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UNIVERSITÀ DEGLI STUDI DI NAPOLI FEDERICO II
DIPARTIMENTO DI INGEGNERIA CHIMICA DEI MATERIALI E DELLA PRODUZIONE INDUSTRIALE
Project ETB-2012-26
OPTISOLV - Development, optimization and scale-up of biological solvent production
3nd International Meeting
PortoMantovano, December 01, 2014
F. Raganati
SUMMARY
Biofilm reactors Start Up Glucose/Lactose Lactose Scheduled Activity
The ABE fermentation process by adopting renewable resources. Characterization in terms of kinetics and yields.
simple sugars (glucose, fructose and sucrose) typically present in high sugar content beverages;
High Sugar Content Beverages Scheduled Activity
Characterization of the ABE fermentation process. Dynamic kinetic modelling Solventogenic Kinetics Scheduled Activity
Series of4 PBR: Butanol
Production
MEDIUM
TANK
Nutritional Factors
Concentration [g/L]
Sugar 60
Yeast Extract 5
NH4Cl 2
K2HPO4 0.25
KH2PO4 0.25
MgSO4 0.2
FeSO4 0.01
MnSO4 0.01
1 2 3 4
TASK 1.2: SET-UP OF A CONTINUOUS REACTOR IN LAB-SCALE
Voverall = 160 mL
Porto Mantovano – December 1, 2014
BIOFILM REACTORS: CONTINUOUS BUTANOL PRODUCTION. GLUCOSE/LACTOSE
1 2 3 4
0 1 2 3 4 50
1
2
3
4
5
6
7
8
9
10
11
12
13
14G 75% - L 25%
G 50% - L 50%
G 25% - L 75%
L 100%
n° reactor
Bg/L
0 1 2 3 4 50
10
20
30
40
50
60G (G 75%- L 25% )
G (G 50% - L 50%)
G (G 25% - L 75%)
G (L 100%)
L (G 75% - L 25%)
L (G 50% - L 50%)
L (G 25% - L 75%)
L (L 100%)
n° reactor
Sugarg/L
Total Sugar60 g/L
D = 0.15 1/h
Specific lactose production:4 stages @ D = 0.15 1/h: 0.9 g/Lh1 stage @ D = 1 1/h: 4.5 g/Lh
1 stage
Porto Mantovano – December 1, 2014
4 stages
0 1 2 3 4 50
1
2
3
4
5
6
7
8
9
10
11
12
13
n° reattore
Bg/L
0 1 2 3 4 50
10
20
30
40
50
60
Latg/L
BIOFILM REACTORS: CONTINUOUS BUTANOL PRODUCTION. LACTOSE
1 2 3 4
0 1 2 3 4 50
1
2
3
4
5
6
7
n° reactor
ABg/L
0 1 2 3 4 50
1
2
3
4
5
Dtot=0.15
Dtot=0.2
Dtot=0.25
Dtot=0.35
Dtot=0.45
Dtot=0.55
Dtot=0.65
Dtot=0.75
Dtot=0.85
Dtot=0.9
AAg/L
1 stage
4 stages
BIOFILM REACTORS: CONTINUOUS BUTANOL PRODUCTION. LACTOSE
1 2 3 4
Porto Mantovano – December 1, 2014
0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90 1.000
1
2
3
4
5
6
7
8
9
10
D - h-1
Buta
nol P
roduct
ivit
y -
g/L
h
1 stage
4 stages
BIOFILM REACTORS: SCHEDULED ACTIVITY
1 2 3 4
Porto Mantovano – December 1, 2014
Series of 4 packed bed reactors Continuous additional in line feeding between bioreactors
addition of glucose to the 2nd or 3rd bioreactor at D= 0.1 h -1.
addition of AA, AB, glucose or combination of those to the 2nd bioreactor at
D=0.15-0.2 h-1 in concentrations that simulated conditions in the flow from the
1st to 2nd bioreactor at high dilution rates.
addition of butanol at concentrations of around 0.5 g/to the feed to the 1st
bioreactor at D= 0.1-0.15 h-1.
operation of the system at different glucose concentration in the feeding stream.
