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INTRODUCTION

Colloidal systems near to the glass concentration are often taken as excellent models of the molecular glass transition temperature. Yet, one of the most important aspects of the dynamics of molecular glasses, i.e., that of structural recovery in the temperature histories catalogued by Kovacs [1], has yet to be elucidated in colloidal systems. In the present work, we take advantage of a thermo-sensitive PNIPAAM [2,3] colloidal suspension to study the aging behavior near to the glass concentration. We use multi-speckle Diffusive Wave Spectroscopy (DWS) [4] to follow the dynamics during aging. Because, unlike molecular glasses, the thermodynamic variable for colloidal systems is volume fraction and not temperature, we take advantage of the thermosensitive nature of the particles to use temperature to control the concentration. The three classical aging signatures observed in molecular glasses: Intrinsic isotherms, asymmetry of approach, and memory effect, are investigated with this colloidal suspension and the results are compared with those typical of molecular and polymeric glasses.

 

EXPERIMENTAL

The samples we used are aqueous suspensions of PNIPAAM gel particles, which exhibit a temperature-induced swell-shrink response [2, 3]. As temperature increases from 24^oC to 36^oC, the diameter of the particles decreases from 350nm to 150nm (Figure 1), which means, by controlling the temperature, the system can be adjusted to different concentrations and therefore different glassy states.

DWS was applied to study the dynamics of the PNIPAAM colloidal system. In the experiment, laser light is projected onto the sample and back scattered light is collected by a CCD camera. The intensity auto-correlation function is obtained by multiplying and averaging over pixels between two successive frames according to [3]: . A program written in Labview extracts relaxation time from the intensity auto correlation function. 

The parameter used to study the aging signature in molecular and polymer glassy systems is specific volume or density, which are controlled by temperature (or pressure) and a volume departure from equilibrium  is used to define the glassy state. However, in the colloidal system, a similar variable in, e.g., volume concentration is problematic to define even though the experiments require concentration jumps from one temperature to the next. In order to avoid this problem in the experiment, a new term, is used to describe aging behavior.     (RTDE = Relaxation Time Departure from Equilibrium).

 

 

RESULTS

1. Intrinsic Isotherms

Temperature was kept at 31.7^oC for 3000s to reach equilibrium state before cooling to 5 different experimental temperatures. The result of Tau vs. Tw is displayed on Fig.2a All the data except that at 31.1 ^oC are smoothed by using moving average function in Origin. Fig.2b shows the relaxation time as a function of aging time. Similar to glassy polymer, relaxation time at equilibrium is a strong function of temperature  but the time spend to reach equilibrium state is insensitive to the controlling temperature, which is in strong contrast to the response observed in molecular glass.

 

 

 

 

 

2.  Asymmetry of Approach

There are two aspects to the asymmetry of approach experiment, temperature down jump and temperature up jump. In the down jump, temperature was first kept at 31.6^oC for 4000s and then cooled down to a temperature of 31.4 ^oC and the departure from equilibrium monitored as a function of waiting time. In the up jump experiment, temperature was held at 31.2 ^oC for 8000s to equilibrate the sample before heating to 31.4 ^oC.  The colloidal asymmetry of approach result is compared to that of a molecular glass in Figure 3.  We see similar non-linear behavior for the two situations, i.e.,  the sum of up-jump and down jump curve does not equal to zero but reaches a minimum value. For molecular glass, this non-linearity is due to the self-retardation and self-acceleration because of the long chain configuration of polymer. However, the reason for non-linearity of colloid is still unknown and under continuing investigation.

 

3.  Memory effect

In Kovacs's experiments, the volume in any specific experiment was directly measured. However, for the colloid suspension, such a thermodynamic parameter cannot be readily measured and this results in the difficulty of determining the waiting time required to achieve the  partial recovery needed to evidence a memory effect in the colloid, should same exist. To solve this problem, several different waiting times were tried to obtain initial values of log(10RTDE) as close to 0 as possible (in the Kovacs experiments he worked to obtain values in the up jump portion of the experiment that started at d=0). Our results show that for the partial recovery temperature of 31.1^oC and a final temperature of 31.4^oC, the system requires 150s to get close to the relevant initial response at the final temperature. From Fig.4a(insert) , the memory effect peak can be observed clearly although the peak itself is relatively small when compared with the intrinsic isotherm down jump response (Fig.4a).  This is different from what Kovacs observed in the molecular glass forming systems polymer (Fig.4b)

CONCLUSIONS

Similar aging signatures are observed in colloidal suspensions to those observed in molecular glasses. However, there appear to be subtle differences between the two types of glass-former. The intrinsic isotherm shows a strong difference in equilibrium relaxation times at different temperatures, but a very weak dependence on the temperature for the time required to reach the equilibrium state; for the asymmetry of approach, similar non-linearity is observed for the colloidal glass but the reason to explain this phenomenon is still unclear as the colloidal system is ‘aging' at constant concentration; finally the memory effects are similar in character for colloid suspension but seem to be of a weaker magnitude. Work is continuing to understand the observed phenomena.

REFERENCE

1. A. J. Kovacs, Forschr. Hochpolym.-Forch., 3, 394 (1963).

2. M. Balauf and Y. Lu, Polymer 48, 1815 (2007).

3. M. Clements, S.R. Pullela, A.F. Mejia, J. Shen, T. Gong, and Z. Cheng,  J. Coll. Interface Sci., 317, 96 (2008)

4. V. Viasnoff, F. Lequeux, and D. J. Pine, Rev. Sci. Inst. 73, 2336 (2002).

5.  Y. Zheng and G.B. McKenna, Macromolecules, 36, 2387 (2003).