Influence of humidity on accuracy of QCM - IR780-based GUMBOS sensor arrays.

Herein, hydrophobic coating materials are reported for QCM detection of VOCs under dry and humid conditions. In this study, IR780-based GUMBOS ([IR780][OTf] and [IR780][NTf2]) were synthesized using an ion exchange reaction and the anions trifluoromethanesulfonimide ([OTf]) and bisperfluoromethanesulfonimide ([NTf2]). The parent iodide salts and GUMBOS ([IR780][I]), [IR780][OTf], and [IR780][NTf2]) were characterized using several analytical techniques. These salts were then employed as sensor coatings on quartz crystal resonators using an electrospray coating method. These sensors were exposed to four flow ratios of five common VOCs in the absence and presence of 10 vol% water. Fundamental frequency responses were recorded and further employed as input variables to develop highly accurate multi-sensor arrays (MSAs). Accuracy was better than 78.3% without water, and better than 91.7% in the presence of water. When multi-harmonic responses were evaluated as input variables to assess discrimination ability for each sensor, highly accurate virtual sensor arrays (VSAs) were developed using each GUMBOS coating. In the case of [IR780][NTf2], a slight improvement in discrimination was achieved in the presence of water (95%) versus the absence of water. Moreover, this study highlights development of readily synthesized hydrophobic coatings of IR780-based GUMBOS for potential detection and discrimination of VOCs in aqueous systems.

Tailoring Amphiphilic Copolymers for Improved Aqueous Foam Stability.

Amphiphilic copolymers of various-molecular-weight (MW) poly(ethylene glycol) (PEG) were synthesized via reversible addition-fragmentation chain transfer (RAFT) polymerization. The first PEG series, poly(ethylene glycol)monomethacrylate (PEGMA, average Mn 200 and 400 MW), contained an -OH terminal group, and the second series, poly(ethylene glycol) monomethyl ether monomethacrylate (PEGMMA, average Mn 200, 400, and 1000 MW), possessed an -OCH3 terminal group. A total of five PEG-functionalized copolymers contained the same hydrophobic monomer, butyl acrylate (BA), and were successfully reproduced via a one-pot synthesis. The resulting PEG-functionalized copolymers provide a systematic trend of properties including surface tension, critical micelle concentration (CMC), cloud point (CP), and foam lifetime based on the average MW of the PEG monomer and final polymer properties. In general, the PEGMA series produced more stable foams with PEGMA200 demonstrating the least change in foam height with time over a 10 min period. The important exception is that at elevated temperatures, the PEGMMA1000 copolymer had longer foam lifetimes. The self-assembling copolymers were characterized by gel permeation chromatography (GPC), 1H nuclear magnetic resonance (NMR), attenuated total reflection Fourier transform infrared (FTIR-ATR), CMC, surface tension, dynamic light scattering (DLS), as a foam using a dynamic foam analyzer (DFA), and foam lifetime at ambient and elevated temperatures. The copolymers described highlight the importance of the PEG monomer MW and terminal end group for surface interaction and final polymer properties for foam stabilization.

Non-contact detection of fentanyl by a field-portable ion mobility spectrometer.

Rapid on-site detection of fentanyl is paramount for the safety of law enforcement and other first responders. Due to the opioid epidemic, death by overdose is at an all-time high with fentanyl adulteration as the main assailant. Providing a user-friendly method for the presumptive detection of fentanyl will increase safety for first responders. Ion mobility spectrometry (IMS) provides a quick, affordable, and accurate method for detecting fentanyl. Currently, most methods for detecting fentanyl require manipulation or handling of the highly potent substance. A recent comparative analysis study on the headspace of fentanyl determined N-phenylpropanamide (NPPA) a target analyte for fentanyl enabling vapor detection. Here, we demonstrate the development of a handheld IMS method for vapor detection of the target analyte for fentanyl. An alarm was programmed into the handheld IMS device for the detection of NPPA. The system was able to accurately detect NPPA in samples of reference-grade fentanyl and diluted reference-grade fentanyl, as well as 3.67 mg of fentanyl from samples confiscated from the US border. Common adulterants and over-the-counter drugs were tested and resulted in a false alarm rate of 0 for substances sampled. The limit of detection was determined to be as low as 5 ng of NPPA. Overall, the development of this user-friendly, non-contact method has considerable promise for near real-time non-contact detection of fentanyl increasing safety of first responders.

Comparative analysis of vapor profiles of fentalogs and illicit fentanyl.

