Structural Characterization of Loblolly Pine ... - ACS Publications

Subscriber access provided by Monash University Library

Article

Structural Characterization of Loblolly Pine derived Biochar by X-ray Diffraction and Electron Energy Loss Spectroscopy Seunghyun Yoo, Stephen Kelley, David Tilotta, and Sunkyu Park ACS Sustainable Chem. Eng., Just Accepted Manuscript • DOI: 10.1021/ acssuschemeng.7b04119 • Publication Date (Web): 16 Jan 2018 Downloaded from http://pubs.acs.org on January 16, 2018

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.

ACS Sustainable Chemistry & Engineering 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 46 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

ACS Sustainable Chemistry & Engineering

1

Structural Characterization of Loblolly Pine derived Biochar by X-ray Diffraction and Electron

2

Energy Loss Spectroscopy

3 4

Seunghyun Yoo, Stephen Kelley, David Tilotta, and Sunkyu Park*

5 6

a

7

27607, USA

Department of Forest Biomaterials, North Carolina State University, 2820 Faucette Blvd, Raleigh, NC

8 9

*

Corresponding author: Sunkyu Park, Department of Forest Biomaterials, North Carolina State

10

University, 431 Dan Allen Drive, Campus Box 8005, Raleigh, NC 27607-8005, USA

11

Tel: 919-515-0473, E-mail: [email protected]

12 13 14

Keywords: nanomaterial characterization, biomass-to-crystalline carbon development, electron energy loss spectroscopy, biomass carbonization

15 16

Abstract

17

Biochar from lignocellulosic biomass is emerging as a sustainable material with versatile applications,

18

but its detailed property is poorly understood due to the structural complexity. We propose a biochar

19

structural development model based on the experimental results including composition analysis, surface

20

area/pore analysis, x-ray diffraction analysis, electron microscope imaging, and electron energy loss

21

spectroscopy. Loblolly pine derived biochars were produced at different carbonization temperatures

22

from 300 to 1,000℃. Fixed carbon, sp2 content, and number of graphene layer increased with the

23

increased carbonization temperature. Alternating average C-C bond length, interlayer spacing distance,

24

and layer coherence length were observed. Bulk plasmon excitation energy was correlated to the average

25

C-C bond length that it serves as a good indicator of the carbon structure development when compared

26

to the perfect graphitic carbon structure. Based on the experimental results, four different structural

ACS Paragon Plus Environment

ACS Sustainable Chemistry & Engineering 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 46

27

development phases are identified, which provide a comprehensive understanding of biochar nano-

28

carbon crystallite development. Unlike previous biochar structure models, which proposed radially

29

growing polyaromatic carbon crystallite, we propose a lengthwise growing polyaromatic carbon

30

crystallite model. This experimental-based biochar model should be helpful when determining structure

31

of unknown biomass derived carbon materials and disordered pyrolytic carbon materials.

32 33

Biochar is a sustainable carbon material derived from biomass. This study will elucidate the structure of

34

sustainable biochar.

35 36

Introduction

37

Biochar is a biomass derived sustainable carbon source, which can be utilized in both energy and

38

material applications. The traditional role of biochar has been confined to the low value product such as

39

soil amendment, adsorption medium, or solid fuel. There are also potential high-end applications for

40

biochar such as electrodes for electrochemical energy storage systems1-3 and conductive material for

41

sensors and electronic devices.4 For the high-end applications, it is crucial to understand how chemical

42

composition and morphology impact the nano-structure of biochar and its resulting properties. Due to

43

the inherent structural complexity of biochar and limitations of many common analytical techniques, the

44

detailed structure of biochar is not well understood. 2 ACS Paragon Plus Environment

Page 3 of 46 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


45

Advances in nanoscale analytical techniques have enabled characterizations of materials with

46

complex structures. Specifically, solid state nuclear magnetic resonance (NMR) can evaluate carbon

47

aromaticity and amount of protonated (C-H) / nonprotonated (C-C, C-O) carbon in biochar.5-7 Electron

48

energy loss spectroscopy (EELS) can evaluate carbon sp2 content and C-C bond length of biochar.8-12

49

Energy-dispersive X-ray spectroscopy (EDS) can quantify molar fraction of atomic elements in

50

biochar,10, 13 and X-ray photoelectron spectroscopy (XPS) can quantify amount of carbon functional

51

groups (C-O, C=O, COO) in biochar.6, 9, 14-15 X-ray absorption spectroscopy (EXAFS, XANES),14, 16-17

52

and Raman spectroscopy10,

53

Transmission electron microscopy (TEM),8-9, 19 scanning transmission electron microscopy (STEM),10

54

and scanning electron microscopy (SEM)10,

55

structures. With these techniques, more details on biochar structure can be detected.

18

can now be used to understand the polyaromatic structure of biochar.

19

can also be used for image analysis of nanoscale

56

One of the first systematic carbon material structural analyses was performed by Franklin using

57

X-ray diffraction (XRD) to analyze various carbon crystallites, and classifying them into two groups.20

58

One is graphitizing carbon which is characterized by a combination of narrow and sharp (002)

59

reflections XRD patterns after thermal treatment. The other is non-graphitizing carbon which reveals a

60

broad (002) reflection XRD pattern after thermal treatment. Several other studies probed additional

61

details of carbon structural development during the carbonization and graphitization process.21-22

62

Because XRD is a bulk technique, which observes the whole structure of carbon material, Franklin’s

63

classification seemed plausible from the macroscopic point of view and many researchers accept

64

Franklin’s classification. However, with the development of local technique such as TEM, different

65

nanoscale graphitization behaviors in non-graphitizing carbon were examined. Subsequent work on

66

nanoscale graphitization behaviors support the idea that there is no absolute graphitizing carbon or non-

67

graphitizing carbon.23 Graphitic carbon crystallites could also be synthesized from a non-graphitizing

3 ACS Paragon Plus Environment


Page 4 of 46

68

carbon precursor (biomass) through thermo-catalytic reactions.24-25 Thus, rather than using Franklin’s

69

classification as rigid categories, it is more appropriate to view the carbonization and graphitization

70

process as pathways to energetically stable carbon structures.

71

The earlier model suggested by Keiluweit et al.16 is intuitive, but it lacked quantitative data

72

interpretations to distinguish different phases of biochar structure development. Furthermore, their

73

classification of phase components as pyrogenic amorphous carbon, pore space, and turbostratic

74

crystallites is inaccurate. The term “amorphous” cannot be used for pyrolytic carbon26 and pore space is

75

dependent on precursor and pyrolysis condition, and thus it is irrelevant to the disordered and

76

turbostratic structure of carbon material.6 Other prior studies also reported the formation of ordered

77

carbon structures during the thermal treatment of biomass, but they lacked a precise quantification of

78

both the physical structure and chemical composition profiles.5, 27-28

79

This work focused on the systematic characterizations of nano-carbon crystallite development in

80

loblolly pine wood derived biochar using tools to characterize both physical structure and chemical

81

composition. EELS is a powerful analytical technique, which can simultaneously collect information on

82

physical structure (plasmon excitation energy loss and multiple scattering resonance), chemical

83

composition data (sp2 content), and visual images (STEM high angle annular dark-field (HAADF)).

