refnx: neutron and X-ray reflectometry analysis in Python

HIV and influenza fusion peptide interactions with (dis)ordered lipid bilayers: Understanding mechanisms and implications for antimicrobial and antiviral approaches

The interactions of viral fusion peptides from influenza (E4K and Ac-E4K) and human immunodeficiency virus (gp41 and Ac-gp41) with planar lipid bilayers and monolayers was investigated herein. A combination of surface-sensitive techniques, including quartz crystal microbalance with dissipation (QCM-D), Langmuir-Blodgett area-pressure isotherms with Micro-Brewster angle microscopy, and neutron reflectometry, was employed. Differences in the interactions of the viral fusion peptides with lipid bilayers featuring ordered and disordered phases, as well as lipid rafts, were revealed. The HIV fusion peptide (gp41) exhibited strong binding to the DOPC/DOPS bilayer, comprising a liquid disordered phase, with neutron reflectometry (NR) showing interaction with the bilayer's headgroup area. Conversely, negligible binding was observed with lipid bilayers in a liquid ordered phase. Notably, the influenza peptide (E4K) demonstrated slower binding kinetics with DOPC/DOPS bilayers and distinct interactions compared to gp41, as observed through QCM-D. This suggests different mechanisms of interaction with the lipid bilayers: one peptide interacts more within the headgroup region, while the other is more involved in transmembrane interactions. These findings hold implications for understanding viral fusion mechanisms and developing antimicrobials and antivirals targeting membrane interactions. The differential binding behaviours of the viral fusion peptides underscore the importance of considering membrane composition and properties in therapeutic strategy design.

Illuminating the nanostructure of diffuse interfaces: Recent advances and future directions in reflectometry techniques

Diffuse soft matter interfaces take many forms, from end-tethered polymer brushes or adsorbed surfactants to self-assembled layers of lipids. These interfaces play crucial roles across a multitude of fields, including materials science, biophysics, and nanotechnology. Understanding the nanostructure and properties of these interfaces is fundamental for optimising their performance and designing novel functional materials. In recent years, reflectometry techniques, in particular neutron reflectometry, have emerged as powerful tools for elucidating the intricate nanostructure of soft matter interfaces with remarkable precision and depth. This review provides an overview of selected recent developments in reflectometry and their applications for illuminating the nanostructure of diffuse interfaces. We explore various principles and methods of neutron and X-ray reflectometry, as well as ellipsometry, and discuss advances in their experimental setups and data analysis approaches. Improvements to experimental neutron reflectometry methods have enabled greater time resolution in kinetic measurements and elucidation of diffuse structure under shear or confinement, while innovation in analysis protocols has significantly reduced data processing times, facilitated co-refinement of reflectometry data from multiple instruments and provided greater-than-ever confidence in proposed structural models. Furthermore, we highlight some significant research findings enabled by these techniques, revealing the organisation, dynamics, and interfacial phenomena at the nanoscale. We also discuss future directions and potential advancements in reflectometry techniques. By shedding light on the nanostructure of diffuse interfaces, reflectometry techniques enable the rational design and tailoring of interfaces with enhanced properties and functionalities.

Stability Enhancement by Hydrophobic Anchoring and a Cross-Linked Structure of a Phospholipid Copolymer Film for Medical Devices

Surface modification using zwitterionic 2-methacryloyloxyethylphosphorylcholine (MPC) polymers is one of the most reasonable ways to prepare medical devices that can suppress undesired biological reactions such as blood coagulation. Usable MPC polymers are hydrophilic and water soluble, and their surface modification strategy involves exploiting the copolymer structures by adding physical or chemical bonding moieties. In this study, we developed copolymers composed of MPC, hydrophobic anchoring moiety, and chemical cross-linking unit to clarify the role of hydrophobic interactions in achieving biocompatible and long-term stable coatings. The four kinds of MPC copolymers with cross-linking units, such as 3-methacryloxypropyl trimethoxysilane (MPTMSi), and four different hydrophobic anchoring moieties, such as 3-(methacryloyloxy)propyltris(trimethylsiloxy)silane (MPTSSi) named as PMMMSi, n-butyl methacrylate (BMA) as PMBSi, 2-ethylhexyl methacrylate (EHMA) as PMESi, and lauryl methacrylate as PMLSi, were synthesized and coated on polydimethylsiloxane, polypropylene (PP), and polymethyl pentene. These copolymers were uniformly coated on the substrate materials PP and poly(methyl pentene) (PMP), to achieve hydrophilic and electrically neutral coatings. The results of the antibiofouling test showed that PMBSi repelled the adsorption of fluorescence-labeled bovine serum albumin the most, whereas PMLSi repelled it the least. Notably, all four copolymers suppressed platelet adhesion similarly. The variations in protein adsorption quantities among the four copolymer coatings were attributed to their distinct swelling behaviors in aqueous environments. Further investigations, including 3D scanning force microscopy and neutron reflectivity measurements, revealed that the PMLSi coating exhibited a higher water intake under aqueous conditions in comparison to the other coatings. Consequently, all copolymer coatings effectively prevented the invasion of platelets but the proteins penetrated the PMLSi network. Subsequently, the dynamic stability required to induce shear stress was evaluated using a circulation system. The results demonstrated that the PMMMSi and PMLSi coatings on PMP and PP exhibited exceptional platelet repellency and maintained high stability during circulation. This study highlights the potential of hydrophobic moieties to improve hemocompatibility and stability, offering potential applications in medical devices.

Arginine catabolism is essential to polymyxin dependence in Acinetobacter baumannii

Polymyxins are often the only effective antibiotics against the "Critical" pathogen Acinetobacter baumannii. Worryingly, highly polymyxin-resistant A. baumannii displaying dependence on polymyxins has emerged in the clinic, leading to diagnosis and treatment failures. Here, we report that arginine metabolism is essential for polymyxin-dependent A. baumannii. Specifically, the arginine degradation pathway was significantly altered in polymyxin-dependent strains compared to wild-type strains, with critical metabolites (e.g., L-arginine and L-glutamate) severely depleted and expression of the astABCDE operon significantly increased. Supplementation of arginine increased bacterial metabolic activity and suppressed polymyxin dependence. Deletion of astA, the first gene in the arginine degradation pathway, decreased phosphatidylglycerol and increased phosphatidylethanolamine levels in the outer membrane, thereby reducing the interaction with polymyxins. This study elucidates the molecular mechanism by which arginine metabolism impacts polymyxin dependence in A. baumannii, underscoring its critical role in improving diagnosis and treatment of life-threatening infections caused by "undetectable" polymyxin-dependent A. baumannii.

