Effect of Ionic Liquid Pretreatment on the Porosity of Pine: Insights from

Subscriber access provided by UNIVERSITY OF THE SUNSHINE COAST

Article

Effect of ionic liquid pretreatment on the porosity of pine wood: insights from small angle neutron scattering, nitrogen adsorption analysis and x-ray diffraction Xueming Yuan, Lilin He, Seema Singh, Blake A. Simmons, and Gang Cheng Energy Fuels, Just Accepted Manuscript • DOI: 10.1021/acs.energyfuels.7b01567 • Publication Date (Web): 11 Sep 2017 Downloaded from http://pubs.acs.org on September 14, 2017

Just Accepted “Just Accepted” manuscripts have been peer-reviewed and accepted for publication. They are posted online prior to technical editing, formatting for publication and author proofing. The American Chemical Society provides “Just Accepted” as a free service to the research community to expedite the dissemination of scientific material as soon as possible after acceptance. “Just Accepted” manuscripts appear in full in PDF format accompanied by an HTML abstract. “Just Accepted” manuscripts have been fully peer reviewed, but should not be considered the official version of record. They are accessible to all readers and citable by the Digital Object Identifier (DOI®). “Just Accepted” is an optional service offered to authors. Therefore, the “Just Accepted” Web site may not include all articles that will be published in the journal. After a manuscript is technically edited and formatted, it will be removed from the “Just Accepted” Web site and published as an ASAP article. Note that technical editing may introduce minor changes to the manuscript text and/or graphics which could affect content, and all legal disclaimers and ethical guidelines that apply to the journal pertain. ACS cannot be held responsible for errors or consequences arising from the use of information contained in these “Just Accepted” manuscripts.

Energy & Fuels is published by the American Chemical Society. 1155 Sixteenth Street N.W., Washington, DC 20036 Published by American Chemical Society. Copyright © American Chemical Society. However, no copyright claim is made to original U.S. Government works, or works produced by employees of any Commonwealth realm Crown government in the course of their duties.

Page 1 of 18

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

Biomass porosity studied by small angle neutron scattering and nitrogen adsorption analysis 100x70mm (300 x 300 DPI)

ACS Paragon Plus Environment

Energy & Fuels

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

Page 2 of 18

Effect of ionic liquid pretreatment on the porosity of pine: insights from small angle neutron scattering, nitrogen adsorption analysis and x-ray diffraction Xueming Yuana, Lilin Heb, Seema Singhc,d and Blake A. Simmonsc,e and Gang Chenga,c,e* a

College of Life Science and Technology, Beijing University of Chemical Technology, North 3rd Ring East, # 15, Beijing, 100029, China. b Biology and Soft Matter Division, Oak Ridge National Laboratory, 1 Bethel Valley Road, TN, 37830, USA c Deconstruction Division, Joint BioEnergy Institute (JBEI), 5885 Hollis Street, Emeryville, CA 94608, USA. d Biomass Science and Conversion Technology Department, Sandia National Laboratories, 7011 East Avenue, Livermore, CA 94551, USA e Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA 94720, USA.

Abstract. Small angle neutron scattering (SANS) was used to study the porosity of pine samples before and after ionic liquid (IL) pretreatment. Pine samples were pretreated using 1-ethyl-3-methylimidazolium acetate ([C2C1Im][OAc]) at 110 °C for 3 hours at biomass concentrations of 5, 10, 15, 20 and 25 wt.% , and 130 °C for 3 hours at biomass concentrations of 5 and 25 wt.%. For the first time, relative changes in porosity of pretreated pine samples derived from SANS are compared with those obtained from the nitrogen adsorption analysis. Biomass crystalline structures were measured by X-ray diffraction (XRD). Both porosity and XRD data suggest that [C2C1Im][OAc] interacted with pine samples more efficiently at higher biomass concentrations during pretreatment. This was attributed to the presence of resin acid in pine samples.

