http://bura.brunel.ac.uk/handle/2438/22 2026-05-24T15:37:35Z http://bura.brunel.ac.uk/handle/2438/33316 Title: From corporate greenhouse gas inventories to design-relevant LCAs: an integrated framework for industrial decarbonization Authors: Don Merenchige, UAW; Wang, B; Ji, S Abstract: Purpose: Global decarbonization goals demand accurate and transparent greenhouse gas (GHG) accounting across both organizational and product levels. However, existing frameworks such as the GHG Protocol, ISO-based standards, and product-level approaches like Product Carbon Footprint (PCF) and Life Cycle Assessment (LCA) are often applied in isolation, with limited operational integration for product design-oriented decision-making. This study develops and empirically validates an integrated framework linking organizational GHG inventories with product-level LCAs to enhance emission traceability, hotspot identification, and life cycle-based design support while strengthening methodological rigor and transparency. Methods: The proposed framework integrates the methodological principles of the GHG Protocol and ISO 14064–1 for organizational reporting, along with ISO 14040/44 and ISO 14067 for product-level assessment, within a unified structure. Implemented through an Excel-based tool, it systematizes activity data collection, GHG quantification, and allocation across Scopes 1–3 and product life cycle stages. The framework was tested using operational data from an automotive component manufacturer, which converted corporate inventories into product-level life cycle inventory (LCI) datasets. Robustness was evaluated through qualitative uncertainty assessment and quantitative sensitivity analysis. Results and discussion: Scope 3 supply chain emissions were found to dominate the organizational footprint (>90%), primarily driven by raw material extraction and processing of steel and aluminium. Product-level results indicate an average carbon intensity of 7.43 kg CO2e per part, with over 80% of embodied emissions originating from upstream material flows. The framework improves data traceability between operational activities and product emissions, enabling systematic identification of hotspots across materials, transport, and manufacturing processes. Conclusions: The integrated framework addresses the long-standing divide between organizational GHG accounting and product-level LCA by providing a structured and adaptable approach that improves consistency between reporting and product development. By linking operational data with product-level insights, the framework supports both backward-looking emission inventories and forward-looking sustainability assessments. While demonstrated within an automotive manufacturing context, broader application depends on organizational data maturity and sector-specific conditions. Nevertheless, the framework provides practical decision support for low-carbon material selection and supply chain decarbonization, contributing to industrial progress toward net-zero and circular economy objectives. Description: Data availability: The data supporting the findings of this case study were provided by the participating organization under confidentiality agreements. As such, the data are not publicly available in accordance with the organization’s data disclosure policy.; Electronic supplementary material is available online at: https://link.springer.com/article/10.1007/s11367-026-02639-8#Sec42 . 2026-04-27T00:00:00Z http://bura.brunel.ac.uk/handle/2438/33297 Title: Growth twins within (Al₃(Sc,Ti) + α-Al) eutectic cells enable novel grain refinement in recycled Al alloys Authors: Que, Z; Niu, Z; Mendis, CL; Negrea, RF; Fan, Z Abstract: Designing sustainable aluminium alloys with superior mechanical performance requires effective microstructural control during solidification. In this study, a cross-over recycled wrought aluminium alloy system spanning the 1xxx–7xxx series was designed with maximum impurity tolerance. A grain refinement strategy using hypoeutectic Sc additions was developed to simultaneously refine grains and second-phase particles. A previously unreported grain refinement mechanism was identified in this multicomponent recycled alloy, where the growth of α-Al grains is constrained by a network of (Al + Al3(Sc,Ti)) eutectic cells rather than by classical heterogeneous nucleation. Remarkably, α-Al growth twins were observed within these eutectic cells, a crystallographic feature rarely reported in high stacking-fault-energy aluminium. Atomic-scale characterization using scanning transmission electron microscopy (STEM) reveals the structural characteristics associated with this phenomenon. These findings provide a new pathway for microstructural control in complex recycled aluminium alloys and offer design principles for next-generation sustainable lightweight materials with enhanced mechanical performance. Description: Highlights: • Cross-over recycled wrought Al alloys from 1xxx to 7xxx series were designed. • α-Al twins were first observed in (Al3(Sc,Ti) + α-Al) eutectic cells in the as-cast state. • (Al3(Sc,Ti) + α-Al) eutectic cells restrict α-Al dendrite growth and refine the microstructure. • 0.5 wt% Sc provides 5 times stronger grain refinement than a commercial refiner. • Hypoeutectic addition enables grain refinement and fine SPPs simultaneously.; Data availability: Data will be made available on request. 