carbon sequetration strategies in cement based material ... · nano platelet admixture interaction...

Carbon Sequestration Strategies in Cement Based Material: Carbon Nano Platelet Admixture Interaction and Long term

Carbonation of CO2 injected Concrete Blocks

by

Yan Yin (Chloe) Chan

A thesis submitted in conformity with the requirements for the degree of Master of Applied Science

Department of Civil Engineering University of Toronto

© Copyright by Yan Yin (Chloe) Chan 2017

ii

Carbon sequestration strategies in cement based material: carbon

nano platelet admixture interaction and long term carbonation of

CO2 injected concrete blocks

Yan Yin (Chloe) Chan

Master of Applied Science

Department of Civil Engineering

University of Toronto

2017

Abstract

Two novel approaches to sequester carbon in concrete were examined in this study. First, carbon

nano platelets exposed to CO2-laden flue gas were explored for possible use as a concrete

additive to improve mechanical properties. However, carbon nano platelets also have the

potential to interfere with the performance of air entraining admixtures (AEAs) in concrete. The

capacity for carbon to adsorb AEAs is already widely recognized in terms of unburnt carbon

residues present in coal combustion fly ash. In this research, adjustments to Vinsol resin and

synthetic AEA dosages necessary to maintain adequate air void parameters in mortars were

determined using a combined adsorption isotherm test based on chemical oxygen demand

(COD). Second, the long-term carbonation of industrially produced concrete blocks

manufactured using early-age CO2 injection was explored using an accelerated carbonation

chamber. Carbonation rates were found to be similar for CO2-injected and non CO2-injected

blocks.

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Acknowledgments

Firstly, I would like to express my utmost gratitude to my Supervisor, Professor Karl Peterson,

for his constant support, counsel and motivation throughout my research studies. I have truly

benefitted from his enlightening mentoring. In addition, I would like to extend my gratitude to

NSERC, Brampton Bricks, and Carbon Upcycling Technologies for the chance to pursue

research studies in this specific area.

My sincere thanks also goes to Josh Brown CarbonCure Technologies Inc, Mark MacDonald

CarbonCure Technologies Inc, Nirav Rathod of Brampton Brick, Pulin Mondal from the

University of Toronto Groundwater Research Laboratory, and Sal Boccia from the Ontario

Centre for their essential contributions in facilitating the experimental works within this study.

As well, my heartfelt appreciation to Alireza Dehghan, Ekaterina Ossetchkina, Barry Qiu,

Grahan Riehm, Viktoriya Zaytseva, and Dinmukhamed Daniyarbekov for their research

assistance and efforts in the lab.

Finally, I am forever grateful to my family for their support and encouragement throughout my

academic career. Their presence and unconditional love has been a blessing that made it possible

for me to attain this academic achievement.

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Table of Contents

Acknowledgments.......................................................................................................................... iii

Table of Contents ........................................................................................................................... iv

List of Tables ................................................................................................................................. vi

List of Figures ............................................................................................................................... vii

List of Appendices .......................................................................................................................... x

Chapter 1: Introduction ................................................................................................................... 1

1.1 Background Information ....................................................................................................... 1

Chapter 2: Assessment of admixture adsorption by a carbon nano platelet concrete additive ....... 3

2.1 Introduction ........................................................................................................................... 3

2.1.1 Background .................................................................................................................... 3

2.1.2 Adsorption Mechanisms of Chemical Admixtures in Cementitious Systems ............... 5

2.2 Experimental ......................................................................................................................... 7

2.2.1 Materials ........................................................................................................................ 7

2.2.2 Mix Design and AEA doses in mortar ........................................................................... 8

2.2.3 Combined Adsorption Isotherm Test ............................................................................. 9

2.2.4 Mixing Procedure......................................................................................................... 12

2.2.5 Fresh Mortar Properties ............................................................................................... 12

2.2.5.1 Flow Test .............................................................................................................. 12

2.2.5.2 Air content by Gravimetric method ...................................................................... 13

2.2.5.3 Calorimetry ........................................................................................................... 13

2.2.6 Casting and Curing of Specimens ................................................................................ 14

2.2.7 Mechanical Properties .................................................................................................. 14

2.2.8 Air void system measurement ...................................................................................... 14

2.3 Results and Discussion ....................................................................................................... 15

2.3.1 Combined Adsorption Isotherm ................................................................................... 15

2.3.2 Fresh Mortar Properties and Compressive Strength .................................................... 17

2.3.3 Automated Air-void Analysis ...................................................................................... 20

2.3.4 Calorimetric Results..................................................................................................... 24

2.4 Conclusions ......................................................................................................................... 24

v

Chapter 3: Assessment of Carbonation Sequestration Potential of Concrete blocks with an

Accelerated Environmental Exposure Chamber ........................................................................... 25

3.1 Introduction ......................................................................................................................... 25

3.1.1 Background .................................................................................................................. 25

3.1.2 Types of Concrete Carbonation ................................................................................... 27

3.2 Experimental ....................................................................................................................... 29

3.2.1 Carbonation Chamber .................................................................................................. 29

3.2.2 Monitoring Carbonation by Phenolphthalein Indicator Solution................................. 30

3.2.3 Monitoring Carbonation by Profile Grinding and Loss on Ignition ............................ 30

3.2.4 Monitoring Carbonation by Petrographic Microscope ................................................ 32

3.3 Results ................................................................................................................................. 34

3.3.1 Phenolphthalein Stain .................................................................................................. 34

3.3.2 Profile Grinding ........................................................................................................... 34

3.3.3 Petrographic Microscope ............................................................................................. 40

Chapter 4: Significance of Findings and Recommendations ........................................................ 49

References ..................................................................................................................................... 50

Appendices .................................................................................................................................... 63

vi

List of Tables Table 2.1: Material Properties......................................................................................................... 7

Table 2.2: Chemical Admixture Properties .................................................................................... 7

Table 2.3: Fresh and hardened properties of control and carbon blended mixes ......................... 17

Table 2.4: Mortar mixture air void parameters ............................................................................. 20

Table 2.5: Parameters for fitted log-normal distributions ............................................................. 23

Table 3.1: Test for significance of CO2 injection technology on carbonate content at zero days

exposure ........................................................................................................................................ 36

Table 3.2: Test for significance of CO2 injection technology on carbonate content at sixteen days

exposure ........................................................................................................................................ 39

Table 3.3: Test for significance of CO2 injection technology on carbonate content at thirty days

exposure ........................................................................................................................................ 39

Table 3.4: Test for significance of carbonate content in red blocks at sixteen and thirty days

exposure ........................................................................................................................................ 39

Table 3.5: Test for significance of carbonate content in yellow blocks at sixteen and thirty days

exposure ........................................................................................................................................ 39

Table 3.6: Test for significance of CO2 injection technology on carbonate paste pixels at zero

days exposure ................................................................................................................................ 47

Table 3.7: Test for significance of CO2 injection technology on carbonate paste pixels at two

days exposure ................................................................................................................................ 47

Table 3.8: Test for significance of CO2 injection technology on carbonate paste pixels at thirty

days exposure ................................................................................................................................ 48

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List of Figures

Figure 2.1: Schematic of (a) chemisorption of chemical admixtures by cement (Jolicoeur &

Simard 1998), and (b) physical adsorption of chemical admixture by carbon (Freeman et al.

1997) ............................................................................................................................................... 6

Figure 2.2: Combined secondary and back scattered electron images of carbon nano platelet

morphology ..................................................................................................................................... 8

Figure 2.3: XRD pattern for carbon nano platelets and reference pattern (00-041-1487) for

graphite ........................................................................................................................................... 8

Figure 2.4: COD Calibration Curve for closed reflux colorimetric method ................................. 10

Figure 2.5: Combined adsorption isotherms for a) SYN AEA and b) VR AEA .......................... 16

Figure 2.6: Bulk air content in mortar mixtures containing a) SYN AEA and b) VR AEA ........ 18

Figure 2.7: Spacing Factor with the application of a) SYN AEA and b) VR AEA...................... 21

Figure 2.8: Air-void intercept length distributions for SYN (a) and VR (b) mixtures ................. 22

Figure 2.9: Flatbed scanner image after greyscale threshold application of sample a) SYN @

baseline, b) SYN +C @ baseline, and c) SYN +C @ adjusted ..................................................... 23

Figure 2.10: Flatbed scanner image after greyscale threshold application of sample a) VR @

baseline, b) VR +C @ baseline, and c) VR +C @ adjusted ......................................................... 23

Figure 2.11: Calorimetric curves for mixes containing (a) 196 ml/100kg cement of SYN AEA

and (b) 780 ml/100kg cement of VR AEA ................................................................................... 24

Figure 3.1: Schematic of test chamber, adapted from McGrath (2005) ....................................... 29

viii

Figure 3.2: Twenty-four hours of carbonation chamber temperature, humidity, and CO2

concentration data ......................................................................................................................... 30

Figure 3.3: Results of verification test on calcite and gypsum blends fired in ignition furnace .. 31

Figure 3.4: Crossed polar (a), fluorescent (b), and plane polarized (c) images with example

entrapped air void labeled “V” , light weight expanded glass aggregate particle “L”, cement paste

“P”, and dolostone aggregate particle “D” ................................................................................... 33

Figure 3.5: Phenolphthalein staining of fresh surfaces from blocks subjected to specified

exposure times in carbonation chamber (tic marks every cm) ..................................................... 35

Figure 3.6: Bulk carbonate content versus depth .......................................................................... 36

Figure 3.7: Distribution of bulk carbonate content measurements ............................................... 38

Figure 3.8: Crossed polarized illumination of thin sections prepared from masonry blocks at

various exposure time; block exterior surface oriented at top, tic marks every mm .................... 42

Figure 3.9: Fluorescent images to show porosity (brighter regions indicate pore space); block

exterior surface oriented at top, tic marks every mm .................................................................... 43

Figure 3.10: Transmitted plane polarized light images; block exterior surface oriented at top, tic

marks every mm ............................................................................................................................ 44

Figure 3.11: RGB image of combined crossed-polarized, fluorescent, and transmitted plane

polarized light image. Block exterior surface oriented at top, tic marks every mm ..................... 45

Figure 3.12: Binary image of carbonated paste pixels (black); block exterior surface oriented at

top, tic marks every mm................................................................................................................ 46

ix

Figure 3.13: Optical analysis of carbonated paste versus depth from polished thin sections ....... 47

x

List of Appendices

Appendix A: Combined Isotherm Test Detailed Results .............................................................. 63

Appendix B: Mixture Designs ...................................................................................................... 66

Appendix C: Fresh Mortar Properties Detailed Results ............................................................... 68

Appendix D: Automated Air-void analysis Detailed Results ....................................................... 70

1

Chapter 1: Introduction

1.1 Background Information

Portland cement production accounts for approximately 5% of global carbon dioxide (CO2)

emissions (Damtoft et al. 2008; Worrell et al. 2001; Scrivener & Kirkpatrick 2008). Specifically,

cement manufacture, and upstream oil and gas production compose 22% of Canada’s annual

greenhouse gas (GHG) production (Environment Canada 2015). Canada withdrew from the

Kyoto Protocol in 2011 when it became clear that a reduction in GHG emissions to 6% below

1990 levels would not be achieved by 2012 (Matin et al. 2004). More recently, Canada has

targeted a 30% decrease in GHG emissions by 2030 with respect to 2005 levels. It is evident that

industrialized countries continue to face the challenge of mitigating excessive GHG emissions to

control adverse environmental impacts.

