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Effect of deposit chemistry on the stress corrosion cracking susceptibility of CMSX-10 at 550°C and 700°C
Get PDFTurbine blades of aerogas turbines can be at risk of stress corrosion cracking (SCC) below 700 °C due to the effects of stress, sulphur-containing gases and deposits
that are ingested into the turbine. Therefore, understanding the effect of different deposits on the SCC susceptibility of single-crystal nickel-based superalloys at different temperatures is crucial. This study investigated the effect of NaCl, sea salt and 80/20 mol% Na2SO4/K2SO4 on the SCC susceptibility of CMSX-10 at 550 °C and
700 °C. The results suggest that chlorine-containing salts play an important role in accelerating stress corrosion cracking at 550 °C, where the formation of HCl leads
to the breaking down of the oxide and exposing the base alloy to a sulphidation environment. At 700 °C stress corrosion cracking is accelerated by the mix of sulphates that lead to reduced melting points, where the 80/20 mol% Na2SO4/K2SO4 has shown the highest susceptibility to SCC.This work was supported by Innovate UK under the MALIT project [Grant No. 113180]High Temperature Corrosion of Material
Mycotoxin contamination in plant-based beverages and meat alternatives: a survey of the UK market
Get PDFThe study aimed to investigate the natural occurrence and co-occurrence of nineteen mycotoxins in 212 plant-based products collected from several retailers in the UK, including plant-based meat alternatives (PBMAs) (n = 92) and plant-based beverages (PBBs) (n = 120), using liquid chromatography coupled to mass spectrometry in tandem (LC-MS/MS). Mycotoxins included in the analysis were aflatoxins (AFB1, AFB2, AFG1, AFG2), ochratoxin A (OTA), zearalenone (ZEN), fumonisins (FB1, FB2), deoxynivalenol (DON), HT-2/T-2, enniatins (ENNB, ENNB1, ENNA, ENNA1), beauvericin (BEA), alternariol (AOH), alternariol monomethyl ether (AME), and tentoxin (TEN). A high prevalence of emerging Fusarium toxins such as ENNA (93.5 %), ENNA1 (93.5 %), and BEA (98.9 %), and the Alternaria toxins AOH (75.0 %), AME (85.9 %), and TEN (77.2 %), was found in the PBMAs. Similarly, BEA, ENNB, and ENNA were frequently found in the PBBs of the study, with prevalence values ranging from 71.9 % to 100 %. In general, all mycotoxins were found in significantly higher concentrations in the PBMAs compared to the PBBs. The high co-occurrence observed across the samples suggests that food business operators should prioritize the management of mycotoxins in plant-based products as an integral part of their food safety systems. Moreover, further monitoring studies should be conducted to assess the potential risks associated with the consumption of plant-based products, considering the current dietary habits of the population.This work was carried out under the Horizon Europe FunShield4Med project (HORIZON-WIDERA-2021-ACCESS-03) Grant Agreement No 101079173 funded by the European Union. This research is also part of the PRISMA project which is supported by the European Union's Horizon Europe research and innovation programme under the Marie Sklodowska-Curie Grant Agreement No. 101110615.Food Contro
Damage mechanisms in solid particle impact and erosion testing of thermal barrier coatings
Get PDFThe ability of both cyclic and randomly spatially-distributed impact tests of columnar EB-PVD ceramic thermal barrier coating (TBC) systems with yttria stabilised zirconia (YSZ) and gadolinium zirconate (GZO) topcoats to simulate their behaviour in solid particle erosion tests has been investigated. The impact tests were able to replicate the main mechanisms and surface morphology in the erosion tests although there was more compaction in the impact tests. Densification below impact craters on YSZ and sub-surface cracking between the dense layer and the un-densified columns were revealed by focussed ion beam milling. Cracking over several columns and break-up of the columnar structure was observed in the impact and erosion tests on GZO. Clear differences in TBC erosion rate, with GZO being much less resistant to erosion, were replicated in the cyclic and randomly spatially-distributed micro-impact tests.Support from Innovate UK under Smart Award project #10020751, High temperature tools for designing sustainable erosion resistant coatings, is gratefully acknowledgedSurface and Coatings Technolog
Exploring unstable approaches in aviation: utilising functional resonance analysis method
No full textUnstable approaches are one of the main safety concerns that contribute to approach and landing accidents. The International Air Transport Association reports that, between 2012 and 2016, 61% of accidents occurred during the approach and landing phase, of which 16% involved unstable approaches. This study addresses this issue by applying the Functional Resonance Analysis Method to examine the dynamics of stable approaches. A total of 195 aviation safety reports, which referred to near-miss data from a single airline, were used in the analysis to identify both actual and aggregated variability. The findings revealed that variability mainly occurred in the following functions: control speed, configure aircraft for landing, communicate with air traffic control and manage flight paths. Effective communication, coordination and collaboration, as well as monitoring, briefings and checklists, were key factors in managing the variability of a stable approach. The study reveals how adopting a perspective of ‘how things go right’ provides insightful findings regarding approach stability, complementing traditional approaches focused on ‘what went wrong’. This study also highlights the value of utilising the Functional Resonance Analysis Method to analyse near-miss data and uncover systemic patterns in everyday flight operations.The Aeronautical Journa
