ORI GIN AL

A comparison of nanoindentation cell wall hardnessand Brinell wood hardness in jack pine(Pinus banksiana Lamb.)

Manon Vincent • Queju Tong • Nasko Terziev •

Geoffrey Daniel • Cecilia Bustos •

William Gacitua Escobar • Isabelle Duchesne

Received: 1 November 2012

� Her Majesty the Queen in Right of Canada as represented by the Service Canadiens des Forets 2013

Abstract Nanoindentation is a powerful tool for hardness testing on a very small

scale. Since the technique was first introduced for studying wood cell wall

mechanics, it has been integrated as an important tool for measuring the modulus of

elasticity and hardness of wood cell walls. In this study, hardness measured with

nanoindentation (nanohardness) was compared with hardness measured by the

standard Brinell test method (Brinell hardness) on jack pine (Pinus banksiana

Lamb.) wood. Nanoindentation was performed on both the S2 layer of the sec-

ondary cell wall and the middle lamella (ML) of early- and latewood fibers. Four

annual growth rings were studied. The influence of growth ring and initial spacing

on both measurements was analyzed. The relationship between Brinell hardness,

nanoindentation measurements, and average ring density was also studied. Results

suggest that Brinell- and nanohardness are controlled by different mechanisms and

factors. The location of nanohardness measurements (i.e., S2 layer or ML) also

M. Vincent (&)

Departement des sciences du bois et de la foret, Universite Laval,

Pavillon Gene-H.-Kruger, Quebec, QC G1K 7P4, Canada

e-mail: manon_vincent@uqac.ca

Q. Tong

Pulp, Paper and BioProducts, FPInnovations, Quebec, Canada

N. Terziev � G. Daniel

Department of Forest Products, Swedish University of Agricultural Sciences (SLU),

Uppsala, Sweden

C. Bustos � W. G. Escobar

Departamento de Ingenierıa en Maderas, Biomaterials and Nanotechnology Center (CBN),

Universidad del Bıo-Bıo, Concepcion, Chile

I. Duchesne

Natural Resources Canada, Canadian Forest Service, Canadian Wood Fibre Centre, Quebec,

QC G1V 4C7, Canada

123

Wood Sci Technol

DOI 10.1007/s00226-013-0580-5

influenced hardness differently. It was concluded that nanomeasurements are not an

exact representation of wood mechanical properties conducted at the macro level

because of the hierarchical structure of wood. The effect of other factors such as

moisture or wood extractive content may also need consideration.

Introduction

The wide range of wood products from construction materials to pulp and paper

products through wood–plastic composites requires an exhaustive understanding of

the wood properties at different scales (Jozsa and Middleton 1997). Recently, the

increased use of mathematical models in the applied and fundamental sciences

associated with high computational capability has led to an increasing need for

multi-scale modeling approach (Weinan and Engquist 2003). These new tools

should provide a better understanding of wood behavior resulting from the high

heterogeneity of wood components. In this respect, the development of new

technologies such as nanometer and micrometer technologies has brought new life

into studies of wood fiber properties (Yan 2001). Nanoindentation, an indentation

test at a very small scale, was first introduced for examination of wood cell wall

mechanics by Wimmer and Lucas (1997). Since then, several authors have used

this method not only to analyze the mechanical properties of wood cell walls

(Wimmer and Lucas 1997; Gindl and Gupta 2002; Tze et al. 2007), but also to

characterize the adhesive bond effect on cell wall properties in a defined area

(Konnerth and Gindl 2006) or to examine the effects of forest management

practices on wood micro-scale properties (Duchesne et al. 2011). The effects of

silviculture and site characteristics on wood properties, interpreted through their

effect on tree growth, are for example well documented (e.g., Jozsa and Middleton

1997; Debell et al. 2004; Kang et al. 2004; Makinen et al. 2005; Schneider et al.

