The goal of this research is to measure and regulate the shape and size of particles created by nucleation and growth processes in crystallizers.
In the final year of the grant, we implemented feedback control on a semi-batch crystallization in which an impurity free feed flows through the crystallizer and we regulate the flowrate of a habit modifier stream in order to maintain a desired shape.
At the 2000 IFPRI Annual meeting, we showed our first results in which without any prior knowledge of model parameters, a simple proportional-integral control algorithm is able to maintain a desired crystal shape and in doing so, determines the critical concentration of habit modifier required to maintain this shape. The prototypical system and process we selected is semi-batch crystallization of sodium chlorate (NaClOs). Sodium dithionate (NazS20s) is a habit modifier that influences the relative growth rates of 100 and i ii faces of the crystal. In the presence of at least 50 ppm sodium dithionate the growth of the iii faces is blocked by the impurity and the crystal shape changes from cubic to tetrahedral. Without impurity present, the 100 faces grow slower than the iii faces and the crystal shape changes from tetrahedral to cubic. The shape change is easy to detect with video images alone, though there are limitations with extracting useful numerical information from images for use as a signal for feedback control.
This prototypical process displays the following industrial characteristics.
1. Particle shape is affected by unmeasured disturbance variables.
2. Online sensing is available in the form of video images. The images are replete with bad data. Some particles are fused or broken; it is difficult to obtain representative samples; particle boundaries overlap each other; there are significant levels of process noise; and it is difficult to sample enough images to remove the effects of this noise through averaging. The standard image analysis software provides simple measures such as particle boxed area and aspect ratio; as we show later, these simple measures are inadequate signals for feedback control.
3. We can manipulate a process variable that also influences particle shape. Through this feedback policy, we maintain the desired shape in the face of the unmeasured disturbances. The video images are processed in real time to produce the feedback signal that is used for control.
Accomplishments.
1. Developed and implemented a repeatable prototype process for illustrating online crystal shape control.
2. Added a higher level functionality to the standard image analysis software and tai- lored it to detect transitions between cubic and tetrahedral crystals in a slurry.
3. Implemented feedback control and maintained a desired shape in a semi-batch crystallization process
As far as we know, these results are the first demonstration of real time control of crystal shape. Although serious challenges remain, and the prototype process is somewhat idealistic, we hope these results inspire practitioners to think seriously about application of these principles in suitable industrial processes.