‘Greening’ the UK: a comparative study of heat pumps and hydrogen boilers in residential heating

This article belongs to the Special Issue Energy Transition: Interaction of Gas/Hydrogen and Electricity SystemsWith a key policy decision on the role of hydrogen boilers expected by 2026, the UK is at a strategic crossroads in implementing its Heat and Buildings Strategy. This study evaluates the relative advantages of hydrogen boilers and heat pumps in residential heating, focusing on their impact on national energy demand, which is a critical factor in achieving full decarbonisation by 2050. Using the End-state Decarbonisation Resource Analysis framework, this study demonstrates that electrification with widespread heat pumps could reduce current residential primary energy demand by over 53%, whereas a hydrogen boiler-dominant pathway could increase demand by 42%. When translated into generation and infrastructure requirements, the hydrogen pathway would demand significantly more resources than the heat pump alternative. Incorporating heat pumps into the electrification strategy would make the delivery of net-zero targets more achievable. Notably, heat pumps could deliver nearly six times higher economic benefits than hydrogen, while requiring only 67% of investment needed for additional generation assets. These findings support prioritising heat pumps over hydrogen boilers in the UK’s national residential decarbonisation strategy.Energie

Scalable and sustainable cellulose xerogels for high-capacity enrichment of per- and polyfluoroalkyl substances

The phase-out of long chain per- and polyfluoroalkyl substances (PFAS) has accelerated the adoption of alternative emerging PFAS, posing a dual pollution challenge with persistent long-chain residues and their substitutes unclear fate in water treatment. Herein, we develop a scalable and closed-loop strategy producing aminated cellulose xerogel (CNPK) for PFAS removal. CNPK demonstrates excellent mechanical strength (1.96 MPa) and superior PFAS adsorption capacities (3.26 g−1 HFPO-TrA, 1.82 g−1 PFOA, 2.14 g−1 HFPO-DA, 1.27 g−1 PFHxA, 1.02 g−1 PFBA and 1.01 g−1 PFPrA) at pH 3. Its ability to absorb several times its own weight of PFAS is orders of magnitude higher than that of traditional adsorbents. In multi-component systems, the enhanced kinetics and affinity for short/ultra-short chain PFAS facilitate their near-complete removal. This is due to the preferential capture of long chains that provide additional van der Waals (vdW) interactions to accelerate short/ultra-chain adsorption. After five consecutive cycles, CNPK still achieves removal rates of 82%-99% for six types of PFAS and can be dissolved and reproduced. The proof-of-concept filter column achieves over 95% removal for short/ultra-short chain PFAS. The life cycle assessment (LCA) highlights xerogels having lower carbon footprint (161.28–161.71 kg CO2eq kg−1 PFAS) compared to most carbon-based adsorbents. Overall, this xerogel strategy tackles the urgent PFAS contamination through high-capacity enrichment under the principles of the circular economy.This work was supported by the “Pioneer” and “Leading Goose” R&D Program of Zhejiang Province (2024C03112, 2024C03233).Water Researc

An innovative digital liquid metal manufacturing method for aerospace applications: incorporating life cycle assessment for sustainability

The Ultra Clean Cast (UCC) system presents an innovative approach to aerospace manufacturing by prioritizing component quality and manufacturing repeatability. It incorporates a cradle-to-gate life cycle assessment to highlight its additional environmental benefits, with a greater focus on enhancing sustainability. This novel approach improves upon traditional shape-casting by maintaining the high cleanliness of melt metal, critical for aluminum alloys, and difficult to achieve in general for aerospace parts, under varied conditions. By providing a sustainable, cost-efficient route for fabricating complex components, UCC is adaptable across aerospace platforms and evaluates the use of recycled aluminum, supporting the sector’s shift towards a circular economy. This paper outlines the UCC system’s integration of technological advancements with environmental responsibility, incorporating recycled aluminium raw material, material manufacturing, and product manufacturing stages. This system provides a new benchmark for environmentally friendly aircraft manufacturing by outlining process improvements and their implications for industry sustainability and efficiency. The findings highlight UCCs potential to affect aerospace manufacturing in the future, combining high-quality output with environmental considerations.The authors gratefully acknowledge the funding by the Ultra Clean Cast DLMM Program No 10065261.20th Global Conference on Sustainable Manufacturing (GCSM)Lecture Notes in Mechanical Engineerin