84

XRD is not solely a nanoscale oriented technique, but extracted XRD patterns give useful information

85

about the size and morphology of nano-carbon crystallite. Combined with material composition data,

86

this study quantitatively characterized the carbonization behavior of biochar at a series of thermal

87

treatment steps. Then, based on the collective interpretation of physical and chemical structure

88

developments of nano-carbon crystallite, we propose a schematic model of carbon structural

89

development.

90 4 ACS Paragon Plus Environment

Page 5 of 46 1 2 3 91 4 5 6 92 7 8 93 9 10 94 11 12 95 13 14 15 96 16 17 18 97 19 20 21 98 22 23 99 24 25 100 26 27 101 28 29 30 102 31 32 103 33 34 104 35 36 37 105 38 39 106 40 41 107 42 43 44 108 45 46 109 47 48 110 49 50 111 51 52 53 112 54 55 113 56 57 58 59 60


Materials and Methods Biochar sample preparation Air dried Loblolly pine (Pinus taeda) wood chips were milled into 20-mesh size particle using laboratory Wiley Mill and air dried for 24 hours. An OTF-1200X quartz tube furnace (MTI Corporation, Richmond, CA) was used for the carbonization. Before loading a sample, the furnace was preheated to target temperatures (300, 350, 400, 500, 600, 700, 800, 900, and 1000℃). After reaching the target temperature, an alumina boat containing 7-8 g of loblolly pine wood particles was inserted into the quartz tube for 15 minutes under a constant stream of nitrogen gas (1 L/min). Calculated heating rates for each sample were 183, 216, 249, 316, 383, 449, 516, 583, and 649 ℃/s. The resulting biochar was cooled down under nitrogen flow. The nomenclature of biochar sample is Nxxx where xxx indicates the carbonization temperature.

Material Composition Analysis Carbon, hydrogen, and nitrogen content of the biochar and activated carbon samples were analyzed by using PerkinElmer 2400 Series II elemental analyzer (PerkinElmer, Waltham, MA). Oxygen content was calculated by difference. Proximate analysis was done to determine volatile matter, fixed carbon, and ash contents using TA Q500 thermogravimetric analyzer (TA Instruments, New Castle, DE). The specific measurement condition followed modified ASTM D7582-15.29

BET surface area and micropore volume analysis BET surface area and micro pore volume of biochar samples were analyzed with Gemini VII 2390 surface area analyzer (Micromeritics, Norcross, GA, USA). 0.15 ~ 0.20 g of sample was loaded in the quartz tube and the sample was degassed at 220°C with nitrogen for 2 hours. Multipoint BET surface 5 ACS Paragon Plus Environment

ACS Sustainable Chemistry & Engineering 1 2 3 114 4 5 6 115 7 8 116 9 10 117 11 12 118 13 14 15 119 16 17 120 18 19 121 20 21 22 122 23 24 123 25 26 124 27 28 29 125 30 31 126 32 33 127 34 35 128 36 37 38 129 39 40 130 41 42 131 43 44 45 132 46 47 133 48 49 134 50 51 52 135 53 54 136 55 56 57 58 59 60

Page 6 of 46

area was calculated from the linear relative pressure regime of 0.05 < P/P 0 < 0.30. Total pore volume was calculated at P/P0 = 0.98. Micropore volume was calculated by summation of pore volumes with diameter of less than 2 nm.30

STEM sample preparation and EELS analysis Samples for the electron energy loss analysis were prepared by using UC7 Ultramicrotome (Leica Microsystems Inc. Buffalo Grove, IL). Biochar sliced into 100 nm thick samples that were transferred to the copper TEM grid (Protochips, Raleigh, NC). Electron energy loss spectrum was collected with the electron energy loss spectrometer (Gatan, Pleasanton, CA) attached to the Titan 80300 Probe Aberration Corrected Scanning Transmission Electron Microscope (FEI, Hillsboro, OR). High voltage is 200 kV and energy resolution is 0.15 eV. Biochar zero energy loss, bulk plasmon excitation energy loss, and carbon K-edge core energy loss spectra were collected. Electron multiple scattering effect was corrected by using Gatan Digital Micrograph software.31 Corrected carbon K-edge energy loss spectrum was deconvolved into three Gaussian spectra for further calculation.8-9 STEM HAADAF images were taken at 500 nm magnification. Image resolution was 0.07 nm in STEM mode.

X-ray diffraction pattern analysis Biochar X-ray diffraction patterns were collected by using a SmartLab X-ray diffractometer (Rigaku, Woodlands, TX). Operating voltage was 40 kV and operating current was 44 mA. A Cu Kα Xray tube was used to generate X-rays at a wavelength of wavelength was 0.1541 nm. A Graphite monochromator and Kβ filter were used for the collection of diffracted beam. Biochar particles were placed on a quartz supported sample holder. Then, the sample holder was placed inside the x-ray chamber. Measurement of 2θ angle range was set from 10 degrees to 90 degrees. Each step was 0.05


Page 7 of 46 1 2 3 137 4 5 6 138 7 8 139 9 10 140 11 12 141 13 14 15 142 16 17 18 143 19 20 144 21 22 145 23 24 25 146 26 27 147 28 29 148 30 31 32 149 33 34 150 35 36 151 37 38 39 152 40 41 153 42 43 154 44 45 155 46 47 48 156 49 50 157 51 52 158 53 54 55 159 56 57 58 59 60


degree and the X-ray detector remained constant for 4 seconds at each step to collect the diffracted Xrays. Background subtraction and signal smoothing were done with HighScore Plus 3.0 software (PANalytical, Westboroough, MA). Processed XRD patterns were normalized at (002) reflection intensity. Peak position 2θ angle and full width at half maximum (FWHM) of (002) reflection and (100) reflection were extracted for further analysis.

