The Power of Heterogeneity: Parameter Relationships from Distributions
| Autor: | Nathan H. Williamson, Magnus Nydén, Siobhan J. Bradley, Thomas Nann, Melissa R. Dewi, Magnus Röding |
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| Přispěvatelé: | Röding, Magnus, Bradley, Siobhan J, Williamson, Nathan H, Dewi, Melissa Rosdiana, Nann, Thomas, Nyden, Magnus |
| Jazyk: | angličtina |
| Rok vydání: | 2016 |
| Předmět: |
Photon
Distribution Curves Polymers lcsh:Medicine field gradient 02 engineering and technology 01 natural sciences nmr Naturvetenskap Nanotechnology Data Mining Electron Microscopy Statistical physics lcsh:Science Mathematics Mass Diffusivity Microscopy Multidisciplinary Physics Magnetism 021001 nanoscience & nanotechnology Condensed Matter Physics Power (physics) Chemistry nuclear-magnetic-resonance Macromolecules Physical Sciences Probability distribution Engineering and Technology Natural Sciences 0210 nano-technology Elementary Particles Algorithms Research Article Statistical Distributions spectroscopy Diffusion (acoustics) Materials by Structure Nuclear Magnetic Resonance Materials Science 010402 general chemistry Research and Analysis Methods diffusion measurements Quantum Dots Computer Simulation Particle Physics Photons graphene quantum dots Chemical Physics Models Statistical catalysis lcsh:R Probability Theory Probability Distribution Polymer Chemistry labels 0104 chemical sciences lcsh:Q Transmission Electron Microscopy |
| Zdroj: | PLoS ONE PLoS ONE, Vol 11, Iss 5, p e0155718 (2016) |
| ISSN: | 1932-6203 |
| Popis: | Complex scientific data is becoming the norm, many disciplines are growing immensely data-rich, and higher-dimensional measurements are performed to resolve complex relationships between parameters. Inherently multi-dimensional measurements can directly provide information on both the distributions of individual parameters and the relationships between them, such as in nuclear magnetic resonance and optical spectroscopy. However, when data originates from different measurements and comes in different forms, resolving parameter relationships is a matter of data analysis rather than experiment. We present a method for resolving relationships between parameters that are distributed individually and also correlated. In two case studies, we model the relationships between diameter and luminescence properties of quantum dots and the relationship between molecular weight and diffusion coefficient for polymers. Although it is expected that resolving complicated correlated relationships require inherently multi-dimensional measurements, our method constitutes a useful contribution to the modelling of quantitative relationships between correlated parameters and measurements. We emphasise the general applicability of the method in fields where heterogeneity and complex distributions of parameters are obstacles to scientific insight. Refereed/Peer-reviewed |
| Databáze: | OpenAIRE |
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