Pyrolysis Two-Dimensional GC-MS of Miscanthus Biomass

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Pyrolysis Two-Dimensional GC-MS of Miscanthus Biomass: Quantitative Measurement using an Internal Standard Method Gary Steven Groenewold, Kristyn Marie Johnson, Stephen Carter Fox, Cathy Rae, Christopher A Zarzana, Bethany R. Kersten, Salene M. Rowe, Tyler L. Westover, Garold L. Gresham, Rachel M. Emerson, and Amber N. Hoover Energy Fuels, Just Accepted Manuscript • DOI: 10.1021/acs.energyfuels.6b02645 • Publication Date (Web): 03 Jan 2017 Downloaded from http://pubs.acs.org on January 13, 2017

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Pyrolysis Two-Dimensional GC-MS of Miscanthus Biomass: Quantitative Measurement using an Internal Standard Method Gary S. Groenewold,* Kristyn M. Johnson, S. Carter Fox, Cathy Rae, Christopher A. Zarzana, Bethany R. Kersten, Salene M. Rowe, Tyler L. Westover, Garold L. Gresham, Rachel M. Emerson, and Amber N. Hoover Idaho National Laboratory, 3531 University Boulevard, Idaho Falls, ID, 83415-3531

ABSTRACT Accurate measurement of biomass pyrolysis products can provide valuable guidance for thermal processing.

However, pyrolysis generates large numbers of compounds in varying

concentrations, factors that can make compound identification and quantitation difficult. In this study, Miscanthus biomass samples were analyzed using pyrolysis/two-dimensional gas chromatography/mass spectrometry (Py-GCxGC-MS), which provided a more comprehensive chromatographic separation and mass spectral compound identification.

Quantitative

measurement was performed for 34 calibrated pyrolysis compounds using an internal standard method. Pyrolysis efficiency was measured as a function of sample mass, pyrolysis temperature,

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and pyrolysis temperature ramp rate. For most of the calibrated pyrolysis products, production efficiency decreased with sample mass, increased with pyrolysis temperature, and decreased pyrolysis temperature ramp rate. Significantly, the temperature profiles of the different pyrolysis products were variable, notably acetic acid and the vinyl- and formyl-derivatives of phenol and guaiacol, which were produced at lower temperatures compared to other compounds such as the syringyl derivatives and levoglucosan. Lignol ratios were compared with those generated using 1

H/13C heteronuclear single quantum coherence (HSQC) nuclear magnetic resonance

spectroscopy (NMR). Lower fractions of syringyl-, and guaiacyl-lignols, and higher fractions of the phenol-lignols were generated by Py-GCxGC-MS compared to HSQC-NMR.

Introduction Agricultural production results in generation of a significant quantity of biomass material that has limited food value for either humans or animals, but has potential value as either a source of fuel or commodity chemicals. However the leaves, stalks, and other residues that constitute typical biomass have chemical and physical variations due to a host of factors, including species, geographical location, land management practices, and local weather patterns.1, 2 These variations can affect the value of the processed biomass,3 and consequently, there is an ongoing emphasis on developing biomass characterization methodologies that can predict product value and guide biomass conversion decisions. The research described herein is focused on development of a characterization approach that combines high accuracy identification and quantitative measurement of compounds formed by biomass pyrolysis. Biomass characterization is complicated because the material consists of cellulose, hemicellulose and lignin polymers4-6 whose composition and quantity are difficult to measure.


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The most common method for compositional analysis of biomass is acid digestion followed by HPLC determination of solubilized sugars.7 Biomass polymers can also be pyrolyzed to generate small molecules that can be identified using gas chromatography (GC) in combination with mass spectrometry (MS).8-13 GC/MS characterization studies of biomass pyrolysates and pyrolysis oils are numerous, and pyrolysis (Py)-GC-MS has been applied to corn stalks and food waste,14 switchgrass, alfalfa, and tall fescue,15 birch,16 Bermuda grass,17, 18 and Miscanthus,19 which is the subject of this study. A large number of cellulose-, hemicellulose- and lignin- derived compounds have been identified using mass spectral library searching.20-25 The dominant cellulose-derived product is anhydro-α-glucopyranose (levoglucosan),26 however smaller organic oxygenates are also seen, including furfural, 5-(hydroxymethyl)furfural, acetol, acetic acid and many others.6, 26-28 The pyrolysis process also converts some of the lignin into hydroxy,methoxy-phenylpropane derivatives, for example, p-coumaryl alcohol, coniferyl alcohol, and sinapyl alcohol; these compounds, and other related aromatics, are derived from the p-hydroxyphenyl (H)-, guaiacyl (G)-, and syringyl (S)- classes of lignin.5, 10, 28, 29 Thermogravimetry30 coupled with different measurement instruments, specifically FTIR.31, 32 has also been used to investigate biomass pyrolysis, and significant differences in the decomposition temperatures of the polymer classes were noted: hemicellulose degrades at lower temperatures (220 – 300oC),6, 26, 33 cellulose at 350 - 400oC,6, 33-35 while lignin tends to have a broadened thermogravimetric profile, stretching from ~ 250 to 500oC.6, 33, 36 The large number of pyrolysis products results in instances of chromatographic co-elution, which will compromise identification by searching mass spectral libraries. Two-dimensional gas chromatography (GCxGC) can improve chromatographic separation,37-44 and combined with MS, GCxGC has been used for bio oils from beech,45 rice husks and peach pits,46 pine wood,47, 48


