuel properties of PMBD and comparison with international standards.
| Property | Methods | PMBD ALM-B100 | ASTM D-6751 | EN-14214 | China GB/T 20828-2007 |
| Color | Visual | 2 | 2.0 | – | – |
| Acid number (mg KOH g−1) | ASTMD- | 0.246 | ≤5 | ≤0.8 | ≤0.5 |
| Flash point (°C) | ASTMD-93 | 90 | ≥90 | ≥130 | ≥120 |
| Pour point (°C) | ASTMD-97 | −13 | −15 to 16 | – | – |
| Kinematic viscosity (mm2 s−1 at 40°C) | ASTMD-445 | 5.45 | 1.9–6.0 | – | 3.4–5.0 |
| Kinematic Density (kg m−3 at 40°C) | ASTMD-1298 | 0.8722 | ≤120 | – | 0.86–0.89 g m−3 |
| Sulfur content (wt.%) | ASTMD-4294 | 0.00432 | ≤0.05 | ≤0.05 | ≤0.20 |
| Cloud point (°C) | ASTMD-2500 | −9 | −3.0 to 12 | – | – |
The reusability of catalysts was examined and shown in Figure 11. Repeated transesterification tests were carried out under ideal experimental conditions, such as CH3OH:oil (9:1), nanocatalyst amount (0.135 wt.%), time set point (150 min), and temperature set point (80°C). After the reaction was complete, the catalyst was taken out of the system, recovered by filtration, and then subjected to a methanol wash in order to achieve the intended outcome. After that, the catalyst was baked for 4–5 h at 600°C to get rid of any last bits of moisture. The catalyst's reusability was investigated over the course of eight cycles, and the findings demonstrated that the first five recycling procedures reliably produced 95% biodiesel. Nonetheless, the yield of biodiesel did somewhat decrease from the fifth reaction to the eighth reaction.
DISCUSSION
In this study, the potential role of novel nonedible P. maderaspatensis seed oil was investigated for synthesizing sustainable biodiesel using phytofabricated chromium oxide nanoparticles derived from the waste fruit parts of aubergine. Based on the green catalyst and synthesized biodiesel analysis and statistical applications, the following key observations are recapitulated.
Scanning electron microscopy ofThe scanning electron microscopy of P. maderaspatensis seeds, as shown in Figure 1a–d, exhibits remarkable features. It is crucial to correctly identify inedible oil seeds before processing them for synthesizing bio-based diesel. In this context, electron microscopy (SEM) provides an aid to unveil several important morphological features like seed shape, surface sculpturing, wall ornamentation, and some other physiological structures that form the basis of taxonomic identifications (Chaudhry et al., 2022; Munir, Ahmad, Waseem, et al., 2019). SEM has been effectively utilized for the identification of diverse plant texa coupled with anatomical features and environmental impacts that may lead to different structures. This is equally effective for the recognition and identification of micro-morphological characters in seed coats that may lead to the identification of species up to the genus level (Munir, Ahmad, Waseem, et al., 2019).
Characterization of nanocatalystPowder X-ray diffraction (XRD) is a very useful tool for providing knowledge regarding the size and phases of different particles present in solid catalysts. This may include the structure and characterization of different components while detecting the active sites of the catalyst (Schloegl, 2009). In the current work, the spectra of Cr2O3 (Figure 2a) are in line with already reported work and also confirmed with JCPDS file N0. 38-1479 (Khan et al., 2021). However, the size of the synthesized nanocatalyst was also in line with the work reported elsewhere (Khan et al., 2021; Yahyazadehfar et al., 2020).
To ascertain the chemical components present in a compound or material, an analysis technique called EDX (Figure 2b) is utilized. These tests confirmed the presence of chromium (50.07%) and oxygen (37.47%). The phytochemicals present in the phytoextract were absorbed by the surface of Cr2O3 nanoparticles, which could be the cause of the carbon peak. Our results correlate with earlier studies (Khan et al., 2021; Tsegay et al., 2021). The FTIR spectrum of green Cr2O3 nanoparticles (Figure 2c) depicts the presence of the strongest peaks of crystalline chromium oxide observed at 657.53 and 501.4 cm−1, thus confirming that the prepared material is the nanoparticles of chromium oxide. These results are also in line with the reported work (Khan et al., 2021). Scanning electron microscopic investigation was used to ascertain the sizes and morphology of synthesized catalysts. The SEM images of Cr2O3 nanocatalysts (Figure 2d) were somehow similar to the work reported previously (Ahmad et al., 2022), depicting the spherical morphology of the catalyst.
