Production of biodiesel from Aspergillus terreus KC462061 using gold-silver nanocatalyst

Figures & data

Table 1. The main variables and the related three levels.

Level	X1*	X2	X3	X4	X5
−1	1:2	0.5	5	60	20
0	1:1	1	6	90	25
+1	2:1	1.5	7	120	30

^a X₁, X₂, X₃, X₄ and X₅ refer to ratio of AgNO₃/HAuCl₄.3H₂O, amount of fungal cell-free (mL), pH of solution, reaction time(min), reaction temperature, respectively.

Table 2. Factors affecting lipid production and their levels.

Factors	Level
	−1	0	+1
Glucose (Y1), g	30	40	50
Peptone (Y2), g	1	1.5	2
NaCl (Y3), g	0.5	1.0	1.5
Na2HPO4 (Y4)	4	6	8
pH (Y5)	5.0	5.5	6
Incubation temperature (Y6), °C	25	28	31
Incubation time (Y7), d	4	5	6

Table 3. The main variables and the corresponding three levels affecting biodiesel production.

Level	Z1*	Z2	Z3	Z4
−1	2	15:1	25	60
0	3	20:1	30	65
+1	4	25:1	35	70

^a Z₁, Z₂, Z₃, and Z₄ refer to amount of nanocatalyst (%), methanol/oil ratio (mole/mole), reaction time (min), reaction temperature (°C), respectively.

Figure 1. Description of changes in color during the biosynthesis of Au@Ag NPs.

Figure 2. UV–visible spectrum of Au@Ag NPs biosynthesized by A. terreus KC462061

Figure 3. TEM image showing the morphology of Au@Ag NPs.

Figure 4. XRD pattern analysis of Au@Ag NPs.

Figure 5. FTIR spectrum of Au@Ag NPs.

Table 4. FTIR wave numbers for different peaks of Au@Ag NPs.

S. No.	Wave Number cm^-1 Reference	Wave Number cm^-1 Au@Ag NPs	Functional Group Assignment	Compounds Identified
1	3500–3200	3361	O-H stretch	Alcohols or phenols
2	2900–2800	2915	-CH (CH2) stretch	Aliphatic compound lipids
3	2100–1800	1969	C = O frequency	Carboxylic acid
4	1700–1600	1741	C = O stretch	Aldehyde compound
5	1600–1500	1630	C = O stretching vibration	Ketone compound
6	1400–1300	1381	CN stretch	Aliphatic amines
7	1000–900	1028	N-H stretch	Primary amine of the protein
8	900–800	847	P-O-C stretch	Aromatic phosphates

Figure 6. EDS spectrum of Au@Ag NPs synthesised

Table 5. RSM matrix with experimental and predicted responses.

Run	X1*	X2	X3	X4	X5	Actual (absorbance)	Predicted (absorbance)
1	−1	0	−1	0	0	1.166	1.165
2	−1	0	+1	0	0	1.125	1.123
3	−1	0	0	0	−1	1.170	1.168
4	−1	0	0	0	+1	1.151	1.150
5	−1	0	0	+1	0	1.146	1.144
6	−1	+1	0	0	0	1.184	1.183
7	−1	−1	0	0	0	1.143	1.140
8	−1	0	0	−1	0	1.165	1.168
9	+1	−1	0	0	0	1.117	1.115
10	+1	−1	0	0	0	1.122	1.119
11	+1	+1	0	0	0	1.198	1.195
12	+1	0	−1	0	0	0.952	0.951
13	+1	0	+1	0	0	0.872	0.870
14	+1	0	0	−1	0	0.926	0.924
15	+1	0	0	+1	0	1.245	1.243
16	+1	0	0	0	+1	1.211	1.208
17	0	+1	+1	0	0	0.904	0.908
18	0	+1	0	0	−1	0.846	0.845
19	0	+1	0	+1	0	0.931	0.930
20	0	+1	0	−1	0	0.969	0.968
21	0	0	−1	+1	0	0.971	0.970
22	0	0	+1	+1	0	1.123	1.122
23	0	0	−1	0	+1	1.162	1.160
24	0	0	0	0	0	1.471	1.469

^a X₁, X₂, X₃, X₄ and X₅ refer to ratio of AgNO₃/HAuCl4.3H₂O, amount of fungal cell-free (mL), pH of solution, reaction time(min), reaction temperature, respectively.

