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To realize high areal density, hard disk drives larger than 4 Tbit inâˆ'2, ultrafine FePt grains of less than 5 nm and grain density larger than 24 T inâˆ'2 are required. Although there have been many investigations to reduce the grain size of FePt, there are only a few reports on the control of grain density. To increase the grain density, we focused on three aspects of the surface morphology and grain density: nucleation sites on the substrate surface, surface free energy, and lattice mismatch. We achieved 14 T inâˆ'2 by maximizing the number of nucleation sites in the FePt-C granular film and found that the surface free energy and lattice mismatch are crucial parameters for controlling the grain density. [ABSTRACT FROM AUTHOR]

Iron (Fe) is an important essential micronutrient and its deficiency is a widespread micronutrient malnutrition problem for human being in the world. Iron biofortification of staple food crop is regarded as an effective way to solve this problem. Rice is the most important food crop in the world feeding over half of the global population; therefore, a small increase in Fe concentration in rice grain can greatly improve human health. However, the mechanisms of Fe dense accumulation in rice grain are not fully understood, which limits the advance of high Fe-dense rice breeding. In this paper, the characteristics of Fe re-utilization in the dense rice genotype (IR68144) were studied, as compared with the indense rice genotype (IR64). The results showed that the ability of iron remobilization from “source” to “sink” was much greater in IR68144 than in IR64, i.e. from root, the 1st, 2nd, and 3rd leaf, as well as leaf sheath to the new growing leaves and tillers at vegetative stage, and from root, stem, and flag leaf to grain at reproductive stage. It was estimated that the re-mobilization of Fe in the dense genotype IR68144 accounted for 28.5% of total Fe of the plant at the 4th leaf stage, which was 1.6-fold higher than that of the in-dense genotype IR64. At the reproductive growth stage, the re-translocation of Fe from leaves and stems to grain was found to be much greater in the dense than in the indense rice genotype, and the re-translocation of Fe depended greatly on Fe pretreatment levels before anthesis and Fe/Zn nutritional status after anthesis. The dense genotype remobilized about 10-time more Fe from stem with low Fe pretreatment, and exported around 6-time more Fe from roots and 10-time more Fe from the flag leaf with adequate Fe pretreatment, as compared to the indense genotype. The remobilization of Fe from the vegetative organs to grain was greater at low Fe supply than at higher Fe supply, and greater re-translocation of Fe was noted in IR68144 than in IR64 when pretreated with low Fe. After stopped Fe supply at anthesis, the Fe export from the flag leaf decreased with increasing Fe pretreatment levels in IR68144, but Fe input in the flag leaf was noted in IR64. After anthesis, the contribution of remobilized Fe to brown rice Fe accumulation was greater in IR68144 than in IR64 with low, adequateand high Fe pretreatments. The results indicate that the Fe-dense rice genotype has greater ability of reutilizing Fe in the source tissues than the indense genotype, and the remobilization ability of Fe from older leaf to the new growing leaves could be used for predicting grain Fe accumulation ability.

ABSTRACT: Unchanged reference values of grain nutrient contents for corn have been used for over 20 years, despite yield increases, the development of new hybrids, and modifications to cropping systems, especially the establishment of in-season second crops and the wide adoption of no-tillage. This study measured macro- and micronutrient contents in corn grains from different regions, in the first (summer) and second (fall) crop, to update the reference values of estimated nutrient removal. A secondary objective was to determine whether there were correlations between grain nutrient contents and grain yields and densities. In this study, 175 corn grain samples of experiments on cultivar evaluation and 22 samples from soil management trials from five states (SP, PR, MG, MT, and MS) were used. Grain nutrient contents were ranked as follows: N > K > P > Mg > S (g kg−1) and Ca > Zn > Fe > Mn > B > Cu (mg kg−1). Content values for half of the nutrients analyzed were negatively correlated with yield and/or seed weight, whereas grain density was not correlated with nutrient contents. For the first crop of corn, the N, S, and Cu contents clearly decreased with increases in grain yield and seed weight, indicating a lower nutrient removal at higher yields. The great variability of results among environments makes it difficult to differentiate between the first and second crop of corn. The reference values currently in use overestimate the removal of N, P, K, Ca, Mg, S, and Zn grain contents, but underestimate Cu and B in corn. The results of this study can be used to update the reference values of nutrient contents of corn grains to better estimate nutrient removal from the soil.