1 ACS Paragon Plus Environment

Page 3 of 18

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

1. Introduction Lignocellulosic biomass represents a vast and renewable source of sugar and aromatics. The production of fuels and chemicals from agricultural and forestry residues have been subjected to vigorous research in recent years.1 Enzymatic hydrolysis of lignocellulosic biomass suffers from low efficiency due to inherent biomass recalcitrance. 2

Various biomass pretreatment methods have been developed to overcome the

recalcitrance and make conversion processes economically viable.3 Cellulose crystalline structures, cellulose accessibility to cellulase and lignin content are considered as major factors affecting either initial enzymatic hydrolysis rate or final sugar conversion.4,5 Enzymatic hydrolysis requires effective adsorption of the cellulase onto the cellulose surface.6,7 Cellulose accessibility to cellulase has been evaluated by different approaches which were summarized nicely in several articles.7-10 Specific surface area (m2/g substrate) and cumulative pore volume distribution (cm3/g substrate) as a function of pore size are commonly measured by gas adsorption (N2, CO2) and mercury porosimetry.8 Porosity (cm3/cm3) is obtained if the skeleton density of the substrate is known. The measured specific surface area includes external surfaces and internal pore surfaces (open pores) of the substrate which are accessible to the probe molecules. Other techniques include DSC thermoporometry, Simons’ staining, solute exclusion and NMR cryoporometry.6,10,11 All of the above mentioned techniques can provide measures of the overall surface area and porosity of biomass samples. However, the obtained surface area and porosity depend on the size of the probe used. More accurate representation of cellulose accessibility can be obtained by using cellulose-binding module (CBM)containing green fluorescent protein (TGC). It is measured based on the maximum TGC


Energy & Fuels

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

Page 4 of 18

adsorption capacity after a blocking adsorption with a large amount of bovine serum albumin.7 Small angle neutron scattering (SANS) is a powerful technique to characterize porous systems such as porous carbon, coal and shale samples.12,13 It measures total porosity (open and closed pores) of the sample in a range of ~1-100 nm. Larger pores in the size range of 100-1000 nm can be accessed by ultra small angle neutron scattering (USANS). SANS and USANS can also track changes in structure of biomass samples during the course of enzymatic digestion, thus offering a unique tool to understand biomass pretreatment and enzymatic hydrolysis.14,15 Relative changes in porosity of white poplar and eucalyptus after ionic liquid pretreatment were analyzed by SANS in a previous work.15 In this study, changes in porosity of pine samples as a function of IL pretreatment conditions were studied using both SANS and nitrogen adsorption measurements, which demonstrated applicability of SANS to study the porosity biomass samples.16 In addition, pine samples responded differently to IL pretreatment than the white poplar and eucalyptus samples, which was related to a specific component in pine.

2. Experimental 2.1 Materials Wood chips were prepared from pine (Pinus tabuliformis) trees harvested from a local farm in Beijing, China. Biomass samples were ground and sieved to retain particles with sizes equal to or less than 2 mm. The pine was extracted with water and ethanol for 12 h using a Soxhlet apparatus to remove non-structural materials. This extraction was for the purpose of analyzing biomass components in the untreated and treated biomass


Page 5 of 18

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

samples. The ionic liquid, [C2C1Im][OAc], were purchased from Lanzhou Institute of Chemical Physics, China. 2.2 Compositional analysis Cellulose and xylan contents were determined by a two-step acid hydrolysis and subsequent HPLC analysis, based on the standard NREL procedure (NREL/TP-51042618). The sugar composition of the hydolysates was determined by high performance liquid chromatography (HPLC) using a refractive index detector (Hitachi, Tokyo, Japan). The cellulose and xylan contents were calculated from glucose and xylose contents multiplied by conversion factors of 0.90 and 0.88, respectively (NREL/TP-510-42618). A Sugar-pak1 column (Waters, Milford, MA, USA) was used at 80oC with ultrapure water as the eluent at a flow rate of 0.5mL/min. The lignin content was determined with the acetyl bromide method using an averaged extinction coefficient of 23.007L /g· cm.17 2.3 Biomass pretreatment In most cases the IL pretreatments were done with the samples after extraction with ethanol and water. To show the impact of resin acid on the IL pretreatment, one sample was subjected to second extraction using petroleum ether and acetone in order to remove resin acid in pine. That sample was then pretreated at a biomass concentration of 15 wt.%. Pretreatments were carried out by combining 0.3 g of biomass with varying amount of [C2C1Im][OAc] (5.7 g, 2.7 g, 1.7 g, 1.2 g and 0.9 g to reach biomass concentrations of 5, 10, 15, 20 and 25 wt.% ) in 50 mL glass centrifuge tubes. The mixtures were heated in an oil bath without stirring at 110 ºC for 3 h. Stirring is becoming difficult with biomass loading larger than 15 wt.% in [C2C1Im][OAc] 18 unless