Diffused reflectance spectroscopic analysis (Figure 3a,b) of Cr2O3 nanocatalyst was evaluated to determine the phytoconstituents in charge of reducing metal salt to its nanostructures and to calculate the band gap for the samples. Band gap energy (Eg) is determined by using the Kubelka Munk function (Weckhuysen et al., 1997). The observed wide band gap is (Eg = 3.48 eV), which is a very important property for determining the suitability of optoelectronic applications and any catalyst and reactivity as well (Tsegay et al., 2021).
The zeta potential and size distribution of Cr2O3 nanoparticles (Figure 3c) were measured using a Malvern Zetasizer Ver. 8.00.4813. By using a Malvern Zetasizer Ver. 8.00.4813, the size distribution and zeta-potentials (ZP) of thermally annealed green synthesized Cr2O3 NPs were found. For the suspension of Cr2O3, the outcomes showed that 168.7 and 1045 nm bigger particles agglomerate. The Zeta Potential analysis is dependent on the particle movement that occurs underneath an electric field. A usual intuitive conclusion holds that repulsion must be sufficient to prevent agglomeration when the zeta potential ranges between −30 and +30 mV (Clogston & Patri, 2011; Serrano-Lotina et al., 2023). All of these results of characterization supported the green synthesis of the targeted Cr2O3 nanoparticles.
The stability assessment of the synthesized material (Cr2O3 NPs) was conducted using a thermogravimetric analyzer (TGA) (Figure 3d) under inert conditions, monitoring weight loss (%) across a temperature range of 40–800°C. The TGA curve for the catalyst after the reaction did not show significant differences except for a slight increase in observed mass loss. These findings unequivocally validate the stability of the catalyst both before and after the reaction (Alexzman et al., 2022).
Biodiesel synthesis and statistical analysisThe seed oil of P. maderaspatensis was successfully transesterified using methanol and green nano Cr2O3 catalyst (Figure 4). The seeds of P. maderaspatensis seeds possess very low FFA content (0.8722 mg KOH g−1), thus allowing a single-step transesterification reaction (Athar et al., 2022). The highest biodiesel yield of 92% was achieved under ideal conditions, thus confirming the suitability of feedstock to overcome energy issues. Our work is in line with the reported work done on the vast variety of nonedible oil seeds and green nanocatalysts (Akhtar et al., 2023; Jabeen et al., 2022).
The synthesized biodiesel from P. maderaspatensis seed oil was optimized statistically (Figure 5, Tables 1 and 2) using central composite design, followed by investigating the influence of combined parameters on the final biodiesel yield (Figure 6a–f) (methanol:oil and catalyst loading, methanol-to-oil ratio and the reaction time, methanol:oil and the reaction temperature, catalyst dosage and reaction time, catalyst loading and temperature, time period, and the heating temperature). In all these cases, the biodiesel yield increases (92%) using ideal reaction conditions like 9:1 methanol-to-oil ratio, 0.135 wt.% catalyst concentration, and a reaction duration of 150 min at 80°C. Similar work was also reported in previously reported work (Maleki et al., 2024).
A sudden drop in yield was observed as the conditions deviated from the ideal conditions. It has been demonstrated that raising the catalyst quantity caused undesirable byproducts to form, which decreased the output of biodiesel (Kumar et al., 2020). The bidirectional steps of glycerolysis take place, which results in the restoration of monoglycerides in the reaction by mixing glycerol with the produced methyl ester; ultimately, the yield of biodiesel reduces (Akhtar et al., 2023; Munir, Ahmad, Saeed, et al., 2019). Likewise, by reducing the reaction time and temperature, a similar drop in yield was also seen. This is probably due to the fact that there wasn't enough time for the reaction to react properly, which resulted in insufficient output (Elkelawy et al., 2020). The solubility of glycerol was enhanced (Rahman et al., 2022), and it became more challenging to separate it from synthetic biodiesel when the quantity of alcohol (CH3OH) was raised above a predetermined range (Munir, Ahmad, Saeed, et al., 2021).
