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Modeling in tribology: recent advances, applications, and open questions
No full textRecent advances in modeling have enhanced our ability to make quantitative predictions for tribological phenomena, thereby unraveling relevant mechanisms. Algorithmic innovations, including those based on multiscale methods and machine learning, have been especially impactful, for example in overcoming long-standing bottlenecks that hinder simulations of systems with strong coupling across disparate scales. However, traditional modeling approaches, such as boundary-element techniques, have also progressed and continue to yield new insights. This article reviews developments from the past decade, examining how both new and established methods have deepened our understanding of experimental results and have furthered theoretical approaches in key tribological areas, including contact mechanics, lubrication, metal friction, and tribo-chemistry. Selected applications, such as tunable interfaces and energy harvesting, illustrate the broad influence of recent developments on the field
AI-assisted living evidence databases for conservation science
No full textLiving evidence databases offer a robust and dynamic alternative to static systematic reviews but require a resilient technical infrastructure for continuous evidence processing. This working paper describes the architecture and implementation of a complete, end-to-end pipeline for this purpose, developed initially for the conservation science domain. Designed to operate on local infrastructure using self-hosted models, the system ingests and normalizes documents from academic publishers, screens them for relevance using a multi-stage process, and extracts structured data according to a predefined schema. Key features include a hybrid retrieval model; a human-AI collaborative process for refining inclusion criteria from complex protocols, and the integration of an established, statistically-principled stopping rule to ensure efficiency. In a baseline evaluation against a prior large-scale manual review, the fully automated pipeline achieved 97% recall and identified a significant number of relevant studies not included in the original review, demonstrating its viability as a foundational tool for maintaining living evidence databases
Run-and-tumble particle with diffusion: boundary local times and the zero-diffusion limit
No full textThe one-dimensional run-and-tumble particle (RTP) is one of the simplest examples of active matter. The persistent nature of an RTP can lead to novel phenomena such as accumulation at walls in the absence of attractive
particle interactions and motility-based phase separation. Most theoretical studies of RTPs are based on the analysis of the forward or backward Kolmogorov
equation, whose solution determines the probability distribution of sample paths. The effects of a confining wall are typically implemented by supplementing the
Kolmogorov equation with some form of non-sticky or sticky boundary condition. However, from a biological perspective, one would like to develop more bio physically motivated models of microorganism-boundary interactions. A starting point for such an approach is to develop a probabilistic theory that allows one to incorporate boundary conditions at the level of individual sample paths.We have previously shown how to achieve this for both non-sticky and sticky partially absorbing boundaries. In this paper we extend the theory to include
the effects of diffusion. One of the non-trivial consequences of combining drift-diffusion with tumbling is that the zero diffusion limit D → 0 is singular in the sense that the number of boundary conditions is doubled when D > 0. We use stochastic calculus to derive the forward Kolmogorov equation for two distinct boundary conditions that reduce, respectively, to non-sticky and sticky boundary conditions in the zero-diffusion limit. In the latter case, it is necessary to include a boundary layer in a neighbourhood of the wall and use singular perturbation theory. We also treat the wall as partially absorbing by assuming that the particle is absorbed when the amount of boundary-particle contact time (discrete or continuous local time) exceeds a quenched random threshold. Finally, we analyse the survival probability and corresponding first-passage time density for absorption by deriving the corresponding backward Kolmogorov equation
Optimisation of low-carbon hydrogen production via sorption enhanced autothermal membrane technology and ammonia cracking
No full textThis PhD thesis presents the development and optimization of innovative hydrogen production technologies for sustainable, low-carbon fuel generation. The research focuses on three key innovations: The Industrial Sorption Enhanced Autothermal Membrane (ISEAM) process for blue hydrogen production, the Hybrid Air-Volt Ammonia Cracker (HAVAC) for centralized ammonia cracking, and a novel on-board ammonia cracker for light-duty fuel cell vehicles. The research methodology is underpinned by rigorous process flowsheeting and numerical modelling techniques, developed to simulate and evaluate the performance of the proposed processes. The modelling framework is validated against existing experimental data and benchmarks reported in peer-reviewed literature, with reference to established studies conducted by reputable research groups in the field. By drawing on this body of experimental work, the reliability and accuracy of the simulation outputs are enhanced, ensuring that the models presented reflect practical operating behaviour and remain grounded in experimentally observed phenomena. The ISEAM process advances blue hydrogen production by integrating membrane separation, sorption-enhanced reforming, and chemical looping combustion technologies. It achieves high-purity hydrogen (99.99%) with a production efficiency of 97.5% and methane conversion rates exceeding 99.9%. Compared to conventional steam methane reforming (SMR), ISEAM shows ≥ 32% improvements in most of the technical parameters that were evaluated and reduces the levelized cost of hydrogen (LCOH) by 37.5% and CO₂ removal costs by 57.5%, offering a cost-effective and sustainable solution for industrial-scale hydrogen production.