The cement industry is exploring many approaches to tackle this challenge, with an ultimate goal

of reducing GHG emissions to half of 2006 levels by 2050 (World Business Council for

Sustainable Development 2009). Carbon Capture and Storage (CCS) technologies will play a

critical role, as in many cases they are able to offset emissions from fixed sites over a short time

period. A wide range of technologies have been explored to recycle captured CO2 in the curing,

production and alteration of cement composites, including i) accelerated carbonation curing, ii)

magnesium oxide based cement, iii) γ-C2S blended concrete, iv) the Calera (CaCO3) process, v)

Calix’s cement, vi) geopolymer cement and vii) cement substitution with reactive minerals (Jang

et al. 2016).

One promising CO2 capture technology for post combustion applicable to cement-based material

is adsorption of CO2 by carbon allotropes, especially high surface area graphene (Najafabadi

2015). Graphene-based membranes have displayed gas separation abilities and selective

permeation for CO2 when exposed to flue gas, which facilitates CO2 uptake. The application of

these carbon-based CO2 adsorbents as reinforcement additives in concrete presents an

opportunity to not only increase the compressive and flexural strength, but effectively capture

CO2 in concrete.

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For CO2 storage, mineral carbonation, or atmospheric reactions between CO2 and reactive

constituents in cement-based composites are well known and capable of binding CO2 in the

phase of thermodynamically stable calcium carbonates (Jang et al. 2016; Pade & Guimaraes

2007; Galan et al. 2010; Kashef-Haghighi & Ghoshal 2010; Kim et al. 2015; Jang & Lee 2016).

As such, cement-based composites are a potential sink for carbon sequestration. Formerly,

carbonation was viewed primarily as a deterioration mechanism leading to corrosion of

embedded steel reinforcements and subsequent concrete cracking (Moreno et al. 2004; Ahmad

2003). Nevertheless, carbonation can contribute to the beneficial development of engineering

properties, and as such, concrete has been presented as a feasible medium for CO2 storage in

multiple studies (Fernandezbertos et al. 2004).

Fundamentally, these strategies are too underdeveloped for general construction application due

to technical and economical limitations. Extended research is required to verify their capability

to uptake CO2 without compromising engineering properties.

The current research focuses on the technical issues for two specific strategies: 1) cement

replacement with carbon nano platelets exposed to a CO2-rich flue gas, and 2) the influence of an

early age CO2 concrete curing regime on long-term carbonation. Carbon nano platelets are not

only efficient adsorbents of CO2, but also efficient adsorbents of organic admixtures routinely

used in concrete, and thus may interfere with admixture performance. The second aspect

explores the potential impact CO2-injection might have on the natural carbonation of concrete

with atmospheric CO2 that occurs over a period of years or decades.

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Chapter 2: Assessment of admixture adsorption by a carbon nano platelet concrete additive

Chapter 2 is derived in part from an extended abstract submitted to the 2017 Euroseminar on

Microscopy Applied to Building Materials.

2.1 Introduction

2.1.1 Background

Carbon nano additives have gained increasing attention in recent years, mostly in terms of

improving the compressive and tensile strengths of concrete (Pan et al. 2015; Gong et al. 2015).

The high surface area of the nano materials promotes chemical and physical interactions with

cement, strengthening the matrix while providing reinforcement (Pan et al. 2015). For example,

carbon allotropes such as graphene oxide (GO) and other derivatives have been shown to

promote hydration reactions (Lv et al. 2014). Graphene-based materials have also been explored

as an advantageous adsorbent for CO2 captured from flue gas owing to their highly porous

structure and functionalization. CO2 is effectively captured as the molecules align with the

hexagonal structure, enabling optimized sorption of 37.9 wt% on a sheet of graphene (Najafabadi

2015). Therefore, the constructive incorporation of CO2 treated carbon nano additives in concrete

offers an appealing technique for carbon sequestration. However, the amphiphilic nature and

high surface area of GO also has an adsorption capacity for water and other organic admixtures,

potentially compromising fresh concrete workability. Many studies indicate that the

incorporation of GO can compromise fluidity and affect rheological parameters (Pan et al. 2015;

Gong et al. 2015; Chuah et al. 2014; Shang et al. 2015). Moreover, adsorption capacity of the

carbon content in GO for air entraining admixtures (AEAs) leads to critical concerns regarding

the formation of fine entrained air voids (Chuah et al. 2014). The surface adsorption between

carbon/AEA interactions interferes with the bridging action of AEAs to stabilize air in concrete,

and has already been demonstrated in unburnt carbon residues on coal combustion fly ash

(Freeman et al. 1997; Dhir et al. 1999; Pedersen et al. 2008). In Canada, AEAs are critical for

freeze-thaw resistance of concrete. The uniformly distributed µm to mm sized entrained voids

produced using AEAs are crucial to relieving detrimental pressures generated in capillary pores

in subzero climates. Specifically, entrained air void systems with a spacing factor below 0.20

4

mm are expected to provide adequate protection for cement paste undergoing freezing and

thawing (Powers & Helmuth 1953; Litvan 1972; Fagerlund 1977).

Interestingly, Mohammed et al. (2016) conducted a comparative study on the freeze-thaw

resistance of plain concrete and GO blended composites at 0.01, 0.03, and 0.06 wt% substitution

rates, without chemical admixtures. The researchers suggested GO additives can act as effective

air entraining agents in place of conventional surfactants, and increase the air content up to 40%

of the plain cement mixture, and simultaneously provide mechanical improvements.

Furthermore, mixtures with higher GO replacement levels demonstrated the least amount of

weight loss after cyclic freeze-thaw testing. In a similar comparative study of mortars without

AEAs, Tong et al. (2016) found that graphene nano platelets compromised freeze-thaw

performance, whereas GO nano platelets enhanced durability. Thus, the role of carbon nano

additives in the freeze-thaw performance of blended composites remains ambiguous.

When carbon nano additives are used, corresponding increases in AEA dosages may be required

to achieve the equivalent air void system as exhibited in ordinary concrete. Adjustments can be

arrived at through trial and error, but the capability to measure the adsorption potential and

corresponding adjustment could represent real time-saving. There are few standardized methods

for the characterization of unburnt carbon residue on fly ash, including loss on ignition (LOI)

(ASTM C311, 2016), iodine number test (ASTM D4607, 2014), and direct adsorption isotherm

tests (ASTM D3860, 2014) to either infer or quantify the unburnt carbon adsorption capacity

(Ahmed & Hand 2014; Pedersen et al. 2007; Sutter et al. 2013; Baltrus & Lacount 2001;

McCarthy et al. 2012). The limited number of standardized techniques also acts as an

impediment for the extensive use of nano carbon additives in concrete (Bartoňová 2015). Ahmed

et al. (2014) have developed a directly applicable and precise combined adsorption isotherm

strategy for fly ash that quantifies the equilibrated correlation between the aqueous and solid

phase AEA concentrations based on a Freundlich isotherm model. To develop isotherm points, a

sufficient mass of cement is included to account for chemisorption by cement, such that

detectable changes in AEA concentrations can be attributed to physical adsorption by unburnt

carbon on the fly ash. The authors used the combined adsorption isotherm approach to determine

successful AEA dosage adjustments for 25 wt% substituted fly ash blended mixtures that

5

achieved target air content. The technique has been verified for AEAs with different chemical

natures, including Vinsol resin, ɑ-olefin sulfonate and combinations thereof (Ahmed, & Hand

2015).

In this chapter, the compatibility issue of a carbon nano platelet with types of AEA (Vinsol resin

and synthetic) is addressed, and an adopted combined adsorption isotherm technique is

investigated to mitigate interferences with air entrainment for freeze-thaw durability. The

resultant air void systems are described using Power’s spacing factor (�̅�) (Powers & Helmuth

1953) in addition to bulk air content.

2.1.2 Adsorption Mechanisms of Chemical Admixtures in

Cementitious Systems

In assessing the adsorption of chemical admixtures in cementitious systems, the sorptivity

phenomenon of AEA with components of concrete can be classified into two mechanisms: i)

chemisorption achieved through electron exchange between the adsorbate and adsorbent, and ii)

physical adsorption achieved through van der Waal’s forces between adsorbate and porous

adsorbent.

In the interaction between AEA and cement, the governing sorption mechanism is chemisorption

due to the ionic nature of cementitious materials (Figure 2.1a). Given such, the anionic groups in

AEA molecules react energetically with cement, establishing electrochemical bonds with the

cement grain surfaces (Jolicoeur, & Simard 1998). The adsorption of organic molecules onto

cement is consequential as it limits the abundance of molecules participating in air entrainment.

Studies by Sutter et al. (2013) quantified that approximately 10 g of cement mixed with 200 mL

of dilute AEA solutions can be sufficient in assessing the full chemisorption capacity of cement

particles for AEA. Additional cement contents were observed to not prompt the occurrence of

chemisorption. The mass of cement required to quantify chemisorption was also examined, and

found to be insensitive to changes in cement types. Based on experimental results, the authors

concluded a conservative procedure of utilizing 20 grams of cement mixed with 200 mL of AEA

solution was adequate to account for full chemisorption in adsorption isotherm testing.

6

In the interaction between AEA and aggregates, the solid aggregate surfaces are recognized to be

inconsequential as AEA molecules have a preferential adsorption to the cement particles based

on thermodynamics (Du & Folliard 2005). Sutter et al. (2013) detected unsubstantial variations

in the aqueous AEA concentrations when solutions were equilibrated with masses of sand and

gravel. Given such, it was reflected that electrochemically neutral aggregates do not influence

the concentrations of AEAs. Hence, aggregates may be reasonably neglected in AEA adsorption

tests.

For the interaction between AEA and carbon particles in nano additives, the governing sorption

process is physical adsorption (Figure 2.1b). The physical adsorption mechanism is based on the

non-polar surfaces of carbon in the nano additives having an affinity for the hydrophobic ends of

AEA molecules. The non-polar surfaces act as active adsorption sites, limiting the quantity of

free aqueous AEAs to stabilize air bubbles (Pedersen et al. 2008). The AEA molecules are

physically hindered from interacting with the air/water interface. Sutter et al. (2013) found that

continual additions in carbon content prompted continual drops in AEA aqueous phase

concentrations, not achieving a steady state in its interaction. In fact, ongoing additions of carbon

will eventually adsorb all aqueous phase AEA, with no AEA residual in solution to participate in

air void stabilization.

a. b.

