Evaluation of Lake Erie algae as bio-fuel feedstock

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The University of Toledo

The University of Toledo Digital Repository Theses and Dissertations

2010

Evaluation of Lake Erie algae as bio-fuel feedstock Vasudev Gottumukala The University of Toledo

Follow this and additional works at: http://utdr.utoledo.edu/theses-dissertations Recommended Citation Gottumukala, Vasudev, "Evaluation of Lake Erie algae as bio-fuel feedstock" (2010). Theses and Dissertations. Paper 851.

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A Thesis entitled

Evaluation of Lake Erie Algae as Bio-fuel Feedstock

by Vasudev Gottumukala

Submitted to the Graduate Faculty as partial fulfillment of the requirements for The Master of Science in Chemical Engineering

_____________________________ Advisor: Constance A. Schall ______________________________ Committee Member: Thomas Bridgeman ______________________________ Committee Member: Sridhar Viamajala ______________________________ Dean: Dr. Patricia Komuniecki College of Graduate Studies The University of Toledo May 2010

An Abstract of Evaluation of Lake Erie Algae as Bio-fuel Feedstock by Vasudev Gottumukala Submitted to the Graduate Faculty in partial fulfillment of the requirements for the Master of Science in Chemical Engineering The University of Toledo May 2010 Currently, transportation fuels are produced from continuously depleting fossil fuel sources. This calls for additional renewable sources that could be used for the production of high quality transportation fuel. Bio-diesel is one such alternative. Soybean, a food crop, has been used in the past as a source of lipids for the production of bio-diesel. Algae are an alternative non-food source of lipids for bio-diesel and/or carbohydrates for bio-ethanol. We have surveyed algae and phytoplankton in the western Lake Erie basin to identify the predominant algae species. The lipid, carbohydrate and the protein content of lake species were determined. Sampling at selected lake sites was performed at regular intervals of time in an attempt to correlate lake conditions (i.e. temperature, phosphorus and nitrogen) with the selection and composition of species. Based on the results of these analyses, native species were identified as candidates for bio-diesel or bio-ethanol production.

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Few preliminary experiments were performed to process soybean oil using a batch reactor to convert the triacylglycerides to free fatty acids which would then be converted to fatty acid methyl esters (bio-diesel) through transesterification. The optimized processing conditions can then be utilized to process algae.

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This work is dedicated to my parents, sister & brother-in-law and to my best friends for their tremendous support and encouragement throughout.

Acknowledgements

I wish to express my sincere gratitude to my advisor Dr. Constance A. Schall. I would also like to thank Dr. Thomas Bridgeman, Dr. Sasidhar Varanasi and Dr. Sridhar Viamajala for their guidance and support during my research. I would like to thank Dr. Cyndee Gruden, Dr. Thomas Kina and Dr. Pannee Burckel for their help with analytical equipments and useful suggestions. I would like to thank Dr. Glenn Lipscomb for giving me admission in University of Toledo. I am grateful to the Department of Chemical and Environmental Engineering for financial assistantship throughout my course of study. I would also like to thank the Center for Innovative Food technology for funding my project. I would really like to thank my labmates and friends Indira Priya Samayam, Noureen Faizee, Thehazhnan Ponnaiyan, Christopher Barr, Amber Bosley, Brett Digman, Richard Hausman, Justin Chaffin, Olga Mileyeva-Biebesheimer, Ananth Dadi, Kripa Rao and Micheal Mayer for their help, support and encouragement. Last but not the least I would like to thank my colleagues at my company, Midwest Bio Renewables, for believing in me and giving me complete freedom and flexibility in my job timings in order to complete my thesis.

