birhane.pptxcz v fgfgfbgdgh gh n h n n n

cddfe

1. By Messenbet Geremew By Messenbet Geremew Program of process engineering By Birhanie Getachew Advisor: Nigus Gabbiye (Ph.D .) March , 2023 Bahirdar, Ethiopia 1 Lactic Acid Production From Water Hyacinth By Acid Catalysed Chemical Hydrolysis

2. Presentation outline Introduction Statement of problem Objectives Material and M ethods Results and Discussion Summary 2

3. 1.Introduction Water hyacinth ( Eichhornia crassipes ) is an aquatic weed native to the world and anxious beauty due to its beautiful purple flowers. It has become a problem in all continents apart from Europe as well as in Ethiopia. Water hyacinth grows over a wide variety of wetland types such as lakes, streams, ponds, waterways, ditches, and backwater areas (Williams, 2017). Water hyacinth is an aquatic weed having the potential to produce different solid acid catalyst and is source of value added chemicals. Lactic acid ( LaA ) is one of the top fifteen rostrum chemicals derived from lignocellulosic biomass, with two enantiomers (D- LaA and L- LaA ). 3

4. Conti Carl Wilhelm Scheele, a Swedish chemist, discovers lactic acid for the first time from sour milk in the year 1780 . Lactic acid can be synthesized either by chemical or enzymatic hydrolysis method. Chemical catalysis is becoming increasingly popular as a powerful technique for converting cellulosic biomass into value-added compounds with adequate selectivity(Yuan & Wang, 2021). The process creates lactic acid directly from lignocellulosic biomass by using either homogeneous or heterogeneous catalyst in the hydrolysis step. Heterogeneous acid catalysts are the most selective catalysts for chemical catalysis or acid hydrolysis of lactic acid from water hyacinth biomass. 4

5. Statement of problem The weeds like water hyacinths, become a threat or problem by invading important natural resources such as land and water in Ethiopia. It is an obvious fact that control management systems require incurring a high amount of budget. Also , water hyacinth has a great potential for the production of value-added chemicals as well as other biofuels through chemical hydrolysis. Therefore converting these to useful product assists us to minimize the cost through integrated management of applying the “waste to value-added chemicals” concept . Thus , the production of lactic acid as a building block material reduces the currency burden, environmental impacts, and costs of controlling invasive weed infestation. 5

6. Objectives General objective The objective of this thesis is to optimize the chemical hydrolysis of lactic acid production from water hyacinth using solid GO catalyst. Specific objectives To determine the proximate and chemical composition of raw water hyacinth biomass To Investigating the effect of pretreatment and chemical hydrolysis parameters on lignin removal, holo-cellulose recovery as well as on lactic acid yield. To synthesize the solid –acid GO catalyst from pure graphite powder. To manufacture LA from water hyacinth by using solid acid catalyst Characterizing and quantifying the yield based on its quality attributes.   6

7. Materials and Methods Raw materials and chemicals Raw Materials and Chemicals Raw material Freshwater hyacinth Chemicals to be used Lactic acid (85%) Distilled water, and deionized water 3,5-dinitrosalicyclic acid Acetaldehyde HCN Ethanol (96%) 7 KMnO 4 ( 99%) Peroxide ( 30%) NaOH H 2 SO 4 (98%) Graphite powder H 3 PO 4

8. Materials and instruments used during production of LA PROPOSAL 8 Equipment to be used   Digital balance The pH meter Thermometer UV FTIR XRD DEM Oven Furnace Pressure Vessel An autoclave

9. Water H yacinth B iomass Preparation 9

10. Experimental design on biomass pretreatment To carry out the study, the design were three factorial experiments on a central composite design (CCD) and response surface methodology (RSM ). Three factors in the pre-treatment process of the sample such as Liquid-solid ratio Time Temperature 10

