Evaluation of the impact of phase change humidity control material on energy performance of office buildings

Phase change humidity control material (PCHCM) is a new kind of composite made of high performance PCM microcapsules and diatomite. The PCHCM composite can moderate the hygrothermal variations by absorbing or releasing both heat and moisture and significantly reduce the peak/valley values of indoor temperature and relative humidity. In this paper, a novel model is developed to evaluate the energy performance of office buildings with PCHCM. The model is validated by a series of experiments, and then applied to investigate the effect of PCHCM on energy consumption in different typical climates worldwide (i.e. Beijing, Paris, Atlanta, and Guangzhou). Results show that high values of energy efficiencies can be obtained in the climates which characterized by a wide amplitude of temperature and humidity difference all day along (Paris and Atlanta). Noteworthy, the highest potential energy saving rate could be up to 19.57% for the office building in Paris

Dual Long Short-Term Memory Networks for Sub-Character Representation Learning

Characters have commonly been regarded as the minimal processing unit in Natural Language Processing (NLP). But many non-latin languages have hieroglyphic writing systems, involving a big alphabet with thousands or millions of characters. Each character is composed of even smaller parts, which are often ignored by the previous work. In this paper, we propose a novel architecture employing two stacked Long Short-Term Memory Networks (LSTMs) to learn sub-character level representation and capture deeper level of semantic meanings. To build a concrete study and substantiate the efficiency of our neural architecture, we take Chinese Word Segmentation as a research case example. Among those languages, Chinese is a typical case, for which every character contains several components called radicals. Our networks employ a shared radical level embedding to solve both Simplified and Traditional Chinese Word Segmentation, without extra Traditional to Simplified Chinese conversion, in such a highly end-to-end way the word segmentation can be significantly simplified compared to the previous work. Radical level embeddings can also capture deeper semantic meaning below character level and improve the system performance of learning. By tying radical and character embeddings together, the parameter count is reduced whereas semantic knowledge is shared and transferred between two levels, boosting the performance largely. On 3 out of 4 Bakeoff 2005 datasets, our method surpassed state-of-the-art results by up to 0.4%. Our results are reproducible, source codes and corpora are available on GitHub.Comment: Accepted & forthcoming at ITNG-201

Growth of Large Domain Epitaxial Graphene on the C-Face of SiC

Growth of epitaxial graphene on the C-face of SiC has been investigated. Using a confinement controlled sublimation (CCS) method, we have achieved well controlled growth and been able to observe propagation of uniform monolayer graphene. Surface patterns uncover two important aspects of the growth, i.e. carbon diffusion and stoichiometric requirement. Moreover, a new "stepdown" growth mode has been discovered. Via this mode, monolayer graphene domains can have an area of hundreds of square micrometers, while, most importantly, step bunching is avoided and the initial uniformly stepped SiC surface is preserved. The stepdown growth provides a possible route towards uniform epitaxial graphene in wafer size without compromising the initial flat surface morphology of SiC.Comment: 18 pages, 8 figure

Weak antilocalization in epitaxial graphene: evidence for chiral electrons

Transport in ultrathin graphite grown on silicon carbide is dominated by the electron-doped epitaxial layer at the interface. Weak anti-localization in 2D samples manifests itself as a broad cusp-like depression in the longitudinal resistance for magnetic fields 10 mT$< B <$ 5 T. An extremely sharp weak-localization resistance peak at B=0 is also observed. These features quantitatively agree with graphene weak-(anti)localization theory implying the chiral electronic character of the samples. Scattering contributions from the trapped charges in the substrate and from trigonal warping due to the graphite layer on top are tentatively identified. The Shubnikov-de Haas oscillations are remarkably small and show an anomalous Berry's phase.Comment: 5 pages, 4 figures. Minor change