SUMMARY
Biofilm reactors Start Up Glucose/Lactose Lactose Scheduled Activity
The ABE fermentation process by adopting renewable resources. Characterization in terms of kinetics and yields.
simple sugars (glucose, fructose and sucrose) typically present in high sugar content beverages;
High Sugar Content Beverages Scheduled Activity
Characterization of the ABE fermentation process. Dynamic kinetic modelling Solventogenic Kinetics Scheduled Activity
THE ABE FERMENTATION PROCESS BY ADOPTING RENEWABLE RESOURCES: HSCB
Batch tests using single representative sugars
Batch tests using a mixture of the 3 sugars
GFS
Kinetic characterization
Nutritional Factors
Concentration [g/L]
Sugar 60
YE 5
NH4Cl 2
K2HPO4 0.25
KH2PO4 0.25
MgSO4 0.2
FeSO4 0.01
MnSO4 0.01
CaCO3 5
Syrups:Lemon & Almond
Fruit juices:Pineapple & Pear
Soft drinks:Coca cola & Sprite
Sport drinks:Powerade
COMPLEX MEDIUM
Porto Mantovano – December 1, 2014
Porto Mantovano – December 1, 2014
THE ABE FERMENTATION PROCESS BY ADOPTING RENEWABLE RESOURCES: HSCB
Unsupplemented
Medium (HSCB)
Supplemented
Medium (HSCB+)
Hydrolized
Supplemented
Medium (HHSCB+)NO
GROWTH
Lack of some indispensable
nutrients
• Glucose conversion: complete • Fructose conversion: almost complete
about 10 g/L of butanol were produced
a significant amount of sucrose was unconverted
tests with hydrolysed HSCB+ (HHSCB+) were performed
improved solvents production and sugar conversion degree
13 g/L
THE ABE FERMENTATION PROCESS BY ADOPTING RENEWABLE RESOURCES: SCHEDULED ACTIVITY
HSCB as complex substrate to feed the 4 PBR in series.
1 2 3 4
Porto Mantovano – December 1, 2014
SUMMARY
Biofilm reactors Start Up Glucose/Lactose Lactose Scheduled Activity
The ABE fermentation process by adopting renewable resources. Characterization in terms of kinetics and yields.
Simple sugars (glucose, fructose and sucrose) typically present in high sugar content beverages;
High Sugar Content Beverages Scheduled Activity
Characterization of the ABE fermentation process. Dynamic kinetic modelling Solventogenic Kinetics Scheduled Activity
CHARACTERIZATION OF THE ABE FERMENTATION PROCESS: DYNAMIC KINETIC MODEL
A kinetic dynamic model of acetone–butanol–ethanol (ABE) production by Clostridium acetobutylicum DSM 792 was developped according to the biochemical networks simulator COPASI
Substrate effects investigation: • glucose, mannose, fructose• sucrose, lactose• xylose, and arabinose
• The Embden-Meyerhof-Parnas (EMP) pathway for hexoses and disaccharides
• The pentose phosphate (PP) pathway for pentoses.
Porto Mantovano – December 1, 2014
The proposed model was an update of the model by Shinto et al. (2007, 2008)*
Kinetics Shinto et al. Proposed Model
Substrate Inhibition+
Non Competitive Butanol Inhibition
Substrate Inhibition+
Complete Butanol Inhibition
BA Activation +
Non Competitive Butanol Inhibition
BA Activation+
CompleteButanol Inhibition
Non Competitive Butanol Inhibition
Multi ProductInhibition
Mass ActionSpecific Butanol Activation
Porto Mantovano – December 1, 2014
Glu Man Fru Suc Lac Ara Xyl
ProposedModel
0.855 0.812 0.820 0.800 0.904 0.848 0.830
Shinto et al.(2007-2008)
0.894 0.887 0.870 0.880 0.925 0.904 0.890
The r2 increased with respect to that calculated for Shinto’s simulation, whatever the tested sugar
The results confirmed that the structure of the present model improved the simulation results.
