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Atomic Level Structure Characterization of Biomass Pre and Post Lignin Treatment by Dynamic Nuclear Polarization-Enhanced Solid State NMR Frédéric A. Perras, Hao Luo, Ximing Zhang, Nathan S. Mosier, Marek Pruski, and Mahdi M. Abu-Omar J. Phys. Chem. A, Just Accepted Manuscript • DOI: 10.1021/acs.jpca.6b11121 • Publication Date (Web): 27 Dec 2016 Downloaded from http://pubs.acs.org on December 30, 2016

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The Journal of Physical Chemistry

Atomic Level Structure Characterization of Biomass Pre and Post Lignin Treatment by Dynamic Nuclear Polarization-Enhanced Solid-State NMR Frédéric A. Perras,a,1 Hao Luo,b,1,2 Ximing Zhangc Nathan S. Mosier,c Marek Pruski,a,d* and Mahdi M. Abu-Omarb,2* a

US DOE, Ames Laboratory, Ames, IA, 50011, USA

b

Department of Chemistry, School of Chemical Engineering, and the Center for direct Catalytic Conversion of Biomass to Biofuels (C3Bio), Purdue University, West Lafayette, IN, 47907, USA.

c

Laboratory of Renewable Resources Engineering, Department of Agricultural and Biological Engineering, and the Center for direct Catalytic Conversion of Biomass to Biofuels (C3Bio), Purdue University, West Lafayette, IN, 47907, USA d

Department of Chemistry, Iowa State University, Ames, IA, 50011, USA

1

Authors contributed equally to this work.

2

Current address: Department of Chemistry and Biochemistry, Department of Chemical Engineering, University of California, Santa Barbara, CA 93106, USA

*

To whom correspondence should be addressed. [email protected] (M.M.A.-O.)

Email:

ACS Paragon Plus Environment

[email protected] (M.P.),


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Abstract: Lignocellulosic biomass is a promising sustainable feedstock for the production of biofuels, biomaterials, and bio-specialty chemicals. However, efficient utilization of biomass has been limited by our poor understanding of its molecular structure. Here, we report a dynamic nuclear polarization (DNP)-enhanced solid-state (SS)NMR study of the molecular structure of biomass, both pre- and post-catalytic treatment. This technique enables the measurement of 2D homonuclear 13C-13C correlation SSNMR spectra under natural abundance, yielding, for the first time, an atomic-level picture of the structure of raw and catalytically treated biomass samples. We foresee that further such experiments could be used to determine structure-function relationships and facilitate the development of more efficient, and chemically-targeted, biomassconversion technologies.


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1. Introduction Increased atmospheric greenhouse gas concentrations, and other environmental issues resulting from fossil fuel combustion, have motivated the development of renewable energy sources. One such promising renewable energy source is lignocellulose, which is the main component of plant biomass. Lignocellulose has the potential to provide a sustainable source of biomaterials and biofuels, yielding 50-80 EJ of energy per year, and can help diminish our reliance on fossil fuels for energy, improve the carbon balance in the biosphere, and provide high-value chemicals.1,2,3,4,5,6 Lignocellulose is composed of carbohydrate polymers (cellulose, hemicellulose) and lignin. The latter is a heavily cross-linked polymer consisting of three principal building blocks, p-hydroxyphenyl (H), guaiacyl (G), and syringyl (S), which are depicted in Scheme 1. Cellulose has great potential to be used as a renewable fuel source, as it constitutes up to 40-50% of the dry plant mass and can be converted to bioethanol, as well as other high-value chemicals. 7 Unfortunately, lignocellulosic biomass has a rigid and compact structure, due in part to the crystallinity of cellulose and its cross-linking with lignin, 8 , 9 , 10 which renders it particularly resilient to biodegradation.8 The conversion of lignocellulose into valuable products is therefore highly challenging and is an active field of research.11,12 A number of studies have investigated the effects of crystallinity and the degree of polymerization on the enzymatic hydrolysis of cellulose, 13 , 14 , 15 , 16 highlighting the need for pretreatment to expand the accessibility of cellulose.17 The widely accepted model states that pretreatment both increases the surface area of cellulose and converts its crystalline phase into more reactive amorphous cellulose.18,19