Density, porosity, and pore morphology constitute the basic physical properties of meteorites. These properties of 214 fragments from 163 different ordinary chondrites (OCs), including falls, non‐Antarctic finds, and Antarctic finds, were measured, calculated, and investigated. Of all the measured OCs data, densities, and porosities of 37 OC falls (14 H, 17 L, and 6 LL), 31 non‐Antarctic finds (9 H and 22 L), and 95 Antarctic finds (24 H and 73 L) are reported for the first time. The individual masses of all the meteorite fragments measured in this study ranged between 0.8953 and 7.7133 g, and these masses were too low to be measured by the Archimedean glass bead method. Our study indicated that the grain density and porosity of find OCs are significantly reduced by terrestrial weathering. As a result, such OCs are not suitable for their physical propertie study. Shock degree ≤S2 slightly increases the measurable porosities of the meteorites by generating a certain amount of tiny cracks in the silicates to connect some isolated pores with the measurable pores. Shock degree over S2 significantly reduces the porosities of meteorites by compacting or even melting the material. Weathering reduced the porosities via space filling of weathering products. Shock load over S2 reduced the porosities of the meteorites by minerals compressing or melting. Moreover, the shock load over S2 also converted intergrain irregular pores into intragrain cracks. Thermal metamorphism mainly changed the pore morphology (size) by pore merging during mineral recrystallization. The pore morphology also plays a significant role in controlling the friability of OCs. Plain Language Summary: This study aimed to obtain high‐precision density and porosity data for ordinary chondrites (OCs) and to understand the major influences on these properties. The grain densities, bulk densities, and porosities of 214 small (0.8953–7.7133 g) OC fragments of falls, non‐Antarctic finds, and Antarctic finds were measured using the high‐precision Pycnometer‐balloon vacuum packing method. The Grove Mountain OCs from Antarctica and falls in China have seldom studied in previous works. Moreover, the pore morphologies of the OCs were systematically observed. The results indicated that the grain densities and porosities of non‐Antarctic finds and Antarctic finds were significantly altered by terrestrial weathering. Shock strength ≤S2 increases measurable porosities by generating intragrain cracks and connecting some isolated pores. However, shock intensity over S2 reduces the porosities of meteorites by minerals compressing or melting. Thermal metamorphism changes the pore morphology by pore merging during mineral recrystallization. Our high‐precision porosity and density data can be used not only to evaluate the homogeneity of a meteorite shower samples but also to understand the structures of S‐type asteroids. Key Points: The high‐precision densities and porosities of 214 fragments from 163 different ordinary chondrites (OCs) including falls, non‐Antarctic finds, and Antarctic finds were measured and calculated; the pore morphology of some selected OCs were investigatedWeak shock (

Controlling the number density of grains in magnetic recording media is critical for improving the areal density of the recording. Herein, we report the dependence of grain density and microstructure of FePt-based granular films for heat-assisted magnetic recording media on the lattice mismatch between the FePt films and substrates SrTiO 3 , MgAl 2 O 4 , MgO and TiO 2. The grain density and grain size of the FePt films increased and decreased, respectively, with the increasing lattice mismatch between the films and substrates. The optimum lattice mismatch for the FePt-based granular films was found to be 8%, which corresponds to the MgO substrate. FePt films grown on TiO 2 substrate, which had the largest lattice mismatch of 16%, showed poor morphology and low grain density. The results imply that an underlayer with which a film develops a suitable mismatch plays a key role in controlling the microstructure and magnetic properties of the film. • The grain density and morphology were controlled by varying the lattice mismatch. • The optimum grain density and microstructure would be obtained in the underlayer-FePt mismatch between 8.3% and 15.9%. • The underlayer with suitable mismatch plays a key role to control microstructure and magnetic properties. [ABSTRACT FROM AUTHOR]

• FePt-Cr 2 O 3 granular film shows the highest grain density of 25.2 Tgrain/in2 in FePt-based granular film. • Low L 1 0 order is due to a small contact area at the MgO/FePt-Cr 2 O 3 interface and Cr diffusion. • The solid–liquid interfacial energy in the FePt granular system was a key factor in controlling the microstructures. Increase in the FePt grain density is necessary to achieve an ultra-high recording density of the heat-assisted magnetic recording. Herein, the highest grain density in FePt-Cr 2 O 3 granular thin films was obtained by utilizing a densified FePt nucleation layer. The reduced magnetic properties were attributed to the grain shape and effect of elemental diffusion at the FePt/Cr 2 O 3 interface. The equilibrium shape of the FePt grains indicated that the solid–liquid interfacial energy in the FePt granular system is a key factor in controlling the microstructures. [ABSTRACT FROM AUTHOR]

Metal matrix composites (MMCs) have received much attention due to their promising advanced mechanical properties. The aim of this work is to create a micro-macro model of composite crystallization. The developed model is coupled with the process of heat flow in the macroscopic scale, resulting from the heat emission during the nucleation and the growth of grains. Taking into account both of these phenomena, the proposed model is distinguished by a good reflection of reality. Moreover, the presented model assumes that the function of grain density depends on the maximal supercooling and the mass volume of the reinforcement phase particles. The knowledge of the equations, describing the function of grain density depending on the degree of supercooling, is necessary in the, more and more often used, numerical modelling of the casting structure.