Additive roles of antiferromagnetically coupled elements in the magnetic proximity effect in the GdFeCo/Pt system

Interfacial magnetic interactions between different elements are the origin of various spin-transport phenomena in multi-elemental magnetic systems. We investigate the coupling between the magnetic moments of the rare-earth, transition-metal, and heavy-metal elements across the interface in a GdFeCo/Pt thin film, an archetype system to investigate ferrimagnetic spintronics. The Pt magnetic moments induced by the antiferromagnetically aligned FeCo and Gd moments are measured using element-resolved x-ray measurements. It is revealed that the proximity-induced Pt magnetic moments are always aligned parallel to the FeCo magnetic moments, even below the ferrimagnetic compensation temperature where FeCo has a smaller moment than Gd. This is understood by a theoretical model showing distinct effects of the rare-earth Gd 4f and transition-metal FeCo 3d magnetic moments on the Pt electronic states. In particular, the Gd and FeCo work in-phase to align the Pt moment in the same direction, despite their antiferromagnetic configuration. The unexpected additive roles of the two antiferromagnetically coupled elements exemplify the importance of detailed interactions among the constituent elements in understanding magnetic and spintronic properties of thin film systems.

Studying Transient Phenomena in Thin Films with Reinforcement Learning

Neutron reflectometry has long been a powerful tool to study the interfacial properties of energy materials. Recently, time-resolved neutron reflectometry has been used to better understand transient phenomena in electrochemical systems. Those measurements often comprise a large number of reflectivity curves acquired over a narrow q range, with each individual curve having lower information content compared to a typical steady-state measurement. In this work, we present an approach that leverages existing reinforcement learning tools to model time-resolved data to extract the time evolution of structure parameters. By mapping the reflectivity curves taken at different times as individual states, we use the Soft Actor-Critic algorithm to optimize the time series of structure parameters that best represent the evolution of an electrochemical system. We show that this approach constitutes an elegant solution to the modeling of time-resolved neutron reflectometry data.

Lamellar Microphase Separation and Phase Transition of Hydrogen-Bonding/Crystalline Statistical Copolymers: Amide Functionalization at the Interface

Microphase separation of random copolymers, as well as that of high χ-low N block copolymers, is promising to construct sub-10-nm structures into materials. Herein, we designed statistical copolymers consisting of 2-hydroxyethyl acrylate (HEA) and N-octadecylacrylamide (ODAAm) to produce crystallization and hydrogen bond-assisted lamellar structure materials. The copolymers not only formed a crystalline lamellar structure with 3-4 nm domain spacing but also maintained an amorphous lamellar structure via phase transition above the melting temperature up to approximately 100 °C. The key is to introduce hydrogen-bonding amide junctions between the octadecyl groups and the polymer backbones, by which the polymer chains are physically fixed at the interface of lamellar structures even above the melting temperature. The stabilization of the lamellar structure by the amide units is also supported by the fact that the lamellar structure of all-acrylate random copolymers bearing hydroxyethyl and crystalline octadecyl groups is disordered above the melting temperature. By spin-coating on a silicon substrate, the HEA/ODAAm copolymer formed a multilayered lamellar thin film consisting of a hydrophilic hydroxyethyl/main chain phase and a hydrophobic octadecyl phase. The structure and order-disorder transition were analyzed by neutron reflectivity.

Neural network analysis of neutron and X-ray reflectivity data incorporating prior knowledge

Due to the ambiguity related to the lack of phase information, determining the physical parameters of multilayer thin films from measured neutron and X-ray reflectivity curves is, on a fundamental level, an underdetermined inverse problem. This ambiguity poses limitations on standard neural networks, constraining the range and number of considered parameters in previous machine learning solutions. To overcome this challenge, a novel training procedure has been designed which incorporates dynamic prior boundaries for each physical parameter as additional inputs to the neural network. In this manner, the neural network can be trained simultaneously on all well-posed subintervals of a larger parameter space in which the inverse problem is underdetermined. During inference, users can flexibly input their own prior knowledge about the physical system to constrain the neural network prediction to distinct target subintervals in the parameter space. The effectiveness of the method is demonstrated in various scenarios, including multilayer structures with a box model parameterization and a physics-inspired special parameterization of the scattering length density profile for a multilayer structure. In contrast to previous methods, this approach scales favourably when increasing the complexity of the inverse problem, working properly even for a five-layer multilayer model and a periodic multilayer model with up to 17 open parameters.

Millisecond X-ray reflectometry and neural network analysis: unveiling fast processes in spin coating

X-ray reflectometry (XRR) is a powerful tool for probing the structural characteristics of nanoscale films and layered structures, which is an important field of nanotechnology and is often used in semiconductor and optics manufacturing. This study introduces a novel approach for conducting quantitative high-resolution millisecond monochromatic XRR measurements. This is an order of magnitude faster than in previously published work. Quick XRR (qXRR) enables real time and in situ monitoring of nanoscale processes such as thin film formation during spin coating. A record qXRR acquisition time of 1.4 ms is demonstrated for a static gold thin film on a silicon sample. As a second example of this novel approach, dynamic in situ measurements are performed during PMMA spin coating onto silicon wafers and fast fitting of XRR curves using machine learning is demonstrated. This investigation primarily focuses on the evolution of film structure and surface morphology, resolving for the first time with qXRR the initial film thinning via mass transport and also shedding light on later thinning via solvent evaporation. This innovative millisecond qXRR technique is of significance for in situ studies of thin film deposition. It addresses the challenge of following intrinsically fast processes, such as thin film growth of high deposition rate or spin coating. Beyond thin film growth processes, millisecond XRR has implications for resolving fast structural changes such as photostriction or diffusion processes.

Hysteresis in phase volumes, compositions and interfacial roughness in model OPV-small-molecule/polymer thin-films

Domain morphology and composition, and the structure of interfaces between domains are key factors in the performance and stability of organic photovoltaics (OPVs) fabricated from polymer/small-molecule blends. In this study, we investigate the evolution of composition, phase-volume and interfacial roughness in model polymer/small-molecule bilayers, in response to thermal annealing. Polystyrene/fullerene mixing is studied as a function of annealing temperature, using in situ neutron reflectivity, in thin-film bilayer samples comprising pure component or mixed layers. Remarkably, we discover that thermal annealing at temperatures around or above the reported glass transition temperatures, Tg, of the components can result in extensive mass-transfer between layers, that has the superficial appearance of equilibration, but leaves the layer compositions, thicknesses, and/or the interfacial composition profile in a non-equilibrium state. This is not merely a case of slow kinetics near Tg, as subsequent heating to higher temperatures, followed by cooling, reveals pronounced hysteresis in these systems. This has important implications for the measurement of equilibrium compositions in polymer/small-molecule mixtures for OPV applications, and for device stability during operation.

