Lignin properties contributing to monomer i ld d i i l biyields during simultaneous biomass
delignification and lignin depolymerization
Thanaphong Phongpreecha, Nicholas Hool, Kendall Christy, David Hodge
Chemical Engineering & Materials ScienceChemical Engineering & Materials ScienceMichigan State University
22 J 201622 June, 2016
www.glbrc.org
Cellulosic DuPont DuPont –– NevadaNevada,,Iowa, USA Iowa, USA –– 2525M gal/yrM gal/yr
Ethanol AbengoaAbengoa –– Hugoton, Hugoton, Kansas, USAKansas, USA25M gal/yr25M gal/yr
RaízenRaízen ‐‐ Piracicaba, São Paulo, Piracicaba, São Paulo, BrazilBrazil12M gal/yr12M gal/yr
25M gal/yr25M gal/yr
Beta Renewables, Beta Renewables, CrescentinoCrescentino, Italy , Italy ‐‐ 25M gal/yr25M gal/yr
GranBioGranBio –– São São Miguel dos Miguel dos Campos, Campos, AlagoasAlagoas, Brazil , Brazil –– 1212M gal/yrM gal/yrPoetPoet‐‐DSM DSM –– Emmetsburg, Emmetsburg, Iowa, USA Iowa, USA ‐‐ 25M gal/yr25M gal/yr
Cellulosic DuPont DuPont –– NevadaNevada,,Iowa, USA Iowa, USA –– 2525M gal/yrM gal/yr
Ethanol AbengoaAbengoa –– Hugoton, Hugoton, Kansas, USAKansas, USA2525M gal/yrM gal/yr
RaízenRaízen ‐‐ Piracicaba, São Paulo, Piracicaba, São Paulo, BrazilBrazil12M gal/yr12M gal/yr
2525M gal/yrM gal/yr
Challenges1. Logistics – Year‐round supply, storage, transportation2. Low atom efficiency
1000 k bi 300 k th l bi f lBeta Renewables, Beta Renewables, CrescentinoCrescentino, Italy , Italy ‐‐ 25M gal/yr25M gal/yr
e.g. 1000 kg biomass < 300 kg ethanol biofuel3. High CAPEX relative to sugar‐ and starch‐derived ethanol4 Processing challenges – Solids handling biomass4. Processing challenges Solids handling, biomass
heterogeneity5. Need to diversify co‐product portfolio beyond ethanol
GranBioGranBio –– São São Miguel dos Miguel dos Campos, Campos, AlagoasAlagoas, Brazil , Brazil –– 12M gal/yr12M gal/yrPoetPoet‐‐DSM DSM –– Emmetsburg, Emmetsburg, Iowa, USA Iowa, USA ‐‐ 25M gal/yr25M gal/yr
y p p y‐ Opportunity for co‐products from lignin if conversion and
recovery challenges can be overcome
p‐xylene Terephthalicacid
Isobutanol
RenewablePolymersPolyethylene,
FDCA C2H2
PLAPHAsPET, …
EthyleneAcrylic Acid
Lactic Acid
Renewable
C2H5OHEthanol
h dRenewableSugars (Glucose)
3‐hydroxy‐propionic acid
ic
Succinic Acid 1,4 butanediol(BDO)
al
al/Catalyti
Propylene, Isobutene, Butadiene
Biologic
Chem
ica
Lignin Applicationsh ll
Combustion
Gasification
Challenges1. Structural complexity and variability
of ligninsSynthesis of fuels and chemicals
Polymeric material
of lignins2. Process lignins often significantly
modified, reduced reactivity/utility 3 Need to isolate & purify the processPolymeric material
Dispersant, emulsifier, stabiliser or sequestrant
3. Need to isolate & purify the process lignins
4. Lignin conversion processes tend to Materials:
• Adhesives, thermosetresins
require severe conditions 5. Complex mixtures of products
• Low yields of single compounds, • Polymer modifiers
Carbon fiber
Aromatic monomers
purification required6. Costs vs. petrochemical alternatives
Aromatic monomers
Scope of PresentationScope of Presentation
1. Linking Fractionated, Alkali Hardwood Lignin Properties to Aromatic Monomer YieldsProperties to Aromatic Monomer Yields
2. Integrated Catalytic Deconstruction of Woody Biomass: Simultaneous Delignification and Lignin Conversion
1. Linking Fractionated, Alkali Hardwood Lignin Properties to Aromatic Monomer YieldsProperties to Aromatic Monomer Yields
Fractionated Hybrid Catalytic Depolymeri ation
Aromatic Poplar Lignins Catalytic Depolymerization Monomers
Correlating Properties to Yields
1. Linking Fractionated, Alkali Hardwood Lignin Properties to Aromatic Monomer Yieldsp
• Lignins– Mild soda pulping of hybrid poplar
Goal: Relate lignin properties to• Fractionation
– SLRP process– Unpressurized CO2; ambient T
properties to product yields
Unpressurized CO2; ambient T• Conversion approaches– Catalytic oxidationThi id l i– Thioacidolysis
• Lignin characterization– 1H NMR ArOH; Aliphatic OH; p– 13C NMR β‐O‐4– HSQC NMR β‐β, β‐5, β‐O‐4, S/G GPC Molecular weight– GPC Molecular weight
– GC/MS Lignin products
Impact of Delignification Conditions on Poplar Enzymatic Hydrolysis Yields
Enzymatic Hydrolysis
Alkaline Delignification
p y y y
St kl t l (2015)
HydrolysisDelignification
LigninsPopulus nigra x )
80
90
100
Stoklosa et al. (2015). Bioenerg Res., 8:1224‐1234.