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Scheme 1. The aromatic building blocks of lignin: H, G, and S, are depicted in (a), (b), and (c), respectively. Some of the major issues associated with biomass utilization can be overcome if lignin and cellulose are separated. Catalytic depolymerization has been intensively investigated in recent years for this purpose and is regarded as one of the most promising pathways for biomass utilization. Currently, research efforts fall into two categories: catalytic conversion of carbohydrates

(cellulose

and

hemicelluloses)

into

alcohols

and

other

platform

chemicals, 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 and catalytic depolymerization of lignin (CDL) into aromatic products.28,29,30,31,32,33,34 Although a great deal of progress has been achieved, the development and commercialization of these catalytic methods are impeded by a poor understanding of the structure of biomass pre- and post-treatment.35 This is the case due to the lack of appropriate noninvasive physical tools to probe the complex structure of biomass with sufficiently high resolution. To date, some structural data have been obtained by cross-polarization magic angle spinning solid-state NMR (CPMAS SSNMR), X-ray diffraction (XRD), infrared spectroscopy, and electron microscopy,25,26,31,36,37 but the elucidation of definite high-resolution structures has been unattainable. SSNMR is perhaps the only technique capable of providing atomic-level structural information on raw biomass, yet structural complexity leads to severe spectral crowding which


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limits the usefulness of SSNMR data. For this reason the structure of lignin remains largely unexplored by SSNMR. 38 The advent of high-field dynamic nuclear polarization (DNP) combined with magic angle spinning (MAS), an effective hyperpolarization technique used to sensitize solid-state NMR spectroscopy, may very well provide a solution to this dilemma.39,40,41 DNP utilizes the much larger Boltzmann polarization of the electrons in order to enhance nuclear polarization. Low concentrations of biradical dopants are impregnated into the sample, as a source of unpaired electrons, and their electron paramagnetic resonance (EPR) transitions are irradiated by high-power microwaves to transfer polarization, via the so-called cross-effect, to the nuclei.40 The theoretical maximum gain in sensitivity corresponds to the ratio of the magnetogyric ratios of the electron and the nucleus, i.e. to ~660 for 1H and ~2600 for

13

C.

Although the application of DNP does not reduce the line widths, the vast improvement in sensitivity offered by this technique can enable the measurement of two-dimensional (2D)

13

C-

13

C homonuclear correlation spectra at natural isotopic abundance. 42,43,44,45 By spreading the

broad resonances of biomass along a second dimension, many overlapping components can then be separated, and identified, without destroying the sample. Here, we used this new technology to study the atomic-level structure of intact raw and catalytically treated genetic variants of poplar. 2. Results and Discussion 2.1 Catalytic Depolymerization of Lignin We previously reported a unique opportunity for selective CDL of wild-type (WT) poplar as well as two genetic variants having an increased, or decreased, S lignin content (high-S and low-S) (32).46,47 This process involves the treatment of intact lignocellulosic biomass with a Pd/C + Zn(OAC)2·2H2O bimetallic catalyst in methanol under 35 bar of hydrogen at 225 °C, and


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results in the removal and upgrading of lignin to aromatic products. The solid carbohydrate byproduct residue (cellulose and hemicellulose) can then be converted into glucose by cellulose enzyme digestion. For poplar, CDL yields a high selectivity for two phenolic products, 2methoxy-4-propylphenol (1) and 2,6-dimethoxy-4-propylphenol (2) (Scheme 2), which originate from G and S lignin, respectively. Moreover, the variations in the lignin monomer compositions in different genetic variants allow the selectivity between the two products to be tuned (Table 1).

Scheme 2. Catalytic depolymerization of lignin (CDL) from lignocellulosic biomass. Subsequently, we have demonstrated the total utilization of an energy crop, miscanthus, by using an earth-abundant metal catalyst (Ni/C).33, 48 Due to differences in the grass and hardwood cell wall compositions and structures, the lignin component in grass is more easily accessed, thus giving a higher yield.49 Additionally, when compared with wood biomass, grass species contain abundant ferulate and diferulate linkages, which connect hemicellulose with lignin. 50 , 51 , 52 Under hydrodeoxygenation (HDO) reaction conditions, these linkages can be


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selectively cleaved to release ferulic acid as the methyl ester (4) and dihydro p-coumaric acid methyl ester (3) as products (see Scheme 2 and Table 1).