2026-04-14T00:00:00Z http://bura.brunel.ac.uk/handle/2438/33279 Title: Optimum scandium addition in A356 cast alloys: alloy design, microstructural evolution and mechanical properties Authors: Khandelwal, P; Negrea, RF; Nunn, J; Honan, S; Ji, S Abstract: The effect of scandium (Sc) addition on the microstructural evolution and mechanical properties of A356.2 cast alloys in both as-cast and T6 heat-treated conditions was investigated using a combined thermodynamic and experimental approach to identify an optimum composition for enhanced performance. Thermodynamic calculations and cooling curve analysis showed that Sc alters solidification behaviour through the formation sequence of Sc-containing intermetallic phases. Experimental results demonstrated that Sc additions up to 0.4 wt% significantly refined primary α-Al grains and reduced secondary dendrite arm spacing (SDAS), while modifying eutectic Si from coarse plate-like to fine fibrous morphology. The transformation of β-Al5FeSi into compact Al-Fe-Si-Sc phases and the formation of nanoscale Al-Si-Sc-(Ti) dispersoids further contributed to strengthening. In the as-cast condition, the A356-0.4Sc alloy exhibited the best combination of strength and ductility, whereas under T6 heat treatment, the A356-0.2Sc alloy showed superior performance due to enhanced precipitation strengthening and thermal stability of Sc-containing dispersoids. At higher Sc content (0.6 wt%), primary AlSc2Si2 formation led to microstructural coarsening and reduced properties. This study establishes an optimum Sc addition range of 0.2–0.4 wt% and provides mechanistic insight into the role of Sc in alloy design. Description: Data availability: Data will be made available on request.; Supplementary data are available online at: https://www.sciencedirect.com/science/article/pii/S0264127526007574?via%3Dihub#s0110 . 2025-05-06T00:00:00Z http://bura.brunel.ac.uk/handle/2438/33202 Title: Modelling of precipitation hardening during non-isothermal thermomechanical treatment of 6 series aluminium alloys Authors: Gharavian, Somayeh Abstract: The future of the automotive industry can be viewed as contingent upon the further development of aluminium alloys. This can be primarily achieved when the behaviour of aluminium alloys during the thermomechanical treatment process of hardening is comprehensively understood and predicted. This study focuses on developing a comprehensive mathematical model for predicting the mechanical behaviour of Al-Mg-Si(Cu) systems subjected to non-isothermal heat treatment to ultimately enable the prediction of mechanical behaviour in the form of a software tool. The Kampmann and Wagner numerical model is among the well-studied mathematical models for precipitation hardening; this model was adapted as the base model for this study where it was further incorporated with critical factors such as multi-stage aging, clustering effects, and the influence of plastic deformation. By coupling the framework to a thermomechanical database and refining precipitation kinetics, the model exhibited improved accuracy in simulating the evolution of microstructure and the mechanical properties under industry specific conditions. Validation of the developed model was carried out by comparing with experimental data obtained from laboratory experiments on Al-Mg-Si (Cu) alloys. These experiments included varying heat treatment duration, temperatures, plastic deformation and different cooling/heating rate to replicate the industrial conditions. The results of the model demonstrate the capability to predict multi-stage aging processes under non-isothermal conditions, facilitating the analysis of various quenching and heating rates. A key advantage is its integration of precipitation and clustering predictions within a unified framework, enabling accurate assessments across a broad range of aging temperatures from natural aging to elevated temperatures like 200°C. Furthermore, the model incorporates the effects of plastic deformation in the form of 4–8% cold stretching, enabling the exploration of not only work hardening but also the influence of deformation on the thermodynamics and kinetics of the process. These findings highlight the significant potential of mathematical modelling to optimize heat treatment process design, substantially reducing the workload in the automotive industry. Moreover, the model has shown significant potential to be used as a helpful tool towards alloy design purposes with further development and validation with experimental data. Description: This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University London 2024-01-01T00:00:00Z