A semi-empirical model relating flow properties to particle contacts in fine binary powder mixtures

Binary powder mixtures, consisting of large and small diameter particles, are used in electrophotographic (EP) printing devices where control of the relationship between the flow properties and mixing ratio is of great importance. In this study, we have experimentally investigated the bulk flow properties (i.e. bulk cohesion and internal friction) of large-and-small fine binary powder mixtures (size ratio: dl/ds = 9.17) as a function of the volume ratio of the smaller component, x_s. Using polymer spheres as the smaller constituents, whose bulk cohesion was controlled by surface additives, we have obtained systematic data on the effect of the smaller constituent. A semi-empirical model was then developed, in which the total bulk cohesion is expressed as a linear superposition of the numbers of the three types of particle–particle contacts (i.e. large–large, small–small, and large–small) involved in the shear motion. The model successfully reproduced the experimental data after fitting appropriate values of a parameter representing the adhesion at large–small particle contacts. The rapid increase of the number of particles involved in the shear motion as a function of x_s near x_s = 0 was also considered in the model. The model clarifies the contributions of the three types of particle–particle contacts to the total bulk flow properties. The effect of large–small particle contacts on the bulk cohesion was observed for almost all values of x_s. The value of x_s at which the contribution of large–small particle contacts in the total bulk cohesion becomes a maximum shifted in the direction of larger x_s when a less cohesive small powder was used. This also resulted in a shift of x_s at which the internal friction reached a minimum.This is the author's accepted manuscript. The final version is published by Elsevier in Powder Technology here: http://www.sciencedirect.com/science/article/pii/S003259101400713X

Managing uncertainty in data-derived densities to accelerate density functional theory

Faithful representations of atomic environments and general models for regression can be harnessed to learn electron densities that are close to the ground state. One of the applications of data-derived electron densities is to orbital-free density functional theory. However, extrapolations of densities learned from a training set to dissimilar structures could result in inaccurate results, which would limit the applicability of the method. Here, we show that a non-Bayesian approach can produce estimates of uncertainty which can successfully distinguish accurate from inaccurate predictions of electron density. We apply our approach to density functional theory where we initialise calculations with data-derived densities only when we are confident about their quality. This results in a guaranteed acceleration to self-consistency for configurations that are similar to those seen during training and could be useful for sampling based methods, where previous ground state densities cannot be used to initialise subsequent calculations

A quantitative comparison of in-line coating thickness distributions obtained from a pharmaceutical tablet mixing process using discrete element method and terahertz pulsed imaging

The application of terahertz pulsed imaging (TPI) in the in-line configuration to monitor the coating thickness distribution of pharmaceutical tablets has the potential to improve the performance and quality of the spray coating process. In this study, an in-line TPI method is used to measure coating thickness distributions on pre-coated tablets during mixing in a rotating pan, and compared with results obtained numerically using the discrete element method (DEM) combined with a ray-tracing technique. The hit rates (i.e. the number of successful coating thickness measurements per minute) obtained from both terahertz in-line experiments and the DEM/ray-tracing simulations are in good agreement, and both increase with the number of baffles in the mixing pan. We demonstrate that the coating thickness variability as determined from the ray-traced data and the terahertz in-line measurements represents mainly the intra-tablet variability due to relatively uniform mean coating thickness across tablets. The mean coating thickness of the ray-traced data from the numerical simulations agrees well with the mean coating thickness as determined by the off-line TPI measurements. The mean coating thickness of in-line TPI measurements is slightly higher than that of off-line measurements. This discrepancy can be corrected based on the cap-to-band surface area ratio of the tablet and the cap-to-band sampling ratio obtained from ray-tracing simulations: the corrected mean coating thickness of the in-line TPI measurements shows a better agreement with that of off-line measurements

Quantifying alignment in carbon nanotube yarns and similar two-dimensional anisotropic systems

