Introduction to Ethanol Production – No, Not the Drinking Kind!

Bia H. Thomas, Ph.D.

ChE 473A Lecture

October 19th, 2011

St. Louis, MO

Outline

• Why is Ethanol Important?• How is Ethanol Made?• The Monod Model• The Wonderful World of Kinetics• The Bioreactor Setup• Some Analytical Techniques• Sample Results• Modeling• Some Final Thoughts

The Renewable Energy Question

• Current world oil consumption is 88 million barrels/day which will continue to grow rapidly

• By 2050 the world population will reach 9-10 billion and current reserves of both oil and natural gas will be exhausted

• How to supply the vast quantities of energy, fuels and chemicals when oil, gas and coal are no longer readily available is one of the most challenging and important problems now facing humanity

• Renewable sources of energy and chemicals will replace the fossil-based fuels and products

• Ethanol is one of the renewable sources of energy which is considered a cleaner source of bioenergy

Ethanol Production From Corn

• 2010: 13 billion gallons of ethanol

Source: www.ethanolrfa.org/industry/locations

The Case for Ethanol

• Demand for ethanol is increasing with ever mounting pace: In 2003, the US production of bioethanol was 2.8 billion gallons from 175 million gallons in 1980 and 1.77 billion gallons in 2001

• Bio-ethanol is derived from cellulosic and lignocellulosic biomass via the following processes:

CellulosicMillingLiquefactionSaccharificationFermentation

LignocellulosicPretreatmentSaccharificationFermentation (C6 and C5)

• Ethanol can be produced from corn, a starch-based cellulosic biomass, according to the reaction:

yeast (X), 36°CC6H12O6 → 2C2H5OH + 2CO2

Glucose (S) → 2 Ethanol (P) + 2 Carbon Dioxide

The Dry Grind Process

• Dry grind:– Corn processed whole– Less complex– Lower initial capital cost– Fewer unit operations – 3 products: ethanol, CO2,

and DDGS• Wet milling:

– Only 30% of facilities are wet milling

– Fractionation of corn kernel into starch, gluten, fiber, germ

• Separation: chemically or enzymatically

– Products: ethanol, gluten meal, gluten feed, oil

• Starch component can be processed into many products

Hammer Mill

Slurry Tank

Liquefaction Fermentor

Beer Well

Distillation Column

Molecular Sieves

Ethanol Storage Tank

1st EffectEvaporator Whole

StillageTank

Centrifuge

Ring Dryer

ThinStillageTank

3rd EffectEvaporator2nd Effect

Evaporator

CO2Scrubber

Syrup Tank

DDGs

Ethanol

Whole Stillage

CornMash

Thin Stillage

Syrup

WDGs

Corn Carbon Dioxide

To CO2 Scrubber

Hammer Mill

Slurry Tank

Liquefaction Fermentor

Beer Well

Distillation Column

Molecular Sieves

Ethanol Storage Tank

1st EffectEvaporator Whole

StillageTank

Centrifuge

Ring Dryer

ThinStillageTank

3rd EffectEvaporator2nd Effect

Evaporator

CO2Scrubber

Syrup Tank

DDGs

Ethanol

Whole Stillage

CornMash

Thin Stillage

Syrup

WDGs

Corn Carbon Dioxide

To CO2 Scrubber

Fermentation Processes

• Ideal fermentation processesIdeal fermentation processes• Growing cells are consuming the substrate (sugars) and producing Growing cells are consuming the substrate (sugars) and producing

more cellsmore cells

rsx = rate of substrate consumptionrsx = rate of substrate consumptionrx = rate of cell growthrx = rate of cell growths = substrate concentrations = substrate concentrationx = cell concentrationx = cell concentrationP = ethanol concentration (in anaerobic case)P = ethanol concentration (in anaerobic case)

rx

Cells (x)P

Cells (x)

rsx

The Monod Model

• Monod's model describes the relationship between the specific growth rate and the growth limiting substrate concentration as:

where µm is the maximum specific growth rate and Ks is a saturation constant

• Despite its empirical nature Monod's model is widely used to describe the growth of many organisms. Basically because it does adequately describe fermentation kinetics

• Model has been modified to describe complex fermentation systems

Assumptions and Constraints

• Monod model represents a very simple model of cell growth and product formation

– Fermentation processes are often much more complex

• Modifications may need to be introduced to handle more complicated systems

• Additional equations would be required to handle multiple products and multiple organisms

• The model has also assumed that product formation is linked to biomass growth

• In reality, many commercially important products are produced in a non-growth associated manner

• The model assumes that biomass and product formation can be represented by averaged yield coefficients

• These assumptions may sometimes be an oversimplification and such a model would give unrealistic results

Why Is It Important?

• When the model is solved numerically, a number of curves are obtained

• With the model it is possible to:

– Determine the number of fermentations that can be performed per year

– Amount of profit that can be made.