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palm fruit,48 and cellulose, lignin and sewage sludge.49, 50 The percentage of identified compounds in pyrolysate increased from 47% to 70% in one report.49 These considerations motivated application of GCxGC-MS for qualitative identification of pyrolysis products, however a drawback was that most biomass applications of GCxGC-MS have been for qualitative characterization of bio-oil, not quantitative measurement of pyrolysate vapor. For bio-oil or pyrolysate vapor, quantitative measurement has proven to be a challenging task, and so chromatographic or mass spectrometric peak areas are used to estimate fractional concentrations of components.51 Peak area ratios generated using this approach can be correlated to preprocessing efficiency,33 for example S/G ratios can be calculated by summing the mass spectra peak intensities for masses seen in Py-molecular beam mass spectrometry52-54 or summing the extracted ion chromatographic peaks from GC-MS.55 The relative fractions of syringyl- and guaiacyl- lignols can be extracted from these ratios by correlating the results with wet chemical analyses.2, 52-54 Quantitative measurements of pyrolysis products have for the most part utilized external calibrations, and have focused on the volatile gases like H2, CO, CO2 and low molecular weight hydrocarbons, and have been applied to higher temperature processes (e.g. 600 and 1200oC).17, 18, 56 Several investigations have quantitatively measured semi-volatile organics generated by pyrolysis, which have included lighter aromatic and oxygenated compounds.50, 57-61 In principle, more accurate quantitation could be achieved using an internal standard,59 and in fact GC/MS methods have been developed for analysis of pyrolysis oils,62, 63 which showed pyrolysis temperature-dependent production efficiency for different pyrolysis products.62 Attempts to generate quantitative data from GCxGC data have been fewer still, in part because it is not straightforward to generate integrated areas from modulated chromatographic peaks.64


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Both external standard65 and internal standard methods have been employed, the latter using both selected ion monitoring66 and full scan MS methods.67 A quantitative method for the analysis of tentatively identified compounds found in bio oil was worked out using GCxGC-MS for qualitative identification, and GCxGC-FID for quantitation.47 Two internal standards, dibutyl ether and fluoranthene, were used to generate calibrations for eighteen compounds, and the FID response factors were calculated using an effective carbon number, and compared to the actual responses. The comparison indicated that the effective carbon number approach worked well, and hence it was applied to more than 150 other tentatively identified compounds. In the present study, a quantitative methodology for Py-GCxGC-MS is described, that employs an internal standard for 34 pyrolysis products. Production efficiencies for the individual compounds were repeatedly measured on a Miscanthus sample,6 which is a genus of grass species that has good potential as a biomass feedstock. Efficiencies were systematically affected by sample mass, pyrolysis temperature and pyrolysis temperature ramp rate. In addition, lignol ratios were compared with results generated using NMR spectroscopy, providing insight into characterization bias inherent in the pyrolysis process.

Experimental Sample Origin and Preparation The parametric studies presented in this manuscript utilized a sample of Miscanthus giganteus that was acquired from Tifton, Georgia in the 2014 crop year, and is an entry in the Idaho National Laboratory biomass sample repository (Idaho Falls, ID),68 and has been the subject of prior studies.6, 19 The samples were dried and ground to a particle size of 200 µm, and further characterization details are provided in Table S1. Pyrolysis sample tubes were loaded with a


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wad of glass wool, tared, loaded with biomass samples, and reweighed to determine sample mass. The sample tubes were then topped with another small wad of glass wool. Sample mass was varied from 300 µg to 2 mg. The sample tubes were spiked with 1 µL of a 3 millimolar internal standard solution (see below) and allowed to stand for ~ 4 - 12 hours before being loaded into the auto-sampler carousel of the pyrolyzer.

Pyrolysis Pyrolysis was conducted using a CDS Analytical (Oxford, PA, USA) model 5250 pyrolysis autosampler. Pyrolysis tubes were dropped into the pyrolysis chamber, held at 100oC for one second, and then heated further at a pyrolysis temperature ramp rate (PTRR) that varied from 12 to 124oC/s. The maximum temperature (Tmax) was varied from 350oC to 550oC, and samples were held at Tmax for an additional five seconds. Both Boateng56 and Srinivasan61 have estimated that the actual pyrolysis temperature of the biomass is 100 – 125oC lower than the programmed value.

The pyrolysis compounds were sent via a six-way valve into the transfer line, which in

turn was plumbed directly into the injector of the GCxGC. The valve oven was maintained at 300oC during the pyrolysis experiment, while the transfer line was operated at 280oC; we note that these temperatures are lower than the Tmax values, and so it is likely that heavier compounds generated by pyrolysis are condensing and reacting on the walls of the transfer line; we did not see any dimeric species in these analyses.

Two Dimensional Gas Chromatography The GCxGC-MS experiments were conducted using a Leco Pegasus 4D GCxGC-time of flight mass spectrometer (Leco Corp., St. Joseph, MI, USA). The GC utilized in this instrument is an


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Agilent Technologies 7890A system modified to accommodate a secondary oven and a thermal modulator. Compounds from the pyrolyzer were deposited onto the head of the primary GC column via a split-splitless injector, operated at a split ratio of 20:1. The inlet flow was maintained at 1 mL/min over the course of the entire run. Thus the front inlet total flow was 21 mL/min, and temperature was 300oC. The temperature program in the column oven consisted of: a) hold at 50oC for 0.5 min; b) ramped at 7.5o/min to 260oC; and finally c) isothermal at 260oC for 1 min. The GCxGC utilizes two columns connected in a serial fashion using a press fitted column connector. Primary separation was achieved using a 30-meter column with a 250 µm i.d. and a stationary phase film thickness of 0.5 µm. The stationary phase was DB-5ms, which separates compounds roughly on the basis of boiling point.37, 47 Separation in the second chromatographic dimension was achieved using a one meter column with a 100 µm i.d. and a stationary phase film thickness of 0.1 µm. The stationary phase used was Rxi-17, which has a higher fraction of phenyl substituents on the siloxane backbone and functions to separate compounds roughly on the basis of polarity. The secondary column passes through a quad-jet cryogenic modulator (Leco, St. Joseph, MI, USA) situated about 5 cm downstream from the press-fitted connection. The modulator temperature was maintained at 15oC above the primary GC oven temperature. The modulator contains two sets of paired jets, one hot and one cold, that pulse cold nitrogen and hot air, at the section of the column that resides in the modulator.69 A pulse from the first cold jet condenses compounds eluting from the primary column, which are then volatilized by the first hot jet, where they are nearly immediately re-condensed by the second cold jet. The second hot jet then


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re-volatilizes the compounds, enabling them to flow into the secondary column. The sequence is repeated twice because this more sharply defines the chromatographic profiles of the compounds as they enter the remainder of the secondary column. The overall modulation frequency was one cycle per every three seconds (Table S2), with longer cold jet times early in the run to more effectively condense the lighter compounds, and longer hot jet times later in the run, to more effectively volatilize the heavier compounds. After the modulator, the secondary column enters the secondary oven, which contains about 0.79 meters of the overall 1-meter length. The secondary column was maintained at 5oC above the temperature of the primary oven. The remainder of the secondary column (~ 0.20 meter) extends from the secondary oven to the MS ionization source via a transfer manifold that is kept at 280oC. Over the course of a single modulation period, the secondary column operates essentially in an isothermal mode.

