PHYSICAL AND THERMAL CHARACTERIZATIONS OF INSULATION COMPOSITE
MADE OF WOOD FIBERS

By

Tianxiao Hu
B.Sc. University of Canterbury, 2016

PROJECT SUBMITTED IN PARTIAL FULFILLMENT OF
THE REQUIREMENT FOR THE DEGREE OF
MASTER
OF
NATURAL RESOURCES AND ENVIRONMENTAL STUDIES

UNIVERSITY OF NORTHERN BRITISH COLUMBIA
April 2021

© Tianxiao Hu, 2021

© Tianxiao Hu, 2021

Abstract
Currently, mineral fiber or cellular plastic insulation materials dominate the building
construction market because of their relatively competitive price and low thermal conductivity
properties; however, the environmental impacts of cellular plastic insulation materials during
their whole life cycle are significantly higher. Additionally, the forestry sector in Canada
generates approximately 5.38 × 106 oven-dried tons of wood product residues per year and there
are opportunities to further process and use them as the raw materials for producing wood-based
fiber insulation boards.
The purpose of this study is to investigate the methods to utilize the woody residues and process
them into wood fibers to form insulation boards. Additionally, an eco-friendly casein adhesive
was chosen to bind the wood particles together. The boards were successfully formed and have
thermal conductivity values ranging from 0.057 to 0.078 W/mK, based on different board
densities and moisture contents, which satisfy the minimum requirement of the ASTM insulation
standard. Thus, this study of forming wood-based fiber insulation boards shows opportunities of
reducing the environmental impacts and reducing the building energy consumption due to
heating or cooling at the same time.

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Table of contents

Abstract ........................................................................................................................................... 1
Chapter 1: Introduction ................................................................................................................... 5
1.1

Background ....................................................................................................................5

1.2 Objectives ...............................................................................................................................7
Chapter 2: Literature review ........................................................................................................... 8
2.1 Introduction ............................................................................................................................8
2.2 Types of insulation material ...................................................................................................8
2.3 Wood fiber insulation panels................................................................................................10
2.4 Other types of renewable insulation materials .....................................................................11
2.5 Types of Adhesives ..............................................................................................................12
2.6 Physical performance of renewable materials-based insulation panels ...............................14
2.7 Literature review summary ..................................................................................................15
Chapter 3: Materials and methods ................................................................................................ 16
3.1 Purpose .................................................................................................................................16
3.2 Materials preparation............................................................................................................16
3.2.1 Wood particles .............................................................................................................. 16
3.2.2 Moisture content ........................................................................................................... 18
3.2.3 Adhesive ....................................................................................................................... 18
3.3 Board preparation .................................................................................................................19
3.4 Adhesive preparation............................................................................................................21
3.5 Panel formation ....................................................................................................................23
3.5.1 Ratio of glue to wood particles ..................................................................................... 23
3.5.2 Mix wood particles with casein adhesive ..................................................................... 24
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3.5.3 Results .......................................................................................................................... 26
3.6 First evaluation of the consistency of the panels by observations .......................................26
Chapter 4: Experimental Study ..................................................................................................... 28
4.1 Determination of density and moisture content ...................................................................28
4.4.1 Determination of dimensions, moisture content and density of the sample ................. 28
4.1.2 Dimension measurement procedures ............................................................................ 28
4.1.3 Mass measurement procedures ..................................................................................... 28
4.1.4 Calculation of the density and moisture content of the samples .................................. 29
4.2 Determination of thermal conductivity ................................................................................30
4.2.1 Terminology ................................................................................................................. 30
4.2.2 Test machine and principles ......................................................................................... 30
4.2.3 Preparing samples and testing procedure ..................................................................... 31
4.2.4 Thermal conductivity measurements ............................................................................ 32
Chapter 5: Experimental results and discussions .......................................................................... 33
5.1 Specimen density and moisture content ...............................................................................33
5.2 Specimen thermal conductivity ............................................................................................38
Chapter 6: Conclusion................................................................................................................... 43
6.1 Objective accomplishment ...................................................................................................43
6.2 Applications .........................................................................................................................44
6.3 Further works and suggestions .............................................................................................44
References ..................................................................................................................................... 46
Appendix ....................................................................................................................................... 49

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List of tables
Table 1: Board preparation final plan ........................................................................................... 20
Table 2: Casein Glue Formula No. 11 .......................................................................................... 21
Table 3: The amount of wood particles used for samples ............................................................ 24
Table 4: Actual average density of oven dried samples ............................................................... 33
Table 5: Actual average density of samples at 20% relative humidity ......................................... 34
Table 6: Actual average density of samples at 50% relative humidity ......................................... 36
Table 7: Thermal conductivities at 200, 250, & 300 kg/m3 of each category ............................... 39
List of figures
Figure 1: Types of the wood particles........................................................................................... 17
Figure 2: Formulation of Casein Glues ......................................................................................... 23
Figure 3: Steps to mix glue with wood particles........................................................................... 25
Figure 4: Transfer the mixture into the mold and press ................................................................ 25
Figure 5: A picture of the Heat Flow Meter (HFM) ..................................................................... 31
Figure 6: Actual density of oven dried panels .............................................................................. 34
Figure 7: Actual density of panels at 20% relative humidity........................................................ 35
Figure 8: Actual moisture content of panels at 20% relative humidity ........................................ 35
Figure 9: Actual density of panels at 50% relative humidity........................................................ 36
Figure 10: Actual moisture content of panels at 50% relative humidity ...................................... 37
Figure 11: Thermal conductivity vs. sample density of category A ............................................. 41
Figure 12: Thermal conductivity vs. sample density of category B ............................................. 41
Figure 13: Thermal conductivity vs. sample density of category C ............................................. 42
Figure 14: Thermal conductivity vs. sample density of category D ............................................. 42

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Chapter 1: Introduction
1.1 Background
The building sector is one of the major energy consumers and greenhouse gas (GHG) emissions
contributors. Canada has a relatively high energy intensity due to climate and standard of living,
nearly 25% of GHG emissions are from residential, commercial, and institutional buildings in
2015 (NRC, 2017). The total energy consumption of the residential sector in Canada was 1608.7
million gigajoules (GJ) with an intensity of 0.81GJ/m2 in 2016 (CPC, 2018). The commercial
and institutional sectors consumed a total of 911.2 million GJ of energy with an energy intensity
of 1.14GJ/m2 in 2014 (NRC, 2016). The energy consumption for heating or cooling the building
accounted for about 12% of national GHG emissions in Canada in 2014. It takes a large
proportion of the building’s total energy consumption. 65% of the energy is used for space
heating, 17% is used for water heating, 12% is used for appliances, and 6% is used for lighting in
2015 (NRC, 2017).
Thermal insulation materials play an essential role in the building construction industry. The use
and production of thermal insulation materials for buildings have become more important in
recent years, because energy-efficient buildings not only lessen the demand on the electric grid,
decrease stress on natural gas supplies, but also improve local air quality, reduce pollution, and
reduce energy consumption cost. For the new construction in British Columbia and in Canada,
buildings must meet energy efficiency requirements listed in the 2015 National Building Code of
Canada and the BC Building Code (NRC, 2017) as well as the BC Energy Step Code.

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The use of insulation materials is key for constructing energy-efficient and code-compliant
buildings. A high R-value envelope does not only provide thermal comfort to the users but also
reduces energy consumption and environmental impact. Thus, the production of suitable
materials for insulation becomes of great importance. Currently, insulation materials are usually
made from mineral fiber or cellular plastic because of the relatively competitive price and the
mature market compared to plant-derived materials. However, the suspicion of health and
environmental risks that these mineral fibers or cellular plastic materials could have, has risen in
recent years. Thus, it is important to investigate plant-derived materials to benefit both the
consumers and the environment.
The Canadian forestry industry is a major contributor to the Canadian economy. The forest
sector contributed $23.7 billion to Canada’s nominal gross domestic product (GDP) in 2019
(NRC, 2020). Canada’s forestry sector also produced a large number of wood residuals and
byproducts. According to research conducted by Levin et al. (2007), Canada generates a total of
approximately 1.45 × 108 tons of residual biomass from forestry, agriculture, and municipal
sources per year including 9.18 × 107 oven-dried tons of woody non-stem residues and 5.38 ×
106 oven-dried tons of wood product residues. These residual biomasses are not well managed
and are responsible for about 10% of Canada’s greenhouse gas emissions. As a result, if the
woody residual in the forestry sector would be well managed, processed, and utilized, not only
will a large amount of energy will be conserved and GHG emissions could be reduced, but also a
potential source of revenue can be created. The wood residuals can be utilized via further
processing them into smaller wood fibers and particles. Then, the smaller wood particles and
fibers can be used as raw material for producing plant/animal-derived wood fiber insulation
boards.

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1.2 Objectives
The purpose of this project was to test the thermal conductivity of simply produced wood fiber
boards, using an environmentally benign binding agent, dependent on the fiber mixture, binding
agent content, density, and humidity of the final panel. This project explores a simple way of
utilizing wood residuals such as wood shavings, produced in the forestry sector and then further
process them into thermal insulation boards for buildings to reduce energy consumption and
GHG emissions.
This research consists of two steps; the first step is to investigate a proper environmentally
friendly and economically viable method to produce the panel and a proper bio-adhesive to bind
the wood shaves and sawdust together. The second step is to investigate and compare the thermal
performance and physical properties of the formed insulation board.

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Chapter 2: Literature review
2.1 Introduction
Many studies have been conducted to investigate the feasibilities of replacing the mineral fiber or
cellular plastic thermal insulation materials with plant/animal-derived materials. Thorough
literature reviews, the advantages, and disadvantages of current insulation materials used in the
industry, have been summarized and compared. Also, insulation materials based on renewable
materials have been examined. Some of the renewable raw materials and adhesives that are
suitable for making insulation boards, as well as the methods, and processes for making those
insulation boards, and the thermal and physical performance of these boards are also summarized
and compared.
2.2 Types of insulation material
Thermal insulation materials are widely used for constructing energy-saving buildings. The
insulation materials are divided into three different groups of materials, mineral fiber materials
i.e. rock wool, slag wool, and glass wool; the cellular plastic materials based on fossil fuels, i.e.
rigid polyurethane, phenolic, expanded polystyrene (XPS), and extruded polystyrene (EPS), and
renewable material i.e. cellulose fiber, sheep wool, cotton, flax (CTCN, n.d). The renewable
insulation materials such as wood fiber insulation, and cellulose insulation materials have
already been commercialized in the European market.
Mineral fiber or cellular plastic materials dominated the world’s insulation material market.
According to the research (Asdrubali, 2015), in 2011, 52% of the market share is dominated by
mineral wool, 41% of the market share is dominated by cellular plastic. These materials usually
have a competitive price and good thermal performance, but they are not sustainable because

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they cause large environmental impacts and health risks during their production, installation,
reuse, and landfill cycle. Specifically, mineral fiber materials may contain harmful additives and
fine dust which could cause health risks if they are not properly applied and sealed from the
room air (Kienzlen et al. 2014). For cellular plastic materials, the embodied energy is
significantly high, the primary energy requirements for the production of foam glass, PU, or XPS
can up to 1300 kWh/m3 which makes the energy payback period significantly long (Kienzlen et
al. 2014). Additionally, some of the synthetic materials may have formaldehyde emission
problems, and disposal of these materials causes environmental issues, especially for the oilbased insulations. Oil based insulation is cost-effective which makes recycling uneconomical,
thus the oil-based insulation material usually ends up in the landfill or incineration. Since plastic
is also not biodegradable which means it can last for hundreds of years when they contribute to
the landfill; and burning plastic creates harmful dioxins and if incinerators are inefficient, these
leak into the environment (BBC, 2018). Contrarily, plant/animal-derived materials are renewable
resources that have lower embodied energy compare to synthetic-based insulation materials.
Producing plant/animal-derived materials is more eco-friendly because they require much less
energy for production than conventional building insulation materials such as mineral wool and
fossil-based materials. Additionally, instead of inducing toxic materials or greenhouse gases,
renewable insulation materials can bind CO2 during the growth phase. Most renewable based
insulation materials such as straw, hay, hemp, wool, cotton, wheat hulls, and sawdust are
agricultural and forestry by-products. Depending on the situation they might even offer a
solution to issues regarding the disposing of such materials. If a new application method can be
discovered, it will solve potentially two industrial problems at the same time.