Planar Polymer Membranes Accommodate Functional Self-Assembly of Inserted Resorcinarene Nanocapsules

Solid-supported polymer membranes (SSPMs) offer great potential in material and life sciences due to their increased mechanical stability and robustness compared to solid-supported lipid membranes. However, there is still a need for expanding the functionality of SSPMs by combining them with synthetic molecular assemblies. In this study, SSPMs served as a flexible matrix for the insertion of resorcinarene monomers and their self-assembly into functional hexameric resorcinarene capsules. Resorcinarene capsules provide a large cavity with affinity specifically for cationic and polyhydroxylated molecules. While the capsules are stable in apolar organic solvents, they disassemble when placed in polar solvents, which limits their application. Here, a solvent-assisted approach was used for copolymer membrane deposition on solid support and simultaneous insertion of the resorcinarene monomers. By investigation of the molecular factors and conditions supporting the codeposition of the copolymer and resorcinarene monomers, a stable hybrid membrane was formed. The hydrophobic domain of the membrane played a crucial role by providing a sufficiently thick and apolar layer, allowing for the self-assembly of the capsules. The capsules were functional inside the membranes by encapsulating cationic guests from the aqueous environment. The amount of resorcinarene capsules in the hybrid membranes was quantified by a combination of quartz-crystal microbalance with dissipation and liquid chromatography-mass spectrometry, while the membrane topography and layer composition were analyzed by atomic force microscopy and neutron reflectometry. Functional resorcinarene capsules inside SSPMs can serve as dynamic sensors and potentially as cross-membrane transporters, thus holding great promise for the development of smart surfaces.

Polysaccharide-Targeting Lipid Nanoparticles to Kill Gram-Negative Bacteria

The rapid increase and spread of Gram-negative bacteria resistant to many or all existing treatments threaten a return to the preantibiotic era. The presence of bacterial polysaccharides that impede the penetration of many antimicrobials and protect them from the innate immune system contributes to resistance and pathogenicity. No currently approved antibiotics target the polysaccharide regions of microbes. Here, describe monolaurin-based niosomes, the first lipid nanoparticles that can eliminate bacterial polysaccharides from hypervirulent Klebsiella pneumoniae, are described. Their combination with polymyxin B shows no cytotoxicity in vitro and is highly effective in combating K. pneumoniae infection in vivo. Comprehensive mechanistic studies have revealed that antimicrobial activity proceeds via a multimodal mechanism. Initially, lipid nanoparticles disrupt polysaccharides, then outer and inner membranes are destabilized and destroyed by polymyxin B, resulting in synergistic cell lysis. This novel lipidic nanoparticle system shows tremendous promise as a highly effective antimicrobial treatment targeting multidrug-resistant Gram-negative pathogens.

Structure of graphene oxide-phospholipid monolayers: A grazing incidence X-ray diffraction and neutron and X-ray reflectivity study

HYPOTHESIS

Graphene oxide-based nanotechnology has aroused a great interest due to its applications in the biomedical and optoelectronic fields. The wide use of these materials makes it necessary to study its potential toxicity associated with the inhalation of Graphene Oxide (GO) nanoparticles and its interaction with the lung surfactant. Langmuir monolayers have proven to be an excellent tool for studying the properties of the lung surfactant and the effect of intercalation of nanoparticles on its structure and properties. Therefore, to know the origin of the phospholipids/GO interaction and the structure of the lipid layer with GO, in this work we study the effect of the insertion of GO sheets on a Langmuir film of 1,2-Dipalmitoyl-sn-glycerol-3-phosphocholine (DPPC).

EXPERIMENTS

Surface pressure-area isotherms, Neutron (NR) and X-ray Reflectivity (XRR) and Grazing Incidence X-ray Diffraction (GIXD) measurements of hydrogenated and deuterated DPPC monolayers with and without GO have been carried out.

FINDINGS

The results outline a strong interaction between the GO and the zwitterionic form of DPPC and prove that GO is in three regions of the DPPC monolayer, the aliphatic chains of DPPC, the head groups and water in the subphase. Comparison between results obtained with hydrogenated and deuterated DPPC allows concluding that both, electrostatic attractions, and dispersion forces are responsible of the interaction GO/DPPC. Results also demonstrated that the insertion of GO into the DPPC aliphatic chains does not induce significant changes on unit cell of DPPC.

Comparing polymer-surfactant complexes to polyelectrolytes

HYPOTHESIS

Understanding the complex interactions between polymers and surfactants is required to optimise commercially relevant systems such as paint, toothpaste and detergent. Neutral polymers complex with surfactants, forming 'pearl necklace' structures that are often conceptualised as pseudo-polyelectrolytes. Here we pose two questions to test the limits of this analogy: Firstly, in the presence of salt, do these polymer-surfactant systems behave like polyelectrolytes? Secondly, do polymer-surfactant complexes resist geometric confinement like polyelectrolytes?

EXPERIMENTS

We test the limits of the pseudo-polyelectrolyte analogy through studying a poly(N-isopropylacrylamide) (PNIPAM) brush in the presence of sodium dodecylsulfate (SDS). Brushes are ideal for interrogating pseudo-polyelectrolytes, as neutral and polyelectrolyte brushes exhibit distinct and well understood behaviours. Spectroscopic ellipsometry, quartz crystal microbalance with dissipation monitoring (QCM-D), and neutron reflectometry (NR) were used to monitor the behaviour and structure of the PNIPAM-SDS system as a function of NaCl concentration. The ability of the PNIPAM-SDS complex to resist geometric confinement was probed with NR.

FINDINGS

At a fixed SDS concentration below the zero-salt CMC, increasing NaCl concentration <100 mM promoted brush swelling due to an increase in osmotic pressure, not dissimilar to a weak polyelectrolyte. At these salt concentrations, the swelling of the brush could be described by a single parameter: the effective CMC. However, at high NaCl concentrations (e.g., 500 mM) no brush collapse was observed at all (non-zero) concentrations of SDS studied, contrary to what is seen for many polyelectrolytes. Study of the polymer-surfactant system under confinement revealed that the physical volume of surfactant dominates the structure of the strongly confined system, which further differentiates it from the polyelectrolyte case.