Time-of-Flight (TOF) Mass Spectrometry Compounds eluting from the secondary column are detected by a TOF-MS that was operated at an ion source temperature of 250oC. Ionization was accomplished using 70 eV electrons. The time-of-flight mass spectrometer was scanned from m/z 43 to 450, at a rate of 200 scans per second. The fast acquisition rate enabled collection of approximately 20 spectra across a chromatographic peak.

Concentrations of Pyrolysis Compounds (CPCs) Measured using an Internal Standard


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Calibration curves were generated for 34 pyrolysis products that had previously been observed in Py-GCxGC-MS analyses; these compounds are measured in a quantitative fashion, and are designated calibrated pyrolysis compounds, or CPCs. Calibration curves were generated by injecting a dilution series of CPC standard solutions into the GCxGC-MS instrument using a rail auto-sampler (Gerstel MPS2 Multipurpose Sampler version 2.5.2 driven by Maestro software version 1.4.22.11, Mülheim an der Ruhr, Germany). The standard solutions also contained 9(9H)-fluorenone at a constant concentration of 1 mM. This compound served as an as an internal standard: it is not formed by biomass pyrolysis, and it survives volatilization during pyrolysis and transfer through the heated tube connecting the pyrolyzer and the injector of the GC. The s base peak corresponds to the molecular ion at m/z 180, and this together with m/z 152 (loss of CO) was used for quantitation. Calibration curves were generated from the analyses of the standard solutions: the ratio of the peak area of the extracted ion chromatographic peak for quantitation ion(s) of the CPC to that of the fluorenone quantitation ions, multiplied by the quantity of fluorenone was plotted versus the concentration of the CPC injected. Regression analyses generated values for slope, intercept and concentration range for each CPC (Table S3, and Figure 1S). Three µL of the 1 mM 9-(9H)-fluorenone solution was added to the loaded pyrolysis capillary tubes. The method then reports the ratio of the CPC quantitation ions to those of fluorenone. This ratio multiplied by the quantity of the internal standard can be used to calculate the quantity of the CPC generated using the calibration equation generated by the analyses of the standard solutions. The internal standard corrects for variations in compound transfer efficiency in the injector which can be seen in the raw area counts of the internal standard and the CPCs, both in


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the calibration analyses and in the pyrolysis experiments (e.g., Supplementary Information Fig. 2S). A single chromatographic peak in the first chromatographic dimension is divided into multiple modulated peaks in the GCxGC analysis. Chromatographic peak areas for the extracted ion chromatograms have to take this into account and in the present study, peak areas were generated by manually summing all modulated peaks.64 While time consuming, this was necessary because of widely varying chromatographic profiles resulting from varying compound concentrations and chromatographic behavior. In the pyrolysis experiments, products are formed and are transferred to the injector of the GCxGC; at the same time 9-(9H)-Fluorenone is volatilized and transferred to the injector. Thus the analysis produces extracted ion chromatographic peaks derived from the quantitation ions of each CPC, and the internal standard. The product of the quantity of internal standard divided by the CPC-to-IS quant ion ratio produces the measured concentration values in the pyrolysate using the equation generated by the regression analysis of the standard analyses.

Ratios of lignin moieties using HSQC NMR spectroscopy The monolignol composition of the Miscanthus reference material from the Bioenergy Feedstock Library68 was determined using 1H/13C heteronuclear single quantum coherence (HSQC) nuclear magnetic resonance spectroscopy (NMR). The protocol used to make the measurement was adapted from previously published methods for performing HSQC NMR analysis on ball milled biomass in a gelled state70 and acetylated biomass in a solution.71


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The Miscanthus was first ground to pass a 0.2 mm screen. It was then swirled in deionized water and centrifuged. The supernatant after centrifuging was discarded, and the washing process was repeated until the supernatant appeared nearly colorless. Next, the biomass was subjected to Soxhlet extraction using acetone for 18 hours. The recovered biomass was then dried in a vacuum oven at 40 °C. After drying, the about 1 g of the biomass was ball milled using a Retsch PM 100 mill in a 50 mL grinding jar lined with zirconium dioxide. Ten 10 mm diameter zirconium dioxide grinding balls were placed inside the grinding jar, and the jar was sealed in an argon glovebox. The ball mill was programmed to run at 600 rpm for 5 minute intervals followed by 10 minutes of rest. The total program time was 12 hours for a cumulative milling time of 4 hours. The rest intervals were incorporated to allow heat generated during the milling to dissipate. The gel state HSQC NMR analysis was conducted by adding approximately 50 mg of the ball milled Miscanthus to a NMR sample tube. Then 0.5 mL of a 4:1 (v:v) solution of deuterated dimethyl sulfoxide (DMSO) and deuterated pyridine (pyr) was added to the NMR tube. After all of the biomass inside the NMR tube appeared to be wetted by the DMSO/pyr solution, the tube was placed in a sonication bath for 1 hour. The resulting gelled sample was then analyzed in a Bruker Avance 600 NMR using the Bruker hsqcetgpsisp2.2 pulse sequence. The spectral width was 12 ppm with 1024 data points in the 1H dimension and 220 ppm with 512 data points in the 13

C dimension. The interscan delay was 0.5 s, and the number of scans per increment was 512.

During spectral processing, the 13C dimension was zero-filled to 1024 data points. The solution state HSQC NMR analysis of acetylated biomass was conducted by weighing approximately 100 mg of ball milled Miscanthus into a reaction vial with 2 mL DMSO and 1 mL N-methylimidazole. The biomass was stirred for 3 hours, after which 0.5 mL acetic anhydride


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was added. The reaction was stirred for an additional 1.5 hours. The reaction was halted by pouring the solution into 100 mL of a 0.2 M aqueous solution of ethylenediaminetetraacetic acid adjusted to pH = 7. A precipitate immediately formed and was filtered out. The reaction product was resuspended in 100 mL deionized water and again filtered out. The acetylated biomass was then dried in a vacuum oven at 40 °C. Approximately 50 mg of the acetylated Miscanthus was dissolved in deuterated chloroform and transferred to an NMR tube. The sample was then analyzed the same way as the gel state sample, except that the number of data points in the 1H dimension was increased to 2048, the interscan delay was increased to 1.0 s, and the number of scans per increment was 105.

