Evaluating the temperature dependence of heat-transfer based detection: A case study with caffeine and Molecularly Imprinted Polymers as synthetic receptors

Molecularly Imprinted Polymers (MIPs) are synthesized for the selective detection of caffeine. The polymerization process, monomer and crosslinker monomer composition are varied to determine the optimal synthesis procedure via batch rebinding experiments evaluated with optical detection. The selectivity is tested by comparing the response of caffeine to compounds with similar chemical structures (theophylline and theobromine) and dopamine, another neurotransmitter. Subsequently, the MIP polymer particles are integrated into bulk modified MIP screen-printed electrodes (MIP-modified SPEs). The sensors are used to measure caffeine content in various samples employing the Heat-Transfer Method (HTM), a low-cost and simple thermal detection method that is based on differences in thermal resistance at the solid-liquid interface. At first, the noise is minimized by adjusting the settings of temperature feedback loop. Second, the response of the MIP-modified SPE is studied at various temperatures ranging from 37 to 50 and 85 degrees C. The binding to MIP-modified SPEs has never been studied at elevated temperatures since most biomolecules are not stable at those temperatures. Using caffeine as proof-of-concept, it is demonstrated that at 85 degrees C the detection limit is significantly enhanced due to higher signal to noise ratios and enhanced diffusion of the biomolecule. Thermal wave transport analysis (TWTA) is also optimized at 85 degrees C producing a limit of detection of similar to 1 nM. Next, MIP-modified SPEs are used to measure the caffeine concentration in complex samples including caffeinated beverages, spiked tap water and waste water samples. The use of MIP-modified SPEs combined with thermal detection provides sensors that can be used for fast and low-cost detection performed on-site, which holds great potential for the determination of contaminants in environmental samples. The platform is generic and by adapting the MIP layer, we can expand to this a range of relevant targets.