Data processing: measuring – calibrating – or testing – Measurement system in a specific environment – Chemical analysis
Reexamination Certificate
1999-10-12
2002-09-10
Hoff, Marc S. (Department: 2857)
Data processing: measuring, calibrating, or testing
Measurement system in a specific environment
Chemical analysis
C324S457000
Reexamination Certificate
active
06449563
ABSTRACT:
FIELD OF THE INVENTION
The invention relates to the determination of the particle size distribution and zeta potential of particles in a colloidal system.
BACKGROUND OF THE INVENTION
This invention deals with a particular kind of dispersed system (or colloid), which can be described as a collection of small particles immersed in a liquid. These particles can be either solid (suspensions) or liquid (emulsions). Such dispersed systems play an important role in paints, lattices, food products, cements, abrasives, minerals, ceramics, blood, and enumerable other applications.
These systems have a common feature. Because of the small particle size, the total surface area of the particles is large relative to their total volume. Therefore surface related phenomena determine their behavior in many processes. This invention has particular application to dispersed systems where these surface effects are dominant, corresponding to a range of particle size up to about 10 microns. The importance of these surface effects disappears for larger particles.
In particular, this invention deals with concentrated dispersed systems, which are different from dilute systems because of the importance of particle-particle interactions. The boundary between dilute and concentrated systems is somewhat subjective and may vary from 1% vol to 10% vol depending on the measuring technique. We will use the boundary of 2%-5% vol suggested by Hunter in his recent review of electroacoustics. (Hunter, R. J. “Review. Recent developments in the electroacoustic characterization of colloidal suspensions and emulsions”, Colloids and Surfaces, 141, 37-65, 1998)
The characterization of such concentrated suspensions and emulsions is important not only for the manufacture, but also the development of new systems with improved properties. There are two basic notions for characterizing these dispersed systems: “particle size distribution” and “zeta potential”. Several methods are known for determining these characteristics. Most methods are based on light, for example: microelectrophoresis; light scattering; light diffraction; etc. There is a new alternative method based on ultrasound that is rapidly becoming important. This ultrasound method has a big advantage over traditional light-based techniques because it is able to characterize a concentrated system without dilution. Light-based methods usually require extreme dilution in order to make the sample sufficiently transparent for measurement. This invention deals with improvements of this ultrasound characterization technique.
There are two methods for ultrasound characterization of disperse systems: Acoustics and Electroacoustics. This invention deals only with Electroacoustics. An electroacoustic method applies an acoustic input and measures an electrical response, or conversely applies an electrical input and measures an acoustic response.
This electroacoustic method involves two steps. The first step is to perform an experiment on the disperse system to obtain a set of measured values for certain macroscopic properties such as temperature, pH, Colloid Vibration Current, etc. The second step is an analysis of the measured data to compute the desired microscopic properties such as particle size or &zgr; (zeta) potential. Such an analysis requires three tools: a model dispersion, a prediction theory, and an analysis engine.
A “model dispersion” is an attempt to describe the real dispersion in terms of a set of model parameters including, of course, the desired microscopic characteristics. The model, in effect, makes a set of assumptions about the real world in order to simplify the complexity of the dispersion and thereby also simplify the task of developing a suitable prediction theory. For example, most particle size measuring instruments make the assumption that the particles are spherical and therefore a complete geometrical description of the particle is given by a single parameter, its diameter. Obviously such a model would not adequately describe a dispersion of carpet fibers that have a high aspect ratio and any theory based on this over-simplified model might well give incorrect results. The model dispersion may also attempt to limit the complexity of the particle size distribution by assuming that it can be described by certain conventional distribution functions, such as for example a lognormal distribution.
A “prediction theory” consists of a set of equations that describes some of the measured macroscopic properties in terms of these microscopic properties of the model dispersion. For example, a prediction theory for Electroacoustics would attempt to describe a macroscopic property such as the colloid vibration current in terms of such microscopic properties as the particle size distribution and zeta potential.
An “analysis engine” is essentially a set of algorithms, implemented in a computer program, which calculates the desired microscopic properties from the measured macroscopic data using the knowledge contained in the prediction theory. The analysis can be thought of as the opposite or inverse of prediction. Prediction describes some of the measured macroscopic properties in terms of the model dispersion. Analysis, given only the values for some of the model parameters, attempts to calculate the remaining properties by an analysis of the measured data. There are many well-documented approaches to this analysis task.
There are two different approaches to electroacoustic measurements. The first approach employs an electric field to cause the particles to move relative to the liquid. This particle motion generates an ultrasound signal that can be measured. This is the so-called Electrokinetic Sonic Amplitude (ESA) approach. It is described by Oja (U.S. Pat. No. 4,497,208), O'Brien (U.S. Pat. No. 5,059,909), and Cannon (U.S. Pat. No. 5,245,290).
The second approach is the reverse of the first: an ultrasound wave makes the particles move and a resultant electric signal is measured. The electrical signal can be expressed as either a Colloid Vibration Potential (CVP) or a Colloid Vibration Current (CVI), depending on whether one measures the open circuit voltage or the short circuit current between two suitable electrodes. The CVI mode is preferable because it eliminates the need to measure the complex conductivity, which would otherwise be required to calculate the desired &zgr; potential. Marlow (U.S. Pat. No. 4,907,453) and Cannon (U.S. Pat. No. 5,245,290) describe this CVI approach.
In principle, the Electroacoustic signal contains information about both particle size and zeta potential. O'Brien suggests using such electroacoustic measurements at multiple frequencies for characterizing both parameters, the so-called “O'Brien method (Column 4). Cannon describes an implementation of this process into a particular device.
There are two main aspects of O'Brien's claims (Column 4, lines 15-22),
“(1) A method for determining particle size and charge from measurement of particle velocity in an alternating electric field”
“(2) A method of obtaining that particle velocity from measurements of the interaction of sound waves and electric fields in the suspension.”
From this it becomes clear that the notion of the “particle velocity” or “particle dynamic electrophoretic mobility” (O'Brien, Column 4, lines 30-65) is an essential part of the invention. O'Brien's method [Column 10, line 15, Equation 7] relies heavily on the notion of a “dynamic electrophoretic mobility” &mgr; and proposes a very simply relationship between &mgr; and the measured electric current produced by the sound wave &agr; given by:
α
=
ϕ
Δ
ρ
ρ
μ
(
1
)
where &phgr; is the volume fraction of the particles, &rgr; is a solvent density, and &Dgr;&rgr; is the difference between the density of the particles and the density of the solvent.
Equation (1) follows from O'Brien's reciprocal relationship suggested in O'Brien, R. W. “Electro-acoustic Effects in a dilute Suspensio
Dukhin Andrei
Goetz Philip J.
Dispersion Technology, INC
Raymond Edward
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