Rutherford Appleton Laboratory

Many clinically used drugs are amphiphiles, yet the effect of their amphiphilicity on their therapeutic activity is poorly understood. As cell membranes are the first barrier a drug encounters on route to its site of action, we propose that an amphiphilic drug's membrane activity will impact its clinical efficacy. Comprehensive quantitative detail on the membrane interactions of the amphiphilic β-blocker drug, (±) propranolol has been investigated, using a synergistic combination of surface area-pressure measurements, ellipsometry, Brewster angle microscopy and selective H/D contrast variation neutron reflectometry, and using Langmuir monolayers comprising zwitterionic, 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC) alone and with 30mol% of negatively charged, 1-palmitoyl-2-oleoyl-sn-glycero-3-phospho-1'-rac-glycerol sodium (POPG). The interaction of propranolol with the lipid monolayers was resolved in terms of changes in lipid morphology, the extent of lipid loss from the membrane, and the drug's favoured location and orientation within the membrane. Propranolol is proposed to interact with the lipid monolayers in three stages: (1) electrostatic binding to the lipid head groups, (2) drug-mediated lipid loss from the membrane, and (3) the re-organisation of the drug's hydrophobic region within the membrane lipid chains. At steady state, and regardless of lipid packing, the monolayer contains more drug than lipid molecules. Further, the presence of negatively charged POPG does not enhance the cationic drug's interactions with the monolayer, most likely due to the differential solubilisation of membrane lipid in the aqueous subphase. Significantly, these results demonstrate how a drug's amphiphilic nature can determine its membrane activity and thereby impact its clinical efficacy.

Trehalose is widely recognized for stabilising proteins under conditions that promote dehydration, denaturation, or loss of function, yet its underlying mechanisms remain elusive. We examine myoglobin in trehalose solutions of two concentrations to evaluate whether trehalose forms a protective sugar shell beyond the hydration layer-a concept suggested by molecular dynamics simulations but not experimentally verified. Using neutron diffraction, we demonstrate that myoglobin remains almost fully hydrated in both systems, even at high trehalose concentrations. To probe myoglobin-trehalose interactions, we constructed two starting models: (i) trehalose molecules dispersed randomly in the solvent and (ii) a pre-assembled trehalose shell positioned adjacent to the protein surface. After refinement, both models converged with experimental data in the Q range (1-30 Å-1), despite resulting in markedly different final configurations, although the protein was preferentially hydrated by water in both cases. However, the shell model yields substantially higher low-Q intensities (0.03-0.5 Å-1), inconsistent with the experimental data, demonstrating that trehalose does not form a pronounced layer outside the hydration shell. Residue-resolved analysis further confirms that there are almost no direct trehalose-protein interactions for hydrophilic or hydrophobic amino acids. In addition, quasielastic neutron scattering reveals slower dynamics for all components in the concentrated system. Furthermore, the protein motions are considerably slower in the three-component systems compared to those in a trehalose-free binary solution. This finding shows the significance of the dynamically stabilising effect of trehalose on proteins in cryoprotective and pharmaceutical applications.

Polymer blends in thin films offer versatile opportunitiesfortailoring material properties. Among available deposition methods,the Langmuir film technique enables the formation of well-controllednanometer-thick films at the air–water interface, revealingunique miscibility and phase behaviors not observed in bulk. In thiswork, we investigate 2D polymer blends composed of amphiphilic PEO11–PPO35–PEO11 and hydrophobicPDMS using a multiscale approach that combines surface pressure–areaisotherms, Brewster angle microscopy (BAM), neutron reflectometry(NR), and sum-frequency generation (SFG) spectroscopy. This methodologyenabled us to construct a 2D surface pressure–composition phasediagram, identifying miscibility regions and two distinct first-orderphase transitions. Across all compositions, no lateral phase separationwas observed at the mesoscopic scale by BAM, even during phase transitions.Instead, NR revealed vertical segregation at specific surface pressuresand compositions. In PEO11–PPO35–PEO11-rich blends, a homogeneous monolayer undergoes a transitionto a bilayer, with hydrophobic PDMS positioned atop PEO11–PPO35–PEO11. PDMS-rich blendsdisplay a similar bilayer structure at all pressures, with the phasetransition mainly involving thickening of the PDMS layer, as seenin pure PDMS films. SFG spectroscopy reveals that both polymers havedistinct behavior in the blends and in pure films, due to either lateralor vertical interactions. Notably, despite their contrasting hydrophobicities,the polymers exhibit miscibility over a range of compositions andsurface pressures, with evidence of attractive interactions. Thesefindings underscore the unique behavior of confined polymer blendsand the importance of 2D-specific phase diagrams for designing functionalinterfacial materials.