Results and Discussion Biochar composition analysis Figure 1 summarizes the composition analysis result of raw loblolly pine wood and biochar samples. Bar graph indicates the atomic compositions (molar %) of the biochar samples. As the carbonization temperature increases from 300 to 1,000℃, the atomic carbon content of biochar increases from 36.2 to 92.9 mol.%. Conversely, the atomic oxygen content of biochar decreases from 18.1 to 4.2 mol.% and the atomic hydrogen content decreases from 51.8 to 2.2 mol.%. The amount of nitrogen remains nearly constant between 0.1 to 0.8 mol.%. The dotted lines in Figure 1 shows the proximate analysis (weight %) of the biochar samples. As the carbonization temperature increases from 300 to 1,000℃, the amount of fixed carbon increases from 22.2 to 94.9 wt.% while the amount of volatile decreases from 77.2 to 3.4 wt.%. The amount of ash remains nearly constant in between 0.7 to 1.7 wt.%. A major transition in composition occurs at the carbonization temperature between 300 to 350℃. When the carbonization temperature increases from 300 to 350℃, the atomic carbon content increases by 15.0 mol.% while the atomic oxygen and hydrogen content decrease by 7.2 mol.% and 7.8 mol.% each. The amount of fixed carbon also increases by 36.3 wt.% while the amount of volatile decreases 36.5 wt.%. This result matches well-known biomass degradation behavior.32-34 The cellulose and hemicellulose in biomass are rapidly degraded at temperatures between 300 and 400℃.32 Biomass 7 ACS Paragon Plus Environment

ACS Sustainable Chemistry & Engineering 1 2 3 160 4 5 6 161 7 8 162 9 10 163 11 12 164 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 165 36 37 38 39 40 41 42 43 166 44 45 167 46 47 168 48 49 169 50 51 170 52 53 54 171 55 56 172 57 58 59 60

Page 8 of 46

degradation products are emitted as volatiles and the amount of stable fixed carbon increases rapidly. As a result, it can be assumed that the structure of biochar produced at 300℃ is similar to the lignocellulosic structure because only limited degradation of the structural polymers has occurred.32-34 Although the biomass compositional analysis does not imply a specific biochar structure, it clearly differentiates the initial phase of biochar structural development from other subsequent structural development processes.

Figure 1. Composition analysis result of loblolly pine (raw) and nine biochar samples (top). Magnified atomic nitrogen content and ash content (bottom). Bar graphs represent the atomic compositions (mol.%) of carbon, hydrogen, oxygen, and nitrogen. Line graphs represent the proximate analysis results of fixed carbon, volatile, and ash (wt.%).

BET surface area and micropore volume analysis 8 ACS Paragon Plus Environment

Page 9 of 46 1 2 3 173 4 5 6 174 7 8 175 9 10 11 12 176 13 14 15 177 16 17 178 18 19 179 20 21 22 180 23 24 25 26 181 27 28 29 182 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 183 49 50 184 51 52 185 53 54 186 55 56 57 58 59 60


Figure 2 shows BET surface area and micropore (pore diameters less than 2nm) volume of biochar as a function of carbonization temperature. During the carbonization, BET surface area and micropore volume start to increase from 400℃ (1.98 m2/g and 0.0004 cm3/g each) and maximum values are attained at 600℃ (329.63 m2/g and 0.0101 cm3/g each). Then, additional heat input breaks down the porous network of biochar and the BET surface area and micropore volume start to decrease. N1000 has a BET surface area of 12.34 m2/g and a micropore volume of 0.0007 cm3/g. A similar trend for woody biomass has also been reported.16 Overall graphs of BET surface area/micropore volume as a function of carbonization temperature resemble symmetric bell-shaped curve. Below 400℃, the BET surface area

and micropore volume are not well-developed. Between 400℃ and 800℃, biochar structures develops and the porous structure collapses. Above 900℃, the microporous network of biochar almost disappears.

Figure 2. BET surface area and micropore volume of biochar samples.

Carbon K-edge core energy loss analysis and carbon sp2 content calculation


ACS Sustainable Chemistry & Engineering 1 2 3 187 4 5 6 188 7 8 189 9 10 11 12 13 14 15 16 190 17 18 191 19 20 21 192 22 23 193 24 25 194 26 27 195 28 29 30 196 31 32 197 33 34 198 35 36 37 199 38 39 200 40 41 201 42 43 44 202 45 46 203 47 48 204 49 50 51 205 52 53 206 54 55 207 56 57 58 59 60

Page 10 of 46

Deconvoluted carbon K-edge energy loss spectra of N1000 are presented in Figure 3(a). The sp2 content is a relative value between the sample 1s to π* transition peak area ratio and that of graphite. The equation is given as,35

When the electron beam passes through a thin carbon specimen, three different electronic transitions occur, and these three transitions can be fitted by Gaussian curves.31 The transition at 285.0eV (G1) represents the electronic transition from carbon 1s orbital to C=C π* bonding orbital.8-9, 11, 35-37

The second transition at 292.0eV (G2) represents the electronic transition from carbon 1s orbital to

C-C σ* bonding orbital and the third transition at 298.0eV (G3) represents the electronic transition from carbon 1s orbital to C=C σ* bonding orbital.8-9, 11, 35-37 Figure 3(b) shows changes in the calculated sp2 content of biochar produced at different carbonization temperatures. The calculated sp2 content increases from 58.0 to 77.6 mol.% when the carbonization temperature increases from 300 to 1,000℃. From the sp2 content plot, two noticeable transitions are observed. The first transition was found at 350℃, with a 4.7 mol.% increase in sp2 content, which was larger than any other temperature step. This result also correlates with the composition analysis, where degradation of the carbohydrate content contributes to an increase in atomic carbon and fixed carbon content.16 Another transition is found between 400 and 500℃, where sp2 content increases by 4.2 mol.%. At this interval, residual biomass components are further degraded and the fraction of carbon in biochar increases.38 This interval shows both a change in sp2 chemical structures and organization as measured by XRD, vide infra. The structure development of ideal biochar is related to the thermal treatment temperature.39 However, the precise criterion for the biochar structure development was vague due to lack of numerical indicator. Figure 3(b) suggests a numerical indicator 10 ACS Paragon Plus Environment

Page 11 of 46 1 2 3 208 4 5 6 209 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 210 25 26 27 28 29 30 31 32 33 34 35 36 37 38 211 39 212 40 41 213 42 43 44 214 45 46 215 47 48 216 49 50 51 217 52 53 218 54 55 219 56 57 58 59 60


for the biochar structure development, which is sp2 content as a function of carbonization temperature. This criterion will be helpful for further structure analysis of unknown biochar samples.

Figure 3. (a) N800 carbon K-edge energy loss spectrum and deconvoluted Gaussian curves (G1 (red), G2 (green), and G3 (yellow)). (b) Calculated biochar sp2 content. Four to six data points were taken from each sample and the error bars are one standard deviation.