Random wavelet kernels for interpretable fault diagnosis in industrial systems

Deep learning is a powerful method for fault diagnosis, but its "black-box" nature raises concerns in critical applications. This paper presents an interpretable, lightweight method combining random convolution kernel transformation (ROCKET) with wavelet kernels, which offer systematic time-frequency analysis and intuitive insights. Principal component analysis (PCA) is used to extract relevant patterns, forming a health indicator that guides maintenance decisions. A case study on linear actuator fault diagnosis demonstrates the method's balance of interpretability and computational efficiency, making it a valuable tool for reliable asset health monitoring in resource-limited settings.Engineering and Physical Sciences Research Council (EPSRC)The research was partially supported with EPSRC funding (EP/P027121/1).CIRP Annal

Human factors integration in complex systems: awareness, challenges and strategies

Human Factors Integration (HFI) is crucial for the development of complex systems, ensuring both effectiveness and safety. This research presents a case study on HFI awareness and implementation in a missile and guided weapons development company, focusing on the application of HFI principles, the challenges faced, and potential areas for improvement. Semi-structured interviews were conducted with twelve respondents across various roles in the company, and thematic analysis was used to analyse interview data. Key themes were identified concerning HFI awareness, organisational dynamics and practical challenges. The findings revealed significant gaps in formal HFI training, limited integration of HFI into project specifications and inconsistent end-user involvement. Organisational and cultural resistance hindered HFI due to cost and timeline constraints. The study suggests that early integration of HFI into the Systems Engineering process, alongside enhanced training programmes and a cultural shift towards prioritising HF, are essential for overcoming these challenges.Ergonomic

Atmospheric pressure plasma etching of Ti-6Al-4 V using SF6 etchant

Atmospheric pressure plasma (APP) etching has been developed recently into a manufacturing technique for silicon-based materials used for large optical lenses. However, there are few reports published regarding APP etching of non-silicon-based materials. We report here the development of an APP process using SF6 for the etching of Ti-6Al-4 V metal alloy. Ti-6Al-4V is extensively used in aerospace and biomedical fields for its excellent properties; however, these properties also make it difficult to machine. Current techniques such as precision grinding and laser polishing can be slow, energy intensive, and cause damages and defects which reduce the lifetime of vital components. The results in this paper demonstrate effective material removal and little surface damage by APP etching of Ti-6Al-4V. Material removal rates between 0.5 and 2 mm3 min−1 were obtained, and the proposed material removal mechanism is through the formation of volatile VFx and TiF4. These results show that APP etching is a promising technique for surface finishing of Ti-6Al-4V, particularly for large- and complex-shaped components.This work was supported by EPSRC Centre for Doctoral Training in Ultra Precision (Grant no. EP/L016567/1) and the Manufacturing Technology Centre Ltd.Journal of Materials Science: Materials in Engineerin

A standardized comparative framework for machine learning techniques in lithium-ion battery state of health estimation

The accurate estimation of lithium-ion battery State of Health (SOH) is essential for enhancing performance, safety, and lifecycle management in modern energy systems. While numerous individual studies have explored machine learning approaches for SOH prediction, a systematic comparative analysis using consistent experimental protocols and rigorous cross-validation remains limited. This study addresses this gap by presenting the first comprehensive comparison of three advanced machine learning models—Extreme Gradient Boosting (XGBoost), Random Forest, and Support Vector Machine (SVM)—using a standardized experimental framework with NASA battery datasets. Our novel contribution lies in implementing a unified training-testing protocol using battery #5 for training and batteries #6, #7, and #18 for validation, combined with systematic hyperparameter optimization through grid search and k-fold cross-validation. Key improvements include: (1) first standardized one-to-many validation protocol ensuring cross-battery generalization assessment that eliminates the data splitting limitations of previous comparative studies, (2) unified hyperparameter optimization methodology applied identically across all algorithms, eliminating the confounding effects of inconsistent parameter tuning that have biased previous comparisons, and (3) establishment of quantitative performance benchmarks providing evidence-based model selection criteria for practical Battery Management System (BMS) applications. The XGBoost model achieved superior performance with MAE of 0.016 and MSE of 0.000347, establishing empirical benchmarks for model selection in battery health diagnostics through our systematic comparative methodology. This work provides the first standardized comparative framework for SOH estimation, offering evidence-based guidance for BMS implementations and advancing the field toward more rigorous and replicable research practices in battery prognostics.Future Batterie

