Martin Felhofer1, Peter Bock1, Adya Singh1, Batirtze Prats-Mateu2, Ronald Zirbs3, Notburga Gierlinger1. 1. Institute for Biophysics, Department of Nanobiotechnology (DNBT), University of Natural Resources and Life (BOKU) Sciences, Vienna, Muthgasse 11/II, 1190 Vienna, Austria. 2. Institute of Science and Technology Austria, Am Campus 1, 3400 Klosterneuburg, Austria. 3. Institute for Biologically Inspired Materials, Department of Nanobiotechnology (DNBT), University of Natural Resources and Life Sciences, Vienna, Muthgasse 11/II, 1190 Vienna, Austria.
Abstract
Wood, as the most abundant carbon dioxide storing bioresource, is currently driven beyond its traditional use through creative innovations and nanotechnology. For many properties the micro- and nanostructure plays a crucial role and one key challenge is control and detection of chemical and physical processes in the confined microstructure and nanopores of the wooden cell wall. In this study, correlative Raman and atomic force microscopy show high potential for tracking in situ molecular rearrangement of wood polymers during compression. More water molecules (interpreted as wider cellulose microfibril distances) and disentangling of hemicellulose chains are detected in the opened cell wall regions, whereas an increase of lignin is revealed in the compressed areas. These results support a new more "loose" cell wall model based on flexible lignin nanodomains and advance our knowledge of the molecular reorganization during deformation of wood for optimized processing and utilization.
Wood, as the most abundant carbon dioxide storing bioresource, is currently driven beyond its traditional use through creative innovations and nanotechnology. For many properties the micro- and nanostructure plays a crucial role and one key challenge is control and detection of chemical and physical processes in the confined microstructure and nanopores of the wooden cell wall. In this study, correlative Raman and atomic force microscopy show high potential for tracking in situ molecular rearrangement of wood polymers during compression. More water molecules (interpreted as wider cellulose microfibril distances) and disentangling of hemicellulose chains are detected in the opened cell wall regions, whereas an increase of lignin is revealed in the compressed areas. These results support a new more "loose" cell wall model based on flexible lignin nanodomains and advance our knowledge of the molecular reorganization during deformation of wood for optimized processing and utilization.
With increasing focus on growing
global bioeconomy, the production technologies for sustainable wooden
materials are rapidly advancing and include high-performance structural
and multifunctional smart materials.[1−10] The strength of engineered wood was increased 8 times by delignification
and re-pressing,[11] and furthermore cooling
properties were reported.[12] Besides these
high performance multifunctional wooden materials, also new avenues
were opened by fabricating 3D shapes with tunable fiber architecture[2] and by curved mass timber structures through
hygroscopic self-shaping.[4] Most of these
advanced wood modifications use the unique hierarchical structure
of wood as a scaffold to carry heavy loads. For the performance as
well as for the functionalization and modification of wood, the microstructure
(tissue and cell properties) plays a crucial role as well as the cellulose
fibril network with matrix polymers (hemicellulose, lignin) and pores
(water) on the nanoscale.Thus, one key challenge in the emerging
field of advanced wood
functionalization is to improve nanostructural control of chemical
and physical processes in the confined pore space of the cell wall
and microstructure.[13] Of utmost importance
are therefore methods probing in situ the structure,
chemistry, and mechanics of the plant cell wall on the micro- and
nanoscale. Among the label-free cell wall imaging techniques, atomic
force microscopy (AFM) and confocal Raman microscopy have proven powerful
to track topography and mechanics on the nanolevel and chemistry in
context with the microstructure, respectively.[14−17] Although the two techniques are
complementary in terms of length scale (micro to nanoscale) and investigated
features, correlative applications are rare as they are difficult
to perform on plant cell walls.[18] Furthermore,
both methods are nondestructive and enable us to watch the plant cell
walls in situ, e.g., in the stretched state[19] or enzymatically[20] or thermochemically[21] treated. Here we
study for the first time the plant cell walls on the submicron and
