by S Mantellato, Q Mehmeti, L Ceni, M Palacios, and R.J Flatt
EXPERIMENTAL PROCEDURE (3 PAGES) Materials
A commercial Portland cement CEM I 52.5N according to the European standard EN 197-1:2000 was used. The specific surface area measured by nitrogen adsorption (BET model) was 1.17 m2/g following the procedure described elsewhere.11 Its Blained specific
surface was 4200 cm2/g. Its mineralogical composition was determined by Rietveld anal-
ysis of the X-ray diffraction (XRD) patterns and expressed in values normalized to 100% of crystalline phases (see Table 1).
Three pure non-commercial PCE polymers, provided by SIKA Technology AG (Zürich, Switzeraland), were used in the present study. Before use, they were ultrafiltrated to remove the copolymerization residues. Their backbone is based on polymethacrylic acid (PMA) and their side chains on polyethylene oxide (PEO) with different lengths, 1000 and 5000 Da. The real carboxylate to ester ratio (C/E) was calculated by UPLC (Waters). The molecular weight of comb polymers was determined by Gel Permeation Chromatography (GPC) using a Agilent 1260 Infinity equipment with PSS Suprema columns (0.8 × 30 cm, particle size 10 μm). Na2HPO4 0.067 M was used as eluent and PEO/PEG were used as
calibration standards.
Table 1. Mineralogical composition (%w/w) of Portland cement determined by Rietveld analysis of the XRD patterns.
C3S C2S C3A C4AF Quartz Calcite Gypsum Hemihydrate
Methods
Cement paste preparation— Two mixing procedures were used for mixing the cement
paste keeping the water-to-cement ratio of 0.30 constant. Small batches of cement pastes were prepared mixing 200 grams of cement and 60 g of ultrapure water containing PCE admixture with an IKA stirrer at 800 rpm for 5 minutes. After mixing, both spread flow (see below) and filtration of pore solutions were conducted.
A big batch of about 2.5 Kg of cement paste was prepared in a Hobart N50 mixer to study the flow loss using the same original paste. Right after mixing, the cement paste was poured in small plastic beakers and covered with parafilm. Then, these small batches were remixed for 30 seconds at a speed of 200 rpm with the IKA stirrer and left to rest for one minute before carrying out spread flow measurements (see below). The first flow test was carried out after 10 minutes, considered t0.
In a first series of experiments, the superplasticizer dosages were tested between 0 and 8 mg superplasticizer (SP) dry per g cement. With this initial set of data, two dosages for each polymer were selected for further tests (to limit the number of samples of which the evolution in time is measured). These were selected from spread flow tests giving diam- eters of 15 cm and 20 cm. As these can be considered to be respectively associated to low and high surface coverage of the particles by the polymers, we will refer to them as such.
These were chosen so as to provide a low and high surface coverage of identical magni- tude and are given in Table 2.
Cement paste spread flow tests— After the mixing described previously, the paste was
filled in a cylinder of 50 mm of diameter and 50 mm height. The cylinder was lifted and the diameter of the resulting cake was measured as a flow value. The yield stress was calculated from the following equation that interpolates between the analytical asymptotes determined by Roussel and Coussot12,13:
τ ρ π π 0 2 2 5 3 225 128 1 225 128 3 = + − gV R VR ( ( * ) Equation (1)
Table 2: Molecular characteristics of the superplasticizers used.
Name C/E ratio Mn (g/mol) Mw (g/mol) Polydispersity index (PDI = Mw/ Mn)
2.5PMA1000 2.7 22600 39500 1.75 4.0PMA1000 4.5 16400 25800 1.58 2.5PMA5000 2.3 70700 121800 1.72
Table 2. Selected dosages for each superplasticizer to reach the selected common low and high surface coverage
Investigated dosages 2.5 PMA 1000 [mg polymer/g cement]
4.0 PMA 1000 [mg polymer/g cement]
2.5 PMA 5000 [mg polymer/g cement]
Low surface coverage 1.5 1.5 2.5
High surface coverage 4.0 2.0 4.0
where ρ and V are the density and volume of the paste, respectively, g the gravitational acceleration and R the radius of the spread. The data are reported as normalized yield stress with respect to the initial point.