Gaseous water exhibits significantly greater spatiotemporal variability than other major greenhouse gases, such as carbon dioxide and methane. Consequently, satellite-based global monitoring of atmospheric water vapour is an essential methodology for elucidating its climate impacts at regional and global scales over timescales ranging from short to multidecadal. To track water vapour, total column measurements are derived from satellite observations of reflected solar radiation within the UV-VIS spectral region centred at 440 nm. This water vapour absorption band is an alternative to the conventional NIR band centred at 648 nm. The advantage of this band is that it is detectable across all European Sentinel platforms and their predecessor instruments, such as GOME on ERS-2, SCIAMACHY on Envisat and GOME-2 on MetOp-A/B/C, as well as future instruments, e.g. CO2M.This work presents recent advancements in the application of differential optical absorption spectroscopy (DOAS) to geostationary Sentinel-4 and polar-orbiting Sentinel-5P observations. This work serves as preparatory research for future implementations with the polar-orbiting Sentinel-5 mission.The retrieval methodology has several advantages over existing sensing techniques: (1) optimal sensitivity and coverage characteristics across both terrestrial and oceanic domains; (2) enhanced spatial resolution and temporal sampling frequency, particularly for European observations via Sentinel-4, which improves weather forecasting, scientific product development, air quality assessment and environmental policy applications; and (3) the continuous extension of long-term datasets starting with GOME-type sensors, which is crucial for regional and global climate modelling. This naturally introduces the possibility of creating a homogeneous climate data record since 1995.

In this work we report on the development of a Shunt LDO (SLDO) for use in the serial powering chain of staves and discs at the Electron Ion Collider (EIC). The device is designed in a 110nm CMOS technology and can supply up to 1 A at a voltage of 1.1 to 1.4 V. Simulated PSRR at DC is -56 dB, and efficiency is above 70 %. Safety features such as load overcurrent protection and the ability to shunt the current of failed parallel SLDOs are included. A first prototype has been submitted. In this work we will report on the design of the device, and on simulation results of the prototype.

Abstract Na-ion batteries (NIBs) have gained attention as a cost-effective option for large-scale energy storage, offering electrochemical properties similar to lithium-ion batteries (LIBs). To improve safety and energy density, solid-state electrolytes (SSEs) are being incorporated into NIBs, paving the way for high-performance all-solid-state sodium-ion batteries (ASSNIBs). This review summarises recent progress in Na-based SSEs, categorised into oxides, sulfides, and halides, with particular emphasis on their crystal structures, ion conduction mechanisms, and electrochemical performance. We then critically examine the key challenges facing ASSNIBs, including low ionic conductivity, unstable electrode/electrolyte interfaces, and the reliance on rare or costly materials. To gain deeper insights into these issues, we highlight advanced characterisation and modelling techniques, including cryogenic electron microscopy, in-situ/operando characterisation, and machine learning approaches—all of which contribute to understanding Na-ion transport mechanisms and interfacial dynamics more comprehensively, and comparing with conventional electrochemical tests, structural characterisation and modelling methods. Building on these insights, we explore promising strategies such as microstructural design, mixed-ion approaches, and interface engineering to overcome the current limitations in Na SSEs. Finally, we offer perspectives on future research directions to support the rational design and optimisation of Na SSEs, ultimately advancing the development of next-generation ASSNIBs. The advanced characterisation and machine learning methodologies emphasised herein will also prove valuable for broader applications in electrochemical energy storage systems. Graphical abstract

