Solid electrolytes for all-solid-state batteries are generating remarkable research interest as a means to improve the safety, stability and performance of rechargeable batteries. Solid electrolytes are often polycrystalline and the effect that grain boundaries have on the material properties is often not fully characterised. Here, we present a comprehensive molecular dynamics study that quantifies the effect of grain boundaries on Li-ion transport in perovskite Li3xLa(2/3)−xTiO3 (0 < x < 0.16) (LLTO). Our results predict that grain boundaries hinder Li-ion conductivity by 1 to 2 orders of magnitude compared to the bulk. We attribute the poor Li-ion conductivity of the grain boundaries to significant structural alterations at the grain boundaries. Our detailed analysis provides important insight into the influence of grain boundary structure on transport of Li-ions in solid electrolyte materials.
Nanomaterials, with potential application as bio-medicinal agents, exploit the chemical properties of a solid, with the ability to be transported (like a molecule) to a variety of bodily compartments. However, the chemical environment can change significantly the structure and hence properties of a nanomaterial. Accordingly, its surface reactivity is critically dependent upon the nature of the (biological) environment in which it resides. Here, we use Molecular Dynamics (MD) simulation, Density Functional Theory (DFT) and aberration corrected TEM to predict and rationalise differences in structure and hence surface reactivity of ceria nanoparticles in different environments. In particular we calculate reactivity ‘fingerprints’ for unreduced and reduced ceria nanoparticles immersed in water and in vacuum. Our simulations predict higher activities of ceria nanoparticles, towards oxygen release, when immersed in water because the water quenches the coordinative unsaturation of surface ions. Conversely, in vacuum, surface ions relax into the body of the nanoparticle to relieve coordinative unsaturation, which increases the energy barriers associated with oxygen release. Our simulations also reveal that reduced ceria nanoparticles are more active towards surface oxygen release compared to unreduced nanoceria. In parallel, experiment is used to explore the activities of ceria nanoparticles that have suffered a change in environment. In particular, we compare the ability of ceria nanoparticles, in an aqueous environment, to scavenge superoxide radicals compared to the same batch of nanoparticles, which have first been dried and then rehydrated. The latter show a distinct reduction in activity, which we correlate to a change in the redox chemistry associated with moving between different environments. The reactivity of ceria nanoparticles is therefore not only environment dependent, but is also influenced by the transport pathway or history required to reach the particular environment in which its reactivity is to be exploited.
Novel sensing technologies for liquid biopsies offer promising prospects for the early detection of metabolic conditions through omics techniques. Indeed, high-field nuclear magnetic resonance (NMR) facilities are routinely used for metabolomics investigations on a range of biofluids in order to rapidly recognise unusual metabolic patterns in patients suffering from a range of diseases. However, these techniques are restricted by the prohibitively large size and cost of such facilities, suggesting a possible role for smaller, low-field NMR instruments in biofluid analysis. Herein we describe selected biomolecule validation on a low-field benchtop NMR spectrometer (60 MHz), and present an associated protocol for the analysis of biofluids on compact NMR instruments. We successfully detect common markers of diabetic control at low-to-medium concentrations through optimised experiments, including α-glucose (≤2.8 mmol/L) and acetone (25 µmol/L), and additionally in readily accessible biofluids, particularly human urine. We present a combined protocol for the analysis of these biofluids with low-field NMR spectrometers for metabolomics applications, and offer a perspective on the future of this technique appealing to ‘point-of-care’ applications.