Tom Willhammar1, Kazuho Daicho2, Duncan N Johnstone3, Kayoko Kobayashi2, Yingxin Liu1, Paul A Midgley3, Lennart Bergström1, Tsuguyuki Saito2. 1. Department of Materials and Environmental Chemistry, Stockholm University, SE-106 91 Stockholm, Sweden. 2. Department of Biomaterial Sciences, Graduate School of Agricultural and Life Sciences, The University of Tokyo, Tokyo 113-8657, Japan. 3. Department of Materials Science & Metallurgy, University of Cambridge, Cambridge CB3 0FS, U.K.
Abstract
Cellulose is crystallized by plants and other organisms into fibrous nanocrystals. The mechanical properties of these nanofibers and the formation of helical superstructures with energy dissipating and adaptive optical properties depend on the ordering of polysaccharide chains within these nanocrystals, which is typically measured in bulk average. Direct measurement of the local polysaccharide chain arrangement has been elusive. In this study, we use the emerging technique of scanning electron diffraction to probe the packing of polysaccharide chains across cellulose nanofibers and to reveal local ordering of the chains in twisting sections of the nanofibers. We then use atomic force microscopy to shed light on the size dependence of the inherent driving force for cellulose nanofiber twisting. The direct measurement of crystalline twisted regions in cellulose nanofibers has important implications for understanding single-cellulose-fibril properties that influence the interactions between cellulose nanocrystals in dense assemblies. This understanding may enable cellulose extraction and separation processes to be tailored and optimized.
Cellulose is crystallized by plants and other organisms into fibrous nanocrystals. The mechanical properties of these nanofibers and the formation of helical superstructures with energy dissipating and adaptive optical properties depend on the ordering of polysaccharide chains within these nanocrystals, which is typically measured in bulk average. Direct measurement of the local polysaccharide chain arrangement has been elusive. In this study, we use the emerging technique of scanning electron diffraction to probe the packing of polysaccharide chains across cellulose nanofibers and to reveal local ordering of the chains in twisting sections of the nanofibers. We then use atomic force microscopy to shed light on the size dependence of the inherent driving force for cellulose nanofiber twisting. The direct measurement of crystalline twisted regions in cellulose nanofibers has important implications for understanding single-cellulose-fibril properties that influence the interactions between cellulose nanocrystals in dense assemblies. This understanding may enable cellulose extraction and separation processes to be tailored and optimized.
Entities:
Keywords:
CNF; TEM; cellulose; diffraction; electron diffraction; nanofiber
Cellulose is the most
abundant biomolecule on Earth, produced in
the cell wall of plants and many other organisms by the condensation
polymerization of glucose. The constituent polysaccharide chains typically
form nanocrystalline units with dimensions that depend on the organism
growing the crystals. Such “nanocellulose”, which may
comprise cellulose nanofibers (CNFs) or nanocrystals (CNCs), is lightweight,
strong, and chiral, leading to significant interest for sustainable
materials applications ranging from biomedical scaffolds to thermal
insulation foams, packaging materials, and photonic films.[1−3]The mechanical and functional properties of nanocellulose
and the
ability of nanocellulose dispersions to form liquid crystalline phases
depend on the structure, morphology, and inherent defects of the CNFs
and CNCs. Bulk measurements of the atomic structure in nanocellulose,
using fiber X-ray and neutron diffraction of highly crystalline specimens,[4,5] typically reveal two different average crystal structures, the triclinic
Iα cellulose (P1, a = 6.718
Å, b = 5.963 Å, c = 10.401
Å, α = 118.09°, β = 114.81°, γ =
80.38°) and the monoclinic Iβ cellulose (P21, a = 7.785 Å, b = 8.202 Å, c = 10.380 Å, α = 90°,
β = 90°, γ = 96.5°) polymorphs. The crystallinity
and crystal imperfections of cellulose fibers have been identified
and quantified, e.g., using cross-polarization 13C nuclear magnetic resonance (NMR).[6−8] However, these
characterization techniques typically only provide information related
to the bulk averaged atomic structure and crystalline domain size.[9] Twisting and kinking of nanocellulose extracted
from both plants and other organisms has been observed by electron
microscopy and atomic force microscopy (AFM).[10−12] This twist
is associated with the tough, energy dissipating, cross-ply structures
in the cell walls of many plants and the ability of CNCs to form cholesteric
phases,[3] but the local atomic and molecular
arrangement in these twisted regions has remained elusive in the absence