Kinetics, Kinetics, More Kinetics

• The rates of microorganisms’ growth, the consumption of glucose, and the formation of products are:

Xrdt

dXX

Xqrdt

dPPP

(1)

(3)

(2)

(4)

Rate of reaction relative to cell mass concentration

Rate of reaction relative to ethanol concentration

Rate of reaction relative to glucose concentration

Specific growth rate without inhibition effect Monod’s model

(5)

(6)

Yield coefficient (X w.r.t. S)

Yield coefficient (P w.r.t. S)SS

PP

dS

dPY

SS

XX

dS

dXY

SK

S

dt

dX

x

XY

qr

dt

dS

o

oSP

o

oSX

S

m

SP

PS

1

/

1

The Bioreactor Setup

Thermostatically controlled

heating/cooling water bath

Variable Speed Drive

Gas Meter

Analyzer

Fraction Collector

Bidirectional Pump

37L Reactor

Inoculum Port

Thermocouple

Drive Belt

Draft Tubefor heating/

cooling

The Bioreactor Setup

Online biochemistry analyzer for ethanol concentration detection

Automatic temperature control via draft tube

pH meter for optimum pH control

Fraction collector for automatic sampling system

Turbine impeller for uniform yeast distribution

Temperature Read Out

Bench-scale 37L Stirred Fermentor (active volume: 16 L)

Analytical and Measurement Techniques

• YSI analyzer– Takes online samples every hour to measure ethanol and glucose

concentrations– Automatically samples test tubes for substrate concentration

• Spectrophotometer– Absorbance measurement for each test tube – Absorbance used for calculating yeast concentration in each test tube

using calibration curve• Gas Meter:

– Measures the volume of CO2 evolved during fermentation– Volume used to calculate number of moles of ethanol produced

• Other methods such as Brix Glucose Test and Ethanol Reagent Kits can be used to determine sample composition

Sample Results

TA Results

0

5

10

15

20

0 500 1000 1500T ime (min)

Su

bst

rate

Co

nce

ntr

atio

n (

g/L

)

0

1

2

3

4

5

6

7

8

9

10

Eth

ano

l C

on

cen

trat

ion

(g

/L)

Subst rate Concent rat ion Ethanol Concent rat ion

• Results of the base line study (20 g/L of glucose and 4 g/L yeast) at 36°C• pH kept between 5.5 and 4.0• Samples taken every 45 minutes

Sample Results

Yeast concentration inside the fermentor throughout the experimentation time

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0 10 20 30 40 50Time (hr)

Ye

ast

co

nce

ntr

atio

n in

sid

e t

he

re

act

or

(g/L

)Glucose 50 g/L

Glucose 100 g/L

Glucose 150 g/L

Glucose 200 g/L

Glucose 250 g/L

• The plot shows that at high initial glucose concentrations the growth of the yeast gets affected and thus, the yeast takes longer time to inhibit the growth

Sample Results

• Yeast was not incubated prior to experiment which explains the delay in the production of ethanol for all groups

• From the figure initial glucose concentrations of 50, 100, and 150 g/L allowed fermentor to reach its maximum capacity

• For the 2 highest glucose concentrations students believe that the time for the experiment was not long enough

Ethanol production throughout the experimentation time

0

1

2

3

4

5

6

7

8

0 10 20 30 40 50Time (hr)

Eth

an

ol C

on

cen

tra

tion

insi

de

th

e r

ea

cto

r (g

/L)

Glucose 50 g/L

Glucose 100 g/L

Glucose 150 g/L

Glucose 200 g/L

Glucose 250 g/L

Slight Problems

• What can go wrong?

• Errors given by the analytical equipment

• Error in reading gas meter

• Water bath can stop working

• Error given by misuse of analyzer

• Faulty impeller motor shaft

• Faulty pumps

Kinetic Modeling

Glucose and Ethanol Concentration vs Time

0

5

10

15

20

0 500 1000 1500T ime (min)

Subs

trat

e C

once

ntra

tion

(g/L

)

0

1

2

3

4

5

6

7

8

9

10

Eth

anol

Con

cent

ratio

n (g

/L)

Subst rate Concent rat ion Model-SEthanol Concent rat ion Model-P

Xrdt

dXX

Xqrdt

dSSS

Xqrdt

dPPP

2.5

44.12

1.0

386.0

P

S

I

m

I

m

q

q

K

SK

S

μm = maximum specific growth rate

KI = saturation coefficient for cell growth

qP = specific ethanol production rate

qS = specific glucose production rate

• Experimental data consistent with basic Monod model• Kinetic parameters are obtained from Baltes (1994, Biotechnol. Prog.)

Final Thoughts

• Ethanol is NOT the answer – As fuel or to drown your sorrows!

• Multi-prong approach is necessary to solve world’s energy problems– Solar, Wind, Biogas, Bio-oil, Biodiesel, Biochemicals, …

• Multidisciplinary efforts are necessary to make it work

• Applied engineering and scale-up research will make solutions feasible and cost effective

• Alternative energy technologies must have legs of its own to survive– No tax credits– No government incentives

• What you learn in this class will help solve the problems of today and of the future

Questions