Figure 2.1: Schematic of (a) chemisorption of chemical admixtures by cement (Jolicoeur &

Simard 1998), and (b) physical adsorption of chemical admixture by carbon (Freeman et

al. 1997)

7

2.2 Experimental

2.2.1 Materials

The Portland cement (CSA A3001 Type GU) used in these experiments was acquired from Saint

Marys Cement, Bowmanville, Ontario, Canada plant. The proprietary carbon nano platelets were

provided by Carbon Upcycling Technologies (CUT). The fine aggregates used in mortars came

from a natural source near Sunderland, Ontario, and originated from carbonate-rich fluvially

sorted glacial sediments generated by the Laurentide ice sheet. The material properties are

presented in Table 2.1.

Two commonly used AEAs from BASF Canada were selected; a Vinsol resin, Master VR 10

(referred to hereafter as VR), and a synthetic, MasterAir AE 200 (referred to hereafter as SYN).

Chemical composition and physical properties of the AEAs are reported in Table 2.2.

For the combined adsorption isotherm test, HACH COD kits (2125925) were purchased from

Hach Canada Ltd. In addition, potassium hydrogen phthalate (KHP) standard BioXtra, ≥99.95%

were procured from Sigma Aldrich for development of the COD calibration curve for

spectrophotometric COD method.

Table 2.1: Material Properties

Material Relative Density Absorption

GU cement 3.15 N/A

Carbon nano platelets 2.18 N/A

Fine aggregate 2.69 0.60 %

Table 2.2: Chemical Admixture Properties

Product Composition [wt%] Relative

Density

MasterAir AE 200

1 - 3 % Sulfonic acids, and sodium salts

1.01 0 – 5 % Potassium hydroxide

0 – 1 % Rosin

MasterAir VR 10 5 – 7 % Rosin

1.03 0.3 – 1 % Potassium hydroxide

8

The composition of carbon nano platelets is demonstrated by x-ray diffraction (XRD) using a

Philips PW 1730 X-ray generator and Cu Kα ( λ = 1.5418 Å) radiation. The morphology was

explored by scanning electron microscopy (SEM) using a JEOL 6610 LV. The morphology of

the carbon nano platelets is shown in Figure 2.2, and the XRD pattern in Figure 2.3.

Figure 2.2: Combined secondary and back scattered electron images of carbon nano

platelet morphology

Figure 2.3: XRD pattern for carbon nano platelets and reference pattern (00-041-1487) for

graphite

2.2.2 Mix Design and AEA doses in mortar

All mortars in this study were produced at a water to cementitious materials ratio (w/cm) of 0.42,

and with an aggregate:paste volume ratio of 1:1. In blended mortars, carbon nano platelets were

substituted for Portland cement at a fixed replacement level of 0.5 wt%. Detailed mortar mixture

designs can be found in Appendix B. The baseline dosages for the control mortars (196 ml of

9

SYN AEA / 100 kg cement and 780 ml of VR AEA / 100 kg cement) were selected to achieve a

target spacing factor ≤ 0.20 mm.

2.2.3 Combined Adsorption Isotherm Test

The adsorption capacity of the carbon nano platelets was measured using a combined adsorption

isotherm test based on ASTM WK47571, with minor modifications. The results were used to

predict the dosage of AEA required in a carbon blended mortar, to achieve a similar air void

system as the control mortar. Through all stages of this adsorption test, chemical oxygen demand

(COD) is used as a proxy for AEA concentration (Ahmed et al. 2014; ASTM WK47571). COD

is a common procedure used to measure organic matter in water (Jirka & Carter 1975). During a

COD test, organics are oxidized by a potassium dichromate (K2Cr2O7) solution through sulphuric

acid (H2SO4) and heat (150ºC). As potassium dichromate is consumed, carbon dioxide (CO2) is

produced, and the Cr+6

ions are reduced to Cr+3

, imparting a green colour to the solution. The

amount of Cr+3

ions is proportional to the amount of organics consumed. In a spectrophotometer

the absorption of red light (600 nm) is proportional to the concentration of Cr+3

ions in solution.

The absorption is used as an indirect measure of the oxygen consumed by the organic matter (the

COD), and expressed in units of mg O2/L. As AEAs are composed of combinations of organic

compounds, higher measured COD values are proportional to higher concentrations of AEA in

the aqueous phase. In the current work, a HACH DR 2700 portable spectrophotometer was used

in combination with HACH high-range (20-1,500 mg/L COD) digestion vials using the 5220D

standard closed reflux colorimetric method (Eaton & Franson 2005). Initially, a COD calibration

curve (Figure 2.4) was constructed using varying concentration of KHP equivalent to specific

COD concentrations to interpret spectrophotometer readings.

10

Figure 2.4: COD Calibration Curve for closed reflux colorimetric method

In addition to the physical adsorption occurring between the AEA and carbon, chemisorption

also occurs between the AEA and cement. In order to properly quantify adsorption by the

carbon, it is necessary to first quantify chemisorption by cement (Ahmed et al. 2014; ASTM

WK47571). To begin, three different solutions of varying AEA concentrations in distilled water

were prepared. 200 mL from each solution were mixed with 20 g of Portland cement and

allowed to equilibrate. The solutions were filtered, and the filtrate collected was used for COD

analysis. The initial AEA concentrations were selected such that results fell within the 20-1,500

mg/L COD detection range. For the SYN AEA solutions, concentrations of 1.0, 2.0, and 3.0 vol.

% were used. For the VR AEA solutions, concentrations of 0.3, 1.0, and 1.7 vol. % were used.

All tests were repeated in triplicate. Next, the procedure was repeated, but in addition to the

cement, carbon nano platelets were also added. The carbon nano platelet addition levels were

selected such that results fell within the detection range of 20-1,500 mg/L COD, and lower than

80% of the cement only filtrate COD value. For the SYN AEA solutions, 1.0 g of carbon nano

platelets were added. For the VR AEA solutions, 0.5 g of carbon nano platelets were added.

11

The reduction in AEA concentration (∆𝐴) for each AEA + Portland cement + carbon nano

platelet mixture was computed according to Equation 2.1 (Ahmed et al. 2014; ASTM

WK47571):

∆𝐴𝑖 = [(𝐶𝑂𝐷𝐵𝑖− 𝐶𝑂𝐷𝐶𝑖

) × 𝐶0𝑖] 𝐶𝑂𝐷𝐵𝑖⁄ Equation 2.1

Where: ∆𝐴𝑖 = reduction in AEA concentration at solution strength i, ml/L

𝐶𝑂𝐷𝐵𝑖= COD of the cement-only equilibration (the blank), mg COD/L

𝐶𝑂𝐷𝐶𝑖= COD of the cement + carbon nano platelet equilibration, mg COD/L

𝐶0𝑖= initial AEA solution strength, ml/L

The adsorption capacity (𝑞) for each AEA + Portland cement + carbon nano platelet mixture was

computed according to Equation 2.2 (Ahmed et al. 2014; ASTM WK47571):

𝑞𝑖 = (∆𝐴𝑖 × 0.2 L) 𝑀𝐶𝑖⁄ Equation 2.2

Where: 𝑞𝑖 = adsorption capacity at solution strength i, ml AEA/g carbon

𝑀𝐶𝑖= mass of carbon nano platelets in solution, g

Finally, the residual AEA concentration (𝐶𝐹) after equilibration of the AEA + Portland cement +

carbon nano platelet mixture was computed according to Equation 2.3 (Ahmed et al. 2014;

ASTM WK47571):

𝐶𝐹𝑖= (𝐶0𝑖

− ∆𝐴𝑖) 10⁄ Equation 2.3

Where: 𝐶𝐹𝑖= residual AEA concentration at solution strength i, vol. % AEA

Upon developing the isotherm plot, interpolation using a fitted power line was required to

determine the carbon adsorption capacity corresponding to a baseline dosage in the control

mortar. The initial AEA concentration (vol. %) for the control sample was calculated based on

the following equation:

12

𝐴𝐸𝐴 𝑐𝑜𝑛𝑐. = [𝐴𝑏𝑎𝑠𝑒𝑙𝑖𝑛𝑒/ (𝐴𝑏𝑎𝑠𝑒𝑙𝑖𝑛𝑒 + 𝑤)] 𝑥 100 Equation 2.4

Where: 𝐴𝑏𝑎𝑠𝑒𝑙𝑖𝑛𝑒 = mass of AEA at baseline dosage, g

𝑤 = water content, g

Following the interpolation for 𝑞, adjusted AEA volumes required for the carbon blended sample

were calculated as follows:

𝐴𝑑𝑗𝑢𝑠𝑡𝑒𝑑 𝐴𝐸𝐴 𝑣𝑜𝑙. 𝑟𝑒𝑞𝑢𝑖𝑟𝑒𝑑 = ( 𝑞 x 𝑀𝑛𝑎𝑛𝑜) + 𝐴𝑑𝑜𝑠𝑒 Equation 2.5

Where: 𝑀𝑛𝑎𝑛𝑜 = mass of carbon nano platelet in mortar sample, g

𝐴𝑑𝑜𝑠𝑒 = volume of AEA at baseline dosage determined in control mortar, ml

The obtained adjusted AEA volume was translated into units of ml AEA/100 kg cement through

mix design proportioning.

2.2.4 Mixing Procedure

The mixing procedures applied within this study adhered to ASTM C305. The fine aggregate

was oven-dried prior to mixing. The pre-measured water and AEA was initially poured into the

mixing bowl. With the mixer started, the cementitious material was added over a 30 sec interval.

Immediately following, the fine aggregate was added to the mixer over a 30 sec interval.

Subsequently, the batch was further mixed for 30 sec. The mixer was then stopped for a 1.5

minute rest period, with the initial 15 sec used to scrape down accumulated mortars on the side

of the bowl into the batch. Finally, the mixer was restarted for an additional 1 minute of mixing.

To ensure repeatability, duplicate mixtures were cast for all control mixtures and for all carbon

blended mixtures.

2.2.5 Fresh Mortar Properties

2.2.5.1 Flow Test

Flow tests were performed according to ASTM C1437 to evaluate the consistency of fresh

mortar mixes. The target mortar flow was set at 100 - 130% (ASTM C109, 2016). Fresh concrete

13

was packed into the flow mold at the center of a flow table in two equal layers and tamped 20

times per layer. Surplus mortar was cleared off to level with the top of the mold by applying a

straightedge to saw across the top of the mold. The mold was then lifted from the mortar and the

table was dropped 10 times. Utilizing a caliper as specified in ASTM C230, the diameter of the

mortar along the four lines inscribed in the table top was measured. The summation of the four

readings were then reported as the flow in %.

2.2.5.2 Air content by Gravimetric method

Bulk air content was measured according to ASTM C185. Mortars not used in the flow test were

placed into a measurement cup of known volume (exceeding 400 mL) in three equivalent layers.

The layers were each tamped 20 times in a full revolution to ensure compaction of the mortar.

After filling, the cup was tapped to remove entrapped excess air, and surplus mortar cleared level

with the top of the cup. The mass of the mortar-filled cup was recorded, and the air content was

calculated using the following equation:

𝐴 = 100[1 − (𝑊𝑎 𝑊𝑐⁄ )] Equation 2.6

Where: A = air content (vol. %)

Wa = unit weight determined by test method.

