Securing defense critical minerals: challenges and U.S. strategic responses in an evolving geopolitical landscape

The growing dependence on critical minerals (CMs) for advanced military technologies presents significant and escalating challenges for the United States (U.S.) and its allies. As global competition intensifies and supply chains remain vulnerable to geopolitical disruptions, securing a stable supply of defense CMs has become a top strategic priority. This article identifies key defense CMs, emphasizing their dual-use nature and the risks posed by reliance on adversarial nations such as China and Russia. It analyzes U.S. strategic responses and offers recommendations for balancing national security, economic feasibility, and sustainability in managing defense CM supply chains using a comprehensive approach.Comparative Strateg

Beyond survival …

The purpose of this closing paper is to “draw threads” from the collection of papers presented in this Special Issue, with the aim of exploring the defence industrialisation experiences of small and medium powers. Structurally, the paper begins by examining the challenges Tier Two and Three nations face in developing and sustaining defence industries. Attention then switches to assessing the coping strategies these countries adopt in seeking to overcome the limitations imposed by constricted scale and defence economic infrastructure. Government has an important role to play in addressing trade-offs linked to the autonomy, dependence, and efficiency trilemma. The aim is to ensure that the required degree of indigenous defence industrial capacity offers an acceptable level of sovereignty and manufacturing efficiency that is also affordable. The final section speculates on the future defence industrial opportunities and threats Tier Two and Three states are likely to confront. Whatever the future holds, there is a sense from the case studies presented that small and medium powers can survive the constraints of relative smallness and prosper.Defence Studie

Selective exploration and information gathering in search and rescue using hierarchical learning guided by natural language input

In recent years, robots and autonomous systems have become increasingly integral to our daily lives, offering solutions to complex problems across various domains. Their application in search and rescue (SAR) operations, however, presents unique challenges. Comprehensively exploring the disaster-stricken area is often infeasible due to the vastness of the terrain, transformed environment, and the time constraints involved. Traditional robotic systems typically operate on predefined search patterns and lack the ability to incorporate and exploit ground truths provided by human stakeholders, which can be the key to speeding up the learning process and enhancing triage. Addressing this gap, we introduce a system that integrates social interaction via large language models (LLMs) with a hierarchical reinforcement learning (HRL) framework. The proposed system is designed to translate verbal inputs from human stakeholders into actionable RL insights and adjust its search strategy. By leveraging human-provided information through LLMs and structuring task execution through HRL, our approach not only bridges the gap between autonomous capabilities and human intelligence but also significantly improves the agent's learning efficiency and decision-making process in environments characterised by long horizons and sparse rewards.2024 IEEE International Conference on Systems, Man, and Cybernetics (SMC

Environmental impact lifecycle assessment of green sand moulding in foundries

The metal casting industry faces significant challenges in reducing its environmental impact. This paper presents a study aimed at evaluating and minimizing the environmental effects of green sand moulding processes. The project uses advanced Life Cycle Assessment (LCA) methodologies, specifically the ReCiPe method, to analyse the entire lifecycle of moulding sand, from extraction to disposal. The study measures emissions during the metal pouring process and identifies key contributors to greenhouse gas emissions. By incorporating sustainable binder technologies and optimizing sand reclamation processes, the project suggests practical strategies for reducing the carbon footprint of foundries. The outcomes include a detailed lifecycle inventory report, an impact assessment highlighting critical areas for intervention, and a practical guide for implementing emission reduction strategies. This research supports global net zero targets and offers a model for sustainable practices in the foundry industry. The findings provide essential insights and feasible strategies for foundries to achieve substantial environmental impact reductions, contributing to a more sustainable future in metal casting. This comprehensive approach ensures that the proposed solutions are both effective and scalable, aligning with broader environmental sustainability goals.The authors thank and acknowledge Foseco International Ltd for their support and contribution to this research.Light Metals 2025. TMS 2025 Annual Meeting & Exhibitio

Battery pack technological considerations for hybrid-electric regional aircraft feasibility

This paper presents a study of the effects of the durability and level of energy storage technology on energy management strategies and the performance of hybrid electric turboprops. The results highlight the key role of battery energy density on the durability of the battery pack and the viability of the concept of hybrid electric aircraft. Additionally, the trade-off between zero-day environmental compatibility and battery lifetime is identified, caused by the size of the pack. The effective energy density would decrease with the aging of the cells, leaving a significant inert mass and increasing fuel consumption. Optimal energy management strategies are suggested in light of this new information. Higher specific energy of the pack would mitigate this aspect, along with a reduction in fuel consumption and NOx emissions. Indeed, the improvement of environmental compatibility was found to be nonlinear with a positive rate, suggesting high returns in investing in great improvements in energy density over a gradual increase. This result relates to the results of the statistical technological forecast presented in this study, which, without an increase in funding, predicts the availability of the specific energy required to match the fuel-only baseline in the 2040–2050 decade.This project has received funding from the European Union’s Horizon 2020 Research and Innovation programme under Grant Agreement No 875551.The Aeronautical Journa