It is attributed to the increased interaction of triglycerides with extra alcohol during transesterification (Abbasi et al., 2023), which may reduce the biodiesel yield. Considering heterogeneous catalysts usually have specificity in availability and require intense heat to work (Vogt & Weckhuysen, 2022), the reaction temperature represents one of the crucial factors in the generation of bio-based diesel using these catalysts. Enough time was needed for the catalyst to engage properly in order for transesterification to achieve its equilibrium state (Foroutan et al., 2021). All these factors, therefore, play a crucial role in improving the biodiesel yield, and abrupt changes in any condition may cause a halt of reaction, thus minimizing the conversion efficiency of oils to biodiesel.
Characterization of biodieselNuclear magnetic resonance spectral analysis is excellent for analyzing biofuels. After transesterification, it is utilized to characterize different important components of manufactured biodiesel (Doudin, 2021). In accordance with the existence of various indications in the nuclear magnetic resonance, 1H and 13C-NMR, two important spectral approaches, are used to track the transesterification activity (Ahmad et al., 2023). 1H NMR spectroscopy (Figure 7) was used to evaluate and characterize the conversion of Phyllanthus seed oil to biodiesel. The quantification of biodiesel conversion rate was calculated by counting the relative number of hydrogens present in targeted groups like the methoxy group present in methyl esters at 3.45 ppm and αcarbonyl methylene at 2.23–2.28 ppm with a coupling constant 3J = 7.5 Hz. Similarly, in 13C-NMR (Figure 8), a characteristic peak appeared at 174.0 ppm, indicating the presence of carbonyl carbon of ester (-COOCH3). All the peaks observed in 1H and 13C-NMR (Figures 7 and 8) spectra are in line with already reported work (Braga et al., 2024; Jan et al., 2022).
The chemical makeup, architectural design, and form of FAMEs in PMBD can be identified via GC spectroscopic analysis (Figure 9, Table 5; Sarkar et al., 2022). The majority of biodiesel's important fuel qualities are highly dependent on the different fatty acid compositions of the oil source used to create it (Yaşar, 2020). Thus, further research into the fatty acid composition of biodiesel is required. The viscosity and cetane number of biodiesel fuel are significantly influenced by its quality and chemical composition, specifically the degree of saturation and unsaturation (Folayan et al., 2019). Eight different types of FAMEs were reported in Phyllanthus biodiesel, which is similar to the already reported work on different feedstocks (Sienkiewicz et al., 2020). However, unsaturated fatty acids are also less in the synthesized biodiesel, which is indicative of the smooth burning of biodiesel in the automobile engine without producing any knocking (Zhang et al., 2022).
FTIR (Figure 11a,b) of Phyllanthus oil and biodiesel shows different types of functional groups. However, the most distinctive band appears at 1435.68 cm−1 in biodiesel spectra, corresponding to the methyl ester group, which is absent in oil spectra. Among all the peaks, the carbonyl group area has been considered by earlier research to be the most susceptible to changes in chemical and molecular structure (Das et al., 2023). Similar bands were observed in already reported work, thus confirming the conversion of Phyllanthus seed oil to biodiesel (Munir et al., 2023).
Fuel propertiesBiodiesel quality requirements are necessary for their commercial use because they may impair engine reliability and efficiency. All biodiesel standards typically set boundaries that are lower and higher (Munir et al., 2023). Table 5 shows the fuel properties of Phyllanthus biodiesel, and all the fuel properties are in good agreement with the international biodiesel standards. The potential of a fuel to ignite when mixed with oxygen from the atmosphere is measured by the fire (flash) point. Because biodiesel has a greater ignition point than regular petroleum, it is simpler to handle, store, and carry off (Ameen et al., 2022). Fuels with increased flash points reduce the chance of unintentional fires and guarantee a secure environment. The ASTM-D93 approach was used to assess the flash points and compare them with international standards (Table 5).
