Tailoring new composites within a perspective of sustainable
development is applied to more and more materials
Electrical Conductivity of Lignocellulose Composites Loaded with
Copper powdersTailoring new composites within a perspective of
sustainable development is applied to more and more materials.
Ecological concerns have resulted in a renewed interest in natural,
renewable resources-based and compostable materials, and therefore
issues such as materials elimination and environmental safety are
becoming important. For these reasons, material components such as
natural fibers, biodegradable polymers obtained from biomass can be
considered as interesting environmentally safe alternatives for the
development of new biodegradable composites (biocomposites).
Biomass is defined as consisting of all plant and plant-derived
materials including livestock manures. The main classification of
biodegradable polymers in different families is: agro-polymers
(e.g., polysaccharides) obtained from biomass by fractionation;
polyesters, which are obtained by fermentation from biomass or from
genetically modified plants (e.g., polyhydroxyalkanoate: PHA);
polymers synthesized from monomers obtained from biomass (e.g.,
polylactic acid: PLA); and polyesters synthesized by petrochemical
process (e.g., polycaprolactone: PCL, polyesteramide: PEA,
aliphatic or aromatic copolyesters), from fossil resources [1]. A
large number of these biodegradable polymers are commercially
available. They show a large range of properties and at present,
they can compete with non-biodegradable polymers in different
industrial fields (e.g., packaging, agriculture, hygiene, and
cutlery) [2].
Lignocellulosic biomass is the nonstarch, fibrous part of plant
material and is an attractive resource because it is renewable and
abundant [3]. Lignocellulose-based fibers are the most widely used.
Intrinsically, these fibers have a number of interesting mechanical
and physical properties [4-6]. The structural and chemical
composition of lignocellulosic feedstocks is highly variable
because of genetic and environmental influences and their
interactions (Table 1). Table 1 lists general characteristics of
agriculture-derived biomass, specifically crop residues from corn
and small grains and dedicated perennial grasses, and other
potential biomass resources [2].
Chemical composition of lignocellulosic feedstocks is a key
factor affecting properties of this biodegradable polymer and its
composites [7, 8]. With their environmentally friendly character
and some techno-economical advantages, these fibres motivate more
and more different industrial sectors (automotive) to replace
common fibreglass, for example. Biocomposites are obtained by the
combination of biodegradable polymer as the matrix material and
fillers [1].
Lignocellulose is the term used to describe the
three-dimensional polymeric composites formed by plants as
structural material. It consists of variable amounts of cellulose,
hemicellulose, and lignin [2]. Lignocellulosic feedstocks are
composed primarily of carbohydrate polymers (cellulose and
hemicellulose) and phenolic polymers (lignin). Lower concentrations
of various other compounds, such as proteins, acids, salts, and
minerals, are also present. Cellulose, the most abundant naturally
occurring plant polysaccharide, consists of long chains of
anhydro--D-glukopyranose units (AGU) with each cellulose molecule
having three hydroxyl groups per AGU, with the exception of the
terminal ends, whereas hemicellulose is the second most abundant
plant polysaccharide readily available, especially from annual
plants and agriculture crop residues such as corn cobs, corn grain,
wheat stems, seed coats, and sugar cane stalks. Polysaccharides
associated with hemicellulose constitute the cell wall of land
plants; D-glucoronic acid, L-arabinose, and D-xylose are present in
the cell wall of corn cobs in the approximate ratio of 2:7:19,
respectively [9]. Lignin (1525% of total feedstock dry matter) is
polyphenolic structural constituent of plants. It is the largest
non-carbohydrate fraction of lignocellulose. Unlike cellulose and
hemicellulose, lignin cannot be utilized in fermentation processes;
however, it may be useful for other purposes. Other compounds
present in lignocellulosic feedstocks are known as extractives.
These include resins, fats and fatty acids, phenolics,
phytosterols, salts, minerals, and other compounds [2].