11. Treatment Combination of The Experiment     Factor 1 Factor 2 Factor 3 Std run Tem(℃) Time (min) Liquid/solid(ml/g) 23 1 100 60 10 22 2 120 120 12.5 3 3 120 90 10 1 4 140 60 10 4 5 120 90 12.5 2 6 140 60 10 25 7 140 120 10 26 8 140 90 12.5 27 9 140 120 10 24 10 120 60 12.5 13 11 120 120 12.5 15 12 100 120 10 16 13 100 120 15 14 14 100 60 10 19 15 120 90 15 17 16 100 120 15 18 17 140 60 15 5 18 140 60 15 8 19 120 90 15 6 20 120 90 12.5 7 21 120 90 10 32 22 140 120 15 33 23 100 60 15 31 24 100 90 12.5 29 25 120 90 12.5 30 26 100 60 15 28 27 140 90 12.5 20 28 100 120 10 21 29 120 90 12.5 11 30 100 90 12.5 12 31 120 60 12.5 9 32 120 90 12.5 10 33 140 120 15 11

12. Sample Pretreatment Process 12

13. 13 The structural features of treated and untreated water hyacinth can provide a piece of information that is used to describe the hydrolysis performance. The WHB was characterized by the compositional analysis UV and FTIR spectroscopy. The proximate analysis of the biomass sample were analyzed by standard ASTM method. Proximate analysis is the determination by prescribed methods of moisture, volatile matter, fixed carbon, and ash should sum to 100% of the biomass. The contents of cellulose, hemicellulose and lignin were also determined by standard ASTM method. All components can be calculated using the formula below.   Characterization of raw and pretreated biomass 13

14. Result and discussion 14 Parameters Authors R. Kumar, 2009 Reales –Alfaro, 2013 A.S.Kalamdhad, 2017 Nigam, 2002 This study Cellulose 18.4 32.84 31.67 40-65 44.8 Hemicellulose 49.2 24.7 27.33 48 25.12 Lignin 3.55 8.10 3.93 3.5-4.6 6.58 Proximate and compositional analysis of raw WH biomass parameters measurement units(%) Moisture content 89 Ash content 2.04 Volatile matter 6.06 Fixed carbon 2.9 Proximate analysis Compositional analysis

15. FT-IR analysis of the sample WHB 15

16. Data Analysis Stat-Ease Design_Expert_11.1.2.0 version statistical software was used for analysis of multiple data in the form of mean (±SD) The treatment means were separated using Turkey's Honest Significance Difference (HSD) test at 95% confidence interval and 5% level of significance A descriptive statistics analysis was used to compare the mean values obtained by usual practice with mean grouping value obtained the current finding Regression analysis and ANOVA were performed The graphs were created using an excel 16

17. T reatment C ombination result of the Experiment in mean grouping value 17 Rep Factor 1 Factor 2 Factor 3 Lignin removal(%) Holo-cellulose recovery (%) NO. Rep. times Temperature (⁰C) Time (min) L-SR (l/g) Mean St.Dev Mean St.Dev 1 2 100 60 10 7.5725 0.0354 77.6895 0.0354 2 2 100 60 15 0.0283 0.0566 3 2 100 90 12.5 8.935 0.0212 84.651 0.629 4 2 100 120 10 7.5225 0.0283 74.7095 0.12 5 2 100 120 15 0.0212 0.0424 6 2 120 60 12.5 6.185 0.417 62.7161 0.269 7 5 120 90 12.5 7.39556 0.0158 70.342 0.419 8 2 120 90 10 0.191 0.00707 9 2 120 90 15 0.1202 0.0919 10 2 120 120 12.5 6.57 0.1131 63.436 0.0141 11 2 140 60 10 7.935 0.00707 74.162 0.283 12 2 140 60 15 0.00707 0.0141 13 2 140 90 12.5 8.909 0.341 82.816 0.792 14 2 140 120 10 8.3425 0.0141 77.4495 0.0212 15 2 140 120 15 0.00707 0.0283

18. Analysis of variance for lignin removal 18 Source Sum of Squares df Mean Square F-value p-value   Model 18.26 9 2.03 327.52 < 0.0001 significant A-T 1.34 1 1.34 215.74 < 0.0001   significant B-t 0.2808 1 0.2808 45.34 < 0.0001   significant C-LSR 0.0344 1 0.0344 5.56 0.0272   significant AB 0.1425 1 0.1425 23.00 < 0.0001   significant AC 0.0473 1 0.0473 7.64 0.0111   significant BC 0.1073 1 0.1073 17.31 0.0004   significant A² 13.95 1 13.95 2252.01 < 0.0001   significant B² 6.92 1 6.92 1117.20 < 0.0001   significant C² 0.0437 1 0.0437 7.05 0.0141   significant Residual 0.1425 23 0.0062       Lack of Fit 0.1367 5 0.0273 85.60 < 0.0001 significant Pure Error 0.0057 18 0.0003       Cor Total 18.40 32        

