Magnetisation of 2.6T in Gadolinium Thin Films

There is renewed interest in rare-earth elements and gadolinium in particular for a range of studies in coupling physics and applications. However, it is still apparent that synthesis impacts understanding of the intrinsic magnetic properties of thin gadolinium films, particularly for thicknesses of topicality. We report studies on 50nm thick nanogranular polycrystalline gadolinium thin films on SiO2 wafers that demonstrate single-crystal like behavior. The maximum in-plane saturation magnetization at 4K was found to be 4pMS4K = (2.61±0.26)T with a coercivity of HC4K = (160±5)Oe. A maximum Curie point of TC = (293±2)K was measured via zero-field-cooled - field-cooled magnetization measurements in close agreement with values reported in bulk single crystals. Our measurements revealed magnetic transitions at T1 = (12±2)K (as deposited samples) and T2 = (22±2)K (depositions on heated substrates) possibly arising from the interaction of paramagnetic fcc grains with their ferromagnetic hcp counterparts.

Towards a general framework for social media research using big data

The increasing adoption of cloud computing, social networking, mobile and big data technologies provide challenges and opportunities for both research and practice. Researchers face a deluge of data generated by social network platforms which is further exacerbated by the co-mingling of social network platforms and the emerging Internet of Everything. While the topicality of big data and social media increases, there is a lack of conceptual tools in the literature to help researchers approach, structure and codify knowledge from social media big data in diverse subject matter domains, many of whom are from nontechnical disciplines. Researchers do not have a general-purpose scaffold to make sense of the data and the complex web of relationships between entities, social networks, social platforms and other third party databases, systems and objects. This is further complicated when spatio-temporal data is introduced. Based on practical experience of working with social media datasets and existing literature, we propose a general research framework for social media research using big data. Such a framework assists researchers in placing their contributions in an overall context, focusing their research efforts and building the body of knowledge in a given discipline area using social media data in a consistent and coherent manner.