of a suitable nanoscale structural probe.The strong electrostatic
interaction between electrons and matter
enables electron diffraction data to be obtained from regions on the
few nanometer scale. 3D single-crystal electron diffraction methods
have evolved into important techniques for structure determination
of submicrometer sized crystals over the past decade,[13−15] and that has now been applied to inorganic materials,[16,17] small organic molecules,[18,19] and proteins.[20] Electron diffraction has been used for studies
of the average crystal structures of cellulose down to beam sizes
of ∼70 nm, and high-resolution transmission electron microscopy
(TEM) images with lattice resolution have been used to study the morphology–structure
relationship of individual CNFs.[21−24] Dark-field (DF) TEM imaging has
been used to obtain information about the crystalline microstructure
of CNFs, but the small number of DF TEM images that can be formed
by conventional means has left many questions unanswered.[25] Scanning electron diffraction (SED) is a 4D
scanning TEM (4D STEM) technique,[26] in
which a 2D electron diffraction pattern is recorded at every position
as a focused electron probe is scanned across the sample (see Figure a,b). SED has recently
emerged as a powerful technique for obtaining spatially resolved electron
diffraction data from beam sensitive materials including molecular
crystals,[27] polymers,[28] proteins,[29] halide perovskites,[30] and metal–organic frameworks.[31,32] In this study, we use SED to map the crystalline microstructure
of nanocrystalline CNFs with a resolution down to a few nanometers.
Further, we complement our direct measurements of the local crystal
structure with AFM measurements of the size and morphology of numerous
CNFs.
Figure 1
SED reveals local crystallinity in a twisting tunicate CNF. (a)
The electron probe is scanned in a raster pattern across the specimen,
and a diffraction pattern is acquired at each probe position. (b)
A 4D SED data set is generated comprising a 2D diffraction pattern
at each probe position in the 2D scan. (c) SED data obtained from
a sample of CNFs extracted from a tunicate. From three parts of a
single CNF, distinct zone-axis electron diffraction patterns can be
identified corresponding to the electron beam being incident along
the crystallographic directions of the cellulose Iβ structure
indicated. (d-f) The zone-axis diffraction patterns can be indexed
as the [010], [110], and [11̅0] directions of the cellulose
Iβ structure, respectively. The three orientations describe
a twist around the extended axis of the CNF, which is the crystallographic c axis aligned with the polysaccharide chain axis. The twist
angles between [010] ^ [110] and [110] ^ [11̅0] are 47 and 93°
respectively.
SED reveals local crystallinity in a twisting tunicate CNF. (a)
The electron probe is scanned in a raster pattern across the specimen,
and a diffraction pattern is acquired at each probe position. (b)
A 4D SED data set is generated comprising a 2D diffraction pattern
at each probe position in the 2D scan. (c) SED data obtained from
a sample of CNFs extracted from a tunicate. From three parts of a
single CNF, distinct zone-axis electron diffraction patterns can be
identified corresponding to the electron beam being incident along
the crystallographic directions of the cellulose Iβ structure
indicated. (d-f) The zone-axis diffraction patterns can be indexed
as the [010], [110], and [11̅0] directions of the cellulose
Iβ structure, respectively. The three orientations describe
a twist around the extended axis of the CNF, which is the crystallographic c axis aligned with the polysaccharide chain axis. The twist
angles between [010] ^ [110] and [110] ^ [11̅0] are 47 and 93°
respectively.
Results and Discussion
We extracted
CNFs from a tunicate (Halocynthia roretzi) mantle
(i.e., body wall) through a mild TEMPO
oxidation under weakly acidic conditions at pH 5 and 40 °C, followed
by wet disintegration and centrifugation.[33] SED data were collected from the tunicate CNFs with ∼5 nm
spatial resolution and a convergence angle of <2 mrad, as shown
in Figure (see also Figures and 4 and Supplementary Figures 1 and 2). The measured diffraction patterns in Figure d–f contain sharp Bragg discs to beyond
0.55 Å–1, indicating that the crystalline quality
of the specimen is good and that our SED measurement has not caused
significant damage during acquisition. Along the single CNF, shown
in Figure c, different
diffraction patterns are obtained (Figure c–f). These diffraction patterns can
be indexed to different crystal orientations of the monoclinic Iβ
cellulose crystal structure, as illustrated in Figure c–f. This indexation of the diffraction
data shows that the long axis of the CNF corresponds to the crystallographic c-axis, which is the direction of the polysaccharide chain
axis (Figure d–f).