Wc = theoretical unit weight of mixture design, calculated on an air-free basis.

2.2.5.3 Calorimetry

Calorimetry was used to investigate any potential impact the carbon nano additives might have

on hydration, and performed according to ASTM C1679. Promptly after completing the mixing

cycle, a representative sample of mortar (approximately 100 g) was transferred to sealed vial.

The vial was loaded into the calorimeter, and thermal power measurements commenced after

inputting the sample mass and base temperature. For this study, an I-CAL 8000 calorimeter was

used, with the base temperature set at 23° C for measurements. Thermal data was collected for

50 hours at 60 second intervals.

14

2.2.6 Casting and Curing of Specimens

50 mm3 cubical specimens were cast in triplicate for compressive strength testing. The cubes

were packed in 3 uniform layers and tampered 32 times per layer in 4 rounds, with each round in

a perpendicular direction to the previous, as specified in ASTM C109. After surplus mortar was

cleared, the filled molds were covered with polyethylene sheets at 23± 2 ° C for 24 hours prior to

demolding. After demolding the cubes were placed in a lime-saturated solution at temperature of

23± 2 °C, and removed at appropriate intervals for strength testing.

2.2.7 Mechanical Properties

In this study, compressive strength measurements were conducted following ASTM C109. A

Forney Model FT-40 machine was used with a loading rate of 2 kN/second.

2.2.8 Air void system measurement

The same sample preparation and automated air void analyses described by Peterson et al. (2015)

were used in this study. Prepared specimen surfaces were scanned with a V800 Epson Perfection

flatbed scanner at 8 um/pixel resolution in 8 bit grayscale. Calibration data for the optimum air

content and void frequency thresholds utilized are documented in Table D.2 within Appendix D.

15

2.3 Results and Discussion

2.3.1 Combined Adsorption Isotherm

The developed isotherm plots for both VR and SYN AEA are presented in Figure 2.5. The data

for 𝑞 and 𝐶𝐹 were fitted using a Freundlich adsorption isotherm equation (Ahmed et al. 2014;

ASTM WK47571). The volume of AEA adsorbed by the carbon nano platelets on a per gram

basis for the baseline dosage in blended mortar mixtures are interpolated and indicated on Figure

2.5. Tables A.5 and A.6 with the data used to construct Figure 2.5 are included in Appendix A.

The Freundlich equation directly quantifies the adsorption capacity by carbon nano platelets as a

function of baseline AEA dosage in the control mix. To determine the adjusted dosages, the

quantified adsorption capacity is added to the established baseline dosage to obtain the required

AEA concentration for the carbon nano platelet blend mixtures. It is important to note that the

developed isotherms in Figure 2.5 are specific to the carbon nano platelets, AEAs, and cement

tested in this study. The good correlation of results with the Freundlich model implies that the

contact time employed in this technique sufficiently allowed for full physical adsorption of AEA

by the carbon nano platelets. Insufficient equilibrium time is a critical factor that can lead to

lower-than-actual measurements of adsorption capacity (Wang et al. 2016). An advantage of the

combined isotherm technique is that it ensures accurate quantification of adsorption capacity

with a standardized endpoint, in comparison to the dynamic foam index test with a subjective

endpoint yielding inconsistent results (Folliard et al. 2009). A secondary advantage of the

combined isotherm technique is that it accounts the chemisorption demand of the cement

(Ahmed et al. 2014). The researcher is not left to judge if the equilibrated AEA concentrations

are fully allocated to the carbon adsorption capacity as the technique embraces a conservative

measure of including 20 g of cement to each isotherm point to ensure full chemisorption.

16

a.

b.

Figure 2.5: Combined adsorption isotherms for a) SYN AEA and b) VR AEA

17

Based on the interpolation of the SYN isotherm (Figure 2.5a) an adjusted AEA dosage of 555

ml/100 kg cement was determined for the mortar mixtures at the 0.5 wt% carbon nano platelets

substitution level. Based on the interpolation of the VR isotherm (Figure 2.5b) an adjusted AEA

dosage of 1420 ml/100 kg cement was determined for the mortar mixtures at the 0.5 wt% carbon

nano platelets substitution level.

2.3.2 Fresh Mortar Properties and Compressive Strength

As reported in Table 2.3, the baseline AEA doses in the control mixes have yielded ideal flow

properties close to the target range of 100 - 130%. In comparison, carbon nano platelet

replacement of 0.5 wt% in mortars resulted in flows approximately 10% below the control

mixtures. These results could be credited to the high surface area of carbon nano platelets that

inflicts high water demand to lubricate their surfaces, hence limiting the accessible free water in

the fresh paste. These observed reductions in flow are in agreement with other researchers

(Wang et al. 2015; Lv et al. 2016; Cao et al. 2016; Lu et al. 2016). In GO blended cement

composites substituted in a range of 0.03 to 0.08 wt%, reductions in flow diameter of up to 40 %

have been reported (Pan et al. 2015; Gong et al. 2015; Shang et al. 2015).

Table 2.3: Fresh and hardened properties of control and carbon blended mixes

Mixture ID

wt% carbon

nano

platelet

substitution

AEA

dosage

(ml/100kg

cement)

Flow

(%)

Avg. Air

content

(vol. %)

Avg. 7 d

compressive

strength

(MPa)

SYN @ baseline 0 196 92 9.9 ± 0.62 45.0 ± 0.80

0 196 83

SYN + C @ baseline 0.5 196 86 2.9 ± 0.24 66.0 ± 0.56

0.5 196 84

SYN + C @ adjusted 0.5 555 83 6.5 ± 0.24 44.7 ± 1.44

0.5 555 84

VR @ baseline

0 780 95 8.6 ± 0.16 43.1 ± 0.82

0 780 95

VR + C @ baseline 0.5 780 85 7.9 ± 0.16 43.7 ± 0.29

0.5 780 84

VR + C @ adjusted 0.5 1420 87 7.9 ± 0.27 50.1 ± 0.40

0.5 1420 87

18

a.

b.

Figure 2.6: Bulk air content in mortar mixtures containing a) SYN AEA and b) VR AEA

19

From Table 2.3, at the baseline dosage, the SYN carbon blended mixture had 70% less air

content than the control mix, and a corresponding increase in strength. For the VR carbon

blended mixture, the reduction in air content was less pronounced. In both cases, after applying

the adjusted AEA dosages, air contents for the carbon blended mixtures were substantially

increased to similar levels to control mixtures.

The relationship between air content in carbon blended mortars versus increasing admixture

dosage is explored further in Figure 2.6. Both the carbon blended SYN and VR mixtures show a

positive linear trend, but with marked variation in slope. This signifies non-uniform carbon

adsorption capacity across the two AEAs. The carbon nano platelets exhibit a higher adsorption

capacity for synthetic AEA. This corresponds with the results obtained from the SYN isotherm

(Figure 2.5a) where large volume adjustments are required with respect to the baseline dosage.

Additionally, the relationship between air content in the carbon blended mixtures with respect to

AEA dosage appear to be less consistent for VR AEA. The variability makes it difficult to

establish quantitative relationships on the adsorption capacity of carbon nano additives. This is

particularly true if mortar mix designs are to be scaled to concrete mixture designs.

Since the compressive strength of concrete is predominately controlled by porosity, mechanical

results must be compared under similar air content conditions to have a non-biased evaluation of

the potential toughening effects contributed by carbon nano platelets. Consequently, it may be

implied that observed strength improvements might be attributed to the lower porosity rather

than the effectiveness of carbon nano platelets as reinforcing material. The results presented here

diverge from the mechanical improvements noted in previous studies (Pan et al. 2015; Lv et al.

2014; Wang et al. 2015; Shang et al. 2015; Tong et al. 2016), and it is not clear whether these

studies conducted mechanical testing under equivalent air content conditions. Additionally, Du et

al. (2016) explained that graphene nano platelets, although larger than C-S-H particles, fall

within the same length scale as the interfacial transition zones (ITZ). As such, the dimensions of

graphene nano platelets are ineffective in transferring stresses and supplying a bridging effect

over ITZs.

20

2.3.3 Automated Air-void Analysis

Air-void parameters and air void chord length distributions are reported in Table 2.4 and Figures

2.7-2.8. The uncertainties reported in Table 2.4 were calculated based on stereological

approaches (Snyder et al. 2001). In the context of freeze-thaw durability, the evaluated spacing

factor is determined to be the most critical parameter in judging the compatibility between

carbon nano additives and AEAs in cement composites.

Table 2.4: Mortar mixture air void parameters

Mixture ID

wt% carbon

nano platelet

substitution

AEA dosage

(ml/100kg

cement)

Air content

(vol. %)

Specific

surface

(mm-1

)

Spacing factor

(mm)

SYN @ baseline 0 196 5.69 ± 0.42 30.5 ± 1.76 0.191 ± 0.008

SYN + C @ baseline 0.5 196 3.07 ± 0.38 20.9 ± 1.95 0.370 ± 0.020

SYN + C @ adjusted 0.5 555 3.97 ± 0.36 36.7 ± 2.54 0.188 ± 0.009

VR @ baseline 0 780 7.21 ± 0.46 33.5 ± 1.74 0.155 ± 0.005

VR + C @ baseline 0.5 780 4.32 ± 0.44 17.0 ± 1.11 0.390 ± 0.020

VR + C @ adjusted 0.5 1420 5.81 ± 0.40 39.5 ± 2.36 0.146 ± 0.005

In this study, the AEA baseline dosages were designed such that an optimal spacing factor of <

0.20 mm was attained in the control mixes. At the baseline dosages, the carbon blended mixtures

experienced a substantial increase in spacing factor from 0.191 to 0.370 mm and 0.155 to 0.390

mm for the SYN and VR mixtures respectively. At the 0.5 wt% carbon platelet substitution level,

the unaccounted adsorption capacity significantly rendered the AEAs ineffective in terms of

entraining uniformly dispersed air-voids.

Mortar mixtures with the adjusted dosages of 555 ml of SYN AEA/100kg cement and 1420 ml

of VR AEA/100kg cement recovered the desirable air void parameters. Based on the isotherms,

the addition of 0.5 wt% carbon nano platelets required 1.8 times higher VR AEA doses and 2.8

times higher SYN AEA doses to maintain the equivalent desirable air void parameters found in

control mixtures.

Spacing factor measurements for carbon blended mixtures containing increasing AEA dosages

are provided in Figure 2.7. As shown for both AEAs, the adjusted dosages determined from the

isotherm technique achieved desirable spacing factor results. Generally, as AEA dosages

21

increase, the spacing factor decreases. Initial attempts to fit the data with an exponential decay

relationship demonstrated a poor correlation. This may be attributed to the coalescence of

entrained air voids at high AEA dosages, causing an increase in the spacing factor as opposed to

following an exponential decay trend.

a.

b.