Energy & Fuels

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

Page 6 of 18

special reactors are used, such as twin-screw extruder.19 The samples were not stirred during IL pretreatment.20 After pretreatment, the reaction was quenched with different amount of water (19 g, 22 g, 24 g, 23.5 g and 23.8 g for samples of 5, 10, 15, 20 and 25 wt.%) such that the final weight of the water, IL and biomass was equal to 25 g. The samples were then centrifuged and decanted or filtered. The pretreated biomass samples were then washed with same amount of water for 4 times. The recovered solids were lyophilized for 24 h and then stored in a sealed plastic bag at 5 ºC for analysis. For each pretreatment condition, three replicates were performed. The losses of biomass components, cellulose, xylan and lignin, during pretreatment are calculated by the following equation: Component loss = 1-

% ×%

%

2.4 XRD measurement The samples were scanned on a D8 ADVANCE diffractometer equipped with a sealed tube Cu Kα source. The operating voltage and current were 40 kV and 40 mA and the x-ray wavelength was 0.15406 nm. Scans were collected from 2θ = 5 to 60º with step size of 0.03 at 4 s per step. To minimize the uncertainty introduced by biomass pretreatment, samples obtained from three parallel pretreatments under the same conditions were averaged for the XRD measurement. The XRD data were deconvoluted using Gaussian functions with Origin. 2.5 SANS Measurement SANS measurement was performed at the Oak Ridge National Laboratory (ORNL). Two sample–to-detector distances (SDDs) (1.7 and 14.5 m) with a detector offset of 40 cm and a neutron wavelength of λ=6 Å were used to cover scattering vectors


Page 7 of 18

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

(q =

, 2θ is the scattering angle) ranging from 0.004 to 0.4 Å−1. Powder samples

were loaded into quartz cells for the measurement. Since the bulk and skeleton density of the biomass particles were not measured, the effective thickness was not available,21 thus absolute calibration was not executed. However, a relative comparison of the scattering intensity was possible by normalizing the scattering curve by the mass of the sample put into the cell, assuming the particles illuminated in the neutron beam have the similar packing density for different samples. It was controlled by putting similar amount of samples (~70 mg) into the sample cells. The SANS data were analyzed semi quantitatively by comparing the scattering invariant of different samples which represents the scattering power of a sample and is given as follows :22 P=

0 1 I/q)q, dq = ∆ρ, φ5 61 − φ5 8 2π, 1

Where ∆ρ is the difference in scattering length density (SLD) between pores and the matrix; φ5 represents the porosity of the sample. The scattering invariant is proportional to the porosity in the biomass samples provided the porosity is less than 50% which is usually the case for lignocellulosic biomass.10 The SLDs of cellulose, hemicellulose and lignin are similar to each other,16 therefore any changes to the scattering invariant are caused by the porosity of the sample. The background from 0.1 to 0.4 Å-1 was subtracted from the SANS data before calculating the scattering invariant and the integration limit was taken from 0.004 to 0.1 Å-1. 2.6 Surface area and Porosity by N2 adsorption