Results and Discussion Biomass pyrolysis generates a wide range of compounds in quantities that are dependent on the parameters used in the pyrolysis process. Hence the objective of this study was to understand the effects of sample mass, the maximum pyrolysis temperature (Tmax), and the pyrolysis temperature ramp rate (PTRR) on the production efficiency of 34 calibrated pyrolysis compounds (CPCs, Table 1). We sought to do this by measuring the production efficiencies of the CPCs in a quantitative fashion using internal standard-based calibrations. Significant pyrolysis research had been conducted in our laboratories using Miscanthus biomass, and so this material was selected for parametric studies. The CPCs have been categorized based on a priori estimates of their origin, viz., cellulose (C, including hemicellulose), phenolic lignin (H), guaiacyl-lignin (G), and syringyl-lignin(S), and compound names for the aromatic lignols have been selected to reflect structure and probable origin. Registry numbers are provided in Table S1 to enable unequivocal identification.


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Chromatographic and Mass Spectrometric Characteristics of the CPCs The one-dimensional gas chromatogram generated from pyrolysis of 600 µg Miscanthus biomass with a Tmax = 500oC and PTRR = 50o/second shows a very complex pattern characterized by broad chromatographic peaks at retention times under 400 seconds, and in addition displaying many other compounds (Figure 1) eluting at longer times. There are many co-eluted peaks which can make compound identification challenging, as a result of mass spectra that are contaminated with contributions from closely eluting compounds. Extracted ion chromatograms (EICs, generated from selected ions representative of the CPCs) provide separation in one-dimensional chromatography in many cases, but not all. Representative EICs generated by the two-dimensional gas chromatography produce multiple, narrow peaks for single compounds eluting from the second column, as a result of the modulator “slicing” single chromatographic peaks eluting from the first column. For example 5-(hydroxymethyl)furfural eluting at about 980 seconds actually shows up as three peaks (or “slices”) in the extracted ion chromatogram of its quant ion m/z 126 (Figure 1b). In pyrolysis experiments, the production of very large quantities of product compounds exacerbates the co-elution problem which is illustrated by the extracted ion chromatograms for m/z 60, the quantitation ion for acetic acid and levoglucosan, and to a lesser extent by furfural and 4-vinylphenol.


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4.0x105

a. tic

2.0x105 0.0 200 intensity

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1.0x105 5.0x10

4

400

600

800

1000

1200

C04 furfural

240 260 280

460 480 500 960

1600

1800

b.

60 96 126

C01 acetic acid

1400

C13 furfural, 5-(hydroxy methyl)

C17 levoglucosan

0.0 6.0x104 4.0x10

G03, guaiacol, 4-vinyl

H03, phenol, 4-vinyl

4

120 150 180

2.0x104

980 1000

1300 1320

G05 guaiacol, 4-formyl

c.

H06 phenol, 4-formyl

122 152

9-fluorenone (i.s.)

0.0 950

1000

1050

1100

1150

1200 1520 1540

Time (s)

Figure 1. a. Total ion chromatogram (TIC) generated by pyrolysis of 600 µg Miscanthus biomass, Tmax = 500 oC, PTRR = 50 oC/second. b. Extracted ion chromatograms for m/z 60, 96 and 126, which are diagnostic for acetic acid and levoglucosan, furfural, and 5-(hydroxymethyl) furfural, respectively. c. Extracted ion chromatograms for m/z 120, 122, 150, 152 and 180, which are diagnostic for 4-vinylphenol, 4-formylphenol, 4-vinylguaiacol, 4-formylguaiacol (vanillin), and the fluorenone internal standard, respectively. Improved chromatographic separation is achieved using two-dimensional chromatography, in this case by employing a 30 m DB-5 column, which achieves separation correlated to boiling point, followed by a 1 m Rxi-17 column, which achieves separation based on polarity. The twodimensional chromatogram is displayed as a color contour plot, with the first and second retention times (RT1, RT2) on the x and y axes, and the peak intensity correlated to the color


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scale on the right hand side of the plot (Figure 2). This display shows that the majority of the compound co-elution problems have been overcome, which enables acquisition of purer mass spectra, and subsequently more accurate assignment by library searching. 4-Vinyl guaiacol (compound G03, Figure 2) is illustrative: eluting at 1085 seconds in the first chromatographic dimension, it exactly co-elutes with α-ketobutyric acid; however in the second chromatographic dimension, it is well-separated from the acid. The 3D contour plot of the summed m/z 51 (originating from 4-vinylguaiacol) and 45 (originating from α-ketobutyric acid) illustrate the separation achieved in the second dimension (Figure 3). The cleaner chromatographic separation enabled unambiguous identification of the CPCs on the basis of two dimensional retention time (Table S3) and mass spectral criteria. And for pyrolysis products that do not have standards, where identification relies exclusively on mass spectral library matching, the acquisition of pure mass spectra enabled by the two-dimensional chromatography is even more critical.


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OCH3

OH

O

OCH3

3.7x105

OH

levoglucosan C17

OH

OH

4-formyl guaiacol G05

OCH3

4-formyl phenol H06

syringol S01

O

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O OH O OH

OH

OH OCH3

H3CO

O

4-aceto syringol S03

O

1.5

O

O

C13

O

hydroxymethylfurfural

1.6

O

O

OH

O

C07

acetol C03

O

O

O

2-hydroxy-γ-butyroloactone

1.7

O

5-methyl furfural C11

1.8

C07

acetic acid C01

1.9

acetoxyacetone

2.0

O

OH

1.4

9H-fluoren-9-one

rt2 (seconds)

1.3 1.2 1.1

O

0.9

OCH3

OH OCH3

O

1 70 0

1 60 0

1 50 0

1 40 0

1 30 0

1 20 0

11 0 0

1 00 0

9 00

8 00

7 00

6 00

5 00

0

O

OCH3

4-(allyl)-syringol S02

OH

OH

OCH3

OCH3

H3CO

OH

OH 4-(1-propenyl) guaiacol G06

OH

4-vinyl guaiacol G03

2-furyl alcohol C06

O

O

4 00

0.5

furfural C04

0.6

O

3 00

2,3-butanedione C02

0.7

furfural C04 O

4-vinyl phenol H04

0.8

guaiacol G01

phenol H01

OH OH

4-cinnamyl guaiacol G07

1.0

2 00

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2(5H)-furanone C08

Energy & Fuels

rt1 (seconds)

Figure 2. Color contour plot depicting the two dimensional chromatographic profile of Miscanthus. The retention time in the first chromatographic dimension (RT1) found on the xaxis, while the corresponding second dimension (RT2) is on the y axis. The peak intensities increase across the color scale from blue (low) to red (high), as indicated on the color scale on the right axis.