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2.3 Wood fiber insulation panels
Wood fiber insulation boards are wood boards made of wood fibers with a density between 50
kg/m3 and 220 kg/m3; they have a high thermal mass and good thermal performance. They are
used as continuous insulation layer in central Europe. They can be produced via the dry
processing method or wet processing method.
The wet processing method is the traditional method. In the wet processing method (IBO, 2016),
the wood chips are deflocculated with water vapor, grinding, mixing with water and additives,
then vacuum absorption is adapted to remove the production water. After that, it is dried in a
stacked dryer for days at 120-190 ℃ until the moisture drops from 40% to 2%. In the wet
process method, the wood lignin is activated, thus it requires no additional adhesives. However,
this method requires high temperature and pressure (Bouajila et al. 2005), and consumes a large
amount of energy and water. Thus, the cost is higher than the dry processing method.
The dry processing method (IBO, 2016) became more popular in recent years due to its lower
costs. In the dry proceeding method, the wood chippings are deflocculated into fibers in a refiner,
and then fibers are sprayed with polyurethane resins or mixed with bi-component synthetic fibers
and bound into homogenous panels under heat and pressure.
The drawback of wood fiber insulation board is that it has a higher price compared to mineral
fiber or cellular plastic materials, but have a similar thermal performance. The high cost of the
wood fiber panels is mainly due to the high production cost of the wood fiber; thus, lowering the
production costs of wood fiber insulation panels is essential for promoting the wood fiber
insulation boards to replace the Mineral fiber or cellular plastic insulation boards.

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2.4 Other types of renewable insulation materials
According to literature review, plant/animal derived raw materials can be adapted for making
insulation boards. The thermal performances of these renewable insulation materials such as
wood chips, cotton stalk, wheat straw, rice husk, coconut husk, and textile waste-fibers could be
competitive with those of mineral fiber or cellular plastic materials if they are industrially
manufactured.
The wood-based raw materials have a good thermal performance. A study shows that manual
filling or mechanical blowing the wood chips and particles into the walls between the studs of
the frame and without using any binder achieved a relatively low thermal conductivity (value
ranged from 0.048 to 0.055 W/mK) at a low density (value ranged from 117 to 158 kg/m3)
(Cetiner et al. 2018). This method is cheap because it does not use any adhesives or energy to
press the wood chips, however, this method has similar drawbacks as the cellulose insulation.
Loose-fill insulation could settle after application, which will decrease the thermal performance
of the building. Moreover, small wood particles can be blown into the house through inadequate
seals around fixtures or small holes.
The other renewable materials such as plant stalk, rice straw, coconut husk, and textile wastefibers can also be used as raw materials for forming insulation boards. Wei et al. (2015)
produced insulation panels made from rice straw, the research showed that the board with a
density of 250 kg/m3, and a particle moisture content (MC) of 14%, had optimal physical and
mechanical properties with a thermal conductivity ranging from 0.051 to 0.053 W/(mK). Hajj et
al. (2011) produced insulation panels made from flax-tows; the panels achieved an optimum
thermal conductivity of 0.065 W/mK with a density of 170 kg/m3. Panyakaew et al. (2011)
produced insulation panels made from coconut husk and bagasse; the panels have thermal
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conductivity values ranging from 0.046 to 0.068 W/mK with a density of 350 kg/m3. The panels
made from plant stalk have a relatively higher thermal conductivity. Zhou et al. (2010) produced
insulation panels made from cotton stalk fibers that had thermal conductivity values ranging
from 0.0585 to 0.0815 W/mK with a density of 150-450 kg/m3. Binici et al. (2014) produced
panels from sunflower stalk, the thermal conductivity was not ideal with a value of 0.1642
W/mK.
2.5 Types of Adhesives
The adhesive is essential for making insulation boards. Generally, two types of adhesives are
available in the market which are bio-adhesive and synthetic adhesive. The bio-adhesives have
an environmental-friendly lifecycle, it does not produce formaldehyde emissions and it is easy to
dispose of. The bio-adhesives, such as lignin, starch, and plant or animal protein can be used to
bind the renewable materials together. Bio-adhesives showed promising binding abilities for
cotton stalk fibers, textile waste fibers and wheat straws. Zhou et al. (2010) made insulation
boards via hot pressing to activate the cellulose and lignin inside the cotton stalk with no
adhesive added because cotton stalk is rich in cellulose and lignin. Belakroum et al. (2017) used
70% of starch solution which contains 15% of starch and 85% of water as a binder mixed with
30% of date palm fiber to make insulation panels. Wang (2002) investigated using soy proteinbased adhesive [i.e. sodium hydroxide (NaOH)-modified soy protein isolate (SPI)] to making
low-density particleboard (300–340 kg/m3) from wheat straw and corn pith. The results showed
that NaOH-modified SPI increased the tensile strength and compressive strength of the
particleboard. Mati-Baouche et al. (2014) investigated the feasibility of using chitosan as the
adhesive to bind sunflower particles forming panels. Results showed that the mechanical and
thermal performances are competitive with those of other insulating plant/animal derived

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materials available on the market. Lacoste et al. (2018) investigated the use of sodium alginate
(Alginate derived from seaweed) as a binder to bind wood fibers or textile waste fibers to make
insulation panels. The formed panel has a relatively higher density (308–333 kg/m3) with a
thermal conductivity ranging between 0.078 and 0.089 W/mK. Tůmová et al. (2017) investigated
forming straw insulation panels by using casein adhesive, the panels can reach a density of 72 to
92 kg/m3, with thermal conductivity of 0.045 W/mK.
Synthetic adhesives can also be used to bind the bio-waste together. Generally, they have better
performance than the plant/animal derived adhesives because they do not have molding problems
and they have stronger binding abilities. Currently, all the engineered wood products in the
industry such as wood fiber insulation panels, particleboard or low-density fiberboard (LDF),
medium-density fiberboard (MDF), and hardboard (high-density fiberboard, HDF) are made via
synthetic adhesives. The commonly used synthetic adhesives in the industry including Ureaformaldehyde (UF) resin, Phenol formaldehyde resins (PF) resin, Melamine–formaldehyde (MF)
resin, Melamine–Urea–Formaldehyde (MUF) resin, and polymeric diphenylmethane
diisocyanate (pMDI) resin (IBO, 2016). The adhesives such as UF, PF, and MUF resin induce
formaldehyde emissions that are found to cause negative health effects compare to pMDI resin.
Although pMDI resin is more expensive, it can give the product a higher internal bond strength
(IBS), better modulus of elasticity (MOE) and modulus of rupture (MOR) and additional
moisture resistance, and requiring less formaldehyde testing and monitoring. (Tan, 2012).
Many experiments showed that synthetic adhesives can also be used to bind other renewal
materials. Binici et al. (2014) investigated using epoxy resin binding sunflower stalk, textile
waste and stubble fibers to make bio-insulation panels. The drawback of most synthetic

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adhesives is that no matter how the formula modified or how small the amount of the synthetic
adhesives used, it will always induce a little amount of toxins such as formaldehyde emission.
2.6 Physical performance of renewable materials-based insulation panels
The literature review showed that the mechanical performance of the boards including the
bending modulus of rupture (MOR), and modulus of elasticity (MOE), are affected by the
following factors such as the pressing method and time, the moisture content (MC) of the
particles, and the density of the panels.
The MOR and MOE of the panel increased with increasing board density. The MOR and MOE
of the panel also depend on chemical and physical properties of different materials as well as
individual fiber strengths and fiber geometry of which the panel was made, (e.g. coconut husk,
rice straw, cotton stalk), (Yang et al. 2003, Panyakaew et al. 2011 & Wei 2015). For the
formation of the panel without adhesive, a higher pressing temperature and a longer pressing
time increased the internal-bonding strength (IBS) between the particles, hence increased the
MOR and MOE of the panels. Moreover, a slight increase in the moisture content (MC) of the
particles (from 7% to 13%) enhanced the IBS by about 33%. (Zhou et al. 2010 & Panyakaew et
al. 2011).
Yang et al. (2003) manufactured insulation boards by mixing rice straw and wood particles. A
commercial urea-formaldehyde adhesive was used as the composite binder. It was found that the
bending MOR increased slightly with the rice straw particle length and width. Wei et al. (2015)
used adhesive MDI to bind rice straw to make panels. It was found that IB and MOR increased
with increasing particle size.

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According to research conducted by Holt et al. (2012) and Wei et al. (2015), the thermal
performance of boards is related to particle size. An increase in particle size resulted in an
increase in the thermal performance of the boards. Additionally, according to Wei et al. (2015),
the thermal performance of boards decreased with an increase in the board density. The thermal
conductivity also increased with increasing ambient temperature. Thermal insulating properties
deteriorated due to moisture; however, it remained constant at the relatively low particle
moisture content (MC between 10% and 18%).
2.7 Literature review summary
In previous research, attempts to make eco-friendly, economically viable plant/animal derived
insulation boards via its raw materials, the manufacturing method, and process, the types of
adhesives proved that the plant/animal-derived insulation products can be competitive regarding
their mechanical and thermal performances with those of mineral fiber or cellular plastic
materials and wood fiber boards currently widely used in the European market. Additionally,
mineral fiber or cellular plastic materials have a substantial environmental impacts and health
risks during their life cycle. So far, synthetic adhesives have a better physical performance than
bio-based adhesives. However, synthetic adhesives have a larger environmental impact than biobased adhesives. Nonetheless, several experiments have shown that some of the bio-based
adhesives had a promising performance for binding the plant derived materials; particularly, the
casein adhesive shows a strong binding ability. Casein can cure at room temperature; however,
the research into of adapting casein adhesive for forming the insulation boards are limited and
require further research.