Energy & Fuels

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

Page 8 of 18

The surface area and pore size distribution of straw samples are determined by N2 adsorption isotherm at 77 K using a ASAP 2020 HD88 instrument (Micromeritics Co.). N2 adsorption–desorption isotherm was operated at relative pressure approximately P/P0 = 0.03–1 (P: system pressure, P0:1 bar). Surface area of pine was determined by BET at P/P0 = 0.03–0.2.23 The mesoporous distribution of pore volume with respect to pore size is estimated by using the Barrett-Joyner-Halenda (BJH) method.24 2.7 Enzymatic hydrolysis Enzymatic hydrolysis of the samples was carried out in a reciprocating shaker (Scientific Industries, INC., SI-1402) at 50 °C and 30 rpm. All samples were diluted to 5 g substrates per liter in a 50 mM sodium acetate buffer with a pH of 4.8 supplemented with 0.08 g/L tetracycline. The total volume was 10 mL with cellulase (NS50013) concentration of 50 mg protein/g glucan, β-glucosidase (NS50010) concentration of 5 mg protein/g glucan and hemicellulase (NS22002) concentration of 34 mg protein/g xylan. The hydrolysate liquid after 72h hydrolysis was separated from the enzymatic residue by high speed centrifugation (10,000g for 10 min) and analyzed with DNS assay against a glucose standard.25 All assays were performed in triplicate.

3. Results and Discussion Figure 1a presents the SANS data of untreated and pretreated pine samples at different biomass concentrations: 5, 10, 15, 20 and 25 wt.%. The scattering curves follow power law over a q range from 0.1 to 0.004 Å−1 , which is similar to prior SANS studies of dry biomass samples.26 They also resemble the scattering data of other porous materials such as shale.21,27 The power law scattering curves suggest a power law size distribution of pore sizes or fractal pore-matrix interfaces in the samples.22 For 7 ACS Paragon Plus Environment

Page 9 of 18

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

polydisperse porous media, an appropriate relationship between pore radius (R) and the q is derived: R≈ 2.5/q.22 Therefore SANS data in this work cover pores with radius in a range from ~ 2 to 60 nm.

Figure 1. (a) SANS data; (b) normalized BET surface area and SANS porosity; (c) normalized BJH pore volume and SANS porosity; (d) losses of biomass components and percentage of biomass solids recovery after pretreatment. Since the SANS data were not on an absolute scale, one compares the relative change of the porosity measured by SANS in this q range. The relative increases in porosity for pine samples after IL pretreatment, obtained by normalizing the scattering invariant (see the data analysis in the SANS measurement section) of the pretreatment samples with that of untreated ones, are shown on the right axis of Figure 1b. The porosity increases after IL pretreatment at a biomass concentration of 5 wt.%. Surprisingly, it keeps increasing with increasing biomass concentration until 20 wt.% . Biomass porosity increases as a result of removal and/or redistribution of biomass 8 ACS Paragon Plus Environment

Energy & Fuels

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

Page 10 of 18

components and swelling of biomass samples during pretreatment.28,29 In the previous work, a lower IL-to-biomass ratio during IL pretreatment led to removal of less amount of biomass components and therefore smaller porosity.15 As shown in the right axis of Figure 1d, the percentage of recovered solids after pretreatment slightly increases from 80 to 84 wt.% with increasing biomass concentrations, consistent with the prior work. This indicates that the increased porosity as a function of biomass concentration is mainly caused by relocation and redistribution of biomass components and swelling of biomass. Although SANS measures total porosity, the increase in SANS due to IL pretreatment is caused by open pores. This is because IL pretreatment less likely creates closed pores in the samples. Further investigation was needed to explain the reason behind the increasing porosity with increasing biomass concentration. To confirm the results obtained by SANS, both specific surface area obtained by the BET analysis and cumulative pore volumes extracted from the BJH method for the pine samples are shown on the left axis of Figure 1b and 1c, respectively. The untreated pine sample has a specific surface area of 1.09 m2/g and a total pore volume of 0.0032 cm3/g, which are on the same order of magnitude of several biomass samples.29 The specific surface area and the cumulative pore volume of the pretreated samples are normalized by those of untreated pine sample, enabling comparison with changes of porosity from the SANS data. It is noted that the pore radius is in the range of 1-100 nm based on the BJH analysis, which is wider than that of the SANS data. Both specific surface area and the cumulative pore volume increase with increasing biomass concentration from 5 to 20 wt.%, consistent with SANS analysis. This supports the hypothesis that the increase in porosity is caused by open pores. The apparent