Figure 2.7: Spacing Factor with the application of a) SYN AEA and b) VR AEA

Figure 2.8 shows the air-void intercept distributions for all mixtures listed in Table 2.4. The

distributions were fitted to a log-normal distribution, a common procedure for describing

entrained air void systems (Snyder et al. 2001; Roberts & Scheiner 1981). Parameters of the

fitted distributions are shown in Tables 2.5. The different classification of pores in concrete play

a crucial role in the macro performance of the composite and sized µm to mm entrained air voids

are highly acknowledged for governing freeze thaw related deteriorations. In the control

22

mixtures, a high frequency of fine air-voids in the 0.1 mm size range and fewer mm sized air

voids are measured, indicating adequate air entrainment for freeze-thaw durability. In contrast,

the carbon blended mixtures contained at least 77% lower frequencies for these smaller-sized air

voids. After applying AEA dosage adjustments to the carbon blended mixtures, the air-void size

distribution returns within the range of the control mixtures.

a.

b.

Figure 2.8: Air-void intercept length distributions for SYN (a) and VR (b) mixtures

23

Table 2.5: Parameters for fitted log-normal distributions

Mix ID µ σ 95% confidence

interval for µ

95% confidence

interval for σ

SYN baseline 4.224 1.082 [4.168, 4.280] [1.044, 1.122]

SYN +C @ baseline 4.383 1.442 [4.250, 4.516] [1.354 ,1.543]

SYN +C @ adjusted 4.210 1.010 [4.151, 4.269] [0.970, 1.053]

VR baseline 4.230 1.017 [4.186, 4.274] [0.987, 1.049]

VR +C @baseline 4.721 1.071 [4.637, 4.805] [1.015,1.134]

VR + C @ adjusted 4.314 0.980 [4.266, 4.362] [0.947, 1.015]

Figures 2.9 and 2.10 present processed scanner images to provide visualization of the air void

systems for the different mixtures. Control mortars and carbon blended mortars with proper AEA

dosage adjustments exhibited closer air void spacing factors.

a.

b.

c.

Figure 2.9: Flatbed scanner image after greyscale threshold application of sample a) SYN

@ baseline, b) SYN +C @ baseline, and c) SYN +C @ adjusted

a.

b.

c.

Figure 2.10: Flatbed scanner image after greyscale threshold application of sample a) VR

@ baseline, b) VR +C @ baseline, and c) VR +C @ adjusted

24

2.3.4 Calorimetric Results

The catalytic behavior of nano carbon materials in cement hydration for the potential of

enhanced early age strength development have been confirmed and acknowledged in previous

research works (Lin et al. 2016; Horszczaruk et al. 2015; Sobolkina et al. 2016). From Figure

2.11, the addition of carbon nano platelets containing the baseline dosage had negligible

influence on the heat of hydration compared to the control mixtures. No evident increase in

exothermic peaks and acceleration in the reaction rates between the two calorimetric curves was

observed.

a.

b.

Figure 2.11: Calorimetric curves for mixes containing (a) 196 ml/100kg cement of SYN

AEA and (b) 780 ml/100kg cement of VR AEA

2.4 Conclusions

An adopted combined adsorption isotherm technique was tested with cabon nano platelets to

evaluate its effectiveness in quantifying the carbon adsorption capacity, serving as a strategy to

mitigate interferences with air entrainment for freeze-thaw durability. The AEA dosage

adjustments estimated from the isotherms resulted in spacing factors of ˂ 0.20 mm in carbon

blended specimens, in contrast to the unfavourable air void parameters measured in unadjusted

carbon blended mortars. The combined adsorption isotherm test appears to be a promising

approach to correct for interference between carbon nano additives and AEAs, although a larger

variety of carbon nano additives and AEA combinations should be tested.

25

Chapter 3: Assessment of Carbonation Sequestration Potential of Concrete blocks with an Accelerated Environmental Exposure

Chamber

Chapter 3 is derived from a paper submitted to 13th

Canadian Masonry Symposium, Halifax

Canada, June 4-7, 2017.

3.1 Introduction

3.1.1 Background

Carbonation injection technology is being adopted by the concrete block manufacturing industry

as part of an effort to sequester CO2 (Shi & Wu 2008; Shi et al. 2012a; Shi et al. 2012b; El-

Hassan et al. 2013a; Kashef-Haghighi et al. 2015; Monkman & Macdonald 2016; Zhanet al.

2016). Before the blocks have hardened, CO2 is introduced and precipitates within the blocks as

nanometer-scale crystalline CaCO3 (Goodbrake et al. 1979; Shtepenko et al. 2006; El-Hassan &

Shao 2015). The resulting reactions between CO2 gas with freshly hydrating cement are rapid

and exothermic (Goodbrake et al. 1979). The consumption of CO2 for the nucleation of calcium

carbonate effectively binds CO2 in concrete.

As carbonation curing is introduced at early age, C2S and C3S are the dominant phases subjected

to carbonation, drawing acceleration in early strength gain (Kashef-Haghighi & Ghoshal 2010).

Previous research suggests that concrete products treated with carbonation curing benefit from

improved strength and reduced water absorption (Monkman & Shao 2010; Rostami et al. 2015;

Shao et al. 2014; El-Hassan & Shao 2014). The improved performance is attributed to

modifications in the microstructure of carbonated paste. Carbonated paste was found to contain

calcium-silicate-hydrates (C-S-H) structures with longer chains, along with CaCO3 of higher

crystallinity. Furthermore, CaCO3 precipitates were examined to provide a widespread pore-

filling effect, saturating narrow pores in the size range of 4 µm (Kashef-Haghighi & Ghoshal

2013). The reduction in pore volume from the growth of CaCO3 deposits was demonstrated by

mercury intrusion porosimetry analyses.

26

Concrete blocks produced using CO2 injection are associated with a 1.4 wt% reduction in CO2

emissions as compared to conventional concrete blocks (Monkman & MacDonald 2016). In

similar studies, Kashef-Haghighi and Ghoshal (2010) found the CO2 adsorption by mortar to

have achieved a maximum carbonation efficiency of 14 - 19%. Ideally, free metal oxides in

cement should theoretically allow for CO2 storage amounting to half the cement’s weight. As

such, the authors suggested the pore filling effects of CaCO3 in cement paste to limit the

diffusion of calcium ions and carbonate ions for carbonation reactions (Kashef-Haghighi, &

Ghoshal 2013). Concrete blocks also naturally carbonate in the presence of atmospheric CO2, but

over a period of years or decades (Pade & Guimaraes 2007). Although often acknowledged as a

deterioration mechanism, weathering carbonation has also been regarded as an opportunity to

reabsorb CO2 into concrete throughout its service life. Analysis by Jacobsen and Jahren (2002)

quantified that 16% of CO2 emissions from calcination are recovered by Norwegian concrete

through weathering carbonation over its life span. Pade and Guimaraes (2007) modelled 24%

CO2 uptake in concrete structures attributed to weathering carbonation over a century. As the

rate of carbonation is contingent on the pore system of hardened concrete, denser microstructures

from early age carbonation may affect the diffusion of atmospheric CO2 into carbonation cured

concrete. Hence, it is uncertain whether early-age CO2 injection impedes, enhances, or have

negligible influence on the long-term natural carbonation process over the life cycle of a concrete

block.

In this chapter, the influence of carbonation injection on natural carbonation rates is investigated

with concrete blocks retrieved from an industrial block manufacturer using an accelerated

carbonation experiment. Half of the blocks were produced using CO2 injection, and the other half

were produced without CO2 injection. As-received, one group was painted with a yellow stripe,

and the other group was painted with a red stripe. The blocks were of equivalent age and

provided “blind” so that it was unknown whether the yellow or red population was CO2 injected.

For accelerated simulations of the natural carbonation process, CO2 concentrations in the range

of 4-5% over one week have been reported as equivalent to one year of natural exposure (Ho &

Lewis 1987; Sanjuan et al. 2003). However, concentrations > 3% have also been reported to

induce mineralogical changes that deviate from natural atmospheric carbonation (Castellote et al.

27

2009). Relative humidity is another important parameter for accelerated carbonation testing, and

an RH of 65% has been reported as optimal for the promotion of carbonation reactions (RILEM

1988). Carbonation rates of the blocks are monitored and compared through phenolphthalein

indicator, optical birefringence in thin sections, and profile grinding coupled with furnace

decomposition (RILEM 1988; Lo & Lee 2002; Chang & Chen 2006; Villain et al. 2007; Galan et

al. 2012; El-Hassan et al. 2013b; Morshed et al. 2015). However, testing a real-world industrial

product that contains carbonate aggregates significantly complicates the analysis. Furthermore, it

is also common practice to inter-grind limestone with the clinker during Portland cement

production, adding yet another source of carbonate material.

3.1.2 Types of Concrete Carbonation

As introduced, gaseous carbon dioxide may interact with concrete through either weathering

carbonation or carbonation curing.

Weathering carbonation proceeds in mature concrete over prolong periods and under

atmospheric pressure levels. Reactants of the process include CO2, concrete pore solution,

calcium hydroxide, and hydrated calcium silicates (Slegers & Rouxhet 1976). It is interpreted as

a deterioration mechanism as the consumption of calcium hydroxide decomposes C-S-H gel

within the paste. An affiliated decline in the pH of concrete pore solution prompts the

depassivation and corrosion of steel reinforcements embedded in concrete, leading to concrete

cracking (Parrott 1990). Chemical reactions involved in weathering carbonation are as follows

(Possan et al. 2017):

Ca(OH)2 + CO2 → CaCO3 + H2O Equation 3.1

3CaCO∙2SiO2∙3H2O + 3CO2 → 3CaCO3 + 2SiO2∙H2O Equation 3.2

Weathering carbonation is primarily initiated under humidity conditions between 40 to 90% RH.

Carbonation curing proceeds in fresh concrete through controlled exposure to CO2 for a limited

duration, and simultaneously with cement hydration. Carbonation curing techniques have been

28

extensively developed due to their promising capability for mineral CO2 sequestration and

advantageous strengthening effects. Reactants of the process include CO2, C3S and C2S,

producing solely C-S-H and calcium carbonates. As documented by Young et al (1974), the

diffused CO2 gas in concrete enters the aqueous phase and forms carbonic acid. The acid then

ionizes to H+, HCO3

-, and CO3

2- ions. In the ionization process, pH of the cement matrix is

reduced but recovered as hydration resumes. The subsequent dissolution of the silicate cement

phases are expressed in the following equations (Goodbrake et al. 1979).

3 CaO∙SiO2 + (3-x)CO2 + yH2O xCaO∙SiO3∙yH2O + (3-x)CaCO3 Equation 3.3

2 CaO∙SiO2 + (2-x)CO2 + yH2O xCaO∙SiO3∙yH2O + (2-x)CaCO3 Equation 3.4

The formed products of C-S-H like gel and calcite are subsequently carbonated to silica gel and

CaCO3. The development of large carbonate crystals is the main source of observed high initial

strength gain. On the other hand, CO2 interaction with C3A and C4AF are unaccounted for as

they are non-reactive during the limited exposure time (Shtepenko et al. 2006).