2008; Auty 2011). As outlined above, wood property variations with growth rate

can be studied from different points of view as well as different scales, for

example differences in the type of wood produced—juvenile/mature wood

proportions (Zobel and Sprague 1998), heartwood/sapwood proportions (Yang

and Hazenberg 1992; Morling and Valinger 1999) or early-/latewood ratios, and

cell wall characteristics (microfibril angle, cellulose, and lignin content) (Lind-

strom et al. 1998; Koga and Zhang 2002; Jungnikl et al. 2008). It is hypothesized

that any change observed at the smallest scale should reflect to some extent a

change of wood properties at a larger level. In this study, the authors focused on

the estimation of cell wall hardness measured by nanoindentation and compared it

with hardness measured by macroindentation (specifically Brinell hardness) for

different growth rates of jack pine.

Previous nanoindentation studies have been conducted according to the

isotropic theory developed by Oliver and Pharr (1992) to determine the reduced

modulus of elasticity (MOEr) and hardness. This theory makes possible

determination of the MOEr of wood samples from initial elastic unloading.

However, this MOEr is lower than the expected longitudinal modulus (obtained

from single fiber tensile tests or model calculations), and concerns have been

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raised about the theory (Gindl and Schoberl 2004; Jager et al. 2011). Jager et al.

(2011) therefore developed a model according to anisotropic indentation theory to

determine MOEr. This model appears promising since it includes additional

variables such as microfibril angle and elastic properties of cell walls. The

relationship between nano- and macro-indentation was also studied to understand

the mechanism of wood property modification at the microscopic level using

chemical treatments (Frihart et al. 2008; Moon et al. 2009; Konnerth et al. 2010).

Other studies explored correlations or the variations of the changes observed

between the measured hardness of the cell wall layer and the hardness of bulk

wood (Holmberg 2000; Gindl et al. 2004; Tze et al. 2007). To the authors’

knowledge, however, few studies have directly addressed the relationship between

the cell wall hardness measured using a nanoindenter and wood hardness measured

according to the standard method (Brinell hardness), specifically related to the

growth rate variations (Moon et al. 2006, 2009).

The aim of the study is to determine whether the changes that occurred with

growth rate variation that are noticeable with Brinell hardness partly result from

changes that occurred at smaller scale, or whether the correlation between

nanohardness (measured in cell wall constituent) and macro-hardness would vary

depending on growth rate, due to different changes occurring at different scale.

Materials and methods

Tree selection and sample preparation

This study was based on a 32-year-old Nelder spacing plot (Nelder 1962)

established in 1977 near Woodstock, New Brunswick, Canada. Half of the plot was

composed of jack pine (Pinus banksiana Lamb.), and the other half of the plot was

composed of white spruce (Picea glauca (Moench) Voss). Trees were planted at the

intersection of the radial lines and circular arches at an increasing spacing from

0.87 m 9 0.91 m (the innermost circular arc) to 3.5 m 9 3.66 m (the outermost

circular arc) (stand density from 12,600 to 780 trees/ha, respectively). A detailed

description of this Nelder plot and tree sampling can be found in Tong et al. (2013).

In this study, three initial spacings (IS) were selected, representing a common

practice spacing (2.2 m 9 2.3 m), narrow spacing (1.38 m 9 1.45 m), and

extremely wide spacing (3.5 m 9 3.65 m). In this study, ‘‘spacing’’ or ‘‘initial

spacing’’ refers to distance between trees, which determines stand density, i.e., the

number of tree per unit area. Two jack pine (JP) trees from each spacing were

sampled for nanoindentation experiments (Fig. 1) in 2009. For each tree, diameter

at breast height (dbh), tree height (H), and width and length of the living crown were

recorded (Table 1).

A 5-cm-thick disk was cut at stump height of each tree. From each disk, a

25-mm-wide (tangentially) slice was extracted from pith to bark in the northern

direction (Fig. 2). Each slice was sawn into three strips transversely. The top strip

was used for nanoindentation, the middle strip for macroindentation to measure

Brinell hardness, and the bottom strip for X-ray densitometry to obtain growth ring

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density. The strips were then dried in a conditioning chamber for 7 days under slight

vacuum at 25 �C for 24 h and then with a gradual increase in temperature to 60 �C

to avoid drying defects.