Page 11 of 18

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

discrepancy seen at 25 wt.% is currently under investigation. One possible reason is that there are larger pores contributing more to the increased porosity that is not captured by the SANS data. To further understand the increase of porosity with increasing biomass concentration, the impact of biomass concentration on cellulose crystalline structure was studied. XRD data reveals interactions of cellulose with IL molecules during pretreatment. 30

Figure 2a presents the XRD data of pine samples after IL pretreatment. The XRD

pattern of untreated pine sample is consistent with that of cellulose I lattice, indicated by the presence of three peaks, a main peak at 22.3°, a secondary peak at 15.6° which is a composite peak consisting of reflections from (101) and (1019) planes and a third small peak at 34.5° (Figure 2b).16 The resolution of the XRD data of biomass samples does not allow us to separate the broad peak at 15.6° into two peaks. The XRD curves of pretreated samples show a gradual distortion of the native cellulose I structure and transition to cellulose II with increasing biomass concentration. The deconvoluted XRD data of the pine sample pretreated at a concentration of 5 wt.% shows the co-existence of a cellulose II and distorted cellulose I lattices (Figure 2c). A comparison between Figure 2b and 2c show significant broadening of the peak at around 16° and merging of this peak with the amorphous scattering peak. With increasing of biomass concentration to 15 wt.%, a cellulose II lattice dominates the pretreated pine sample (Figure 2d). Both of the samples pretreated at 10 and 20 wt.% biomass concentrations exhibit a structure which is close to cellulose II indicated by the width of characteristic peak at around 12° which is about twice of the sample pretreated at 15 wt.%. The sample pretreated at a concentration of 25 wt.% contains only distorted cellulose I lattice. 10 ACS Paragon Plus Environment

Energy & Fuels

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

Page 12 of 18

Figure 2. (a) XRD data of untreated and pretreated pine samples at 110°C; (b) peak deconvolution analysis for untreated pine sample (b); pretreated pine sample at 5 wt.% concentration (c) and pretreated pine sample at 15 wt.% concentration (d).


Page 13 of 18

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

Figure 3 (a) XRD data of pretreated pine samples before and after extraction with petroleum ether and acetone; (b) XRD data pretreated pine samples at 130°C; (c) Sugar conversion after 72h hydrolysis by DNS method.

With biomass concentrations increasing from 5 to 15 wt.%, pretreated pine samples show a transition from cellulose I to II. This is also surprising considering the ratio of IL-to-cellulose is decreasing with increasing biomass concentration. This result was confirmed by different researchers in this lab. Pretreatment of 5 and 10 wt.% biomass samples with agitation also produced similar XRD data ring. Previous studies suggest that IL pretreatment transforms cellulose crystalline structure via dissolution and regeneration.26 Both porosity and XRD data suggest that IL molecules diffused into plant cell walls and solubilized a fraction of cellulose at higher biomass concentrations. It is interesting to note that the lignin extraction percentage is around 10 wt.% after pretreatment at 15 and 20 wt.% biomass concentrations while it is almost zero for the other pretreated samples (Figure 1d, left axis). The lower extractability of lignin from pine samples pretreated at 5, 10 and 25 wt.% is consistent with a recent work.11 The result indicates that IL molecules interacted with lignin more effectively at higher biomass concentrations during biomass pretreatment in this work. This also suggests that lignin extraction contributed to the enhanced porosity observed in these two samples. 12 ACS Paragon Plus Environment