29

3.2 Experimental

3.2.1 Carbonation Chamber

To accelerate the carbonation process, the blocks were placed in a chamber maintained at 30°C,

55% RH, and 3% CO2 (Figure 3.1) (McGrath 2005). A saturated salt solution of a commercial

de-icer blend of NaCl, KCl, and Ca2Cl was used to control humidity (Young 1985). In order to

fit blocks inside the chamber, the samples were cut in half. To demonstrate chamber

performance, Figure 3.2 shows a typical day’s worth of temperature, humidity, and CO2

concentration data.

Figure 3.1: Schematic of test chamber, adapted from McGrath (2005)

30

Figure 3.2: Twenty-four hours of carbonation chamber temperature, humidity, and CO2

concentration data

3.2.2 Monitoring Carbonation by Phenolphthalein Indicator

Solution

At the beginning of the experiment, a pair of yellow blocks and a pair of red blocks were set

aside as controls. A 50 mm thick slice was cut from each block, and the fresh cut face sprayed

with a phenolphthalein solution. When the solution comes into contact with calcium hydroxide

present in the hydrated paste, the surface turns pink. Calcium hydroxide converts to CaCO3 when

exposed to CO2, hence areas that do not turn pink after phenolphthalein application are

considered carbonated (RILEM 1988). Additional pairs of yellow and red blocks were placed in

the carbonation chamber, and pulled at exposure intervals of two, four, eight, and sixteen days.

3.2.3 Monitoring Carbonation by Profile Grinding and Loss on

Ignition

Carbonation profile tests were performed on the control blocks and the blocks exposed for

sixteen and thirty days. For the profiling, layers of block were removed by diamond grinding, at

one millimeter increments, from the surface inward, and the powder collected layer by layer.

About 2-3 grams of powdered block were collected from each layer. The initial masses were

31

recorded after drying at 105°C, and recorded again after firing in an ignition furnace at 550°C

and 900°C. The difference between the masses at 900°C (the calcination temperature to liberate

CO2 from CaCO3) and 550°C (the dehydration temperature to remove chemically bound H2O in

the hydrated paste), divided by the initial mass, provides an approximate measure of the

carbonate content (El-Hassan et al. 2013b). To verify the validity of the approach, known blends

of gypsum and calcium carbonate were prepared and tested, as shown in Figure 3.3. Good

agreement was found between the expected and measured mass losses associated with CO2 from

the calcite and H2O from the gypsum.

Figure 3.3: Results of verification test on calcite and gypsum blends fired in ignition

furnace

32

3.2.4 Monitoring Carbonation by Petrographic Microscope

Epoxy impregnated polished thin sections were prepared from blocks after zero, two, and thirty

days exposure. To minimize carbonation of the samples during preparation, the thin sections

were prepared anhydrously, using mineral oil and kerosene as coolant. Furthermore, to avoid

subsequent carbonation after preparation, glass coverslips were fixed to the thin section surface

using mineral oil.

Under a petrographic microscope, certain minerals, when placed between two polarized filters

(where the orientations of the filters were set 90º to each other), exhibit interference colours as

the minerals are revolved in different directions. Such minerals are termed anisotropic. Dolomite

(CaMg(CO3)2) and quartz (SiO2) are two common examples of anisotropic minerals. The

interference colours arise due to the fact that as light enters an anisotropic mineral, it is split into

two orthogonal waves that travel at different velocities. After leaving the mineral, the waves

return to their original velocities, but with an associated shift in phase. In a petrographic

microscope, polarized light entering an anisotropic mineral from below is split into the two

orthogonal waves, and the components of these waves that are parallel to the upper polarizing

filter, when combined, can yield characteristic interference colours. The interference colours and

intensities are a function of the mineral’s thickness, orientation and the difference in wave

velocity. Other transparent minerals or materials, when placed between cross polarized filters

appear black, regardless of their orientation. Such materials are termed isotropic. Halite (rock

salt) and glass are two common examples of isotropic materials. For those less familiar with

petrographic methods, an excellent introduction is provided by Raith et al. (2012).

As hardened cement paste carbonates, microscopic crystals of calcite and aragonite (two

different varieties of CaCO3) are formed. Calcite and aragonite are both anisotropic minerals,

therefore as carbonated paste is observed under cross polarized light, they impart a distinctive

bright appearance compared to non-carbonated paste. Cement paste with a bright appearance

under cross polarized light is diagnostic of carbonation (Walker et al. 2006; St. John et al. 1998).

The utility of a petrographic microscopic as applied to concrete is not limited to the detection of

carbonated paste. In the case of the concrete blocks examined in this research, the petrographic

microscope was also used to identify the aggregates used, and to directly observe porosity

33

(Figure 3.4). Manufactured (crushed) dolostone aggregate particles were identified due to their

bright appearance under cross polarized light, and the typical rhombic shape of the individual

dolomite crystals that make up the particles. Light-weight expanded glass aggregate particles

were easily identified due to their dark appearance under cross polar filters, as well as their many

internal spherical voids. A fluorescent yellow dye was added to the epoxy to assist with the

observation of pore space. The epoxy fills not only the larger µm to mm scale void spaces, but

also the capillary pore spaces within the cement paste. A blue filter is used to excite the dye,

which fluoresces green and a yellow blocking filter is used to remove blue wavelengths, so that

only the fluoresced green wavelengths from pore spaces can be seen (Walker et al. 2006).

a. b.

c.

Figure 3.4: Crossed polar (a), fluorescent (b), and plane polarized (c) images with example

entrapped air void labeled “V” , light weight expanded glass aggregate particle “L”,

cement paste “P”, and dolostone aggregate particle “D”

34

3.3 Results

3.3.1 Phenolphthalein Stain

Figure 3.5 shows the slices cut from the blocks after application of the phenolphthalein solution.

For the control blocks, the entire surface is stained pink, indicating that carbonation was

negligible. After eight days exposure, the pink coloration is significantly fainter, where the pink

coloration is absent within the first 1-2 cm of the block exterior. After sixteen days exposure, the

pink coloration is almost completely absent, with only traces remaining in the yellow blocks.

3.3.2 Profile Grinding

Figure 3.6 shows the profile data collected from the blocks exposed at zero and sixteen days, and

Figure 3.7 compares the populations of data collected at zero, sixteen, and thirty days exposure.

From Figure 3.6, there does not appear to be a gradient of carbonate content versus depth. There

also does not appear to be any significant difference in carbonate content between the yellow and

red blocks, but both populations show consistently higher carbonate content after exposure.

Furthermore, from Figure 3.7 the carbonate content appears relatively stable between sixteen and

thirty days exposure.

A t-test for two population means assuming equal variance were conducted to see if the CO2

injection technology had any significant influence on the initial bulk carbonate content (Table

3.1). The test was performed at a significance level (α) of 0.05. The null hypothesis (H0) was that

the means (µR, µY) of the two populations (red and yellow blocks) were equal. The alternative

hypothesis (HA) was that µR ≠ µY. In Table 3.1, the absolute value of the measured t-statistic is

less than the t-critical value, thus the null hypothesis could not be rejected, and thus it appears

that CO2-injection did not introduce a significant variation in the initial bulk carbonate content.

35

Figure 3.5: Phenolphthalein staining of fresh surfaces from blocks subjected to specified

exposure times in carbonation chamber (tic marks every cm)

Red blocks Yellow blocks

0 d

2 d

4 d

8 d

16 d

36

Figure 3.6: Bulk carbonate content versus depth

Table 3.1: Test for significance of CO2 injection technology on carbonate content at zero days exposure

Statistic red blocks yellow blocks

Mean 13.72 14.08

Variance 0.3402 0.7995

Observations 20 20

Pooled Variance 0.5698

t Stat -1.539

P(T<=t) two-tail 0.1320

t Critical two-tail 2.024

Additional t-tests were performed after sixteen and thirty days exposure to test whether or not

CO2 injection technology slows down the carbonation process (Tables 3.2 and 3.3). The tests

were performed at a significance level (α) of 0.05. The null hypothesis (H0) was that the means

(µR, µY) of the two populations were equal. The alternative hypothesis (HA) was that µR ˂ µY.

After sixteen days exposure (Table 3.2), the measured t-statistic is greater than the t-critical

value, thus the null hypothesis could not be rejected, and it appears that CO2-injection does not

interfere with carbonation. However, at thirty days exposure (Table 3.3), the measured t-statistic

37

is less than the t-critical value, thus the null hypothesis is rejected, and it appears that CO2-

injection may have slowed down the carbonation process. The two t-tests demonstrated

conflicting results, but the profile grinding technique is also susceptible to the heterogeneity of

the material at the mm scale, as the presence or absence of the dolomitic (carbonate) aggregate

particles introduces considerable interference within the materials sampled per layer. From the

phenolphthalein tests, it appears that carbonation is almost complete after sixteen days. Tables

3.4 and 3.5 compare carbonate content for the same block colour series at sixteen and thirty days

exposure, to explore whether or not significant additional carbonation occurs after sixteen days.

In both cases, |t(stat)| > t(crit two-tail), therefore the difference in mean carbonate content

between the sixteen and thirty days blocks is statistically significant. For the red series (Table

3.4), blocks at sixteen days exposure measured higher mean carbonate content than thirty days

exposure. In contrast, yellow blocks at sixteen days exposure measured lower mean carbonate

content than thirty days exposure (Table 3.5), implying further carbonation. Similarly, it is likely

that interference from dolomitic aggregate particles overshadows any meaningful measurements

of carbonate content attributed to carbonation.

38

Figure 3.7: Distribution of bulk carbonate content measurements

39

Table 3.2: Test for significance of CO2 injection technology on carbonate content at sixteen days

exposure


Mean 15.70 15.23

Variance 0.9500 1.136

Observations 20 20


t Stat 1.429



Table 3.3: Test for significance of CO2 injection technology on carbonate content at thirty days exposure


Mean 15.00 16.05

Variance 1.242 1.472

Observations 20 20


t Stat -2.841



Table 3.4: Test for significance of carbonate content in red blocks at sixteen and thirty days exposure

Statistic 16 days 30 days

Mean 15.70 15.00

Variance 0.9499 1.242

Observations 20 20


t Stat 2.089



Table 3.5: Test for significance of carbonate content in yellow blocks at sixteen and thirty days exposure

Statistic 16 days 30 days

Mean 15.23 16.05


Observations 20 20


t Stat -2.261



40

3.3.3 Petrographic Microscope

Figures 3.8 through 3.10 consist of grayscale optical images of the polished thin sections. Under

cross-polarized light (Figure 3.8) the anisotropic dolostone aggregate particles are bright, while

the isotropic LWA particles are completely dark. Also under cross-polarized light, the

carbonated paste exhibits an intermediate brightness, while non-carbonated paste remains dark.

The fluorescent images (Figure 3.9) show abundant irregularly-shaped entrapped air voids in the

paste, as well as the smaller spherical voids within the light weight aggregate (LWA) particles.

In the transmitted plane polarized light images (Figure 3.10) the LWA particles are primarily

translucent and clear, as are the dolostone aggregate particles, while the paste appears darker.