Three distinct orientations can be identified in the selected CNF
segment, corresponding to the [010], [110], and [11̅0] zone-axis
orientations, which are reached sequentially moving along the CNF.
This sequential change in orientation describes the trajectory of
a twist around the crystallographic c axis (Figure d–f). Between
the regions at zone-axis orientations, the diffraction patterns contain
the 004 reflection, which is approximately perpendicular to the incident
beam direction (see Supplementary Figure 1). The twist angles between each of the pairs of diffraction patterns
can be calculated based on the geometry of the cellulose Iβ
crystal structure and are ∼47° for [010] ^ [110] and ∼93°
for [110] ^ [11̅0], indicating a twist rate of ∼0.65
and ∼0.63°/nm, respectively. Further, the agreement between
the measured diffraction patterns and the diffraction expected for
the Iβ cellulose crystal structure (see Supplementary Figure 2) demonstrates that local crystallographic
ordering is preserved through the twisted regions.
Figure 2
SED visualizes twisting
of a tunicate CNF. By plotting the intensity
within selected masks as a function of probe position, VDF images
can be formed. For the case where Bragg reflections are selected,
domains of the corresponding orientations are revealed. VDF images
formed from (a) an annular mask and (b–d) the three selected
Bragg reflections; 110, 11̅0, and 200 respectively. Representable
diffraction patterns of each orientation extracted from the SED data
are shown as the inset in (b–d). The sequential occurrence
of the three reflections indicates twisting regions of the CNF, marked
by rectangles in (b–d). The twisted regions are separated by
flat domains.
Figure 4
Revealing
crystallinity transverse to the fiber axis using SED.
VDF images generated using the SED data obtained from (a) tunicate
CNFs and (b) CNCs of bacterial origin. Annular VDF images show the
overall morphology of the CNF/CNC. VDF images generated by integrating
windows containing selected key reflections show the domains of given
orientations. (c–f) Line traces across the CNF/CNC, comparing
the same domains of the annular (orange) and reflection (blue) VDF
maps. The tunicate CNFs have an approximately uniform crystallinity
extending over the cross section of the fiber as seen in (c) and (d),
whereas the CNCs of bacterial origin exhibit fragmented domains as
shown by the split in the blue traces in (e) and (f). The line trace
from the annular map of the tunicate CNFs shows a slightly wider profile
compared to the line trace from 004 and 200 reflections indicating
that the CNF is not crystalline through its entire width. The Bragg
reflections are indexed with respect to the Iβ and Iα
cellulose crystal structures for tunicate and bacterial cellulose,
respectively.
SED visualizes twisting
of a tunicate CNF. By plotting the intensity
within selected masks as a function of probe position, VDF images
can be formed. For the case where Bragg reflections are selected,
domains of the corresponding orientations are revealed. VDF images
formed from (a) an annular mask and (b–d) the three selected
Bragg reflections; 110, 11̅0, and 200 respectively. Representable
diffraction patterns of each orientation extracted from the SED data
are shown as the inset in (b–d). The sequential occurrence
of the three reflections indicates twisting regions of the CNF, marked
by rectangles in (b–d). The twisted regions are separated by
flat domains.The twisting of numerous CNFs
in a scanned region was observed
and quantified by forming virtual dark-field (VDF) images (see Figure ). VDF images are
generated by filtering each diffraction pattern in the SED data using
a mask, e.g., at the position of a selected Bragg
disc. In this case, the obtained maps will illuminate crystalline
domains with an orientation corresponding to the selected Bragg reflection.
VDF images were formed using the three strongest Bragg discs corresponding
to the crystal planes (hkl) 200, 110, and 11̅0,
which are associated with interchain spacing between polysaccharide
chains of ∼3.87, 5.31, and 5.96 Å, respectively. These
VDF images reveal where these reflections come into the Bragg condition.
The observation that these Bragg conditions are sequentially met along
the CNFs indicates that parts of the fibers are twisted. This twisting
is not continuous, as the sequence of reflections appears in short
sections separated by regions where the CNF lies flat on the support
grid. In the twisting sections of the fibers, the pitch of the twist
can be determined based on the distance between the measured orientations.