Abstract. The Characterising CiRrus and icE cloud acrosS the specTrum-Microwave (CCREST-M) aircraft campaign (February–March 2024) was based around the Chilbolton Observatory, UK, using the Facility for Airborne Atmospheric Measurements (FAAM) BAe-146 aircraft. The campaign was designed primarily as a testbed for ice-cloud scattering and radiative transfer models across the microwave and sub-millimetre spectrum. A key requirement for such closure tests is a near one-to-one relationship between the ice particle size distributions (PSDs) that enter the radiative transfer model and the radiometric measurements. Owing to the FAAM BAe-146 aircraft being unable to perform simultaneously above-cloud radiometric measurements and in-situ sampling within the same volume of cloud, we retrieve PSDs from the ground-based zenith-pointing radars at the time of the radiometric overpasses and then use the aircraft in-situ PSDs as an independent validation dataset. We present a novel hybrid retrieval framework for mid-latitude ice PSD parameters (slope λ, intercept No, and shape μ of the gamma size distribution) that combines a machine-learning (ML) ensemble with physics-based multi-frequency radar retrievals using 3, 35, and 94 GHz reflectivities. An ensemble of ML models is trained on observations from the Parameterising Ice Clouds using Airborne ObServationS and triple–frequency dOppler radar (PICASSO) campaign, also centred on Chilbolton Observatory. These models predict PSD moments from temperature, pressure, 3 GHz-retrieved ice water content (IWC), and the mean mass-weighted dimension. The ML predictions are converted into first guess gamma-PSD parameters at each height. A subsequent deterministic optimisation then adjusts No and λ, using a randomly oriented rosette-aggregate scattering model, to enforce simultaneous agreement with the observed 35 and 94 GHz reflectivities. In this way, the ML ensemble acts as a compact, data-driven representation of the prior information, this being an alternative approach to the Bayesian optimal-estimation framework. We apply the retrieval to three of the CCREST-M cases with co-incident in-situ aircraft data. We show that the ML ensemble reproduces PSD moments well for two cases but fails when extrapolating beyond its trained temperature range in the third case. Retrieved IWCs from the 3 GHz radar compare favourably with PICASSO derived in-situ measurements of IWC, and exponential (μ=0) and gamma PSD assumptions show comparable performance overall. Retrieved mean and median PSDs show generally good agreement with in-situ PSDs as a function of temperature, although systematic biases remain in one case, likely due to temporal cloud evolution between radar and in-situ sampling. The IWCs derived from the retrieved PSDs are generally within about 50 % of the in-situ measured IWCs over much of the –50 to –10o C temperature range, with near-unity agreement between the estimated and in-situ IWCs for one of the cases. Independent validation using 200 GHz radar reflectivity profiles confirms retrieval consistency where ML predictions are reliable and for a well constrained case, reinforcing the robustness of the retrieval approach and ice crystal scattering model. The retrieved PSDs provide radar-constrained inputs for forthcoming radiative transfer closure studies using collocated mm-wave and sub-mm-wave radiometer observations.

The evolution of buried interfaces, the hidden junctionswheredistinct phases exchange charge, mass, and mechanical response undernonequilibrium conditions, strongly influences the performance andstability of functional devices such as batteries, but they remaindifficult to probe directly. This perspective summarizes the typesof buried interfaces that form within battery electrodes and theirelectrochemical function in the device, and it discusses how advancesin operando probes, cell architectures, and multimodaland correlative strategies have enabled dynamic and chemically specificvisibility of their evolution. Despite this progress, operando signals remain challenging to interpret because they are affectedby, for example, beam damage-induced changes, variations in operando cell geometry, and intrinsic sample-to-sample differences,which together limit quantitative insight. Building on these considerations,the perspective examines how operando visibilitycan be transformed into quantitative diagnosis by integrating multimodalmeasurements with physically informed interface models and data-drivenanalysis. The final section outlines a roadmap for reproducible andquantitative operando analysis, centered on standardizedcell architectures, long-term autonomous measurements, and artificialintelligence approaches that incorporate physical constraints. Insummary, these developments define a pathway from operando visibility to quantitative diagnosis and provide a foundation foradvancing interface characterization and quantitative analysis inbatteries and related energy materials.

Abstract In the last few decades, lanthanum halide scintillators such as LaBr3(Ce), LaBr3(Ce+Sr) and LaCl3(Ce) have been extensively used for gamma ray spectroscopy measurements. They offer excellent energy resolution (about 3-4 % at 662keV) and fast scintillation time, allowing high counting rate measurements. These scintillators find applications in many research fields such as nuclear physics, astrophysics, nuclear fusion and nuclear medicine. More recently, thanks to the exploitation of the n-35Cl nuclear reaction channel, LaCl3(Ce) crystals have been used as neutron spectrometers. This opened up the opportunity to explore pulse shape discrimination algorithms for enabling the neutron/gamma discrimination. In this work, an innovative algorithm for particle discrimination applied to lanthanum halide scintillators is presented. The effectiveness of the algorithm has been demonstrated first on the intrinsic radioactivity measurement of the crystals, which is characterized by gamma ray emissions from 138La decay and alpha decays due to actinides contamination, and then with fast neutrons. The particle discrimination feature allows for a better description of the intrinsic activity of the crystal and improved background suppression when performing gamma ray spectroscopy measurements in low cross-section measurements or in a mixed gamma-neutron radiation field.