Towards a circular economy in lithium ion battery recycling by integrating microbial processes with electrowinning and precipitation for sustainable metal recovery
No full textWith increased use of Lithium-Ion Batteries (LIBs) and the scarcity of some of their components, their recycling and the recovery of their metals have become essential. In this work, an indirect bioleaching process was designed to solubilise metals from LIB black mass using biogenic acid generated in a stirred tank bioreactor. The biogenic acid was used in addition to H2O2 as a reductant for improved solubilisation, and influential factors including pulp density, temperature, and concentration of H2O2 were optimised. The best results were achieved at 55 °C, with a pulp density of 7.5% (w/v) and 0.5% (v/v) H2O2, which resulted in 82% Li, 32% Ni, 24% Co and 21% Mn solubilisation in 5 min of the process. However, over time transition metals in the leachate did not remain in solution, due to their adsorption onto the carbon content of the black mass. To selectively recover solubilized Co, Ni, Mn, and Li from the leachate, a combined process of electrowinning and precipitation was applied to the leachate, leading to the successful electroplating of Co, Ni and Mn with 100%, 100% and 97.2% of solubilised metals respectively, while 40% of the Li was recovered by precipitation following the addition of sodium carbonate. These results constitute a promising step toward closing the loop for the sustainable selective recovery of critical metals used in LIB manufacturing and suggest the next targets to improved bioleaching efficiency.Journal of Environmental Managemen
Attention-based multi-head feature-fusion network: a generalised method for hot deformation behaviour prediction in low-alloy steels
No full textModelling hot deformation of low alloy steels is important for optimising processing efficiency and cost reduction. Existing approaches lack generalisation as they primarily focus on single steel grades, ignoring chemical composition. To address this, a dataset comprising 58 distinct low-alloy steels and an Attention-Based Multi-Head Feature Fusion Network (AMHFnet) has been established and proposed. AMHFnet uses multi-head residual modules and a head weighting mechanism to adaptively learn high-dimensional representations of both chemical composition and processing variables, which are then fused and processed via a feature filtering and repeat step decision mechanism to predict hot deformation response. It demonstrated superior accuracy and generalisability in 10-fold cross-validation compared to existing decision tree-based models and state-of-the-art deep learning models. Ablation studies demonstrate the effectiveness of individual components of the network. An investigation of the effect of carbon demonstrated that AMHFnet could reliably reflect elemental effects on hot deformation behaviour, further validating its reliability and applicability. The model successfully captures work hardening behaviour and dynamic recrystallisation for most compositions. By accurately predicting hot deformation behaviour across diverse low-alloy steels, this work can simplify the alloy-composition design process and target the experimental testing.Engineering Applications of Artificial Intelligenc
Physics-informed machine learning for near real-time stress prediction on a structural component: application for landing gears
No full textLightweight design constitutes a pivotal research and development objective for next-generation landing gear systems. Nevertheless, achieving reduced weight while maintaining structural safety and reliability presents considerable challenges. The establishment of a digital twin (DT) for structural health monitoring (SHM) offers a promising approach to address these concerns across the design, testing, and operational lifecycle of landing gears. In this study, we develop a physics-informed neural network (PINN) model for near real-time stress prediction on the drag strut of a nose landing gear (NLG), specifically for an A320-type aircraft, serving as a foundational component of a DT system. The proposed PINN framework directly outputs displacement fields while deriving stresses as secondary quantities, effectively incorporating the fundamental equations of linear elasticity into the loss function. Displacement boundary conditions, informed by finite element method (FEM) simulations, are integrated as penalty terms to enhance trainability and physical consistency. The training dataset is constructed using load cases statistically representative of actual landing gear operations, with high-fidelity FEM providing corresponding displacement and stress references. The model demonstrates strong predictive accuracy, with relative errors between 5% and 7% compared to FEM results, and significantly outperforms both pure stress-output PINNs and conventional deep neural networks (DNNs). Moreover, the trained PINN achieves inference times within seconds under time-varying loads, highlighting its capability for near real-time stress monitoring. This work underscores the potential of physics-informed machine learning for enhancing DT-enabled SHM systems in safety-critical aerospace structures.Engineering Applications of Artificial Intelligenc
Iron in copper metallurgy at the dawn of the Iron Age: insights on iron invention from a mining and smelting site in the Caucasus
No full textData on analyses of slags, ores, and fluxes is provided in the supplementary information and in an open access dataset published on the Harvard Dataverse (Erb-Satullo and Klymchuk, 2025).