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Chapter 3: Materials and methods
3.1 Purpose
To form the insulation panels, the larger wood residuals need to be further process into smaller
wood particles, shavings, and fine fibers; then the adhesives can be applied and boards can be
formed. Therefore, the first purpose of this chapter is to examine the feasibilities of using the
different proportions of the wood particles, shavings, and fine fibers in the prepared mixture so
that the boards can be formed. The second purpose of this chapter is to examine an
environmentally friendly and economically viable adhesive, i.e. casein to bind these wood
particles and to form insulation boards.
3.2 Materials preparation
3.2.1 Wood particles
This project simulated utilizing the woody residuals of the local forest industry as the main
biomass from sawmills, to further process them into the wood particles, wood shavings, and
wood fibers in order to form wood-based insulation board. The literature review suggested that
currently available on the market are wood fiber insulation panels consisting of 100% fine
processed wood fibers, similar to the fibers used for the manufacturing of MDF boards.
Processing the wood residuals into the fine wood fibers requires additional energy, therefore
replacing a large portion of the fibers with wood particles and wood shavings can reduce the cost
of the insulation board. The size of wood particles and wood shavings cannot be too large to
avoid the creation of larger air pockets. This would potentially decrease the thermal performance
as well reducing the structural integrity. The longer wood fibers out of an MDF production line
are used to add structural performance to the insulation board. Part of the project was to

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investigate the ratio between wood shavings, wood particles and a small amount of processed
fibers to produce boards and still maintain their structural integrity.
The wood shavings, wood particles, and wood fibers used in this project were obtained from the
West Fraser WestPine MDF plant in Quesnel BC, Canada. These different types of particles used
are shown in Figure 1. The wood particles 1a & 1b were wood particles and wood shavings, the
wood particles 1c were highly refined wood fiber used in MDF production. The wood particles
(Figure 1a) had a thicker, but a relatively shorter and narrower shape compared to 1b, with a
length from 1mm to 50mm and width from 1mm to 5mm, the wood shavings (Figure 1b) had a
roughly round and thin shape with a diameter from 2mm to 30mm. The highly refined wood
fiber (Figure 1c) were very fine, they were as fine as wood powder.

(a) wood particles

(b) Wood shavings

(c) highly refined wood fiber

Figure 1: Types of the wood particles
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3.2.2 Moisture content
According to pervious research (Tůmová et al. 2017), the desired moisture content (MC) of the
wood particles is 12% before applying casein adhesive. The moisture content of wood particles
obtained from West Fraser WestPine MDF company (mcsd) was measured to be at 6%. Thus, a
few grams of water were added to the particles to increase the MC ratio to 12%. The amount of
water that was added was calculated via the moisture content equation (eq. 1) (Wimmers et al.
2019).
=

×

×

(eq. 1)

Where mcd is the desired moisture content (MC) of the wood particles (which was 12%), msd is
the mass of sawdust (which is the actual mass of the wood particles used for each mixture), mcsd
is the moisture content of sawdust (was 6% for the wood samples used), mH2O is mass of added
water, mcH2O is the moisture content of water (which is 100%) since the mass of sawdust was
known for preparing each sample, the mass of added water can be determined via the moisture
content equation.
3.2.3 Adhesive
Casein adhesive was selected for binding the wood particles together as it is a natural and ecofriendly glue. It has been used in the woodworking industry for more than 100 years. The main
reason for selecting casein is its strong binding ability with wood particles and its ability to cure
at colder temperatures, which makes the production process easier. Casein is a family of related
phosphoproteins (α-s1 Casein, α-s2 Casein, β-Casein, and κ-Casein). It is extracted from cow's
milk, 80% of the protein in cow's milk is casein (Fisher Scientific, n.d.). The casein adhesive
used for this project was casein sodium salt, which is the most common form of casein. It was

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purchased from Thermo Fisher Scientific (USA) and was used without further purification. It is
presented in the form of a yellow powder (Figure 2: Casein).
The casein adhesive needs to be mixed in the correct ratio to water, and hydrated lime, or sodium
hydroxide before using. Two formulas, developed by U.S Forest Products Laboratory (1967)
have been used for this project. In the first casein adhesive formula, the glue is prepared with
casein, water, and sodium hydroxide, this formula has high dry strength and long working life,
but poor water resistance. In the second casein adhesive formula, the glue is prepared with
casein, water, hydrated lime, and copper chloride, this glue has a high-water resistance but a
short working life. Based on the properties of these two adhesives, the second formulate was
adapted for this project, because water resistance is an essential aspect for insulation panels.
Thermal insulation panels are more likely exposed to water or at least high levels of humidity
towards the outside of a wall assembly. As this glue has a short working life, it had to be used
immediately after it was mixed.
The chemicals that were used for the formulation of the casein glues including hydrated lime
(Ca(OH)2), silicate of soda (Na2Si3O7) and copper chloride (CuCl2) was purchased from Laballey
(USA). Hydrated lime is presented in the form of a white powder (Figure 2: hydrated lime);
silicate of soda is presented in the form of a transparent thick liquid (Figure 2: silicate of soda)
and copper chloride is presented in the form of a blue powder (Figure 2: copper chloride).
3.3 Board preparation
The first step was to determine the mass of the wood particles used for the samples. The first and
second wood particles (Figure 1 a & b) are rough processed wood particles and shavings and
they had been mixed by a ratio of 1: 1 before mixed with the fine processed highly refined wood

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fiber used in MDF production (Figure 1c). The mixing ratio of rough processed wood particles
and shavings and fine processed wood fiber, board density is shown in Table 1. The initial trial
eliminated the board that formed with a low density (i.e. density at 100 kg/m3), and with a low
proportion of the wood/glue ratio (e.g. wood: glue of 80:20) and with a panel made by 100%
wood fibers and shavings, as these panels showed little consistency and strength as the panels
break apart after formation.
Table 1: Board preparation final plan
Category

A
B
C
D

Mixing ratio
Wood particles &
shavings (%)
50
30
0
70

Density (kg/m3)

wood fiber (%)

Glue
(%)

50
70
100
30

40/30
40/30
40/30
40/30

200/250/300
200/300
200/300
200/300

As a result, the adjusted plan was determining to prepare four mixing ratio of wood particles,
wood shavings, and wood fiber which were 70:30, 50:50, 30:70, 0:100 based on weight
respectively. The mixing ratios of casein adhesive and wood particles based on weight was
determined to be 40:60 and 30:70 respectively. Each panel was pressed to reach a density of 200
and 300 kg/m3 respectively. Additionally, for the mixing ratio of wood fibers and shavings and
sawdust at 50:50, the glue content at 30% and 40%, the panels with the density of 250 kg/m 3
were also produced for investigating the relationship between the density and thermal
conductivity of the panels. For each category of the panel in Table 1, 6 to 7 replicates were
produced for comparison as the actual density of the panels could not achieve the exact required
values. As a result, around 120 panels were produced. Each sample was marked and categorized
in Appendix A-1. According to Appendix A-1, the boards were first divided into 4 primary
categories A, B, C and D which represents the different mixing ratio between the wood fiber, and
20 | P a g e

wood particles, wood shavings, which are 50:50, 70:30, 30:70 and 100:0 respectively. Then, the
boards were further divided into the secondary category 1, 2, 3 and 4 which represents different
density and different wood/adhesive ratio; thus, under each primary category (A, B, C, and D):
Secondary category 1 represents a target density of 200 kg/m3 with a wood/glue ratio of 60:40.
Secondary category 2 represents a target density of 300 kg/m3 with a wood/glue ratio of 60:40.
Secondary category 3 represents a target density of 200 kg/m3 with a wood/glue ratio of 70:30.
Secondary category 4 represents a target density of 300 kg/m3 with a wood/glue ratio of 70:30.
Secondary category 5 represents a target density of 250 kg/m3 with a wood/glue ratio of 60:40.
Secondary category 6 represents a target density of 250 kg/m3 with a wood/glue ratio of 70:30.
3.4 Adhesive preparation
Table 2 (CASEIN GLUE FORMULA NO. 11) shows the casein glue formula (U.S Forest
Products Laboratory, 1967) that was adopted in this research. The casein adhesive was
formulated by following the ingredient percentages in CASEIN GLUE FORMULA NO. 11
shown in Table 2. The main chemicals in this formula were hydrated lime (Ca(OH)2), silicate of
soda (Na2Si3O7) and copper chloride (CuCl2).
Table 2: Casein Glue Formula No. 11
Ingredients
Casein
Water
Hydrated lime
Water
Silicate of soda
Copper chloride
Water
Total

Parts by weight (g)
100
220-230
20-30
100
70
2-3
30-50
578

Parts by percentage (%)
17.3
38.7-39.8
3.49-5.15
17.3
12.1
0.519-0.862
5.38-8.65
100

21 | P a g e

The glue formulation process is illustrated in Figure 2. Firstly, the casein and water were placed
in the glass bottle onto a stirring hot plate (Figure 2), the paddle was rotated stirring the mixture
until all the casein has been dissolved in the water. The copper chloride was placed in a solution
and poured into the mixture of casein in a thin stream before the lime is added. When casein and
copper chloride were combined they form large lumps, thus the mixture was stirred vigorously
by a kitchen blender until the lumps of copper chloride with casein were broken up and finally
disappeared. Simultaneously, the hydrated lime was mixed with water in a separate container, the
mixture of hydrated lime was being stirred to keep the lime in suspension before the mixture was
poured quickly into the united mixture of casein and copper. Lastly, the solution of casein,
copper chloride, and hydrated lime was being continually stirred by a kitchen blender until they
were homogenous before sodium silicate was added. Finally, the mixture was stirred until it
because a smooth violet-colored and consistent liquid.