Table 6. ANOVA values and statistical analysis by response surface model fitting.

Source	Sum of squares	Df	Mean square	F-value	p-value
Block	53.11	1	53.11
Model	907.42	15	60.494	9.41	0.0032	significant
X1	3.51	1	3.51	0.014	0.0057
X2	6.19	1	6.19	0.098	0.0045
X3	5.81	1	5.81	0.056	0.0021
X4	8.23	1	8.23	0.084	0.0082
X5	7.04	1	7.04	0.038	0.0014
X1X2	125.76	1	125.76	2.395	0.0144
X1X3	147.39	1	147.39	3.145	0.0393
X1X4	135.57	1	135.57	5.847	0.0340
X1X5	165.11	1	165.11	6.651	0.0191
X2X3	156.62	1	156.62	5.218	0.0215
X2X4	141.38	1	141.38	7.223	0.0177
X2X5	162.19	1	162.19	6.571	0.0287
X3X4	191.27	1	191.27	5.754	0.0211
X3X5	174.90	1	174.90	6.823	0.0282
X4X5	159.49	1	159.49	6.316	0.0191
X1^2	179.09	1	179.09	8.665	0.0183
X2^2	161.17	1	161.17	7.254	0.0231
X3^2	156.89	1	156.89	6.183	0.0135
X4^2	168.78	1	168.78	5.413	0.0168
X5^2	174.24	1	174.24	6.715	0.0197
Residual	341.02	15	22.734
Lack of fit	45.24	5	9.048	0.2631	0.7863	Not significant
Pure error	312.83	4	78.207
Regression analysis of Au@Ag NPs biosynthesis
R^2		0.6651
Adjusted R^2		0.4178
Predicted R^2		0.2732
Adeq Precision		4.5096

Table 7. Comparison between experimental and estimated lipid production.

Run	Factors							Lipid (% of dry biomass)		Error (%)
	Y1	Y2	Y3	Y4	Y5	Y6	Y7	Experimental	Estimated
1	−1	−1	−1	−1	−1	−1	−1	16.71	16.68	0.084
2	−1	+1	+1	−1	−1	−1	−1	19.50	19.48	0.088
3	−1	−1	−1	0	0	−1	−1	22.41	22.37	0.119
4	−1	+1	−1	0	0	+1	+1	19.29	19.27	0.091
5	−1	+1	+1	0	0	+1	+1	20.81	20.78	0.123
6	−1	0	+1	−1	+1	−1	−1	29.69	29.65	0.139
7	−1	0	−1	+1	+1	+1	+1	17.05	17.03	0.114
8	0	0	0	0	0	0	0	19.63	19.59	0.109
9	0	0	−1	0	−1	0	0	18.57	18.55	0.098
10	0	−1	1	−1	0	−1	−1	23.46	23.44	0.121
11	0	−1	−1	0	0	+1	0	18.94	18.95	0.081
12	0	+1	1	−1	−1	0	+1	17.87	17.85	0.099
13	0	−1	−1	−1	0	−1	−1	20.61	20.59	0.096
14	0	0	1	−1	+1	0	0	19.85	19.82	0.117
15	1	+1	+1	+1	+1	+1	+1	18.11	18.08	0.118
16	1	0	+1	−1	0	−1	0	23.71	23.69	0.126
17	1	0	0	−1	+1	0	+1	20.43	20.40	0.124
18	1	−1	0	+1	−1	0	0	17.09	17.06	0.121
19	1	0	0	−1	+1	−1	−1	41.86	41.83	0.122
20	1	+1	−1	0	0	−1	+1	22.39	22.35	0.129
21	1	+1	−1	−1	0	+1	0	19.37	19.33	0.137

Table 8. The optimal variables at maximum lipid production (41.83%).