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OH

O OH

OCH3 O

2.0 1064 1.5

1074 1084

1.0 1094 1104

0.5

Figure 3. 3-D plot of the summed ion profiles generated from m/z 45 and 51, which originate exclusively from 4-vinylguaiacol and α-ketobutyric acid, respectively. The two compounds coelute in the first chromatographic dimension (left axis), but are readily separated in the second (right axis).


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Table 1. Calibrated pyrolysis compounds (CPCs), with approximate first dimension retention time. CPC #

CPC name

RT1, sec

CPC #

C01

Acetic Acid

236

H04

Benzofuran, 2,3-dihydro

962

C02

2,3-Butanedione

242

C13

Furfural, 5-(hydroxymethyl)

971

C03

Acetol

287

H05

Phenol, 4-isopropyl-

974

C04

Furfural

470

C14

1,4:3,6-Dianhydro-D-mannitol

977

C05

2-Cyclopentenone

470

G03

Guaiacol, 4-vinyl-

1085

C06

2-Furyl alcohol

491

S01

Syringol

1121

C07

Acetoxyacetone

503

H06

Phenol, 4-formyl-

1127

C08

2-(5H)-Furanone

569

G04

Guaiacol, 4-(2-allyl)-

1130

C09

Furyl methyl ketone

572

C15

2-Deoxy-D-ribono-1,4-lactone

1178

C10

2-(5H)-Furanone, 5-methyl-

605

G05

Guaiacol, 4-formyl-

1184

C11

Furfural, 5-methyl-

641

H07

Phenol, 4-aceto-

1214

H01

Phenol

653

C16

1,6-Anhydro-B-Dmannopyranose

1235

C12

2-Hydroxy-γ-butyrolactone

674

G06

Guaiacol, 4-(1-propenyl)-

1235

H02

Phenol, 4-methyl-

782

C17

Levoglucosan

1277

G01

Guaiacol

812

S02

Syringol, 4-allyl-

1376

H03

Phenol, 4-vinyl-

812

S03

Syringol, 4-aceto-

1499

G02

Guaiacol, 4-methyl-

941

G07

Guaiacol, 4-cinnamyl-

1511

CPC name

RT1, sec

In most cases the mass spectra of the CPCs contained abundant molecular ions and diagnostic fragment ions which made compound identification unambiguous (Table 2S). In a few instances however, the mass spectrum was not diagnostic: the salient example is 1,6-anhydro-β-D-glucose (levoglucosan, C17), which is the dominant product generated from cellulose pyrolysis, and was positively identified on the basis of first and second dimension retention times. However its electron ionization mass spectrum is not distinctive, lacking a molecular ion at m/z 162, and containing virtually no distinctive higher m/z fragment ions (Figure 3S). Salient peaks in the mass spectrum are seen at m/z 44, 57, 73, together with a base peak at m/z 60 that is a C2H4O2 radical cation; this could originate from a variety of locations on the levoglucosan molecule


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(Scheme 1S). Two other isomeric anhydro-sugars were analyzed as part of the calibration mixtures, 1,6-anhydro-β-D-mannopyranose and 1,6-anhydro-β-D-galactose, and they produced nearly identical mass spectra, but had notably different retention times. The very intense chromatographic peak attributed to acetic acid is also a potential source of ambiguity, in that it is possible that it is co-eluted with hydroxyacetaldehyde, an isomer of acetic acid that has been reported as a significant biomass pyrolysis product. Hydroxyacetaldehyde displays a lower abundance molecular ion at m/z 60, which would be obscured by the intense molecular ion of acetic acid. The most intense ions in the hydroxyacetaldehyde mass spectrum are m/z 31 and 29, which are below the scan range of these analyses. The spectrometer was only scanned to m/z 43 in order to cut off response to acetonitrile, which was the solvent in the internal standard. While a prevalent hydroxyacetaldehyde cannot be ruled out on the basis of the current experiments, we do not have evidence for it, and it has not been noted as an important compound in prior qualitative studies of Miscanthus pyrolysis.19 The CPCs account for only a small fraction of the pyrolysis products that are generated from Miscanthus, and there are several compounds that are produced in abundance that are not accounted for in the parameter evaluations below. The majority of the non-CPC peaks were identified on the basis of library searching, and their production efficiencies will require an alternative quantitative strategy.

Variation of the CPC production efficiency vs sample mass Variability in run-to-run pyrolysis efficiency was hypothesized to correlate to variations sample mass. At constant Tmax (450 oC) and PTRR (50 oC/sec) values, the CPCs showed a


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significant decrease in production efficiency as the sample mass increased from 300 µg to 2 mg; representative compounds are shown in Figure 4, and the complete set of plots is provided in Figures 4S – 9S. The efficiency vs. sample mass plots displayed exponential profiles; for example, the efficiency of acetic acid production decreases dramatically between 300 and 600 µg, but then levels off at higher sample masses (between 1 and 2 mg). Other cellulose-derived compounds acetol, furfural, 5-(hydroxymethyl) furfural, and levoglucosan showed similar behavior, as did the vinyl lignols 4-vinylphenol and 4-vinyl guaiacol. The exponential profiles could be the result of several factors, including more bimolecular reactions, and perhaps poorer heating efficiency for the larger samples. Higher sample masses will produce higher quantities of the pyrolysis compounds, increasing the potential for bimolecular reactions producing more char and higher molecular weight molecules, and less of the lower molecular weight compounds. Since the same heating conditions were used in all of these experiments, the amount of heat delivered per milligram of biomass must be smaller in the experiments using higher sample masses. The current experiments do not allow us to distinguish between these possibilities, however the high reactivities that are seen for 4-vinylphenol and 4vinylguaiacol suggest that bimolecular reaction chemistry may be playing a role: these compounds would be capable of styrene-type polymerization reactions, which might explain the very large decreases seen for these two compounds when comparing efficiency at low versus high sample masses. This contrasts with compounds like syringol and phenol, which also undergo decreases in production efficiency, but are significantly less affected by increasing sample mass. The sample mass dependence contrasts with quantitative Py/GC/MS studies of switchgrass pyrolysis between 600 and 1200oC, which showed that masses less than 2 mg gave