Abstract: The uniaxial orientational order in a macromolecular system is usually specified using the Hermans factor which is equivalent to the second moment of the system's orientation distribution function (ODF) expanded in terms of Legendre polynomials. In this work, we show that for aligned materials that are two‐dimensional (2D) or have a measurable 2D intensity distribution, such as carbon nanotube (CNT) textiles, the Hermans factor is not appropriate. The ODF must be expanded in terms of Chebyshev polynomials and therefore, its second moment is a better measure of orientation in 2D. We also demonstrate that both orientation parameters (Hermans in three dimensional (3D) and Chebyshev in 2D) depend not only on the respective full‐width‐at‐half‐maximum of the peaks in the ODF but also on the shape of the fitted functions. Most importantly, we demonstrate a method to rapidly estimate the Chebyshev orientation parameter from a sample's 2D Fourier power spectrum, using an analysis program written in Python which is available for open access. As validation examples, we use digital photographs of dry spaghetti as well as scanning electron microscopy images of direct‐spun carbon nanotube fibers, proving the technique's applicability to a wide variety of fibers and images

Mechanical properties of carbon nanotube fibres: St Venant's principle at the limit and the role of imperfections

Carbon nanotube (CNT) fibres, especially if perfect in terms of purity and alignment, are of extreme anisotropy. With their high axial strength but ready slippage between the CNTs, there is utmost difficulty in transferring the force applied uniformly. Finite element analysis is used to predict the stress distribution in CNT fibres loaded by grips attached to their surface, along with the resulting tensile stress-strain curves. This study demonstrates that in accordance with St Venant’s principle very considerable length-to-diameter ratios (~ 103) are required before the stress becomes uniform across the fibre, even at low strains. It is proposed that lack of perfect orientation and presence of carbonaceous material between bundles greatly enhances the stress transfer, thus increasing the load it can carry before failing by shear. It is suggested that a very high strength batch of fibres previously observed experimentally had an unusually high concentration of internal particles, meaning that the pressure exerted by the grips would assist stress transfer between the layers. We conclude, that the strength of CNT fibres depends on the specific testing geometries and that imperfections, whether by virtue of less-than-perfect orientation or of embedded impurities, are actually major positive contributors to the observed strength.The authors are grateful to USN ONR GLOBAL for the provision of funding under award number N62909-14-1-N200. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the Office of Naval Research.This is the accepted manuscript. The final version is available at http://www.sciencedirect.com/science/article/pii/S0008622315004728

From Collisions to Bundles: An Adaptive Coarse-Grained Model for the Aggregation of High-Aspect-Ratio Carbon Nanotubes

We present an adaptive mesoscale model for carbon nanotube (CNT) systems. In our model, CNTs are represented as a chain of nodes connected by tensile and torsion springs to describe stretching and bending of the chain with intermolecular interactions being calculated using a mesoscopic Lennard-Jones potential. Computational adaptivity was achieved by dynamically adjusting node spacing and number during the simulation to optimise the number of simulated particles and lower computational effort. Adaptive simulations were up to five times faster than non-adaptive ones whilst quantitatively preserving all system dynamics. In particular, the model enables the study of the timescale of CNT bundling that leads to the formation of dilute CNT networks, so-called aerogels. These aerogels constitute the first step in the direct spinning of CNT fibres from chemical vapour deposition synthesis. Understanding the factors governing CNT bundling and network formation is key to controlling CNT fibre microstructure, and therefore optimising their properties. Using the model, we simulated the bundling dynamics of two CNTs with an initial point contact at varying angles for CNT lengths of up to 10 µm. We find that bundling times are an increasing function of initial collision angle and follow a power law with increasing CNT length that range from 10−1 to 103 ns. We postulate that when this bundling time becomes of the same order as the CNT bundle collision time, the aerogel will form.EPSRC: EP/M015211/1, EP/P020259/

Mapping the parameter space for direct-spun carbon nanotube aerogels

Industrial-scale use of carbon nanotube (CNT) materials and prototype development is limited by availability of economic, high throughput production methods. Recent investigations have demonstrated the feasibility of producing direct-spun macroscopic CNT materials via floating catalyst chemical vapour deposition. However, few quantitative results have been reported regarding process yield and correlations with product quality. Validation of results is therefore challenging as identification of the key fundamental process parameters is hindered. This first meta-analysis quantifies atomic input rates and correlates them with product outputs to map the current parameter space of 55 successful conditions leading to spinnable aerogels. All mapped processes fall within a bulk residence time of 5–240 s, operating temperature of 1100–1500°C and an atomic S:Fe of 0.1–10. Low (high) S/Fe ratios favour single (multi)-wall CNTs in the direct-spun product. A high atomic carbon dilution, only 3% of the input atoms being C, is a common feature across many systems. Furthermore, we connect the findings to known catalyst and product growth behaviour, as well as the thermodynamics of intermediates, to create an emerging picture of direct-spun CNT product formation. Elucidation of the most important factors influencing material synthesis, and the relationships between them, provides opportunities for gains in industrial-scale synthesi

Mesoscale simulations of confined Nafion thin films.