Cellulose and hemicellulose typically make up two-thirds of cell
wall dry matter and can be hydrolyzed to sugars and then fermented
to ethanol. Also, both cellulose and hemicelluloses have properties
for potential use in the biomedical area, as they have the ability
to pass through the digestive tract unchanged. Owing to their
resistance to digestion, they are eligible as potential excipients
that could be used in the pharmaceutical industry [10].
The research effort on electrically conducting polymer
composites filled with metallic powders has had a great development
in the last two decades. The addition of metals fillers into a
polymer matrix allows enables the preservation of the mechanical
properties of the polymer while exploiting the electrical
conduction properties of the metal [11]. The conductivity of filled
polymers is usually strongly dependent on the nature of the contact
between the conductive filler elements and depends critically on
the volume fraction of the conducting filler particles, and is well
explained by percolation theory [12-14].
Table 1: Composition of different natural lignocellulosic
feedstocks [2].CelluloseHemi-
celluloseLigninAcid
detergent
ligninCrude
ProteinAsh
Crop residues
Corn stover382619456
Soybean3314-1456
Wheat straw382915946
Rye straw3125-336
Barley straw4228-7711
Warm-season grasses
Switchgrass372919636
Big bluestem372818666
Indiangrass3929-638
Little bluestem3531---7
Prairie cordgrass4133-636
Miscanthus432419-32
Cool-season grasses
Intermediate wheatgrass3529-636
Reed canarygrass2436-2108
Smooth bromegrass3236-6148
Timothyb2830-576
Tall fescue252514-1311
Other crops
Alfalfa2712-8179
Forage sorghum341716--5
Sweet sorghum231411--5
Pearl millet2535-3109
Sudangrass3327-81212
Information about numerous existing possibilities of polymers
containing dispersed conductive fillers and various methods of
manufacture of such materials have been reported widely in the
literature for the last years [1522]. Metal-filled conducting
polymer composites have found uses in electromagnetic shielding of
computers and electronic equipment, as conducting adhesives in
electronics packaging, underfill for flip chips, cold solders,
switching devices, static charge dissipating materials and devices
for surge protection [11, 23-26]. Also they found numerous
technological applications as self regulating heater, photothermal
optical recording, direction finding antennas, chemical detecting
sensors used in electronic noses, chemical and electrochemical
catalysts and adsorbents [27-33].
These polymer-based electrically conducting composites have
several advantages over their pure metal counterparts, including
lower cost, ease of manufacture, high flexibility, reduced weight,
mechanical shock absorption ability, corrosion resistance, and
conductivity control [11].The method most often employed to alter
the electrical properties of a polymer is an extrinsic approach
whereby the insulating polymer is combined with a conductive
additive. It is known that, in general, the percolation theory is
used to describe the nonlinear electrical conductivity of extrinsic
conductive polymer composites. Hence, the electrical conductivity
of polymer composites does not increase continuously with
increasing electroconductive filler content. The conducting
additive is incorporated into polymers at levels that allow the
composite to maintain its electrically insulative qualities, as
well as at higher levels, which allow the composite to become
electrically semiconductive. As the volume fraction of the
conducting filler particles increases, the particles come into
contact with one another to form the conduction paths through the
composite. As the result there is a critical composition
(percolation threshold) at which the conductivity increases by some
orders of magnitude from the insulating range to values in the
semiconductive or metallic range [12,13,16].For efficiency and in
order to decrease the difficulty of the process and economic costs,
the amount of the conductive phase for achieving materials with
high conductivity should be usually as small as possible. The
percolation threshold is typically 1530 vol.% for dense spherical
micron size particles [11, 16, 23, 25] A huge number of different
models have been proposed for the estimation of the conductivity
(or inverse resistivity) vs. filler concentration curves [34 -
39].
