Distinguishing between Structural Models of β′-Sialons Using a Combined Solid-State NMR, Powder XRD, and Computational Approach

β′-Sialons (Si6–zAlzOzN8–z, where 0 ≤ z ≤ ∼4.2) are studied using a combination of 29Si and 27Al solid-state NMR, using magnetic fields of up to 20 T, powder X-ray diffraction, and density functional theory (DFT) calculations of both the structure and NMR parameters. Four different structural models have been proposed in the literature for the replacement of silicon and nitrogen by aluminum and oxygen within a β-Si3N4-structured lattice. Experimental data are presented for the variation with composition (z) of the unit cell parameters from diffraction and the local coordination units present suggested by NMR data. The experimental data are compared to the changes with composition in the DFT calculations of the structure and the NMR parameters according to the four models, allowing the models to be distinguished. It is shown that only one of these, the domain model, is fully consistent with all of the experimental data and is, therefore, a good structural model for β′-sialons. More speculatively, it is suggested that for the domain model, 27Al NMR data might provide a constraint on the thickness of its aluminum-rich layers

Improved Understanding of Atomic Ordering in Y4SixAl2- xO9- xNxMaterials Using a Combined Solid-State NMR and Computational Approach

Ceramics based around silicon aluminum oxynitrides are of both fundamental structural chemistry and technological interest. Certain oxynitride crystal structures allow very significant compositional variation through extensive Si/N exchange for Al/O, which implies a degree of atomic ordering. In this study, solid-state 29Si MAS NMR and variable field 1D and 2D 27Al MAS NMR measurements are combined with density functional theory calculations of both the structural and NMR interaction parameters for various points across the Y4Si2O7N2-Y4Al2O9 compositional range. This series provides numerous possibilities for significant variation of atomic ordering in the local ditetrahedral (Si,Al)2O7-xNx units. The two slightly structurally inequivalent aluminum sites in Y4Al2O9 are unambiguously assigned to the observed resonances. Computational findings on Y4Si2O7N2 demonstrate that the single observed 29Si NMR resonance covers a range of local inequivalent silicon environments. For the first time, the MAS NMR and neutron diffraction data from the Y4SiAlO8N structure have been directly reconciled, thus establishing aspects of atomic order and disorder that characterize this system. This comparison suggests that, although the diffraction data indicates long-range structural order supporting a highly crystalline character, the short-range information afforded by the solid-state NMR measurements indicates significant atomic disorder throughout the (Si,Al)2O7-xNx units

Porous silica-pillared MXenes with controllable interlayer distances for long-life Na-ion batteries

MXenes are a recently discovered class of two-dimensional materials that have shown great potential as electrodes in electrochemical energy storage devices. Despite their promise in this area, MXenes can still suffer limitations in the form of restricted ion accessibility between the closely spaced multistacked MXene layers, causing low capacities and poor cycle life. Pillaring, a strategy where a secondary species is inserted between layers, has been used to increase interlayer spacings in clays with great success, but has had limited application in MXenes. We report a new amine-assisted pillaring methodology that successfully intercalates silica-based pillars between Ti3C2 layers. Using this technique, the interlayer spacing can be controlled with the choice of amine and calcination temperature, up to a maximum of 3.2 nm, the largest interlayer spacing reported for an MXene. Another effect of the pillaring is a dramatic increase in surface area, achieving BET surface areas of 235 m2 g-1, a sixty-fold increase over the unpillared material and the highest reported for MXenes using an intercalation-based method. The intercalation mechanism was revealed by different characterisation techniques, allowing the surface chemistry to be optimised for the pillaring process. The porous MXene was tested for Na-ion battery applications, and showed superior capacity, rate capability and remarkable stability compared with non-pillared materials, retaining 98.5% capacity between the 50th and 100th cycles. These results demonstrate the applicability and promise of pillaring techniques applied to MXenes, providing a new approach to optimising their properties for a range of applications. Porous MXenes are very promising materials for a range of applications including energy storage, conversion, catalysis and gas separations

TRY plant trait database – enhanced coverage and open access

Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

A structural investigation of organic battery anode materials by NMR crystallography

Conjugated alkali metal dicarboxylates have recently received attention for applications as organic anode materials in lithium- and sodium-ion batteries. In order to understand and optimise these materials, it is important to be able to characterise both the long-range and local aspects of the crystal structure, which may change during battery cycling. Furthermore, some materials can display polymorphism or hydration behaviour. NMR crystallography, which combines long-range crystallographic information from diffraction with local information from solid-state NMR via interpretation aided by DFT calculations, is one such approach, but this has not yet been widely applied to conjugated dicarboxylates. In this work, we evaluate the application of NMR crystallography for a set of model lithium and sodium dicarboxylate salts. We investigate the effect of different DFT geometry optimisation strategies and find that the calculated NMR parameters are not systematically affected by the choice of optimisation method, although the inclusion of dispersion correction schemes is important to accurately reproduce the experimental unit cell parameters. We also observe hydration behaviour for two of the sodium salts and provide insight into the structure of an as-yet uncharacterised structure of sodium naphthalenedicarboxylate. This highlights the importance of sample preparation and characterisation for organic sodium-ion battery anode materials in particular

Pillared Mo2TiC2MXene for high-power and long-life lithium and sodium-ion batteries

In this work, we apply an amine-assisted silica pillaring method to create the first example of a porous Mo2TiC2MXene with nanoengineered interlayer distances. The pillared Mo2TiC2has a surface area of 202 m2g−1, which is among the highest reported for any MXene, and has a variable gallery height between 0.7 and 3 nm. The expanded interlayer distance leads to significantly enhanced cycling performance for Li-ion storage, with superior capacity, rate capably and cycling stability in comparison to the non-pillared analogue. The pillared Mo2TiC2achieved a capacity over 1.7 times greater than multilayered MXene at 20 mA g−1(≈320 mA h g−1) and 2.5 times higher at 1 A g−1(≈150 mA h g−1). The fast-charging properties of pillared Mo2TiC2are further demonstrated by outstanding stability even at 1 A g−1(under 8 min charge time), retaining 80% of the initial capacity after 500 cycles. Furthermore, we use a combination of spectroscopic techniques (i.e.XPS, NMR and Raman) to show unambiguously that the charge storage mechanism of this MXene occurs by a conversion reaction through the formation of Li2O. This reaction increases by 2-fold the capacity beyond intercalation, and therefore, its understanding is crucial for further development of this family of materials. In addition, we also investigate for the first time the sodium storage properties of the pillared and non-pillared Mo2TiC

Invited review: Determination of large-scale individual dry matter intake phenotypes in dairy cattle

Feed efficiency has been widely studied in many areas of dairy science and is currently seeing renewed interest in the field of breeding and genetics. A critical part of determining how efficiently an animal utilizes feed is accurately measuring individual dry matter (DM) intake. Currently, multiple methods are used to measure feed intake or determine the DM content of that feed, resulting in different levels of accuracy of measurement. Furthermore, the scale at which data need to be collected for use in genetic analyses makes some methodologies impractical. This systematic review aims to provide an overview of the current methodologies used to measure both feed intake in ruminants and DM content of feedstuffs, current methods to predict individual DM intake, and applications of large-scale intake measurements. Overall, advances in milk spectral data analysis present a promising method of estimating individual DM intake on a herd scale with further validation of prediction models. Although measurements of individual feed intake rely on the same underlying principle, the methods selected are largely dictated by the costs of capital, labor, and necessary analyses. Finally, DM methodologies were synthesized into a comprehensive protocol for use in a variety of feedstuffs.</p