Surface diffusivity of cleaved NaCl crystals as a function of humidity: Impedance spectroscopy measurements and implications for crack healing in rock salt

Rock salt offers an attractive host rock for geological storage applications, because of its naturally low permeability and the ability of excavation-induced cracks to heal by fluid-assisted diffusive mass transfer. However, while diffusive transport rates in bulk NaCl solution are rapid and well characterized, such data are not directly applicable to storage conditions where crack walls are coated with thin adsorbed water films. To reliably predict healing times in geological storage applications, data on mass transport rates in adsorbed films are needed. We determined the surface diffusivity in such films for conditions with absolute humidities (AH) ranging from 1 to 18 g/m 3 (relative humidities (RH) of 4%-78%) by measuring the surface impedance of single NaCl crystals. We use the impedance results to calculate the effective surface diffusivity S = DδC using the Nernst-Einstein equation. The S values obtained lie in the range 1 × 10-27 m3 s-1 at very dry conditions to 1 × 10-19 m 3 s-1 for the deliquescence point at 296 K, which is in reasonable agreement with existing values for grain boundary diffusion under wet conditions. Estimates for the diffusivity D made assuming a film thickness δ of 50-90 nm and no major effects of thickness on the solubility C lie in the range of 1 × 10-14 to 8 × 10-12 m 2 s-1 for the highest humidities studied (14-18 g/m 3 AH, 60%-78% RH). For geological storage systems in rock salt, we predict S values between 1 × 10-22 - 8 × 10-18 m3 s-1. These imply crack healing rates 6 to 7 orders of magnitude lower than expected for brine-filled cracks

Personality and taxonomy preferences, and the influence of category choice on the user experience for music streaming services

Music streaming services increasingly incorporate different ways for users to browse for music. Next to the commonly used “genre” taxonomy, nowadays additional taxonomies, such as mood and activities, are often used. As additional taxonomies have shown to be able to distract the user in their search, we looked at how to predict taxonomy preferences in order to counteract this. Additionally, we looked at how the number of categories presented within a taxonomy influences the user experience. We conducted an online user study where participants interacted with an application called “Tune-A-Find”. We measured taxonomy choice (i.e., mood, activity, or genre), individual differences (e.g., personality traits and music expertise factors), and different user experience factors (i.e., choice difficulty and satisfaction, perceived system usefulness and quality) when presenting either 6- or 24-categories within the picked taxonomy. Among 297 participants, we found that personality traits are related to music taxonomy preferences. Furthermore, our findings show that the number of categories within a taxonomy influences the user experience in different ways and is moderated by music expertise. Our findings can support personalized user interfaces in music streaming services. By knowing the user’s personality and expertise, the user interface can adapt to the user’s preferred way of music browsing and thereby mitigate the problems that music listeners are facing while finding their way through the abundance of music choices online nowadays