The HAVAC process introduces a dual-fuel capability, enabling ammonia cracking to produce hydrogen using either renewable electricity or an autothermal ammonia-air mixture. With ammonia conversion rates of up to 99.4% and hydrogen yields ranging from 84% to 99.5%, HAVAC offers high flexibility and efficiency. Its thermal efficiency of 94-95% outperforms traditional ammonia cracking technologies. The process demonstrates financial viability with a competitive LCOH between 4.73/kg-H₂.Open Acces
X-ray imaging with AI-driven super-resolution deep learning for investigating battery electrode microstructural properties over cycling
No full textRechargeable batteries are promising for transition to clean energy. This study investigates microstructural dynamics of LiNi0.8Mn0.1Co0.1O2 (NMC811)-based cathodes over cycling using X-ray computed tomography (XCT). There is a long-standing imaging challenge of compromising between the large field-of-view (FoV) to be representative of the electrodes and high resolution to observe fine details of individual particles. Here, we provide a framework that mitigates this trade-off by comparing two deep learning models—convolutional neural networks (CNNs) and generative adversarial networks (GANs)—for super-resolution enhancement of the XCT data to achieve both a large FoV (4 times larger) and sub-micron resolution. We fabricated NMC811 cathodes containing different initial porosities (0.46–0.85) and tortuosities (1.24–2.74) by two different methods, directional ice templating (DIT) and dry processing to eliminate toxic organic solvents during fabrication. Micro-cracks inside individual NMC811 secondary particles and shifts in pixel intensity distributions were observed after 100 (dis)charge cycles. The DIT cathode exhibited larger irreversible volume expansion due to the more favorable ion diffusion kinetics and higher active material utilization. Interestingly, the higher pore volume and carbon binder domain (CBD) surrounding the NMC811 particles effectively accommodated the volume expansion, and the DIT cathode exhibited higher capacity retention over cycling than the dry coated cathode that exhibited initial lower porosity and higher tortuosity. A linear regression model was used to determine the correlation among the various microstructural properties such as porosity and tortuosity in the pristine state, and expansion after cycling to develop a framework for predicting the optimal initial microstructure and electrochemical performance over cycling
Applying high‐dimensional propensity scores in a study of inhaled corticosteroids and COVID-19 outcomes
No full textBackground
In pharmacoepidemiologic studies of COVID-19, there were concerns about bias from residual confounding. We investigated the effects of inhaled corticosteroids (ICS) on COVID-19 outcomes, applying high-dimensional propensity scores (HDPS) to adjust for unmeasured confounding.
Methods
We selected patients with chronic obstructive pulmonary disease on 01 March 2020 from Clinical Practice Research Datalink (CPRD) Aurum, comparing ICS/LABA/(+/−LAMA) and LABA/LAMA users. ICS effects on the outcomes COVID-19 hospitalisation and death were assessed through IPT-weighted and unweighted Cox regression. HDPS were estimated from primary care observations, prescriptions and hospitalisations. SNOMED-CT codes and dictionary of medicines and devices codes from CPRD Aurum were mapped to International Classification of Disease 10th revision codes and British National Formulary paragraphs, respectively. We estimated propensity scores (PS) combining prespecified and HDPS covariates, selecting the top 100, 250, 500, 750 and 1000 covariates ranked by confounding potential.
Results
When excluding triple therapy users, conventional PS-weighted estimates showed weak evidence of increased COVID-19 hospitalisation risk among ICS users (HR 1.19 [95% CI: 0.92–1.54]). Results varied slightly based on the number of covariates included in HDPS (HR using 100 HDPS covariates excluding triple therapy 1.01 [95% CI: 0.76–1.33], HR using 250 HDPS covariates excluding triple therapy 1.24 [95% CI: 0.83–1.87]). Conventional PS-weighted models showed weak evidence of a harmful association of ICS with COVID-19 death when excluding triple therapy users (HR 1.24 [95% CI: 0.87–1.75]). HDPS-weighting moved estimates toward the null (HR using 250 HDPS covariates excluding triple therapy 1.08 [95% CI: 0.73–1.59]).
