Conversion of Biomass-Derived Levulinic Acid into γ-Valerolactone Using Methanesulfonic Acid: An Optimization Study Using Response Surface Methodology
Abstract
:1. Introduction
2. Materials and Methods
2.1. Materials
2.2. Hydrogenation of Commercial LA into GVL
2.2.1. Effect of Temperature, Time, and Catalyst Loading on GVL Production from Commercial LA Using MsOH
2.2.2. Effect of Catalysts on GVL Yield
2.2.3. Effect of Solvent on the Production of GVL
2.3. DSB Preparation
2.4. DSB Conversion to GVL
2.4.1. Conversion of DSB to LA
2.4.2. Hydrogenation of LA Derived from DSB into GVL
2.5. Product Analysis Using High Performance Liquid Chromatography
2.6. Experimental Design
3. Results and Discussion
3.1. Effect of Temperature, Time, and Catalyst Loading for GVL Production from Commercial LA to GVL
3.2. Response Surface Methodology (RSM) Analysis
3.3. Effect of Catalysts on GVL Yield
3.4. Effect of Solvent on the Production of GVL
3.5. DSB Conversion to GVL
3.5.1. Conversion of DSB to LA
3.5.2. Hydrogenation of LA Derived from DSB into GVL
3.6. Techno-Economic Assessment of GVL Production from Sugarcane Bagasse
4. Conclusions
Author Contributions
Funding
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Factors | Range and Level | ||
---|---|---|---|
−1 | 0 | +1 | |
Time (h) | 2 | 6 | 10 |
Temperature (°C) | 25 | 112.5 | 200 |
Catalyst loading (g) | 0.5 | 2.75 | 5 |
Run | Factor 1 | Factor 2 | Factor 3 | Response | LA Conversion (%) | GVL Selectivity (%) (SGVL) |
---|---|---|---|---|---|---|
A: Time (h) | B: Temperature (°C) | C: Catalyst Loading (g) | GVL (%) (YGVL) | |||
1 | 2 | 112.5 | 0.5 | 48.6 | 66 | 74 |
2 | 6 | 112.5 | 2.75 | 78.1 | 93 | 84 |
3 | 6 | 112.5 | 2.75 | 78.6 | 97 | 81 |
4 | 10 | 112.5 | 0.5 | 52.3 | 75 | 70 |
5 | 6 | 200 | 5 | 49.1 | 72 | 68 |
6 | 6 | 112.5 | 2.75 | 77.9 | 96 | 81 |
7 | 10 | 200 | 2.75 | 39.2 | 57 | 69 |
8 | 6 | 200 | 0.5 | 39.5 | 54 | 73 |
9 | 10 | 112.5 | 5 | 58.3 | 72 | 81 |
10 | 6 | 25 | 5 | 58 | 85 | 68 |
11 | 6 | 112.5 | 2.75 | 78.3 | 95 | 82 |
12 | 2 | 25 | 2.75 | 46.7 | 70 | 70 |
13 | 6 | 25 | 0.5 | 48 | 67 | 67 |
14 | 10 | 25 | 2.75 | 45.9 | 63 | 73 |
15 | 2 | 112.5 | 5 | 61 | 87 | 70 |
16 | 6 | 112.5 | 2.75 | 78 | 98 | 80 |
17 | 2 | 200 | 2.75 | 36.1 | 59 | 61 |
Source | Sum of Squares | df * | Mean Square | F-Value | p-Value |
---|---|---|---|---|---|
GVL (R2 = 0.9998) | |||||
Model | 3785.69 | 9 | 420.63 | 4384.69 | <0.0001 |
A | 1.32 | 1 | 1.32 | 13.76 | 0.0076 |
B | 150.60 | 1 | 150.60 | 1569.84 | <0.0001 |
C | 180.12 | 1 | 180.12 | 1877.58 | <0.0001 |
AB | 3.71 | 1 | 3.71 | 38.63 | 0.0004 |
AC | 10.24 | 1 | 10.24 | 106.74 | <0.0001 |
BC | 0.0484 | 1 | 0.0484 | 0.5045 | 0.5005 |
A² | 936.51 | 1 | 936.51 | 9762.16 | <0.0001 |