The aim of this work was to investigate electrical properties of
copper powder filled lignocellulose matrix composites produced
under different pressures, as well to compare the obtained results
with previous research in this field and percolation
theories.Materials and methods
Given that one of the most abundant sources of lignocellulose is
corn cob, the matrix natural polymer used in experiments was a
commercial grade lignocellulose produced by Maize Research
Institute "Zemun Polje" [15]. Celgran C fraction was used, with
particle size below 88 m. Chemical composition of Celgran C
fraction including moistrue, ash, oil, protein and nitrogen free
extracts content is given in Table 2. Composition of lignocellulose
complex of cob fraction is given in Table 3. All presented data
were statistically analysed using variance analysis (LSD) for
unifactorial experiment with randomized block design [15].Table 2.
Chemical composition of Celgran ( C fraction [15]Fraction
Moisture
(%)Ash
(%)Oil
(%)Protein
(%)NFE
(%)
C11.201.210.064.3165.10
LSD 0.010.3140.3140.3140.3140.314
NFE nitrogen free extractsTable 3. Lignocellulose complex of cob
fraction [15]FractionCellulose (%)Hemicellulose
(%)Lignin
(%)NDF (%)ADF (%)
C29.4039.706.6079.439.7
LSD 0.010.4440.3140.3140.5440.314
NDF - neutral detergent fiber
ADF - acidic detergent fiber
Table 4. Physical and chemical properties of Celgran ( C
fraction [15]FractionCLSD0.01
Solubility - %
Water11.150.314
Ethanol5,00 0,314
Acetone10,99 0,314
Sodium hydroxide25,96 0,314
Absorption - %
Water580,16 24,64
Oil129,27 0,623
Oil after water absorption (moist sample)24,79 0,314
Oil after water absorption (dry sample)286,22 0,314
Thermal stability of the lignocellulose was investigated by
thermogravimetry using TA Instruments Q600 thermal analyzer at
10oC/min heating rate under dynamic argon atmosphere. Obtained TGA
curve, presented on Fig.1, illustrates thermal behavior (stability)
of used lignocellulose and characteristic temperatures of the
observed thermal events confirm presence of the main constituents
(Table 3.).
Fig. 1. Results of thermogravimetric analysis of lignocellulose
- fraction Celgran C
The mass loss below 100oC can be attributed to the evaporation
of water (moisture) originally present in the sample (Table 2.).
The mass loss increases with temperature gradually up to
approximately 200oC while in the region between 200 and 400oC more
significant mass loss occurs. On the obtained DTGA curve (Fig.1)
two distinct peaks can be observed within this temperature
interval, suggesting the existence of two separate thermal events.
According to the literature data [20-22], the first event that
occurs at 210-300oC can be associated with the decomposition of
hemicellulose and the slow degradation of lignin, while the second
event (275-350oC) can be attributed to the degradation of
cellulose. Possible discrepancies between literature data and the
DTGA results may be associated with the amount of cellulose and
lignin in the lignocellulose material (Table 3.), given that
Shebani etal.3 and DAlmeida etal.14 demonstrated that higher
cellulose and lignin content in lignocellulosic materials leads to
a greater thermal stability.
Bakarni prah korien kao elektro provodni punioc dobijen je
elektrohemijskim putem, programiranim strujno-naponskim reimom -
reversnom strujom [16,17]. Amplitudna gustina struje je imala
vrednost 3600 A/m2. Vreme katodnog taloenja je iznosilo 40 s, a
vreme anodnog rastvaranja 0.2s. Vreme narastanja praha (r=15 min,
protok elektrolita, Q=0.11 dm3/min, temperatura elektrolita,
t=(50(2)oC, koncentracija bakra, C(Cu+2) = 15 g/dm3 i koncentracija
sumporne kiseline, C(H2SO4) = 140 g/dm3. Bakarni prah je
stabilizovan rastvorom pogodne povrinski aktivne materije [18].