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Table of Contents

Abstract ......................................................................................................................... iii Acknowledgement .......................................................................................................... vi Table of Contents ..........................................................................................................vii List of Tables.................................................................................................................. xi List of Figures ............................................................................................................. xiii Introduction ..................................................................................................................... 1 Chapter 1 - Characterization of Algae .............................................................................. 8 1.1

Chapter Introduction ...................................................................................................... 8

1.2

Dry weight analysis ....................................................................................................... 9

1.3

1.2.1

Equipment ......................................................................................................... 9

1.2.2

Materials ............................................................................................................ 9

1.2.3

Methods ............................................................................................................. 9

1.2.4

Sample calculations ........................................................................................... 9

Lipid analysis .............................................................................................................. 10

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1.4

1.5

1.6

1.3.1

Equipment ....................................................................................................... 10

1.3.2

Reagents .......................................................................................................... 10

1.3.3

Materials .......................................................................................................... 11

1.3.4

Methods ........................................................................................................... 12

1.3.5

Sample calculations ......................................................................................... 19

Protein analysis ........................................................................................................... 20 1.4.1

Equipment ....................................................................................................... 20

1.4.2

Materials .......................................................................................................... 20

1.4.3

Methods ........................................................................................................... 20

1.4.4

Sample calculations ......................................................................................... 21

Structural carbohydrate & lignin analysis ..................................................................... 22 1.5.1

Equipment ....................................................................................................... 22

1.5.2

Reagents .......................................................................................................... 22

1.5.3

Materials .......................................................................................................... 23

1.5.4

Methods ........................................................................................................... 23

Starch analysis ............................................................................................................. 24 1.6.1

Equipment ....................................................................................................... 24

1.6.2

Reagents .......................................................................................................... 25

1.6.3

Materials .......................................................................................................... 26

1.6.4

Methods ........................................................................................................... 26

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Chapter 2 - Characterization of Aulacoseira granulata .................................................. 29 2.1

Chapter Introduction .................................................................................................... 29

2.2

Results and Discussion ................................................................................................ 30 2.2.1

Dry weight analysis .......................................................................................... 30

2.2.2

Lipid analysis ................................................................................................... 31

2.2.3

Starch, structural carbohydrate and lignin analysis ............................................ 38

2.2.4

Protein analysis ................................................................................................ 39

2.2.5

Conclusions ..................................................................................................... 40

Chapter 3 - Characterization of Cladophora glomerata .................................................. 41 3.1

Chapter Introduction .................................................................................................... 41

3.2

Results and Discussion ................................................................................................ 43 3.2.1

Dry weight analysis .......................................................................................... 43

3.2.2

Lipid analysis ................................................................................................... 44

3.2.3

Starch, structural carbohydrate and lignin analysis ............................................ 47

3.2.4

Protein analysis ................................................................................................ 49

3.2.5

Conclusions ..................................................................................................... 51

Chapter 4 - Characterization of Lyngbya wollei.............................................................. 52 4.1

Chapter Introduction .................................................................................................... 52

4.2

Results and Discussion ................................................................................................ 54 4.2.1

Dry weight analysis .......................................................................................... 54

4.2.2

Lipid analysis ................................................................................................... 55

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4.2.3

Starch, structural carbohydrate and lignin analysis ............................................ 57

4.2.4

Protein analysis ................................................................................................ 59

4.2.5

Conclusions ..................................................................................................... 60

Chapter 5 – Effect of nutrient availability on growth of Aulacoseira granulata .............. 61 5.1

Chapter Introduction .................................................................................................... 61

5.2

Nutrient availability related to Aulacoseira granulata’s growth.................................... 67

5.3

Conclusions ................................................................................................................. 74

Chapter 6 – Soybean oil processing ............................................................................... 76 6.1

Chapter Introduction .................................................................................................... 76

6.2

Approach..................................................................................................................... 78

6.3

Hydrolysis of soybean oil ............................................................................................ 80 6.3.1

Equipment ....................................................................................................... 81

6.3.2

Reagents .......................................................................................................... 82

6.3.3

Materials .......................................................................................................... 83

6.3.4

Methods ........................................................................................................... 83

6.4

Results and Discussion ................................................................................................ 87

6.5

Sample calculations ..................................................................................................... 89

Chapter 7 – Conclusions and future work ...................................................................... 93 References ..................................................................................................................... 96 Appendices .................................................................................................................. 100