maximowiczii cv. NM6)
40
50
60
70
80
ose Yield (%
)
Pulping Conditions:Pulping Conditions:Pulping Conditions:
0
10
20
30
Gluco Pulping Conditions:
170°C, 1 hour54% biomass/pulp yield85% of lignin removed
Pulping Conditions: 150°C, 3 hour67% biomass/pulp yield62% of lignin removed
Pulping Conditions: 150°C, 30 minutes78% biomass/pulp yield51% of lignin removed
0 24 48 72 96 120
Time (hours)
H‐Factor = 579 H‐Factor = 1430H‐Factor = 166
Lignocellulose Deconstruction and ConversionLignocellulose Deconstruction
Enzymatic Hydrolysis
Alkaline Delignification HydrolysisDelignification
LigninsPopulus nigra x ) Ligninmaximowiczii cv. NM6)
Deconstruction
Lignin (Fractionation? +) Depolymerization
IntermediatePhenolic Monomers Lignin Oligomers
IntermediateProducts
Additional Processing
Additional Processing
Additional Processing
Conversion of Intermediates
“Other” Lignins
Final Products(Targeting Diverse
k S )
Processing Processing Processing
High‐value flavor and fragrance
d
Bulk Aromatics
Novel bio‐based foams, adhesives
d ti
Intermediates
Lignin‐derived solid fuels for
h tMarket Sectors)
Increasing Product Value
compounds and coatings
Product 1 Product 2 Product 3 Product 4
process heat
Lignin Fractionation by CO2 Acidification
1 SLRP Process Recovered Lignin Stoklosa et al., 2013. Green Chem. 15:2904‐29121. SLRP Process
• CO2 acidification of alkaline black liquor at elevated temperature pH 11 10 5
gFractions
liquor at elevated temperature and pressure– Generation of hydrated lignin phase
d l d
pH 11, 10.5
– Liquid‐liquid separation
2. Atmospheric acidificationpH 2, 9, 10, 10.6, 11
• 50 mg/g catalyst (CuSO )
Lignin Depolymerization: Oxidationh d d d/50 mg/g catalyst (CuSO4)
loading; 2 M NaOH; T = 180°C; 0.5 MPa O2
• Maximum yields achievable
• Further degradation and/or repolymerization of monomers
• Maximum yields achievable at 5‐7 minutes
14
16
Lignin
8
10
12
d on
Klason
ass Ba
sis)
2
4
6
onom
er Yield
(% M
a
0
2
0 3 5 7 10 14
Mo
Time (min)
Lignin Depolymerization: Hydrogenolysis• Lignin depolymerization in ethanol with Ni/CLignin depolymerization in ethanol with Ni/C catalyst at 220˚C
• No addition of H• No addition of H2
– Simultaneous alcohol reforming and hydrogenolysis
ld h• Lower yields than thioacidolysis or
doxidation – Lower solubility?
a
– Contaminating metals?