22 | P a g e

Figure 2: Formulation of Casein Glues
3.5 Panel formation
3.5.1 Ratio of glue to wood particles
Firstly, the prepared casein glue needed to be diluted, because the initial casein adhesive
prepared according to the formula is for bonding wood panels. For bonding wood particles, the
viscosity of the glue was too high that it was difficult to mix the glue evenly and homogenously
with the wood particles. After a few initial experiments, the ratio of casein glue and water ratio

23 | P a g e

was determined between 1:1.5 for 40% glue boards and 1:2 for 30% glue boards. At this ratio,
the wood particles can be soaked by the liquid glue completely and the mixture was also not too
runny. Hence, the ratio of wood particles, casein glue, and water were 6:4:6 for 40% glue boards,
7:3:6 for 30% glue boards.
The next step was to determine the mass of the wood particles to be filled into the mold to reach
the right density. The final dimension of the panel was 200 × 200 × 30 mm. The final mass of the
panel was 360 g for the panel to achieve a target density of 300 kg/m 3, and 240 g for the panel to
achieve a target density of 200 kg/m3. The mass of the wood particles and glues were calculated
based on the final weight of the sample, the mass of wood particle and adhesive are shown in
Table 3. The glue to wood particle had a ratio of 40:60, and the mass percentage of casein glue
ingredients was 20% of the total dry sample mass. For the glue and wood particle ratio of 30:70,
the mass percentage of casein glue ingredients was around 12.8% of the total dry sample mass.
Table 3: The amount of wood particles used for samples
Panel category

Mass of wood
particles (g)

Mass of glue
ingredients (g)

200

Amount of glue
before dilution
(g)
133

40

Mass % of glue
ingredients in
dry sample (%)
20

Density 200 kg/m3
40% Glue
Density 300 kg/m3
40% Glue
Density 200 kg/m3
30% Glue
Density 300 kg/m3
30% Glue

300

200

60

20

212.7

91.1

27

12.70

319

137

41

12.85

3.5.2 Mix wood particles with casein adhesive
Firstly, the wood shavings, wood fibers, and sawdust were mixed according to the different
percentages shown in Table 1. In the meantime, the casein glue was prepared and diluted, then

24 | P a g e

was poured into the wood particle mixture (Figure 3a). Next, the paint mixer connect to a drill
was put into the bucket and rotated via the drill to mix the wood particles thoroughly for 5 to 10
minutes (Figure 3b) until a homogenous mixture was obtained (Figure 3c).

(a) Pouring adhesive

(b) Rotating the mixer

(c) Homogenous of mixture

Figure 3: Steps to mix glue with wood particles
The blended particles were formed by hand using a forming mold (Figure 4a). After forming, the
fiber was pre-pressed by hand and covered with a lid (Figure 4b). Then a certain amount of
pressing pressure was applied using clamps (Figure 4c) and pressed the samples into the
specified density to a thickness of 30mm. The whole process was done within 30 minutes due to
the start of hardening of the casein adhesive.

(a) Putting mat into the mold

(b) Putting lid on mold

(c) Pressing via clamps

Figure 4: Transfer the mixture into the mold and press
25 | P a g e

3.5.3 Results
After the samples with 200 kg/m3 density were pressed, the clamps were ready to be released
after 4 hours. The samples with a density of 300 kg/m 3 took a longer time to press, and clamps
were ready to be released after 24 hours. After releasing the clamps, the samples were kept in the
laboratory environment until they were fully hardened and were ready to be de-molded after 48
to 96 hours. Then, the samples were kept in the laboratory environment for 7 days to fully
mature, followed by drying for 8 hours at 100 °C to fully evaporate the water contained in the
samples, and to measure the dry mass of each board. By taking the above methods, a total of 123
samples were formed. The picture was taken and shown in Appendix A-2.
3.6 First evaluation of the consistency of the panels by observations
The process of forming the panels is simple and triggers fairly low cost; thus, it is potentially
economical to produce the panels. The panels made from mixing of wood particles with casein
adhesive showed good appearance and consistency for the tested mixing ratio of sawdust, wood
shavings, and wood fibers with casein adhesive with a density between 200 and 300 kg/m3. The
feasibility samples produce with a density of 2100 kg/m3 were falling apart and therefore not
further examined. The boards with a higher density of 300 kg/m 3 were appearing firmer than the
board with a lower density of 200 kg/m3, because it took a higher force to break them by hand.
The boards that were formed with 30% highly refined MDF wood fiber and 70% wood shavings
and particles showed the worst stability because some wood particles were dropping from the
board when it was dropped from 1 meter above the ground. The boards that formed with 100%
sawdust showed the best stability, because there were no loose wood fibers dropping when the
board was dropped from 1 meter above the ground. The boards that were formed with 70%
highly refined MDF wood fiber and 30% wood shavings and particles showed the next best

26 | P a g e

stability, as there were only a little loose wood fiber dropping when the board was dropped from
1 meter above the ground. The target density of 300 kg/m3 was never fully achieved as the
boards tended to expand after de-molding. Additionally, the content of glue (30% & 40%) did
not have a significant effect on the stability of the samples.
The following limitations were found: A low density of the panel (e.g. density at 100kg/m 3)
could not be achieved; these panels were breaking apart after formation. Potentially this is
happening because the gaps between the wood fibers are too large so that they cannot
sufficiently contact each other. Secondly, the panels cannot be formed using 100% of the coarse
wood particles. Potentially because the gaps between the coarse particles are too large so that
they cannot sufficiently touch each other, thus some of the fine particles need to be used to fill in
the gaps to form the panels. Thirdly, a low proportion of the wood/glue ratio (e.g. wood: glue of
80:20) could not be achieved due to the lower binding ability of casein adhesive compared to the
synthetic adhesives. All the three limitation factors require further research.

27 | P a g e

Chapter 4: Experimental Study
Several experiments were conducted to measure the mass, volume, resulting density, and thermal
conductivity of the formed samples. The test equipment, sample preparation, and test procedures
are also explained in this section.
4.1 Determination of density and moisture content
4.4.1 Determination of dimensions, moisture content and density of the sample
The dimensions and apparent density of the samples were determined according to ASTM C30321 (2021), the moisture content of the samples was determined according to ASTM C1616-07
(2018). These standards illustrate the apparatus and procedures for determining the dimensions,
density and moisture content under reference conditions.
4.1.2 Dimension measurement procedures
All the 123 samples with a target formation dimension of 200×200×30 mm was prepared for
dimension measurement. The samples were placed into a room with a temperature around 22°C
with relative humidity of around 20% for 21 days for conditioning. After conditioning, a caliper
was used to measure the dimensions. Three measurements were taken for both the width and
length of the specimen. They are measured in three locations with 50 mm apart from each other
and 25 mm from the two edges. The thickness was measured along the edges in four different
locations, each measurement was taken in 50 mm from the corner. Then, the average values of
width, length, and thickness of the specimen were calculated and recorded.
4.1.3 Mass measurement procedures
All the 123 samples were prepared for mass measurement under three conditions. Firstly, the
moisture-free weight of the samples (WMF) was obtained by an oven drying method, the samples
28 | P a g e

were dried in an air-circulating oven at a temperature of 100 °C for 8 hours at 100 °C according
to ASTM C1616-07. The weight of the samples was taken one time per hour after 4 hours until
the difference of the last two weight measurements was less than 1 gram to ensure the water was
fully vaporized. Then, the weight of the samples (Wf) with a temperature of around 22°C with a
relative humidity of around 20% was also measured after conditioning the samples in the normal
room for another 21 days. Finally, the weight of the samples (Wf) at a temperature of around
22°C with a relative humidity of around 50% was also measured after conditioning the samples
for 21 days until they had reached moisture equilibrium according to ASTM C870-11.
4.1.4 Calculation of the density and moisture content of the samples
According to ASTM C303-21 (2021), the volume of each sample was calculated from the
average width, length, and thickness obtained from section 4.2.2 via the volume equation (eq. 2).
Volume, m 3 = length × mm × width, mm × thickness, mm, m 3 ×10-9

(eq. 2)

Then, the density of the specimen from the measured mass in section 4.2.3 and calculated
volume was calculated via equation 3.
Density, kg/m =

,

,

(eq. 3)

According to ASTM C1616-07 (2018), the moisture content of each sample was calculated via
equation 4 (eq. 4).
M = 100% × [

] (eq. 4)

Where Wf is the specimen weight, WMF is the moisture-free weight which was both determined
in section 4.2.3.

29 | P a g e

4.2 Determination of thermal conductivity
4.2.1 Terminology
ASTM C168-19 (2019) defines thermal conductivity (λ) as the time rate of steady state heat flow
(i.e. the quantity of heat transferred to or from a system in unit time, W) through a unit area (1
m) of a homogeneous material induced by a unit temperature gradient (1 K) in a direction
perpendicular to that unit area. It is expressed in W/mK. Thermal resistance (R) is defined
(ScienceDirect, n.d) as the ratio of the temperature difference between the two faces of a material
to the rate of heat flow per unit area. Thermal resistance determines the heat insulation property
of a insulation material. The higher the thermal resistance, the lower is the heat loss. It is
expressed in m 2 K/W.
4.2.2 Test machine and principles
The thermal conductivities of the specimens were determined in accordance with ASTM C51817. This standard specifies the test method for Steady-State Thermal Transmission Properties by
means of a Heat Flow Meter (HFM) apparatus. The HFM-100 test machine that was used in this
project shown in Figure 5 was manufactured by ThermTest Inc, Canada and freshly calibrated
before the tests. Once a specimen is placed into the HFM, the plates will automatically clamp the
sample with a pressure of 2.5 kPa. Then, one-dimensional heat flux through the test specimen is
established by applying two constant but different temperatures of the two plates. The heat flux
is measured by the transducers located inside the HFM. The thermal resistance of the test
specimen shall be greater than 0.10 m2K/W, and the temperature difference between the hot plate
and the cold plate shall be greater than 10°C to ensure the accuracy of the measurement.

30 | P a g e

Figure 5: A picture of the Heat Flow Meter (HFM)
4.2.3 Preparing samples and testing procedure
The tests of 123 samples at two different moisture states were performed which were conditioned
to a temperature around 22°C with relative humidity around 20% and 50% respectively. The
20% room humidity was achieved by conditioning the specimens in the normal room in the
UNBC research lab, the 50% room humidity was achieved by conditioning the specimens in the
UNBC research lab conditioning chamber. The masses of the specimens were measured
throughout the conditioning period until the differences of the last two measurements were less
than 1 gram to ensure the moisture had reached equilibrium. After conditioning, each specimen
was placed into a plastic bag, then immediately transferred into the HFM for testing to ensure the
exchange of moisture between the specimen and the surrounding was at a minimum.

31 | P a g e

4.2.4 Thermal conductivity measurements
In the HFM, the specimen was placed between two plates with two different closely-controlled
temperatures. The temperature ranging from -20°C to 70°C can be set in the HFM depending on
the external cooling capacity in order to create a temperature gradient so that the heat flow can
be created. The heat flow will vary if the temperature difference changes, thus the thermal
conductivity value of one specimen will also change. However, for simplification, the
temperature of the two plates were kept the same throughout all the tests. The temperature of the
upper plate was set at 40°C, and the temperature of the lower plate was set at 10°C, so that the
heat flow direction was from upper plate to lower plate. The thermal conductivity (W/mK) and
thermal resistance (m2K/W) of the specimen values were automatically generated after the test
was completed.

