Deformation behaviour of electrodeposited nanocrystalline Ni with broad grain size distribution

In the present work, nanocrystalline Ni (nc-Ni) with a broad grain size distribution (BGSD) of 5-120 nm and an average grain size of 27.2 nm was prepared. The BGSD nc-Ni sample shows a similar strength and good ductility in comparison with electrodeposited nc-Ni with a narrow grain size distribution. The intracrystalline dislocation network was observed in the post-deformed microstructure confirming the conventional intracrystalline dislocation sliding mechanism in BGSD nc-Ni. The uniaxial tensile loading-unloading-loading deformation shows BGSD nc-Ni has the capability to store dislocations in the grain interior, which is very limited compared with that of coarse grained metals. For BGSD nc-Ni, the strain rate sensitivity of flow stress m enhances with decreasing strain rate. At the strain rate of 5 x 10(-6) s(-1), m was estimated to be 0.055. At the corresponding strain rate, the enhanced ductility along with the decreased strength was achievable, indicating activation of other deformation mechanisms, e. g. grain boundary sliding or diffusion.

Late Quaternary aeolian dust input variability on the Chinese Loess Plateau: inferences from unmixing of loess grain-size records

IEECAS SKLLQG

ENVIRONMENTAL EVOLUTION OF ORDOS DESERT IN CHINA SINCE 1.1MA B. P. AS INDICATED BY YULIN STRATIGRAPHICAL SECTION AND ITS GRAIN-SIZE ANALYSIS RESULTS

IEECAS SKLLQG

Changes in grain-size and sedimentation rate of the Neogene Red Clay deposits along the Chinese Loess Plateau and implications for the palaeowind system

IEECAS SKLLQG

Grain size distribution of quartz isolated from Chinese loess/paleosol

Grain size distribution of bulk loess-paleosol and quartz chemically extracted from the loess/paleosol shows that mean size of the bulk samples is always finer than that of the quartz, The original aeolian depositions have been modified to various degrees by post-depositional weathering and pedogenic processes. The grain size distribution of the isolated quartz should be close to that of the primary aeolian sediment because the chemical pretreatment excludes secondary produced minerals. Therefore, the grain size of the quartz may be considered to more clearly reflect the variations of winter monsoon intensity.

How Porosity and Permeability Vary Spatially With Grain Size, Sorting, Cement Volume, and Mineral Dissolution In Fluvial Triassic Sandstones: The Value of Geostatistics and Local Regression

Although it is well known that sandstone porosity and permeability are controlled by a range of parameters such as grain size and sorting, amount, type, and location of diagenetic cements, extent and type of compaction, and the generation of intergranular and intragranular secondary porosity, it is less constrained how these controlling parameters link up in rock volumes (within and between beds) and how they spatially interact to determine porosity and permeability. To address these unknowns, this study examined Triassic fluvial sandstone outcrops from the UK using field logging, probe permeametry of 200 points, and sampling at 100 points on a gridded rock surface. These field observations were supplemented by laser particle-size analysis, thin-section point-count analysis of primary and diagenetic mineralogy, quantitiative XRD mineral analysis, and SEM/EDAX analysis of all 100 samples. These data were analyzed using global regression, variography, kriging, conditional simulation, and geographically weighted regression to examine the spatial relationships between porosity and permeability and their potential controls. The results of bivariate analysis (global regression) of the entire outcrop dataset indicate only a weak correlation between both permeability porosity and their diagenetic and depositional controls and provide very limited information on the role of primary textural structures such as grain size and sorting. Subdividing the dataset further by bedding unit revealed details of more local controls on porosity and permeability. An alternative geostatistical approach combined with a local modelling technique (geographically weighted regression; GWR) subsequently was used to examine the spatial variability of porosity and permeability and their controls. The use of GWR does not require prior knowledge of divisions between bedding units, but the results from GWR broadly concur with results of regression analysis by bedding unit and provide much greater clarity of how porosity and permeability and their controls vary laterally and vertically. The close relationship between depositional lithofacies in each bed, diagenesis, and permeability, porosity demonstrates that each influences the other, and in turn how understanding of reservoir properties is enhanced by integration of paleoenvironmental reconstruction, stratigraphy, mineralogy, and geostatistics.