Table 1. Product yields from CDL reactions of lignocellulosic biomass samples.a substrate catalyst % yield of major phenolic products b 1 (G)

2 (S)

3 (H)

4 (G)

WT poplar

Pd/C+Zn(OAc)2

9

23

-

-

Total %Yield 32

high-S poplar

Pd/C+Zn(OAc)2

5

35

-

-

40

low-S poplar miscanthusc

Pd/C+Zn(OAc)2 Ni/C

13 21

13 19

12

16

26 68

a

Reaction conditions: Substrates (1.0 g) milled to 40 mesh, in 45 mL methanol at 225 °C under 35 bar H2 for 12 h. b Yields are calculated based on theoretical lignin content in different biomass substrates. c Reference 33. The CDL reactions are highly selective for the removal of lignin, and thus the remaining cellulose residues become accessible for further transformations. We have confirmed this by performing enzymatic hydrolysis of the raw, and CDL-treated, biomass samples (Figure 1). Prior to CDL treatment, the saccharification yields were very low (c.a. 10%). There were also no significant differences in the saccharification kinetics and yields of the three poplar variants, in spite of the differences in the monomeric constituents of lignin. Contrary to this, microcrystalline cellulose (Avicel) is hydrolyzed to 59% within 72 hours and wood pulp (Solka Floc) is hydrolyzed with high yields (89%). These results are consistent with previous reports and indicate that cellulose is largely inaccessible in raw lignocellulosic biomass because of the crosslinking with lignin. 53 Following CDL treatment, however, the enzymatic hydrolysis yields radically improve for all three genetic variants and exceed the yield achieved with Avicel. The CDL-treated high-S poplar was the best performing material, being completely converted after 72 hours, followed by WT poplar, which performed similar to commercial wood pulp (Solka


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Floc). Ciesielski and co-workers have noticed a similar trend in lignin-modified Arabidopsis thaliana, which they treated with maleic acid prior to enzymatic hydrolysis.54 Their results, as well as ours, indicate that genetic modification of the lignin monomer content has a clear impact on the enzyme digestibility of plant cell walls following a treatment to remove, or rearrange, lignin.53

Figure 1. Enzymatic hydrolysis yields of different cellulose sources are plotted as a function of the reaction time. Wild-type poplar is represented by black squares, low-S poplar by blue circles, and high-S poplar by red triangles. Open symbols represent untreated poplar while filled symbols refer to CDL-treated samples. Green dashes represent Avicel (crystalline cellulose) and purple crosses represent Solka Floc (wood pulp). Error bars represent ±1 standard deviation. Lines are added as a guide to the eye. Surprisingly, we found that the relative crystalline index (RCI) of the three poplar variants, measured by XRD, increased from 46-49% to 67-69% following CDL treatment (see Figure S3 in Supporting Information). Since lignin has highly amorphous structure, its removal may increase the apparent crystallinity of the remaining cellulose.55 The XRD data (Table S1)


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also indicate that there is no correlation between the relative crystallinity of the cellulose and the corresponding enzymatic hydrolysis yields. These findings seem to contradict the general belief that only amorphous cellulose is accessible for hydrolysis17,18 and show that crystallinity is not the sole factor determining the rate of hydrolysis. Other factors, such as surface area and accessibility of cellulose also affect the enzymatic hydrolysis rate.19,56 2.2 DNP-Enhanced SSNMR The proportion of the different linkages connecting the lignin monomers may be the leading cause of the different catalytic efficacies in poplar variants. As mentioned earlier, the information concerning the connectivities between the building blocks of plant cell walls in biomass can only be accessed by 2D One such experiment, namely 2D

13

13

C-13C homonuclear correlation SSNMR spectroscopy.