Characterization of cement pore solutions—Cement pore solutions were obtained by
filtration of cement pastes through a membrane filter Sartorius 0.45 μm and immediately acidified to prevent the precipitation of hydrates with HCl 0.1 M and 2% (w/w) HNO3 solu-
tions for TOC and ICP measurements, respectively. In a further series of samples, filters of 0.2 and 0.1 μm were used.
The total organic carbon content in pore solutions was determined by SHIMADZU TOC-V CSH total organic carbon (TOC) analyser. The amount of adsorbed polymer on cement was measured by depletion method, considering the difference between the amount of initially added and the amount in the liquid phase.
Inductively Coupled Plasma Optical Emission Spectroscopy (ICP-OES) Thermo iCAP 6000 was used for quantifying the ionic composition of cement pore solutions. The elements of interest were Na, Ca, K, S, Fe, Mg, Si and Al. Pore solutions were diluted 200 times to quantify Na (589.5), Ca (315.8 and 318.1), K (766.4 and 769.8), and S (182.6). The same cement pore solutions were also diluted 10 times to improve the accuracy in the quantification of the elements whose concentrations lie in the range of ppb (μg/L), such as Fe (259.9), Mg (279.5), Si (251.6), and Al (396.1). The numbers in brackets represent the spectral lines selected for each element expressed in nm.
RESULTS
Initial impact of superplasticizer (for a several dosages)
Adsorption isotherms—The adsorption isotherms for the three PCE polymers are shown
in Figure 1, where the content of polymer adsorbed is plotted versus the initial PCE dosage,
Figure 1. Adsorption isotherms of PCEs on cement pastes. Diamonds, squares and circles are for 2.5PMA1000, 2.5PMA5000 and 4PMA1000.
expressed as mg of active polymer per gram of cement. At low dosages, the added poly- mers are almost totally adsorbed on the cement, which is evidenced by the data lining up on the 1:1 continuous line in Figure 1. The departure from this line has the following order 4.0 PMA 1000 < 2.5 PMA 1000 < 2.5 PMA 5000, which follows the order of decreasing charge density of these polymers. The adsorption plateau are not clearly determined in these experiments, but appear to tend all towards similar values, which is consistent with side chains maintaining a coiled conformation when polymers are adsorbed.9
Aqueous phase composition—The elemental analysis of the aqueous phases of these
pastes shows constant Na, K, Ca, and S concentrations, regardless the structure and the dosage of the polymer (Table 3). The amounts of Al, Si, Fe and Mg increase by increasing
Figure 2. Concentration of Al (diamond), Si (square), Fe (circle) and Mg (triangle) as a function of dosage for the three different superplasticizers used. a) 2.5 PMA 1000, b) 2.5 PMA 5000, c) 4.0 PMA 1000.
Table 3. Average concentration of elements for the different superplasticizer dosages used
Na [mM] k [mM] Ca [mM] S [mM] 2.5PMA1000 55 ± 2 490 ± 17 19 ± 3 202 ± 9 4.0PMA1000 70 ± 4 481 ± 24 22 ± 5 209 ± 11 2.5PMA5000 69 ± 2 464 ± 16 19 ± 1 198 ± 11
the polymer dosage in the cement paste. The polymer addition causes the largest changes for aluminium and magnesium (Figure 2). Aluminum concentrations reached in particular very high values, which is explicitly addressed in the discussion section.
Impact of superplasticizer over time (for two selected dosages)
We restricted the study of flow loss to two dosages per superplasticizer. As explained in the methods section, these were chosen such that they achieved identical common values in the spread test. Values indicated are given in Table 2 and are referred to as high and low surface coverages.