Availability of fentanyl is at a record high with 3138 kg of fentanyl and related substances being seized in 2019. Fentanyl's high toxicity makes a lethal dose for most mere milligrams. With such a high potency and a consistent rise of abuse, the chances of injury or death of frontline workers increase with every interaction. Development of a non-contact detection method for fentanyl would decrease the chances of a workplace mishap. To aid in the development of a non-contact detection method, target analytes in the vapor profile of fentanyl need to be identified. In order to achieve this goal, semi-quantitative headspace analysis of fentanyl analogs and confiscated fentanyl exhibits was accomplished using solid-phase microextraction and gas chromatography coupled with mass spectrometry (SPME-GC-MS). The vapor signatures of these samples were compared to a previously reported reference-grade fentanyl vapor signature to determine the target analyte(s) for fentanyl detection in the vapor phase. A total of 20 fentalogs and confiscated exhibits, with masses ranging from 2 to 19 mg, were sampled. N-Phenylpropanamide(NPPA) or N-phenethyl-4-piperidone(NPP) was identified as target analytes in 75% of these samples. This is a crucial component for the development of a non-contact detection method for fentanyl.

Protein Discrimination Using a Fluorescence-Based Sensor Array of Thiacarbocyanine-GUMBOS.

Sensitive and selective detection of proteins from complex samples has gained substantial interest within the scientific community. Early and precise detection of key proteins plays an important role in potential clinical diagnosis, treatment of different diseases, and proteomic research. In the study reported here, six different compounds belonging to a group of uniform materials based on organic salts (GUMBOS) have been synthesized using three thiacarbocyanine (TC) dyes and employed as fluorescent sensors. Fluorescence properties of micro- and nanoaggregates of these TC-based GUMBOS formed in phosphate buffer solutions are studied in the absence and presence of seven proteins. Fluorescence response patterns of these TC-based GUMBOS were analyzed by linear discriminant analysis (LDA). The constructed LDA model allowed discrimination of these seven proteins at various concentrations with 100% accuracy. The sensing and discrimination abilities of these TC-based GUMBOS were further evaluated in mixtures of two major proteins, i.e., human serum albumin and hemoglobin. Fluorescence response patterns of these mixtures were analyzed by LDA. This model allowed discrimination of various mixtures with 100% accuracy. Moreover, spiked urine samples were prepared and the responses of these sensors were collected and analyzed by LDA. Remarkably, discrimination of these seven proteins was also achieved with 100% accuracy.

Quartz Crystal Microbalance Based Sensor Arrays for Detection and Discrimination of VOCs Using Phosphonium Ionic Liquid Composites.

Herein, we examine two sensing schemes for detection and discrimination of chlorinated volatile organic compounds (VOCs). In this work, phosphonium ionic liquids (ILs) were synthesized and vapor sensing properties examined and compared to phosphonium IL-polymer composites. Pure IL sensors were used to develop a QCM-based multisensory array (MSA), while IL-polymer composites were used to develop an MSA and virtual sensor arrays (VSAs). It was found that by employing the composite MSA, five chlorinated VOCs were accurately discriminated at 95.56%, which was an increase in accuracy as compared to pure ILs MSA (84.45%). Data acquired with two out of three VSAs allowed discrimination of chlorinated VOCs with 100% accuracy. These studies have provided greater insight into the benefits of incorporating polymers in coating materials for enhanced discrimination accuracies of QCM-based sensor arrays. To the best of our knowledge, this is the first report of a QCM-based VSA for discrimination of closely related chlorinated VOCs.

Class specific discrimination of volatile organic compounds using a quartz crystal microbalance based multisensor array.

The use of quartz crystal microbalance (QCM) sensor arrays for analyses of volatile organic compounds (VOC) has attracted significant interest in recent years. In this regard, a group of uniformed materials based on organic salts (GUMBOS) has proven to be promising recognition elements in QCM based sensor arrays due to diverse properties afforded by this class of tunable materials. Herein, we examine the application of four novel phthalocyanine based GUMBOS as recognition elements for VOC sensing using a QCM based multisensor array (MSA). These synthesized GUMBOS are composed of copper (II) phthalocyaninetetrasulfonate (CuPcS4) anions coupled with ammonium or phosphonium cations respectively (tetrabutylammonium (TBA), tetrabutylphosphonium (P4444), 3-(dodecyldimethyl-ammonio)propanesulfonate (DDMA), and tributyl-n-octylphosphonium (P4448)). These materials were characterized using ESI-MS and FTIR, while thermal properties were investigated using TGA. Vapor sensing properties of these GUMBOS towards a set of common VOCs at three sample flow rate ratios were examined. Upon exposure to VOCs, each sensor generated analyte specific response patterns that were recorded and analyzed using principal component and discriminant analyses. Use of this MSA allowed discrimination of analytes into different functional group classes (alcohols, chlorohydrocarbons, aromatic hydrocarbons, and hydrocarbons) with 98.6% accuracy. Evaluation of these results provides further insight into the use of phthalocyanine GUMBOS as recognition elements for QCM-based MSAs for VOC discrimination.