Experimental and simulation study of self-assembly and adsorption of glycerol monooleate in n-dodecane with varying water content onto iron oxide

The self-assembly and surface adsorption of glycerol monooleate (GMO) in n-dodecane are studied using a combination of experimental and molecular dynamics simulation techniques. The self-assembly of GMO to form reverse micelles, with and without added water, is studied using small-angle neutron scattering and simulations. A large-scale simulation is also used to investigate the self-assembly kinetics. GMO adsorption onto iron oxide is studied using depletion isotherms, neutron reflectometry, and simulations. The adsorbed amounts of GMO, and any added water, are determined experimentally, and the structures of the adsorbed films are investigated using reflectometry. Detailed fitting and analysis of the reflectometry measurements are presented, taking into account various factors such as surface roughness, and the presence of impurities. The reflectometry measurements are complemented by molecular dynamics simulations, and good consistency between both approaches is demonstrated by direct comparison of measured and simulated reflectivity and scattering length density profiles. The results of this analysis are that in dry systems, GMO adsorbs as self-assembled reverse micelles with some molecules adsorbing directly to the surface through the polar head groups, while in wet systems, the GMO is adsorbed onto a thin layer of water. Only at high surface coverage is some water trapped inside a reverse-micelle structure; at lower surface coverages, the GMO molecules associate primarily with the water layer, rather than self-assemble.

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.

Solvent-Modulated Specific Ion Effects: Poly(N-isopropylacrylamide) Brushes in Nonaqueous Electrolytes

Pertinent to cryopreservation as well as energy storage and batteries, nonaqueous electrolytes and their mixtures with water were investigated. In particular, specific ion-induced effects on the modulation of a poly(N-isopropylacrylamide) (PNIPAM) brush were investigated in various dimethyl sulfoxide (DMSO)-water solvent mixtures. Spectroscopic ellipsometry and neutron reflectometry were employed to probe changes in brush swelling and structure, respectively. In water-rich solvents (i.e., pure water and 6 mol % DMSO), PNIPAM undergoes a swollen to collapsed thermotransition with increasing temperature, whereby a forward Hofmeister series was noted; K+ and Li+ electrolytes composed of SCN- and I- salted-in (stabilized) PNIPAM chains, and electrolytes of Cl- and Br- salted-out (destabilized) the polymer. The cation was seen to play a lesser role than that of the anion, merely modulating the magnitude of the anion effect. In 70 mol % DMSO, a collapsed to swollen thermotransition was noted for PNIPAM. Here, concentration-dependent specific ion effects were observed; a forward series was observed in 0.2 mol % electrolytes, whereas increasing the electrolyte concentration to 0.9 mol % led to a series reversal. While no thermotransition was observed in pure DMSO, a solvent-induced specific ion series reversal was noted; SCN- destabilized the brush and Cl- stabilized the brush. Both series reversals are attributed to the delicate balance of interactions between the solvent, solute (ion), and substrate (brush). Namely, the stability of the solvent clusters was hypothesized to drive polymer solvation.

Galinstan Liquid Metal Electrical Contacts for Monolayer-Modified Silicon Surfaces

Galinstan is the brand name for a low-melting gallium-based alloy, which is a promising nontoxic alternative to mercury, the only elemental metal found in the liquid state at room temperature. Liquid alloys such as Galinstan have found applications as electromechanical actuators, sensors, and soft contacts for molecular electronics. In this work, we validate the scope of Galinstan top contacts to probe the electrical characteristics of Schottky junctions made on Si(111) and Si(211) crystals modified with Si-C-bound organic monolayers. We show that the surface-to-volume ratio of the Galinstan drop used as a macroscopic contact defines the junction stability. Further, we explore chemical strategies to increase Galinstan surface tension to obtain control over the junction area, hence improving the repeatability and reproducibility of current-voltage (I-V) measurements. We explore Galinstan top contacts as a means to monitor changes in rectification ratios caused by surface reactions and use these data, most notably the static junction leakage, toward making qualitative predictions on the DC outputs recorded when these semiconductor systems are incorporated in Schottky-based triboelectric nanogenerators. We found that the introduction of iron particles leads to poor data repeatability for capacitance-voltage (C-V) measurements but has only a small negative impact in a dynamic current measurement (I-V).

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.

Triglyceride-Tethered Membrane Lipase Sensor

Sensors that can quickly measure the lipase activity from biological samples are useful in enzyme production and medical diagnostics. However, current lipase sensors have limitations such as requiring fluorescent labels, pH control of buffer vehicles, or lengthy assay preparation. We introduce a sparsely tethered triglyceride substrate anchored off of a gold electrode for the impedance sensing of real-time lipase activity. The tethered substrate is self-assembled using a rapid solvent exchange technique and can form an anchored bilayer 1 nm off the gold electrode. This allows for an aqueous reservoir region, providing access to ions transported through membrane defects caused by triglyceride enzymatic hydrolysis. Electrical impedance spectroscopy techniques can readily detect the decrease in resistance caused by enzymatically induced defects. This rapid and reliable lipase detection method can have potential applications in disease studies, monitoring of lipase production, and as point-of-care diagnostic devices.

Combining molecular dynamics simulations and x-ray scattering techniques for the accurate treatment of protonation degree and packing of ionizable lipids in monolayers

The pH-dependent change in protonation of ionizable lipids is crucial for the success of lipid-based nanoparticles as mRNA delivery systems. Despite their widespread application in vaccines, the structural changes upon acidification are not well understood. Molecular dynamics simulations support structure prediction but require an a priori knowledge of the lipid packing and protonation degree. The presetting of the protonation degree is a challenging task in the case of ionizable lipids since it depends on pH and on the local lipid environment and often lacks experimental validation. Here, we introduce a methodology of combining all-atom molecular dynamics simulations with experimental total-reflection x-ray fluorescence and scattering measurements for the ionizable lipid Dlin-MC3-DMA (MC3) in POPC monolayers. This joint approach allows us to simultaneously determine the lipid packing and the protonation degree of MC3. The consistent parameterization is expected to be useful for further predictive modeling of the action of MC3-based lipid nanoparticles.

Diblock copolymer pattern protection by silver cluster reinforcement

Pattern fabrication by self-assembly of diblock copolymers is of significant interest due to the simplicity in fabricating complex structures. In particular, polystyrene-block-poly-4-vinylpyridine (PS-b-P4VP) is a fascinating base material as it forms an ordered micellar structure on silicon surfaces. In this work, silver (Ag) is applied using direct current magnetron sputter deposition and high-power impulse magnetron sputter deposition on an ordered micellar PS-b-P4VP layer. The fabricated hybrid materials are structurally analyzed by field emission scanning electron microscopy, atomic force microscopy, and grazing incidence small angle X-ray scattering. When applying simple aqueous posttreatment, the pattern is stable and reinforced by Ag clusters, making micellar PS-b-P4VP ordered layers ideal candidates for lithography.