The grain density, Nv, in the solid state after solidification of AZ91/SiC composite is a function of maximum undercooling, ΔT, of a liquid alloy. This type of function depends on the characteristics of heterogeneous nucleation sites and number of SiC present in the alloy. The aim of this paper was selection of parameters for the model describing the relationship between the grain density of primary phase and undercooling. This model in connection with model of crystallisation, which is based on chemical elements diffusion and grain interface kinetics, can be used to predict casting quality and its microstructure. Nucleation models have parameters, which exact values are usually not known and sometimes even their physical meaning is under discussion. Those parameters can be obtained after mathematical analysis of the experimental data. The composites with 0, 1, 2, 3 and 4wt.% of SiC particles were prepared. The AZ91 alloy was a matrix of the composite reinforcement SiC particles. This composite was cast to prepare four different thickness plates.They were taken from the region near to the thermocouple, to analyze the undercooling for different composites and thickness plates and its influence on the grain size. The microstructure and thermal analysis gave set of values that connect mass fraction of SiC particles, and undercooling with grain size. These values were used to approximate nucleation model adjustment parameters. Obtained model can be very useful in modelling composites microstructure.

The main aim of this research is to establish the effects of moisture content on some physical properties of soybean seeds. Testing was performed for the Balkan and Sava varieties. The following physical properties were measured: dimensions, equivalent diameter, sphericity, grain density, apparent density, coefficient of friction, dynamic angle of repose, grain volume and mechanical properties. Moisture content of soybean seeds ranged from 8 to 20%. This paper presents the preliminary results from the first year of research. It was noted that most of the soybean physical properties depends on the humidity in the measured range. It is known from science literature that soya seed (grain) deforming, may cause two cases. The final outcome of dry seeds is grinded grain, and in case of wet grains they may be crushed . This research presents preliminary values of rupture force in the case of grinding grain and analyze the change of modulus of elasticity.

Grain texture defines the structural component of barley and can be quantified by measuring endosperm hardness and grain density. Both components impact on important grain quality traits, in particular water-uptake efficiency, steeping, malt-extract potential, pearling efficiency, milling efficiency, digestibility, and grain appearance. Grain composition, grain size, grain morphology are traits found to impact the expression of endosperm hardness and grain density. However, little is known about the genomic regions that are directly associated with the expression of grain texture and how these regions may be employed to improve grain quality. A combination of small-scale phenotyping tools, consensus maps, proteomics, and genomics will aid in understanding how grain texture is associated with barley processing and malt-quality related traits. This review highlights the interactions between endosperm hardness, grain density, grain size traits, and malt-quality. For grain texture it is clear that even when all the allelic variations at the Hardness locus have been fully described, there will remain a need to understand the pleiotropic effects on grain texture of a range of other gene loci that are currently considered to be important in physical grain size or phenology. [ABSTRACT FROM AUTHOR]

Grain weight, which can be dissected into grain length, grain width grain shape and density, is one of the determinants of wheat yield and milling performance. To get more information on cultivar and environment effects on grain weight and size variation in winter wheat, we studied by image analysis grains of 27 wheat cultivars, harvested from yield trials performed in South Romania in three years (2013-2015) with different weather conditions. We found large differences among cultivars for grain weight (TKW), length (L), width (w) and the factor Form*Density (F). Grain length was less influenced by environment than the other grain weight components. Correlation between the three components of grain weight (L, w and F) was low and not significant, suggesting that combining high values of these components might be possible to a certain extent. Considering both the amplitude of variation among studied cultivars and the lower influence of years, grain length seems to be the component with highest probability of determining genetic progress in breeding for grain weight. To obtain most effect of increased grain weight and size on yield, research on the strength and possible deviations from the negative correlation between grain weight and grain number are necessary. [ABSTRACT FROM AUTHOR]

