No abstract

The ongoing COVID-19 pandemic has increased the use of single-use medical fabrics such as surgical masks, respirators, and other personal protective equipment (PPE), which have faced worldwide supply chain shortages. Reusable PPE is desirable in light of such shortages; however, the use of reusable PPE is largely restricted by the difficulty of rapid sterilization. In this work, we demonstrate successful bacterial and viral inactivation through remote and rapid radio frequency (RF) heating of conductive textiles. The RF heating behavior of conductive polymer-coated fabrics was measured for several different fabrics and coating compositions. Next, to determine the robustness and repeatability of this heating response, we investigated the textile’s RF heating response after multiple detergent washes. Finally, we show a rapid reduction of bacteria and virus by RF heating our conductive fabric. 99.9% of methicillin-resistant Staphylococcus aureus (MRSA) was removed from our conductive fabrics after only 10 min of RF heating; human cytomegalovirus (HCMV) was completely sterilized after 5 min of RF heating. These results demonstrate that RF heating conductive polymer-coated fabrics offer new opportunities for applications of conductive textiles in the medical and/or electronic fields.

Molecularly imprinted polymers (MIPs) may be used to confer specific recognition properties to a variety of practical sensors and sorbents. However, the synthetic parameters (monomer species, template/monomer ratio, etc.) used to generate MIPs significantly impact their sensitivity and selectivity, generally requiring arduous empirical optimization to obtain materials with maximal target affinity. We present a MIP synthesis strategy that prioritizes the optimization of the pre-polymerization complex as a predictive model for the final polymer properties and demonstrate how greater target affinity may be obtained without iterative analysis of the polymer film. 2,4-Dichlorophenoxyacetic acid (2,4-D), a prevalent herbicide, was chosen for detection using electrogenerated molecularly imprinted polymers (eMIPs). eMIPs were rationally designed using molecular simulations to down-select an ideal functional monomer with a maximal affinity for 2,4-D. Following monomer selection, proton-based nuclear magnetic resonance ( 1 H NMR) titrations were used to verify the simulation results and optimize the monomer/2,4-D ratio by tracking the chemical shift associated with monomer/target binding. Following optimization, eMIPs were synthesized by the anodic electropolymerization of the selected monomer, o-phenylenediamine, onto gold substrates in the presence of 2,4-D, which was subsequently stripped away via solvent washing to reveal 2,4-D-specific binding sites. Surface sites were blocked upon 2,4-D association with the eMIP when placed in contaminated water, which was tracked electrochemically. The ability of molecular simulations and 1 H NMR titrations to predict optimal monomer/2,4-D ratios was evaluated by fitting the experimental data to a Langmuir−Freundlich isotherm, revealing a significant increase in target affinity (K a ) and binding site homogeneity (m) related to the chemical shifts exhibited by the prepolymerization complex for o-phenylenediamine (o-PD). The two techniques, when evaluated on o-PD, predicted ideal monomer/ template ratios with remarkable agreement. Thus, the synthetic strategy outlined herein represents a streamlined approach for the rapid prototyping and design of eMIP-based sensing elements essential for the realization of next-generation polymeric sensors and sorbents.

No abstract