Rapid decarbonization requires industrial efficiency

The potential of effciency to support decarbonization is underestimated and overlooked relative to more expensive and intensive actions. Implementing resource and energy effciency strategies in industry could deliver rapid and cost-effective decarbonization.Nature Reviews Clean Technolog

Seakeeping analysis of catamaran and barge floats for floating solar arrays: a CFD study with experimental validation

Whilst floating photovoltaic (FPV) is gaining attention for ocean-based applications, their motion response in waves significantly affects structural integrity and power generation efficiency. In particular, FPV is expected to operate in arrays consisting of extensive solar panels, and thus, floating solar systems are required to be analysed with neighbouring devices connected by joints. This study investigates the seakeeping characteristics of two FPV systems in arrays, comparing conventional barge floats with twin-hull (catamaran) floats under various wave conditions. A systematic investigation using Computational Fluid Dynamics (CFD) was conducted for the hydrodynamic response of both isoslated-single-floater and multi-body (1 × 3) configurations in regular waves, with non-dimentional wavelength ratio (λ/L) 1.62-4.27 to the floater length. Wave tank experiments were conducted to validate the CFD model, showing agreement with less than 10% discrepancies. The study focused on the multi-body behavior of heave and pitch Response Amplitude Operators (RAOs) and mooring line forces. Results show that the multi-catamaran configuration exhibited lower heave RAOs (by approximately 20°%) compared to multi-barge pontoons in long waves (λ/L > 2.47) while maintaining similar pitch responses. However, in shorter waves (λ/L < 2), the catamaran configuration showed up to 15% higher RAOs than barge's. The multi-body arrangement demonstrated significant array effects, with the leading float experiencing 30% higher mooring loads than the trailing float. The leading float also experiences the highest mooring forces. As the wavelength ratio increases, the barge float's front mooring force increases dramatically, reaching nearly twice that of the catamaran at a ratio of 4.27. These findings align with the RAO results, indicating that the barge float is more wave-sensitive under long-wavelength conditions, whereas the catamaran demonstrates superior station-keeping with lower mooring forces. This work provides quantitative guidance for selecting appropriate floater forms for FPV applications based on expected wave conditions.L.H. acknowledges grants received from Innovate UK (No. 10048187, 10079774, 10081314), the Royal Society (IEC∖NSFC∖223253, RG∖R2∖232462) and UK Department for Transport (TRIG2023 – No. 30066).Ocean Engineerin

Unifying nucleation and crystal growth mechanisms in membrane crystallisation

While several mechanisms have been proposed to describe crystallisation processes in membrane distillation, it has not been possible to provide a definitive description since the nucleation kinetics are difficult to measure. This study therefore introduced non-invasive techniques to measure induction time within two discrete domains (the membrane surface and bulk solution) and was complemented by the introduction of a modified power law relation between supersaturation and induction time, that enables mass and heat transfer processes in the boundary layer to be directly related to classical nucleation theory (CNT). Temperature (T, 45–60 °C) and temperature difference (ΔT, 15–30 °C) were used to adjust boundary layer properties, which established a log-linear relation between the nucleation rate and the supersaturation level in the boundary layer at induction, which is characteristic of CNT. Crystal size distribution analysis demonstrated how nucleation rate and crystal growth rate could be adjusted using ΔT and T respectively. Consequently, ΔT and T can be used collectively to fix the supersaturation set point within the boundary layer to achieve the preferred crystal morphology. However, at higher supersaturation levels, scaling was observed. Discrimination of the primary nucleation mechanisms, using measured induction times, revealed scaling to be formed homogeneously, which indicates exposure of the pores to extremely high supersaturation levels. Morphological analysis of scaling indicated growth to be dominated by secondary nucleation mechanisms, that resulted in a habit that is distinctive from the crystal phase formed in the bulk solution. From this analysis, a critical supersaturation threshold was identified, below which kinetically controlled scaling can be ‘switched-off’, leaving crystals to form solely in the bulk solution comprising the preferred cubic morphology. This study serves to unify understanding on nucleation and growth mechanisms to enhance control over crystallisation in membrane systems.This research was financially supported by European Research Council Starting Grant 714080, ‘Sustainable chemical alternatives for reuse in the circular economy’ (SCARCE).Journal of Membrane Scienc