The soundeness of the model has been tested according to two procedures:
the assessment of the average squared correlation coefficients (r2) between the simulation results and the experimental data.
the comparison of the results of the presenet model with those reported by Shinto et al. (2007-2008).
r2
Porto Mantovano – December 1, 2014
CHARACTERIZATION OF THE SOLVENTOGENESIS KINETICS: THEORETICAL FRAMEWORK
R = 0.14, 0.54 and 0.88
D = 0.02 - 0.15 h-1.
The system was described by the equation set:
BIOMASS BALANCE
CELL TRANSFORMATION PATHS
REACTION SET
Porto Mantovano – December 1, 2014
CHARACTERIZATION OF THE SOLVENTOGENESIS KINETICS: RESULTS
R=0.88
The concentration of acidogenic cells increases linearly with D while the spore concentration decreases exponentially with D
The concentration of solventogenic cells is almost constant with D except for a little increase at low D
As D increases, the progressively shift toward a less harsh conditions – low concentration of solvents and acids – promotes the presence of acidogenic cells at spore’s expense
Porto Mantovano – December 1, 2014
The agreement between the model prediction and experimental data is satisfactory.
CHARACTERIZATION OF THE SOLVENTOGENESIS KINETICS: RESULTS
rBMAX
gB/gDMhKL
g/LKAA
g/LKBA
g/LKB
g/L
5 0 0.8 0.05 0.48
The production rate of butanol referred to the mass unit of solventogenic cells was calculated for all tests.
Lactose, acetic acid and butyric acid were considered as substrate and butanol as the inhibition product (Monod-Boulton model)
Porto Mantovano – December 1, 2014
CHARACTERIZATION OF THE ABE FERMENTATION PROCESS: SCHEDULED ACTIVITY
Model of a Biofilm PBR
Model based on:
Porto Mantovano – December 1, 2014
Dynamic Model
Acidogenic Kintics
Solventogenic Kintics
List of contributions
Raganati, F., Olivieri, G., Procentese, A., Russo, M. E., Salatino, P., Marzocchella, A. (2013). Butanol production by bioconversion of cheese whey in a continuous packed bed reactor. Bioresource Technology, 138, 259–265
Raganati, F., Procentese, A., Olivieri, G., Russo, M. E., Marzocchella, A.. MFA of Clostridium acetobutylicum pathway: the role of glucose and xylose on the acid formation/uptake. Chemical Engineering Transactions. 2014 V. 38, p.193-198
A. Procentese, T. Guida, F. Raganati, G. Olivieri, P. Salatino, A. Marzocchella. Process Simulation of Biobutanol Production from Lignocellulosic Feedstocks. Chemical Engineering Transactions. 2014 V. 38, p.343-438
A. Procentese, F. Raganati, G. Olivieri, M.E. Russo, P. Salatino, A. Marzocchella. Butanol production by fermentation of Clostridium acetobutylicum: solventogenic kinetics. Submitted to Bioresource Technology
F. Raganati, A. Procentese, G. Olivieri, P. Gotz, P. Salatino, A. Marzocchella. Kinetic study of butanol production from various sugars by Clostridium acetobutylicum using dynamic model . Submitted to Biochemical Engineering Journal
F. Raganati, A. Procentese, F. Montagnaro, G. Olivieri, A. Marzocchella. Butanol Production from Leftover Beverages and Sport Drinks. BioEnergy Research. 2014 - DOI 10.1007/s12155-014-9531-8Porto Mantovano – December 1, 2014
UNIVERSITÀ DEGLI STUDI DI NAPOLI FEDERICO II
DIPARTIMENTO DI INGEGNERIA CHIMICA DEI MATERIALI E DELLA PRODUZIONE INDUSTRIALE
Teresa GuidaAntonio MarzocchellaGiuseppe OlivieriAlessandra ProcenteseFrancesca RaganatiMaria Elena Russo (IRC – CNR)Piero Salatino
WORKING PLAN & PROJECT SCHEDULE
