Hybrid organic/inorganic polymers have been prepared incorporating fluoroalkyl-substituted bisphenol groups linked using oligosiloxane spacers. These hydrogen-bond acidic materials have glass-to-rubber transition temperatures below room temperature and are excellent sorbents for basic vapors. The physical properties such as viscosity and refractive index can be tuned by varying the length of the oligosiloxane spacers and the molecular weight. In addition, the materials are easily cross-linked to yield solid elastomers. The potential use of these materials for chemical sensing has been demonstrated by applying them to surface acoustic wave devices as thin films and detecting the hydrogen-bond basic vapor dimethyl methylphosphonate with high sensitivity. It has also been demonstrated that one of these materials with suitable viscosity and refractive index can be used to clad silica optical fibers; the cladding was applied to freshly drawn fiber using a fiber drawing tower. These fibers have potential as evanescent wave optical fiber sensors.

Four hydrogen bond acidic polymers are examined as sorbent layers on acoustic wave devices for the detection of basic vapors. A polysiloxane polymer with pendant hexafluoro-2-propanol groups and polymers with hexafluorobisphenol groups linked by oligosiloxane spacers yield sensors that respond more rapidly and with greater sensitivity than fluoropolyol, a material used in previous SAW sensor studies. Sensors coated with the new materials all reach 90% of full response within 6 s of the first indication of a response. Unsupervised learning techniques applied to pattern-normalized sensor array data were used to examine the spread of vapor data in feature space when the array does or does not contain hydrogen bond acidic polymers. The radial distance in degrees between pattern-normalized data points was utilized to obtain quantifiable distances that could be compared as the number and chemical diversity of the polymers in the array were varied. The hydrogen bond acidic polymers significantly increase the distances between basic vapors and nonpolar vapors when included in the array.

A series of novel hyperbranched hydrogen-bond acidic polymers for surface acoustic wave (SAW) sensor applications were prepared by functionalizing hyperbranched polycarbosiloxanes or polycarbosilanes with phenol or hexafluoro-2-propanol groups. Starting polymer, sensor polymer, and reagent structures were confirmed by IR, 1 H, 13 C, and 29 Si NMR, SEC, or GCMS as appropriate. The hyperbranched sensor polymers were coated onto 500 MHz SAW platforms and their responses to the nerve agent simulant dimethyl methylphosphonate (DMMP) were studied. The hyperbranched sensor polymers with phenol groups gave very high initial responses to DMMP which dropped to 30% of the initial levels over a period of 6 months, and the hyperbranched sensor polymers with hexafluoro-2-propanol groups gave lower initial responses that did not change with time. Hence, the long-term performances of hyperbranched phenolic sensor polymers and hyperbranched hexafluoro-2-propanol sensor polymers were found to be comparable.

Apparent partition coefficients, K, for the sorption of toluene by four different polymer thin films on thickness shear mode (TSM) and surface acoustic wave (SAW) devices are compared. The polymers examined were poly(isobutylene) (PIB), poly(epichlorohydrin) (PECH), poly(butadiene) (PBD), and poly(dimethylsiloxane) (PDMS). Independent data on partition coefficients for toluene in these polymers were compiled for comparison, and TSM sensor measurements were made using both oscillator and impedance analysis methods. K values from SAW sensor measurements were about twice those calculated from TSM sensor measurements when the polymers were PIB and PECH, and they were also at least twice the values of the independent partition coefficient data, which is interpreted as indicating that the SAW sensor responds to polymer modulus changes as well as to mass changes. K values from SAW and TSM measurements were in agreement with each other and with independent data when the polymer was PBD. Similarly, K values from the PDMS-coated SAW sensor were not much larger than values from independent measurements. These results indicate that modulus effects were not contributing to the SAW sensor responses in the cases of PBD and PDMS. However, K values from the PDMS-coated TSM device were larger than the values from the SAW device or independent measurements, and the impedance analyzer results indicated that this sensor using our sample of PDMS at the applied thickness did not behave as a simple mass sensor. Differences in behavior among the test polymers on SAW devices are interpreted in terms of their differing viscoelastic properties.

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In previous work, it was shown that, in principle, vapor descriptors could be derived from the responses of an array of polymer-coated acoustic wave devices. This new chemometric classification approach was based on polymer/vapor interactions following the well-established linear solvation energy relationships (LSERs) and the surface acoustic wave (SAW) transducers being mass sensitive. Mathematical derivations were included and were supported by simulations. In this work, an experimental data set of polymer-coated SAW vapor sensors is investigated. The data set includes 20 diverse polymers tested against 18 diverse organic vapors. It is shown that interfacial adsorption can influence the response behavior of sensors with nonpolar polymers in response to hydrogen-bonding vapors; however, in general, most sensor responses are related to vapor interactions with the polymers. It is also shown that polymer-coated SAW sensor responses can be empirically modeled with LSERs, deriving an LSER for each individual sensor based on its responses to the 18 vapors. Inverse least-squares methods are used to develop models that correlate and predict vapor descriptors from sensor array responses. Successful correlations can be developed by multiple linear regression (MLR), principal components regression (PCR), and partial least-squares (PLS) regression. MLR yields the best fits to the training data, however cross-validation shows that prediction of vapor descriptors for vapors not in the training set is significantly more successful using PCR or PLS. In addition, the optimal dimension of the PCR and PLS models supports the dimensionality of the LSER formulation and SAW response models.

Summary: Microcontact printing was used to deposit stable, nanostructured, amphiphilic and crosslinkable patterns of poly(amidoamine organosilicon) (PAMAMOS)‐dimethoxymethylsilyl (DMOMS) dendrimer multilayers onto silicon wafers, glass, and polyelectrolyte multilayers. The effects of dendrimer ink concentration, contact time, and inking method, on the thickness, uniformity, and stability of the resulting patterns were studied using optical microscopy, fluorescence microscopy, atomic force microscopy (AFM), and contact‐angle analysis. Microarrayed dendrimer film thickness was found to be controllable by conditions used during spin self‐assembly.

SummarySorbent and functionalized polymers play a key role in a diverse set of fields, including chemical sensors, separation membranes, solid-phase extraction techniques, and chromatography. Sorbent polymers are critical to a number of sensor array or "electronic nose" systems. The responses of the sensors in the array give rise to patterns that can be used to distinguish one compound from another, provided that a sufficiently diverse set of sensing materials is present in the array. Figure S1 illustrates the concept of several sensors, each with a different sensor coating, giving rise to variable responses to an analyte that appear as a pattern in bar-graph format. Using hydrosilylation as the bond-forming reaction, we have developed a versatile and efficient approach to developing sorbent polymers with diverse interactive properties for sensor applications. Both the chemical and physical properties of these polymers are predictable and tunable by design.