C refocused Incredible Natural Abundance DoublE

QUAntum Transfer Experiment (INADEQUATE),57,58 is particularly useful because it provides simple to interpret spectra featuring exclusively resonances from pairs of directly bound

13

C

nuclei. Performing such a measurement is unrealistic using conventional SSNMR without isotopic enrichment, as only 1 of ~10,000 carbon-carbon pairs can elicit an NMR response under natural abundance. Recently, Takahashi and co-workers have demonstrated its feasibility under DNP conditions using microcrystalline cellulose.41 It is, however, not immediately clear whether DNP-enhanced SSNMR is applicable to lignocellulosic biomass samples. The large grain sizes can act as barriers for the penetration of the biradical molecules, limiting the efficiency of the hyperpolarization.42,59 (On the other hand, this physical separation between the radicals and the studied biomass assures that its structure remains intact; note also that even the surface and subsurface regions of the sample must be separated from the nearest radical by at least 1 nm to be observed). Nevertheless, DNP has been successfully applied to studying the carbohydrate and


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protein structures of plant cell walls.60 Here, we also observed that biomass samples absorbed meaningful quantities of an AMUPol61 solution and yielded large signal to noise enhancement factors of 65-74, as demonstrated by the 1D

13

C CPMAS spectra in Figure 2. Importantly, the

enhancement is identical for both cellulose and lignin; a testament to their interconnected structures. CDL treatment led to a reduction in DNP efficiency (enhancement factors of 26-33, depending on the sample), likely due to either the presence of paramagnetic metal residues, or a reduction in porosity. We first note that very similar 1D 13C CPMAS spectra to those shown in Figure 2 were obtained for untreated and treated samples of wild-type and low-S poplar (see Figures S3 in Supporting Information). All these spectra are dominated by the resonances attributable to cellulose. Although there is a considerable overlap, the C4 resonances from crystalline (88 ppm) and amorphous (82 ppm) cellulose are well resolved in one dimension.62,63 Notably, it can be observed (Figure 2b) that the relative crystalline cellulose content in the CDL-treated samples is similarly higher than in the raw biomass, in agreement with the XRD results. Lignin is represented by only three, very broad, resonances in the 1D spectra of untreated samples, which is due to the similar chemical shifts of the carbon nuclei in the three phenolic monomers of lignin. These peaks are absent in the treated samples confirming high conversion and removal of lignin aromatics during the CDL process. Spectra acquired on CDL-treated miscanthus demonstrate that the CDL method is generally applicable to both grass and wood biomass species (see Figure S4 in the Supporting Information).


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Figure 2. DNP-enhanced 1D 13C CPMAS NMR spectra of raw (a, i), as well as CDL-treated (a, ii) high-S poplar. The spectra acquired with and without the application of microwaves are shown in (a) along with the enhancement factor. Comparisons of the cellulose (b) and lignin (c) regions of the DNP-enhanced CPMAS spectra of the raw (black trace) and CDL-treated (red trace) high-S poplar samples are also shown. Note that the C4 peak of crystalline cellulose (marked on the Figure) has a higher relative intensity in the CDL-treated sample. The complete removal of lignin can be observed in the comparison shown in (c). Remarkably, the improved resolution provided by the DNP-enabled 2D

13

C refocused

INADEQUATE experiment (Figure 3) allows a clear distinction of the three lignin monomers present in the raw samples. Again, as can be seen in Figure 3bi, the 2D spectra are dominated by the resonances from cellulose and acetate. The resonances associated with the lignin monomers, however, appear in an isolated spectral region. The diverse 2D patterns representing this region


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in Figure 3bii-iv remain in striking contrast with the almost indistinguishable 1D CPMAS spectra of the same samples shown in Figure 3ai-iii. It can be seen that, in agreement with the CDL data in Table 1, the wild-type biomass is mainly composed of S lignin and has a smaller content of G and a trace of H lignins. The INADEQUATE spectrum of the high-S poplar variant, however, is very clean and features nearly exclusively S lignin while the low-S poplar mutant has a lower S lignin content and the cross-peaks from G and H lignin monomers are more easily discernable. Although the relative ratios of lignin monomers could be estimated based on the products of the CDL treatment, SSNMR analysis clearly shows that all three types of lignin are successfully depolymerized, as no traces of lignin could be detected post-CDL treatment, even by DNP (Figures 2c and S3). The remaining resonances from the cellulose residue appear to be essentially unaffected in all CDL-treated samples (see Figure S3). The CDL process is then highly specific for lignin, and leaves the cellulose intact without altering the atomic linkages, with the main difference in the cellulose post-CDL treatment being the increased crystallinity, vide supra.


