From Smart Methods to Smartphones: The Dunning-Kruger Effect hits Analytical Science
Analytical science sheds light on chemical challenges. Analytical technology feeds operative needs to that. Unfortunately, too often non-analytical disciplines understand "analytics" as mere button-push data harvesting. Analytical science is however not analytical technology. Analytical science is about enabling insights, across dimensions of underlying information.
Correlative spectroscopies, as well as data fusion methods , are obvious examples. Less obviously, analytical science highlights orthogonal information dimensions . For instance, feature imaging vs. sensitivity or lapse framing vs. selectivity, and so forth. Bulk quantitation is thus the new quasi. True quantitation make emerge informant dimensions, e.g. space, time, components, etc.
Hencewith, the revival of interest on chemometrics gears up virtually unlimited power. New advanced mathematical procedures, e.g. compressive sensing, relax the need for complex experimental requirements, e.g. permitting fast operando XAFS with tabletop X-ray lasers. Similarly, cohorts of time-of-flight hyperspectral data teach a solver to provide 3D chemical tomographs for batteries and/or photovoltaic thin films characterization with unprecedented detail. On the other hand, analytical science contributes also to the shrinking of instrumentation footprint, as enabled by increasingly efficient engineering, as the hardware-to-software (HW2SW) hype gets momentum. Synchrotrons become available for installation in your lab, NMR on a tabletop, XUV Raman in a shoebox . While high-end facilities are still important "as airplanes" are, lab "Tesla cars" make their way to the market. Examples are given.
The progress of methods and devices is however so extreme that advanced diagnostics becomes possible with the smartphone in your pocket. This gives unexperienced users the confidence to be much smarter than their data. As analytical science significantly relies on creativity, so much technology self-confidence may make "small data", rather than "big data", the next gold standard in analytical science.
 Borgschulte, A., et al., Inelastic neutron scattering evidence for anomalous H–H distances in metal hydrides. Proceedings of the National Academy of Sciences, 2020. 117(8): p. 4021-4026.
 Bleiner, D., et al., Spatially resolved quantitative profiling of compositionally graded perovskite layers using laser ablation-inductively coupled plasma mass spectrometry. Journal of Analytical Atomic Spectrometry, 2003. 18(9).
 Bleiner, D., Tabletop Beams for Short Wavelength Spectrochemistry. Spectrochimica Acta Part B: Atomic Spectroscopy, 2020.