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Key words ZnO thin films, Mg-doped, modified pechini method, band gap, photoluminescence spectra.ZnO thin films with different Mg doping contents (0%, 3%, 5%, 8%, 10%, respectively) were prepared on quartz glass substrates by a modified Pechini method. XRD patterns reveal that all the thin films possess a polycrystalline hexagonal wurtzite structure. The peak position of (002) plane for Mg-doped ZnO thin films shifts toward higher angle due to the Mg doping. The crystallite size calculated by Debey-Scherrer formula is in the range of 32.95-48.92 nm. The SEM images show that Mg-doped ZnO thin films are composed of dense nanoparticles, and the thickness of Mg-doped ZnO thin films with Mg doped at 8% is around 140 nm. The transmittance spectra indicate that Mg doping can increase the optical bandgap of ZnO thin films. The band gap is tailored from 3.36 eV to 3.66 eV by changing Mg doping concentration between 3% and 10%. The photoluminescence spectra show that the ultraviolet emission peak of Mg-doped ZnO thin films shifts toward lower wavelength as Mg doping content increases from 3% to 8%. The green emission peak of Mg-doped ZnO thin films with Mg doping contents were 3%, 8%, and 10% is attributed to the oxygen vacancies or donor-acceptor pair. These results prove that Mg-doped ZnO thin films based on a modified Pechini method have the potential applications in the optoelectronic devices.

a b s t r a c tA fundamental goal of datacenter networking is to efficiently interconnect a large number of servers in a cost-effective way. Inspired by the commodity servers in today's data centers that come with dual-port, we consider how to design low-cost, robust, and symmetrical network structures for containerized data centers with dual-port servers and low-end switches. In this paper, we propose a family of such network structure called a DCube, including H-DCube and M-DCube. The DCube consists of one or multiple interconnected sub-networks, each of which is a compound graph made by interconnecting a certain number of basic building blocks by means of a hypercube-like graph. More precisely, the H-DCube and M-DCube utilize the hypercube and 1-möbius cube, respectively, while the M-DCube achieves a considerably higher aggregate bottleneck throughput compared to H-DCube. Mathematical analysis and simulation results show that the DCube exhibits graceful performance degradation as the failure rate of server or switch increases. Moreover, the DCube significantly reduces the required wires and switches compared to the BCube and fat-tree. In addition, the DCube achieves a higher speedup than the BCube does for the one-to-several traffic patterns. The proposed methodologies in this paper can be applied to the compound graph of the basic building block and other hypercube-like graphs, such as Twisted cube, Flip MCube, and fastcube.

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The use of digital information in geological fields is becoming very important. Thus, informatization in geological surveys should not stagnate as a result of the level of data accumulation. The integration and sharing of distributed, multi-source, heterogeneous geological information is an open problem in geological domains. Applications and services use geological spatial data with many features, including being cross-region and cross-domain and requiring real-time updating. As a result of these features, desktop and web-based geographic information systems (GISs) experience difficulties in meeting the demand for geological spatial information. To facilitate the real-time sharing of data and services in distributed environments, a GIS platform that is open, integrative, reconfigurable, reusable and elastic would represent an indispensable tool. The purpose of this paper is to develop a geological cloud-computing platform for integrating and sharing geological information based on a cloud architecture. Thus, the geological cloud-computing platform defines geological ontology semantics; designs a standard geological information framework and a standard resource integration model; builds a peer-to-peer node management mechanism; achieves the description, organization, discovery, computing and integration of the distributed resources; and provides the distributed spatial meta service, the spatial information catalog service, the multi-mode geological data service and the spatial data interoperation service. The geological survey information cloud-computing platform has been implemented, and based on the platform, some geological data services and geological processing services were developed. Furthermore, an iron mine resource forecast and an evaluation service is introduced in this paper.

Geologic survey procedures accumulate large volumes of structured and unstructured data. Fully exploiting the knowledge and information that are included in geological big data and improving the accessibility of large volumes of data are important endeavors. In this paper, which is based on the architecture of the geological survey information cloud-computing platform (GSICCP) and big-data-related technologies, we split geologic unstructured data into fragments and extract multi-dimensional features via geological domain ontology. These fragments are reorganized into a NoSQL (Not Only SQL) database, and then associations between the fragments are added. A specific class of geological questions was analyzed and transformed into workflow tasks according to the predefined rules and associations between fragments to identify spatial information and unstructured content. We establish a knowledge-driven geologic survey information smart-service platform (GSISSP) based on previous work, and we detail a study case for our research. The study case shows that all the content that has known relationships or semantic associations can be mined with the assistance of multiple ontologies, thereby improving the accuracy and comprehensiveness of geological information discovery.

Three-dimensional (3D) geological models are important representations of the results of regional geological surveys. However, the process of constructing 3D geological models from two-dimensional (2D) geological elements remains difficult and is not necessarily robust. This paper proposes a method of migrating from 2D elements to 3D models. First, the geological interfaces were constructed using the Hermite Radial Basis Function (HRBF) to interpolate the boundaries and attitude data. Then, the subsurface geological bodies were extracted from the spatial map area using the Boolean method between the HRBF surface and the fundamental body. Finally, the top surfaces of the geological bodies were constructed by coupling the geological boundaries to digital elevation models. Based on this workflow, a prototype system was developed, and typical geological structures (e.g., folds, faults, and strata) were simulated. Geological modes were constructed through this workflow based on realistic regional geological survey data. The model construction process was rapid, and the resulting models accorded with the constraints of the original data. This method could also be used in other fields of study, including mining geology and urban geotechnical investigations.