Appendix A. Supplementary data. Supplementary data to this article can be found on the publisher web page.Despite enormous interest in the origins of the iron, the world's quintessential industrial metal, the technological foundations of the invention and innovation of extractive iron metallurgy remain unclear. While fundamental aspects of geology and thermodynamics favor a model for the invention of iron by copper smelters, empirical archaeological evidence to support this model is lacking. Reanalysis of the smelting workshop at Kvemo Bolnisi, originally published as an iron smelting site in the 1960s and dated to the late 2nd millennium BC, offers insights by which copper smelters recognized and experimented with iron oxides. Chemical and microscopic analysis of slags and minerals samples via optical microscopy and SEM-EDS conclusively shows that metalworkers at the site were smelting copper rather than iron. However, our analyses, coupled with a reassessment of the excavation report, show that iron oxides were deliberately stockpiled and added to the furnace as a separate component of the charge to flux the silica-rich host rock. These discoveries make Kvemo Bolnisi arguably the earliest unequivocal example of the deliberate use iron oxide fluxes in copper metallurgy. The knowledge and behaviors reflected in the Kvemo Bolnisi copper smelting technology have important implications for theories about the invention of iron metallurgy by copper smelters.This research was supported by the British Institute at Ankara, the Gerda Henkel Foundation (AZ 33/F/22), and the American Research Institute of the South Caucasus, and the Teschmacher Fund.Journal of Archaeological Scienc
What is Environmental Biotechnology? although widely applied, a clear definition of the term is still needed
No full textThe term Environmental Biotechnology is widely used, but lacks a universally accepted definition, with varying interpretations across disciplines and sectors leading to challenges in funding, policy formulation, and interdisciplinary collaboration. Through a literature review and engagement activities, this study examines existing definitions, identifies key areas of divergence, and explores pathways toward a more cohesive understanding. Findings reveal a spectrum of valid interpretations, often shaped by specific contexts, with researchers generally recognising a shared conceptual framework within their own subfields but encountering ambiguities across subject boundaries. Common points of difference include whether Environmental Biotechnology is restricted to microorganisms or encompasses other biological systems. Some understandings reflect sector-specific needs, contributing to fragmentation, though a broader approach could strengthen the field’s identity by providing a unifying framework, mapping overlaps with related fields such as Industrial Biotechnology. A working definition is proposed for Environmental Biotechnology as the use of biologically mediated systems for environmental protection and bioremediation, incorporating resource recovery and bioenergy production where these enhance system sustainability. Importantly, it was recognised that any definition must remain adaptable, reflecting the evolving nature of both the science and its applications.The authors gratefully acknowledge the support of the Biotechnology and Biological Sciences Research Council (BBSRC) and the Physical Sciences Research Council (EPSRC) through grant number BB/S009795/1 (‘Environmental Biotechnology Network’).Environment
Real‐time terrain traversability analysis and mapping for autonomous robotics in dynamic environments: fusing appearance‐ and geometry‐based approaches
No full textThis paper presents advanced methodologies for real‐time terrain analysis and mapping in autonomous robotic systems. The focus is on appearance‐based terrain traversability analysis and geometric‐based terrain traceability analysis. In the appearance‐based approach, an enhanced segmentation model using pixel‐based augmentation and 13 unique classes is proposed for reliable terrain classification. Semantic images are projected onto a 2.5D map by transforming two‐dimensional image data into a three‐dimensional coordinate system. The geometric‐based approach involves depth estimation from stereo cameras, employing three Zed‐2 cameras and the Depth Sensing application programming interface. The research contributes to improved perception and decision‐making capabilities of autonomous robots operating in complex and dynamic environments and also provides a new comprehensive data set named CranfieldTerra. Experimental results validate the effectiveness of the proposed methodologies, demonstrating their potential in various applications, such as search and rescue, agriculture, and exploration. This study establishes a foundation for further advancements in autonomous robotics, enhancing their ability to navigate safely and efficiently in challenging terrains.The first author acknowledges the Republic of Turkey, Ministry of National Education (YLYS), for supporting the studies under PhD scholarship ref:U9BYTAB2LDGA7LKJournal of Field Robotic