Following this, a twist rate can be determined as the angle by which
the fiber is twisting per nanometer. The average twist rate between
the 11̅0 ^ 200 reflections is 0.65 ± 0.18°/nm and
between the 110 ^ 11̅0 reflections is 0.63 ± 0.14°/nm,
with errors reported as one standard deviation.We use atomic
force microscopy (AFM) to assess the morphology of
numerous CNFs, as shown in Figure , and relate this morphology to the twisting observed
directly using SED. An automated method was implemented to extract
the height profile from a 3-pixel-wide line along the center of each
CNF, and the histogram of CNF heights, shown in Figure b, comprises a distribution modeled as three
normal distributions with mean values at 3.0 ± 1.5, 7.4 ±
2.0, and 13.0 ± 2.9 nm. By considering the spatial distribution
of these height measurements, we determine that the distributions
around 3.0 and 7.4 nm correspond to isolated CNFs, whereas the distribution
around 13.0 nm, which is broader, corresponds primarily to regions
where CNFs are overlapping. The analysis of many CNFs showed that
individual CNFs could also display thicker regions separated by domains
of uniform thickness (Figure c). The increased thickness of the individual CNFs indicates
the parts of the CNFs that are twisted with respect to the extended
regions of very consistent thickness, which is similar to our SED
observations. We use the large amount of data extracted from analysis
of the AFM height images to provide more insight into the tunicate
CNFs twisting.
Figure 3
Atomic force microscopy of twisted tunicate CNFs. (a)
Height images
of networked and isolated regions of the tunicate CNFs deposited on
a flat substrate. (b) Histogram of the height profile along a 3-pixel-wide
center line of each CNF, which is fit to three Gaussians and separated
into three size groups (blue, green, and red) that are mapped in (c).
The isolated CNF includes locally thick, red domains resulting from
the twisting of the CNFs. (d) The cross-sectional models parallel
and vertical to the fiber axis of the twisted CNF where α is
the peak height at the locally twisted part, β is the height
of the flat region, δ is the full width at half-maximum (fwhm)
of the peak profile in the twisted region, and χ is the distance
between the subsequent two peaks. The heights α and β
correspond to the longest and shortest dimensions of the vertical
cross section, which is modeled as an ellipse based on the truncated
parallelogram shape observed by Helbert et al. (e)
The linear correlation between α and β indicates a geometric
similarity of the cross-sectional shapes. (f) The inherent twist rate,
given by 180/χ, as a function of the reciprocal of the vertical
cross-sectional area.
Atomic force microscopy of twisted tunicate CNFs. (a)
Height images
of networked and isolated regions of the tunicate CNFs deposited on
a flat substrate. (b) Histogram of the height profile along a 3-pixel-wide
center line of each CNF, which is fit to three Gaussians and separated
into three size groups (blue, green, and red) that are mapped in (c).
The isolated CNF includes locally thick, red domains resulting from
the twisting of the CNFs. (d) The cross-sectional models parallel
and vertical to the fiber axis of the twisted CNF where α is
the peak height at the locally twisted part, β is the height
of the flat region, δ is the full width at half-maximum (fwhm)
of the peak profile in the twisted region, and χ is the distance
between the subsequent two peaks. The heights α and β
correspond to the longest and shortest dimensions of the vertical
cross section, which is modeled as an ellipse based on the truncated
parallelogram shape observed by Helbert et al. (e)
The linear correlation between α and β indicates a geometric
similarity of the cross-sectional shapes. (f) The inherent twist rate,
given by 180/χ, as a function of the reciprocal of the vertical
cross-sectional area.By measuring the thickness
of the CNFs in the flat sections as
well as in twisted regions, the shortest and longest sides of their
cross section, defined in Figure d, could be determined. A correlation of the two dimensions,
as shown in Figure e, indicates that the dimensions of the cross section are highly
correlated and there is geometrical similarity of the cross-sectional
shape along the CNF. To evaluate the twist rate given that twisting
is highly localized to specific regions, we note that the CNFs are
hydrophilic and have high free-energy surfaces, such that the interaction
with the hydrophilic substrate affects the way the fiber behaves.