32 | P a g e

Chapter 5: Experimental results and discussions
The results of the experiments carried out for determining density, moisture content, and thermal
conductivity are presented in this section.
5.1 Specimen density and moisture content
The densities of the samples under three conditions were calculated using Eq. 3 as described in
section 4.1.4. The density of all the samples can be found in Appendix A-3. The moisture content
of the samples under two conditions is calculated using Eq. 4 as described in section 4.1.4. The
moisture content of all the samples can be found in Appendix A-4.
The density results of the samples in each category as defined in section 3.2 are presented in
Figures 6, 7 & 9. The x-axis represents the category of each formed sample as defined in section
3.2; the y-axis represents the density. The moisture content results of the samples in each
category are presented in Figures 8 & 10. The x-axis represents the category of each formed
sample as defined in section 3.2; the y-axis represents the moisture content.
Figure 6 is the oven-dried densities of all the samples. The actual average density of oven dried
samples is given in Table 4. The actual densities of the oven dried boards are in the range of 157201 kg/m3, 205-209 kg/m3, and 219-322 kg/m3 respectively.
Table 4: Actual average density of oven dried samples
Panels
ρ kg/m3
Panels
ρ kg/m3

A1
A2
A3
A4
184.89 261.13 174.98 263.18
C1
C2
C3
C4
183.78 254.50 175.61 239.91

A5
A6
B1
B2
B3
B4
203.01 189.23 188.55 263.99 185.44 255.44
D1
D2
D3
D4
190.35 276.56 176.70 247.08

33 | P a g e

Actual density of oven dried panels
350

Sample Density (kg/m3)

300
250

Sample1

Sample2

200

Sample3

150

Sample4
Sample5

100

Sample6

50
0

Sample7
A1

A2

A3

A4

A5

A6

B1

B2

B3

B4

C1

C2

C3

C4

D1

D2

D3

D4

Sample Category

Figure 6: Actual density of oven dried panels
Figure 7 is the densities and Figure 8 is the moisture content at which the samples that are
conditioned to a temperature around 22°C with relative humidity around 20% respectively. The
actual average density of each group as defined in section 3.2 is given in Table 5. The actual
densities are in the range of 170-230 kg/m 3, 218-222 kg/m3, and 250-340 kg/m 3 for the target
board densities of 200, 250, and 300 kg/m3 with moisture contents ranging from 5.66%-6.82%,
6.54%-6.61%, and 5.12%-7.12% respectively. The actual densities of the in the 20% relative
humidity are approximately 6% higher than oven-dried samples.
Table 5: Actual average density of samples at 20% relative humidity
Panels
ρ kg/m3
Panels
ρ kg/m3

A1
A2
A3
A4
A5
A6
B1
B2
B3
196.03 276.38 185.29 278.97 215.52 201.02 200.41 280.68 196.9
C1
C2
C3
C4
D1
D2
D3
D4
195.17
271.7 186.38 253.56 201.29 291.22 187.03 259.67

B4
270.16

34 | P a g e

Actual density of panels at 20% relative humidity
400

Sample Density (kg/m3)

350
300

Sample1

250

Sample2

200

Sample3

150

Sample4
Sample5

100

Sample6

50
0

Sample7
A1

A2

A3

A4

A5

A6

B1

B2

B3

B4

C1

C2

C3

C4

D1

D2

D3

D4

Sample Category

Figure 7: Actual density of panels at 20% relative humidity

Actual moisture content of panels at 20% relative humidity
0.08

moisture content

0.075
0.07

Sample1

0.065

Sample2

0.06

Sample3

0.055

Sample4
Sample5

0.05

Sample6

0.045
0.04

Sample7
A1

A2

A3

A4

A5

A6

B1

B2

B3

B4

C1

C2

C3

C4

D1

D2

D3

D4

Sample Category

Figure 8: Actual moisture content of panels at 20% relative humidity

35 | P a g e

Figure 9 contains the densities and Figure 10 contains the moisture content at which the samples
that were conditioned to a temperature around 22°C with relative humidity around 50%
respectively. The actual average density of each group as defined in section 3.2 is given in Table
6. The actual densities are in the range of 175-225 kg/m3, 227-232 kg/m3, and 264-355 kg/m3 for
the target board densities of 200, 250, and 300 kg/m3 with moisture contents ranging from
10.60%-11.76%, 10.11%-11.98%, and 9.74%-12.28% respectively. The actual densities of the in
the 50% relative humidity are approximately 4% higher than that in 50% relative humidity.
Table 6: Actual average density of samples at 50% relative humidity
Panels
ρ kg/m3
Panels
ρ kg/m3

A1
A2
A3
A4
A5
A6
B1
B2
B3
204.79 290.23 193.98 291.81 225.01 210.03 208.64 292.87 205.3
C1
C2
C3
C4
D1
D2
D3
D4
203.69 282.26 194.55 265.89 209.87 305.65 194.77 272.46

B4
283.42

Actual density of panels at 50% relative humidity
400

Sample Density (kg/m3)

350
300

Sample1

250

Sample2

200

Sample3

150

Sample4
Sample5

100

Sample6

50
0

Sample7
A1

A2

A3

A4

A5

A6

B1

B2

B3

B4

C1

C2

C3

C4

D1

D2

D3

D4

Sample Category

Figure 9: Actual density of panels at 50% relative humidity

36 | P a g e

Actual moisture content of panels at 50% relative humidity
0.13

moisture content

0.125

0.12

Sample1

0.115

Sample2

0.11

Sample3

0.105

Sample4
Sample5

0.1

Sample6

0.095
0.09

Sample7
A1

A2

A3

A4

A5

A6

B1

B2

B3

B4

C1

C2

C3

C4

D1

D2

D3

D4

Sample Category

Figure 10: Actual moisture content of panels at 50% relative humidity
The density and the moisture content results are used to study the influence of moisture on the
thermal and mechanical performances of the samples. Overall, the actual densities of the formed
sample do not achieve the exact target board densities because each panel was formed separately
one by one that resulted in a little inconsistency in the actual density. The panels that formed
with a target density of 300 kg/m3 showed more variation than with a target density of 200 kg/m 3
because forming the larger density board requires a larger pressure and it is difficult to control
the pressure when manually forming these panels. Moreover, larger density boards tend to
expand during the drying process once the pressure is released after 24 hours. As a result, most
of the larger density boards do not reach the 300 kg/m3 target density especially for the larger
wood particle size panels, such as C4 samples only reached a density of 250 kg/m 3 (20%
humidity). As expected, the density of the samples increased as the relative humidity of the
environment increased since in a more humid condition more moisture going into the samples to
reach the moisture balance.
37 | P a g e

The moisture contents of the boards that conditioned to 20% relative humidity were between
5.1% and 6.3% with an average of 5.968%, the moisture contents of the boards that conditioned
to 50% relative humidity were between 10.2% and 11.1% with an average of 10.72%. This
research shows that the moisture content of samples is affected dramatically by the relative
humidity. The moisture content increased approximately 80% with an increase of the relative
humidity from 20% to 50%. Additionally, this preliminary result also shows that the density of
the board (200 & 300 kg/m3) does not show a significant affect with the changes of the moisture
content of the samples under different relative humidity conditions; however, the wood particle
size has a slight effect on the moisture content of the samples under different relative humidity
conditions. The average moisture content of the boards formed by 100% sawdust (category D)
was 5.5% and 10.3% under the relative humidity of 20% and 50% respectively which were
significantly lower than the other three categories. However, due to the lack of sufficient data
(i.e. the moisture content of the samples under more different relative humidity conditions), the
relationships between particle size and the moisture content of the samples under different
relative humidity conditions require further investigation.
5.2 Specimen thermal conductivity
The thermal conductivity measured by the Heat Flow Meter for each category of specimens can
be found in Appendix A-5. Appendix-5 presents the thermal conductivity values of specimens

measured via steady-state heat flux measurement method using a Heat Flow Meter as described
in section 4.2 for both relative humidity around 20% and 50% conditioned samples. The values
are measured for the case of a 30°C temperature difference between two measurement plates
with a mean temperature of 25°C (Top plate @ 10°C, bottom plate @ 40°C). According to
Cetiner et. al (2018), the thermal conductivity of the sample will increase with the increasing of

38 | P a g e

the ambient temperature; however, the schedule of this project is limited, this research does not
test the samples under different temperatures and investigate the relationship between the
ambient temperature and thermal conductivity of these samples.
All the thermal conductivity results from Appendix A-5 (Category A, B, C, D) is plotted
separately as a linear function of corresponding sample density, as shown in Figures 11, 12,13 &
14. Figure (a) in each category plotted the results of samples with a wood/glue ratio of 6:4,
Figure (b) in each category plotted the results of samples with a wood/glue ratio of 3:7. Two
linear functions were generated in each figure which was the high moisture content (MC @
10.72%) and low moisture (MC @ 5.968%) content lines. All the figures indicate that the
correlation between thermal conductivity and board density is high. The correlation factor R2 of
all the graphs has a range between 0.80 and 0.97. Especially, the thermal conductivity of samples
in categories A, B, C, and D increased as the average board density increased. As the board
density increases, voids within the board are decreased. The heat flow transfers through solid
substance and void, while the thermal conductivity of air within the voids is much lower than
that of solid substance, which lead to a lower thermal conductivity of the whole material (Zhou
et. al, 2010).
Table 7: Thermal conductivities at 200, 250, & 300 kg/m3 of each category
MC &
Density
MC low 200
MC low 250
MC low 300
MC high 200
MC high 250
MC high 300

A(6:4).λ.
(W/mK)
0.0619
0.0659
0.0699
0.0666
0.0716
0.0766

A(7:3).λ.
(W/mK)
0.0617
0.0657
0.0697
0.0675
0.0725
0.0775

B(6:4).λ.
(W/mK)
0.0623
0.0668
0.0713
0.0683
0.0733
0.0783

B(7:3).λ.
(W/mK)
0.0603
0.0653
0.0703
0.0640
0.0690
0.0740

C(6:4).λ.
(W/mK)
0.0626
0.0676
0.0726
0.0658
0.0708
0.0758

C(7:3).λ. D(6:4).λ.
(W/mK) (W/mK)
0.0628
0.0572
0.0668
0.0622
0.0708
0.0672
0.0610
0.0659
0.0660
0.0709
0.0710
0.0759

D(7:3).λ.
(W/mK)
0.0565
0.0615
0.0665
0.0625
0.0675
0.0725

39 | P a g e

The approximation of thermal conductivities at 200, 250, & 300 kg/m 3 of each category were
summarized in Table 7. The values in Table 7 were obtained via the trend line equation from
Figures 11, 12,13 & 14. Knowing that material is qualified as an insulator when its thermal
conductivity is less than 0.1 W/mK, the boards formed in the research can be considered as
insulation materials because the samples that conditioned at 20% relative humidity had thermal
conductivities ranging from 0.057 to 0.076 W/mK. The samples that conditioned at 50% relative
humidity had thermal conductivities ranging from 0.063 to 0.078 W/mK with the density from
200 to 300 kg/m3. As expected, the average thermal conductivity of all the samples (Category A,
B, C, D) increased by approximately 6% as the average moisture content increased from 5.968%
to 10.72%. As the thermal conductivity of water is much higher than that of air within the voids,
once the moisture content of the sample increases, this means more voids are occupied by water
which resulted in a higher thermal conductivity value. Additionally, comparing the thermal
conductivities of each category at the density of 200, 250, 300 kg/m3 showed that the boards that
formed via 100% sawdust (Category D) were slightly lower than the mix ratio between the wood
fibers, shavings, and sawdust at other proportions (Category A, B, C). Thus, the boards that
formed via 100% sawdust (Category D) had the best thermal performance; however, the
difference is too small that within the experiment error arrange that more data is required to
support this conclution. Finally, the wood/glue ratio did not have a significant effect on the
thermal conductivity of the samples.