Factor	Value
Glucose (Y1), g	0.439
Peptone (Y2), g	0.027
NaCl (Y3), g	0.259
Na2HPO4 (Y4)	0.335
pH (Y5)	0.005
Incubation temperature (Y6), °C	0.009
Incubation time (Y7), d	0.113

Table 9. Factors affecting biodiesel production using transesterification process.

Run order	Catalyst %	Mole ratio	Time	Temperature	Biodiesel production %	predicted
1	2	15	25	60	32.45	34.78
2	2	15	30	65	36.81	38.92
3	2	15	35	70	37.34	39.72
4	2	15	25	65	35.29	37.57
5	2	15	25	70	36.41	38.48
6	2	20	30	65	38.13	40.41
7	2	20	35	70	41.37	43.69
8	2	20	30	70	40.28	42.35
9	2	20	35	65	41.59	43.96
10	3	20	30	65	42.21	43.74
11	3	20	35	70	40.39	41.68
12	3	20	30	70	43.28	44.69
13	3	20	35	65	39.57	40.95
14	3	15	25	60	37.11	38.63
15	3	15	30	60	36.45	37.83
16	3	25	35	70	31.67	32.35
17	3	25	30	65	33.51	34.84
18	3	25	35	60	32.91	33.21
19	4	25	35	70	30.36	31.67
20	4	25	30	65	31.05	32.46
21	4	25	25	60	29.35	30.03
22	4	20	30	65	27.61	28.16
23	4	20	30	70	35.58	36.02
24	4	20	35	65	27.19	28.78
25	4	15	25	60	25.48	26.97
26	4	15	30	65	26.87	27.26
27	4	15	35	70	27.96	28.43

Table 10. ANOVA for response surface methodology.

Factor	P value
amount of nanocatalyst (%) (Z1)	0.008
methanol/oil ratio (mole/mole) (Z2)	0.003
reaction time (min) (Z3)	0.041
reaction temperature (°C) (Z4)	0.029

Figure 7. GC-MS analysis of the fatty acid methyl ester mixture.

Table 11. GC-MS analysis of fatty acid esters profile.

Fatty acid	Molecular formula	Lipid number	Percentage (%)	Total FAME (%)
Myristic acid	C14H28O2	14:0	17.24	98.48
Pentadecanoic acid	C15H30O2	15:0	10.34
Palmitic acid	C₁₆H₃₂O₂	16:0	18.69
Searic acid	C18H36O2	18:0	30.17
Oleic acid	C18H34O2	18:1	9.63
Linoleic acid	C18H32O2	18:2	12.41

Table 12. Properties of the produced biodiesel compared to international standards.

Properties	EN14214	ASTM D6751-08	A. terreus KC462061
SFAs (%)	-	-	76.44
MUFAs (%)	-	-	22.04
PUFAs (%)	-	-	1.52
kinematic viscosity (ln(kv)); mm^2/s)	3.5–5.0	1.9–6.0	3.59
Density (g/cm3)	-	0.86-0.9	0.85
Iodine Number (IN; gI2100/g oil)	≤120	-	14.78
Oxidation Stability (OS; h)	≥8	≥3	9.37
Cetane Number (CN)	≥51	≥47	73.25
Saponification Value (SV; mg KOH/g)	-	-	189.17

Table 13. Biodiesel yield from different oils using various nanocatalysts.

Catalyst	Reaction condition			Biodiesel yield (%)	Type of oil used	Reference no.
	Temperature (°C)	Time (h)	Methanol/oil molar ratio
CaO	60	5	14:1	90.0	Sunflower	(26)
TiO2-MgO	160	6	50:1	92.3	Waste cooking oil	(27)
Mg-Zn mixed metal oxide	120	3	25:1	83.1	Jatropha curcas oil	(28)
Mg-Al hydrotalcites	67	4	9:1	90.0	Soybean	(29)
BaFeNPs	45	4	4:1	89.2	Fungal lipid	(30)
magnetic nanoparticle	45	4	4:1	84.0	Fungal lipid	(31)
Au@Ag NPs	70	30 min	20:1	43.0	Fungal lipid	^a

^a Present work.

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