Multiple scattering in near-edge structure and average C-C bond length calculation In Figure 3(a), a broad hump, physically related to multiple scattering resonance of the ejected core electron was detected. When the core electron is ejected from the excited atom, it behaves as a standing wave such that multiple scattering occurs.11 Understanding the multiple scattering is crucial for 11 ACS Paragon Plus Environment

ACS Sustainable Chemistry & Engineering 1 2 3 220 4 5 6 221 7 8 222 9 10 223 11 12 224 13 14 15 225 16 17 226 18 19 227 20 21 22 228 23 24 229 25 26 230 27 28 29 30 31 32 33 34 35 36 231 37 38 232 39 40 41 233 42 43 234 44 45 235 46 47 48 236 49 50 237 51 52 238 53 54 239 55 56 57 58 59 60

Page 12 of 46

the analysis of electron energy loss near-edge structure (ELNES) because a large volume of backscattering reflects the local structure of the specimen.31 To get better understanding of the multiple scattering phenomenon, an imaginary shell concept is proposed (Figure 4(a)). The excited core atom is surrounded by imaginary circles with radius define as the distance from the core atom to nth nearest neighbor atom. The ejected core electron is backscattered at the boundary between two adjacent shells. The contribution of backscattered ELNES modulations is effective within 1nm from the excited core atom.40 The wave number of the ejected electron k obeys the relationship “kR = constant” where R is bond length.17 Therefore, the multiple scattering resonance energy (EMSR) is proportional to the inverse square of R as shown in equation (2).11-12, 41 Here, RMSR is the radius of the secondary shell (2.467 Å ) and KMSR is a constant value (1980.8904eVÅ 2). The average C-C bond length is the radius of the primary shell, so RMSR value from equation (2) fits into equation (3).

Calculated average C-C bond lengths in biochar is plotted in Figure 4(b) as a function of carbonization temperature. Three significant transition points are found in the data. Between 350℃ and 500℃, the average C-C bond length decreases from 0.143 nm to 0.142 nm. Then, the C-C bond length is constant until 800℃ when the average C-C bond length increases from 0.143 nm in N700 to 0.143 nm in N800. From 900℃ to 1,000℃, the average C-C bond length decreases from 0.143 nm to 0142 nm. Drastic collapse and degradation of surface area and pore volume above 800℃ seem to have a relationship with decreasing C-C bond length. The fluctuation in the average C-C bond length implies that biomass carbonization includes various phase changes. More details will be compared with plasmon excitation results of biochar samples.


Page 13 of 46 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 240 16 17 241 18 19 242 20 21 243 22 23 244 24 25 26 245 27 28 246 29 30 247 31 32 33 248 34 35 249 36 37 250 38 39 40 251 41 42 252 43 44 253 45 46 47 254 48 49 255 50 51 256 52 53 54 55 56 57 58 59 60


Figure 4. (a) Visualization of multiple elastic scattering structure by excited core electron. (b) Calculated average C-C bond length based on ideal graphene structure. 4 to 6 data points were taken from each sample and the error bar corresponds to one standard deviation.

Low energy loss and quantum mechanical interpretation of bulk plasmon excitation Bulk plasmon excitation energy loss spectrum appears at the low energy loss region (0 ~ 100 eV). The low energy loss region spectrum of N900 is presented in Figure 5(a). The bulk plasmon exciatation energy loss peak (Ep) provides a measure of the order for different carbon materials. The diamond plasmon peak appears at 33 eV, the graphite plasmon peak appears at 27 eV, and the amorphous (or disordered) carbon plasmon peak appears at 25 eV.31, 37 Figure 5(b) shows the bulk plasmon excitation energy peak values of biochar. Biochar bulk plasmon excitation energy values are placed in between 2223 eV, consistent with known disordered carbon.8 The plasmon excitation energy increases until the carbonization temperature reaches 500℃ and then it gradually shifts to a lower energy region. A similar trend from disordered carbon was also reported.8

An electron energy loss peak related to π-π*

bonding molecular orbital transition is also observed (5-6 eV), but due to its weak intensity (dielectric nature of biochar) and overlap with the zero-loss peak, further data interpretation is not practical.


ACS Sustainable Chemistry & Engineering 1 2 3 257 4 5 6 258 7 8 259 9 10 11 12 13 14 15 260 16 17 261 18 19 262 20 21 22 263 23 24 264 25 26 265 27 28 29 266 30 31 267 32 33 268 34 35 36 37 38 39 40 41 42 43 44 269 45 46 270 47 48 271 49 50 51 52 53 54 55 56 57 58 59 60

Page 14 of 46

Physical interpretation of plasmon excitation requires a quantum mechanical approach. Equations for the resonance frequency of plasma oscillation and the plasmon energy can be derived from the Drude model, which explains displacement of a quasi-free electron in a local electric field.

In these equations, n is the electron density (valence electrons per unit volume), e is the elementary charge of an electron, m is the mass of electron, and ε0 is the vacuum permittivity.31 The resonance frequency of plasma directly related to the bulk plasmon energy, which value is proportional to the square root of the electron density. However, in a real solid, the plasma resonance is strongly confined by the damping due to single electron transitions.31 For the analysis of insulating or semiconducting materials like biochar, the band structure (for crystalline material) or HOMO (highest occupied molecular orbital) – LUMO (lowest unoccupied molecular orbital) structure (for non-crystalline materials) should be considered. As a result, the oscillator strength term, f, is introduced to modify the equation (4).42-43

Eg is an energy gap and ani is an atomic dipole matrix element for the excitation. The energy gap in the nano-sized material is determined by the quantum confinement effect.44 The equation of changing energy gap (ΔEg, equation (7)) induces an equation of changing plasmon energy (ΔEp, equation (8)).43


Page 15 of 46 1 2 3 4 5 6 7 8 272 9 10 273 11 12 274 13 14 275 15 16 17 276 18 19 277 20 21 278 22 23 24 279 25 26 280 27 28 281 29 30 31 282 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 283 49 50 51 52 53 54 55 56 57 58 59 60


m* is the effective mass of electron, d is the average distance between carbon atoms, and the subscript (b) refers to the bulk properties. Usually, d relates to nanocluster size or polymer chain length (for conductive polymer). However, the exact nanocluster size of disordered carbon cannot be measured (XRD only quantifies the average size of crystalline region) so d is replaced by the average C-C bond length as an indirect measurement of the disordered carbon nanocluster size. Based on the equation (8), the inverse square of the average C-C bond length is plotted as a function of plasmon excitation energy in Figure 5(c). The bulk plasmon excitation energy is physically related to the average C-C bond length so it indicates the development of a disordered carbon structure during the carbonization and graphitization of biomass. Perfect graphitic structure has a bulk plasmon excitation energy of 27.0 eV with the inverse square of the average C-C bond length (49.5738 nm-2).


ACS Sustainable Chemistry & Engineering 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 284 16 285 17 18 19 286 20 21 287 22 23 288 24 25 26 289 27 28 290 29 30 291 31 32 33 292 34 35 293 36 37 294 38 39 295 40 41 42 296 43 44 297 45 46 298 47 48 49 299 50 51 52 300 53 54 55 56 57 58 59 60

Page 16 of 46

Figure 5. (a) Low energy loss spectrum of N900. (b) Peak positions of biochar bulk plasmon excitation energy loss spectrum. (c) Correlation between plasmon excitation energy loss and inverse square of the average C-C bond length. 4 to 6 data points were taken from each sample and the error bars are one standard deviation.