Underscreening in concentrated electrolytes: re-entrant swelling in polyelectrolyte brushes

Hypersaline environments are ubiquitous in nature and are found in myriad technological processes. Recent empirical studies have revealed a significant discrepancy between predicted and observed screening lengths at high salt concentrations, a phenomenon referred to as underscreening. Herein we investigate underscreening using a cationic polyelectrolyte brush as an exemplar. Poly(2-(methacryloyloxy)ethyl)trimethylammonium (PMETAC) brushes were synthesised and their internal structural changes and swelling response was monitored with neutron reflectometry and spectroscopic ellipsometry. Both techniques revealed a monotonic brush collapse as the concentration of symmetric monovalent electrolyte increased. However, a non-monotonic change in brush thickness was observed in all multivalent electrolytes at higher concentrations, known as re-entrant swelling; indicative of underscreening. For all electrolytes, numerical self-consistent field theory predictions align with experimental studies in the low-to-moderate salt concentration regions. Analysis suggests that the classical theory of electrolytes is insufficient to describe the screening lengths observed at high salt concentrations and that the re-entrant polyelectrolyte brush swelling seen herein is consistent with the so-called regular underscreening phenomenon.

Microscopic Analysis of the Water/Glycerol/EO30PS System in Bulk and on a Solid Substrate

Surfactant systems are often employed in cosmetic formulations where they dry on skin as a surface, thereby becoming increasingly concentrated systems. To better understand this drying process, we focused on the difference of self-assembled structures of the water/glycerol/polyoxyethylene (30) phytosteryl ether (EO30PS) system in bulk and on a solid substrate because the interaction between the substrate and the surfactant may have a substantial effect on the self-assembly, which may be related to the bulk structure but in detail may also differ strongly from the bulk situation. In bulk, small-angle neutron scattering (SANS) experiments showed that with increasing loss of water, the degree of ordering increases but changes of the aggregate structure are rather small. The results indicate that ellipsoidal micelles of EO30PS are densely packed and simply become more ordered in bulk during the drying process. On the other hand, neutron reflectometry revealed that EO30PS molecules adsorb onto a Si surface in the form of bilayers and analysis indicates that at a high concentration (c = 20 wt %), there are on average two bilayers (a double bilayer) on the Si substrate. The adsorbed membrane structure of EO30PS is rather thin with respect to its hydrophobic part, indicating tilted molecules, containing only some solvent, and being not highly ordered. These experimental results then allow for a much deeper understanding of the structural properties of practical formulations as they are applied, for instance, in cosmetic lotions.

Composition Dictates Molecular Orientation at the Heterointerfaces of Vapor-Deposited Glasses

Physical vapor deposition (PVD) can prepare organic glasses with a preferred molecular orientation. The relationships between deposition conditions and orientation have been extensively investigated in the film bulk. The role of interfaces on the structure is less well understood and remains a key knowledge gap, as the interfacial region can govern glass stability and optoelectronic properties. Robust experimental characterization has remained elusive due to complexities in interrogating molecular organization in amorphous, organic materials. Polarized soft X-rays are sensitive to both the composition and the orientation of transition dipole moments in the film, making them uniquely suited to probe molecular orientation in amorphous soft matter. Here, we utilize polarized resonant soft X-ray reflectivity (P-RSoXR) to simultaneously depth profile the composition and molecular orientation of a bilayer prepared through the physical vapor deposition of 1,4-di-[4-(N,N-diphenyl)amino]styryl-benzene (DSA-Ph) on a film of aluminum-tris(8-hydroxyquinoline) (Alq3). The bulk orientation of the DSA-Ph layer is controlled by varying deposition conditions. Utilizing P-RSoXR to depth profile the films enables determination of both the bulk orientation of DSA-Ph and the orientation near the Alq3 interface. At the Alq3 surface, DSA-Ph always lies with its long axis parallel to the interface, before transitioning into the bulk orientation. This is likely due to the lower mobility and higher glass transition of Alq3, as the first several monolayers of DSA-Ph deposited on Alq3 appear to behave as a blend. We further show how orientation at the interface correlates with the bulk behavior of a codeposited glass of similar blend composition, demonstrating a straightforward approach to predicting molecular orientation at heterointerfaces. This work provides key insights into how molecules orient during vapor deposition and offers methods to predict this property, a critical step toward controlling interfacial behavior in soft matter.

Photoinduced bidirectional switching in lipid membranes containing azobenzene glycolipids

Following the reaction of biological membranes to external stimuli reveals fundamental insights into cellular function. Here, self-assembled lipid monolayers act as model membranes containing photoswitchable azobenzene glycolipids for investigating structural response during isomerization by combining Langmuir isotherms with X-ray scattering. Controlled in-situ trans/cis photoswitching of the azobenzene N = N double bond alters the DPPC monolayer structure, causing reproducible changes in surface pressure and layer thickness, indicating monolayer reorientation. Interestingly, for monolayers containing azobenzene glycolipids, along with the expected DPPC phase transitions an additional discontinuity is observed. The associated reorintation represents a crossover point, with the surface pressure and layer thickness changing in opposite directions above and below. This is evidence that the azobenzene glycolipids themselves change orientation within the monolayer. Such behaviour suggests that azobenzene glycolipids can act as a bidirectional switch in DPPC monolayers providing a tool to investigate membrane structure-function relationships in depth.

Structural insights on ionizable Dlin-MC3-DMA lipids in DOPC layers by combining accurate atomistic force fields, molecular dynamics simulations and neutron reflectivity

Ionizable lipids such as the promising Dlin-MC3-DMA (MC3) are essential for the successful design of lipid nanoparticles (LNPs) as drug delivery agents. Combining molecular dynamics simulations with experimental data, such as neutron reflectivity experiments and other scattering techniques, is essential to provide insights into the internal structure of LNPs, which is not fully understood to date. However, the accuracy of the simulations relies on the choice of force field parameters and high-quality experimental data is indispensable to verify the parametrization. For MC3, different parameterizations in combination with the CHARMM and the Slipids force fields have recently emerged. Here, we complement the existing efforts by providing parameters for cationic and neutral MC3 compatible with the AMBER Lipid17 force field. Subsequently, we carefully assess the accuracy of the different force fields by providing a direct comparison to neutron reflectivity experiments of mixed lipid bilayers consisting of MC3 and DOPC at different pHs. At low pH (cationic MC3) and at high pH (neutral MC3) the newly developed MC3 parameters in combination with AMBER Lipid17 for DOPC give good agreement with the experiments. Overall, the agreement is similar compared to the Park-Im parameters for MC3 in combination with the CHARMM36 force field for DOPC. The Ermilova-Swenson MC3 parameters in combination with the Slipids force field underestimate the bilayer thickness. While the distribution of cationic MC3 is very similar, the different force fields for neutral MC3 reveal distinct differences ranging from strong accumulation in the membrane center (current MC3/AMBER Lipid17 DOPC), over mild accumulation (Park-Im MC3/CHARMM36 DOPC) to surface accumulation (Ermilova-Swenson MC3/Slipids DOPC). These pronounced differences highlight the importance of accurate force field parameters and their experimental validation.