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List of Tables

1-1

Acetanilide (standard) - expected vs. obtained results .......................................... 21

2-1

Average dry weight analysis data - Aulacoseira granulata centrifuged paste......... 31

2-2

Gravimetric quantification of lipid – Aulacoseira granulata ................................ 32

2-3

Percent lipid and FAMES extracted from Aulacoseira granulata, calculated on a dry weight basis ............................................................................................... 35

2-4

Aulacoseira granulata – Free fatty acid distribution............................................. 35

2-5

GC-MS data – Aulacoseira granulata summer-2008 sample ................................ 36

2-6

GC-MS data – Aulacoseira granulata summer-2009 sample ................................ 37

2-7

C H N weight percent data – Aulacoseira granulata ............................................ 39

3-1

Average dry weight analysis data - Cladophora glomerata centrifuged paste ....... 43

3-2

Gravimetric quantification of lipid – Cladophora glomerata ................................ 44

3-3

Percent lipid and FAMES extracted from Cladophora glomerata, calculated on a dry weight basis ............................................................................................... 45

3-4

GC-MS data – Cladophora glomerata December-2008 sample ............................ 46

3-5

Cladophora glomerata – Free Fatty Acid Distribution ......................................... 46

3-6

HPLC data from the total carbohydrate analysis – Cladophora glomerata ........... 47

3-7

HPLC data from the starch analysis – Cladophora glomerata .............................. 48 xi

3-8

C H N weight percent data – Cladophora glomerata ............................................ 50

4-1

Average dry weight analysis data for Lyngbya wollei centrifuged paste .............. 55

4-2

Gravimetric quantification of lipid – Lyngbya wollei ........................................... 56

4-3

Percent lipid and FAMES extracted from Lyngbya wollei, calculated on a dry weight basis ......................................................................................................... 57

4-4

HPLC data from the total carbohydrate analysis – Lyngbya wollei ....................... 58

4-5

HPLC data from the starch analysis – Lyngbya wollei .......................................... 59

4-6

C H N weight percent data – Lyngbya wollei ....................................................... 60

5-1

Set of nutrient ratios (millimolar basis) calculated from the nutrient sources measured at the sampling location of Aulacoseira granulata in the year 2008 on 07/07/2008 ..................................................................................................... 69

5-2

Set of nutrient ratios (millimolar basis) calculated from the nutrient sources measured at the sampling location of Aulacoseira granulata in the year 2009 on 06/26/2009 ..................................................................................................... 69

6-1

Theoretical yields obtained in soybean oil hydrolysis ........................................... 89

6-2

FFA distribution at varying reaction times and catalyst loadings .......................... 91

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List of Figures

I-1

Top ten fossil fuel producing and consuming countries in 2008 .............................. 1

I-2

Overall energy consumption in the U.S during the years 2003-2007 ....................... 2

I-3

Closed carbon cycle – Algae .................................................................................. 5

I-4

Lake Erie ................................................................................................................ 6

I-5

Algae life cycle ...................................................................................................... 7

1-1

Sample calibration curve of a mixed standards analyzed by GC with flame ionization detection (FID) ................................................................................... 16

1-2

Sample chromatogram of a mixed standard run through GC ................................ 17

2-1

Microscopic image of Aulacoseira granulata....................................................... 30

2-2

Sample chromatogram showing external standards run through GC ..................... 33

2-3

Sample chromatogram showing Aulacoseira granulata (summer-2008) sample run .......................................................................................................... 34

3-1

Microscopic image of Cladophora glomerata ...................................................... 42

3-2

Chromatogram – Cladophora glomerata December-2008 sample run .................. 45

4-1

Microscopic image of Lyngbya wollei .................................................................. 54

4-2

Chromatogram – Lyngbya wollei July-2009 sample run ....................................... 57

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5-1

HPLC Comparison between the TN: TP molar ratio for the data obtained in the year 2008 and 2009 ............................................................................................. 71

5-2

Comparison between the TSi: TP molar ratio for the data obtained in the year 2008 and 2009 ............................................................................................. 72