Conclusions
HDPS may have better controlled confounding for COVID-19 deaths in this case. HDPS results can be sensitive to the number of covariates included, highlighting the importance of sensitivity analyses
Optimal transitional mechanisms of incompressible separated shear layers subject to external disturbances
No full textOptimal transitional mechanisms are analysed for an incompressible shear layer developing over a short, pressure gradient-induced laminar separation bubble (LSB) with peak reversed flow of 2 %. Although the bubble remains globally stable, the shear layer destabilises due to the amplification of external time- and spanwise-periodic disturbances. Using linear resolvent analysis, we demonstrate that the pressure gradient modifies boundary layer receptivity, shifting from Tollmien–Schlichting (T-S) waves and streaks in a zero-pressure-gradient environment to Kelvin–Helmholtz (K-H) and centrifugal instabilities in the presence of the LSB. To characterise the nonlinear evolution of these disturbances, we employ the harmonic-balanced Navier–Stokes (N-S) framework, solving the N-S equations in spectral space with a finite number of Fourier harmonics. Additionally, adjoint optimisation is incorporated to identify forcing disturbances that maximise the mean skin friction drag, conveniently chosen as the cost function for the optimisation problem since it is commonly observed to increase in the transitional stage. Compared with attached boundary layers, this transition scenario exhibits both similarities and differences. While oblique T-S instability is replaced by oblique K-H instability, both induce streamwise rotational forcing through the quadratic nonlinearity of the N-S equations. However, in separated boundary layers, centrifugal instability first generates strong streamwise vortices due to multiple centrifugal resolvent modes, which then develop into streaks via lift-up. Finally, we show that the progressive distortion and disintegration of K-H rollers, driven by streamwise vortices, lead to the breakdown of large coherent structures
Diagnostic algorithms for tuberculosis in Europe: insights from the European Reference Laboratory Network for Tuberculosis (ERLTB-Net)
No full textThe reported poor treatment outcomes for extensively drug-resistant tuberculosis (TB) in the European region highlight the urgent need for effective and context-appropriate diagnostic strategies. While the World Health Organisation (WHO) provides model algorithms, these require adaptation to the European Union/European Economic Area (EU/EEA) context, a setting with low TB incidence but high resources. This viewpoint from the European Reference Laboratory Network for TB (ERLTB-Net) proposes a tailored diagnostic algorithm that prioritises the universal use of WHO-recommended molecular rapid diagnostic tests, systematic culture, and whole genome sequencing (WGS). This approach integrates phenotypic drug susceptibility testing strategically and outlines the possible role of targeted next-generation sequencing (tNGS) in the EU/EEA setting. The algorithm also addresses the importance of diagnostic harmonisation, cross-border collaboration, and sustained investment in sequencing capacity. By aligning diagnostic practices with the regional epidemiology and laboratory infrastructure, this stepwise, resource-sensitive approach aims to strengthen TB control, improve treatment outcomes, and guide public health action in the EU/EEA
The crown: rolling splash
No full textThis paper is associated with a poster winner of a 2024 American Physical Society's Division of Fluid Dynamics (DFD) Gallery of Fluid Motion Award for work presented at the DFD Gallery of Fluid Motion. The original poster is available online at the Gallery of Fluid Motion, https://doi.org/10.1103/APS.DFD.2024.GFM.P268551
Demographics of epithelioid trophoblastic tumour and placental site trophoblastic tumour: a 21 year UK population study
No full textBackground
Epithelioid and placental site trophoblastic tumours are rare gestational malignancies which have little detailed information on their population incidence or risk related to maternal age.
Methods
We performed a retrospective UK national population-based study examining all of the cases registered between 2000 and 2020 using the databases at the UK’s two gestational trophoblastic treatment centres at Charing Cross Hospital in London and Weston Park Hospital in Sheffield. The data obtained was compared with the contemporary UK birth and pregnancy statistics.
Results
Over the 21-year study period, there were 132 cases of ETT or PSST. PSTT comprised 57% of the cases, 30% were ETT and 13% had mixed pathology. The combined incidence of ETT and PSTT was 1:118,736 relative to live births and 1:150,872 compared to total viable conceptions. For women aged under 20 the incidence relative to live births was 1:412,488, increasing to 1:188,292 for women 30–34 years, and 1:1,426 for women aged 45 and above. The median interval from the antecedent pregnancy to the time of diagnosis was 15 months (0–288) for the PSTT patients compared to 24 months (0–336) for patients with a diagnosis of ETT.
Conclusions
ETT and PSTT are both rare diagnoses with little detailed information on their demographics. The data in this study indicates a wide range in the interval from the antecedent pregnancy to diagnosis and confirms a close relationship between increasing incidence and rising maternal age.
PLAIN LANGUAGE SUMMARY
Epithelioid and placental site trophoblastic tumours are two similar but rare tumours arising from the cells of pregnancy. Due to their rarity there is little accurate information on the risk of having these diagnoses and how that risk may change with increasing maternal age. In a 21-year UK wide national study we found a total of 132 cases from a total of approximately 19.9 million pregnancies giving an overall risk of 1:150,872.
The risk increased appreciably with rising maternal age increasing from 1:526,349 in women aged under 20 to 1:10,343 for women 45 and over. Despite the rarity the large majority of patients are cured with modern therapy