White spruceJack pine

White spruceJack pine

Fig. 1 Nelder plot design andlocation of sample trees (Nelder1962). Trees are planted at theintersections of radial lines andcircular arches. Filled dotsrepresent the locations of sampletrees

Table 1 Summary statistics of sample jack pine trees by spacing

# row Spacing

(m 9 m)

Number

of trees

Mean dbh

(cm)

Mean

H (m)

Mean diameter

of live crown (m)

Mean length

of live crown (m)

6a 2.2 9 2.3 2 12.6 (0.8) 16.8 (0.6) 0.9 (0.2) 6.4 (1.6)

11 1.38 9 1.45 2 18 (1.4) 17.2 (1.3) 3.1 (0.4) 5.9 (1.1)

16 3.5 9 3.65 2 25.5 (3) 16.8 (1.7) 6.1 (1.6) 9.6 (0.1)

Mean values are followed by standard deviation in parenthesesa Innermost row

5 cm

2.54 cm

Radial Longitudinal

Tangential

X-ray densityBrinell Nanohardness

Fig. 2 A 5-cm-thick and 2.54-cm wide slice was sawn from the middle of each disk

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Nanoindentation

Four growth rings formed in 1984, 1989, 1994, and 2001 of each strip were selected

to examine the hardness of the cell walls in early- and latewood. A 4 9 4 9 4 mm3

cube was cut from each growth ring in such a way that it contained the latewood of

the years of interest and the earlywood formed in the following years. For example,

the cube for 1984 contained latewood of 1984 and earlywood of 1985. This allows

for both earlywood and latewood contained in the same cube and avoids applying

nanoindentation on wood cells within earlywood to latewood transition zone. This

ensured that all rings were tested in the same manner, since some growth rings were

wider than the final smooth surface allowed in the nanoindenter. The wood cubes

were embedded in Spurr’s (Spurr 1969) epoxy resin according to the manufacturers’

protocol for hard resin. Following resin impregnation, samples were placed under

vacuum (1 h), the vacuum released (1 h), and the vacuum treated again. Finally, the

resin was heat polymerized at 70 �C for at least 12 h in an oven. The embedding

epoxy resin, once cured, provided mechanical support for microtome sectioning and

prevents wood cell walls from buckling during indentation. The resin-embedded

cubes were shaped into a truncated pyramid such that the bottom and top of the

pyramid were parallel to each other and perpendicular to the longitudinal axis. A

particular attention was paid to specimen preparation since it has been demonstrated

that fiber/fibril alignment is important and can significantly influence results and

scattering (Gindl et al. 2004; Konnerth et al. 2009; He and Swain 2011; Jager et al.

2011). The top surface of each truncated pyramid was leveled using a glass knife

and then cut with a rotary microtome (Leica RM2265) equipped with a diamond

knife to generate a smooth surface of 2 9 2 mm2 (Fig. 3). After conditioning for

24 h at 21 �C and 60 % relative humidity (11 % equilibrium moisture content) in

the room housing the nanoindenter, nanoindentation was performed using a

Hysitron TI 900 Tribo Indenter equipped with a cube corner tip to measure

nanohardness.

The standard Oliver–Pharr method was used to assess nanohardness using load

and area of contact for each individual nanoindentation. Two types of indenters

were tried for nanoindentation, i.e., cube Corner and Berkovich tip. The cube corner

tip is a three-side pyramid with mutually perpendicular faces arranged in geometry

like the corner of a cube. The centerline to face angle for this indenter is 34.38. In

Fig. 3 Truncated pyramid with2 by 2 mm of smooth transversesurface

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preliminary tests, the cube corner and Berkovich tips gave the same information and

no significant differences in terms of hardness.

Before nanoindention, calibration was performed on quartz following procedures

recommended by the manufactures to ensure the accuracy of the measurements.

Axial nanoindentations were performed across the transverse surface of the

secondary cell wall (S2) and middle lamellae (ML) of both early- and latewood

fibers. A loading function was applied to load a peak force of 100 lN.