5-3

Comparison between the TSi: TN molar ratio for the data obtained in the year 2008 and 2009 ............................................................................................. 73

6-1

Transesterification reaction .................................................................................. 76

6-2

Reactor assembly along with the controlling unit ................................................. 84

6-3

Separation between the fatty acid layer and the aqueous glycerin layer ................ 85

6-4

Darkening of FFA layer with increasing reaction time (30, 45, 60 min) ............... 87

6-5

Chromatogram showing FFA sample run through GC.......................................... 88

6-6

Chromatogram showing overlay of three sample (varying reaction times) runs through GC ................................................................................................. 90

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Introduction

One of the major problems that the world is facing is the dependence on fossil fuels for our day to day energy requirements. Studies have shown that almost 85% of the total energy being utilized is provided by the fossil fuels (Liu L., Cheng S. Y. et al. 2007). The increasing use of fossil fuel directly relates to global warming issues due to increased green house gas emissions (Schneider U. A. and McCarl B. A. 2003). Due to high dependence and usage of this fuel, a decline in its availability is being observed (Liu L., Cheng S. Y. et al. 2007). Fossil fuels include petroleum, coal and natural gas. Each of these feed stocks has importance in various energy applications. An important use of fossil fuels is in transportation in the form of liquid fuels.

Figure I-1. Top ten fossil fuel producing and consuming countries in 2008. 1

The fossil fuel production and consumption based on the data provided by the U. S. Energy Information Administration (Administration 2008) for the year 2008 is shown in the Fig.I-1. While being one of the top fossil fuel producing countries, the U.S is also the highest fuel consuming nation. The consumption rate is close to more than double its fuel production rate. Because of this, the U.S has to depend on production in other countries and imports most fuel. There are alternative sources which can be investigated for fuel production that could, if not eliminate, reduce the dependence on other nations for fuel requirements. Recent research has focused on development of renewable fuel sources such as corn stover, soy beans, switch grass and algae for producing fuels that could be used directly or blended with the existing fuels. This could not only help in reducing the current fuel pricing but may also utilize agricultural waste and low quality lands in a productive way.

Figure I-2. Overall energy consumption in the U.S during the years 2003-2007.

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An energy survey by the Energy Information Administration (EIA, official energy statistics from the U.S. government) for the years 2003-2007 (Administration 2007), summarizes the energy use in U.S in Figure I-2. It is clear from Figure I-2 that a major part of U.S energy requirements comes from fossil fuels. Due to continuously depleting fossil fuel, the focus is now on using renewable sources for producing fuels for our energy requirements. The statistics shown in Figure I-2 clearly indicate that a major portion of renewable energy is obtained from biomass. As mentioned earlier, there are a number of biomass sources available. Biomass with high lignocellulosic content, like corn stover, is being considered for producing bioethanol (Sun Y. and Cheng J. 2002). Currently, US bio-ethanol is produced primarily from corn grain with the corn stover available as an agricultural residue. Soy bean oil has been used extensively in U.S, because of its high lipid content (also known as triacylglycerols, TAGs), as a feedstock for biodiesel (soy diesel) production (Van Gerpen J., Shanks B. et al. 2004). Biodiesel draws attention because of its ease of production and simple blending with diesel fuel. It can also be utilized directly in its pure form (Van Gerpen J., Shanks B. et al. 2004). Other sources of vegetable oils have been evaluated using the fuel extraction process developed for soy bean oil (Van Gerpen J., Shanks B. et al. 2004). With limited fossil fuel sources, the need for developing a process of producing alternative fuel using renewable feedstock has increased manifold. An energy crisis was observed during the early 1970’s. This encouraged the U.S. Department of Energy (U.S.D.O.E) to look for an alternative energy source. The U.S.D.O.E’s Office of Fuel Development then funded a nationwide research program, named The Aquatic Species