ssing Data
Mi
Atmospheric Fractionation SLRPpH 2 9 10 10.6 11 10.5 11
Monomer Yields as a Function of Lignin Recovery Conditions 7
8
9
10
12
14
16
18
drogen
olysis
Oxidation
of Lignin Recovery Conditions• Diverse range of yields
• Comparable trends between3
4
5
6
4
6
8
10
mer Yield by Hyd
nomer Yield by O
• Comparable trends between methods 0
1
2
0
2
4
0 5 10 15 20
Mon
om
Mon
Monomer Yield by Thioacidolysis
16
18
20
Lignin
Acetosyringone AcetovanilloneSyringic acid Vanillic acidSyringaldehyde Vanillin4‐Hydroxybenzaldehyde 16
18
20
Lignin
ass)
p‐Hydroxyphenyl Monomers
Guaiacyl Monomers
Syringyl Monomers
8
10
12
14
eld on
Klason L
Mass Ba
sis)
10
12
14
elds on Klason
olyis (%
by Ma
2
4
6
8
Mon
omer Yie
(% M
4
6
8Mon
omer Y
ieby
Thioacid
0
2
2.00 9.00 10.00 10.60 11.00 10.5‐10 11‐10.5 12.0‐11
pH
0
2
2.00 9.00 10.00 10.60 11.00 10.5‐1011‐10.512.0‐11
pHAtmospheric Fractionation SLRPpH 2 9 10 10.6 11 10.5 11
Atmospheric Fractionation SLRPpH 2 9 10 10.6 11 10.5 11
Lignin Aromatic and Aliphatic Hydroxyl• 1H NMR to quantify MeO ArOH Aliphatic OH• 1H‐NMR to quantify MeO, ArOH, Aliphatic OH• Normalized to a per monomer basis using MeO and S/G ratio• Strong correlation between aromatic hydroxyl content and g y yalkaline solubility– pKa of ArOH ≈ 10.5
• Correlation with other properties?• Correlation with other properties?
1 60
1.801.00 % molPhOH % mol AlOH
r mer
1.20
1.40
1.60
0.70
0.80
0.90
r mon
omer
per mon
om
Ph lhβ l0.60
0.80
1.00
0.50
0.60
0.70ArO
Hpe
r
phatic OH p
‐(β‐O‐4)
Phenylcoumaran(β‐5 + α‐O‐4)
etherβ aryl 0.400.40 A
lip
Atmospheric Fractionation SLRPpH 2 9 10 10.6 11 10.5 11
Alkyl‐Aryl Ether Content • β‐O‐4 contents estimated by integrating Cγ peak of β‐O‐4 per MeO with S/G ratios taken into account
• Clear trend of decreasing β‐O‐4 content with decreasing pH of separation
QuantitativeQuantitative 13C NMR β-O-4 per 100 Ar Mn
7000
8000
30
35
Mnβ‐O‐4
4000
5000
6000
15
20
25β O 4
1000
2000
3000
5
10
δ (ppm)
002 9 10 10.6 11 10s 11spH 2 9 10 10.6 11 10.5 11Atmospheric Fractionation SLRP
2‐D 1H‐13C HSQC NMR: Lignin Structures
β‐O‐4 content βas recovery pH
) m)
13C δ(ppm
)
13C δ(ppm
1
1H δ (ppm)1H δ (ppm)
Correlating Properties
R² = 0.98920.60
0.70
0.80
0.90
per A
r)
0.20
0.30
0.40
0.50
ArO
H Con
tent (
0.00
0.10
0 10 20 30 40
A
β‐O‐4 Content by 13C NMR (per 100 Ar)
5000
6000
7000
8000
age MW
R² = 0.9857
1000
2000
3000
4000
Num
ber A
ver
0
1000
0 10 20 30 40
β‐O‐4 Content by 13C NMR (per 100 Ar)‐1 ‐0.5 0 0.5 1
Correlating Properties
R² = 0.98920.60
0.70
0.80
0.90
per A
r)
0.20
0.30
0.40
0.50
ArO
H Con
tent (
0.00
0.10
0 10 20 30 40
A
β‐O‐4 Content by 13C NMR (per 100 Ar)
5000
6000
7000
8000
age MW
R² = 0.9857
1000
2000
3000
4000
Num
ber A
ver
‐0.99
0.99
0
1000
0 10 20 30 40
β‐O‐4 Content by 13C NMR (per 100 Ar)‐1 ‐0.5 0 0.5 1
Relating Monomer Yields to Lignin Properties
• Clear correlations betweenClear correlations between many properties
i ld l l d d• Yields clearly dependent on initial β‐O‐4 content
‐1 ‐0.5 0 0.5 1
Prediction of Maximum Possible Monomer Yields from LigninMonomer Yields from Lignin
triadn‐3
m3d1 m4
d2 d3m1 m2 mn 1dn‐3 mdn‐2 dn‐1mn 2mn 3
triad1
mi
triadn‐2
m3 m4m1 m2 mn‐1 mnmn‐2mn‐3
triad2
mi
n‐8n = number of monomers in polymer m is a monomerp yn‐1 = number of dyads (adjacent monomer pairs)
that could be linked by an aryl ethern 2 = number of triads (adjacent dyads)