Nanohardness (GPa) was calculated as the ratio of the maximum load to the

projected contact area. To control the proper positioning of the indenter tip and

avoid edge effects (Jakes et al. 2008a, 2009), a dedicated incident light microscope

(509) mounted in the nanoindenter Hysitron TI900 was used to scan sample surface

and locate proper spots for the indentation. This was followed by a probe scanning,

which revealed topographic surface of fibre cross section, and several points of

interest, 3–4 lm apart, were located and marked on the topographic images for

indentation (Fig. 4). After nanoindentation, a rescanning was performed to verify

the indentation positions. Nanohardness data measured at compromised positions,

i.e., positions too close to the edge of interested area (S2 layer and ML) as proposed

by Jakes et al. (2008a, 2009), or having significantly deviated from the marking

points, were discarded for analysis.

Brinell hardness and X-ray densitometry

Brinell hardness tests were conducted according to a modified Brinell hardness

method (Brinell ball of 11.3 mm in diameter on the end face—transverse section)

with adjustments according to ASTM D1037 and Green et al. (2006). Each wood

sample was cut into 13-mm-thick (longitudinally) and 25-mm-wide (tangentially)

slices with length (radius) depending on tree diameter. Tests were performed at

12 % moisture content by a universal testing machine (Shimadzu AG–X 50 KN).

The measurement accuracy was ±0.01 mm for position, ±0.1 % for speed, and

Fig. 4 a Topographic images showing the positions of indentations on the S2 layer of two adjacentearlywood tracheids of jack pine. Small open circles followed by numbers are designated indentationpositions, showing the relationships with actual positions of indentation (triangular shape); b 3D view ofa nanoindentation on S2 layer of three adjacent latewood tracheids of jack pine

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±0.5 % for loading. The Brinell hardness test was conducted on the same rings

(1984, 1989, 1994, and 2001) as for nanoindentation. The geometric center of each

ring was first identified to correspond to the impact point of the Brinell ball. Loading

rate was 4 mm/min, and hardness was measured as the ball penetration, i.e.,

displacement under a load of 1,500 N. A large displacement implies a low Brinell

hardness, and vice versa.

For X-ray analyses, a small strip was cut from the corresponding strip to yield a

1.57-mm-thick (longitudinally) sample using a special saw table adapted for precise

cutting. Sawn strips were scanned by an X-ray densitometer (QTRS-01X, Quintek

Measurement Systems, Knoxville, Tennessee) in air-dry conditions. Ring density

was used as one of the independent variables to explain Brinell hardness variations.

Statistical analyses

Brinell hardness variations were analyzed with three-factor ANOVA using

restricted maximum likelihood estimation (REML). A mixed model with tree

(TREE) as random factor and calendar year (YEAR, four levels) and initial spacing

(IS, three levels) as fixed factors was built. Displacement (DISPL, mm), which is

inversely proportional to Brinell hardness (GPa), was the independent variable.

Similar analyses were done to test the effect of year, IS, and wood type (W;

earlywood or latewood) on nanohardness in the middle lamella and S2 layer.

Treatment means were compared using Bonferroni’s test. In addition, Brinell

hardness (GPa) calculated as the ratio of the maximum load to projected area was

compared with nanohardness.

A regression analysis was performed to describe the Brinell hardness as simply as

possible in order to explain the relationship between Brinell- and nanohardness.

Five independent variables were used to find a fitting model for the studied variable

DISPL (hardness at macro-scale) in relation to hardness on earlywood middle

lamella (HEWML), hardness on latewood middle lamella (HLWML), hardness on

earlywood S2 layer (HEWS2), hardness on latewood S2 layer (HLWS2), and

average ring density (average RD). The Durbin–Watson test was performed to

detect the presence of first-order correlation in the residuals. Null hypothesis (H0: no

first-order correlation between explicative variables) was not rejected according to

the Durbin–Watson table (d = 1.87, dL = 0.90, and dU = 1.92) (Durbin and

Watson 1951). The stepwise method was used to select the variables to be included

in the final model. Finally, the form of the variables in the final model was

determined with the partial residuals.

Results

Variation of Brinell hardness with initial spacing and year

Figure 5 shows displacement variations with IS. Brinell hardness increased with

cambial age, whereas it decreased with increasing IS. DISPL decreased from 1.7

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(±0.2) mm to 1.3 (±0.3) mm from 1984 to 2001 and varied from 1.39 (±0.08) mm

to 1.74 (±0.17) mm with decreasing in initial spacing.