Energy & Fuels

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

Page 14 of 18

However, as discussed before, the main reason of improved porosity as a function of biomass concentration is relocation of biomass components and swelling of biomass samples since the losses of biomass solids after pretreatment decreases with increasing biomass concentrations. Although the lignin loss is higher for these two samples, their xylan losses are lower, which makes the overall biomass loss to be 20 and 17 wt.% , respectively. Acids have been used to enhance performance of IL pretreatments.33 A previous study has shown that acidic ionic liquid 1-H-3-methylimidazolium chloride can extract lignin from yellow pine by hydrolyzing the ether linkages in lignin.34 In another study, pretreatment of corn stover using 1,3-dimethylimidazolium dimethylphosphate and dilute hydrochloric acid (HCl) produced a porous and fragmented structure.35 Some ether linkages between lignin and carbohydrates were cleaved during pretreatment.35 Improved porosity and lignin removal were also observed in a study of pretreatment of Arundo donax Linn. using 1-butyl-3-methylimidazolium chloride with the aid of a protic acid resin Amberlyst 35DRY 36. The studies also suggest partial depolymerization of cellulose and removal of hemicellulose during acid-catalyzed IL pretreatment.33,37 These literature studies demonstrate that acids facilitate deconstruction of biomass during IL pretreatment. In this work, a hypothesis is that the observed changes in porosity and cellulose crystalline structures are due to the presence of resin acid in pine samples.38 The resin acid content in Scots pine (Pinus sylvestris) sapwood/heartwood was found to be 1 to 4 wt.% .39 In this study, it was believed that the resin acid was not extracted by using water and ethanol in the Soxhlet apparatus. In the prior work, they were extracted with petroleum ether and acetone.38 The impact of resin acid on the IL pretreatment was


Page 15 of 18

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

confirmed with XRD data of the pine samples extracted further with petroleum ether and acetone. Shown in Figure 3a, the pine sample pretreated at 15 wt.% biomass concentration after the extraction demonstrates a different XRD pattern than that without the second extraction. The characteristic cellulose II peak disappears indicating no cellulose solubilization during IL pretreatment due to removal of resin acid from the pine sample. The concentration of resin acids increases with increasing pine concentration during IL pretreatment, which explains the observed porosity and cellulose crystalline structural changes with biomass concentration. Acids and IL work synergistically to dissolve, depolymerize biomass components and cause swelling of biomass samples. However, lower mass transport rate limits the synergism of acids and IL for the sample pretreated 25 wt.%, which explains the observed cellulose crystalline structure in this sample. The hypothesis is further supported by the XRD data of the samples pretreated at 130°C for 3 hours (Figure 3b). Higher temperatures lead to faster heat and mass transport. Figure 2c shows that a cellulose II peak (~12.5°) is present in the sample pretreated at 25 wt.% while a distorted cellulose I is still dominating the sample pretreated at 5 wt.%. It suggests that the transformation of cellulose crystalline structures is caused by the resin acid which promotes solvation of cellulose at higher concentrations. It is noted that specific surface area and porosity increase continually with biomass concentration shown by the nitrogen adsorption data, this is because cellulose dissolution is not required to increase the porosity and specific surface area. The presence of resin acid in pine samples promoted cellulose solubilization and transition of its native crystalline structure which increased IL pretreatment efficiency. It


Energy & Fuels

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

Page 16 of 18

also led to higher porosity in the samples pretreated with less amount of IL. These are beneficial to enzymatic hydrolysis of pretreated pine samples due to higher porosity and less recalcitrant cellulose structures. As shown in Figure 3c, the total sugar conversion after 72h enzymatic hydrolysis shows that pine samples pretreated at 15 and 20 wt.% concentrations exhibit higher sugar conversion that other samples. This is because these two samples have higher porosity and contain less recalcitrant cellulose II structure.

4. Conclusions Relative changes in specific surface area and cumulative pore volume of the pines samples as a function of biomass concentration measured by nitrogen adsorption analysis are consistent with porosity measurement derived from SANS data. The results provide a basis for future in-situ study of biomass pretreatment and enzymatic hydrolysis using SANS. Both the changes in porosity and cellulose crystalline structures suggest that IL molecules interacted with biomass more efficiently at higher biomass concentrations, which is attributed to the presence of resin acid in pine. This benefits the IL pretreatment and conversion of pine samples since less IL is required to achieve higher porosity and less recalcitrant cellulose II structure.