40 | P a g e

Thermal conductivity vs. density

y = 0.0001x + 0.0466
R² = 0.851

0.08

y = 0.0001x + 0.0475
R² = 0.9199

0.08

0.07

0.07

0.06

0.05

Thermal conductivity vs. density

0.09

Thermal conductivity (W/mK)

Thermal conductivity (W/mK)

0.09

0.06

y = 8E-05x + 0.0459
R² = 0.8401

0.05
150

200

250

Sample Density (kg/m3)

A1 MC low
A5 MC low
A2 MC high
Linear (A1A2A5low)

300

350

y = 8E-05x + 0.0457
R² = 0.8587

150

200

250

A3 MC low
A6 MC low
A4 MC high
Linear (A3A4A6low)

A2 MC low
A1 MC high
A5 MC high
Linear (A1A2A5high)

(a) wood/glue ratio 6:4

300

Sample Density (kg/m3)

350

A4 MC low
A3 MC high
A6 MC high
Linear (A2A4A6high)

(b) wood/glue ratio 7:3

Figure 11: Thermal conductivity vs. sample density of category A

0.08

Thermal conductivity vs. density
y = 0.0001x + 0.0483
R² = 0.8193

0.075
0.07

0.065
y = 9E-05x + 0.0443
R² = 0.8023

0.06

0.055

150

200

250

300

Sample Density (kg/m3)

B1 MC low
B1 MC high
Linear (B1B2low)

350

400

B2 MC low
B2 MC high
Linear (B1B2high)

(a) wood/glue ratio 6:4

Thermal conductivity vs. density

0.085

Thermal conductivity (W/mK)

Thermal conductivity (W/mK)

0.085

y = 0.0001x + 0.044
R² = 0.9414

0.08
0.075
0.07
0.065

y = 0.0001x + 0.0403
R² = 0.943

0.06
0.055

150

200

250

300

Sample Density (kg/m3)

B3 MC low
B3 MC high
Linear (B3B4high)

350

B4 MC low
B4 MC high
Linear (B3B4low)

(b) wood/glue ratio 7:3

Figure 12: Thermal conductivity vs. sample density of category B

41 | P a g e

0.08

Thermal conductivity vs. density
y = 0.0001x + 0.0458
R² = 0.886

0.075

0.08
y = 0.0001x + 0.041
R² = 0.8803

0.075

0.07

0.065

0.07

0.065

y = 1E-04x + 0.0426
R² = 0.884

0.06

0.055

Thermal conductivity vs. density

0.085

Thermal conductivity (W/mK)

Thermal conductivity (W/mK)

0.085

150

200

250

300

Sample Density (kg/m3)

C1 MC low
C1 MC high
Linear (C1C2low)

350

y = 8E-05x + 0.0468
R² = 0.8121

0.06

0.055

150

200

250

C4 MC low
C4 MC high
Linear (C3C4low)

C2 MC low
C2 MC high
Linear (C1C2high)

(a) wood/glue ratio 6:4

300

Sample Density (kg/m3)

C3 MC high
C3 MC low
Linear (C3C4high)

(b) wood/glue ratio 7:3

Figure 13: Thermal conductivity vs. sample density of category C

Thermal conductivity vs. density
y = 0.0001x + 0.0459
R² = 0.9399

0.08

y = 0.0001x + 0.0425
R² = 0.9218

0.08

0.075

0.075
0.07

0.07

0.065

0.065
y = 0.0001x + 0.0372
R² = 0.9444

0.06

0.055

Thermal conductivity vs. density

0.085

Thermal conductivity (W/mK)

Thermal conductivity (W/mK)

0.085

150

200

250

Sample Density (kg/m3)

D1 MC low
D1 MC high
Linear (D1D2low)

300

350

D2 MC low
D2 MC high
Linear (D1D2high)

(a) wood/glue ratio 6:4

y = 0.0001x + 0.0365
R² = 0.9687

0.06

0.055

150

200

250

Sample Density (kg/m3)

D3 MC low
D3 MC high
Linear (D3D4low)

300

D4 MC low
D4 MC high
Linear (D3D4high)

(b) wood/glue ratio 7:3

Figure 14: Thermal conductivity vs. sample density of category D

42 | P a g e

Chapter 6: Conclusion
6.1 Objective accomplishment
In this project, the boards with a dimension of 200 × 200 × 30 mm were successfully formed by
using wood particles. The first objective was to investigate the mixing ratios of wood fibers and
shavings and sawdust so that the boards can be successfully formed. The results showed that the
boards can be formed with a mixing ratio of the wood fibers and shavings and sawdust at 70:30,
50:50, 30:70, 0:100. The boards cannot be formed using 100% of the coarse wood particles
because the gaps between the coarse particles are too large that they cannot sufficiently touch
each other and to the glues.
The second objective was to prove that forming wood-based insulation boards using 100% bioadhesive is achievable. The casein adhesive has a strong binding ability and a simple curing
requirement which makes the embodied energy of the board relatively low. However, the casein
adhesive percentage within the board in this research has a range between 12% to 20% which
was higher than the synthetic adhesive proportion in the mineral or fossil-based insulation
materials.
For the third objective, the thermal conductivity values of boards with different densities and
moisture content ranged from 0.057 to 0.078 W/mK which satisfied the minimum requirement
(i.e. 0.1 W/mK) in the ASTM insulation Standard. The conclusion of the performance of the
board in each category can be found as following points:
1. The glue portion (30% & 40%) does not have a significant effect on either the appearance
or on the thermal conductivity of the samples.

43 | P a g e

2. The thermal conductivity of the board increased with an increase in the density and
moisture content of the board. Additionally, the boards that had a higher density of 300
kg/m3 were firmer than the board with a lower density of 200 kg/m 3, as it took a higher
force to break by hand.
3. The boards that formed via 100% highly refined MDF wood fiber (Category D) had the
best thermal performance as the thermal conductivities values of Category D were slightly
lower than the mix ratio between the wood particles, shavings, and wood fibers at other
proportions (Category A, B, C).
4. Overall, the boards that formed via 100% wood fibers (Category D) had the best
appearance as there were no wood fibers dropping when the board was shaken heavily and
the best thermal performance as it had a relatively low thermal conductivity value
compared to the other groups (Category A, B, C).
6.2 Applications
This casein bonded wood-based board could be used as an eco-friendly thermal insulation material
although it has a higher thermal conductivity value compared to current mineral or fossil-based
insulation materials in the construction market. It could be used as an insulation material in timber
frame wall construction. Further research is needed to optimize the thermal performance by
adjusting the ratio and density. Durability, fire resistance, mold resistance and other aspects have
to be explored further before this material can be used in construction.
6.3 Further works and suggestions
There are several limitations that existed in this project which require further investigations. The
suggestions are as following:

44 | P a g e

1. Wood particles are used as the raw materials forming the boards; however, the thermal
conductivity of the board is higher than expected, this could be potentially improved by
adapting different natural fibers such as straw, hay, hemp, wool, cotton, or wheat hulls as
the literature review shows that some of these materials have a better thermal performance
than wood particles.
2. This research discovered that the formed boards will have mold problems if the temperature
remains around 22°C with a relative humidity above 60% because the casein glue contains
protein which favors the growth of mold according to the CASEIN GLUE FORMULA
(U.S Forest Products Laboratory, 1967). This can be eliminated by adding more copper
salts and other chemicals.
3. Furthermore, additional physical tests such as dimensional stability, water absorption,
accelerated aging tests, and mechanical tests including flexure strength, elastic modulus,
compressive strength and tensile strength tests, fire and mold resistance and sound
absorption should be conducted.

45 | P a g e

References
ASTM International. C168-19 Standard Terminology Relating to Thermal Insulation. West
Conshohocken, PA; ASTM International, 2019. doi: https://doi.org/10.1520/C0168-19
ASTM International. C303-21 Standard Test Method for Dimensions and Density of Preformed
Block and Board–Type Thermal Insulation. West Conshohocken, PA; ASTM International,
2021. doi: https://doi.org/10.1520/C0303-21
ASTM International. C518-17 Standard Test Method for Steady-State Thermal Transmission
Properties by Means of the Heat Flow Meter Apparatus. West Conshohocken, PA; ASTM
International, 2017. doi: https://doi.org/10.1520/C0518-17
ASTM International. C165-07(2017) Standard Test Method for Measuring Compressive
Properties of Thermal Insulations. West Conshohocken, PA; ASTM International, 2017. doi:
https://doi.org/10.1520/C0165-07R17
ASTM International. C870-11(2017) Standard Practice for Conditioning of Thermal Insulating
Materials. West Conshohocken, PA; ASTM International, 2017. doi:
https://doi.org/10.1520/C0870-11R17
ASTM International. C1616-07(2018) Standard Test Method for Determining the Moisture
Content of Organic and Inorganic Insulation Materials by Weight. West Conshohocken, PA;
ASTM International, 2018. doi: https://doi.org/10.1520/C1616-07R18
Asdrubali, F., D’Alessandro, F., & Schiavoni, S. (2015). A review of unconventional sustainable
building insulation materials. Sustainable Materials and Technologies, 4, 1–17.
https://doi.org/10.1016/j.susmat.2015.05.002
Belakroum, R., Gherfi, A., Bouchema, K., Gharbi, A., Kerboua, Y., Kadja, M., … Lachi, M.
(2017). Hygric buffer and acoustic absorption of new building insulation materials based on date
palm fibers. Journal of Building Engineering, 12, 132–139.
https://doi.org/10.1016/j.jobe.2017.05.011
Binici, H., Eken, M., Dolaz, M., Aksogan, O., & Kara, M. (2014). An environmentally friendly
thermal insulation material from sunflower stalk, textile waste and stubble fibres. Construction
and Building Materials, 51, 24–33. https://doi.org/10.1016/j.conbuildmat.2013.10.038
Bouajila, J., Limare, A., Joly, C., & Dole, P. (2005). Lignin plasticization to improve binderless
fiberboard mechanical properties. Polymer Engineering & Science, 45(6), 809–816. doi:
10.1002/pen.20342
Cetiner, I., & Shea, A. D. (2018). Wood waste as an alternative thermal insulation for buildings.
Energy and Buildings, 168, 374–384. https://doi.org/10.1016/j.enbuild.2018.03.019
CTCN. (n.d.). Building envelope thermal insulation. Building envelope thermal insulation |
Climate Technology Centre & Network | Tue, 11/08/2016. https://www.ctcn.org/technologies/building-envelope-thermal-

