Structure and thermoelectric properties of higher manganese silicides synthesized by pack cementation

Higher manganese silicides (HMS) are promising alternative materials for middle to high temperature thermoelectric applications as a low-cost, non-toxic and highly stable p-type leg. Many of the preparation methods that have been reported previously require long-time and energy consuming processes, as well as expensive equipment, and often do not result in a material of sufficient quality. In this study, the simple, cost-effective and eco-friendly technique of pack cementation is applied. HMS powders synthesized at different experimental conditions are studied and compared considering their structure, composition, short-term thermal stability in air and thermoelectric properties. X-ray diffraction analysis, X-ray photoelectron spectroscopy, scanning electron microscopy, thermogravimetry and thermoelectric measurements (in terms of Seebeck coefficient, electrical and thermal conductivity) were employed for the characterization of the material and evaluation of its performance. All samples were identified as HMS and only some negligible traces of MnSi were detected. They moderately oxidize when heated non-isothermally under air atmosphere up to 1473 K, while the presence of HMS remains dominant even at such high temperatures. Their thermoelectric properties were remarkable for an undoped material, with a maximum figure of merit (ZT) of 0.47 at 777 K. Pack cementation appeared to have a great potential as the synthesis route of high-efficiency HMS.     

Evaluating the Use of Daily Care Notes Software for Older People with Dementia

There has been little research to investigate the impact of software to support the care for older people with dementia care. This article reports the evaluation of software adapted to support one key person-centered task for the care of older residents with dementia – recording and sharing daily care notes. The evaluation on the dementia wing of 1 residential home for over 6 months revealed that use of the software on mobile devices carried by the carers increased the number and volume of daily care notes recorded, but only for the types of content that were already being recorded by carers. Carers reported more advantages that resulted from daily care notes once in digital form than from the documenting task, as well as barriers to the use of mobile digital software to record daily care notes.     

Fatigue crack growth simulation in adhesively bonded composite joints

A numerical model has been developed for simulating fatigue crack growth (debonding) in adhesively bonded composite joints subjected to mode‐I, mode‐II, and mixed‐mode I + II loading conditions. The model employs a cohesive zone model described by a modified bilinear traction‐separation law. Fatigue damage in the composite adherends is not considered in the model. To account for crack divergence and reduce sensitivity of numerical results on mesh density, a crack front detection algorithm based on the effective element's length was employed. The model is implemented as a user‐defined subroutine (UMAT) in the commercial FE code LS‐DYNA. The model's input parameters, in the form of a modified Paris law, and the validation data were obtained from experimental tests conducted by the authors. It was found that the model is able to successfully simulate crack growth in the regime of the experimental data.     

Phytoextraction technologies for mercury- and chromium-contaminated soil: a review

Mercury and chromium represent two important elements of environmental concern and with a strong impact on human health. Several technologies are available to clean up the environment from these kinds of contaminants, but most of them are costly and difficult to use to get optimum results. Currently, phytoextraction is an effective and affordable technological solution used to extract or remove metals from contaminated soil and water by the use of plants as tools. This technology is environment-friendly and potentially cost-effective. This paper aims to compile some information about the two metals mercury and chromium, their effects and their possible treatment by phytoextraction, a branch of phytoremediation technologies aimed to confront metal/metalloid pollution. © 2019 Society of Chemical Industry     

Graphite Oxide and Aromatic Amines: Size Matters

Experimental and theoretical studies are performed in order to illuminate, for first time, the intercalation mechanism of polycyclic aromatic molecules into graphite oxide. Two representative molecules of this family, aniline and naphthalene amine are investigated. After intercalation, aniline molecules prefer to covalently connect to the graphene oxide matrix via chemical grafting, while napthalene amine molecules bind with the graphene oxide surface through π–π interactions. The presence of intercalated aromatic molecules between the graphene oxide layers is demonstrated by X‐ray diffraction, while the type of interaction between graphene oxide and polycyclic organic molecules is elucidated by X‐ray photoelectron spectroscopy. Combined quantum mechanical and molecular mechanical calculations describe the intercalation mechanism and the aniline grafting, rationalizing the experimental data. The present work opens new perspectives for the interaction of various aromatic molecules with graphite oxide and the so‐called “intercalation chemistry”.     

Local community detection with hints

Local community detection is a widely used method for identifying groups of nodes starting from seeding nodes. The seed(s) are usually selected either randomly or based only on structural properties of the network. However, in many cases the choice of seed(s) incorporates external knowledge that attaches to these nodes an additional importance for their community. This knowledge, may be derived from an expert on the domain, or may arise from the network’s side information and it constitutes our motivation for the present work; this additional information about the importance of seed(s) can be exploited for detection of better and more relevant communities. We call such biased seed(s), hint(s). Our approach, is to reflect the importance of hints by changing appropriately the network in their vicinity. To the best of our knowledge, no such viewpoint of the seeding nodes in local community detection has been considered before. The aim of this study is to identify a single community which contains the hint(s). Our key contribution is the proposed Hint Enhancement Framework(HEF) that applies a two-step procedure to discover the community of the hint(s): 1) it changes the network by amplifying the hint(s) using re-weighting or re-wiring strategies so as to materialize the bias towards them and 2) it applies local community detection algorithms on the altered network of step 1. We experimentally evaluate HEF in synthetic and real datasets, and demonstrate the positive aspects of the framework in identifying better communities, in comparison with plain local community detection algorithms as well as a global one.

     

Intelligent building energy management system using rule sets

The current study presents an intelligent decision support model using rule sets based on a typical building energy management system. In addition, the model's impact on the energy consumption and indoor quality of a typical office building in Greece is presented. The model can control how the building operational data deviates from the settings as well as carry out diagnosis of internal conditions and optimize building's energy operation. In this context, the integrated “decision support model” can contribute to the management of the daily energy operations of a typical building, related to the energy consumption, by incorporating the following requirements in the best possible way: (a) the guarantee of the desirable levels of living quality in all building's rooms and (b) the necessity for energy savings.