Investigation on the relationship between lipid composition and structure in model membranes composed of extracted natural phospholipids

HYPOTHESIS

Unravelling the structural diversity of cellular membranes is a paramount challenge in life sciences. In particular, lipid composition affects the membrane collective behaviour, and its interactions with other biological molecules.

EXPERIMENTS

Here, the relationship between membrane composition and resultant structural features was investigated by surface pressure-area isotherms, Brewster angle microscopy and neutron reflectometry on in vitro membrane models of the mammalian plasma and endoplasmic-reticulum-Golgi intermediate compartment membranes in the form of Langmuir monolayers. Natural extracted yeast lipids were used because, unlike synthetic lipids, the acyl chain saturation pattern of yeast and mammalian lipids are similar.

FINDINGS

The structure of the model membranes, orthogonal to the plane of the membrane, as well as their lateral packing, were found to depend strongly on their specific composition, with cholesterol having a major influence on the in-plane morphology, yielding a coexistence of liquid-order and liquid-disorder phases.

High-Density Lipoprotein function is modulated by the SARS-CoV-2 spike protein in a lipid-type dependent manner

There is a close relationship between the SARS-CoV-2 virus and lipoproteins, in particular high-density lipoprotein (HDL). The severity of the coronavirus disease 2019 (COVID-19) is inversely correlated with HDL plasma levels. It is known that the SARS-CoV-2 spike (S) protein binds the HDL particle, probably depleting it of lipids and altering HDL function. Based on neutron reflectometry (NR) and the ability of HDL to efflux cholesterol from macrophages, we confirm these observations and further identify the preference of the S protein for specific lipids and the consequent effects on HDL function on lipid exchange ability. Moreover, the effect of the S protein on HDL function differs depending on the individuals lipid serum profile. Contrasting trends were observed for individuals presenting low triglycerides/high cholesterol serum levels (LTHC) compared to high triglycerides/high cholesterol (HTHC) or low triglycerides/low cholesterol serum levels (LTLC). Collectively, these results suggest that the S protein interacts with the HDL particle and, depending on the lipid profile of the infected individual, it impairs its function during COVID-19 infection, causing an imbalance in lipid metabolism.

Extraction of interaction parameters from specular neutron reflectivity in thin films of diblock copolymers: an "inverse problem"

Diblock copolymers have been shown to undergo microphase separation due to an interplay of repulsive interactions between dissimilar monomers, which leads to the stretching of chains and entropic loss due to the stretching. In thin films, additional effects due to confinement and monomer-surface interactions make microphase separation much more complicated than in that in bulks (i.e., without substrates). Previously, physics-based models have been used to interpret and extract various interaction parameters from the specular neutron reflectivities of annealed thin films containing diblock copolymers (J. P. Mahalik, J. W. Dugger, S. W. Sides, B. G. Sumpter, V. Lauter and R. Kumar, Interpreting neutron reflectivity profiles of diblock copolymer nanocomposite thin films using hybrid particle-field simulations, Macromolecules, 2018, 51(8), 3116; J. P. Mahalik, W. Li, A. T. Savici, S. Hahn, H. Lauter, H. Ambaye, B. G. Sumpter, V. Lauter and R. Kumar, Dispersity-driven stabilization of coexisting morphologies in asymmetric diblock copolymer thin films, Macromolecules, 2021, 54(1), 450). However, extracting Flory-Huggins χ parameters characterizing monomer-monomer, monomer-substrate, and monomer-air interactions has been labor-intensive and prone to errors, requiring the use of alternative methods for practical purposes. In this work, we have developed such an alternative method by employing a multi-layer perceptron, an autoencoder, and a variational autoencoder. These neural networks are used to extract interaction parameters not only from neutron scattering length density profiles constructed using self-consistent field theory-based simulations, but also from a noisy ad hoc model constructed previously. In particular, the variational autoencoder is shown to be the most promising tool when it comes to the reconstruction and extraction of parameters from an ad hoc neutron scattering length density profile of a thin film containing a symmetric di-block copolymer (poly(deuterated styrene-b-n-butyl methacrylate)). This work paves the way for automated analysis of specular neutron reflectivities from thin films of copolymers using machine learning tools.

Native Function of the Bacterial Ion Channel SthK in a Sparsely Tethered Lipid Bilayer Membrane Architecture

The plasma membrane protects the interiors of cells from their surroundings and also plays a critical role in communication, sensing, and nutrient import. As a result, the cell membrane and its constituents are among the most important drug targets. Studying the cell membrane and the processes it facilitates is therefore crucial, but it is a highly complex environment that is difficult to access experimentally. Various model membrane systems have been developed to provide an environment in which membrane proteins can be studied in isolation. Among them, tethered bilayer lipid membranes (tBLMs) are a promising model system providing a solvent-free membrane environment which can be prepared by self-assembly, is resistant to mechanical disturbances and has a high electrical resistance. tBLMs are therefore uniquely suitable to study ion channels and charge transport processes. However, ion channels are often large, complex, multimeric structures and their function requires a particular lipid environment. In this paper, we show that SthK, a bacterial cyclic nucleotide gated (CNG) ion channel that is strongly dependent on the surrounding lipid composition, functions normally when embedded into a sparsely tethered lipid bilayer. As SthK has been very well characterized in terms of structure and function, it is well-suited to demonstrate the utility of tethered membrane systems. A model membrane system suitable for studying CNG ion channels would be useful, as this type of ion channel performs a wide range of physiological functions in bacteria, plants, and mammals and is therefore of fundamental scientific interest as well as being highly relevant to medicine.

From Hofmeister to hydrotrope: Effect of anion hydrocarbon chain length on a polymer brush

HYPOTHESIS

Specific ion effects govern myriad biological phenomena, including protein-ligand interactions and enzyme activity. Despite recent advances, detailed understanding of the role of ion hydrophobicity in specific ion effects, and the intersection with hydrotropic effects, remains elusive. Short chain fatty acid sodium salts are simple amphiphiles which play an integral role in our gastrointestinal health. We hypothesise that increasing a fatty acid's hydrophobicity will manifest stronger salting-out behaviour.

EXPERIMENTS

Here we study the effect of these amphiphiles on an exemplar thermoresponsive polymer brush system, conserving the carboxylate anion identity while varying anion hydrophobicity via the carbon chain length. Ellipsometry and quartz crystal microbalance with dissipation monitoring were used to characterise the thermoresponse and viscoelasticity of the brush, respectively, whilst neutron reflectometry was used to reveal the internal structure of the brush. Diffusion-ordered nuclear magnetic resonance spectroscopy and computational investigations provide insight into polymer-ion interactions.