X-ray diffraction analysis of biochar crystalline structure Background subtracted biochar XRD patterns are plotted together in Figure S1(a) and S1(b) (supporting information). The N300 biochar XRD pattern is dominated by the crystalline cellulose in the original biomass16, 45 and the pattern is not included in the biochar analysis. Increasing intensity at the (110) reflection is also observed, but the broad FWHM and weak (110) reflection intensity limit the detailed interpretation of this peak. The interlayer spacing distance is derived from the Bragg’s law.46 The layer coherence length of d100 spacing and the average number of graphene layer are derived from the Scherrer equation.8, 47-48 (002) interlayer spacing (average distance between two adjacent planes), (100) layer coherence length (La, average size of carbon crystallite in a plane), and average number of ) of biochar are calculated.48

graphene layers in an ordered graphitic stacking, ( From the Bragg’s law,


Page 17 of 46 1 2 3 301 4 5 6 302 7 8 303 9 10 11 12 13 14 304 15 16 305 17 18 306 19 20 21 307 22 23 308 24 25 309 26 27 28 310 29 30 311 31 32 312 33 34 35 313 36 37 314 38 39 315 40 41 42 316 43 44 317 45 46 318 47 48 49 319 50 51 320 52 53 321 54 55 322 56 57 58 59 60


where d is the interlayer spacing, λ is the wavelength of X-ray, and θ is the diffraction angle.46 The interlayer spacing d is inversely proportional to the incident angle θ. The (100) layer coherence length and the average number of graphene layers were derived from the Scherrer equation,

where t is the layer coherence length (mean size of ordered domain), K is the dimensionless shape factor, β is the FWHM (in radians of theta) of each d spacing, λ is the wavelength of X-ray, and θ is the diffraction angle.8, 47-48 The K value for d002 spacing equals 0.9 and that of (100) spacing equals 1.84.47 A schematic of the graphitic structure is shown in Figure 6(d). The FWHM and peak position 2θ angle of (002) and (100) reflection (Figure 6(a) and 6(d)) are used to calculate the interlayer spacing distance and the layer coherence length. From the XRD patterns, three phase transitions of biochar are observed. The initial phase transition appears at 350℃ and can be called “transition char”. As the carbonization temperature increases from 300 to 350℃, the crystalline cellulose XRD pattern disappears and single-broad XRD (002) pattern appears (Figure S1(a)). The disappearance of the crystalline cellulose XRD pattern during biomass pyrolysis is well-known.7, 16 This change is also consistent with the results of the composition analysis and EELS analysis. The secondary phase transition appears between 350 and 500℃ as the structure moves from “disordered char” to “composite char”. Indicative of this transition, the coherence length decreases dramatically from 70.2 to 2.0 nm. Above 500℃, the (100) layer coherence length starts to increase again as the carbonization temperature increases (Figure 6(c), length values of N350 and N400 biochar were too big that not plotted together but given as written numbers). N350 and N400 biochar have much longer (100) layer coherence length compared to other biochar samples. It is assumed that long range disordered structure, which is a mixture of carbon cluster and residual biomass components, dominated during this phase. The substantial decrease in the (100) layer coherence length supports the theory that increasing carbonization temperature induces structural 17 ACS Paragon Plus Environment

ACS Sustainable Chemistry & Engineering 1 2 3 323 4 5 6 324 7 8 325 9 10 326 11 12 327 13 14 15 328 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 329 31 32 33 34 35 36 37 38 39 40 41 42 43 44 330 45 331 46 47 48 332 49 50 333 51 52 334 53 54 55 335 56 57 58 59 60

Page 18 of 46

changes from disordered carbon clusters to more ordered carbon clusters. The last phase transition is found at 900℃. At the carbonization temperature step from 800 to 900℃, a crossover between the (002) interlayer spacing distance and the (100) layer coherence length is observed (Figure 6(c)). The decrease in the (002) interlayer spacing is consistent with a transition from disordered stacking of graphite layers to more ordered turbostratic stacking. The increase in the (100) layer coherence length supports growth of nano-carbon crystallites.

Figure 6. XRD pattern and derived physical profiles of biochar. (a) FWHM and peak 2θ angle of the (002) reflection. (b) FWHM and peak 2θ angle of the (100) reflection. (c) (002) interlayer spacing distance and (100) layer coherence length of biochar produced above 500℃. (002) interlayer spacing distances of N350 and N400 are 0.48 and 0.40 nm each. (100) layer coherence lengths of N350 and N400 are 70.2 and 10.0 nm each. (d) Visualization of crystalline graphitic structure. Numerical values


Page 19 of 46 1 2 3 336 4 5 6 337 7 8 338 9 10 339 11 12 340 13 14 15 341 16 17 342 18 19 343 20 21 22 344 23 24 345 25 26 346 27 28 29 347 30 31 348 32 33 349 34 35 36 350 37 38 351 39 40 352 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 353 57 58 59 60


for d002 and d100 spacing distance are given. Compared to graphite, biochar has wider (002) interlayer spacing and shorter (100) layer coherency length because ordered graphitic structure is not formed yet.

STEM HAADF imaging and modeling of nano-carbon crystallite in biochar STEM HAADF images (all at 500 nm magnification) are shown in Figure 7. Images of N300 and N400 biochar show a dense structure with parallel and repeating lines consistent with a dense morphology from the original wood. These images correspond with the BET surface area data, because the BET surface area and micropore are hardly developed below 400℃. N500 biochar shows splitting of the dense structure and the initial formation of primitive fibril-like structures. With biochar N700, there is clear separation of carbon fibril-like structures represented as raised nodes. The N800 and N900 biochars show more separation, twisting, and breaks as the length of carbon fibril structure is shortened. These STEM HAADF images suggest a path for the structural development of nano-carbon crystallites in biochar. Previous biochar structural development models proposed radially growing polyaromatic carbon crystallite.5-6 However, the STEM HAADF images suggest lengthwise growth of carbon crystallite because carbon fibril-like structure is observed from biochar. Increasing (001) layer coherence length also supports a lengthwise growth model.


ACS Sustainable Chemistry & Engineering 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 354 18 355 19 20 356 21 22 23 357 24 25 358 26 27 359 28 29 30 360 31 32 361 33 34 362 35 36 37 363 38 39 364 40 41 365 42 43 366 44 45 46 367 47 48 368 49 50 369 51 52 53 370 54 55 371 56 57 58 59 60

Page 20 of 46

Figure 7. HAADF images of biochar at 500 nm magnification. (a-f) N300, N400, N500, N700, N800 and N900.