The morphology and transport properties of thin films of the ionomer Nafion, with thicknesses on the order of the bulk cluster size, have been investigated as a model system to explain the anomalous behaviour of catalyst/electrode-polymer interfaces in membrane electrode assemblies. We have employed dissipative particle dynamics (DPD) to investigate the interaction of water and fluorocarbon chains, with carbon and quartz as confining materials, for a wide range of operational water contents and film thicknesses. We found confinement-induced clustering of water perpendicular to the thin film. Hydrophobic carbon forms a water depletion zone near the film interface, whereas hydrophilic quartz results in a zone with excess water. There are, on average, oscillating water-rich and fluorocarbon-rich regions, in agreement with experimental results from neutron reflectometry. Water diffusivity shows increasing directional anisotropy of up to 30% with decreasing film thickness, depending on the hydrophilicity of the confining material. A percolation analysis revealed significant differences in water clustering and connectivity with the confining material. These findings indicate the fundamentally different nature of ionomer thin films, compared to membranes, and suggest explanations for increased ionic resistances observed in the catalyst layer

An integrative view of mammalian seasonal neuroendocrinology

This is the peer reviewed version of the following article: Dardente, H., Wood, S.H., Ebling, F. & Sáenz de Miera, C. (2019). An integrative view of mammalian seasonal neuroendocrinology. Journal of neuroendocrinology. Journal of Neuroendocrinology, 31(5), e12729, which has been published in final form at https://doi.org/10.1111/jne.12729. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions.Seasonal neuroendocrine cycles that govern annual changes in reproductive activity, energy metabolism and hair growth are almost ubiquitous in mammals that have evolved at temperate and polar latitudes. Changes in nocturnal melatonin secretion regulating gene expression in the pars tuberalis (PT) of the pituitary stalk are a critical common feature in seasonal mammals. The PT sends signal(s) to the pars distalis of the pituitary to regulate prolactin secretion and thus the annual moult cycle. The PT also signals in a retrograde manner via thyroid‐stimulating hormone to tanycytes, which line the ventral wall of the third ventricle in the hypothalamus. Tanycytes show seasonal plasticity in gene expression and play a pivotal role in regulating local thyroid hormone (TH) availability. Within the mediobasal hypothalamus, the cellular and molecular targets of TH remain elusive. However, two populations of hypothalamic neurones, which produce the RF‐amide neuropeptides kisspeptin and RFRP3 (RF‐amide related peptide 3), are plausible relays between TH and the gonadotrophin‐releasing hormone‐pituitary‐gonadal axis. By contrast, the ways by which TH also impinges on hypothalamic systems regulating energy intake and expenditure remain unknown. Here, we review the neuroendocrine underpinnings of seasonality and identify several areas that warrant further research

Multi-scale modelling of carbon nanotube reinforced crosslinked interfaces

In this paper, we study the crosslinking route and interfacial interactions for achieving superior properties in carbon nanotube (CNT)-reinforced epoxy-based nanocomposites by using multi-scale modelling. For that purpose, polymeric epoxy matrices consisting of EPON 862 epoxy and TETA hardener molecules were coarse-grained and simulated using the dissipative particle dynamics (DPD) method. Furthermore, CNTs were coarse-grained as rigid rods and embedded into the uncrosslinked mesoscopic polymer system. Reverse-mapping of the atomistic details onto the coarse-grained models was carried out to allow further simulations at the atomistic scale using molecular dynamics (MD) while keeping the periodicity of the CNTs’ structure. The mechanism of crosslinking was simulated, and both neat and CNT-reinforced thermoset nanocomposites with different degrees of crosslinking were reconstructed. Normal stresses in both tensile and compressive loading directions (up to 0.2% strain) were calculated, and the yield strength (at 0.2% offset) and compressive/elastic modulus in both normal directions are reported, which match well with experimental values. Overall, this paper explores a fast and straightforward procedure to bridge periodic mesoscopic structures, such as CNTs and their nanocomposites, to experimentally tested material properties