Advice on describing Bayesian analysis of neutron and X-ray reflectometry

Epitaxial graphene growth on cubic silicon carbide on silicon with high temperature neutron reflectometry: an operando study

The growth of graphene on silicon carbide on silicon offers a very attractive route towards novel wafer-scale photonic and electronic devices that are easy to fabricate and can be integrated in silicon manufacturing. Using a Ni/Cu catalyst for the epitaxial growth of graphene has been successful in the mitigation of the very defective nature of the underlying silicon carbide on silicon, leading to a consistent graphene coverage over large scales. A more detailed understanding of this growth mechanism is warranted in order to further optimise the catalyst composition, preferably via the use of operando characterization measurements. Here, we report in situ neutron reflectometry measurements of (Ni, Cu)/SiC films on silicon wafers, annealed from room temperature to 1100 °C, which initiates graphene formation at the buried (Ni, Cu)/SiC interface. Detailed modelling of the high temperature neutron reflectometry and corresponding scattering length density profiles yield insights into the distinct physical mechanisms within the different temperature regimes. The initially smooth solid metallic layers undergo intermixing and roughening transitions at relatively low temperatures below 500 °C, and then metal silicides begin to form above 600 °C from interfacial reactions with the SiC, releasing atomic carbon. At the highest temperature range of 600-1100 °C, the low neutron scattering length density at high temperature is consistent with a silicon-rich, liquid surface phase corresponding to molten nickel silicides and copper. This liquid catalyst layer promotes the liquid-phase epitaxial growth of a graphene layer by precipitating the excess carbon available at the SiC/metal interface.

On the interactions between RNA and titrateable lipid layers: implications for RNA delivery with lipid nanoparticles

Characterising the interaction between cationic ionisable lipids (CIL) and nucleic acids (NAs) is key to understanding the process of RNA lipid nanoparticle (LNP) formation and release of NAs from LNPs. Here, we have used different surface techniques to reveal the effect of pH and NA type on the interaction with a model system of DOPC and the CIL DLin-MC3-DMA (MC3). At only 5% MC3, differences in the structure and dynamics of the lipid layer were observed. Both pH and %MC3 were shown to affect the absorption behaviour of erythropoietin mRNA, polyadenylic acid (polyA) and polyuridylic acid (polyU). The adsorbed amount of all studied NAs was found to increase with decreasing pH and increasing %MC3 but with different effects on the lipid layer, which could be linked to the NA secondary structure. For polyA at pH 6, adsorption to the surface of the layer was observed, whereas for other conditions and NAs, penetration of the NA into the layer resulted in the formation of a multilayer structure. By comparison to simulations excluding the secondary structure, differences in adsorption behaviours between polyA and polyU could be observed, indicating that the NA's secondary structure also affected the MC3-NA interactions.

Neutron reflection and scattering in characterising peptide assemblies

Self-assemblies of de novo designed short peptides at interface and in bulk solution provide potential platforms for developing applications in many medical and technological areas. However, characterising how bioinspired supramolecular nanostructures evolve with dynamic self-assembling processes and respond to different stimuli remains challenging. Neutron scattering technologies including small angle neutron scattering (SANS) and neutron reflection (NR) can be advantageous and complementary to other state-of-the-art techniques in tracing structural changes under different conditions. With more neutron sources now available, SANS and NR are becoming increasingly popular in studying self-assembling processes of diverse peptide and protein systems, but the difficulty in experimental manipulation and data analysis can deter beginners. This review will introduce the basic theory, general experimental setup and data analysis of SANS and NR, followed by provision of their applications in characterising interfacial and solution self-assemblies of representative peptides and proteins. SANS and NR are remarkably effective in determining the morphological features self-assembled short peptides, especially size and shape transitions as a result of either sequence changes or in response to environmental stimuli, demonstrating the unique capability of NR and SANS in unravelling the interactive processes. These examples highlight the potential of NR and SANS in supporting the development of novel short peptides and proteins as biopharmaceutical candidates in the fight against many diseases and infections that share common features of membrane interactive processes.

Advice on describing Bayesian analysis of neutron and X-ray reflectometry

As a result of the availability of modern software and hardware, Bayesian analysis is becoming more popular in neutron and X-ray reflectometry analysis. The understandability and replicability of these analyses may be harmed by inconsistencies in how the probability distributions central to Bayesian methods are represented in the literature. Herein advice is provided on how to report the results of Bayesian analysis as applied to neutron and X-ray reflectometry. This includes the clear reporting of initial starting conditions, the prior probabilities, the results of any analysis and the posterior probabilities that are the Bayesian equivalent of the error bar, to enable replicability and improve understanding. It is believed that this advice, grounded in the authors' experience working in the field, will enable greater analytical reproducibility in the work of the reflectometry community, and improve the quality and usability of results.