Nominations Sought for AOAC Awards
AOAC International is seeking nominations for the Harvey W. Wiley Award and for recognition as a Fellow of AOAC International.
Nominations Sought for AOAC Awards
AOAC International is seeking nominations for the Harvey W. Wiley Award and for recognition as a Fellow of AOAC International. The AOAC Awards Program recognizes significant contributions to the analytical science community and to AOAC itself.
The Harvey W. Wiley Award is presented to a scientist (or group of scientists) who has made an outstanding contribution to analytical method development in an area of interest to AOAC International. The recipient is selected from nominations received from members of the analytical science community, with nominations accepted year round. All nominating materials for the 2016 Harvey W. Wiley Awards must be received no later than January 31, 2015.
The Fellow of AOAC International Award recognizes meritorious service to the Association. This award is given to members of AOAC whose volunteer efforts have significantly contributed to the success and prestige of the Association. All nominating materials for 2015 Fellows of AOAC must be received no later than February 15, 2015.
For eligibility and nomination guidelines, visit the AOAC web site or contact May Rose Jones, Program Manager, at +1 301-924-7077 ext. 114, or email at mjones@aoac.org.
Scientists Unveil Better Mixing Rule for Absorption Spectroscopy of Aerosols and Colloids
June 16th 2025Researchers have introduced a simple yet powerful new rule based on Rayleigh scattering theory that accurately links the absorption behavior of composite media, like aerosols or colloids, to the properties of their nanoparticle constituents.
Short Tutorial: Complex-Valued Chemometrics for Composition Analysis
June 16th 2025In this tutorial, Thomas G. Mayerhöfer and Jürgen Popp introduce complex-valued chemometrics as a more physically grounded alternative to traditional intensity-based spectroscopy measurement methods. By incorporating both the real and imaginary parts of the complex refractive index of a sample, this approach preserves phase information and improves linearity with sample analyte concentration. The result is more robust and interpretable multivariate models, especially in systems affected by nonlinear effects or strong solvent and analyte interactions.
