This study investigates pattern formation during evaporation of water-based nanofluid sessile droplets placed on a smooth silicon surface at various temperatures. An infrared thermography technique was employed to observe the temperature distribution along the air-liquid interface of evaporating droplets. In addition, an optical interferometry technique is used to quantify and characterize the deposited patterns. Depending on the substrate temperature, three distinctive deposition patterns are observed: a nearly uniform coverage pattern, a "dual-ring" pattern, and multiple rings corresponding to "stick-slip" pattern. At all substrate temperatures, the internal flow within the drop builds a ringlike cluster of the solute on the top region of drying droplets, which is found essential for the formation of the secondary ring deposition onto the substrate for the deposits with the "dual-ring" pattern. The size of the secondary ring is found to be dependent on the substrate temperature. For the deposits with the rather uniform coverage pattern, the ringlike cluster of the solute does not deposit as a distinct secondary ring; instead, it is deformed by the contact line depinning. In the case of the "stick-slip" pattern, the internal flow behavior is complex and found to be vigorous with rapid circulating flow which appears near the edge of the drop.

This is the pre-peer reviewed version of the following article: Deltombe R., Kubiak K.J., Bigerelle M, How to select the most relevant 3D roughness parameters of a surface (2011) Summary:In order to conduct a comprehensive roughness analysis, around sixty 3D roughness parameters are created to describe most of the surface morphology with regard to specific functions, properties or applications. In this paper, a multiscale surface topography decomposition method is proposed with application to stainless steel (AISI 304), which is processed by rolling at different fabrication stages and by electrical discharge tool machining. Fifty-six 3Droughness parameters defined in ISO, EUR, and ASME standards are calculated for the measured surfaces. Then, expert software "MesRug" is employed to perform statistical analysis on acquired data in order to find the most relevant parameters characterizing the effect of both processes (rolling and machining), and to determine the most appropriate scale of analysis. For the rolling process: The parameter Vmc (the Core Material Volume-defined as volume of material comprising the texture between heights corresponding to the material ratio values of p = 10% and q = 80%) computed at the scale of 3 mm is the most relevant parameter to characterize the cold rolling process. For the EDM Process, the best roughness parameter is SPD that represents the number of peaks per unit area after segmentation of a surface into motifs computed at the scale of 8 µm.

No abstract