The variability of Brinell hardness between years tends to be greater for high

stand density (narrow IS) than for low stand density (wide IS) (Fig. 5).

Table 2 outlines ANOVA results for Brinell hardness. The effect of YEAR was

the only factor that significantly affected DISPL (Table 2, p = 0.0063). The

interaction IS 9 YEAR was nonsignificant on DISPL (p = 0.0828).

The Bonferroni test showed a significantly higher DISPL in 1984 and 1989 than

in 2001. This implies that wood has a higher hardness on ring formed in 2001 than

that formed in 1984 and 1989.

Comparison with hardness measured by nanoindentation

Figure 6 shows nanohardness variations with YEAR on A) earlywood middle

lamella (HEWML), B) latewood middle lamella (HLWML), C) earlywood S2 layer

(HEWS2), and D) latewood S2 layer (HLWS2). In the middle lamella,

Fig. 5 Displacement (DISPL)variations with initial spacing(IS) for the 4 years (YEARS).1984, 1989, 1994, and 2001refer to calendar years. Treeswere 32-year old when sampledin 2009

Table 2 ANOVA results for Brinell hardness (fixed effects) measured as DISPL (mm)

Source df F Pr [ F LSmeana

IS 2 6.40 0.0828

YEAR 3 8.10 0.0063 84 and 89 [ 01

IS 9 YEAR 6 0.82 0.5831

IS initial spacing (m 9 m), YEAR for calendar years, LSmean least square meana 84, 89, 94, and 01 refer to calendar years 1984, 1989, 1994, and 2001. The plantation occurred in 1977,

and trees were harvested in 2009. Where effects are significant, means were compared using Bonferroni’s

test. Significant levels were adjusted according to the number of comparisons

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nanohardness on earlywood (HEWML) varied from 0.273 to 0.395 GPa and on

latewood (HLWML) from 0.264 to 0.412 GPa. In the S2 layer, nanohardness on

earlywood (HEWS2) varied from 0.234 to 0.301 GPa and on latewood (HLWS2)

from 0.235 to 0.334 GPa. The effect of IS on nanohardness variation is not clear

according to Fig. 6, specifically because nanohardness measured on trees from

intermediate IS (2.2 9 2.3) does not evolve similarly to the others (Fig. 6a–c).

Table 3 outlines the ANOVA results for nanohardness obtained for both ML and

S2 layer. No significant effect of IS on nanohardness for the middle lamella (ML)

(p = 0.53) or for the S2 layer (p = 0.14) was observed. YEAR showed a significant

effect on nanohardness for ML (p = 0.03). Nanohardness on ML was higher in

rings formed in 1984 and 1989 than in 2001. Although not significantly different

between cambial ages, a decreasing trend with calendar year can be observed in

Fig. 6 Nanohardness variations with calendar year (YEAR) for three initial spacings (IS) on a earlywoodmiddle lamella (HEWML), b latewood middle lamella (HLWML), c earlywood S2 layer (HEWS2), andd latewood S2 layer. 1984, 1989, 1994, and 2001 refer to calendar years. Plantation was in 1977, and treesharvested in 2009

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nanohardness measured in S2 layer (Fig. 6c, d). A decreasing trend of nanohardness

was observed from pith to bark for both the ML and S2 layers. While wood type had

no significant effect, it may affect the S2 layer nanohardness differently in different

initial spacings and cambial ages, as shown by the nearly significant interaction

effect (p = 0.06, Table 3).

YEAR has an inverse effect on Brinell hardness and nanohardness in the middle

lamella, while YEAR did not significantly affect nanohardness in the S2 layer.

Moreover, IS did not affect nano- or Brinell hardness.

When DISPL data (mm) are transformed into hardness in GPa by dividing the

load (1,500 N) by the projected area, the resulting hardness appears 10 times lower

than average hardness of S2 and ML obtained through nanoindentation (average

values of 0.029 ± 0.005 vs. 0.297 ± 0.034 GPa, respectively).

