This paper investigates the potential of reducing greenhouse gas emissions in data centers by intelligently scheduling batch processing jobs. A carbon-aware scheduler, S.C.A.L.E (Scheduler for Carbon-Aware Load Execution), was developed and applied to a resource-intensive data processing pipeline at ING. The scheduler optimizes the use of green energy hours, times with higher renewable energy availability, and lower carbon emissions. The S.C.A.L.E comprises three modules for predicting task running times, forecasting renewable energy generation and electricity grid demand, and interacting with the processing pipeline. Our evaluation shows an expected reduction in greenhouse gas emissions of around 20% when using the carbon-aware scheduler. The scheduler’s effectiveness varies depending on the season and the expected arrival time of the batched input data. Despite its limitations, the scheduler demonstrates the feasibility and benefits of implementing a carbon-aware scheduler in resource-intensive processing pipeline.

Building hardware that fit within the philosophy of Ambient Intelligence often requires access to responsive materials. For this purpose responsive materials are defined as materials that change appearance or shape as a function of an external stimulus. That may be as much as the way a person experiences the look of a material in its interaction with light related to addressable properties such as absorption (colour, brightness, transmission) and scattering (velvet tones, metallic, transmission). But it can also be related to other properties to trigger a person's perception of its ambient, such as surface roughness, odour release, acoustic reflection, etc. The driving force for the change in the material's property can be an electrical voltage or current as a response to a stimulus from a sensor. In that case the sensor picks up a signal from the environment it is in. Examples are the presence of a person, change in conditions such as temperature, humidity, ambient light, the use of audio-visual equipment, etc. But the response of the materials can also be more autonomous where it changes properties as a result of the dynamically changing environmental conditions without the intervention of an additional sensor.When integrated in commodities as furniture and electronic equipment or even in the walls of a building or in the interior or exterior of vehicles, one can speak of so-called smart-skins or electronic skins which draw much attention in the world of military equipment and in programs such as Ambient Intelligence.

The reliability of coatings that are used in industrial applications critically depends on their mechanical properties. Nanoindentation and scratch testing are well-established techniques to measure some of these properties, namely the elastic modulus and hardness of coatings. In this paper, we investigate the possibility of also assessing the coating fracture toughness and the energy of adhesion between the coating and the substrate using indentation and scratch testing. Various existing and new methods are discussed, and they are illustrated by measurements on particle-filled sol-gel coatings on glass. All methods are based on the occurrence of cracking, and they are therefore only applicable to coating systems that act like brittle materials and exhibit cracking during indentation and scratching. The methods for determining the fracture toughness give comparable results, but the values still differ to within about 50%. The values of the adhesion energy obtained from different measurements are consistent, but it remains uncertain to which extent the obtained values are quantitatively correct. The results show that the methods used are promising, but more research is needed to obtain reliable quantitative results.

The scratch test has long been used to study the adhesion of coatings. In this test an indenter is drawn across the surface of a coating under an increasing (continuous or stepwise) load. The load (normal to the surface) at which detachment of the coating occurs is termed the critical load. Usually, the magnitude of the critical load is related to the adhesion between the substrate and the coating by some theoretical model. It is well known that apart from the adhesion the critical load depends on several other parameters including the friction coefficient. In this paper a review of theoretical models applicable to scratch adhesion testing is given. Experimental data is used to compare the ability of these theoretical models to describe the effect of friction between the indenter and the coating on the critical load. We applied the scratch test to a model system consisting of a (hybrid) sol-gel coating deposited on polypropylene. The friction coefficient between indenter and coating was varied by a short plasma modification of the surface of the coating, while all other relevant parameters (i.e. interfacial adhesion, layer thickness, E-modulus of the coating, etc.) remained constant. The critical load (normal to the surface) showed a pronounced decrease of more than an order of magnitude with increasing friction coefficient. Several models are discussed and compared to the experimental data. In addition, the effect of substrate pretreatment on coating adhesion was studied. The adhesion of the sol-gel coating induced by microwave oxygen plasma modification of polypropylene is considerably better than the adhesion obtained by wet-chemical modification in chromo-sulfuric acid at room temperature. The adhesion induced by immersion in chromosulfuric acid is shown to be independent of the immersion time between 1 and 10 min.