Combining all the information from STEM HAADF, EELS, and XRD analysis, a new biochar structural development model is proposed, as shown schematically in Figure 8. The descriptive nomenclature for each phase follows the work of Keiluweit et al.16 Transition char: The original biomass structure dominates the biochar structure. Transition char has a high fraction of hydrogen, oxygen, and volatiles. The XRD pattern is dominated by the crystalline cellulose structure. The initial degradation of biomass structure between 300 to 350℃ is clearly observed and the increases in carbon, fixed carbon and sp2 content are the highest among any other carbonization temperature step. BET surface area and micropore are not well-developed at this transition char stage. The XRD pattern associated with crystalline cellulose disappears during this transition. There is no evidence for multiple-layer carbon stacking. Disordered char: A disordered carbon structure appears at 350℃. Residual biomass components only occupy a minor structural fraction. BET surface area and micropore volume start to increase. The average C-C bond length decreases from 0.14339 nm to 0.14246 nm. The sp2 content of biochar gradually increases and the FWHM of the (002) reflection narrows due to degradation of biomass 20 ACS Paragon Plus Environment

Page 21 of 46 1 2 3 372 4 5 6 373 7 8 374 9 10 375 11 12 13 376 14 15 377 16 17 378 18 19 379 20 21 22 380 23 24 381 25 26 382 27 28 29 383 30 31 384 32 33 385 34 35 36 386 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


components. Decrease in (100) layer coherence length supports formation of nano-carbon crystallites. The term “amorphous” in carbon material should be used carefully due to the above mentioned reasons. Composite char: Nano-carbon crystallite begins to grow at 500℃. BET surface area and micropore volume reach their maximum values at 600℃ and then start to decrease. The average C-C bond length remains still at about 0.142 nm range. The sp2 content continues to increase, while the (100) layer coherence length gradually increases from 2.0 to 2.3 nm and the average number of graphene layer increases from 1.4 to 2.0 layers. The initial nano-carbon crystallite molecular structure can be detected within the composite char phase. Turbostratic char: Primitive graphitic structure appears at about 900℃. The microporous structure of biochar mostly disappears. Turbostratic char still does not have completely ordered graphitic structure, but it has two to three layers of ordered graphitic stacking. The average C-C bond length decreases from 0.14301 nm to 0.14235 nm. The cross over between (002) interlayer spacing distance and (100) layer coherence length clearly differentiates turbostratic char from composite char. Biochar sp 2 content reaches the maximum value seen in this work (78.6 mol.%).



Page 22 of 46

Figure 8. Schematic of the chemical and morphological changes that occur during the carbonization of biomass at different temperatures.

Conclusions We propose a biochar structural development model based on the experimental results including their compositions, BET surface area, micropore volume, sp2 content, average C-C bond length, bulk plasmon excitation energy, interlayer spacing, and layer coherence length. As pine biomass is thermally treated, four different structural development phases are identified, which provide a comprehensive understanding of biochar nano-carbon crystallite development. Unlike previous biochar structure models, which proposed radially growing polyaromatic carbon crystallite, we propose lengthwise growing polyaromatic carbon crystallite model. This experimental-based biochar model should be helpful when determining structure of unknown biomass derived carbon materials. Future study will include quantification of surface functional groups in biochar and reconstruction of disordered carbon structure.


Page 23 of 46 1 2 3 402 4 5 6 403 7 8 404 9 10 405 11 12 406 13 14 15 407 16 17 408 18 19 409 20 21 22 410 23 24 411 25 26 412 27 28 29 413 30 31 414 32 33 415 34 35 416 36 37 38 417 39 40 418 41 42 419 43 44 45 420 46 47 421 48 49 422 50 51 52 423 53 54 424 55 56 57 58 59 60


Acknowledgement. This project is supported by the USDA National Institute of Food and Agriculture (Award 2011-68005-30410) and the US-DOE Office of Energy Efficiency and Renewable Energy (Award Number DE-EE0006639). The characterization was performed at the Analytical Instrumentation Facility (AIF), supported by the State of North Carolina and the National Science Foundation (Award ECCS-1542015).

Supporting Information Supplementary Figure S1(a): XRD patterns 1 Supplementary Figure S2(b): XRD patterns 2


ACS Sustainable Chemistry & Engineering 1 2 3 425 4 5 426 6 427 7 428 8 429 9 10 430 11 431 12 432 13 433 14 434 15 435 16 436 17 437 18 19 438 20 439 21 440 22 441 23 442 24 443 25 444 26 445 27 28 446 29 447 30 448 31 449 32 450 33 451 34 452 35 453 36 454 37 38 455 39 456 40 457 41 458 42 459 43 460 44 461 45 462 46 47 463 48 464 49 465 50 466 51 467 52 468 53 469 54 470 55 56 57 58 59 60