The acid number is an important attribute of biodiesel, which has a deleterious influence on the quality of the engine. The acid figure represents the percentage of FFAs in the sample. More free fatty acids present, a greater acid value, and less free fatty acids, an acid number will be lower (Munir, Ahmad, Saeed, et al., 2021). The kind of substrate utilized, the manufacturing procedure, and the degree of refining in the manufacturing of bio-based diesel all have an impact on it. When methyl ester (C2H3O2R) linkages are hydrolyzed during preservation, the number of acids can expand (Doudin, 2021). Therefore, Phyllanthus biodiesel (Table 5) acid number, due to its close match with international standards, in engine friendly too.
Kinematic viscosity is the difficulties of a solution exhibited for gravitational movement at 40°C. Kinematic viscosity is among the significant components of fuel and is fundamental to the production of the mixtures, the spraying of the fuel, and the subsequent combustion process. The overall fuel particle diameter and permeation out from the nozzle grow as kinematic viscosity rises (Choi & Reitz, 1999). Because fuel with greater viscosities leads to problems in cooler temperatures, viscosity rises with lowering air conditions (Ahmad et al., 2023). The kinematic viscosity of Phyllanthus biodiesel enables it to burn completely without releasing any harmful gases into the ecosystem that may cause climatic changes and other health issues.
The density of the produced biodiesel is also within the safe line of international standards (Table 5), thus determining how well the atomization process works (Ryan et al., 1984). The proportion of fuel to air in the ignition chamber of the engine is significantly influenced by kinematic density. In the presence of a significant amount of unsaturation, FAMEs have a greater density proportion. On the other hand, a longer carbon chain results in a lower fuel density. Biodiesels are more dense than fossil-based diesel (Alsaiari et al., 2022). The cold flow qualities known as pour as well as cloud points provide knowledge regarding the fuel at low temperatures and are highly influenced by the kind of oils utilized for the manufacturing of methyl esters as well as the amount of saturation in them. The lowest temperature at which the fuels can be sensed is referred to as the pour point (Klaassen & Amdur, 2013). When paraffin crystallizes, it separates from the residual solution in fuel that is so cold that it appears as a hazy and milky material. This temperature is recognized as the cloud point. Poor fuel characteristics are indicated by a greater cloud point (Munir, Ahmad, Saeed, et al., 2019), and these values in understudy biodiesel are sufficient enough to tackle cold temperature-related issues.
Sulfur concentration in biodiesel is a result of either the dehydrating agent or the nanocatalyst that was utilized. Unlike opposed to fossil diesel, which contains a sulfur concentration of 50 ppm and releases sulfur oxides, which pollute the atmosphere, biodiesel has an ultra-low sulfur content of 1 ppm, making it the preferable fuel. Biodiesel with a low sulfur concentration significantly extends the durability of engines and is environmentally friendly (Anwar et al., 2010).
Catalyst reusability testSince reusable catalysts reduce costs and accelerate production, they are critical to the industrial synthesis of biodiesel. It is easy to separate the reaction mixture once it is completed if there is a solid nanocatalyst present in both phases. However, it's important to keep in mind that the catalyst used and the separation methods employed determine the efficacy and reaction rate of a recycled catalyst (Munir, Ahmad, Mubashir, et al., 2021). The reusability of catalysts was examined and shown in Figure 11. The catalyst was found to be active up to four cycles without a drop in biodiesel yield; however, after this, a drop in yield was observed. This drop in yield is attributed to surface poisoning and pore-filling by triglycerides and glycerol, as well as the catalyst's solubility in methanol, which might result in catalyst loss during recovery (Munir et al., 2023). In summary, catalyst reusability plays a critical role in the production of biodiesel. When both phases of the reaction mixture contain a solid nanocatalyst, separation is easier after the reaction is complete. The catalyst's performance and reaction rate are influenced by the specific kind of catalyst used as well as the separation methods employed.
CONCLUSIONSThe current work is based on one of the major current problems of the fuel crisis, to help and resolve the world's and Pakistan's energy issues in particular. In this investigational project, two nonedible seed oil plant species are carefully examined morphologically. Green nanocatalysts of chromium oxide nanoparticles (waste fruit extract of Solanum melongena) were used to synthesize biodiesel via novel nonedible oil seeds of P. maderaspatensis. These plants can flourish on unused and neglected sites. The nonedible seed oils of P. maderaspatensis used in the project have an oil proportion of 35% (w/w), and FFA proportions of 0.8722 KOH g−1. They can reduce emissions of greenhouse gases (GHGs) because they are a renewable, bio-sustainable energy resource that emits fewer particulates and oxides of nitrogen (NOx). Cr2O3 green nanoparticles proved remarkably catalytic in converting PMSO triglycerides to esters of the methyl group.