Particle size of used lignocellulose and copper powder was
analysed using Malvern Instruments laser diffractometer Mastersizer
2000 with the Scirocco 2000 module. Obtained particle size
distributions are presented on Fig.2. The mean particle sizes of
lignocellulose powder and copper powder determined by laser
diffractometry are d(0.5) = 60.544 m and d(0.5) = 27.219 m,
respectively.
a)
b)
Fig 2. Particle size distribution of used matrix and conductive
filler powders: a) lignocellulose and b) copper
Morphology of matrix (lignocellulose) and conductive filler
(copper) powders was analysed using scanning electron micrscopy
(SEM). The size and the shape of the matrix and filler particles
are illustrated in Fig.3.
a)
b)
Fig. 3. SEM micrographs of pure matrix and filler powders a)
lignocellulose and b) copper
Investigated lignocellulose and copper powder composites were
prepared with filler contents in the range 10 wt.% - 90 wt.% with
the 10 wt.% increment, while pure lignocellulose and copper samples
were prepared as reference materials. The samples were produced
from thoroughly homogenized powder mixtures that were pressed into
16 mm diameter tablets at ambient temperature (t = 25oC) under
pressure of 10, 20 and 27 MPa. Morphology of the investigated
composites was analyzed using scanning electron microscopy
(SEM).
Fig. 4. SEM micrograph of the obtained lignocellulose-copper
powder composite
Sample thicknesss (necessary for the calculation of porosity and
conductivity) was determined using micrometer, to an accuracy of
0.01 mm. Several thickness measurements were taken per sample and
then averaged.
Theoretical density of composites t was calculated according to
relation [2,19]:
(1)
where V is volume fraction, density while f and m indexes
correspond to filler (copper powder) and matrix (lignocellulose),
respectively.
Porosity of the investigated composites was determined by
comparison of experimental and theoretical densities of the samples
according to relation [19]:
(2)
where e is experimentally obtained value of composite
density.
Electrical conductivity measurements were carried out by DC
U/I-characteristic measurements of the samples using Digital
Multimeter, Model 464, Simpson Elec. Company. Geometry of the
instrument contacts (rings) used is such that it minimizes edge
effects thus it can be assumed that they do not exist. Electrical
conductivity was determined according to relation:
(3)
where is electrical conductivity, I current through sample, U
potential difference, l length and S cross-sectional area of the
sample.
Hardness of the samples was determined at ambient temperature (t
= 25oC) using Shore D hardness testing method in acordance with
ASTM D 2240-68 standard. Five data points were taken for each
sample and no difference was found between values obtained for both
faces of each sample.Results and discussion
The theoretical density of the composite (dt) was calculated
from the relation
(1)[pinto, jahorina, tara]where V is the volume fraction, d is
the density, and m and f stand for the matrix and filler,
respectively.
Porosity of the investigated composites, , was determined by
comparison of experimental and theoretical densities of the samples
according to relation:
(2)where de represents the experimental density.
Figure 4 represents the porosity rate of different composites as
function of the filler volume fraction at various processing
pressures. It can be seen that, as expected, the porosity decreases
with the increase of pressure, due to higher packaging effect. On
the other hand, as the volume fraction of the very porous natural
matrix decreases, the porosity decreases too. In all cases, the
porosity is still rather high around percolation threshold and it
is between 24% and 30%. These results show that although the
quality of the obtained composites was good, some changes in the
preparation processes can lead to lover porosity composites.
Figure 4: Porosity of the copper powder filled lignocellulose
matrix composites at various pressures.
Figure 5 shows the dependence of hardness measured as shore D
values, in various composite of lignocelluloses matrix and copper
powder filler prepared under various pressures. As expected with
pressure molding under low temperatures (25C), the hardness
decreases with the increase of the filler fraction and it increases
with the increase in processing pressure.
Figure 5: Hardness of lignocelluloses matrix and copper powder
filler composites prepared under various pressures. Measurements
are shown as Shore D values.