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no significant changes in yield.56 However in this conclusion was based on the measurement of the volatile gases, and not semi-volatile organic compounds.

efficiency (nMol/mg)

400

C01, acetic acid H03, phenol, 4-vinyl

G03, guaiacol, 4-vinyl C03, acetol C13, furfural, 5-(hydroxymethyl) C17, levoglucosan

40

300 30

200

20

100

10

0

0 0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

2.2

C04, furfural H06, phenol, 4-formyl G05, guaiacol, 4-formyl G07, guaiacol, 4-cinnamyl

40

efficiency (nMol/mg)

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 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Energy & Fuels

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

2.2

5

H01, phenol S01, syringol S03, syringol, 4-aceto

4

30 3

20 2

10

1

0

0 0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

2.2

0.2

0.4

0.6

sample mass (mg)

0.8

1.0

1.2

1.4

1.6

1.8

2.0

2.2

sample mass (mg)

Figure 4. CPC production efficiencies (nanomole/milligram) versus sample mass. The error bars represent standard deviations calculated from three experiments in which the sample mass was replicated as closely as possible. Experiments were conducted using a Tmax = 450oC, and a PTRR = 50oC/sec.

Variation of the CPC production efficiency vs maximum pyrolysis temperature, Tmax It is well known that pyrolysis compound production is affected by the pyrolysis temperature,72 however detailed quantitative information is more limited. Different pyrolysis products were hypothesized to display differing temperature responses that may reflect their rate of production,


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their stability, reactivity, and their physical properties (particularly volatility). A series of experiments were conducted to evaluate how the CPC production efficiencies responded to changes in the pyrolysis temperature Tmax, holding the sample mass constant at 600 µg, and using a PTRR of 50oC/sec. Plotting production efficiency versus Tmax generated profiles that enabled a comparison of the different CPCs on the basis of their responses to varying Tmax values. Figure 5 provides a sample of several compounds in the different CPC categories, and a complete set of Tmax profiles are supplied in Figures 10S through 15S. At Tmax = 350oC, acetic acid is produced together with a bit of 4-vinylphenol, however the majority of the CPCs are not observed. The experiments run at 400oC displayed significant increases in 4-vinylphenol, 4-formylphenol, with more modest increases for several other compounds including acetic acid. Several compounds, notably acetol, the furanones, levoglucosan, and a number of the lignol derivatives are not formed in any significant quantity at 400oC. At 450oC acetic acid production jumps significantly, as do 4-vinylguaiacol and 4formylguaiacol (vanillin). 4-Cinnamylguaiacol (i.e. 4-hydroxy-3-methoxycinnamaldehyde), and the 4-(1-propenyl) guaiacol derivative also experience a big increase in production efficiency at 450oC. The syringol derivatives are not produced in any abundance at this temperature, while the majority of the small organic oxygenates derived from cellulose showed modestly increased production efficiency. Pyrolysis temperatures of 500oC and 550oC resulted in further increases in production efficiency, however at 550oC many of the CPCs show signs of leveling off, or even decreasing. For example, the efficiency versus Tmax profiles for acetoxyacetone (Figure 11S) and 4-cinnamylguaiacol actually decrease at 550oC (Figure 5).


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800

C01, acetic acid C03, acetol C17, levoglucosan

700

C04, furfural C13, furfural, 5-(hydroxymethyl) G03, guaiacol, 4-vinyl H03, phenol, 4-vinyl

60

600

nMol/mg

500 40 400 300 20

200 100 0

0 350

400

450

500

550

350

G05, guaiacol, 4-formyl G07, guaiacol, 4-cinnamyl H01, phenol

400

450

500

550

450

500

550

H06, phenol, 4-formyl S01, syringol S03, syringol, 4-aceto

30

15

nMol/mg

nMol/mg

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 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Energy & Fuels

20

10

10

5

0

0 350

400

450

500

550

350

Temperature (oC)

400

Temperature (oC)

Figure 5. Production efficiency versus pyrolysis Tmax, for selected compounds. Experiments were conducted using a sample mass of 600 µg, and a PTRR = 50oC/sec. The variations in the efficiency vs. pyrolysis temperature profiles may be reflecting different origins for the CPCs. For example furfural may originate in part from the pentose units found in hemicellulose, which has been shown to pyrolyze at lower temperature compared to the cellulose; its degradation would be expected to generate six-carbon compounds like levoglucosan, 2-hydroxy-γ-butyrolactone, 5-methyl furfural, and furyl methyl ketone. Similarly, the lower temperature profiles for 4-vinyl-, and 4-formylphenol, and 4-formyl- and 4-vinylguaiacol suggest that these compounds originate from pendant moieties that could be more easily liberated compared to structures residing within the bulk lignin polymer. Hemicellulose contains alternative carbohydrate units linked to aromatics like ferrulates that may be the source of the


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formyl and vinyl lignol derivatives observed. On the other hand, the low temperature profile for 4-cinnamyl guaiacol is surprising since this compound is derived from coniferyl aldehyde, a constituent of G-lignin. Pyrolysis of standard materials having more tightly defined polymeric structures will be needed for correlating temperature response to moieties present in biomass polymers.