Page 24 of 46

References (1) Zhang, F.; Wang, K. X.; Li, G. D.; Chen, J. S., Hierarchical porous carbon derived from rice straw for lithium ion batteries with high-rate performance. Electrochem. Commun. 2009, 11, 130-133. (2) Xie, L. J.; Sun, G. H.; Su, F. Y.; Guo, X. Q.; Kong, Q. Q.; Li, X. M.; Huang, X. H.; Wan, L.; Song, W.; Li, K. X.; Lv, C. X.; Chen, C. M., Hierarchical porous carbon microtubes derived from willow catkins for supercapacitor applications. J. Mater. Chem. A 2016, 4, 1637-1646. (3) Zhang, J. B.; Zhong, Z. P.; Shen, D. K.; Zhao, J. X.; Zhang, H. Y.; Yang, M.; Li, W. L., Preparation of BambooBased Activated Carbon and Its Application in Direct Carbon Fuel Cells. Energy Fuels 2011, 25, 2187-2193. (4) Dong, Y. Q.; Zhou, N. N.; Lin, X. M.; Lin, J. P.; Chi, Y. W.; Chen, G. N., Extraction of Electrochemiluminescent Oxidized Carbon Quantum Dots from Activated Carbon. Chem. Mater. 2010, 22, 58955899. (5) Brewer, C. E.; Schmidt-Rohr, K.; Satrio, J. A.; Brown, R. C., Characterization of Biochar from Fast Pyrolysis and Gasification Systems. Environ. Prog. Sustainable Energy 2009, 28, 386-396. (6) Park, J.; Hung, I.; Gan, Z. H.; Rojas, O. J.; Lim, K. H.; Park, S., Activated carbon from biochar: Influence of its physicochemical properties on the sorption characteristics of phenanthrene. Bioresourc. Technol. 2013, 149, 383-389. (7) Kim, K. H.; Kim, J. Y.; Cho, T. S.; Choi, J. W., Influence of pyrolysis temperature on physicochemical properties of biochar obtained from the fast pyrolysis of pitch pine (Pinus rigida). Bioresourc. Technol. 2012, 118, 158-162. (8) Zhang, Z. L.; Brydson, R.; Aslam, Z.; Reddy, S.; Brown, A.; Westwood, A.; Rand, B., Investigating the structure of non-graphitising carbons using electron energy loss spectroscopy in the transmission electron microscope. Carbon 2011, 49, 5049-5063. (9) Marriott, A. S.; Hunt, A. J.; Bergstrom, E.; Wilson, K.; Budarin, V. L.; Thomas-Oates, J.; Clark, J. H.; Brydson, R., Investigating the structure of biomass-derived non-graphitizing mesoporous carbons by electron energy loss spectroscopy in the transmission electron microscope and X-ray photoelectron spectroscopy. Carbon 2014, 67, 514-524. (10) Jorio, A.; Ribeiro-Soares, J.; Cancado, L. G.; Falcao, N. P. S.; Dos Santos, H. F.; Baptista, D. L.; Ferreira, E. H. M.; Archanjo, B. S.; Achete, C. A., Microscopy and spectroscopy analysis of carbon nanostructures in highly fertile Amazonian anthrosoils. Soil Tillage Res. 2012, 122, 61-66. (11) Daniels, H.; Brydson, R.; Rand, B.; Brown, A., Investigating carbonization and graphitization using electron energy loss spectroscopy (EELS) in the transmission electron microscope (TEM). Philos. Mag. 2007, 87, 4073-4092. (12) Craven, A. J.; Garvie, L. A. J., Electron-Energy-Loss near-Edge Structure (Elnes) on the Carbon K-Edge in Transition-Metal Carbides with the Rock-Salt Structure. Microsc., Microanal., Microstruct. 1995, 6, 89-98. (13) Yao, Y.; Gao, B.; Inyang, M.; Zimmerman, A. R.; Cao, X. D.; Pullammanappallil, P.; Yang, L. Y., Removal of phosphate from aqueous solution by biochar derived from anaerobically digested sugar beet tailings. J. Hazard. Mater. 2011, 190, 501-507. (14) Singh, B.; Fang, Y. Y.; Cowie, B. C. C.; Thomsen, L., NEXAFS and XPS characterisation of carbon functional groups of fresh and aged biochars. Org. Geochem. 2014, 77, 1-10. (15) Liu, P.; Liu, W. J.; Jiang, H.; Chen, J. J.; Li, W. W.; Yu, H. Q., Modification of bio-char derived from fast pyrolysis of biomass and its application in removal of tetracycline from aqueous solution. Bioresourc. Technol. 2012, 121, 235-240. (16) Keiluweit, M.; Nico, P. S.; Johnson, M. G.; Kleber, M., Dynamic Molecular Structure of Plant BiomassDerived Black Carbon (Biochar). Environ. Sci. Technol. 2010, 44, 1247-1253. (17) Bianconi, A.; Incoccia, L.; Stipcich, S., EXAFS and near edge structure : proceedings of the international conference, Frascati, Italy, September 13-17, 1982. Springer-Verglag: Berlin; New York, 1983; p 4-65.


Page 25 of 46 1 2 3 471 4 472 5 473 6 7 474 8 475 9 476 10 477 11 478 12 479 13 480 14 481 15 16 482 17 483 18 484 19 485 20 486 21 487 22 488 23 489 24 490 25 26 491 27 492 28 493 29 494 30 495 31 496 32 497 33 498 34 35 499 36 500 37 501 38 502 39 503 40 504 41 505 42 506 43 44 507 45 508 46 509 47 510 48 511 49 512 50 513 51 514 52 515 53 54 516 55 517 56 57 58 59 60


(18) Ferrari, A. C.; Robertson, J., Interpretation of Raman spectra of disordered and amorphous carbon. Phys. Rev. B 2000, 61, 14095-14107. (19) Zhang, M.; Gao, B.; Yao, Y.; Xue, Y. W.; Inyang, M., Synthesis of porous MgO-biochar nanocomposites for removal of phosphate and nitrate from aqueous solutions. Chem. Eng. J. 2012, 210, 26-32. (20) Franklin, R. E., Crystallite Growth in Graphitizing and Non-Graphitizing Carbons. Proc R Soc Lon Ser-A 1951, 209, 196-218. (21) Oberlin, A., Carbonization and Graphitization. Carbon 1984, 22, 521-541. (22) Harris, P. J. F., New perspectives on the structure of graphitic carbons. Crit. Rev. Solid State Mater. Sci. 2005, 30, 235-253. (23) , E. b., Carbons for electrochemical energy storage and conversion systems. CRC Press: Boca Raton, 2010; p 1-220. (24) Hata, T.; Imamura, Y.; Nishimiya, K.; Bronsveld, P.; Vystavel, T.; De Hosson, J.; Kikuchi, H., Electron microscopic study on catalytic carbonization of biomass carbon: I. Carbonization of wood charcoal at high temperature by Al-triisopropoxide. Mol. Cryst. Liq. Cryst. 2002, 386, 33-38. (25) Thompson, E.; Danks, A. E.; Bourgeois, L.; Schnepp, Z., Iron-catalyzed graphitization of biomass. Green Chem. 2015, 17, 551-556. (26) McNaught, A. D.; Wilkinson, A., Compendium of chemical terminology. Second ed.; Wiley: 1997. (27) Emmerich, F. G.; Desousa, J. C.; Torriani, I. L.; Luengo, C. A., Applications of a Granular Model and Percolation Theory to the Electrical-Resistivity of Heat-Treated Endocarp of Babassu Nut. Carbon 1987, 25, 417424. (28) Laine, J.; Yunes, S., Effect of the Preparation Method on the Pore-Size Distribution of Activated Carbon from Coconut Shell. Carbon 1992, 30, 601-604. (29) Standard Test Methods for Proximate Analysis of Coal and Coke by Macro Thermogravimetric Analysis. ASTM International: 2015. (30) Chmiola, J.; Yushin, G.; Dash, R.; Gogotsi, Y., Effect of pore size and surface area of carbide derived carbons on specific capacitance. J. Power Sources 2006, 158, 765-772. (31) Egerton, R. F., Electron energy-loss spectroscopy in the electron microscope. Third ed.; Springer: New York, 2011; p 1-389. (32) Shafizadeh, F., Introduction to Pyrolysis of Biomass. J. Anal. Appl. Pyrolysis 1982, 3, 283-305. (33) Asadieraghi, M.; Daud, W. M. A. W., Characterization of lignocellulosic biomass thermal degradation and physiochemical structure: Effects of demineralization by diverse acid solutions. Energy Convers. Manage. 2014, 82, 71-82. (34) Mansaray, K. G.; Ghaly, A. E., Thermal degradation of rice husks in nitrogen atmosphere. Bioresourc. Technol. 1998, 65, 13-20. (35) Muller, J. O.; Su, D. S.; Wild, U.; Schlogl, R., Bulk and surface structural investigations of diesel engine soot and carbon black. Phys. Chem. Chem. Phys. 2007, 9, 4018-4025. (36) Galvan, D.; Pei, Y. T.; De Hosson, J. T. M.; Cavaleiro, A., Determination of the sp(3) C content of a-C films through EELS analysis in the TEM. Surf. Coat. Technol. 2005, 200, 739-743. (37) Berger, S. D.; Mckenzie, D. R.; Martin, P. J., Eels Analysis of Vacuum Arc-Deposited Diamond-Like Films. Philos. Mag. Lett. 1988, 57, 285-290. (38) Kim, K. H.; Eom, I. Y.; Lee, S. M.; Choi, D.; Yeo, H.; Choi, I. G.; Choi, J. W., Investigation of physicochemical properties of biooils produced from yellow poplar wood (Liriodendron tulipifera) at various temperatures and residence times. J. Anal. Appl. Pyrolysis 2011, 92, 2-9. (39) Lehmann, J.; Joseph, S., Biochar for environmental management : science, technology and implementation. Second ed.; Routledge, Taylor & Francis Group: London ; New York, 2015; p 89-138. (40) Wang, F.; Egerton, R. F.; Malac, M.; McLeod, R. A.; Moreno, M. S., The spatial resolution of electron energy loss and x-ray absorption fine structure. J. Appl. Phys. 2008, 104.