Acknowledgment Gang Cheng acknowledges support for this research by the National Natural Science Foundation of China (U1432109) and China Scholarship Council (201606885004). We acknowledge support by the DOE Joint BioEnergy Institute (http://www.jbei.org) through the U. S. Department of Energy, Office of Science, Office of Biological and Environmental Research, through contract DE-AC02-05CH11231 between Lawrence Berkeley National Laboratory and the U. S. Department of Energy. A portion of this research used resources at the High Flux Isotope Reactor, a DOE Office of Science User Facility operated by the Oak Ridge National Laboratory.


Page 17 of 18

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

References (1) Gallezot, P. Chemical Society Reviews 2012, 41, 1538-1558. (2) Wahlstrom, R. M.; Suurnakki, A. Green Chemistry 2015, 17, 694-714. (3) Kumar, A. K.; Sharma, S. Bioresources and Bioprocessing 2017, 4, 7. (4) Pihlajaniemi, V.; Sipponen, M. H.; Liimatainen, H.; Sirvio, J. A.; Nyyssola, A.; Laakso, S. Green Chemistry 2016, 18, 1295-1305. (5) Davison, B. H.; Parks, J.; Davis, M. F.; Donohoe, B. S. In Aqueous Pretreatment of Plant Biomass for Biological and Chemical Conversion to Fuels and Chemicals; John Wiley & Sons, Ltd: 2013, p 23-38. (6) Pihlajaniemi, V.; Sipponen, M. H.; Kallioinen, A.; Nyyssölä, A.; Laakso, S. Biotechnology for Biofuels 2016, 9, 18. (7) Wang, Q. Q.; He, Z.; Zhu, Z.; Zhang, Y. H.; Ni, Y.; Luo, X. L.; Zhu, J. Y. Biotechnol Bioeng 2012, 109, 381-389. (8) Karimi, K.; Taherzadeh, M. J. Bioresource Technology 2016, 203, 348-356. (9) Meng, X.; Ragauskas, A. J. Current Opinion in Biotechnology 2014, 27, 150-158. (10) Meng, X.; Foston, M.; Leisen, J.; DeMartini, J.; Wyman, C. E.; Ragauskas, A. J. Bioresour Technol 2013, 144, 467-476. (11) Torr, K. M.; Love, K. T.; Simmons, B. A.; Hill, S. J. Biotechnol Bioeng 2016, 113, 540-549. (12) Hollamby, M. J. Physical Chemistry Chemical Physics 2013, 15, 10566-10579. (13) Melnichenko, Y. B. In Small-Angle Scattering from Confined and Interfacial Fluids: Applications to Energy Storage and Environmental Science; Springer International Publishing: Cham, 2016, p 139-171. (14) Kent, M. S.; Cheng, G.; Murton, J. K.; Carles, E. L.; Dibble, D. C.; Zendejas, F.; Rodriquez, M. A.; Tran, H.; Holmes, B.; Simmons, B. A.; Knierim, B.; Auer, M.; Banuelos, J. L.; Urquidi, J.; Hjelm, R. P. Biomacromolecules 2010, 11, 357-368. (15) Yuan, X.; Duan, Y.; He, L.; Singh, S.; Simmons, B.; Cheng, G. Bioresource Technology 2017, 232, 113-118. (16) Cheng, G.; Zhang, X.; Simmons, B.; Singh, S. Energy & Environmental Science 2015, 8, 436-455. (17) Fukushima, R. S.; Kerley, M. S. Journal of agricultural and food chemistry 2011, 59, 3505-3509. (18) Li, C.; Tanjore, D.; He, W.; Wong, J.; Gardner, J. L.; Sale, K. L.; Simmons, B. A.; Singh, S. Biotechnology for Biofuels 2013, 6, 154. (19) da Silva, A. S. A.; Teixeira, R. S. S.; Endo, T.; Bon, E. P. S.; Lee, S.-H. Green Chemistry 2013, 15, 1991-2001. (20) Cruz, A. G.; Scullin, C.; Mu, C.; Cheng, G.; Stavila, V.; Varanasi, P.; Xu, D.; Mentel, J.; Chuang, Y.-D.; Simmons, B. A.; Singh, S. Biotechnology for Biofuels 2013, 6. (21) Melnichenko, Y. B. Small-Angle Scattering from Confined and Interfacial Fluids: Applications to Energy Storage and Environmental Science; Springer International Publishing, 2015. (22) Melnichenko, Y. B. In Small-Angle Scattering from Confined and Interfacial Fluids: Applications to Energy Storage and Environmental Science; Springer International Publishing: Cham, 2016, p 109-138. (23) Lowell, S.; Shields, J. E. In Powder Surface Area and Porosity; Springer Netherlands: Dordrecht, 1984, p 30-35.