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Figure 3. Lignin regions of the DNP-enhanced 13C CPMAS (a) and refocused-INADEQUATE (b) spectra of raw lignocellulosic poplar variants. The full INADEQUTE spectrum of wild-type poplar is shown in (b, i), displaying the dominance of cellulose and acetate moieties. Enlarged portions of the INADEQUATE spectra for wild-type (ii), high-S (iii), and low-S (iv) poplars are also shown to highlight the cross-peaks originating from lignin monomers. The cross-peaks from S, G, and H lignin are labeled in red, blue, and green, respectively. It is of great interest to be able to also determine the type of linkages that connect the lignin monomers together and crosslink with cellulose; these are depicted in Figure 4. This information could be used to design catalysts specifically tailored for a given type of biomass. Unfortunately, the 13C resonances of these dilute species arise in the 50-100 ppm range and are


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obscured in 1D CPMAS spectra by the strong resonances of cellulose. Again, with the use of the DNP-enabled

13

C refocused INADEQUATE spectra, it is possible to detect the correlations

between a lignin monomer and a linkage moiety (i.e. the 13C(aromatic)-13C(benzylic) cross-peak, see Figure 4a) and as such determine the types of linkages that are present in a given biomass sample. Note that, unfortunately, in many instances only one cross-peak in an INADEQUATE pair can be observed due to the obstruction caused by the t1 noise from the larger cellulose resonances. This t1 noise is greater in a through-space post-C7 64 spectrum and so we were unable to identify long-range correlations.

Figure 4. The different types of inter-monomer lignin linkages that have been identified in the raw, untreated, poplar biomass are drawn in (a). Expanded

13

C refocused INADEQUATE

spectra of high-S (b) and low-S (c) poplar genetic variants are also shown in which the additional 13

C-13C cross-peaks corresponding to the lignin linkages are color-coded according to the carbon

pairs in (a). Black cross-peaks correspond to intra-monomer correlations and cellulose.


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In the spectrum acquired on the high-S lignin poplar an additional strong cross-peak is observed at 137/218 ppm. This resonance (shaded red in Figure 4b) can be assigned to β-O-4 linkages that connect two lignin monomers together and are also known to form ether linkages to cellulose at their α position.65 The very high intensity of this resonance, which is comparable to the intra-monomer cross-peaks, indicates that β-O-4 is by far the dominant linkage that connects S monomers together. Note that this resonance may also overlap with that from a β-β’ linkage; we cannot then comment on the relative quantities of the β-O-4 and β-β’ linkages. Since the β-β’ linkage lacks hydroxyl moieties, however, it is unable to link with the cellulose phase through some ether linkages and thus the majority of lignin-cellulose cross-linking must occur through βO-4 linkages.65 Lower-intensity cross-peaks are also present at 133/337 ppm and 120/220 ppm, which can be assigned to oxidized β-O-4 (C=O) and α-O-4 linkages, respectively. Note that INADEQUATE cannot directly detect C-O-C linkages between lignin and cellulose. Nevertheless, the experimental 13C chemical shift of 81 ppm for the β-O-4 linkage is too high for an alcohol moiety which suggests that a majority of these linkages are connected to the carbohydrate phase via C-O-C bonds. In the case of the low-S lignin sample, the previously dominant resonance from the β-O-4 linkage is greatly diminished while the relative intensities of the other cross-peaks appear to be unaffected. Two new cross-peaks can also be identified at 131/229 ppm and 128/183 ppm which are assigned to β-5 linkages as shown in Figure 4. The birth of these new linkages in the low-S poplar variant is not surprising given the fact that the formation of such linkages is prevented by the methoxy moieties present in the case of S lignin. Importantly, like the β-O-4 linkages, the β-5 linkages possess a hydroxyl group that can link with the cellulose phase by forming an ether linkage and would then affect the interactions between the two constituents of lignocellulose.