Porto Mantovano – December 1, 2014
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36WP1Task 1.1 D1.1Task 1.2 D1.2Task 1.3 D1.3Task 1.4 D1.4Task 1.5 D1.5Task 1.6 D1.6WP2Task 2.1 D2.1Task 2.2 D2.2Task 2.3 D2.3Task 2.4 D2.4Task 2.5 D2.5WP3Task 3.1 D3.1Task 3.2 D3.2Task 3.3 D3.3WP4Task 4.1 D4.1Task 4.2 D4.2Task 4.3 D4.3Task 4.4 D4.4WP5Task 5.1 D5.1/M5.1Task 5.2 D5.2/M5.2Task 5.3 D5.3
Italy: Jan 1, 2013Germany: May 20, 2013K.O. meeting: May 27, 2013
December 1, 2014
INTERRELATION BETWEEN ENGINEERING AND NATURAL SCIENCE WORK PACKAGES (WP 1,2 AND 3)
Porto Mantovano – December 1, 2014
CHARACTERIZATION OF THE SOLVENTOGENESIS KINETICS: RESULTS
R=0.88
The lactose conversion and the concentration of products (cells and metabolites) decrease with the D
The butanol selectivity increased with D and it approached a constant value of about 0.90 g/g
Butanol and ABE productivities increased with D.• A double slope may be observed in the productivity vs. D
data with a discontinuity at D≈0.1 1/h• the slope at lower D is higher than that at higher D
Porto Mantovano – December 1, 2014
The µ was typically smaller than D and larger than DOUT
the accumulation of acidogenic cells - µ>DOUT - was prevented by the establishment of a cell population controlled by the equilibrium among acidogenic cells, solventogenic cells and spores.
The analysis of µS and of concentration of acids and solvents suggests that acids promote the solventogenic cell formation while solvents inhibit the formation.
The study carried out during the present Ph.D. program aimed at investigating the Acetone-Butanol-Ethanol (ABE) production process by fermentation of renewable feedstocks
The activities were articulated along three paths
The characterization of the ABE fermentation process as regards kinetics and yields using different renewable resources
sugars representative of hydrolized lignocelluloe (glucose, mannose, arabinose and xylose)
sugars representative of high sugar content beverages (glucose, fructose and sucrose)
Characterization of the ABE fermentation process through MFA and dynamic kinetic models
the MFA was adopted to investigate the role of the main reaction steps of the C. acetobutylicum metabolic pathway to convert reference sugars
A kinetic dynamic model of acetone–butanol–ethanol (ABE) production by Clostridium acetobutylicum DSM 792 was proposed using the biochemical networks simulator COPASI.
Development of innovative continuous reactor for the ABE production
High sugar content beverages & Cheese Whey
CONCLUSIONS
Biofilm Packed Bed Reactor
Assessment of the model parameters
The maximum reaction rate of a reaction step depends on the sugar because it depends on the enzyme concentration
The “affinity” constants do not depend on the sugar because they depend on the enzyme responsible of the reaction step but not on its concentration
Parameters of the sugar uptake reactions have been assessed for each sugar according to Servinsky et al. (2010): C. acetobutylicum has sugar-specific mechanisms for the transport and metabolism genes.
*Servinsky et al., (2010). Microbiol. 156:3478–3491
The soundeness of the model has been tested according to two procedures:
the assessment of the average squared correlation coefficients (r2) between the simulation results and the experimental data.
the comparison of the results of the presenet model with those reported by Shinto et al. (2007-2008).