Correlation between Brinell hardness, nanohardness, and ring density

According to the stepwise selection, only nanohardness measured on latewood

(HLWML and HLWS2) and average RD were included in the final model. Indeed,

multicolinearity was found between nanohardness measured on early- and latewood,

but not between average RD and nanohardness. The model is presented below (Adj

R2 = 0.77, p = 0.002):

DISPL ¼ �0:17� 11:9HLWMLþ 24:66HLWML2 þ 34:53HLWS2

� 72:43HLWS22 � 0:0022AVRD

The main part of variation in DISPL was explained by average RD (AVRD, partial

R2 = 0.48), while HLWS2 and HLWML explained an additional 19 and 14 % of

the variations in DISPL, respectively.

Figure 7 represents the effect of each independent variable on DISPL

(Y) according to the final model. For each graph, one independent variable was

isolated, while the two others were set as constants equal to their mean values.

Table 3 ANOVA results for nanohardness (fixed effects)

Effect df Middle lamella S2 layer

F value p value LSmeana F value p value LSmeana

IS 2 0.81 0.53 2.37 0.14

YEAR 3 4.60 0.03 84 and 89 [ 01 2.44 0.11

IS 9 YEAR 6 1.40 0.32 0.61 0.72

Wood (W) 1 0.03 0.87 0.02 0.90

IS 9 W 2 0.45 0.65 3.57 0.06

YEAR 9 W 3 0.48 0.71 3.20 0.06

IS 9 YEAR 9 W 6 0.92 0.52 2.93 0.06

IS initial spacing (m 9 m), YEAR is for calendar years, Wood is for earlywood and latewooda 84, 89, 94, and 01 refer to calendar years 1984, 1989, 1994, and 2001. The plantation occurred in 1977,

and trees were harvested in 2009. Where effects are significant, means were compared using Bonferroni’s

test. Significant levels were adjusted according to the number of comparisons

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According to the model, DISP decrease with HLWS2, whereas it is positively

affected with HLWML. Regarding average RD, it evolves in opposition to DISPL,

which is not surprising since Brinell hardness increases with ring density.

Discussion

Comparison between Brinell hardness and nanohardness

It is well accepted that mechanical properties such as hardness are closely

correlated with ring density, which is in turn correlated with fiber dimensions such

as cell wall thickness to lumen ratio (Bendtsen 1978; Jozsa and Middleton 1997)

that are partly dependent on growth conditions (Kang et al. 2004; Savva et al.

2010). In softwood species, changes in growth conditions usually lead to a

variation in earlywood–latewood proportions (e.g., Koga and Zhang 2002;

Alteyrac et al. 2005). The fact that wood density explained a major part of

variance in the regression equation and further confirms the important roles that

wood density plays in Brinell hardness.

The fact that Brinell hardness seems mainly influenced by wood density contrasts

with the decrease in nanohardness with YEAR. This variation may be due to a

variation of the S2 layer and the ML properties independent of early-/latewood cell

wall characteristics (Table 3) (i.e., variations in cellulose microfibrillar arrangement

and crystallinity, and the chemical composition of the S2 layer). Similar results

were found by Huang et al. (2012) who studied nanohardness on compression and

opposite wood cell walls of Masson pine (Pinus massoniana Lamb.). The authors

found that in mature conifer wood, nanohardness was not affected by cell wall

thickness.

A variation that occurs with year is likely due to the transition from juvenile to

mature wood and the difference between heartwood and sapwood. Keith and

(B) y~HLWML (C) y~HLWS2(A) y~DISPL

HLWML (GPa)

0,20 0,25 0,30 0,35 0,40 0,45

HLWS2 (GPa)0,20 0,22 0,24 0,26 0,28 0,30 0,32 0,34 0,36

AverageRD (kg/m³)

350 400 450 500 550 600 650 700 750

y

0,8

1,0

1,2

1,4

1,6

1,8

2,0

2,2

2,4

yDISPL

Fig. 7 Effect of individually studied variables displacement (DISPL, mm). a Ring density (average RD,kg/m3). b Hardness of latewood middle lamella (HLWML, GPa) and c hardness of S2 layer (HLWS2,GPa). Variable transformations were chosen according to partial residuals. The solid line in the figure isthe regression line of the variable of interest while keeping other variables constant (average). The scatterplots represent the measured values of DISPL

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Chauret (1988) found a decrease in the extractive content from both juvenile to

mature wood and heartwood to sapwood in European larch (Larix deciduas Mill.).