Variation of the CPC production efficiency vs PTRR The pyrolysis temperature ramp rate (PTRR) was varied to determine whether it influenced product formation from 600 µg samples heated to 500 oC. For the majority of the CPCs, a decrease in production efficiency was seen as the PTRR was increased from 12 oC/sec to 124 o

C/sec, however there were compound-dependent variations in the responses. Levoglucosan

underwent a decrease in production efficiency by about a factor of eight (Figure 6, 16S-21S), and 4-methylphenol (H02), 4-methylguaiacol (G02), furyl,methyl ketone (C09) and 5-methyl-2(5H)furanone (C10) also decreased significantly. Most compounds displayed more modest decreases, like acetic acid (C01), which decreased from ~500 to ~300 nMol/mg, and 5(hydroxymethyl)furfural, which went from around 35 to just under 20 nMol/mg. Decreases on this order were typical for most of the lignols, however several compounds were not seriously impacted by the faster PTRR, notably vinyl- and formyl-phenol and -guaiacol derivatives (H03, H06, G03, and G05). Considering only the cellulose-derived pyrolysis products, it appears that the six-carbon compounds are most susceptible to decreased production efficiency when the faster PTRR is used. And in general, slower PTRR values result in higher production efficiencies, suggesting that high quality data may be achievable using small quantities of sample if the PTRR is kept slow. One explanation may be that the total pyrolysis time is longer in the


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experiments in which the slower PTRR values were used: the 124oC/sec experiment had a total time of 39.3 sec, while the 12oC/sec was 9.2 sec. In the experiments using the slower PTRRs, it may be that peak product concentrations are lower, resulting in fewer intermolecular reactions and higher production efficiencies, while at faster rates, products are produced all at once, resulting in formation of higher molecular weight compounds that do not make it through the system. 1000 C01, acetic acid C03, acetol C17, levoglucosan

130

H03, phenol, 4-vinyl G03, guaiacol, 4-vinyl C17, levoglucosan

120 110

800

100

nMol/mg

90 600

80 70 60

400

50 40 30

200

20 10 0

0 0

20

40

60

80

100

120

140

C04, furfural G05, guaiacol, 4-formyl H06, phenol, 4-formyl G07, guaiacol, 4-cinnamyl

20

0

20

40

60

80

100

120

140

H01, phenol S03, syringol, 4-aceto S01, syringol

10

8

nMol/mg

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 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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6 10 4

2

0

0 0

20

40

60

80

100

120

Pyrolysis Temp Ramp Rate (PTRR, oC/s)

140

0

20

40

60

80

100

120

140

Pyrolysis Temp Ramp Rate (PTRR, oC/s)

Figure 6. CPC production efficiency vs. pyrolysis temperature ramp rate (PTRR). Experiments were conducted using a sample mass of 600 µg, and a Tmax = 500oC.

Lignol ratios from Py/GCxGC/MS, and comparison with HSQC NMR results The ratio of phenol-, guaiacol-, and syringol-derived lignins has been used as a metric for predicting product value and potentially for guiding processing. The lignol CPCs were grouped


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according to base H, G and S structure, summed and plotted versus temperature (Figure 7). We note that this accounted for a large majority of the lignol-derived compounds: other lignol derivatives were formed, but these were of very low intensity. Hence, in the case of Miscanthus, the CPC lignols represent the majority of the lignin-derived compounds. The absolute quantities of the summed lignin CPCs increased with increasing temperature, but that the three classes did not follow the same profiles. The H-lignols increase at the lowest temperatures, and are most abundant at 400oC, principally as a result of the formation of abundant 4-vinylphenol.6 At 450oC, the G-lignins are produced as efficiently as the H lignins, with the most abundant compounds being 4-vinyl-, and 4-formyl-guaiacol. At higher temperatures, both the H- and Glignols continue to increase, and the S-lignols also become significantly more abundant. The Slignols are much less abundant in Miscanthus, which is similar to other biomass like wheat straw: thermogravimetry and Py/GC/MS showed that G-lignols were ~ 4.5 x more abundant than the S-lignols.73 The differing temperature responses means that the lignol H:G:S ratios will also vary with temperature, and this is illustrated in the lower plot of Figure 7. At 350oC, the G and H lignols are produced in comparable quantities, however the ratio is skewed in favor of the H-lignols at 400oC as a result of the preferential formation of 4-vinylphenol. At 450oC the production of 4vinyl guaiacol and 4-formyl guaiacol proceeds in earnest, and the fractions of H- and G- are nearly equal again. The ratios at 500 and 550oC are the same, at H:G:S = 39:47:14


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While these results portray the outcome of thermal processing, their correlation to the lignin composition of the Miscanthus is uncertain. Hence the sample was additionally analyzed using

pyrolysis efficiency, nMol/mg

NMR spectroscopy.

120

sum(H lignol) sum(G lignol) sum(S lignol)

100 80 60 40 20 0 350

400

450

500

550 fractional H fractional G fractional S

0.8 lignol fraction

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 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Energy & Fuels

0.6 0.4 0.2 0.0 350

400

450

pyrolysis temperature, oC

500

550

Figure 7. Top, pyrolysis efficiencies for the CPC lignols summed according to structure, plotted versus temperature. Bottom, lignol ratios plotted versus temperature, with horizontal lines indicating the H, G and S fractions generated using HSQC NMR. The monolignol composition of the Miscanthus was determined using two-dimensional nuclear magnetic resonance spectroscopy (NMR), viz., 1H/13C heteronuclear single quantum coherence (HSQC), comparing ball-milled, gelled samples with dissolved, acetylated samples. The two different sample preparation strategies provide a more complete picture of the lignin chemistry.


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The peaks in the spectrum of the gelled sample are considerably broader than those in the spectrum of the dissolved sample, because the latter enjoys longer T2 relaxation times over which signal can be acquired (Figure 8, 22S). The better resolution in the solution state spectrum means the guaiacyl-2 peak and the ferulate-2 peak are resolved, compared to the spectrum of the gelled sample, where they are overlapped. However, the acetylation step necessary to make the biomass soluble also causes the p-hydroxyphenyl-2/6 peak to overlap with the p-coumarate-2/6 peak. In the un-acetylated gel state sample, those peaks are resolved.