FINDINGS

Surface sensitive techniques unveiled a non-monotonic trend in salting-out ability with increasing anion hydrophobicity, revealing the bundle-like morphology of the ion-collapsed system. An intersection between ion-specific and hydrotropic effects was observed both experimentally and computationally; trending from good anti-hydrotrope towards hydrotropic behaviour with increasing anion hydrophobicity, accompanying a change in hydrophobic hydration.

The Topology of Polymer Brushes Determines Their Nanoscale Hydration

Time-of-flight neutron reflectometry (ToF-NR) performed under different relative humidity conditions demonstrates that polymer brushes constituted by hydrophilic, cyclic macromolecules exhibit a more compact conformation with lower roughness as compared to linear brush analogues, due to the absence of dangling chain ends extending at the polymer-vapor interface. In addition, cyclic brushes feature a larger swelling ratio and an increased solvent uptake with respect to their linear counterparts as a consequence of the increased interchain steric repulsions. It is proposed that differences in swelling ratios between linear and cyclic brushes come from differences in osmotic pressure experienced by each brush topology. These differences stem from entropic constraints. The findings suggest that to correlate the equilibrium swelling ratios at different relative humidity for different topologies a new form of the Flory-like expression for equilibrium thicknesses of grafted brushes is needed.

Spatz: the time-of-flight neutron reflectometer with vertical sample geometry at the OPAL research reactor

The Spatz neutron beam instrument is the second time-of-flight neutron reflectometer to be installed at the OPAL research reactor. The instrument was formerly the V18 BioRef reflectometer at the BER-II reactor in Berlin and was transferred to Australia in 2016. Subsequently the instrument was re-installed in the neutron guide hall of the OPAL reactor at the end position of the CG2B cold-neutron guide and recommissioned. The instrument performance has not been compromised by the move, with reflectivity achieved down to 10^-7 and good counting statistics within a reasonable time frame using a wavelength range of 2-20 Å. Several different samples at the solid-air interface and the solid-liquid interface have been measured to demonstrate the instrument's capabilities.

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.

Cosolvent effects on the structure and thermoresponse of a polymer brush: PNIPAM in DMSO–water mixtures

Structural characterisation of thermoresponsive polymer brushes in binary DMSO–water mixtures reveals both LCST and UCST behaviour.

Faster and lower-dose X-ray reflectivity measurements enabled by physics-informed modeling and artificial intelligence co-refinement

An approach is presented for analysis of real-time X-ray reflectivity (XRR) process data not just as a function of the magnitude of the reciprocal-space vector q, as is commonly done, but as a function of both q and time. The real-space structures extracted from the XRR curves are restricted to be solutions of a physics-informed growth model and use state-of-the-art convolutional neural networks (CNNs) and differential evolution fitting to co-refine multiple time-dependent XRR curves R(q, t) of a thin film growth experiment. Thereby it becomes possible to correctly analyze XRR data with a fidelity corresponding to standard fits of individual XRR curves, even if they are sparsely sampled, with a sevenfold reduction of XRR data points, or if the data are noisy due to a 200-fold reduction in counting times. The approach of using a CNN analysis and of including prior information through a kinetic model is not limited to growth studies but can be easily extended to other kinetic X-ray or neutron reflectivity data to enable faster measurements with less beam damage.

Faster and lower-dose X-ray reflectivity measurements enabled by physics-informed modeling and artificial intelligence co-refinement

An approach is presented for analysis of real-time X-ray reflectivity (XRR) process data not just as a function of the magnitude of the reciprocal-space vector q, as is commonly done, but as a function of both q and time. The real-space structures extracted from the XRR curves are restricted to be solutions of a physics-informed growth model and use state-of-the-art convolutional neural networks (CNNs) and differential evolution fitting to co-refine multiple time-dependent XRR curves R(q, t) of a thin film growth experiment. Thereby it becomes possible to correctly analyze XRR data with a fidelity corresponding to standard fits of individual XRR curves, even if they are sparsely sampled, with a sevenfold reduction of XRR data points, or if the data are noisy due to a 200-fold reduction in counting times. The approach of using a CNN analysis and of including prior information through a kinetic model is not limited to growth studies but can be easily extended to other kinetic X-ray or neutron reflectivity data to enable faster measurements with less beam damage.

GenX 3: the latest generation of an established tool

Improvements to the GenX program are discussed, including performance, model building and error analysis.

Since its publication more than 15 years ago the GenX software has been continuously developed and has established itself as a standard package for analyzing X-ray and neutron reflectometry data. The evolution of the software during the last two major revisions is reported here. This includes a simplified model builder for beginners, simple samples, additional sample models, statistical error analysis and the use of just-in-time compilation modules for the reflectometry kernel to achieve higher performance. In addition, the influence of experimental errors on the reflectivity curve is discussed, and new features are described that allow the user to include these in the error statistics to improve the fitting and uncertainty estimation.

Electro-polymerization rates of diazonium salts are dependent on the crystal orientation of the surface

Electro-polymerization of diazonium salts is widely used for modifying surfaces with thin organic films. Initially this method was primarily applied to carbon, then to metals, and more recently to semiconducting Si. Unlike on other surfaces, electrochemical reduction of diazonium salts on Si, which is one of the most industrially dominant material, is not well understood. Here, we report the electrochemical reduction of diazonium salts on a range of silicon electrodes of different crystal orientations (111, 211, 311, 411, and 100). We show that the kinetics of surface reaction and the reduction potential is Si crystal-facet dependent and is more favorable in the hierarchical order (111) > (211) > (311) > (411) > (100), a finding that offers control over the surface chemistry of diazonium salts on Si. The dependence of the surface reaction kinetics on the crystal orientation was found to be directly related to differences in the potential of zero charge (PZC) of each crystal orientation, which in turn controls the adsorption of the diazonium cations prior to reduction. Another consequence of the effect of PZC on the adsorption of diazonium cations, is that molecules terminated by distal diazonium moieties form a compact film in less time and requires less reduction potentials compared to that formed from diazonium molecules terminated by only one diazo moiety. In addition, at higher concentrations of diazonium cations, the mechanism of electrochemical polymerization on the surface becomes PZC-controlled adsorption-dominated inner-sphere electron transfer while at lower concentrations, diffusion-based outer-sphere electron transfer dominates. These findings help understanding the electro-polymerization reaction of diazonium salts on Si en route towards an integrated molecular and Si electronics technology.