As the fibers dry on the substrate, the twisting forces of the fiber
will be balanced by the surface interaction, and the flat sections
of the fibers are formed with the larger side of the cross section
preferentially lying flat on the substrate.[10,24] This localizes the twisted region along the CNFs as observed by
AFM and SED. This means that the local twist rate of the twisting
domains will be determined by balancing of the inherent driving force
for the twist and the surface interaction. The local twist rate can
be measured from both SED and AFM data by tracing the fiber as it
is twisting. The inherent driving force for twisting will be reflected
by the distance between subsequent twists of 180°, given that
the fiber is drying uniformly on the substrate. This can be used to
estimated the inherent twist rate of the fiber, which will be related
to the twist rate of an isolated fiber. Based on the AFM data, the
interval between twists is related to the cross-sectional area of
the given fiber. The cross section area of the fiber was determined
from the longest and shortest dimensions of the cross section, assuming
elliptical geometry. The inherent twist rate is then found to be proportional
to the inverse of the cross-sectional area, as shown in Figure f, with a measured slope of
14°/nm. This is in agreement with previously reported molecular
dynamics simulations where a similar relationship was observed for
smaller CNFs giving a computed slope of ∼16°/nm.[34] Our observations therefore provide experimental
corroboration of these molecular dynamics simulations. The average
inherent twist rate, as calculated based on subsequent twists, over
all measured fibers was 0.26 ± 0.16°/nm, which is similar
to 0.24 ± 0.09°/nm as determined from the SED data based
on the distance between consecutive appearances of the same orientation
along a CNF after a twist; see the Methods section for more details.The high spatial resolution, ∼5
nm, of our SED measurements
and the 2D raster scan, which is different from earlier sequentially
acquired electron diffraction study studies such as Ogawa,[24] allows us to map out local crystalline ordering
and explore variations in crystallinity transverse to the fiber axis
of cellulose nanofibers. We compare this local crystallinity in tunicate
CNFs and bacterial CNCs, which twist similarly to the CNFs (see Supplementary Figure 7), using VDF imaging, as
shown in Figure . VDF images were formed both by integrating
selected Bragg reflections, to produce diffraction contrast images,
and by integrating between scattering angles of 4–10 mrad,
to produce an annular dark-field scanning TEM image. VDF images formed
from each of the strongest Bragg reflections observed from a tunicate
CNF, Figure a, show
that the corresponding crystalline regions extend uniformly across
the width of the CNF. The CNF therefore comprises approximately a
single crystal transverse to the fiber. The crystalline domains are
slightly narrower than the morphological dimensionality of the CNF
as evidenced by line traces across the CNF (Figure c,d) in VDFs formed using the 200 and 004
reflections and annular masks. In contrast, VDF images formed using
the strongest Bragg reflections recorded from a bacterial CNC, Figure b, show more fragmented
bright regions, also observed in the line traces in Figure e,f. This indicates the crystals
in the CNCs are not as uniform in microstructure and that the CNCs
are composed of smaller discrete entities, in slightly different orientations,
which together form the strongly anisotropic ribbon-like morphology.
Although thinner in morphology, the crystalline domains in the tunicate
CNFs are wider than the corresponding domains of the bacterial CNCs.
This corresponds well with crystal sizes determined from PXRD data
using the Scherrer equation, which yields crystalline domains in tunicate
CNFs of 7.3–9.5 nm, depending on direction, and crystalline
domains in bacterial CNCs of 5.2–5.7 nm. These observations
are also in agreement with earlier findings.[35,36]Revealing
crystallinity transverse to the fiber axis using SED.
VDF images generated using the SED data obtained from (a) tunicate
CNFs and (b) CNCs of bacterial origin. Annular VDF images show the
overall morphology of the CNF/CNC. VDF images generated by integrating
windows containing selected key reflections show the domains of given
orientations. (c–f) Line traces across the CNF/CNC, comparing
the same domains of the annular (orange) and reflection (blue) VDF
maps. The tunicate CNFs have an approximately uniform crystallinity
extending over the cross section of the fiber as seen in (c) and (d),
whereas the CNCs of bacterial origin exhibit fragmented domains as
shown by the split in the blue traces in (e) and (f). The line trace
from the annular map of the tunicate CNFs shows a slightly wider profile
compared to the line trace from 004 and 200 reflections indicating
that the CNF is not crystalline through its entire width. The Bragg
reflections are indexed with respect to the Iβ and Iα
cellulose crystal structures for tunicate and bacterial cellulose,
respectively.