B² | 1910.95 | 1 | 1910.95 | 19,919.77 | <0.0001 |
C² | 284.24 | 1 | 284.24 | 2962.92 | <0.0001 |
Residual | 0.6715 | 7 | 0.0959 | ||
Lack of fit | 0.3635 | 3 | 0.1212 | 1.57 | 0.3277 |
Pure error | 0.3080 | 4 | 0.0770 | ||
Cor total | 3786.36 | 16 |
Reactor Size | |||
---|---|---|---|
Volume (L) | MsOH (g) | MsOH Catalyst (Kg) | Catalyst Cost (USD) |
0.25 | 20.8 | 8.741 | 0.07 |
1.20 | 237.5 | 100 | 0.83 |
12.0 | 2375.0 | 1000 | 8.33 |
18.1 | 3562.4 | 1.500 | 12.50 |
50 | 9860.9 | 4.152 | 34.60 |
50.18 | 9895.7 | 4.167 | 34.72 |
100.35 | 19,791.4 | 8.333 | 69.45 |
250.88 | 49,478.4 | 20.833 | 173.62 |
Amount of Catalyst Needed | |||
---|---|---|---|
Mass Feed/Batch | Catalyst (kg) | Cost (USD) | Reactor Size (L) |
1.000 | 0.10 | 0.83 | 1 |
10.000 | 1.00 | 8.33 | 12 |
15.000 | 1.50 | 12.50 | 18 |
41.667 | 4.17 | 34.72 | 50 |
83.333 | 8.33 | 69.45 | 100 |
208.333 | 20.83 | 173.62 | 250 |
Reactor Capacity (L) | Feedstock Reactor Volume (L) | MsOH Catalyst Feed (kg per Batch) | Residence Time in Reactor (min ×103) | Residence Time in 1 Batch | Number of Rotational Stirring in 1 h | Number of Passes to Get 10 min | MPI Cost for 7 h Residence Time | MPI Cost for 2 h Residence Time | MPI Cost for 1 h Residence Time |
---|---|---|---|---|---|---|---|---|---|
50 | 2.35 | 10 | 600 | 0.235 | 2.35 | 3.0 | ZAR 145.957 | ZAR 29.191 | ZAR 14.596 |
50 | 2.35 | 100 | 6.000 | 0.024 | 0.24 | 29.8 | ZAR 1 459.574 | ZAR 291.915 | ZAR 145.957 |
50 | 2.35 | 167 | 10.000 | 0.014 | 0.14 | 49.6 | ZAR 2 432.624 | ZAR 486.525 | ZAR 243.262 |
50 | 2.35 | 300 | 18.000 | 0.008 | 0.08 | 89.4 | ZAR 4 378.723 | ZAR 875.745 | ZAR 437.872 |
50 | 2.35 | 658 | 39.480 | 0.004 | 0.04 | 196.0 | ZAR 9 604.000 | ZAR 1 920.800 | ZAR 960.400 |
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Mthembu, L.D.; Gupta, R.; Dziike, F.; Lokhat, D.; Deenadayalu, N. Conversion of Biomass-Derived Levulinic Acid into γ-Valerolactone Using Methanesulfonic Acid: An Optimization Study Using Response Surface Methodology. Fermentation 2023, 9, 288. https://doi.org/10.3390/fermentation9030288
Mthembu LD, Gupta R, Dziike F, Lokhat D, Deenadayalu N. Conversion of Biomass-Derived Levulinic Acid into γ-Valerolactone Using Methanesulfonic Acid: An Optimization Study Using Response Surface Methodology. Fermentation. 2023; 9(3):288. https://doi.org/10.3390/fermentation9030288
Chicago/Turabian StyleMthembu, Lethiwe Debra, Rishi Gupta, Farai Dziike, David Lokhat, and Nirmala Deenadayalu. 2023. "Conversion of Biomass-Derived Levulinic Acid into γ-Valerolactone Using Methanesulfonic Acid: An Optimization Study Using Response Surface Methodology" Fermentation 9, no. 3: 288. https://doi.org/10.3390/fermentation9030288