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Additionally, it is known that linkages such as β-5 are more resistant to degradation, when compared to β-O-4, which has been attributed to their lessened conformational freedom.66 These β-5 linkages are also the main structural difference between the biomass samples (Figure 4b and c), which may explain the lower enzymatic saccharification yields obtained when a higher proportion of G lignin is present in the parent biomass. 3. Conclusions Clearly, DNP SSNMR provides a new, and powerful, non-destructive tool to study bond connectivity in biomass structures (lignin and cellulose) on the atomic scale. Notably, we have, for the first time, gained significant structural insights into the lignin portion of lignocellulose, which directly impact the catalytic depolymerization of lignin. In particular, we showed that the proportion of lignin’s β-O-4 linkages, which are most easily removed, is increased by genetically modifying the substrate to produce more S lignin. This in turn improves the saccharification yields post CDL treatment. Our measurements also shatter the myth that cellulose crystallinity determines the rate of enzymatic saccharification of cellulose. This new approach avoids the use of invasive chemical analyses to extrapolate to the biomass structure pre- and post-treatment. DNP SSNMR promises to advance biomass utilization technologies by providing structurefunction relationships in the catalytic treatment of diverse biomass species as illustrated herein for poplar. Experimental All DNP-enhanced solid-state NMR measurements were performed using a Bruker MASDNP system equipped with an AVANCE III console, a 263 GHz gyrotron, and a 3.2-mm lowtemperature MAS probe. All samples were wet with a 10-mM solution of AMUPol61 in water, packed into 3.2-mm o.d. sapphire rotors, and sealed with a Teflon plug. These samples were


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then pre-spun using a benchtop spinning station at room temperature, to equilibrate the sample, and then spun at 10-13 kHz at a temperature of 105 K in the probe. In all cases, cross-polarization of 13C spins from hyperpolarized 1H spins was performed using a 1.5 ms contact time. The 1H excitation pulse lasted 2.75 µs. The recycle delays were set to 1.3T1, in order to maximize sensitivity, and lasted between 2.7 and 6.1 s, depending on the sample.

For the CPMAS measurements, 128 scans were accumulated. The refocused-

INADEQUATE measurements were performed using a radiofrequency field strength of 88 kHz for all

13

C pulses and an MAS frequency of 10 kHz. The four double-quantum filtering delays

were set to 3 ms. 32 t1 increments of 33.3 µs were acquired, each being an accumulation of 640 scans. The States method was used to obtain purely absorptive phase 2D line shapes. The cross-peaks in the 2D refocused INADEQUATE spectra were assigned using ChemBioDraw-predicted chemical shifts, which are as accurate as DFT calculated ones for simple organics67 and are sufficiently accurate to assign the broad peaks observed here. Comprehensive sample preparation and characterization details are given in the supporting information. Associated Content Supporting Information Detailed synthesis and experimental details, powder X-ray diffraction data and supplementary Figures. This information is available free of charge via the Internet at http://pubs.acs.org. Acknowledgements This research was supported by the Center for direct Catalytic Conversion of Biomass to Biofuels (C3Bio), an Energy Frontier Research Center (EFRC) funded by the U.S. Department


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of Energy (DOE), Office of Science, Office of Basic Energy Sciences under award no. DESC000097, and the National Science Foundation Engineering Research Center program (EEC0813570). Solid-state NMR studies at Ames Laboratory were supported by the U.S. DOE, Office of Basic Energy Sciences, Division of Chemical Sciences, Geosciences, and Biosciences, and through a Spedding Fellowship (F. P.) funded by the Laboratory Directed Research and Development (LDRD) program. The Ames Laboratory is operated for the DOE by Iowa State University under Contract No. DE-AC02-07CH11358. F. P. thanks NSERC (Natural Sciences and Engineering Research Council of Canada) and the Government of Canada for a Banting Postdoctoral Fellowship. Reference 1. Serrano-Ruiz J. C.; Luque R.; Sepúlveda-Escribano A. Transformations of Biomass-Derived Platform Molecules: From High Added-Value Chemicals to Fuels via Aqueous-Phase Processing. Chem. Soc. Rev. 2011, 40, 5266-5281. 2. Xu C.; Arancon R. A. D.; Labidi J.; Luque R. Lignin Depolymerization Strategies: Towards Valuable Chemicals and Fuels. Chem. Soc. Rev. 2014, 43, 7485-7500. 3. Lange J. P. Lignocellulose Conversion: an Introduction to Chemistry, Process and Economics. Biofuels, Bioprod. Biorefin. 2007, 1, 39-48. 4. Dale B. E.; Kimm S. In Biorefineries – Industrial Processes and Products: Status Quo and Future Directions; Kamm B.; Gruber P. R.; Kamm M., Eds.; Wiley: Chichester, 2006, pp. 4166.


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