19. Analysis of variance for holo-cellulose recovery 19 Source Sum of Squares df Mean Square F-value p-value   Model 1071.24 9 119.03 1927.28 < 0.0001 significant A-T 1.05 1 1.05 17.06 0.0004   significant B-t 0.4205 1 0.4205 6.81 0.0157   significant C-LSR 27.45 1 27.45 444.44 < 0.0001   significant AB 42.84 1 42.84 693.62 < 0.0001   significant AC 0.2652 1 0.2652 4.29 0.0496   significant BC 3.65 1 3.65 59.07 < 0.0001   significant A² 942.37 1 942.37 15258.79 < 0.0001   significant B² 288.37 1 288.37 4669.32 < 0.0001   significant C² 53.63 1 53.63 868.41 < 0.0001   significant Residual 1.42 23 0.0618       Lack of Fit 0.9899 5 0.1980 8.28 0.0003 significant Pure Error 0.4306 18 0.0239       Cor Total 1072.66 32        

20. Effect of factors on lignin removal and holo-cellulose recovery 20 The effect of temperature and time on the response Higher temperatures, longer times and higher liquid-solid ratios all contribute to higher lignin removal, while generally reducing holo-cellulose yields. This is due to increased cleavage of glycosidic bonds in cellulose causing reduced cellulose hydrolysis and lower yield. Additionally, increasing operating temperatures can cause excessive organic compound degradation resulting in greater carbohydrate losses. In general, higher temperatures tend to result in higher levels of lignin removal, but lead to higher rates of degradation of glucan that are also found in biomass.

21. Conti… 21 The effect of time and L-SR on the response Time affects the efficiency of delignification but has a lesser impact on overall carbohydrate yields. Higher liquid-solid ratios can help increase both lignin removal and carbohydrate recovery, although there may be some dilution effects (Xia et al ., 2013). Higher L-SR can improve both lignin removal and carbohydrate yield by enhancing heat transfer capabilities to minimize any "cold spots" resulting from unequal solid distribution on the untreated feedstock surface for more consistent reactor thermal conditions.

22. Response Surface and Contour Plot for Yield with Parameter Interaction The individual and cumulative effects as well as the mutual interactions between the parameters on the dependent variables were described using response surface and contour plots. A combination of factors may affect the mechanisms through which biomass is decomposed—such as hydrolytic or enzymatic degradation—impacting holo-cellulose recovery levels as well as delignification rate. The interaction effect of pretreatment parameters on lignin removal and holo-cellulose recovery depends on the specific parameters used during pretreatment. Generally, higher temperatures and longer reaction times can lead to increased lignin removal; however, this may come at the expense of holo-cellulose recovery. 22

23. Conti… Lower temperatures, short reaction times and low doses of acid are typically better for holo-cellulose recovery. At the higher-level of temperature and time, the yield of lignin removal is higher and the yield holo-cellulose recovery was lower due to the over degradation of cellulose to undesired products ( Cheng et al ., 2015 ). Generally the effect of pretreatment parameters on lignin and holo-cellulose recovery depends on the biomass type to be pretreated and in this study their effect in terms of main effect and interaction effect were observed briefly in the contour and surface plot for both targets. 23

24. Response Surface and Contour Plot 24

25. Surface Plot For The Response 25

26. Synthesis Of Graphene Oxide By Improved Hammers Method 26

27. S ummary It can be summarized as the ethanol pretreated water hyacinth biomass can be an effective method for lignin removal and holo-cellulose recovery. The ethanol pretreatment process removes lignin effectively while retaining a high holo-cellulose yield, which in turn leads to a higher yield of fermentable sugars when hydrolyzing the biomass. Therefore , the ethanol pretreatment provides a promising approach for maximizing bio-refinery usage of water hyacinth biomass and could potentially be used in larger scale applications. 27

28. Future and Remaining work of the study H ydrolysis of holo-cellulose into glucose and isomerize this into fructose Retro- aldol reaction of fructose by solid Lewis acid catalyst to convert it into lactic acid. Characterize and test the product using different attributes. 28

29. progress 29 THANK YOU FOR YOUR ATTENTION