molecular levels while compressing the wood, as densification/compression
is a key step in the production of many high potential and innovative
wood-based materials.Due to the honeycomb-like structure of
wood, tight densification
is possible and leads in a radial direction to buckling of the thin-walled
earlywood cells (Figure a). Following one single wood cell during deformation shows compressed
cell wall regions together with opened (from curved to straight) cell
wall regions adjacent to cell corners (Supporting Figure 1). Under the Raman microscope these cells reveal heterogeneous
uptake of water molecules within the cell wall (Figure b). In the opened cell wall regions a higher
water content (Figure b, light blue, arrow) is visualized compared to the compressed area
(Figure b, dark regions,
arrowhead). The lower water content in the compressed area goes hand
in hand with cell wall curvature (Supporting Note 1 and Supporting Figure 1 and 2)
and the high intensity of CH-stretching, confirming a denser arrangement
of cell wall polymers (Figure c, dark red regions). Integrating the cellulose peak at 380
cm–1 shows a very similar picture with high intensity
in the compressed region (Figure d), whereas 1600 cm–1 integration
of aromatic components shows the highest intensity between the cells
(red cell corner and middle lamella) in normal and compressed wood
(Figure e). The higher
intensity of the cellulose band in the compressed cell wall areas
(Figure d) points
to a denser arrangement of cellulose microfibrils (Figure d). The visualized molecular
differences between normal, compressed, and opened areas (Figure b–d) are clearly
confirmed in the three extracted Raman spectra, especially in the
OH-stretching region (Figure f). The spectrum extracted from the opened area (Figure f, blue line) showed
the highest OH stretching band, followed by the spectrum extracted
from a “normal” cell wall (Figure f, black) and the smallest band in the compressed
area (Figure f, orange
spectrum). The vice versa picture of low cellulose signal (Figure d) versus high water
signal (Figure b)
is assumed to be due to a change in the distance between microfibrils
and the water between these, respectively. These distance changes
between microfibrils are quantified on the basis of the equation developed
to determine the cellulose nanocrystal separation based on water content.[22] We rearranged this equation (Supporting Note 2) and assumed that the cell wall of the normal
(unaltered) areas is completely saturated (as measured in water).
On the basis of the OH integral values (Figure f) the average water content was calculated
for the compressed and opened region (Supporting Note 3). With a maximal distance (Dmax) of 4.2 nm for a fully saturated cell wall and the minimum distance
(Dmin) of 3.5 nm for completely dry wood,[22] the compressed microfibril distance is 4.04
nm and widens up to 4.68 nm in the opened region (Figure g).
Figure 1
Raman imaging reveals
changes in water content and cellulose compactness
between opened and compressed cell wall areas. (a) Transverse face
of the block viewed with SEM including nomenclature of wood. Early
wood (EW) is highly buckled, but not the late wood (LW). (b)–(e)
Raman images comparing unaltered LW cell walls with compressed EW
cell walls. (b) OH integration reveals heterogeneous water distribution
in EW cell walls whereas LW cells show uniform lower level water content.
(c) The integration of the CH peak depicts denser regions in the cell
wall with the highest curvature (dark red). (d) Raman images based
on the cellulose peak 380 cm–1 show a heterogeneous
pattern. (e) Compressed EW cells show greater lignin concentration
in the middle lamella of compressed cell wall regions. Images are
based on the integral range for lignin (1557–1696 cm–1). (f) Average spectra of normal, opened, and compressed cell wall
areas (see dashed lines in (b) bottom). (g) Distance (D) change between cellulose microfibrils based on eq 1 in Bertinetti
et al.[22] (Supporting Note 2) for compressed, normal, and opened areas and schematic
representation (sketch inspired by Bertinetti et al.[22]).
Raman imaging reveals
changes in water content and cellulose compactness
between opened and compressed cell wall areas. (a) Transverse face
of the block viewed with SEM including nomenclature of wood. Early
wood (EW) is highly buckled, but not the late wood (LW). (b)–(e)
Raman images comparing unaltered LW cell walls with compressed EW
cell walls. (b) OH integration reveals heterogeneous water distribution
in EW cell walls whereas LW cells show uniform lower level water content.