Optimizing experimental design in neutron reflectometry

An approach for optimal experimental design of neutron reflectivity experiments using metrics derived from the Fisher information is presented. This is demonstrated on a range of systems including lipid bilayers and magnetic heterostructures, and it is shown that small (or large) changes to the experimental setup can result in drastically reduced experimental count times.

Using the Fisher information (FI), the design of neutron reflectometry experiments can be optimized, leading to greater confidence in parameters of interest and better use of experimental time [Durant, Wilkins, Butler & Cooper (2021). J. Appl. Cryst.54, 1100–1110]. In this work, the FI is utilized in optimizing the design of a wide range of reflectometry experiments. Two lipid bilayer systems are investigated to determine the optimal choice of measurement angles and liquid contrasts, in addition to the ratio of the total counting time that should be spent measuring each condition. The reduction in parameter uncertainties with the addition of underlayers to these systems is then quantified, using the FI, and validated through the use of experiment simulation and Bayesian sampling methods. For a ‘one-shot’ measurement of a degrading lipid monolayer, it is shown that the common practice of measuring null-reflecting water is indeed optimal, but that the optimal measurement angle is dependent on the deuteration state of the monolayer. Finally, the framework is used to demonstrate the feasibility of measuring magnetic signals as small as 0.01 μ_B per atom in layers only 20 Å thick, given the appropriate experimental design, and that the time to reach a given level of confidence in the small magnetic moment is quantifiable.

Parameter estimation for X-ray scattering analysis with Hamiltonian Markov Chain Monte Carlo

Bayesian-inference-based approaches, in particular the random-walk Markov Chain Monte Carlo (MCMC) method, have received much attention recently for X-ray scattering analysis. Hamiltonian MCMC, a state-of-the-art development in the field of MCMC, has become popular in recent years. It utilizes Hamiltonian dynamics for indirect but much more efficient drawings of the model parameters. We described the principle of the Hamiltonian MCMC for inversion problems in X-ray scattering analysis by estimating high-dimensional models for several motivating scenarios in small-angle X-ray scattering, reflectivity, and X-ray fluorescence holography. Hamiltonian MCMC with appropriate preconditioning can deliver superior performance over the random-walk MCMC, and thus can be used as an efficient tool for the statistical analysis of the parameter distributions, as well as model predictions and confidence analysis.

Neural network analysis of neutron and X-ray reflectivity data: automated analysis using mlreflect, experimental errors and feature engineering

A Python-based analysis pipeline for the fast analysis of X-ray and neutron reflectivity data using neural networks is presented.

The Python package mlreflect is demonstrated, which implements an optimized pipeline for the automated analysis of reflectometry data using machine learning. The package combines several training and data treatment techniques discussed in previous publications. The predictions made by the neural network are accurate and robust enough to serve as good starting parameters for an optional subsequent least-mean-squares (LMS) fit of the data. For a large data set of 242 reflectivity curves of various thin films on silicon substrates, the pipeline reliably finds an LMS minimum very close to a fit produced by a human researcher with the application of physical knowledge and carefully chosen boundary conditions. The differences between simulated and experimental data and their implications for the training and performance of neural networks are discussed. The experimental test set is used to determine the optimal noise level during training. The extremely fast prediction times of the neural network are leveraged to compensate for systematic errors by sampling slight variations in the data.

Characterization of the Interfacial Orientation and Molecular Conformation in a Glass-Forming Organic Semiconductor

The ability to control structure in molecular glasses has enabled them to play a key role in modern technology; in particular, they are ubiquitous in organic light-emitting diodes. While the interplay between bulk structure and optoelectronic properties has been extensively investigated, few studies have examined molecular orientation near buried interfaces despite its critical role in emergent functionality. Direct, quantitative measurements of buried molecular orientation are inherently challenging, and many methods are insensitive to orientation in amorphous soft matter or lack the necessary spatial resolution. To overcome these challenges, we use polarized resonant soft X-ray reflectivity (p-RSoXR) to measure nanometer-resolved, molecular orientation depth profiles of vapor-deposited thin films of an organic semiconductor Tris(4-carbazoyl-9-ylphenyl)amine (TCTA). Our depth profiling approach characterizes the vertical distribution of molecular orientation and reveals that molecules near the inorganic substrate and free surface have a different, nearly isotropic orientation compared to those of the anisotropic bulk. Comparison of p-RSoXR results with near-edge X-ray absorption fine structure spectroscopy and optical spectroscopies reveals that TCTA molecules away from the interfaces are predominantly planar, which may contribute to their attractive charge transport qualities. Buried interfaces are further investigated in a TCTA bilayer (each layer deposited under separate conditions resulting in different orientations) in which we find a narrow interface between orientationally distinct layers extending across ≈1 nm. Coupling this result with molecular dynamics simulations provides additional insight into the formation of interfacial structure. This study characterizes the local molecular orientation at various types of buried interfaces in vapor-deposited glasses and provides a foundation for future studies to develop critical structure-function relationships.

Spontaneous surface adsorption of aqueous graphene oxide by synergy with surfactants

The spontaneous adsorption of graphene oxide (GO) sheets at the air-water interface is explored using X-ray reflectivity (XRR) measurements. As a pure aqueous dispersion, GO sheets do not spontaneously adsorb at the air-water interface due to their high negative surface potential (-60 mV) and hydrophilic functionality. However, when incorporated with surfactant molecules at optimal ratios and loadings, GO sheets can spontaneously be driven to the surface. It is hypothesised that surfactant molecules experience favourable attractive interactions with the surfaces of GO sheets, resulting in co-assembly that serves to render the sheets surface active. The GO/surfactant composites then collectively adsorb at the air-water interface, with XRR analysis suggesting an interfacial structure comprising surfactant tailgroups in air and GO/surfactant headgroups in water for a combined thickness of 30-40 Å, depending on the surfactant used. Addition of too much surfactant appears to inhibit GO surface adsorption by saturating the interface, and low loadings of GO/surfactant composites (even at optimal ratios) do not show significant adsorption indicating a partitioning effect. Lastly, surfactant chemistry is also a key factor dictating adsorption capacity of GO. The zwitterionic surfactant oleyl amidopropyl betaine causes marked increases in GO surface activity even at very low concentrations (≤0.2 mM), whereas non-ionic surfactants such as Triton X-100 and hexaethyleneglycol monododecyl ether require higher concentrations (ca. 1 mM) in order to impart spontaneous adsorption of the sheets. Anionic surfactants do not enhance GO surface activity presumably due to like-charge repulsions that prevent co-assembly. This work provides useful insight into the synergy between GO sheets and molecular amphiphiles in aqueous systems for enhancing the surface activity of GO, and can be used to inform system formulation for developing water-friendly, surface active composites based around atomically thin materials.