Phenotyping the nutritional status of crops using proximal and remote sensing techniques

Understanding the nutritional needs of crops is crucial for ensuring their health and maximising yield. However, the capability to accurately measure relevant physical characteristics (phenotypes) of important crops in response to complex nutrient stresses is limited. For crop breeders and researchers, the existing capacity to characterise crops with adequate precision, detail and efficiency is hindering significant progress in crop development. In this PhD thesis, the use of advanced sensing techniques to assess the nutritional status of African crops was explored, focusing on three main objectives. First, the use of a handheld proximal sensor was investigated to evaluate the spectral properties of quinoa and cowpea crops grown under different N and P supplies in controlled glasshouse conditions (Chapter 3). By analysing these spectral properties, the aim was to identify spectral indices that could show early signs of N and P stress separately in the plants. These stress indicators were related to the overall performance of the crops. Spectral indices were found that could distinguish between N and P stress at the early growth stage of the crops. However, identifying spectral indices for P stress was limited, particularly in cowpea due to the shorter wavelength range of the handheld device. The results showed significant relationships between the spectral indices and traits related to the morphology, physiology and agronomy of the crops. Second, it was demonstrated that different levels of N impact the drought responses of spring wheat (Chapter 4). By evaluating morpho-physiological changes in the plants under high N and low N conditions, an understanding of how spectral reflectance measured at the leaf level could help distinguish between combined and complex stresses such as drought and nutrient deficiency was investigated. The results showed a greater amplitude of drought response in plants that were supplied with high N compared to low N levels, with interactive effects on many morphological and physiological traits. Out of a group of 39 different SRIs, only the Renormalised Difference Vegetation Index (RDVI) and the Red Difference Vegetation Index (rDVI_790) showed better accuracy in detecting drought stress. The results also revealed that indices sensitive to chlorophyll levels, such as the chlorophyll Index (mNDblue_730), Greenness Index (G) and Lichtenthaler Index (Lic2), as well as red-edge indices like Modified Red-Edge Simple Ratio (MRESR), chlorophyll Index Red-Edge (CIrededge) and Normalised Difference Red-Edge (NDRE), were more accurate in detecting N stress. Lastly, the effectiveness of using spectral information from images collected from a drone and spectral reflectance measured with proximal sensors on the ground were compared for detecting N stress in winter wheat under field conditions (Chapter 5). By comparing these two sensing methods, it was assessed which approach is more accurate, reliable and cost- effective for assessing the N nutritional needs of the crop in real-world agricultural settings. The results indicated that the NDVI measured on the ground at the leaf level could accurately detect the small changes in N levels earlier compared to the drone NDVI and canopy level NDVI and for assessing the agronomic performance of winter wheat. Overall, this PhD research sheds new light on the potential of advanced sensing techniques to improve crop management practices and enhance agricultural productivity by providing timely and accurate information about the nutritional status of the studied crops.PhD in Environment and Agrifoo

Wear modeling and friction-induced noise: a review

Wear and friction-induced noise are pivotal tribological phenomena that significantly influence the longevity and efficiency of mechanical systems. This review synthesizes current research on wear modeling and friction-induced noise, exploring their mechanisms, influencing factors, and predictive challenges. Wear modeling encompasses a range of approaches, from traditional methods such as the Archard equation to more advanced numerical and machine learning techniques. These models address diverse mechanisms—adhesive, abrasive, and fatigue wear—which are shaped by material properties, surface roughness, and environmental conditions. Friction-induced noise, arising from stick-slip, sprag-slip, and mode-coupling, is influenced by surface states, damping, and operational parameters. Crucially, wear and noise are interlinked. Wear reshapes surfaces and dynamics, thereby modulating noise, while noise can serve as a diagnostic tool for wear progression. Yet, existing models often isolate these phenomena, neglecting their synergy and impeding accurate system-life predictions. This review highlights this gap and advocates for the development of integrated wear-noise models, harnessing multiscale simulations, advanced computation, and empirical validation. The development of such models has the potential to significantly enhance the accuracy of durability and acoustic performance predictions. They offer a holistic framework that captures the dynamic interplay between surface degradation and noise generation. This framework is essential for advancing non-invasive detection technologies in industries such as automotive, aerospace, and manufacturing. In these sectors, addressing these dual challenges is crucial for enhancing performance, safety, and efficiency.wearFrictio