46 | P a g e

insulation#:~:text=Thermal%20insulation%20is%20an%20important,less%20than%200.1W%2F
mK.
COUNTRY PROFILE CANADA. (2018). The energy intensity of the Canadian residential
sector becomes more efficient. Retrieved from https://www.climate-chance.org/wpcontent/uploads/2019/03/en_fp13-canada-residentiel_def-1.pdf
Holt, Greg & Mcintyre, Gavin & Flagg, Dan & Bayer, Eben & Wanjura, John & Pelletier,
Mathew. (2012). Fungal Mycelium and Cotton Plant Materials in the Manufacture of
Biodegradable Molded Packaging Material: Evaluation Study of Select Blends of Cotton
Byproducts. Journal of Biobased Materials and Bioenergy. J. Biobased Mater. Bioenergy. 431439. 10.1166/jbmb.2012.1241.
IBO Osterreichisches Institut Fur Baubiologie Und -Okologie. (2016). Details for passive houses
a catalogue of ecologically rated constructions (3rd ed.). Birkhauser Architecture.
Kienzlen , V., Erhorn, H., Krapmeier , H., Werner , J., & Wagner , A. (2014). The
significance of thermal insulation. KEA Climate Protection and Energy Agency of BadenWürttemberg GmbH.
https://www.buildup.eu/sites/default/files/content/the_significance_of_thermal_insulation.pdf.
Lacoste, C., El Hage, R., Bergeret, A., Corn, S., & Lacroix, P. (2018). Sodium alginate adhesives
as binders in wood fibers/textile waste fibers biocomposites for building insulation.
Carbohydrate Polymers, 184, 1–8. https://doi.org/10.1016/j.carbpol.2017.12.019
Levin D. B.Zhu H.Beland M.Cicek N.Holbein B. E. (2007). Potential for hydrogen and methane
production from biomass residues in Canada. Bioresource Technology, 98(3), 654-660.
https://doi.org/10.1016/j.biortech.2006.02.027.
Mati-Baouche, N., De Baynast, H., Lebert, A., Sun, S., Lopez-Mingo, C. J. S., Leclaire, P., &
Michaud, P. (2014). Mechanical, thermal and acoustical characterizations of an insulating biobased composite made from sunflower stalks particles and chitosan. Industrial Crops and
Products, 58, 244–250. https://doi.org/10.1016/j.indcrop.2014.04.022
Muthuraj, R., Lacoste, C., Lacroix, P., & Bergeret, A. (2019). Sustainable thermal insulation
biocomposites from rice husk, wheat husk, wood fibers and textile waste fibers: Elaboration and
performances evaluation. Industrial Crops and Products, 135, 238–245.
https://doi.org/10.1016/j.indcrop.2019.04.053
NRC. (2017). Energy Efficiency in the Buildings Sector. Retrieved from
https://sencanada.ca/content/sen/committee/421/ENEV/Briefs/BuildingsSector2017-0917FINAL_e.pdf
NRC. (2016). Survey of Commercial and Institutional Energy Use. Retrieved from
https://www150.statcan.gc.ca/n1/en/daily-quotidien/160916/dq160916c-eng.pdf?st=9o7pmwU5
Panyakaew, S., & Fotios, S. (2011). New thermal insulation boards made from coconut husk and
bagasse. Energy and Buildings, 43(7), 1732–1739. https://doi.org/10.1016/j.enbuild.2011.03.015

47 | P a g e

Pereira, C. M. C., Blanchard, C., Carvalho, L. M. H., & Costa, C. A. V. (2004). High frequency
heating of medium density fiberboard (MDF): Theory and experiment. Chemical Engineering
Science, 59(4), 735–745. https://doi.org/10.1016/j.ces.2003.09.038
Tan, R. (2012). THE USE OF P-MDI RESIN IN MDF MANUFACTURE. Retrieved from
https://open.library.ubc.ca › media › download › pdf
Tůmová, E., Drochytka, R., Černý, V., & Čada, P. (2017). Development of Organic and
Biodegradable Insulating Material for ETICS. In Procedia Engineering (Vol. 195, pp. 81–87).
Elsevier Ltd. https://doi.org/10.1016/j.proeng.2017.04.527
U. S. FOREST SERVICE. (1967, March). Casein glues: Their manufacture, preparation, and
application. Retrieved March 25, 2021, from https://books.google.ca/books?id=Wv-lJoiBNvwC
Wang, D., & Sun, X. S. (2002). Low density particleboard from wheat straw and corn pith.
Industrial Crops and Products, 15(1), 43–50. https://doi.org/10.1016/S0926-6690(01)00094-2
Wei, K., Lv, C., Chen, M., Zhou, X., Dai, Z., & Shen, D. (2015). Development and performance
evaluation of a new thermal insulation material from rice straw using high frequency hotpressing. Energy and Buildings, 87, 116–122. https://doi.org/10.1016/j.enbuild.2014.11.026
Wimmers, G., Klick, J., Tackaberry, L., Zwiesigk, C., Egger, K., & Massicotte, H. (2019).
Fundamental Studies for Designing Insulation Panels from Wood Shavings and Filamentous
Fungi. BioResources, 14(3), 5506-5520. Retrieved from
https://ojs.cnr.ncsu.edu/index.php/BioRes/article/view/BioRes_14_3_5506_Wimmers_Designing
_Insulation_Panels/6900
Yang, H. S., Kim, D. J., & Kim, H. J. (2003). Rice straw-wood particle composite for sound
absorbing wooden construction materials. Bioresource Technology, 86(2), 117–121.
https://doi.org/10.1016/S0960-8524(02)00163-3
Zhou, X. yan, Zheng, F., Li, H. guan, & Lu, C. long. (2010). An environment-friendly thermal
insulation material from cotton stalk fibers. Energy and Buildings, 42(7), 1070–1074.
https://doi.org/10.1016/j.enbuild.2010.01.020
https://www.bbc.com/news/science-environment-43120041
https://www.fishersci.fi/shop/products/mp-biomedicals-casein-sodium-salt/11475672
https://www.nrcan.gc.ca/our-natural-resources/forests-forestry/state-canadas-forestsreport/forest-industry-contribute/16517
https://www.sciencedirect.com/topics/engineering/thermal-resistance

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Appendix

A-1: Samples of each category

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A-2: Appearance of the sample in each category
50 | P a g e

No.1.volume

ρ.dry

ρ.MC10

ρ.MC6 No.2.volume

ρ.dry

ρ.MC10

ρ.MC6 No.3.volume

ρ.dry

ρ.MC10

ρ.MC6 No.4.volume

ρ.dry

ρ.MC10

ρ.MC6

Panels
(m3)
(kg/m3) (kg/m3) (kg/m3)
(m3)
(kg/m3) (kg/m3) (kg/m3)
(m3)
(kg/m3) (kg/m3) (kg/m3)
(m3)
(kg/m3) (kg/m3) (kg/m3)
A1
1078609.862 203.9662 225.29 216.9459 1146370.511 177.9529 198.8886 188.4208 1127395.504 195.14 216.428 206.671 1139989.416 191.2298 211.4055 202.6335
A2
1176283.222 278.8444 307.749 294.997 1198440.583 269.5169 297.0527 285.3708 1219732.977 274.6503 307.4443 291.0473 1223949.233 272.8871 306.3853 288.4107
A3
1178891.026 189.1608 208.6707 201.0364 1318134.461 162.3507 179.7996 172.2131 1228077.784 166.9275 184.8417 176.6989 1111136.322 205.1953 229.4948 216.8951
A4
1198541.983 285.3467 319.5549 301.1993 1107448.783 297.0792 328.6834 315.1387 1195408.755 268.5274 296.133 284.4215 1156605.712 283.5884 312.9848 300.8804
A5
1182345.927 217.3645 239.3547 230.0511 1243796.125 209.0375 232.3532 222.7053 1266115.672 194.295 214.8303 206.1423 1335065.991 183.5115 202.9862 194.7469
A6
1330488.529 191.6589 211.9522 203.6846 1526458.29 168.3636 186.0516 178.8454 1246338.147 205.4017 227.0652 218.2393 1348696.917 194.2616 214.2809 206.1249
B1
1238165.433 176.8746 195.4505 187.374 1092662.106 205.0039 226.0534 216.9015 1083217.939 201.2522 222.4852 214.1767 1163764.318 190.7603 210.5237 202.7902
B2
1229033.372 240.8397 269.3173 257.1126 1185992.361 264.7572 292.582 281.6207 1267176.875 241.4817 266.7347 255.6865 1136768.027 283.2592 313.1686 300.8529
B3
1156874.444 191.032 210.9131 202.2691 1152074.909 192.6958 213.5278 204.8478 1155491.161 188.6644 208.5693 199.915 1158953.996 190.6892 210.5347 202.769
B4
1194049.746 273.8579 302.3325 288.9327 1277571.858 235.6032 263.7816 250.4751 1239928.977 258.0793 285.5002 272.5963 1298274.916 252.6429 278.8315 266.5075
C1
1090904.018 199.8343 220.9177 211.751 1068770.378 203.0371 225.4928 216.1362 1273890.238 172.6993 191.5393 182.9043 1161566.094 187.6777 207.4785 198.8694
C2
1178237.993 276.6843 306.3897 294.5076 1070332.348 305.5126 338.2127 326.0669 1134996.624 289.8687 321.5869 310.1331 1363212.051 223.7363 247.2103 238.4075
C3
1200928.246 189.8531 212.3358 201.5108 1217977.509 171.5959 189.6587 183.0904 1173660.267 186.5957 206.1925 197.6722 1207848.892 185.4537 204.4958 196.2166
C4
1285388.94 254.3977 281.6268 269.9572 1383473.512 243.5898 268.1656 256.6005 1330109.914 244.3407 269.9025 257.8734 1373132.495 233.7721 258.533 246.8808
D1
1092453.845 197.72 217.8582 209.6198 1102125.051 198.707 219.5758 210.5024 1144560.474 181.7291 200.0768 191.3398 1123217.487 188.7435 207.4398 199.4271
D2
1124712.261 273.8478 300.5213 287.1846 1117885.743 296.9892 327.4038 312.1965 1127080.016 282.145 311.4242 297.2282 1071374.587 305.2154 336.0169 320.1495
D3
1185712.261 183.8557 203.2534 194.8196 1219853.607 173.7913 191.0065 183.6286 1225006.214 173.0603 190.2031 182.8562 1285069.227 168.8625 187.5385 178.9787
D4
1260431.288 244.3608 272.1291 257.8482 1250132.533 257.5727 283.17 270.3713 1303486.722 245.4954 270.8121 257.7702 1292778.648 243.6612 267.6406 256.0376
Panels No.5.volume ρ.dry
ρ.MC10 ρ.MC6 No.6.volume ρ.dry
ρ.MC10 ρ.MC6 No.7.volume ρ.dry
ρ.MC10 ρ.MC6
A1
1174867.612 181.297 200.0225 192.3621 1171538.202 181.8123 201.4446 192.9088 1160926.383 162.801 180.0286 172.2762
A2
1298394.115 243.3776 268.7936 257.2408 1292706.144 242.1277 267.6556 256.052 1131877.505 246.4931 276.5317 261.5124
A3
1261375.449 172.0344 189.4757 181.5478 1226082.254 171.2773 190.8518 181.8801 1247524.321 157.9128 174.7461 166.7302
A4
1352841.22 229.1474 253.5405 243.1919 1236889.329 252.2457 278.9255 267.6068 1281498.404 226.2976 252.829 240.3436
A5
1215553.927 198.2635 220.4756 210.6036 1156292.858 208.4247 230.9104 221.3972 1251214.641 210.1958 234.1725 222.9833
A6
1277340.218 190.2391 212.9425 201.9822 1242204.873 194.8149 218.1605 207.6952 1306705.62 179.8416 199.7389 190.5555
B1
1181084.347 182.8828 202.3564 194.7363 1174425.822 174.5534 194.9889 186.4741
B2
1311463.1 244.0023 270.69 259.2524 1179437.902 251.8149 282.3379 268.7721 1016228.336 321.7781 355.2351 341.4587
B3
1179532.48 182.2756 201.7749 194.1447 1156883.417 194.4881 216.0978 206.5895 1257813.348 158.2111 175.7017 167.7514
B4
1220051.477 258.1858 285.2339 272.9393 1164354.091 290.2897 325.5024 307.4666 1326363.501 219.3969 242.769 232.2139
C1
1129087.41 185.1052 205.4757 197.5046 1186374.171 177.0099 195.5538 187.9677 1204074.572 161.1196 179.3909 171.0857
C2
1393728.982 231.7524 256.1474 246.8199 1360530.787 216.8271 241.8174 232.2623 1206123.308 237.1234 264.4837 253.7054
C3
1273277.631 161.7872 178.2801 171.2117 1197383.932 168.7011 186.2393 179.5581 1185990.778 165.2627 184.6557 175.3808
C4
1404935.529 237.7333 266.2044 251.2571 1303276.082 232.491 257.0445 245.5351 1235747.077 233.0574 259.7619 246.8143
D1
1245039.068 174.2917 192.765 184.7332 1070038.7 200.9273 221.4873 212.1419
D2
1119911.188 268.7713 300.0238 284.844 1198951.681 267.7339 295.2579 281.9129 1156611.012 241.222 268.889 255.0555
D3
1240237.456 175.7728 193.5113 186.2547 1206379.996 184.8505 203.0869 195.6266
D4
1272401.221 249.1353 274.2846 261.7099 1218464.079 265.0878 291.3504 278.2191 1400046.318 224.2783 247.8489 235.7065