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Program, which focused on the development of renewable transportation fuels from the high lipid containing algae species (Sheehan J., Dunahay T. et al. 1998). This 18 year long program eventually ended (in 1996) because the cost of producing biodiesel from algae was higher than fuel prices at that time(Sheehan J., Dunahay T. et al. 1998). The unstable fuel prices today justify the need of looking back at algae as a source of biodiesel. Algae can produce greater yields of lipids per unit area than that of soy beans. According to the findings of (Ball R., Purcell L. C. et al. 2000), soybean production yields around 400 g per m2 per harvest (composed of ~18% TAGs) while the production of algae can yield mass up to 50 g per m2 per day (composed of 20-60% TAGs). Algae grow well in a nutrient rich environment. They can make use of nutrients from agricultural runoff and livestock water discharge for their growth and in turn help in treating the contaminated streams (Sriharan S., Bagga D. et al. 1990). Depending on how they store the energy, whether in the form of lipids or carbohydrate, the algae serve as a feedstock for bio-diesel (TAG) or bio-ethanol (carbohydrate). Algae have the ability to recycle the CO2 as a carbon source. The CO2 emissions from fossil fuel power plants or the corn to ethanol facilities can be captured by algae and converted to biomass through photosynthesis. By recycling CO 2, a well designed algal pond can slow the release of the greenhouse gases which would have a positive effect towards global warming. By uptake of nitrogen, phosphorus and other contaminating nutrients, a well designed algal pond can facilitate reduction in the release of these pollutants and prevent the bloom of harmful algae in natural waters. The algae biomass harvested from these algal ponds can then serve as a highly useful feed stock for the bio-

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diesel or bio-ethanol production. Figure I-3 shows a block diagram of the closed carbon cycle used by the algae.

Land plants

Bio-ethanol

Atmospheric CO2 Fossil Fuel Combustion (Power generators)

Waste CO2

CO2

Native Great Lakes algae

Nutrient-rich agricultural run-off, animal manure, waste-water

Waste CO2

Bio-diesel (Diatom algae) and Bio-ethanol (Green algae) Atmosphere

Figure I-3. Closed carbon cycle – Algae.

Lake Erie, one of the five great lakes in U.S, is rich in aquatic species. The western Lake Erie covers Toledo, Ohio and south-east Michigan regions. All the agricultural runoff and waste water from industries around the lake is fed into Lake Erie. The agricultural runoff contains significant amounts of nutrients (from fertilizers) which can result in eutrophication. Combined feed from industries and agricultural runoffs results in the availability of excess nitrogen and phosphorus in the Lake and favors algal blooms which use these macro nutrients (that is nitrogen and phosphorus) for its growth. Each species of alga has its own growth requirements, for example, one species may need more of nitrogen for its growth, while other may require more silica. Algae growth is dependent on many factors such as nutrient availability, light, pH, CO2 availability, and temperature.

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Figure I-4. Lake Erie (N.O.A.A. 2009).

A wide range of algal species grow naturally in the western part of Lake Erie. The composition of various members in a particular group of alga tends to be the similar in most cases. For example, diatoms are known for their high lipid content while green alga is known for its ability to store energy in the form of either starch or lipids (Sheehan J., Dunahay T. et al. 1998). The aim of this study was to survey Lake Erie algae for their potential as a feedstock for bio-diesel or bio-ethanol production. Three different species of algae, Aulacoseira granulata, Cladophora granulata and Lyngbya wollei each belonging to a broad class of algae that is diatom, green alga and cyano-bacteria respectively, were examined. These species were selected based on their abundance. Each of these species was then subjected to proximate chemical analyses to assess the lipid, carbohydrate, starch and protein content.

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Figure I-5. Algae life cycle (Oceanography 2009).

