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The expansion of agricultural frontiers has increased the use of sandy soils as cropping areas; however, the water‐retention capacity (WRC) of the soil is a crucial factor. Thus, fast and accurate methodologies, such as spectroscopy, have gained importance to identify physical‐hydric and other attributes related to the WRC. Some theories indicate the micromorphometry of particles is an important factor in sandy soils. This study (I) investigated the WRC of sandy soils from distinct geologic formations and the influence of particle micromorphometry on the WRC; (II) evaluated the sensitivity of Vis–NIR and MIR spectra to characterise physical‐hydric attributes and particle micromorphometry; and (III) quantified physical‐hydric attributes of sandy soils from their physical attributes, particle micromorphometric indices, and the visible‐near infrared‐mid infrared (Vis–NIR‐MIR) spectra. We determined the values of field capacity (FC), permanent wilting point (PWP), available water (AW), clay, sand, silt, sand fractions, and OM as well as the micromorphometric indices and Vis–NIR and MIR reflectance of 29 sandy soil profiles. Soil attributes were correlated with each other and with the Vis–NIR and MIR spectra to understand their relationship with the WRC. The correlation and the principal component analyses (PCA) were performed to understand the relationship between Vis–NIR and MIR spectra and sand grain micromorphometry. Mathematical models were developed to estimate FC, PWP, and AW using soil attributes, micromorphometry, Vis–NIR, and MIR as predictor variables. Roughness of sand particle greatly influenced the WRC of sandy soils. The MIR region showed high sensitivity to identify different WRC patterns and particle micromorphometry in sandy soils. The Vis–NIR and MIR spectra presented high accuracy to predict FC and PWP of sandy soils. The mathematical models that used soil attributes + micromorphometry presented excellent calibration parameters; however, they did not show accuracy in the validation set. Highlights: The influence of particle roughness on water retention of sandy soils was proven.Roughness had a greater influence on water retention than texture proportions for highly sandy soils.MIR spectra correlate strongly with the roughness of the very fine sand fraction.MIR spectra and roughness can estimate sandy soils water retention with high accuracy. [ABSTRACT FROM AUTHOR]

This publication deals with the influence of the roughnesses of single lithium‐nickel‐manganese‐cobalt‐oxide‐based active material particles on the electrochemical behaviour. A roughness model is used to create particles with a defined roughness depth. Subsequently, comparative calculations are performed using a 3D spatially resolved electrochemical model under different operating conditions. The results show that for small C‐rates below 1C, the usage of the widespread assumption of smooth and spherical active material particles in models is justified. For higher C‐rates, the particle's shape and roughness are not negligible. Small, rough particles show the best performance characteristics for high rate applications. For operation in the diffusion‐limited state (low diffusion coefficient and high C‐rate), the smallest absolute diffusion length represents a better correlation in terms of utilizable capacity compared to the volume‐specific active surface area. [ABSTRACT FROM AUTHOR]

Red-bed soft rock is a common type of bedrock with the characteristics of water softening and disintegration into particles. Micro mechanical properties and macro engineering behavior of softrock have been proven to be influenced by particle shape. Disintegration durability tests were conducted to study the durability of red-bed soft rocks, and two-dimensional images of disintegration particles with varied particle sizes under different dry–wet cycling states were obtained through optical imaging. Shape parameters of particles were established, and the sensitivity of shape parameters to rock durability were analyzed. The evolution behavior and durability differences of rock disintegration was better measured using the disintegration ratio instead of the traditional slake durability index. Results indicate that the aspect ratio and angularity of particles show a decreasing trend with an increasing number of dry–wet cycles, but roundness displays an increasing trend. The roughness decreases with increasing dry–wet cycles, but increases with decreasing particle size. Correlation between surface roughness and rock durability suggests that a higher roughness will enhance the disintegration of soft rock. And sensitivity analysis revealed that surface roughness with the highest grey relational grade of 0.705 is the optimal shape evaluation parameter for rock durability. Microscopic mechanism of surface roughness influencing rock durability was discussed, and the increase in surface area and stress concentration at contour turning points were considered two main factors that roughness affects the rock durability. Finally, the disintegration probability prediction based on renormalization group theory indicates that disintegration probabilities of the red-bed soft rock micro-unit models with triangular and square structures at critical states are 0.5 and 0.16, respectively. The significance of this study is to further investigate the relationship between the micro particle shape and macroscopic mechanical behavior of granular materials. • Shape evolution exhibits significant dry–wet cycling effect and size effect. • Surface roughness is the optimal parameter for evaluating durability. • Triangle and square structures of the micro-unit model were established. [ABSTRACT FROM AUTHOR]

Abstract: A new algorithm for calculating invariant shape descriptors was developed based on the Harmonic Wavelet technique. The algorithm requires the perimeter information from a shadow graph parameterized by length along the perimeter in Cartesian component, complex format. The algorithm returns a set of parameters which represent the net amplitude of a disturbance from a circular shape for features with length scales that fit in a narrow range of fractions of the total perimeter length relative to the major diameter of the particle. In pragmatic terms, the descriptors represent a quantitative measure of “roughness” on a variety of length scales that are smaller than the maximum measure of the particle. The descriptors are fully invariant to size, translation, rotation, and shift. Unlike other descriptor sets, one cannot reconstruct the original shape from these descriptors. However, the calculation time for these parameters is on the order of calculating Feret diameters and is about 11 times faster than calculating invariant FFT descriptors. The speed and quantitative measure allow for sampling of larger data sets which reduce uncertainty and allow for detection of small changes in bulk particle property with far greater statistical significance. The algorithm is also ideal for parallel processing. [Copyright &y& Elsevier]

Abstract: Surface area of volcanic ash particles is of great importance to research including plume dynamics, particle chemical and water reactions in the plume, modelling (i.e. plume shape, particle interactions, dispersion etc.), remote sensing of transport and SO2, HCl, H2O, CO2 levels, forecasting plume location, and transportation and deposition of ash particles. The implemented method presented in this study offers new insights for surface characterization of volcanic ash particles on macro-pore regions. Surface area and volumes of volcanic ash particles were measured using digital elevation models (DEM) reconstructed from stereoscopic images acquired from different angles by scanning electron microscope (SEM). The method was tested using glycidyl methacrylate (GMA) micro-spheres which exhibit low spherical imperfections. The differences between measured and geometrically calculated surface areas were introduced for both micro-spheres and volcanic ash particles in order to highlight the probable errors in modelling on volcanic ash behaviour. The specific surface areas of volcanic ash particles using this method are reduced by half (from mean values of 0.045m2/g to 0.021m2/g) for the size increment 63µm to 125µm. Ash particles mostly have higher specific surface area values than the geometric forms irrespective of particle size. The specific surface area trends of spheres and ash particles resemble for finer particles (63µm). Approximation to sphere and ellipsoid have similar margin of error for coarser particles (125µm) but both seem to be inadequate for representation of real ash surfaces. [Copyright &y& Elsevier]