d is a dyadFlory and Fujiwara. (1969). Macromol. 2(4):315‐327
• Simplified model of lignin assuming:
n‐2 = number of triads (adjacent dyads) ( )
– Population of linear polymers of length n with randomly distributed β‐aryl ethers (no cross‐linking/branching)
– Depolymerization is only C–O cleaving
Prediction of Maximum Possible Monomer Yields from LigninMonomer Yields from Lignin
triadn‐3
m3d1 m4
d2 d3m1 m2 mn 1dn‐3 mdn‐2 dn‐1mn 2mn 3
triad1
mi
triadn‐2
m3 m4m1 m2 mn‐1 mnmn‐2mn‐3
triad2
mi
n‐8n = number of monomers in polymer m is a monomerp yn‐1 = number of dyads (adjacent monomer pairs)
that could be linked by an aryl ethern 2 = number of triads (adjacent dyads)
d is a dyadFlory and Fujiwara. (1969). Macromol. 2(4):315‐327n‐2 = number of triads (adjacent dyads) ( )
• Probability that any triad contains two adjacent β‐aryl ethers is the β‐aryl ether content squaredethers is the β aryl ether content squared
• P((A ∩ B) C) = P(A) P(B) + P(C)• Expected value for yield is:
[ ] [ ])Content4-O-(2)Content4-O-()2n(n1YieldE 2 β×+β×−=
Expected value for yield is:
Prediction of Maximum Possible Monomer Yields from LigninMonomer Yields from Lignin
• Probability that any triad contains two adjacent β‐aryl ethers is the β‐aryl ether content squaredethers is the β aryl ether content squared
• P((A ∩ B) C) = P(A) P(B) + P(C)• Expected value for yield is:
[ ] [ ])Content4-O-(2)Content4-O-()2n(n1YieldE 2 β×+β×−=
Expected value for yield is:
Prediction of Maximum Possible Monomer Yields from LigninMonomer Yields from Lignin
• Expected value for monomer yield is:
[ ] [ ])Content4-O-(2)Content4-O-()2n(n1YieldE 2 β×+β×−=
p y
Prediction of Maximum Possible Monomer Yields from Lignin
• Thioacidolysis yields match model prediction
• Higher yields for oxidation due to cleavage of C C bonds?
Monomer Yields from Lignin
• Higher yields for oxidation due to cleavage of C–C bonds? • Lower yields for hydrogenolysis
16%
12%
14%
16%
Predicted
l/mol)
ThioacidolysisOxidationHydrogenolysis
6%
8%
10%
Mean Max.
er Yield (m
ol n = 10n = 15n = 25
2%
4%
6%
Measured or
Mon
ome n 100
0%0% 5% 10% 15% 20% 25% 30% 35%
M
β‐O‐4 Content
Prediction of Maximum Possible Monomer Yields from Lignin
• Thioacidolysis yields match model prediction for: – Fractionated alkali lignins from hybrid poplar (NM6)
Monomer Yields from Lignin
– In situ lignins from diverse Populus trichocarpa genotypes
– Extracted lignins from silver birch (Betula pendula)
ed Yield n
Birch CEL Lignin
r Qua
ntifie
edicted or
Pre
Scope of PresentationScope of Presentation
1. Linking Hardwood Lignin Properties to Aromatic Monomer YieldsMonomer Yields
2. Integrated Catalytic Deconstruction of Woody Biomass: Simultaneous Delignification and Lignin Conversion
2. Integrated Catalytic Deconstruction of Woody Biomass ‐ Backgroundy g
• Background ‐ Hydrogenolysis– Challenge of low yields from technical lignins due to modification during lignin removal/processing
– High temperature and high H2 pressure required at the expense of selectivity
Meier et al. 1994. Biomass Bioenerg. 40(2):171-177required at the expense of selectivity
– Ni/C capable of H‐transfer from alcohols to lignin with potential for integration with organosolv pretreatment to achieve high
Bioenerg. 40(2):171 177
monomer yields
• Scope of workWang and Rinaldi, 2012. Energ Environ Sci. 5: 8244-8260; Song, et al. 2013. Energ Environ Sci. 6, 994-1007.