A-3: The density of all the samples

51 | P a g e

No.1.
No.1.
No.2.
No.2.
No.3.
No.3.
Panels RH20% RH50% RH20% RH50% RH20%
RH50%
A1
0.063636 0.1045455 0.058824 0.1176471 0.059091 0.1090909
A2
0.057927 0.1036585 0.058824 0.1021672 0.059701 0.119403
A3
0.06278 0.103139 0.060748 0.1074766 0.058537 0.1073171
A4
0.055556 0.119883 0.06079 0.106383 0.05919 0.1028037
A5
0.058366 0.1011673 0.065385 0.1115385 0.060976 0.1056911
A6
0.062745 0.1058824 0.062257 0.1050584 0.0625 0.1054688
B1
0.059361 0.1050228 0.058036 0.1026786 0.06422 0.1055046
B2
0.067568 0.1182432 0.063694 0.1050955 0.058824 0.1045752
B3
0.058824 0.1040724 0.063063 0.1081081 0.059633 0.1055046
B4
0.055046 0.1039755 0.063123 0.1196013 0.05625 0.10625
C1
0.059633 0.1055046 0.064516 0.1105991 0.059091 0.1090909
C2
0.064417 0.107362 0.067278 0.1070336 0.069909 0.1094225
C3
0.061404 0.1184211 0.066986 0.1052632 0.059361 0.1050228
C4
0.061162 0.1070336 0.053412 0.1008902 0.055385 0.1046154
D1
0.060185 0.1018519 0.059361 0.1050228 0.052885 0.1009615
D2
0.048701 0.0974026 0.051205 0.1024096 0.053459 0.1037736
D3
0.059633 0.1055046 0.056604 0.0990566 0.056604 0.0990566
D4
0.055195 0.1136364 0.049689 0.0993789
0.05 0.103125

No.4.
No.4.
No.5.
RH20%
RH50% RH20%
0.059633 0.1055046 0.061033
0.056886 0.1227545 0.056962
0.057018 0.1184211 0.0553
0.060976 0.1036585 0.06129
0.061224 0.1061224 0.062241
0.061069 0.1030534 0.061728
0.063063 0.1036036 0.064815
0.062112 0.1055901 0.0625
0.063348 0.1040724 0.065116
0.054878 0.1036585 0.057143
0.059633 0.1055046 0.066986
0.065574 0.104918 0.065015
0.058036 0.1026786 0.058252
0.056075 0.105919 0.056886
0.056604 0.0990566 0.059908
0.04893 0.1009174 0.059801
0.059908 0.1105991 0.059633
0.050794 0.0984127 0.050473

No.5.
No.6.
No.6.
No.7.
No.7.
Average Average
RH50% RH20% RH50% RH20%
RH50%
RH20%
RH50%
0.103286 0.061033 0.1079812 0.058201 0.1058201 0.060207 0.1076965
0.10443 0.057508 0.1054313 0.060932 0.1218638 0.058391 0.111387
0.101382 0.061905 0.1142857 0.055838 0.106599 0.058875 0.1083744
0.106452 0.060897 0.1057692 0.062069 0.1172414 0.059783 0.1074915
0.112033 0.062241 0.1078838 0.060837 0.1140684 0.06161 0.1083578
0.119342 0.066116 0.1198347 0.059574 0.1106383 0.062284 0.1098968
0.106481 0.068293 0.1170732
0.062965 0.1067274
0.109375 0.06734 0.1212121 0.061162 0.1039755 0.063673 0.1106819
0.106977 0.062222 0.1111111 0.060302 0.1105528 0.062034 0.1066409
0.104762 0.059172 0.1213018 0.058419 0.1065292 0.057602 0.1099248
0.110048 0.061905 0.1047619 0.061856 0.1134021 0.061961 0.1075848
0.105263 0.071186 0.1152542 0.06993 0.1153846 0.06723 0.1082089
0.101942 0.064356 0.1039604 0.061224 0.1173469 0.061399 0.1062146
0.11976 0.056106 0.1056106 0.059028 0.1145833 0.056865 0.1083447
0.105991 0.055814 0.1023256
0.057459 0.1025349
0.116279 0.05296 0.1028037 0.057348 0.1146953 0.052509 0.103931
0.100917 0.058296 0.0986547
0.058446 0.1022982
0.100946 0.049536 0.0990712 0.050955 0.1050955 0.050948 0.1024284

A-4: The moisture content of all the samples

52 | P a g e

Panels
RH20%
A1
A2
A3
A4
A5
A6
B1
B2
B3
B4
C1
C2
C3
C4
D1
D2
D3
D4

No.1.λ.
(W/mK)
0.0629
0.0702
0.0614
0.0706
0.0659
0.0618
0.0609
0.0676
0.0617
0.0704
0.0626
0.0734
0.0625
0.067
0.0632
0.0707
0.0621
0.0687

No.2.λ.
(W/mK)
0.0605
0.0704
0.0603
0.072
0.0661
0.0642
0.0653
0.0742
0.0621
0.0654
0.062
0.0732
0.0637
0.0677
0.063
0.0762
0.0618
0.0721

No.3.λ.
(W/mK)
0.0627
0.0708
0.0615
0.0682
0.0646
0.0636
0.063
0.0704
0.0626
0.07
0.0591
0.0717
0.0623
0.0669
0.0569
0.0711
0.0607
0.0698

No.4.λ.
(W/mK)
0.0618
0.0661
0.061
0.0719
0.0622
0.0645
0.0616
0.0749
0.0603
0.0698
0.0622
0.0682
0.0616
0.0671
0.0615
0.0734
0.0601
0.0696

No.5.λ.
(W/mK)
0.0607
0.0658
0.0602
0.0681
0.0629
0.0602
0.0647
0.0716
0.0622
0.0714
0.0612
0.0693
0.0593
0.0681
0.0589
0.0694
0.0593
0.0718

No.6.λ.
(W/mK)
0.0618
0.0673
0.0623
0.0708
0.0628
0.0622
0.0606
0.0685
0.0627
0.072
0.0642
0.066
0.0596
0.0637
0.0618
0.0712
0.0618
0.0733

No.7.λ.
(W/mK)
0.0585
0.0655
0.0593
0.0652
0.0656
0.0614

Panels
RH50%
A1
A2
A3
A4
A5
A6
B1
B2
B3
B4
C1
C2
C3
C4
D1
D2
D3
D4

No.1.λ.
(W/mK)
0.0687
0.0786
0.0657
0.0814
0.0724
0.0691
0.0674
0.0772
0.0682
0.0778
0.0689
0.0812
0.0684
0.0755
0.0703
0.0801
0.069
0.0755

No.2.λ.
(W/mK)
0.0673
0.0768
0.0649
0.0807
0.0733
0.0701
0.0717
0.0806
0.0678
0.0756
0.0678
0.0795
0.0683
0.0782
0.07
0.0838
0.0679
0.0819

No.3.λ.
(W/mK)
0.0684
0.0809
0.0676
0.0763
0.0703
0.0693
0.0693
0.0773
0.0696
0.0789
0.0647
0.0789
0.0679
0.0762
0.0657
0.0792
0.0666
0.0768

No.4.λ.
(W/mK)
0.0676
0.0758
0.0697
0.0797
0.0694
0.0706
0.0681
0.083
0.067
0.0784
0.0672
0.0752
0.0667
0.0759
0.0697
0.0811
0.069
0.0755

No.5.λ.
(W/mK)
0.065
0.0727
0.0665
0.0743
0.0689
0.0696
0.0704
0.079
0.069
0.0791
0.0677
0.0757
0.0634
0.0788
0.0685
0.0787
0.066
0.0801

No.6.λ.
(W/mK)
0.0657
0.0754
0.067
0.0783
0.0717
0.0691
0.0665
0.0781
0.0719
0.0831
0.0685
0.0742
0.0644
0.0765
0.0685
0.077
0.0695
0.0809

No.7.λ.
(W/mK)
0.064
0.0719
0.0661
0.0751
0.073
0.0679

0.0723
0.0574
0.0659
0.0579
0.0664
0.0599
0.0641
0.0685
0.0687

0.0791
0.0656
0.0721
0.0638
0.0741
0.0664
0.0716
0.0774
0.0761

A-5: The Thermal conductivity of all the samples

53 | P a g e