(c) The integration of the CH peak depicts denser regions in the cell
wall with the highest curvature (dark red). (d) Raman images based
on the cellulose peak 380 cm–1 show a heterogeneous
pattern. (e) Compressed EW cells show greater lignin concentration
in the middle lamella of compressed cell wall regions. Images are
based on the integral range for lignin (1557–1696 cm–1). (f) Average spectra of normal, opened, and compressed cell wall
areas (see dashed lines in (b) bottom). (g) Distance (D) change between cellulose microfibrils based on eq 1 in Bertinetti
et al.[22] (Supporting Note 2) for compressed, normal, and opened areas and schematic
representation (sketch inspired by Bertinetti et al.[22]).A closer look at the Raman images
revealed that lignin in the middle
lamella has a higher intensity in the compressed cell wall regions
(Figure e and Figure a, arrows) compared
to other cell wall regions and unaltered latewood (Figure e and Figure a, arrowhead). The middle lamella seems to
get thicker, and the lignin intensity profile across the “normal”
and compressed cell wall confirms the lignin increase in the middle
lamella and in the compressed cell wall (Figure b). Thus, the question raises: Is lignin
“flowing” when compressing the wood sample? Water-saturated
lignin in cell walls undergoes a glass transition at around 70–100
°C.[23] But there is so far no report
that lignin movement (displacement) in the cell wall can also occur
at ambient temperature when subjected to pressure or mechanical forces,
such as compression. Besides our Raman evidence, also TEM images show
intensely stained lignin patches and streaks for cell walls compressed
at ambient temperature (Figure c). Similar patches have been reported in wood samples at
higher temperatures during pulping,[24] whereas
the normal cell wall area shows uniform lignin distribution (Figure d). In a recent NMR
study it was suggested that lignin/hemicellulose interactions are
much weaker[25] than has been previously
suggested. This implies that lignin can migrate within the cell wall
under mechanical load, as now evidenced by our Raman and TEM experiments
(Figure ).
Figure 2
Compressed
cell wall areas show a higher lignin content. (a) Raman
image shows greater lignin concentration in the middle lamella of
compressed cell wall regions (arrow) as compared to normal and widened
regions (arrowhead). (b) The dashed line drawn across compressed and
normal cell wall regions (in panel a) shows the lignin intensity profile.
Note that the middle lamella in the compressed cell wall region (CW)
has distinctly higher intensity for lignin as well as the inner compressed
cell wall. (c) TEM images of compressed and (d) normal cell walls.
Arrowheads indicate areas of high lignin concentration.
Compressed
cell wall areas show a higher lignin content. (a) Raman
image shows greater lignin concentration in the middle lamella of
compressed cell wall regions (arrow) as compared to normal and widened
regions (arrowhead). (b) The dashed line drawn across compressed and
normal cell wall regions (in panel a) shows the lignin intensity profile.
Note that the middle lamella in the compressed cell wall region (CW)
has distinctly higher intensity for lignin as well as the inner compressed
cell wall. (c) TEM images of compressed and (d) normal cell walls.
Arrowheads indicate areas of high lignin concentration.To gain additionally insights into the organization and mechanical
properties on the nanolevel, we aimed at correlative Raman/AFM microscopy.[18] To probe exactly the same sample and cell wall
area during compression, a sample holder was designed and 3D-printed
(Figure a). While
Raman imaging gives an overview on the distribution of the molecules
on the microscale (Figure b), AFM provides a zoom into the nanostructure (Figure c,d). The scanned areas (Figure b; see insets I–VI
on the lignin image), include normal to opened areas (I, II, III,
IV) as well as compressed (V, VI) regions, which is confirmed by differences
in cellulose density and water content (Figure b). AFM topography images visualize the middle
lamella and cell corner and show a rather flat surface within the
secondary cell wall after microtome cutting (Figure c). A zoom into the S2 layer, however, reveals
the lamellar arrangement of the S2 layer with differences in height
profiles (Figure d,
full width of half-maxima (fwhm) 66 and 35 nm for opened (IVd) and
compressed area (VId), respectively). So far, AFM has been mainly
applied on embedded wood samples, and besides the lamellar structure,
also cellulose aggregate sizes and pore and matrix lamella width have
been determined after chemical and mechanical processing.[26,27] Recently, a new AFM protocol was introduced on native wood samples
to distinguish the CML, S1, and S2 based on their Young’s moduli
and a stiffness gradient in the transition zone S12, but
nanoscale details like the lamellar structure could not be detected.[15]
Figure 3
Correlative Raman/AFM measurements of compressed early
wood of
cell wall regions show microchemical and nanostructural differences.