Conclusions
SED analysis has revealed
crystalline ordering within twisting
cellulose nanofibers. The polysaccharide chains of tunicate CNFs were
found to be packed in the Iβ cellulose crystal structure and
to remain well ordered as the cellulose fiber twists through 180°
about its long axis. The SED data also shows that the fibers extracted
from a tunicate show crystallinity throughout the cross section of
the fiber with a homogeneous crystal orientation. CNCs of bacterial
origin however possess a more complex microstructure where smaller
domains of different orientations are present. Our AFM study reveals
that the twist rate is inversely proportional to the cross-sectional
area of the fiber. We have shown that this is true for both the inherent
twist as well as the local twist rate after the CNF is dried onto
a substrate. The relationship between the twist rate and the cross-sectional
area of the fibers has now been shown experimentally and is consistent
with earlier reported results from modeling. These results are a demonstration
of the mechanical robustness of cellulose crystallites. The twisting
structure is localized yet still ordered at the level of molecular
packing as revealed by SED analysis. This shows that cellulose nanofibers
can preserve crystalline molecular stacking even after being significantly
twisted. It is anticipated that SED will become an important tool
for revealing fine details of the molecular ordering within the microstructure
of single cellulose fibrils and other crystalline biopolymers.
Methods
Preparation of CNFs and
CNCs
Tunicate CNFs were prepared
from a purified mantle of Halocynthia roretzi via a 4-acetamido-TEMPO/NaClO/NaClO2 oxidation reaction,
according to a previously reported protocol.[33] The pH value and temperature of the reaction medium were maintained
at approximately 5 and 40 °C, respectively. After 3 days, the
oxidized mantle was purified with distilled water and suspended in
water at a solid consistency of 0.05% w/w. The suspension (200 mL)
was mechanically treated using a Microtec Physcotron NS-56 double-cylinder-type
homogenizer at 7500 rpm for 8 min and then sonicated with a Nissei
US-300T ultrasonic homogenizer (300 W, 19.5 kHz) at 70% output for
1 min. The CNFs were separated as stably dispersed particles in the
supernatant by centrifugation of the sonicated suspension. A PXRD
pattern from the tunicate CNFs is shown in Supplementary Figure 3.Bacterial CNCs were prepared from commercially
available coconut gel cubes (Chaokoh, Thailand), known as nata de
coco. The coconut cubes were first soaked in deionized water to remove
sugar and other additives and then stirred in 0.1 M sodium hydroxide
solution for 48 h and rinsed until neutral. Purified coconut cubes
(100 g) were hydrolyzed by 40 w% sulfuric acid solution at 80 °C
for 4 h. The reaction was quenched by water dilution of 10 times,
and the slurry was collected by centrifugation and dialyzed for 3
days against deionized water using dialysis bags (cutoff weight of
14 000 Da). Finally, the suspension was probe sonicated for
10 min (output power of 60%, Q2000, Qsonica), followed by centrifugation
for 30 min at 8000 rpm (removing titanium particles). A PXRD pattern
from the bacterial CNCs is shown in Supplementary Figure 4.
AFM Measurements
To prepare samples
for AFM, the CNF
dispersion was diluted to 0.001% w/w, dropped onto a freshly cleaved
mica plate, and dried in a desiccator at ambient pressure. The AFM
measurements were performed using a Bruker MultiMode 8 microscope
equipped with a NanoScope V controller and a ScanAsyst-Air probe with
a low spring constant of 0.4 N/m and a tip diameter of 2 nm. This
instrument was operated in PeakForce Tapping mode with monitoring
to ensure that the repulsion time was ∼10%. The tapping step
was set at ∼2 nm with 1024 × 1024 pixels covering ∼2-μm-wide
squares. The microscope was covered with an acoustic hood during the
observation to minimize vibrational noise.
AFM Data Analysis
The heights of all the CNFs in the
AFM images were extracted by automated image processing, as shown
in Supplementary Figure 5, performed using
the scikit-image and OpenCV Python 3.6.3 libraries. The images were
first binarized to separate the CNFs from the background, and locally
adaptive thresholding was applied to the regions above 0.5 nm. Noise
and contaminations were then removed from the binarized images using
a line detection algorithm, as follows. A probabilistic Hough transform
was applied to each connected component after Canny edge detection,
and the component was treated as noise if the ratio of the detected
lines to the Canny edges was less than 0.35. The center lines of each
CNF were then extracted using a skeletonization algorithm giving 1-pixel-wide
center lines that were expanded to 3-pixel-wide center lines by dilation.