Algae sample were collected during summer of 2008 and 2009. Various parameters such as pH, nutrient (nitrogen, phosphorus and silica) concentration in the lake, temperature and turbidity were also measured during the entire season at the sampling location of diatoms (as it is the species of interest). The data from two years was studied and an effort was made to correlate the growth of algae to nutrient availability. Lastly an attempt was made to develop a processing technique for extracting the lipids from the algae. This was achieved using a bench top, closed pressure reactor using soy bean oil as the feedstock. Soy bean oil was chosen, as some information in literature is available regarding the processing of soy bean oil and this could then become the basis for processing algae. 7

CHAPTER 1

Characterization of Algae

1.1 Chapter Introduction As mentioned in the Introduction, characterization of the various species of algae sampled from Lake Erie is an important step. The three species, Aulacoseira granulata (diatom), Cladophora glomerata (green algae) and Lyngbya wollei (cyanobacteria) sampled from the Lake Erie during mid summer in 2008 and 2009 are subjected to basic characterization analyses. The major focus was to see how each of these species stores the energy through a combined action of nutrient uptake from the lake and photosynthesis. Depending on the nature of the species and the growth ecology, algae can store carbon and energy in the form of lipids, carbohydrates and proteins. The first analysis was the dry weight analysis to calculate moisture content in the given algae sample. Lipid analysis was carried out in two steps: a) Extraction of lipids from the cells. b) Transesterification of the extracted lipids to convert them to fatty acid methyl esters (FAMES). Structural carbohydrate and starch analysis was also performed. The carbohydrate analysis is performed using a two step acid hydrolysis process, while the starch is analyzed using an enzyme hydrolysis process. Finally the protein analysis is

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performed using CHN analyzer which breaks down the sample into its basic constituents (C, H and N). Based on the amount of N in the sample, the protein content is estimated. This chapter includes the details of material and methods required for all these analyses and also the calculations involved in each of these analyses. 1.2 Dry Weight Analysis 1.2.1 Equipment: All the algae samples were dried in a closed vacuum oven (OV-12 – Jeio Tech). The oven is operated at 40-45 oC. 1.2.2 Materials: Low form aluminum fluted weighing dish. 1.2.3 Method: The dry weight analysis is based on the simple drying concept. A known amount of a sample is weighed accurately in aluminum weighing dish and is dried to constant weight in a closed oven at 40-45 oC for approximately 48 hours. For example, the sample is weighed after 45 hours, returned to the oven, then weighed again at 48 hours. If the difference in weights is within 2 % then the sample is considered dry. The weight of the dried sample is then measured, which in turn gives us the moisture content in a given sample. 1.2.4 Sample Calculations: In order to calculate the moisture content in the given sample, the following simple calculation can be used. Initial weight of the sample (wet) = X gm After drying the sample; 9

Final weight of the sample (dry) = Y gm Therefore, the dry weight percent = (Y/X)*100 Moisture content (Z %) = (1 – (Y/X))*100 1.3 Lipid Analysis 1.3.1 Equipment: A Misonix Microson XL2000 ultrasonic homogenizers (110V 50/60Hz, Fisher Scientific) was used to sonicate and lyse the cell membranes to extract the lipids. Fisher vortex genie 2 (Fisher Scientific) was used for mixing the samples efficiently. An eppendorf centrifuge (5810 R - Eppendorf) for centrifuging the 50 ml polypropylene disposable centrifuge tubes (Fisher Scientific, # 06-443-18). An aluminum block heater (FINEPCR- Diagger – ALB 128) was used for heating the samples. And a centrific centrifuge (model 228 – Fisher Scientific) was used for centrifuging the 15 ml polypropylene centrifuge tubes (Fisher Scientific, # 05-539-5). Once the FAMES are formed, the sample is then analyzed with a Shimadzu gas chromatography unit (GC-17A) equipped with a flame ionization detector (FID), an autosampler (AOC-20s) and an auto injector (AOC-20i) and a class VP 7.4 software. The class VP 7.4 software applications were used for the quantification based on peak areas. For analyzing fatty acid methyl esters, a fused silica capillary column, SupelcowaxTM 10 (30m x 0.25mm x 0.25µm , Sigma Aldrich, # 24079), was used. 1.3.2 Reagents: The organic solvents and chemical reagents used for this process were as follows: chloroform (Fisher Scientific, 99.9%, # C606SK-4), methanol (Fisher Scientific, 99.9%, # A412SK-4), toluene extra dry, water

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