– Assess select metal catalysts on an inert support as potential bi‐functional catalysts for simultaneous delignification, alcohol reforming, and hydrogenolysis of lignin directly from birch woodg, y g y g y
– Characterize the effect of lignin removal on enzymatic hydrolysis
– Identify descriptors for hydrogenolysis of lignin model
2. Integrated Catalytic Deconstruction of Woody Biomassof Woody Biomass
Additional Valorization by Catalytic or Biochemical Conversion4. 4. 4.
Sorbitol2. Hydrogenolysis;Hydrogenation
4.
H2Xylitol
4‐propylsyringol4‐propylguaiacol
2
1. Fractionation +Catalytic H‐transfer
LigninXylan
“Other” 3. Hydrolysis
D‐XyloseXylan
CelluloseD‐GlucoseH‐donating Solvent
Enzyme‐or Acid‐Catalyzed
Cellulose
Si l d li ifi i l h l f i d• Simultaneous delignification, alcohol reforming, and hydrogenolysis
Yields and Selectivities at 200°CMonomer Selectivities
(%)
Yi ld b d l i i i l li i• Yields based on total initial lignin
• High selectivities for small range of monomer products
• Cleavage of C–C bonds in side chain region for Pd
Yields and Selectivities at 220°C
(%)
Monomer Selectivities
• Exceptionally high yields for several systemsExceptionally high yields for several systems• No evidence of aromatic ring saturation• Increasing saturation of side chain region for Ru, Co, Ni, and Pd– Reaction products provide evidence for simple reaction pathway
Enzymatic Hydrolysis Yields and DelignificationVisible macroscopic differences and100 Lignin removal Visible macroscopic differences and differences in enzymatic hydrolysis yields due to differences in surface lignin adsorption
60
70
80
90
olysis Yield
gcorrelated to hydrolysis yields
20
30
40
50
Glucose Hydro
220 C
200 C
90
100
(%)
220 C200 C
0
10
0 20 40 60 80 100
G
Lignin Removal
200 C
100d
°°
50
60
70
80
olysis Yields
60
70
80
90
100
olysis Yield
Co
Ni
RuPd
ed
10
20
30
40
ucose Hydro
o Data
20
30
40
50
lucose Hydro Highest monomer yields comparable to highest sugar yields U
ntreate
0
10
None Fe Co Ni Cu Zn Ru Pd Ag
Glu No
0
10
0 20 40 60
G
Aromatic Monomer Yield
Ongoing Work – DFT and MD Studies
Identifying potential descriptors for lignindescriptors for lignin model depolymerization
Adsorption mechanism conformation forAdsorption mechanism, conformation for hypothetical lignins on Ni (1 1 1) surface
Summary
• Lignins can be enriched in select properties by fractionationfractionation
• In fractionated alkali lignins many lignin properties can be correlated to each other and to monomercan be correlated to each other and to monomer yields
• β‐O‐4 content is an important predictor of monomer• β‐O‐4 content is an important predictor of monomer yields from fractionated and native lignins
• Unmodified in situ lignins capable of highest yields• Unmodified in situ lignins capable of highest yields
• Potential for integrated biomass deconstruction processprocess
Acknowledgements
CollaboratorsCollaborators• Cliff Foster, GLBRC• Yue Qi, MSUM k Thi Cl
Funding:• U.S. Department of Agriculture:
• Mark Thies, ClemsonNortheast Sungrant Initiative
Research Group:Dr Ryan Stoklosa Jacob Crowe Thanaphong “Joe” PhongpreechaDr. Ryan Stoklosa, Jacob Crowe, Thanaphong Joe Phongpreecha, Lisaura Maldonado‐Pereira, Georginelly Ferreira Inácio, Angel Santiago‐Colón, Nicholas Hool, Ben Gardner, Nick Ferringa, Kendall Christy
Thank you!
Questions? David HodgeDavid Hodge
Chemical Engineering Mi hi St t U i itMichigan State University Email: [email protected]
Web: http://www.chems.msu.edu/groups/hodge/