A two-way analytical investigation of ancient gold coins: Elemental and colorimetric description of precious materials.

The investigation of ancient artifacts is often constrained by their scarce availability and high protection and custody protocols. Among these, coinage represents an especially valuable kind-of-samples given their uniqueness and the subjacent information that is hidden behind their composition. Their analysis are often carried out using non-destructive techniques in order to avoid any alteration of the samples.

A smartphone image-based method for the colorimetric characterization of historical pigments in mural paintings.

In this article, the detailed description of a smartphone-based analytical method to turn a smartphone into a colorimeter is described and applied to mural painting replicas. The method consists of a camera characterization process, to estimate CIELAB values from RGB camera responses, correcting for potential experimental interferences, like the effect of the lighting/capture geometry or software for color modification and enhancement. Next, the estimated CIELAB descriptors were used to build a chemometric Support Vector Classifier to objectively distinguish among the colors of the different pigments.

3D-printed portable device for illicit drug identification based on smartphone-imaging and artificial neural networks.

In this manuscript, a 3D-printed analytical device has been successfully developed to classify illicit drugs using smartphone-based colorimetry. Representative compounds of different families, including cocaine, 3,4-methylenedioxy-methamphetamine (MDMA), amphetamine and cathinone derivatives, pyrrolidine cathinones, and 3,4-methylenedioxy cathinones, have been analyzed and classified after appropriate reaction with Marquis, gallic acid, sulfuric acid, Simon and Scott reagents. A picture of the colored products was acquired using a smartphone, and the corrected RGB values were used as input data in the chemometric treatment.

Automated HO monitoring during photo-Fenton processes using an Arduino self-assembled automatic system.

A cheap and easy to use Arduino self-assembled automatic system was employed to continuously monitor the hydrogen peroxide consumption during the photo-Fenton degradation of caffeine, selected as model target compound. The automatic system made it possible to measure the HO concentration in the reaction cell via a colorimetric reaction and to take samples for HPLC analysis minimising the operator manual intervention and exposure to UV radiation. The obtained results were compared in terms of LOD and LOQ with HO measurements manually performed using UV-Vis spectrophotometry, evidencing better analytical performance when using the automatic system; LOD and LOQ were respectively 0.