Polyurethane is one of the most flexible classes of polymers available on the market. Polyurethanes are found in numerous consumer products, including car upholstery, golf grips and tennis racquets.
The physical properties of polyurethane are controlled by a variety of factors during the manufacturing process, including the molecular nature of the polyol starting material. Determining the hydroxyl value of the polyol reactants is a crucial step to ensure the polyurethane products exhibit the desired physical and chemical properties. The number of reactive hydroxyl groups (-OH) on the polyol directly impacts the quantity of urethane linkages, which greatly influences the physical properties of the final polyurethane product.
Traditionally, the number of hydroxyl groups on a polyol was determined by reacting the polyol with acetic acid and then titrating with potassium hydroxide (KOH). The milligrams of potassium hydroxide required to neutralize one gram of the solution is called the hydroxyl value, as discussed in ASTM D4274-11.2, Standard Test Methods for Testing Polyurethane Raw Materials: Determination of Hydroxyl Numbers of Polyols.
This wet chemistry method is complicated, time consuming, and requires several reagents. More recently, Fourier transform near-infrared (FT-NIR) spectroscopy has been used to determine the hydroxyl value of various materials, per ASTM D6342-12.3, Standard Practice for Polyurethane Raw Materials: Determining Hydroxyl Number of Polyols by Near Infrared (NIR) Spectroscopy.
With modern FT-NIR instrumentation, small amounts of sample can be analyzed in less than one minute. The application note, Determining the Hydroxyl Value for Polyols Using FT-NIR, describes a method used to analyze a series of polypropylene glycol samples with a variety of hydroxyl values using a FT-NIR spectrometer.
A quantitative calibration for hydroxyl value was created using a set of six polypropylene glycol samples. Spectra were acquired from the FT-NIR spectrometer and opened in quantitative analysis software for calibration model development.
The most basic quantitative analysis model is known as Simple Beer’s Law (SBL), which is useful for many single component calibration curves where peak shapes are well defined and only characteristic of the component of interest. When the SBL calibration model was applied to the hydroxyl value standards, a less than ideal calibration curve was generated
The Partial Least Squares (PLS) mathematical model is one of the most popular statistical methods and can help optimize the calibration data. A PLS model successfully calibrates the data set even when spectral features overlap, multiple components of interest are present, and the relationship between component concentration and absorbance is non-uniform. PLS also allows statistical correlation of spectral features to other non-spectroscopic reference methods, such as wet chemical titrations or chromatography.
Click here to see the calibration curves for both models, plus more detailed discussion of the experimental conditions and results.