At the optimized conditions of catalyst concentration (0.135 wt.%), time duration (150 min), methanol-to-oil molar ratio (9:1), and heat of 80°C, the highest product yield is achieved at 92%. Analytical evaluation of chromium oxide nanomaterials demonstrates their purity in nature and reveals that they are nanocatalysts since they contain dynamite-sized granules and exceptional thermal endurance. The physical features of PMBD have been assessed and contrasted with the worldwide standards for biodiesel. Using these findings, we are able to determine that the novel inedible oil-yielding Madras Leaf Flower has significant potential, is sustainable, and represents a good choice for low-cost and massive bio-based diesel synthesis. It has been shown that Cr2O3 nanocatalysts produce a considerable amount of biodiesel while being extremely selective and environmentally benign. It is suggested that the findings of this research be used in the industrial development of biodiesel to overcome the fuel problems in the world, particularly in Pakistan. The current research also suggests that affordable precursors be used in the manufacture of efficient green nanocatalysts to overcome the environmental pollution caused by typical fossil fuels. Moreover, recently, more attention has been needed for the exploration of nonedible or poisonous seed plants that are easily available for the production of biodiesel.
AUTHOR CONTRIBUTIONSHadiqa Bibi: Conceptualization; data curation; formal analysis; software; supervision; validation; writing – original draft; writing – review and editing. Mushtaq Ahmad: Formal analysis; supervision; validation; visualization; writing – original draft; writing – review and editing. Ahmed I. Osman: Conceptualization; funding acquisition; investigation; methodology; resources; writing – original draft; writing – review and editing. Abdulaziz Abdullah Alsahli: Investigation; writing – review and editing. Mamoona Munir: Formal analysis; supervision; validation; visualization; writing – original draft; writing – review and editing. Ala'a H. Al-Muhtaseb: Formal analysis; visualization; writing – original draft; writing – review and editing. David W. Rooney: Funding acquisition; investigation; visualization; writing – original draft; writing – review and editing. Shazia Sultana: Investigation; resources; visualization; writing – original draft; writing – review and editing.
ACKNOWLEDGMENTSDr. Ahmed I. Osman and Prof. David W. Rooney wish to acknowledge the support of The Bryden Centre project (Project ID VA5048), which was awarded by The European Union's INTERREG VA Programme, managed by the Special EU Programmes Body (SEUPB), with match funding provided by the Department for the Economy in Northern Ireland and the Department of Business, Enterprise, and Innovation in the Republic of Ireland. The authors extend their appreciation to the Researchers Supporting Project number (RSPD2023R678) at King Saud University, Riyadh, Saudi Arabia.
CONFLICT OF INTEREST STATEMENTThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
DATA AVAILABILITY STATEMENTData will be made available by corresponding author upon reasonable request.
DISCLAIMERThe views and opinions expressed in this paper do not necessarily reflect those of the European Commission or the Special EU Programmes Body (SEUPB).
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; Abdulaziz Abdullah Alsahli 4 ; Munir, Mamoona 5 ; Ala’a H. Al-Muhtaseb 6 ; Rooney, David W 3 ; Sultana, Shazia 1 1 Department of Plant Sciences, Quaid-i-Azam University, Islamabad, Pakistan
2 Department of Plant Sciences, Quaid-i-Azam University, Islamabad, Pakistan; College of Life Science, Neijiang Normal University, Neijiang, Sichuan, China
3 School of Chemistry and Chemical Engineering, Queen’s University Belfast, Belfast, Northern Ireland, UK
4 Department of Botany and Microbiology, College of Science, King Saud University, Riyadh, Saudi Arabia
5 Department of Plant Sciences, Quaid-i-Azam University, Islamabad, Pakistan; Department of Botany, Rawalpindi Women University, Rawalpindi, Pakistan
6 Department of Petroleum and Chemical Engineering, College of Engineering, Sultan Qaboos University, Muscat, Oman; Sustainable Energy Research Centre, Sultan Qaboos University, Muscat, Oman