To help isolate and quantify the relative amounts of carbonated paste, the crossed polarized,

fluorescent, and plane polarized light images were combined in 24-bit (0-255 intensity channels

per band) red green blue (RGB) colour space (Figure 3.11). In Figure 3.11, carbonated paste

appears magenta or pink. In RGB colour space, the magenta hue is the result of brighter

intensities in the red (cross polarized light) and blue (plane polarized light) bands, with less

intensity in the green (fluorescent) band. For other detectable features, dolostone aggregate

particles appear yellow/orange, porosity appears light blue, non-carbonated paste appears dark

blue, and majority of LWA particles appear green. At the top of several images, rounded quartz

sand grains (yellow) are present. The quartz sand was added external to the blocks during the

epoxy impregnation to help conserve epoxy. A colour threshold (R ≥ 120, G ≤ 120, B ≥ 120) was

applied to extract the carbonated (magenta/pink) paste pixels, with the result shown in Figure

3.12. Figure 3.13 tabulates the carbonated pixel populations versus depth.

T-tests for two population means assuming equal variance were also performed for the pixel

statistics obtained from Figure 3.11, with results presented in Tables 3.6 – 3.8. The results from

Table 3.6 suggest that at zero days, the red and yellow bocks were statistically different.

Specifically, the mean carbonated pixel area was higher for the red block as compared to the

yellow block, implying that the red block was subjected to CO2 injection. Based on Tables 3.7

and 3.8, the carbonated pixel populations between red and yellow blocks at either two, or thirty

days were analyzed to be not statistically different at 95% level of confidence. Unlike the profile

grinding and ignition method, the petrographic microscope approach was able to distinguish

41

between carbonate aggregate and carbonate paste, and provide a more accurate assessment of the

degree of carbonation. Although the initial degree of carbonation was slightly higher for the

CO2-injected red blocks, at two days and at thirty days in the accelerated carbonation chamber,

the degree of carbonation was equivalent for the CO2-injected and non-CO2-injected blocks.

42

Yellow 0 d 2 d 30 d

Red 0 d 2 d 30 d

Figure 3.8: Crossed polarized illumination of thin sections prepared from masonry blocks

at various exposure time; block exterior surface oriented at top, tic marks every mm

43

Yellow 0 d 2 d 30 d

Red 0 d 2 d 30 d

Figure 3.9: Fluorescent images to show porosity (brighter regions indicate pore space);

block exterior surface oriented at top, tic marks every mm

44

Yellow 0 d 2 d 30 d

Red 0 d 2 d 30 d

Figure 3.10: Transmitted plane polarized light images; block exterior surface oriented at

top, tic marks every mm

45

Yellow 0 d 2 d 30 d

Red 0 d 2 d 30 d

Figure 3.11: RGB image of combined crossed-polarized, fluorescent, and transmitted plane

polarized light image. Block exterior surface oriented at top, tic marks every mm

46

Yellow 0 d 2 d 30 d

Red 0 d 2 d 30 d

Figure 3.12: Binary image of carbonated paste pixels (black); block exterior surface

oriented at top, tic marks every mm

47

Figure 3.13: Optical analysis of carbonated paste versus depth from polished thin sections

Table 3.6: Test for significance of CO2 injection technology on carbonate paste pixels at zero days

exposure Statistic red blocks yellow blocks

Mean 3.523 2.109

Variance 0.6949 0.9453

Observations 20 20


t Stat 4.939

P(T<=t) two-tail 1.608E-05


Table 3.7: Test for significance of CO2 injection technology on carbonate paste pixels at two days

exposure Statistic red blocks yellow blocks

Mean 4.919 4.010


Observations 20 20


t Stat 1.421



48

Table 3.8: Test for significance of CO2 injection technology on carbonate paste pixels at thirty days

exposure Statistic red blocks yellow blocks Mean 12.41 11.27 Variance 6.257 3.274 Observations 20 20 Pooled Variance 4.765 t Stat 1.646 P(T<=t) two-tail 0.1080 t Critical two-tail 2.024

3.4 Conclusions

Three different methods of determining the extent of carbonation were explored, to determine the

influence of CO2 injection on environmentally carbonation rates in industrially-produced

concrete blocks. From a qualitative perspective, the traditional phenolphthalein stain approach

showed equivalent carbonation rates for CO2-injected and non CO2-injected blocks. The profile-

grinding ignition-oven method suffered from heterogeneity of the material at the mm scale, since

the presence or absence of the dolomitic (carbonate) aggregate particles introduced significant

noise, considering the limited amount of material sampled per layer (2 to 3 grams). The optical

microscope method allowed for the distinction between carbonate aggregate and carbonate paste,

and showed equivalent carbonation rates in profile for the CO2-injected and non CO2-injected

blocks.

49

Chapter 4: Significance of Findings and Recommendations

There is huge incentive for researchers to pursue innovative carbon sequestration techniques

linked to concrete as it offers opportunities to control significant GHG emissions produced by

the cement and concrete industry. This study investigated aspects arising from two approaches to

CO2 sequestration as applied to concrete; 1) CO2 capture by carbon nano platelets when used as a

concrete additive, and 2) CO2-injection curing of concrete blocks and its influence on long-term

carbonation. Major findings in this study include:

1) In this pioneer research work to adopt the combined adsorption isotherm technique in

application with carbon nano platelets, the developed isotherms for SYN and VR AEA yielded

successful dose adjustments to compensate for the carbon adsorption capacity. The proposed

adjustments lowered the spacing factor to be equivalent to the control samples. Consequently,

the developed isotherms were evaluated as feasible tools in predicting the required dosage

adjustments for carbon blended mortar.

2) For the accelerated CO2 curing technique, qualitative evidence from the phenolphthalein stain

and quantitative petrographic measurements showed equivalent carbonation rates for CO2-

injected and non CO2-injected blocks regardless of exposure time in the accelerated carbonation

chamber.

Future work in the following areas is recommended to build on these findings, as follows:

1) Within this project, only one type of carbon nano platelets were applied with synthetic and

Vinsol resin AEAs. As classes of surfactants function physically and chemically different to

entrain and stabilize air in concrete, the adsorption mechanism of carbon for the range of

surfactants may have drastic differences. The combined adsorption isotherm technique should be

tested across a matrix of surfactants and types carbon-based nano materials to verify its success

in application with derivative carbon-based materials.

2) Follow-up studies with long-term environmental carbonation experiments could be performed

to better correlate accelerated exposure with natural exposure.

50

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63

Appendices

Appendix A: Combined Isotherm Test Detailed Results

Table A.1: COD results of cement-only isotherm points for SYN AEA

Solution ID COD Bki (mg COD/L) Average COD Bki (mg

COD/L)

1 vol% AEA

389.368 373.896

373.896

347.372

368.370

390.473

2 vol% AEA 714.282 688.864

739.701

642.448

712.072

635.817

3 vol% AEA 916.525 923.709

928.795

925.808

Table A.2: COD results of cement-only isotherm points for VR AEA

Solution ID COD Bki(mg COD/L) Average COD Bki (mg

COD/L)

0.3 vol% AEA

265.59135 271.12

276.64285

1 vol% AEA

747.437 742.65

765.11915

715.3874

1.7 vol% AEA

1261.3315 1248.62

1235.91305

64

Table A.3: COD results for SYN AEA

Sample PC (g) Nano

Carbon (g)

Absorbance Average

Absorbance

COD (mg O2/L)

1 vol% AEA 20.06 1.00 0.095 0.096 0.0955 223.596

1 vol% AEA 20.03 1.00 0.099 0.099 0.099 231.332

1 vol% AEA 20.02 1.00 0.103 0.102 0.1025 239.068

2 vol% AEA 20.08 1.00 0.222 0.221 0.2215 502.093

2 vol% AEA 19.99 1.01 0.222 0.222 0.222 503.199

2 vol% AEA 20.08 1.00 0.227 0.225 0.226 512.04

3 vol% AEA 20.03 1.01 0.327 0.327 0.327 735.28

3 vol% AEA 20.03 1.00 0.332 0.333 0.3325 747.437

3 vol% AEA 20.06 1.00 0.334 0.335 0.3345 751.857

Table A.4 : COD results for VR AEA

Sample PC (g) Nano

Carbon (g)

Absorbance Average

Absorbance

COD (mg

O2/L)

0.3 vol% AEA 20 0.5 0.049 0.049 0.049 120.817

0.3 vol% AEA 20 0.5 0.051 0.052 0.0515 126.342

0.3 vol% AEA 20 0.5 0.056 0.056 0.056 136.289

1 vol% AEA 20 0.5 0.238 0.24 0.239 540.774

1 vol% AEA 20 0.5 0.256 0.256 0.256 578.349

1 vol% AEA 20 0.5 0.262 0.262 0.262 591.611

1.7 vol% AEA 20 0.5 0.445 0.447 0.446 998.306

1.7 vol% AEA 20 0.5 0.447 0.447 0.447 1000.52

1.7 vol% AEA 20 0.5 0.46 0.459 0.4595 1028.14

65

Table A.5: Calculated Adsorption Isotherm for SYN AEA

Solution ID COD Bki(mg

COD/L)

COD Fci(mg

COD/L)

ΔA (mg

COD/L)

Cf (vol % AEA)

Q (ml AEA/ g

Carbon)

1 vol% AEA 373.896 221.3854 4.078959 0.592104 0.815792

1 vol% AEA 373.896 223.596 4.019844 0.598016 0.803969

1 vol% AEA 373.896 231.3317 3.81294 0.618706 0.762588

1 vol% AEA 373.896 239.0678 3.606036 0.639396 0.721207

2 vol% AEA 688.864 502.0935 5.422567 1.457743 1.084513

2 vol% AEA 688.864 503.1986 5.390481 1.460952 1.067422

2 vol% AEA 688.864 512.0398 5.133791 1.486621 1.026758

2 vol% AEA 688.864 524.1965 4.780844 1.521916 0.956168707

3 vol% AEA 923.709 735.2801 6.119749 2.388025 1.22394975

3 vol% AEA 923.709 741.911 5.904392 2.409561 1.169186528

3 vol% AEA 923.709 747.4368 5.724928 2.427507 1.144986

3 vol% AEA 923.709 751.8574 5.581357 2.441864 1.116271

Table A.6: Calculated Adsorption Isotherm for VR AEA

Solution ID COD Bki(mg

COD/L)

COD Fci(mg

COD/L)

ΔA (mg

COD/L)

Cf (vol % AEA)

Q (ml AEA/ g

Carbon)

0.3 vol% AEA 271.12 120.8167 1.663123 0.133688 0.665249

0.3 vol% AEA 271.12 126.3425 1.601979 0.139802 0.640791

0.3 vol% AEA 271.12 136.2888 1.491919 0.150808 0.596768

1 vol% AEA 742.65 540.7737 2.718324 0.728168 1.087329

1 vol% AEA 742.65 578.3488 2.212364 0.778764 0.884946

1 vol% AEA 742.65 591.6106 2.03379 0.796621 0.813516

1.7 vol% AEA 1248.62 998.3058 3.408036 1.359196 1.363214

1.7 vol% AEA 1248.62 1000.516 3.377942 1.351177 1.362206

1.7 vol% AEA 1248.62 1028.145 3.001776 1.20071 1.399822

66

Appendix B: Mixture Designs

Table B.1: Mortar Mixture Design Proportions

Mix Description Cementitious Content (kg/m3) w/c Air content (%) Aggregate content (kg/m3) Admixture Dosage (mL/100kg)

