A proposed novel combined milling and combustion performance model for fuel selection

This paper presents for the first time the development and evaluation of novel combined milling performance metric and a burnout prediction tool. Pistachio shells, walnut shell, rice husks, and palm kernel shells and wood pellets were milled in a vertical spindle mill with pneumatic classification and then pyrolyzed in a drop tube furnace in three particle sizes (53–75 μm, 212–300 μm, 650–850 μm) to produce chars. The Von Rittinger constant was used to rank the milling performance, which allows for the impact of mill choking to be considered, providing a more realistic assessment of milling performance. The novel burnout prediction model (simulating the combustion of the chars produced) is based on composite burnout profiles for different char types and is the first burnout prediction model which uses char morphology data to quantitatively predict burnout. It provides a rapid burnout comparison tool for power generators by quantifying the carbon loss during an iterative process, where the char material is progressively ‘burning’ from the outside inwards. Finally, by combining the milling and burnout metricises, it is possible to predict milling requirements for a desired burnout performance. These tools will enable power generators to make informed holistic decisions about new fuels and understand how composition and particle size influences both milling and subsequent burnout performance

Graphical representation of global water models

Numerical models are simplified representations of the real world at a finite level of complexity. Global water models are used to simulate the terrestrial part of the global water cycle, and their outputs contribute to the evaluation of important natural and societal issues, including water availability, flood risk, and ecological functioning. Whilst global water modeling is an area of science that has developed over several decades, and individual model-specific descriptions exist for some models, there has to date been no attempt to visualize the ways that several models work, using a standardized visualization framework. Here, we address this gap by presenting a community-driven process that developed a framework to visualize several global water models. The models considered participate in the Inter-Sectoral Impact Model Intercomparison Project phase 2b (ISIMIP2b). The diagrams were co-produced between a graphics designer and 16 modeling teams, based on extensive discussions and pragmatic decision-making that balanced the need for accuracy and detail against the need for effective visualization. The model diagrams are based on a standardized ISIMIP2b-complete global water model that represents what is theoretically possible to represent in the current generation of state-of-the-art global water models participating in ISIMIP2b. Model-specific diagrams are then copies of the ISIMIP2b-complete model, with individual processes either included or grayed out. An open-source tool has been developed and published jointly with the diagrams, which allows someone to generate a diagram for their own global water model by adapting the diagrams presented here. As well as serving an educational purpose, we envisage that the diagrams will help researchers in and outside of the global water model community to select suitable model(s) for specific applications, stimulate a community learning process, and identify missing components to help direct future model developments

Influence of Magnetic Anisotropy on the Ground State of [CH3NH3]Fe(HCOO)3: Insights into the Improper Modulated Magnetic Structure

T h e h y b r i d p e r o v s k i t e s [ C H 3 N H 3 ] -CoxNix−1(HCOO)3 with x = 0, 0.25, 0.5, 0.75, and 1.0 possess multiple phase transitions, including incommensurate structures. Notably, [CH3NH3]Ni(HCOO)3 features a proper magnetically incommensurate structure ground state. To explore similar behavior, we investigated the isomorphous [CH3NH3]Fe-(HCOO)3 (1). A combination of magnetometry measurements, single crystal and powder neutron diffraction, and density functional theory calculations have been used to accurately determine and understand the sequence of nuclear and magnetic phases present in compound 1. At room temperature, it crystallizes in the Pnma space group with a perovskite structure. Below 170 K,new satellite reflections indicate a transition to a modulated structure, refined in the Pnma(00γ)0s0 with q1 = 0.1662(2)c*. At 75 K, the satellite reflections become closer to the main reflections, indicating a second transition, which maintains the superspace group symmetry but decreases the modulation wave vector to q2 =0.1425(2)c*, i.e., with a longer modulation period. This modulation persists to 2 K, overlapping with the onset of 3D antiferromagnetic order at 17 K, offering a unique opportunity to study magneto-structural coupling. Our results point to animproper magnetic modulated structure where, interestingly, the spins are perpendicular to those of previously reported compounds

Holistic Design Optimisation of 350 kW High-Speed Permanent Magnet Assisted Synchronous Reluctance Machine for Heavy-Duty Electric Vehicle

The widely adopted “high-speed machine + high-ratio gear” solutions for passenger electric vehicle (EV) drivetrains are yet to be explored for demanding heavy-duty applications. This paper will investigate 350kW level high speed traction motor development based on permanent magnet assisted synchronous reluctance machine (PMaSyRM) topology. With the overall target of boosting active power density under threshold of materials’ performance boundaries, multi-physics solvers are configured by both analytical and simulation tools to tackle design challenges in electromagnetic, mechanical, and thermal domains. To deal with multiple design parameters and performance indicators, a three stage hierarchical development platform is proposed and implemented to feature not only comprehensiveness but also balanced computation resource consumption and accuracy. Apart from globally parametrized machine geometry, the usually pre-defined slot number and pole number are looked into in the first and second stages, respectively, and are down-selected due to their substantial influence on material usage and loss distributions. In the final stage, a novel mechanical stress design concept is proposed, which significantly accelerates the “electromagnetic + mechanical” coupled rotor design process. Moreover, three typical cooling strategies are quantitatively evaluated for further down-selection of the most suitable thermal management. The finalized design is validated by a 1:1 PMaSyRM prototype with 580Nm peak torque, 15000rpm peak speed, which features active power density of 6.3 kW/kg

Study on molecular orientation and stratification in RNA-lipid nanoparticles by cryogenic orbitrap secondary ion mass spectrometry