Figure 8. Aromatic region of the HSQC NMR spectra of Miscanthus whole cell wall biomass. Left, gel state sample. Right, dissolved, acetylated sample. Peak assignments based on data available in the literature enabled identification of five separate structural moieties derived from guaiacyl-2 (G2), syringyl-2/6 (S2/6), ferulate-2 (Fa2), p-coumarate 2/6 (Ca2/6), and p-hydroxyphenyl-2/6 (H2/6). The shorthand use to identify the structural moieties denotes those aromatic carbon atoms that are situated meta to the carbon atom bearing the phenolic hydroxy group (denoted as position 2 and 6). For the syringyl, paracoumarate, and para-hydroxyphenyl moieties, carbon atoms at positions 2 and 6 are structurally identical and so the NMR integral is double that for the guaiacyl and ferulate moieties, where


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Energy & Fuels

these carbon atoms are structurally discrete. The ratios of the aromatic components of the biomass were calculated by integrating the volumes under the G2, S2/6, Fa2, and the combined Ca2/6 and H2/6 peaks in the solution state spectrum. Values for the S2/6, Ca2/6 and H2/6 volume integrals were divided by 2 to reflect that they represent two proton/carbon pairs. The ratio of the Ca2/6 to the H2/6 in the gel-state spectrum was applied to the peak volume of the Ca2/6, H2/6 peak in the solution state spectrum to separate the signal contribution from each monolignol type. These calculations provide the following values: H:G:S = 2:66:32 H:G:S:Fa:Ca = 2:55:27:6:11 There are some important points to note about this procedure. First, HSQC NMR is not a quantitative analytical method. This is due to differences between relaxation rates of different 1H and 13C nuclei during polarization transfer. However, in the procedure used here, the peaks used to determine the relative abundance for each of the monolignols represented proton/carbon pairs in highly similar chemical environments. In this situation, it can be reasonable expected that the relaxation rates would also be similar. Published research comparing HSQC NMR analysis of lignin to data obtained from other analytical methods supports this assumption. A further concern regarding relaxation rates in the gel state analysis is that the relaxation rates in the bulk polymer will be much faster than relaxation rates at the polymer ends since the sample is not completely dissolved. Since ferulate and p-coumarate esters are typically found as pendant groups attached to hemicellulose and lignin, respectively, it is expected that they would be overrepresented in the gel state HSQC NMR analysis. Indeed, previous research has found that this is the case. However, p-hydroxyphenyl monolignols are also often found at the ends of lignin polymer


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chains, and thus it can be expected that the p-hydroxyphenyl units would be overrepresented to a similar extent as the p-coumarates. Since these two moieties are only being measured relative to each other in the gel state spectrum, this effect would cancel out. It is possible, though, for phydroxyphenyl units to be found in the bulk lignin polymer, and thus this may lead to an underrepresentation of p-hydroxyphenyl units in this analysis. For comparison with the pyrolysis data, H was combined with Ca, and G with Fa. This is because it would be expected that the H and Ca moieties would both produce H-lignols by pyrolysis, while the G and Fa moieties would both produce G lignols. These combinations produce adjusted ratios that are compared to those observed in the Py/GCxGC/MS experiments: H:G:S = 13:61:27 Comparison of the ratios generated by the two approaches shows that both the G- and S- lignol fractions in the pyrolysis experiments are significantly lower, and alternatively that the H-lignol fraction is much higher (Figure 7, bottom). The reason for the difference is at present an open question, however it may be that the pyrolytic production of the vinyl- and formylphenol and guaiacol derivatives is much faster as a result of their formation from pendant coumarate and ferulate moieties, as suggested by the NMR studies. If this is the case, it may also suggest that a fraction of the S- and G-lignols will be difficult to access using thermal processing, which could be useful for predicting yields. Generating a better understanding of the differences between the lignol fractions seen in the NMR and Py experiments comprises an area where more work is needed.


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Conclusion A quantitative pyrolysis two-dimensional gas chromatography mass spectrometry method was used to measure the production efficiency of 34 compounds from a Miscanthus sample. For most of the compounds, efficiency decreased in an apparently exponential fashion as sample mass was increased. The maximum pyrolysis temperature was increased from 350 to 550oC, and found to dramatically increase compound production, however, temperature profiles were not uniform for all compounds. In particular, derivatives of phenol (derived from H-lignols) were produced at significantly lower temperatures compared to those of guaiacol (G-lignols), which in turn were generated at lower temperatures than were the syringol (S-lignol) derivatives. Pyrolysis efficiencies were also measured as a function of the pyrolysis temperature ramp rate, and found to decrease as the rate increased for many compounds. However, the production efficiency of many other compounds did not display a significant negative correlation with the ramp rate. These findings provide guidance for parameter selection for comparing different biomass materials, viz., highest efficiency is achieved using small sample size, maximum pyrolysis temperatures at or above 500oC, and slow temperature ramp rates. While the quantitative Py/GCxGC/MS experiments have the potential to provide information relevant to thermal processing, the relationship of the products and their quantities to the polymeric composition of the starting biomass remains uncertain. Comparison with HSQC NMR results showed that the Py/GCxGC/MS produced markedly lower fractions of S- and Glignols, while generating a much higher fraction of H-lignols, specifically 4-vinylphenol. Reconciliation of the responses of these two techniques presents a significant challenge, which nevertheless has the potential to provide a finer level of detail on the outcome of thermal processing, and its relationship to the polymeric structure of the biomass feedstock.


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Author Information Corresponding Author, *E-mail: [email protected]

Acknowledgment This research was supported by the U.S. Department of Energy, under contract number DEAC-07-05ID14517.

Associated Content Supporting Information. The following files are available free of charge. A complete set of responses of the calibrated pyrolysis compounds and the internal standards, with variable sample mass, pyrolysis temperature, and pyrolysis rate are provided in an attached pdf. file that is available on line.

Author Information Corresponding Author * Gary S. Groenewold, [email protected] Author Contributions The manuscript was written through contributions of all authors. All authors have given approval to the final version of the manuscript.

References 1.

Kinney, K. L.; Smith, W. A.; Gresham, G. L.; Westover, T. L., Biofuels 2013, 4, 111-

127. 2.

Sykes, R.; Yung, M.; Novaes, E.; Kirst, M.; Peter, G.; Davis, M., High-Throughput

Screening of Plant Cell-Wall Composition Using Pyrolysis Molecular Beam Mass Spectroscopy.


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Pyrolysis Two-Dimensional GC-MS of Miscanthus Biomass

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