Browsing by Author "Srinivasan, C."

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Open Access
Credible intervals for nanoparticle characteristics
(Elsevier, 2012-01) Charnigo, R.; Francoeur, M.; Kenkel, P.; Mengüç, Mustafa Pınar; Hall, B.; Srinivasan, C.; Mechanical Engineering; MENGÜÇ, Mustafa Pınar
Solving the inverse problem of nanoparticle characterization has the potential to advance science and benefit society. While considerable progress has been made within a framework based on the scattering of surface plasmon-polaritons, an aspect not heretofore considered is the quantification of uncertainty in the estimation of a nanoparticle characteristic. Therefore, the present article offers a technique by which an investigator may augment an estimate of a nanoparticle characteristic with a companion “credible interval”. Analogous to the familiar confidence interval but arising from within the Bayesian statistical paradigm, a credible interval allows the investigator to make a statement such as “the nanoparticle diameter lies between 36 and 48 nm with 95% probability” instead of merely “the nanoparticle diameter is estimated to be 42 nm”. Our technique may even be applied outside of the surface plasmon-polariton scattering framework, as long as the investigator specifies his/her prior beliefs about the nanoparticle characteristic and indicates which potential outcomes are likely or unlikely in whatever experiment he/she designs to estimate the nanoparticle characteristic. Two numerical studies illustrate the implementation and performance of our technique in constructing ranges of likely values for nanoparticle diameters and agglomeration levels, respectively.
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Estimating quantitative features of nanoparticles using multiple derivatives of scattering profiles
(Elsevier, 2011-05) Charnigo, R.; Francoeur, M.; Kenkel, P.; Mengüç, Mustafa Pınar; Hall, B.; Srinivasan, C.; Mechanical Engineering; MENGÜÇ, Mustafa Pınar
Characterization of nanoparticles on surfaces is a challenging in verse problem whose solution has many practical applications. This article proposes a method, suitable for in situ characterization systems, for estimating quantitative features of nanoparticles on surfaces from scattering profiles and their derivatives. Our method enjoys a number of advantages over competing approaches to this inverse problem. One such advantage is that only a partial solution is required for the companion direct problem. For example, estimating the average diameter of nanoparticles to be 53 nm is possible even when a researcher’s existing scattering data pertain to nanoparticles whose average diameters are in multiples of 5 nm. Two numerical studies illustrate the implementation and performance of our method for inferring nanoparticle diameters and agglomeration levels respectively.