Lipid nanoparticle RNA (LNP-RNA) formulations are used for the delivery of vaccines and other therapies. RNA molecules are encapsulated within their interior through electrostatic interactions with positively charged lipids. The identity of the lipids that present at their surface play a role in how they interact with and are perceived by the body and their resultant potency. Here, we use a model formulation to develop cryogenic sample preparation for molecular depth profiling Orbitrap secondary ion mass spectrometry (Cryo-OrbiSIMS) preceded by morphological characterisation using cryogenic transmission electron microscopy (Cryo-TEM). It is found that the depth distribution of individual lipid components is revealed relative to the surface and the RNA cargo defining the core. A preferential lipid orientation can be determined for the 1,2-Dimyristoyl-glycero-3-methox-polyethylene glycol 2000 (DMG-PEG2k) molecule, by comparing the profiles of PEG to DMG fragments. PEG fragments are found immediately during analysis of the LNP surface, while the DMG fragments are deeper, coincident with RNA ions located in the core, in agreement with established models of LNPs. This laboratory-based de novo analysis technique requires no labelling, providing advantages over large facility neutron scattering characterisation

Roles of hormones in regulating root growth–water interactions

Water stress presents a critical challenge affecting plant growth and agricultural productivity, with drought alone causing substantial yield losses. Roots serve as the primary site for water uptake, enabling plants to detect water stress by sensing changes in soil moisture levels. This initial perception prompts roots to initiate a spectrum of adaptive responses at morphological, anatomical, and biochemical levels. In addition to coping with severe water stress conditions such as drought, roots also respond to microscale variations in water availability within the rhizosphere as they navigate through soil, exhibiting responses such as hydrotropism, xerobranching, and hydropatterning. These adaptive responses are orchestrated by dynamic and sophisticated sensing and signalling mechanisms mediated by plant hormones at the cellular level. This review explores recent advances in our understanding of root responses to water stress, emphasizing the hormonal mechanisms underpinning these adaptations. Furthermore, it outlines future perspectives aimed at enhancing crop resilience to water stress through improved understanding and manipulation of root–water interactions

What does a sociologist do? Norwegian, English, and Hungarian university students’ possible future selves

This paper explores how sociology undergraduate and postgraduate students understand and discuss their possible (sociological) futures in three national contexts of Norway, England, and Hungary. Using an international comparative design based on a total of 38 semi-structured interviews from the three case-study countries, it explores first, current university students’ perceptions of roles and activities, goals and outputs, as well as organisational settings one needs to work in to be considered a sociologist. Second, drawing on the possible selves model outlined by Markus and Nurius and further conceptualised by Harrison this paper explores students’ allusions to probable, like-to-be, and like-to-avoid selves, providing a brief window into their imagined sociological futures. Students’ perceptions of their future sociological selves and the influence of role models in shaping their sociological identities reveal intricate decision-making processes, undertaken while navigating their sociological futures

Improving Public Funding Allocation to Reduce Geographical Inequalities

The UK faces severe geographical inequalities that manifest across multiple dimensions – including productivity, income, education, and health – and in different ways within and between areas. These multifaceted issues and their spatial expression create interconnected challenges that hamper national growth and leave economic potential unrealised.The UK’s centralised governance system has failed to address these longstanding inequalities, with standardised policy approaches and ineffective public funding allocation unable to address geographical differences. England’s asymmetric devolution and competitive funding environment particularly disadvantage areas with limited institutional capacity.While the 2024 English Devolution White Paper offers some promise for strengthening subnational governance, its focus on national economic growth is likely to continue benefiting major urban centres with the most immediate economic potential at the expense of other places, thereby reinforcing geographical inequalities.This project proposes improved ways to allocate public funding within and between different areas in England to reduce geographical inequalities and enable more places to contribute meaningfully to national economic growth and renewal. It draws on the research of a multi-disciplinary team of academics, researchers and consultants undertaken between June 2024 and March 2025.This research included evidence reviews, international case studies, analysis of spatially targeted funding streams, ‘deep dives’ into specific topics, interviews with policy practitioners, and citizen engagement. Addressing the role of public funding in reducing geographical inequalities in England, the research identified ten guiding principles and ten key problems with incremental, moderate and radical proposals to help resolve them

Pattern formation on an ice surface

A linear stability model based on a phase-field method is established to study the formation of ripples on the ice surface. The pattern on horizontal ice surfaces, e.g. glaciers and frozen lakes, is found to be originating from a gravity-driven instability by studying ice–water–air flows with a range of water and ice thicknesses. Contrary to gravity, surface tension and viscosity act to suppress the instability. The results demonstrate that a larger value of either water thickness or ice thickness corresponds to a longer dominant wavelength of the pattern, and a favourable wavelength of 90 mm is predicted, in agreement with observations from nature. Furthermore, the profiles of the most unstable perturbations are found to be with two peaks at the ice–water and water–air interfaces whose ratio decreases exponentially with the water thickness and wavenumber

Framework for uncertainty evaluation in optical surface topography measurement using a virtual instrument

Uncertainty evaluation in the measurement of surfaces with complex topography using optical techniques remains a challenge due to the complex interaction between light and the surfaces. The ISO 25178 part 600 specification standard simplifies uncertainty evaluation by introducing a set of agreed metrological characteristics that can be propagated through a mathematical model. To complement this, we developed a virtual coherence scanning interferometer to model error sources and provide task-specific uncertainty evaluation. This paper presents a framework for evaluating measurement uncertainty of areal surface texture parameters, using both the metrological characteristics approach and the virtual instrument method. We demonstrate this framework by assessing the uncertainty of the Sq parameter, which represents the root-mean-square of surface heights, for sinusoidal and quasi-random surfaces. By comparing the combined standard uncertainty from both approaches, we quantify the contribution of topography fidelity, a key but difficult-to-evaluate characteristic. The proposed method offers a comprehensive understanding of uncertainty in optical surface measurement, leading to improved tolerancing in manufacturing