(a) Correlative approach to acquire different images exactly from
the same sample positions of a wood sample compressed in a 3D printed
device. The confocal Raman images visualize the chemistry in context
with microstructure by acquiring the inelastic backscattering of laser
light, whereas the AFM tip reaches the sample from above, providing
a three-dimensional topographical view at nano resolution. (b) Raman
images based on CH-stretching of all organic components (2774–3033
cm–1), aromatic components (1557–1696 cm–1), and components representing lignin and cellulose
(342–402 cm–1) reveal the compactness of
the compressed inner cell wall. (c) Different AFM topographical images
showing differences between outer (opened) and inner (compact) cell
walls. (d) Height profiles of the opened and compressed secondary
cell wall with calculated full width at half-maximum (fwhm).
Correlative Raman/AFM measurements of compressed early
wood of
cell wall regions show microchemical and nanostructural differences.
(a) Correlative approach to acquire different images exactly from
the same sample positions of a wood sample compressed in a 3D printed
device. The confocal Raman images visualize the chemistry in context
with microstructure by acquiring the inelastic backscattering of laser
light, whereas the AFM tip reaches the sample from above, providing
a three-dimensional topographical view at nano resolution. (b) Raman
images based on CH-stretching of all organic components (2774–3033
cm–1), aromatic components (1557–1696 cm–1), and components representing lignin and cellulose
(342–402 cm–1) reveal the compactness of
the compressed inner cell wall. (c) Different AFM topographical images
showing differences between outer (opened) and inner (compact) cell
walls. (d) Height profiles of the opened and compressed secondary
cell wall with calculated full width at half-maximum (fwhm).In this study, we also worked on native, non-embedded
wood samples
and focused on nanomechanics by acquiring a force–distance
curve at every pixel using the digital pulsed force mode (DPFM). Including
the opened and compressed region of the cell walls (Figure a insets) made it possible
to track changes in the nanoarchitecture of the altered wood cell
walls. The different wood polymers making up the wooden cell walls,
lignin, cellulose, and hemicellulose (Hemis) (Figure b), have different mechanical and surface
properties. Crystalline cellulose has a Young’s modulus of
about 130 GPa, whereas lignin has a modulus of roughly 3 GPa.[28] These differences are reflected in changes of
the acquired force–distance curves (Figure c). The adhesion force between tip and the
wood cell wall depends on chemical components interacting with the
tip. As the silicon tip (o.d. 10 nm) used in this work has a preference
for hydrophilic materials such as polysaccharides, it is possible
to distinguish between the hydrophilic polysaccharides and hydrophobic
lignin on the basis of AFM adhesion images (Figure d–f). In the most widened outer cell
wall region, nanodomains and pores (arrowhead) appear more elongated
and in-line with the lamella (Figure d, Supporting Figure 3a–c), compared to the less widened (Figure e) and more compact arrangement in the compressed
region (Figure f).
The corresponding histograms of the adhesion values show three to
four peaks in all three regions but differ in size and shape (Figure d–f, second
column). These peaks seem to reflect the cell wall components and
may come from greater accessibility of the probe tip to opened functional
groups and conformational changes during compression and widening.
The relative peak area of the four peaks in the normal or less stretched
region coincides with the composition of the wooden cell wall,[28] with 42% cellulose, 29% lignin, and 29% hemicellulose
(Figure e, second
column). For softwood, two different hemicelluloses are reported,
glucomannan and xylan, where the xylan is in 2-fold and 3-fold configuration,[25,29] which might be reflected in the two peaks with high adhesion values.
Extracting the adhesion values only from the cell corner region results
in only one peak with low adhesion values (Supporting Figure 3d–f), confirming the lignin classification for
the low adhesion values as the cell corner was shown to have high
lignin content (Figure b). Plotting the distribution of the classified cell wall polymers
reveals nanodomains of the three wood polymers (Figure d–f, third column). In the compressed
state (Figure f),
the proportion of low adhesion values are attributed to lignin increases,
whereas in the more opened state, higher accessibility to hemicelluloses
is observed (Figure d, yellow, sharp, and narrow hemicellulose peak). These changes are
likely facilitated by conformational changes of hemicelluloses, interpreted
as hemicellulose uncoiling into a more linear configuration,[25] as shown in the model (Figure d–f, fourth column). Hemicellulose
conformational changes due to shear forces were already proposed in
previous studies.[25,30] The “Velcro behavior”
of the wood cells is explained by hemicelluloses entangling and disentangling
with the rest of the matrix.[31] On the basis
of adhesion force maps, we reveal for the first time intra-cell wall
rearrangement of wood components on the nanolevel caused by mechanical
deformation.