Page 26 of 46

(41) McCulloch, D.; Brydson, R., Carbon K-shell near-edge structure calculations for graphite using the multiple-scattering approach. J. Phys.: Condens. Matter 1996, 8, 3835. (42) Hummel, R. E., Electronic properties of materials. 4th ed.; Springer: New York, 2011; p 3-75. (43) Mitome, M.; Yamazaki, Y.; Takagi, H.; Nakagiri, T., Size Dependence of Plasmon Energy in Si Clusters. J. Appl. Phys. 1992, 72, 812-814. (44) de Mello Donegá, C., Nanoparticles. Springer: 2014; p 13-26. (45) Park, S.; Baker, J. O.; Himmel, M. E.; Parilla, P. A.; Johnson, D. K., Cellulose crystallinity index: measurement techniques and their impact on interpreting cellulase performance. Biotechnol. Biofuels 2010, 3. (46) Iadonisi, G., Introduction to solid state physics and crystalline nanostructures. 1st edition. ed.; Springer: New York, 2013; p 97-264. (47) Kercher, A. K.; Nagle, D. C., Microstructural evolution during charcoal carbonization by X-ray diffraction analysis. Carbon 2003, 41, 15-27. (48) Hammond, C., The basics of crystallography and diffraction. Fourth edition. ed.; Oxford University Press: Oxford, 2015; p 139-201.


Page 27 of 46 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


Figure 1. Composition analysis result of loblolly pine (raw) and nine biochar samples. Bar graphs represent the atomic compositions (mol.%) of carbon, hydrogen, oxygen, and nitrogen. Line graphs represent the proximate analysis results of fixed carbon, volatile, and ash. 323x221mm (96 x 96 DPI)



Figure 2. BET surface area and micropore volume of biochar samples. 282x169mm (150 x 150 DPI)


Page 28 of 46

Page 29 of 46 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


Figure 3. (a) N800 carbon K-edge energy loss spectrum and deconvoluted Gaussian curves (G1 (red), G2 (green), and G3 (yellow)). 279x152mm (96 x 96 DPI)



Figure 3. (b) Calculated biochar sp2 content. 4 to 6 data points were taken from each sample and the bar follows a standard deviation. 303x174mm (150 x 150 DPI)


Page 30 of 46

Page 31 of 46 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


Figure 4. (a) Visualization of multiple elastic scattering structure by excited core electron. 329x190mm (150 x 150 DPI)



Figure 4. (b) Calculated average C-C bond length based on ideal graphene structure. 4 to 6 data points were taken from each sample and the bar follows a standard deviation. 297x166mm (150 x 150 DPI)


Page 32 of 46

Page 33 of 46 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


Figure 5. (a) Low energy loss spectrum of N900. 301x177mm (150 x 150 DPI)



Figure 5. (b) Peak positions of biochar bulk plasmon excitation energy loss spectrum. 293x172mm (150 x 150 DPI)


Page 34 of 46

Page 35 of 46 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


Figure 5. (c) Correlation between plasmon excitation energy loss and inverse square of the average C-C bond length. 4 to 6 data points were taken from each sample and the bar follows a standard deviation. 288x166mm (150 x 150 DPI)



Figure 6. (a) FWHM and peak 2θ angle of (002) reflection. 179x118mm (96 x 96 DPI)


Page 36 of 46

Page 37 of 46 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


Figure 6. (b) FWHM and peak 2θ angle of (100) reflection. 179x118mm (96 x 96 DPI)



Figure 6. (c) (002) interlayer spacing distance and (100) layer coherence length of biochar produced above 500℃. (002) interlayer spacing distances of N350 and N400 are 0.48 and 0.40 nm each. (100) layer coherence lengths of N350 and N400 are 70.2 and 10.0 nm each. 255x151mm (96 x 96 DPI)


Page 38 of 46

Page 39 of 46 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


Figure 6. (d) Visualization of crystalline graphitic structure. Numerical values for d002 and d100 spacing distance are given. Compared to graphite, biochar has wider (002) interlayer spacing and shorter (100) layer coherency length because ordered graphitic structure is not formed yet. 389x362mm (96 x 96 DPI)



Figure 7. HAADF images of biochar at 500 nm magnification. (a) N300 1040x1075mm (25 x 25 DPI)


Page 40 of 46

Page 41 of 46 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


Figure 7. HAADF images of biochar at 500 nm magnification. (b) N400 270x280mm (96 x 96 DPI)



Figure 7. HAADF images of biochar at 500 nm magnification. (c) N500 1040x1075mm (25 x 25 DPI)


Page 42 of 46

Page 43 of 46 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


Figure 7. HAADF images of biochar at 500 nm magnification. (d) N700 270x280mm (96 x 96 DPI)



Figure 7. HAADF images of biochar at 500 nm magnification. (e) N800 1040x1075mm (25 x 25 DPI)


Page 44 of 46

Page 45 of 46 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


Figure 7. HAADF images of biochar at 500 nm magnification. (f) N900 1040x1075mm (25 x 25 DPI)



Figure 8. Schematic of the chemical and morphological changes that occur during the carbonization of biomass at different temperatures. 309x190mm (150 x 150 DPI)


Page 46 of 46

Structural Characterization of Loblolly Pine ... - ACS Publications

Recommend Documents