Yield stress— Spread flow data were converted to yield stress, using equation (1). Each
data series was further normalized by its initial yield stress. This facilitates the comparison relative changes in yield stress between the data sets at low and high surface coverage. Results in Figure 3, show that as expected that for each polymer the highest dosage leads to the highest flow retention. However, the sequence of flow retention among polymers
Figure 3: Normalized yield stress versus time. Partial (top) and full (bottom) surface coverage. Diamonds, squares and circles are for 2.5PMA1000, 2.5PMA5000 and 4PMA1000.
is inverted between low and high surface coverage. It can also be observed that, at high surface coverage, all polymers show a delayed fluidification, the timing and magnitude of which is strongly polymer dependent.
Aqueous phase evolution—The concentrations of Na, K, Ca, and S remain constant over
time, regardless the structure and dosage of the polymer and are therefore not reported in the present paper. The most useful information from the solution analysis in the context of this paper concerns the aluminium, which shows very significant variations depending on the type and dosage of the polymer (Figure 5). A particularly striking observation is that, at low surface coverage, the polymer 2.5PMA5000 is associated with concentrations of aluminium and magnesium that are one order of magnitude higher than with either of the other polymers having short side chains.
Figure 4. Concentrations of Al in the aqueous phases over time. Partial (top) and full (bottom) surface coverage. Diamonds, squares and circles are for 2.5PMA1000, 2.5PMA5000 and 4.0PMA1000.
At high surface coverage, the amount of elements in the aqueous phases shows quite different trends over the time depending on the polymer and its dosage. The most remark- able results concern the concentrations of aluminium, shown in Figure 5 (Concentrations of other elements will be reported upon separately). Here again it can be observed that the content of the elements in cement suspension with the polymer 2.5 PMA 1000 and 5000 is higher than with 4.0 PMA 1000. In the pore solution with the polymer 2.5 PMA 1000 the concentration of elements was constant until 200 minutes. At this point the amount of elements starts to decrease. The high aluminium concentrations reached are discussed in the next section.
DISCUSSION
Impact of the PCE on aqueous phase composition
The high amount of aluminium that are reached in Figure 5 are unusual and suggest that these aqueous phases may be supersaturated with respect to ettringite. To gain quantitative insight into this question we have computed the activity coefficients of all species in these solutions using GEMS14,15 with the CemData07 database.16 Results in Figure 6 reveal that
solutions are supersaturated not only with respect to ettringite, but also with respect to other aluminate phases such as monocarboaluminate and monosulfoaluminate.
This supersaturation may be due either to complexation of Ca and/or Al ions by the poly- mers or to a stabilization of small ettringite particles. In the later case, the polymer would not only have to poisen their growth but also hinder their agglomeration. As a consequence nano-particles of ettringite might be passing through the filter, something already reported for PCEs by Comparet.17 To test this hypothesis, we filtered some solutions through filters
of 0.2 and 0.1 microns. In most cases this did not decrease the aluminium concentration in
Figure 5. Saturation index of the aqueous phase in suspen- sions prepared with superplasticizer 2.5 PMA1000 at different dosages after mixing.
solution, contrary to what Comparet observed. We are in the process of using nano-particle analysis on these solutions to determine whether particles smaller than 100 nm can be identified in these solutions.
An alternative explanation to the high Al concentration could be a strong complexing capacity of the SPs for Al. At this stage we have only conducted a qualitative examina- tion of this question. For this we first determined the concentration of carboxylate groups from the polymer in solution (not adsorbed). Then in absence of detailed knowledge on the stoichiometry of Al-polymers complexes, we examine the relative number of charges coming from the polymer in solution versus those from the aluminium. It turns out that
Figure 6. Normalized yield stress from Figure 3 replotted versus polymer remaining in solution (top) and carbox- ylate groups in solution (bottom). Empty and filled symbols respectively represent low and high dosages. Diamonds, squares and circles are for 2.5PMA1000, 2.5PMA5000 and 4.0PMA1000.
the number carboxylates in solutions is much larger than the number of charges from the aluminium. This suggests that the supersaturation with respect to ettringite may be due to the presence of complexes between aluminium and the polymers. This is further supported by the fact that all aluminium containing phases are supersaturated. In contrast, gypsum and portlandite are not supersaturated, which suggests that the calcium complexation is not responsible for the calculated supersaturations.