The electrical conductivity of the composites as a function of
filler content for the samples was measured as stated in Materials
section. The conductivity measurements showed typical S-shaped
dependency with three regions (dielectric, transition, and
conductive; Fig. 6). These measurements were performed on all the
samples prepared under three different pressures: 10 MPa, 20 MPa
and 27 MPa. As expected, samples with low filler content were
almost nonconductive. However, the electrical conductivity of the
composites increased dramatically as the copper content reached the
percolation threshold at 14.4% (v/v) filler for all the processing
pressures. The value of the percolation threshold was obtained from
of the maximum of the derivative of the conductivity as a function
of filler volume fraction (Fig. 6). According to Flandin et al.[4],
values of 2040% (v/v) are typical for spherical particles of
filler. This much lower percolation threshold can be explained by
much higher specific area of the highly dendritic copper powder
particles used as filler. The statistical percolation theory is
usually used to relate the electrical conductivity of the composite
to the existence of clusters of connected particles, which give
rise to the so-called conducting infinite cluster above the
threshold. With highly porous, highly dendritic particles with high
values of specific area, more interparticle connections can be
obtained at lower filler content. Above the percolation threshold,
the conductivity of composite increased by much as fourteen orders
of magnitude. The increase in the conductivity is higher than
stated by Pinto et all. due to filler with high specific area. It
can be seen from the Figure 6 that under investigated range of
pressures there is no change in the percolation threshold. However,
in the conductive region, composites with the same volume fraction
of copper powder prepared under higher pressure have higher values
of conductivity.
Figure 6: Variation of electrical conductivity, as a function of
filler content, of lignocellulose composites filled with copper
powder under different processing pressures.For percolation theory,
the relationship between the electrical conductivity of the mixture
and the volume fraction of the conductive filler was given by
Kirkpatrick:
(4)where is the electrical conductivity of the mixture, 0 is the
electrical conductivity of the fillers particles, Vf is the volume
fraction of the filler, Vf* is the critical volume concentration at
the threshold of percolation, and t is an exponent that determines
the increase in the conductivity above Vf*. This theory provided a
good description of the experimental results near the transition
point. However, discrepancies were observed between the critical
parameters (Vf*, t) resulting from eq. (4) and the experimental
values, since this theory does not include the shape of the
conductive filler and it does not consider several other
parameters. Although the experimental results show that the
electrical conductivity depended strongly on the viscosity and the
surface tension of the filled polymers, it also depended on the
filler particles geometrical parameters and the filler matrix
interactions. These parameters were considered by Mamunya et
al.[15,16]. A model they developed consideres specific parameters
for each composite and it is given in the basic theory:
(5)
where m is the maximal conductivity of composites, F is the
filler packing density coefficient (equivalent to the maximal value
of the filler volume fraction), and teff is given by the
relation
(6)
where t1 is equivalent to the t parameter in the basic eq. (4).
t1 usually has a value around 1.7, and t2 depends on the specific
composite. Thus, teff could have higher values depending on the
fillerpolymer interactions.
Treba da resim jednacinu, potom da zavrsim poslednji pasus.
Equation (4) will be used in this study to interpret
experimental results. The fit, above the percolation threshold, of
the electrical conductivity as function of the volume fraction of
Zn filled in urea formaldehyde embedded in cellulose powder is
given in Figure 5. The agreement between the experiment and the
theory was fairly good. The deduced parameters were Vf* 18.5%, teff
2.25, and F 0.45.
The determined packing density coefficient was in good agreement
with the prediction of eq. (4).25 The teff obtained value was close
to 2, which represented the accepted theoretical value for
three-dimensional lattices.26,27 This theoretical value was
independent of the exact composition of the random composites.26 On
the other hand, the critical threshold percolation value obtained
was in good agreement with that determined by experience, Vf*
18.9%. Elsewhere, this result was also close to the 18% found in
Zn-filled nylon 6.22 Indeed, the random composites electrical
conductivity was already shown to depend on several parameters,
1823,28,29 such as the viscosity and the polymers surface tension,
especially in the case of mixes in which the conductive powder is
dispersed; the size, shape, and surface energy of the filling
particles; and the powder dispersion procedure, that is, the type,
duration, and strength of shear. In this study, the particle sizes
and shape of Zn filled in nylon 6 and ureaformaldehyde were the
same, and the dispersion procedure was maintained uniformly.
Consequently, the small difference in threshold values observed
between nylonZn and ureaformaldehyde/Zn composites was probably due
to the specific matrixfiller interaction and viscosity effects.
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