This variation has also been observed for other wood species (Campbell et al. 1990;

Jozsa and Middleton 1997). It could imply that the different properties are measured

in nano- and Brinell hardness since the main difference between latewood and

earlywood detected by Brinell hardness variation is related to cell dimensions

(lumen, cell wall). Yet, the density of dry wood cell walls is reported to be relatively

constant at 1,500 kg/m3 (Shmulsky and Jones 2011), regardless of wood type

(earlywood/latewood) cell wall characteristics are modified during tree growth

along the year. The main parameter, which is known to evolve with year in S2 layer,

is the microfibril angle (MFA) of the S2 layer (Bergander et al. 2002). While the

relationship between MFA and MOEr measured with nanoindentation is well known

(Gindl et al. 2004; Gindl and Schoberl 2004; Konnerth et al. 2009, 2010), that

relationship between MFA and nanohardness is less clear and apparently not as

strong (Tze et al. 2007; Konnerth et al. 2009; Meng 2010; Huang et al. 2012). In

conifers, however, it was shown that the MFA0s was large in the juvenile wood and

small in the mature wood (Donaldson 2008). If MFA was the only parameter

affecting nanohardness, one should therefore see an increase in S2 nanohardness

with age (Tze et al. 2007; Donaldson 2008; Auty et al. 2013). A positive increase in

MFA with ring width was found in Scots and radiata pines (Lasserre et al. 2009;

Auty et al. 2013) that lead to a decrease in nanohardness of S2 layer with increasing

spacing. Different studies have shown nanohardness values from juvenile to mature

wood.

The values of nanohardness observed in this study are similar or lower than those

reported for other pine species. Some studies also reported a similar trend of

nanohardness variation with cambial age. For instance, in opposite latewood of

Masson pine, Huang et al. (2012) found that at breast height, nanohardness varied

from 0.5317 GPa for ring number 2 to 0.5216 GPa for ring number 24 (average

value for 6 rings 0.4868 GPa). In loblolly pine in samples from year ring 2 to 50,

taken at 0.3 m above ground, nanohardness varied from 0.53 to 0.42 GPa (average

value 0.4556) with a mean in juvenile wood of 0.50 (ring 2 and 9) in latewood cell

walls (Tze et al. 2007). Both studies showed a decreasing trend of nanohardness

values with increasing cambial age, which is consistent with this study. Average

nanohardness of 0.38 and 0.358 GPa was also reported for ponderosa pine

(Ponderosa pine) (Frihart et al. 2008; Jakes et al. 2008b) and radiate pine (Moon

et al. 2009), respectively. These values are similar to those presented in this study.

Another variation that occurs during wood formation is the formation of heart-

and sapwood which differs in density, chemical composition, and mechanical

properties (Sellin 1994). The main difference between these two types of wood is

the extractive content that increases in heartwood. Despite difficulties in accurately

determining the micro-distribution of extractives in situ, the presence of extractives

impregnated in the cell wall structure has been demonstrated. Extractives can form

coatings on the cell wall and on pits and can penetrate the cell wall itself (Taylor

et al. 2002). Some authors report a variation in heart-/sapwood proportion with

growth rate, but the results are somehow contradictory. An increase in sapwood

width was observed with growth rate and tree diameter in Norway spruce (Picea

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abies (L.) Karst) and Scots pine (Sellin 1994; Morling and Valinger 1999), while

Gominho and Pereira (2000) observed a positive correlation between heartwood

content and growth rate in young eucalyptus (Eucalyptus globulus Labill).

However, only heart-/sapwood volumes were affected by growth rate and not the

number of rings of each type of wood. If nanohardness differed between heart- and

sapwood cell walls, it could also explain why no differences between nanohardness

values were observed with growth rate variation since the samples of this study

showed no evidence of heartwood at 32 years.