Energy & Fuels

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

Page 18 of 18

(24) Lowell, S.; Shields, J. E. In Powder Surface Area and Porosity; Springer Netherlands: Dordrecht, 1984, p 54-74. (25) Gusakov, A. V.; Kondratyeva, E. G.; Sinitsyn, A. P. International Journal of Analytical Chemistry 2011, 2011, 4. (26) Cheng, G.; Varanasi, P.; Li, C.; Liu, H.; Melnichenko, Y. B.; Simmons, B. A.; Kent, M. S.; Singh, S. Biomacromolecules 2011, 12, 933-941. (27) Ruppert, L. F.; Sakurovs, R.; Blach, T. P.; He, L.; Melnichenko, Y. B.; Mildner, D. F. R.; Alcantar-Lopez, L. Energy & Fuels 2013, 27, 772-779. (28) Chundawat, S. P. S.; Donohoe, B. S.; da Costa Sousa, L.; Elder, T.; Agarwal, U. P.; Lu, F.; Ralph, J.; Himmel, M. E.; Balan, V.; Dale, B. E. Energy & Environmental Science 2011, 4, 973-984. (29) Pu, Y.; Hu, F.; Huang, F.; Davison, B. H.; Ragauskas, A. J. Biotechnology for Biofuels 2013, 6, 15. (30) Zhang, J.; Wang, Y.; Zhang, L.; Zhang, R.; Liu, G.; Cheng, G. Bioresour. Technol. 2014, 151, 402-405. (31) Kanbayashi, T.; Miyafuji, H. Scientific Reports 2016, 6, 30147. (32) Hou, Q.; Ju, M.; Li, W.; Liu, L.; Chen, Y.; Yang, Q. Molecules 2017, 22. (33) Groff, D.; George, A.; Sun, N.; Sathitsuksanoh, N.; Bokinsky, G.; Simmons, B. A.; Holmes, B. M.; Keasling, J. D. Green Chemistry 2013, 15, 1264-1267. (34) Cox, B. J.; Ekerdt, J. G. Bioresource Technology 2013, 134, 59-65. (35) Qing, Q.; Hu, R.; He, Y.; Zhang, Y.; Wang, L. Applied Microbiology and Biotechnology 2014, 98, 5275-5286. (36) You, T.; Zhang, L.; Zhou, S.; Xu, F. Bioresource Technology 2014, 167, 574-577. (37) You, T.; Shao, L.; Wang, R.; Zhang, L.; Xu, F. Biotechnology for Biofuels 2016, 9, 177. (38) Arshadi, M.; Backlund, I.; Geladi, P.; Bergsten, U. Industrial Crops and Products 2013, 49, 535-541. (39) Hovelstad, H.; Leirset, I.; Oyaas, K.; Fiksdahl, A. Molecules 2006, 11, 103.


Effect of Ionic Liquid Pretreatment on the Porosity of Pine: Insights from

Recommend Documents