Applications Of Novel Photo-Curing Oligomer Resins: Generation Two
by Michael L. Gould et al., Ashland Specialty Chemical

Application: Michael addition polyacrylate oligomers can meet almost any required performance parameter in coatings for flexible and rigid plastic substrates, wood, metal, and paper.

A new family of acrylic resins that can self-cure with exposure to UV light requiring little or no added photoinitiator became available in 2002. Since then the science behind reducing the basic concept to commercial reality has advanced several times over. Today resins are possible with nearly unlimited architecture and properties. Self-initiating Michael polyacrylate resins are possible for use on almost any substrate and for nearly any application.

Across a variety of substrates including both low- and high-energy surfaces, novel self-initiating Michael addition polyacrylate oligomers perform at levels comparable to and often exceeding published controls. In almost every case, substantially less photoinitiator is necessary to achieve acceptable cure speeds and cured film performance. In many cases, no photoinitiator is necessary. This remarkable feature underscores both the novelty and utility of this new resin chemistry.

The architectural control inherent in the Michael addition synthetic method allows for tailoring of resins to meet almost any required performance parameter. Commercial “target space” for products based on this new resin technology includes applications such as food and medical packaging where traditional photoinitiators have not had use.

As seen in some examples in this paper, the great design flexibility with Michael addition oligomer resins also may allow for creation of simplified formulations consisting of essentially a single resin compmonent. Performance data for several plastic and wood substrates and for glass are omitted in an effort to keep this summary article brief. Performance in each case nevertheless met or exceeded the control formulations in performance with equivalent or better cure using less or no photoinitiator in every case.

Using Process Control Valves As Rheometers To Predict And Control Polyethylene Molecular Weight And Molecular Weight Distribution
by William G. Todd et al., Lyondell Chemical Company

APPLICATION: Pressure drops across process control valves and die plates can measure viscosity at different shear rates allowing prediction of MW and MWD to control a process.

In polyethylene production, having fast reliable feedback on molecular weight (MW) and molecular weight distribution (MWD) is critical for producing high quality resins. Historically, this feedback comes from a quality control laboratory, but feedback times are at least 30 minutes if not longer. One-third of a railcar can be produced in a large commercial plant in 30 minutes. One alternative is to install an on-line melt indexer or rheometer for these measurements. The disadvantages of these online instruments are that they are expensive and can require frequent maintenance.

Typically a different grade of HDPE is necessary to meet the requirements of various applications. This means frequent transitions between grades in a commercial plant. Twenty or more transitions are typically possible in one month. A typical transition involves changing multiple reactor synthesis conditions such as hydrogen, ethylene, and co-monomer concentrations and reactor temperatures to achieve the desired new MW and MWD. On-line physical property predictive models are useful to help control MW and MWD, but hourly quality control samples are still necessary to validate the model's output. This is especially true during product transitions where 30-minute samples are necessary.

In a HDPE process, pressure drops can estimate liquid viscosities. By using multiple points, one can obtain viscosities at different shear rates that have use to predict MI and MFR. Although predicted values are not absolute, they are good indicators for determining when a product transition is complete. The reduction in laboratory sampling schedule looks promising. The models have proven to be very useful when running plant tests to develop new products.

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