GU Carbon nano platelet Avg (vol.%) Std.dev. (vol. %) MasterAir AE 200

MasterAir VR 10

SYN 641.39 0 0.42 5.4 0.280 1272.37 53 _____

SYN 625.80 0 0.42 7.7 0.355 1241.44 98 _____

Control SYN 610.88 0 0.42 9.9 0.693 1211.85 196 _____

SYN +C 654.33 3.29 0.42 2.9 0.284 1305.81 196 _____

SYN +C 634.88 3.19 0.42 5.8 0.306 1266.99 400 _____

SYN +C 630.16 3.17 0.42 6.5 0.270 1257.57 555 _____

SYN +C 624.1 3.14 0.42 7.4 0.354 1245.47 588 _____

SYN +C 605.85 3.04 0.42 10.1 0.277 1209.05 784 _____

SYN +C 597.82 3.00 0.42 11.3 0.157 1193.02 882 _____

VR 638.01 0 0.42 5.9 0.294 1265.65 _____ 260

VR 633.95 0 0.42 6.2 0.330 1257.58 _____ 520

Control VR 619.71 0 0.42 8.6 0.181 1229.33 _____ 780

VR+C 620.74 3.12 0.42 7.9 0.176 1238.75 _____ 780

VR+C 618.73 3.11 0.42 8.2 0.164 1234.71 _____ 1000

VR+C 612.67 3.08 0.42 9.1 0.250 1222.61 _____ 1250

VR+C 603.91 3.03 0.42 10.4 0.444 1205.12 _____ 1365

VR+C 620.76 3.12 0.42 7.9 0.100 1238.75 _____ 1420

67

Table B.2: Mortar Mixture Design for one litre batches with stockpile values

Mix Description Cementitious Content (g) Water

content (g)

Air content (%) Aggregate content (g) Admixture Dosage (mL)

GU Carbon nano platelet Avg

(vol.%)

Std.dev. (vol.

%)

MasterAir AE

200

MasterAir

VR 10

SYN 641.39 0 276.68 5.4 0.280 1272.37 0.34 _____

SYN 625.80 0 269.66 7.7 0.355 1241.44 0.61 _____

Control SYN 610.88 0 262.63 9.9 0.693 1211.85 1.20 _____

SYN +C 654.42 3.29 282.77 2.9 0.284 1306.00 1.29 _____

SYN +C 634.88 3.19 273.01 5.8 0.306 1266.99 2.55 _____

SYN +C 630.16 3.17 269.99 6.5 0.270 1257.57 3.51 _____

SYN +C 624.10 3.14 267.19 7.4 0.354 1245.47 3.69 _____

SYN +C 605.90 3.04 258.19 10.1 0.277 1209.16 4.77 _____

SYN +C 597.82 3.00 254.15 11.3 0.157 1193.02 5.30 _____

VR 638.01 0 273.85 5.9 0.294 1265.65 _____ 1.66

VR 635.95 0 271.27 6.2 0.330 1261.61 _____ 3.31

Control VR 619.71 0 262.68 8.6 0.181 1229.33 _____ 4.83

VR+C 620.74 3.12 264.44 7.9 0.176 1238.75 _____ 4.87

VR+C 618.73 3.11 262.17 8.2 0.164 1234.71 _____ 6.22

VR+C 612.67 3.08 258.02 9.1 0.250 1222.61 _____ 7.70

VR+C 603.91 3.03 253.61 10.4 0.444 1205.12 _____ 8.28

VR+C 620.76 3.12 260.34 7.9 0.100 1238.75 _____ 8.86

68

Appendix C: Fresh Mortar Properties Detailed Results

Table C.1 : Fresh Properties for Mortars with SYN AEA

Admixture Type

wt. % carbon

nano platelet

substitution

AEA dosage

(ml/100kg

cement)

Flow (%) Air content

(vol. %)

0 53 88 5.1,5.5,5.44

0 53 81 5.6,5.0,5.7

0 96 80 7.21,8.1,8.0,

0 96 89 7.9,7.67.7.4

0 196 92 10.9, 9.5, 8.9

0 196 83 10.0, 10.3, 9.8

0.5 196 86 3.3, 2.5, 2.8

Synthetic AEA 0.5 196 84 2.7, 3.1, 2.9

0.5 400 76 5.4, 6.2, 5.7

0.5 400 81 6.0,5.66,6.1

0.5 555 83 6.15, 6.9, 6.5

0.5 555 84 6.4, 6.23, 6.6

0.5 588 83 7.35,7.14, 7.83

0.5 588 77 7.46,7.21, 7.5

0.5 784 85 9.87,10.15,10.37

0.5 784 82 9.6,10.24,10.08

0.5 882 86 11.5, 11.27,11.2

0.5 882 80 11.1, 11.45, 11.3

69

Table C.2: Fresh Properties for Mortars with VR AEA

Admixture Type

wt. % carbon

nano platelet

substitution

AEA dosage

(ml/100kg

cement)

Flow (%) Air content

(vol. %)

0 260 85 5.4, 6.1, 5.88

0 260 86 5.7,5.9,6.23

0 520 87 5.9, 6.3,6.5

0 520 90 5.87,6.7,6.15

0 780 95 8.5, 8.35, 8.4

0 780 95 8.81, 8.65, 8.7

Vinsol resin AEA 0.5 780 85 7.9, 7.75, 8.1

0.5 780 84 7.8, 8.15, 7.78

0.5 1000 77 8.12, 8.4, 8.32

0.5 1000 80 7.9,8.22,8.3

0.5 1250 84 8.85,9.34, 9.11

0.5 1250 83 9.05, 9.4, 8.7

0.5 1365 86 10.2,9.96,10.01

0.5 1365 87 11, 10.7,10.8

0.5 1420 87 7.4, 7.81, 7.5

0.5 1420 87 7.8, 7.91, 8

70

Appendix D: Automated Air-void Analysis Detailed Results

Table D.1: Air-void parameter Results

Admixture

Type

Wt % nano

carbon

substitution

Dosage( ml/

100 kg

cement)

Length of

traverse

(mm)

Length

through air

(mm)

# of air-

voids

intercepted

Air content

(vol.%)

Mean

air-void

intercept

(mm)

Air-void

frequency

(void/cm)

Specific surface

(mm-1)

Paste to

air ratio

Spacing factor

(mm)

Synthetic 0 196 3359.52 191.08 1455 5.69±0.42 0.131 4.33 30.5± 1.76 8.3 0.191± 0.008

0.5 196 3359.52 103.22 540 3.07±0.38 0.191 1.61 20.9± 1.95 15.8 0.370± 0.020

0.5 400 3359.52 109.07 903 3.25±0.35 0.121 2.69 33.1± 2.74 14.9 0.228± 0.013

0.5 555 3359.52 133.42 1224 3.97±0.36 0.109 3.64 36.7± 2.54 12.1 0.188± 0.009

0.5 588 3359.52 138.66 1369 4.13±0.35 0.101 4.08 39.5± 2.93 11.6 0.172± 0.008

0.5 784 3359.52 189.72 1494 5.65±0.44 0.127 4.45 31.5± 1.82 8.4 0.186± 0.007

0.5 882 3359.52 157.02 1179 4.67±0.41 0.133 3.51 30.0± 2.03 10.2 0.213± 0.010

Vinsol resin 0 520 3359.52 288.20 1508 8.58±0.51 0.191 4.49 20.9±1.94 5.3 0.228±0.009

0 780 3359.52 242.30 2032 7.21±0.46 0.119 6.05 33.5±1.74 6.4 0.155± 0.005

0.5 780 3359.52 145.06 617 4.32±0.44 0.235 1.84 17.0± 1.11 11.1 0.390± 0.020

0.5 1000 3359.52 170.42 1749 5.07±0.37 0.097 5.21 41.1± 2.68 9.4 0.150± 0.006

0.5 1250 3359.52 206.10 2128 6.14±0.43 0.097 6.33 41.3± 2.17 7.7 0.136± 0.005

0.5 1365 3359.52 275.77 2428 8.21±0.54 0.114 7.23 35.2± 1.51 5.6 0.138± 0.004

0.5 1420 3359.52 195.04 1926 5.81±0.40 0.101 5.73 39.5± 2.36 8.1 0.146± 0.005

71

Table D.2: Threshold Determination of Rapid Air 457 versus Flatbed Scanner

sample

IDs

MTO Air

content (%)

MTO

Spacing Factor

(mm)

MTO

Specific Surface

(mm-1)

Void

Frequency Threshold

Air

Content Threshold

Total

Length of Traverse

(mm)

Traverse

Length through

Air (mm)

Total

number of Air Voids

intercepte

d

Average

Chord Length

(mm)

Specific

Surface (mm-1)

Void

Frequency (intercepts

/mm)

Air

Content (vol. %)

Spacing

Factor (mm)

15-

19_0261A

,B

6.3 0.076 45.3 72 76 9120.0 420.4 3290 0.128 31.3 0.361 4.6 0.167

15-19_0263A

,B

2.2 0.571 11.9 72 76 9229.4 135.1 770 0.175 22.8 0.083 1.5 0.381

15-19_0264A

,B

3.0 0.400 14.8 72 76 9003.3 244.7 1217 0.201 19.9 0.135 2.7 0.333

15-19_0361A

,B

8.9 0.066 42.9 72 76 8747.9 678.1 6424 0.106 37.9 0.734 7.8 0.340

15-

19_0362A,B

4.9 0.218 21.3 72 76 8529.0 342.3 1463 0.234 17.1 0.171 4.0 0.325

15-

19_0363A,B

1.3 0.474 17.1 72 76 7996.4 119.7 618 0.194 20.6 0.077 1.5 0.416

15-

19_0364A

,B

5.2 0.159 28.9 72 76 8062.1 530.5 3146 0.1686 23.7 0.390 6.6 0.187

15-

19_0365A

,B

7.6 0.099 32.1 72 76 8018.3 678.9 6247 0.109 36.8 0.779 8.5 0.321

15-19_1061A

,B

5.3 0.138 31.9 72 76 7821.3 410.8 2596 0.158 25.3 0.332 5.3 0.195

15-19_1162A

,B

2.9 0.435 12.5 72 76 8069.4 247.8 976 0.254 15.8 0.121 3.1 0.398

72

a. b.

Figure D.1: Optimum Threshold Value Distribution for a) Air Content, and b) Void Frequency

a. b.

Figure D.2: Regression line and 95% confidence intervals for ASTM C457 and flatbed scanner

results for a) Air Content, and b) Void Frequency with the application of optimum threshold

values

carbon sequetration strategies in cement based material ... · nano platelet admixture interaction...

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