Flow loss
Figure 3 shows that the normalized yield stress is relatively steady over a period of time and then increases rapidly. The first order explanation for this is that as hydrates are formed the total system surface increases and excess polymers in solutions adsorb. Once no more enough polymers are available to maintain a high specific surface, the fluidity would begin to be lost.18 There are two ways to examine the relevance of this view. The first and most
pragmatic approach consists in re-plotting the data of Figure 3 not versus time, but versus the amount of polymer remaining in solution. As shown in Figure 7 (top) this does not link to lead to a collapse of data on a master curve. However, when data are plotted versus the amount of carboxylates remaining in solution (Figure 7, bottom) most data series show a similar concentration range in which the normalized yield stress abruptly increases (0.7-1.2 μeq/g). Only the high dosage of 2.5PMA1000 leads to a substantially different behaviour. Otherwise the rather similar common behaviour of the other polymers suggests that its complexing ability in solution slows down the growth of hydrates and thereby delays the flow loss.
Towards additional insight on flow loss
The results presented in this paper concerning flow loss can be summarized by the these two main observations:
1. A high excess of ettringite is measured in the aqueous phase. This may be due to aluminum complexation by the polymer or a poisoning of ettringite growth complemented by a stabilization of nano-sized ettringite particles.
2. Apart for one case, the flow loss appears to take off when the concentration of carbox- ylate ions in solution drops below a critical value.
These observations suggest that flow loss is controlled by the development of hydrate surfaces and that polymers delay this by hindering the growth of ettringite and/or by poisoning its nucleation (because of aluminum complexation). Determining which of these mechanisms is at stake require more extensive characterization, which we are undertaking but are beyond the scope of this paper.
CONCLUSIONS
Flow loss is a complex phenomena that has only received limited attention in the litera- ture, particularly with regard to the role of the molecular structure of the superplasticizer. The data presented in this paper suggest a critical role of the polymer in either complexing aluminum or preventing ettringite growth. This defines specific characterization objectives to start shedding light on how to relate molecular structure of PCEs to flow loss.
AUTHOR BIOS
Sara Mantellato is Chemist and has great experience on chemical admixtures. She is
currently doing her PhD Thesis on the effect of comb compolymer superplasticizers on the specific surface are evolution in order to understand the flow loss of cementitious systems.
Qendrim Mehmeti and Lindrit Ceni are civil engineering students from ETH Zürich,
who carried out their Bachelor Thesis on the topic of “Flow loss in superplasticized cementitious binders” under the supervision of Sara Mantellato.
Dr. Marta Palacios, Ph.D. in Chemistry, has been working in the area of building mate-
rials for more than 10 years. Her research interests include the interaction of chemical admixtures with Portland and alkaline cements and their effect on the rheological proper- ties and hydration process.
Prof. Dr. Robert Flatt is Professor of Building Materials at ETHZ. Before that he was
Principal Scientist at Sika Technology AG and postdoctoral researcher at the Princ- eton University. He owns a master in Chemical Engineering and a PhD from EPFL. He has received various awards among which the RILEM Robert L’Hermite Medal, the Ross C. Purdy and the Brunauer awards from the American Ceramic Society, as well an Outstanding Research Contribution in the Broad Area of Chemical Admixtures presented at the 10th International Conference on Superplasticizers and Other Chemical Admixtures.
ACKNOWLEDGEMENTS
The authors would like to thank Dr. B. Lothenbach for her advices in the use of GEMS software. We also thank Dr. F. Caruso for his support during the analysis of the aqueous solution by ICP and to G. Gelardi, D. Marchon and D. Altermatt for their help in the characterization of the PCEs. Finally we thank Dr. Lukas Frunz (Sika Technology) for providing us the polymers.
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The ability to control the setting of cement can be of use in various applications such as slip forming, oil well cements, or in normal applications due to variable conditions and time constraints. Typically cement setting is controlled via set retarders or set accelerators, but rarely are the two used in combination. The combination of the two, however, can lead to