Nitrogen (N) application strongly affects both the total spikelets and grain weight in rice (Oryza sativa L.), thereby affecting grain yield. Grain weight is closely related to the grain-filling process after the heading stage, and can be regarded as a combination of grain size and grain density (GD). However, there is a lack of information about the response of GD in rice to N. Here, we examined in a lager panicle hybrid indica rice at two field experimental sites the responses of grain traits (including GD), grain yield, and yield components to various N treatments and their relationships with each other. In this study, the grains with six GD ranges were fractionated into the light grain (1.00 g ml−1 ≤ GD < 1.15 g ml−1) and heavy grain or high-density grain (GD ≥ 1.15 g ml−1). High N application increased the total spikelets m−2, but did not result in high grain yield due to reduced grain weight (seed-setting rate and 1000-grain weight). Reduction of the 1000-grain weight under high N was related to the decrease in grain volume and high-density grain content (the ratio of the weights of high-density grains to the total grains weight). As N application increased from 0 to 225 kg ha−1, on average, the high-density grain content decreased by 31.93 %, from 78.21 % to 53.24 %. Grain plumpness and GD were the main factors affecting grain weight. GD was more important to the grain weight when grain size was smaller, and plumpness degree and GD were both crucial for grain weight when grain volume was larger. Compared with light grains, heavy grains had higher amylose content and lower crude protein content. These results indicated that the constraint and compensation relationship between spikelet number and grain weight in rice was also reflected in the equilibrium between grain size and GD. Although high N input in rice production increased the total spikelets m−2, high N input decreased the grain volume, especially the high-density grain content. • High nitrogen application reduced the high-density (≥ 1.15 g ml−1) grain content. • Rice quality of heavy grain was different from that of light grain. • For larger-volume grain, both plumpness and density affected grain weight. • There were constraint and compensation between grain size and grain density. [ABSTRACT FROM AUTHOR]

Stanley, J.-D. and Clemente, P.L., 2014. Mica and heavy minerals as markers to map Nile Delta coastline displacements during the Holocene. Mica and heavy minerals in sediments of Egypt's Nile Delta are examined to test if measured proportions of these two mineral groups and their distributions can be used to define former coastline positions and their shifts in time and space during the Holocene. The premise of the study is based on the sufficiently different attributes of these two components, especially their shape, density, and size, which could induce their segregation and dissimilar dispersal patterns during sediment transport. To test this hypothesis, mineralogical data from more than 1400 samples from 87 sediment cores recovered across the northern third of the delta margin were analyzed. The marked contrast in both temporal and spatial distributions of high proportions of mica and of heavy minerals indicates distinct separation occurred primarily north of the central delta, in an area from ∼45 km south of the present shoreline to ∼10-15 km offshore during the time span considered. Additionally, detailed examination of core sediment types demonstrates a relationship between the proportions of these two mineral groups and proportions of clay, silt, and sand fractions in which they occur near the present coast. Mica is preferentially deposited with silt and clay landward of the modern shore, while heavy mineral concentrations are generally associated with coarser silt and sand near and seaward of the shoreline. Shifts of the Nile Delta margin have been triggered by natural processes leading to insufficient sediment replenishment: relative sea-level rise involving delta plain subsidence and shoreline erosion, and intensified human activity, especially during the past two centuries, such as construction of dams, barrages, and entrapment by the delta's expanded canal system. The approach used here helps define two of the three major earlier Holocene coastal shifts, and it could be used to measure ongoing and future landward shoreline advances onto the delta plain. [ABSTRACT FROM AUTHOR]

Abstract: Soft computing techniques are recently becoming very popular in the oil industry. A number of computational intelligence-based predictive methods have been widely applied in the industry with high prediction capabilities. Some of the popular methods include feed-forward neural networks, radial basis function network, generalized regression neural network, functional networks, support vector regression and adaptive network fuzzy inference system. A comparative study among most popular soft computing techniques is presented using a large dataset published in literature describing multimodal pore systems in the Arab D formation. The inputs to the models are air porosity, grain density, and Thomeer parameters obtained using mercury injection capillary pressure profiles. Corrected air permeability is the target variable. Applying developed permeability models in recent reservoir characterization workflow ensures consistency between micro and macro scale information represented mainly by Thomeer parameters and absolute permeability. The dataset was divided into two parts with 80% of data used for training and 20% for testing. The target permeability variable was transformed to the logarithmic scale as a pre-processing step and to show better correlations with the input variables. Statistical and graphical analysis of the results including permeability cross-plots and detailed error measures were created. In general, the comparative study showed very close results among the developed models. The feed-forward neural network permeability model showed the lowest average relative error, average absolute relative error, standard deviations of error and root means squares making it the best model for such problems. Adaptive network fuzzy inference system also showed very good results. [Copyright &y& Elsevier]