As material requirements for particular applications become more specific and strict, using a targeted approach to design polymeric materials becomes a necessity. Following a general design framework prevents researchers from using trial-and-error approaches or shoehorning materials into applications for which they are non-optimal. To obtain polymer products with desirable properties (both fundamental characteristics and for a specific application), one must always begin with an awareness of existing materials and methods. This background knowledge informs preliminary design of experiments, which in turn provides insight for additional experiments to synthesize (and characterize) optimally designed materials.

A general framework for the design of polymeric materials has been developed in this thesis, and the specific aspects are grounded in two independent case studies. These two distinct (yet related) case studies have been selected to demonstrate that the framework is not limited to a particular industry or application, nor to a specific type of polymeric material. In Case Study #1, water-soluble terpolymers (and related polymerization kinetics) are investigated for use in polymer flooding during enhanced oil recovery (EOR). In contrast, Case Study #2 examines a variety of polymeric materials that have the potential to be used for acetone gas sensing (for diabetic applications). Both case studies use the same general design framework in a sequential, iterative manner to move towards optimally designed materials for each target application.

Polymers are already used in EOR;​ the most common synthetic material used for polymer flooding is partially hydrolyzed polyacrylamide (HPAM). In many cases, polymers for EOR are exposed to high temperatures, high shear rates, and high concentrations of salt in the reservoir. The shortcomings of HPAM include poor thermal stability, poor shear stability, and poor brine compatibility. As a result, HPAM can degrade during EOR, thus lowering molecular weight averages and reducing oil recovery efficiency. Therefore, the target for Case Study #1 is to build on existing knowledge to improve acrylamide-based polymers for enhanced oil recovery.

Important characteristics of polymeric materials for EOR include good viscosity modification (achieved through water solubility, high molecular weight averages and the incorporation of carboxylate ions), reasonable chemical stability (achieved by incorporating high levels of amide groups into the polymer), and a good distribution of ions along the polymer backbone (that is, a targeted sequence length distribution). HPAM (a copolymer of acrylamide (AAm) and acrylic acid (AAc)) meets these requirements, but the thermal and shear stability concerns described above have not been considered. Therefore, a third comonomer, 2-acrylamido-2-methylpropane sulfonic acid (AMPS) can be added to the polymer formulation, as the bulky sulfonic acid groups are expected to improve thermal stability and protect the main chain from shear degradation. When a multi-component polymer like AMPS/AAm/AAc is being considered for any application, understanding and manipulating ternary reactivity ratios (which are related to both the cumulative terpolymer composition and the sequence length distribution) is essential.

Therefore, once the AMPS/AAm/AAc terpolymer is selected for enhanced oil recovery, relationships between (experimental) synthesis conditions and polymer properties can be researched, verified and exploited. First, a comprehensive study (involving both an examination of the literature and a series of designed screening experiments) is performed to establish the effect of synthesis conditions (like pH, ionic strength, monomer concentration and feed composition) on the terpolymerization kinetics and product terpolymer properties. Deliberate design of screening experiments (designed considering the ‘rule-of-thumb’ for ternary reactivity ratio estimation) makes it possible to establish that the key factors within the experimental range studied are ionic strength (which affects cumulative terpolymer composition and sequence length distribution), monomer concentration (which affects molecular weight averages) and feed composition (which, of course, impacts the cumulative composition of the terpolymer product).

Given the results of the screening experiments, two optimal terpolymers of AMPS/AAm/AAc are designed, synthesized, characterized and tested. The designed terpolymers have polymer properties that agree with model predictions, but (more importantly) show excellent EOR performance. In a series of sand-pack flooding experiments (simulating enhanced oil recovery in a reservoir), the designed terpolymers perform much better than reference materials. The newly synthesized terpolymers achieve an overall oil recovery of (on average) 78.0% for one optimal material and 88.7% for the second optimal material. In contrast, the commercially available reference material allows for an overall oil recovery of 59.8%. Therefore, the design framework has allowed us to converge upon optimal terpolymer formulations with excellent EOR application performance.

The same general framework is applied to inform the design, synthesis and characterization of polymeric sensing materials for acetone detection. Highly concentrated breath acetone measurements are correlated with high levels of blood glucose, so detecting acetone gas could be useful in a non-invasive breath sensor for diabetic applications. In this case, key design considerations (to inform potential backbone selection) include operational temperature (and the glass transition temperature of candidate polymeric materials), surface morphology, and the chemical behaviour of the target analyte. Solubility parameters, for example, can be used to provide insight about the compatibility of the target analyte (acetone) and potential sensing materials. For polymeric sensing materials, the most important characteristics are sensitivity and selectivity. Sensitivity studies provide information about how well the target analyte sorbs onto the polymeric material (that is, whether there is a strong affinity towards acetone), and selectivity measures how well the target analyte sorbs in the presence of other interferent gases.

After preliminary screening (based on a detailed literature review), three polymer backbones and three metal oxide dopants are selected as promising candidates for acetone sensing. Polyaniline, polypyrrole and poly(methyl methacrylate) are doped with varying quantities of SnO2, WO3 and ZnO nanoparticles. In a series of screening experiments, 30 materials are synthesized and evaluated in terms of acetone sorption (using a uniquely designed gas sensing set-up and a highly specialized gas chromatograph). The most promising materials are evaluated further, both in terms of surface morphology and in terms of selectivity (measurement of acetone sorption in the presence of acetaldehyde, ethanol and benzene). In general, pure polyaniline and pure polypyrrole show the most promise of the materials studied;​ poly(methyl methacrylate) does not sorb acetone at all, and metal oxide doping (using these dopants and up to 20 wt% doping) does not improve application performance.

In the customized experiments, adjustments are made to polymer synthesis steps in an attempt to improve the properties of the polymeric sensing materials (especially in terms of selectivity). One customization option that is investigated is the acid-doping of polyaniline (synthesis in an aqueous oxalic acid solution) to change the backbone charge, thereby taking advantage of the polarity of acetone. Another customization option involves the synthesis of copolymers of polyaniline and polypyrrole (both in water and in oxalic acid solution) by combining the two monomers in a single formulation. Product characterization shows some improvement over the original (screening) materials, but further improvement is still possible. Therefore, this target application can continue to benefit from sequential, iterative steps towards optimality.

Ultimately, both case studies overlap when the general design framework is considered. An awareness of existing materials and methods can inform statistically designed preliminary experiments, which eventually lead to optimally designed materials for specific (targeted) applications. The contents of this thesis (especially the two major case studies) and several related publications demonstrate that this framework is useful and relevant for design of polymeric materials. The effectiveness is visible throughout the research process, but it is especially evident in the application performance of the final (optimal) product, along with the flexibility of the design approach with respect to expanding into new areas, at the same time by minimizing time and effort.