Key elements to navigate sustainable product development in aerospace

Product development is critical for sustainable development, yet sustainable design practices remain under-implemented in the industry. This paper explores the aerospace sector, addressing its specific barriers and enablers to sustainable design. Through a comprehensive literature review, group discussions, and expert group interviews, this study introduces an impact model with essential elements for enabling sustainable product development in aerospace and explains their causal relations. Five key elements were identified: business drive, sustainability implementation, knowledge, ownership, and collaboration. In addition to the impact model, the paper discusses aerospace-specific challenges and opportunities for sustainable product development. Findings from this study offer a practical framework for practitioners and researchers to plan and implement interventions in organizations.We sincerely acknowledge the Swedish Innovation Agency Vinnova for funding this research, the focus group discussion participants at the EASN conference 2024, and GKN Aerospace and SAAB for their active participation.ICED25 - 25th International Conference on Engineering DesignProceedings of the Design Societ

Arsenic contamination of rainfed versus irrigated rice

Arsenic (As) contamination of rice remains a major human health issue in Asia. Most research has been on irrigated rice. However much of the projected increase in global rice demand over coming decades must be met by rainfed lowland systems, for which As relations are poorly understood. We present the most comprehensive survey to date of As in rice in farmers’ fields across Bangladesh, covering both irrigated and rainfed systems. We collected rice grain and soil at 943 sites in the three rice growing seasons: irrigated Boro, rainfed Aus, and longer-duration rainfed Aman. Grain As concentrations increased in the order Aman ≪ Boro < Aus with 2, 25 and 41 % of the sites exceeding permitted thresholds, respectively. The greater concentration in Aus than Boro challenges the accepted wisdom that contaminated irrigation water is the main source of As. The main growth and grain filling periods, when most As is taken up, coincide in Aus with the peak of the monsoon rains, suggesting a link between rainfall and high grain As. We suggest this is due to stronger soil reducing conditions and hence As solubility during peak rainfall. We discuss implications for rainfed lowland rice across Asia and mitigation options.This research was funded by a grant from the UK's Biotechnology and Biological Sciences Research Council ‘Metal contamination of rice supplies in Asia’ (Grant Ref. BB/P02274X/1).Environmental Pollutio

High-precision machining behavior of the single crystal scintillator, bismuth germanate (Bi4Ge5O12)

This study focuses on understanding the machinability of a single-crystal scintillator, Bismuth Germanate (BGO), a material widely used in Time-of-Flight Positron Emission Tomography (ToF-PET). The micromachining process of such a hard, brittle material presents several challenges, particularly in maintaining surface integrity without inducing fractures or microcracks. In this work, we employed the Johnson-Holmquist 2 (JH-2) material model to simulate the micro-milling process of BGO. Experimental data from quasi-static uniaxial compression and split tests were used to estimate the key parameters for the JH-2 model. The simulation results closely aligned with experimental outcomes, confirming the reliability of the model in capturing the mechanical behavior of BGO under stress. Simulations were conducted with different machining parameters, successfully replicating the conditions observed in practical machining tests. Our findings demonstrate the impact of feed rate and depth of cut on the machinability of BGO, validating the use of the JH-2 model of this material. Looking ahead, this robust computational framework offers the potential to further optimize the machining process, ultimately enabling the production of high-performance heterostructures for scintillator applications in TOF-PET.Engineering and Physical Sciences Research Council (EPSRC)This work was supported by the UK Engineering and Physical Sciences Research Council (EPSRC) grant EP/S013652/1 for Cranfield University. The authors would like to thank Dr D. Johnson and Mrs C. Kimpton for SEM measurements.Materials Today Communication