Histograms of height obtained from the binarized regions, the 1-pixel-wide
center lines, and the 3-pixel-wide center lines are shown in Supplementary Figure 5. The height distribution
remained unchanged after dilation of the center lines, indicating
that the detected center lines were close to the ridge lines of the
CNFs. The histogram obtained from the 3-pixel-wide center lines was
further analyzed by curve fitting with a Gaussian function.The analysis of twisting parts was carried out for the isolated fibers
in the AFM images. The center of each CNF was tracked manually by
using ImageJ version 1.52 a. Several values were calculated from a
height profile (Supplementary Figure 5),
where the twisting parts appeared as distinct bumps. The twisting
height and interval of the twisting were measured at peak maxima.
A linear background was applied for each peak range, and the width
was calculated at 10% peak height from the background. The height
of the untwisted region was calculated as the average of the height
profile excluding peak regions.
SED Experiments
The dispersion of CNF/CNC was diluted
to a concentration of 0.001% w/w. The ultrathin continuous carbon
film covered TEM grids (Electron Microscopy Sciences) were initially
glow discharged before a droplet of the dispersion was applied to
the grid. The grid was left for 1 min before the remaining dispersion
was blotted away and the grid was dried at ambient conditions. SED
data were acquired using a JEOL ARM300CF fitted with an ultrahigh-resolution
pole piece, a cold-field emission gun, and aberration correctors in
both the probe-forming and image-forming optics (Diamond Light Source,
UK). The instrument was operated at 300 kV in a nanobeam configuration
obtained by switching off the aberration corrector in the probe-forming
optics and using a 10 μm condenser aperture to obtain a convergence
semiangle of ∼0.6 mrad and a diffraction-limited probe diameter
of ∼5 nm. The probe current was measured using a Faraday cup
as ∼2.3 pA, and the exposure time was 1 ms per probe position.
The estimated electron fluence, assuming a disk-like probe, was ∼6
e–/Å2. A diffraction pattern was
acquired at every probe position using a Merlin-Medipix hybrid counting-type
direct electron detector (Quantum Detectors, UK). SED was obtained
in a “blind scanning” point-and-shoot workflow to minimize
the total electron fluence the specimen received.Postprocessing
and visualization of the SED data was performed using the open-source
Python library Pyxem 0.10.0.[37] The postprocessing
of the SED data involved alignment of the diffraction patterns using
a cross-correlation algorithm applied to the direct beam and the creation
of VDF images based on an annular mask to integrated selected regions
of the detector plane, containing particular Bragg reflections, as
a function of probe position. The calculations of the local twist
rate were based on the known geometry of the cellulose crystal structure
and the distance along the fiber separating the given crystallographic
orientations. The local twist rates between [010] ^ [110] and [110]
^ [11̅0] orientations were calculated to be 0.65 and 0.63°/nm,
respectively, with standard deviations of 0.18 and 0.14°/nm.
The calculations were based on 21 and 12 measurements, respectively.
The inherent twist rate was determined by measuring the distance between
consecutive appearances of the same crystallographic orientation along
a CNF after undertaking a twist of 180°. The estimate of the
inherent twist rate of 0.24°/nm was calculated by relating the
distance to the 180° twist to obtain an estimate of the inherent
twist rate of the CNF after dried onto the carbon substrate.
Authors: Tiarnan A S Doherty; Andrew J Winchester; Stuart Macpherson; Duncan N Johnstone; Vivek Pareek; Elizabeth M Tennyson; Sofiia Kosar; Felix U Kosasih; Miguel Anaya; Mojtaba Abdi-Jalebi; Zahra Andaji-Garmaroudi; E Laine Wong; Julien Madéo; Yu-Hsien Chiang; Ji-Sang Park; Young-Kwang Jung; Christopher E Petoukhoff; Giorgio Divitini; Michael K L Man; Caterina Ducati; Aron Walsh; Paul A Midgley; Keshav M Dani; Samuel D Stranks Journal: Nature Date: 2020-04-15 Impact factor: 49.962
Authors: Blaise L Tardy; Bruno D Mattos; Caio G Otoni; Marco Beaumont; Johanna Majoinen; Tero Kämäräinen; Orlando J Rojas Journal: Chem Rev Date: 2021-08-20 Impact factor: 72.087
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