The packing in molecular crystals is determined by intermolecular interactions. An understanding of these interactions would enable the design of systems exhibiting effective conductivity and superconductivity. By careful analysis of the shortest intermolecular interactions in the crystal combined with accurate ab‐initio calculatins it has been shown that CH…X and S…S are the two interactions most likely to influence the structures of these materials.
Scheme 2 range of analyte concentration. Thus, better tuning of hydrogen bond interactions will result in structure-breaking effects at lower analyte concentrations. VCH Rdagsgevell~chuft mhH 0-69469 Weinlirim, 1995 0935-9648/95/1212-1026 $ T 00+ 25,O Adv M a w 1995, 7, No 12
Mueller matrix polarimetry distinguishes the different origins of the reversible and irreversible chiroptical effects emerging in stirred solutions of J-aggregate nanoparticles: the reversible effect is due to an anisotropic ordering in the solution and the irreversible one is due to a bias from the racemic composition of intrinsically chiral structures.
Sweat secreted by the human eccrine sweat glands can provide valuable biomarker information during exercise in hot and humid conditions. Real-time noninvasive biomarker recordings are therefore useful for evaluating the physiological conditions of an athlete such as their hydration status during endurance exercise. In this work, we describe a platform that in-cludes different sweat biomonitoring prototypes of cost-effective, smart wearable devices for continuous biomonitoring of sweat during exercise. One prototype is based on conformable and disposable soft sensing patches with an integrated multisensor array requiring the integration of different sensors and printed sensors with their corresponding functionalization protocols on the same substrate. The second is based on silicon based sensors and paper microfluidics. Both platforms integrate a multi-sensor array for measuring sodium, potassium, and pH in sweat. We show preliminary results obtained from the multi-sensor prototypes placed on two athletes during exercise. We also show that the machine learning algorithms can predict the percentage of body weight loss during exercise from biomarkers such as heart rate and sweat sodium concentration collected over multiple subjects.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.