Figure 4
AFM adhesion values of compressed wood reveal nanodomains
of plant
cell wall polymers and their rearrangement in compressed and opened
regions. (a) Bright field image with insets showing the areas scanned
with AFM. (b) Schematics of AFM tip interaction with the wood polymer
nanodomains within the cell wall (sketch inspired by Mandriota et
al.[32]). (c) Force–distance curves
representative for different cell wall components (extracted from
area 3). (d)–(f) AFM adhesion images (first row) show different
arrangements of nanodomains in highly opened (d, inset A), normal
to opened (e, inset B), and compressed cell wall regions (f, inset
C). Displaying the adhesion values as histograms results in three
to four peaks representing the cell wall polymers (second row). Merged
images of the different cell wall components created by extracting
the pixels under the fitted curves for each component (with standard
error) (third row) give their distribution, and cell wall models (inspired
by Kang et al.[25]) show the relationship
and arrangement of the different cell wall components, including uncoiling
of the hemicellulose (fourth row). Note: The histograms in (d) and
(e) show sharp and well differentiated peaks due to better accessibility
in the normal to opened state. Especially in (d), unfolding of hemicelluloses
due to cell wall widening causes changes in adhesion values leading
to a narrowing of the hemicellulose peak and broadening of the cellulose
peak.
AFM adhesion values of compressed wood reveal nanodomains
of plant
cell wall polymers and their rearrangement in compressed and opened
regions. (a) Bright field image with insets showing the areas scanned
with AFM. (b) Schematics of AFM tip interaction with the wood polymer
nanodomains within the cell wall (sketch inspired by Mandriota et
al.[32]). (c) Force–distance curves
representative for different cell wall components (extracted from
area 3). (d)–(f) AFM adhesion images (first row) show different
arrangements of nanodomains in highly opened (d, inset A), normal
to opened (e, inset B), and compressed cell wall regions (f, inset
C). Displaying the adhesion values as histograms results in three
to four peaks representing the cell wall polymers (second row). Merged
images of the different cell wall components created by extracting
the pixels under the fitted curves for each component (with standard
error) (third row) give their distribution, and cell wall models (inspired
by Kang et al.[25]) show the relationship
and arrangement of the different cell wall components, including uncoiling
of the hemicellulose (fourth row). Note: The histograms in (d) and
(e) show sharp and well differentiated peaks due to better accessibility
in the normal to opened state. Especially in (d), unfolding of hemicelluloses
due to cell wall widening causes changes in adhesion values leading
to a narrowing of the hemicellulose peak and broadening of the cellulose
peak.Besides, also stiffness and Young’s
modulus behavior of
the outer and inner cell wall was calculated from the slope of the
repulsive force signal after the tip snapped in (Figure c). The Young’s modulus
in the compressed inner cell wall is higher than that in the opened
outer cell wall (Supporting Figure 4a–c), and it is in the range of values based on AFM indentation.[33] These results support the finding on the rearrangement
of the cell wall polymers and water in densified wood: a stiffer compressed
region is explained with denser microfibrils and accumulation of lignin,
while the outer opened part is more porous and/or water filled with
hemicellulose being disentangled.Altogether, the results based
on correlative CRM and AFM of the
same cell wall regions provide evidence that cell wall compression
causes molecular level changes at ambient temperature, such as lignin
and water redistribution and conformational changes of hemicellulose.
The generally accepted concept of lignin–hemicellulose interaction
in the cell wall is that these cell wall components interact by forming
covalent linkages.[34] However, according
to a recently proposed cell wall model[25] lignin interacts with hemicelluloses via electrostatic interactions
and occurs in its own nanodomains within the cell wall architecture.
This supports our finding that lignin can relocate within the cell
wall and the weaker electrostatic bonds can be broken if the cell
wall is locally stressed. We suggest that the extreme force generated
during mechanical compression of cell walls causes lignin to detach
from hemicelluloses and locally migrate within the cell wall. The
new fundamental knowledge of molecular behavior is useful in transformation
of wood for smart material applications.
Authors: Philippe Grönquist; Dylan Wood; Mohammad M Hassani; Falk K Wittel; Achim Menges; Markus Rüggeberg Journal: Sci Adv Date: 2019-09-13 Impact factor: 14.136