The model here suggests that nanohardness in the S2 layer affects Brinell

hardness inversely to nanohardness in the ML. This may be explained in terms of

the chemical composition of the ML and S2 because ML has a higher lignin content

compared with S2 layer, while S2 has low lignin concentration and high cellulose

concentration (Wimmer and Lucas 1997). Regarding the S2 layer, a positive

relationship was found between nano- and Brinell hardness, while the opposite

relationship was observed for ML.

Significance of nanohardness measurements

Nanohardness was about ten times higher than Brinell hardness. This result is

consistent with the literature on soft- and hardwoods (Moon et al. 2009; Konnerth

et al. 2010, respectively). It can be explained through differences in woody material

volume fraction within the indentation interaction volume. For nanoindentation, this

is the cell wall material (without lumen) that is indented, while for the Brinell

hardness, the interaction volume is composed of several wood cells, including

lumens that provoke lower material density. Moreover, while buckling is avoided

during nanoindentation because the sample is embedded in epoxy resin, for Brinell

hardness (Tze et al. 2007), it is one of the first failure modes that occurs in

compression.

As two different methods, nano- and Brinell hardness measurements, are not

supposed to be equivalent, as mentioned in the Materials and methods, some

characteristics of nanohardness such as the form of the indent are important and the

cube corner can influence nanohardness results. While Brinell hardness is performed

with a Janka Ball, it was demonstrated that the form of the indent influences

nanohardness values (Fischer-Cripps 2000; Gindl and Schoberl 2004; Konnerth

et al. 2009). In this study, Brinell hardness was overestimated compared with

nanohardness. Indeed, hardness was assessed from the Brinell test by assuming the

total displacement defines the contact area. In contrast, in nanoindentation, the

resulting plastic depth is used with a predetermined area function to define contact

area. These differences, however, do not induce variations in nano- or Brinell

hardness evolution with cambial age or growth rate, but induce a bias in presented

values. Apparently, nanohardness values have to be interpreted with caution. It was

recently demonstrated in loblolly pine (Pinus taeda L.) (Meng 2010) that

nanohardness on non-resin-embedded samples was significantly lower (i.e., 32 %)

than that of samples embedded with epoxy resin.

Based on the literature, the nanohardness variation in S2 layer did not evolve as it

should be if it was influenced by microfibril angle (Donaldson 2008; Auty et al.

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2013). Moreover, despite not being identical, the nanohardness in the S2 layer and

in the ML evolves similarly with cambial age and was not affected by inter-tree

spacing. This result agrees with the suggestion of authors that observed no

relationship between nanohardness and MFA (Gindl et al. 2002, 2004; Konnerth

et al. 2009), but rather function of matrix properties governed by hemicelluloses and

lignin.

Conclusion

The effect of growth rate controlled by silvicultural practices on the type of wood

produced is particularly important with regard to allocation of timber according to

end-use properties. Since nanohardness does not seem to be affected by such

changes, its use as a unique predictor of macro-hardness may be questioned. Indeed,

the relationship that exists by nature between nano- and macro-hardness may vary

with growth conditions. Although it is known that Brinell hardness was indirectly

influenced by the early-/latewood ratio because of the wall anatomy of the cell

types, the nanohardness of early- and latewood cell walls do not seem to be

different. However, according to the results of this study, variations in nanohardness

properties are induced by the changes that occur in the composition of the S2 layer

and middle lamella with age, and nanohardness measurements show other

characteristics that may influence the bulk properties that should be considered. It

could be a useful tool to integrate in mechanistic models to enhance prediction

precision.

Acknowledgments This study was supported by ForValueNet and NSERC (the Natural Sciences and

Engineering Research Council of Canada) Strategic Network. We would like to thank Michel Beaudoin,

Universite Laval, and Michele Bernier-Cardou, Canadian Forest Service, for their constructive and

critical comments that helped to improve the manuscript; Luciane Paes Torquato at Universite Laval,

and Katherine Concha and Paulina Valenzula at the Universidad del Bıo-Bıo for their nanoindentation

work. We also thank Alain Cloutier and Alexis Achim at Universite Laval for providing the opportunity

for this study. Finally, special thanks are due to Denis Belley at Universite Laval and Edwin Swift and his

team at the Canadian Wood Fibre Centre in New Brunswick for the fieldwork.

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