B4C-TiB2 ceramics (TiB2 ranging 5~70 vol%) with Mo-Co-WC as the sintering additive were prepared by spark plasma sintering. In comparison with B4C-TiB2 without additive, the enhanced densification was evident in the sintered specimen with Mo-Co-WC additive. Core-rim structured grain was observed around TiB2 grains. The interface of the rim between TiB2 and B4C phases demonstrated different feature: the inner borderline of the rim exhibited a smooth feature, whereas a sharp curved grain boundary was observed between the rim and the B4C grain. The formation mechanism is discussed: the epitaxial growth of (Ti,Mo,W)B2 rim around the TiB2 core may occur as a result of the solid solution and dissolution-precipitation between TiB2 phase and the sintering additive. It was revealed that the fracture toughness increased as the content of TiB2 content increased, alongside the decreased hardness. B4C-30 vol% TiB2 specimen demonstrated the optimal combination of mechanical properties, reaching Vickers hardness of 24.3 GPa and fracture toughness of 3.33 MPa·m1/2. 相似文献
Low-dimensional carbon nanostructures are ideal nanofillers to reinforce the mechanical performance of polymer nanocomposites due to their excellent mechanical properties. Through molecular dynamics simulations, the mechanical performance of poly(vinyl alchohol) (PVA) nanocomposites reinforced with a single-layer diamond – diamane is investigated. It is found the PVA/diamane exhibits similar interfacial strengths and pull-out characteristics with the PVA/bilayer-graphene counterpart. Specifically, when the nanofiller is fully embedded in the nanocomposite, it is unable to deform simultaneously with the PVA matrix due to the weak interfacial load transfer efficiency, thus the enhancement effect is not significant. In comparison, diamane can effectively promote the tensile properties of the nanocomposite when it has a laminated structure as it deforms simultaneously with the matrix. With this configuration, the interlayer sp3 bonds endows diamane with a much higher resistance under compression and shear tests, thus the nanocomposite can reach very high compressive and shear stress. Overall, enhancement on the mechanical interlocking at the interface as triggered by surface functionalization is only effective for the fully embedded nanofiller. This work provides a fundamental understanding of the mechanical properties of PVA nanocomposites reinforced by diamane, which can shed lights on the design and preparation of next generation high-performance nanocomposites. 相似文献
Coal mining can dramatically change hydrogeological conditions and induce serious environmental problems. Fifty groundwater samples were collected from the main aquifers in the Yuaner coal mine (Anhui Province, China). The results show that the main hydrogeochemical processes in the mine include dissolution, precipitation, pyrite oxidation, desulfurization, and cation exchange. The Neogene porous aquifer is affected by groundwater flow conditions; its main hydrogeochemical processes are dissolution of carbonate minerals and gypsum, and cation exchange. The Permian coal measure’s fractured sandstone aquifer was confirmed to be controlled by the region’s geological structure; its main hydrogeochemical processes are desulfurization and cation exchange. The Carboniferous Taiyuan limestone aquifer was determined by both groundwater flow conditions and regional geological structure; its main hydrogeochemical processes are dissolution of carbonate minerals and gypsum, pyrite oxidation, and cation exchange. Additionally, hydrogeochemical inverse modeling of the groundwater flow path confirm the hydrochemistry results and principal component analysis.
Traditionally, in supervised machine learning, (a significant) part of the available data (usually 50%-80%) is used for training and the rest—for validation. In many problems, however, the data are highly imbalanced in regard to different classes or does not have good coverage of the feasible data space which, in turn, creates problems in validation and usage phase. In this paper, we propose a technique for synthesizing feasible and likely data to help balance the classes as well as to boost the performance in terms of confusion matrix as well as overall. The idea, in a nutshell, is to synthesize data samples in close vicinity to the actual data samples specifically for the less represented (minority) classes. This has also implications to the so-called fairness of machine learning. In this paper, we propose a specific method for synthesizing data in a way to balance the classes and boost the performance, especially of the minority classes. It is generic and can be applied to different base algorithms, for example, support vector machines, k-nearest neighbour classifiers deep neural, rule-based classifiers, decision trees, and so forth. The results demonstrated that (a) a significantly more balanced (and fair) classification results can be achieved and (b) that the overall performance as well as the performance per class measured by confusion matrix can be boosted. In addition, this approach can be very valuable for the cases when the number of actual available labelled data is small which itself is one of the problems of the contemporary machine learning. 相似文献
Bulletin of Engineering Geology and the Environment - Many uncertainties exist in pile-stabilized slopes which make their design substantially complicated. In this paper, a first-order reliability... 相似文献