ABSTRACT
The transmission of the SARS-CoV-2 coronavirus has been shown through droplets generated by infected people when coughing, sneezing, or talking in close contact. These droplets either reach the next person directly or land on nearby surfaces. The objective of this study is to develop a novel, durable, and effective disinfecting antimicrobial (antiviral, antibacterial, and antifungal) styrene-ethylene/butylene-styrene (SEBS) based thermoplastic elastomers (TPE). TPE incorporated with six different formulations was investigated for mechanical and antiviral performance. The formulations consist of a combination of zinc pyrithione (ZnPT), sodium pentaborate pentahydrate (NaB), disodium octaborate tetrahydrate (DOT), and chlorhexidine (CHX). ZnPT and DOT incorporated TPE showed a reduction of microbes such as bacteria by up to 99.99%, deactivated Adenovirus, Poliovirus, Norovirus, and reduced a strain of the coronavirus family by 99.95% in 60 min on TPE samples. Control samples had higher tensile strengths among all formulations and tensile strength decreased by around 14%, 21% and 27% for ZnPT and DOT combinations compared to control samples. The elongation at break decreased by around 7%, 9% and 12% with ZnPT and DOT combinations, where it reached minimum values of 720%, 702% and 684%, respectively. The 100% Modulus and 300% Modulus slightly increased with ZnPT and NaB combination (reaching values from 1.6 to 1.9 MPa and 2.6-2.9 MPa respectively) in comparison with control samples. The MFI also decreased with antimicrobial and antiviral additives (decreasing values from 64.8 to 43.3 g/10 min). ZnPT and NaB combination showed the lowest MFI (43.3 g/10 min) and reduced the MFI of control sample by around 33%. TPE samples containing ZnPT and DOT combination showed biocidal activity against the microorganisms tested and can be used to develop antimicrobial products for multiple touchpoints within a vehicle and micro-mobility.
ABSTRACT
BACKGROUND: Fourier transform infrared spectroscopy (FTIR) equipped with attenuated total reflectance accessory was used to determine honey adulteration. Adulterated honey samples were prepared by adding corn syrup, beet sugar and water as adulterants to the pure honey samples in various amounts. The spectra of adulterated and pure honey samples (n = 209) were recorded between 4000 and 600 cm-1 wavenumber range. RESULTS: Genetic-algorithm-based inverse least squares (GILS) and partial least squares (PLS) methods were used to determine honey content and amount of adulterants. Results indicated that the multivariate calibration generated with GILS could produce successful models with standard error of cross-validation in the range 0.97-2.52%, and standard error of prediction between 0.90 and 2.19% (% w/w) for all the components contained in the adulterated samples. Similar results were obtained with PLS, generating slightly larger standard error of cross-validation and standard error of prediction values. CONCLUSION: The fact that the models were generated with several honey samples coming from various different botanical and geographical origins, quite successful results were obtained for the detection of adulterated honey samples with a simple Fourier transform infrared spectroscopy technique. Having a genetic algorithm for variable selection helped to build somewhat better models with GILS compared with PLS. © 2018 Society of Chemical Industry.
