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Role of the cement industry in climate neutrality considering uncertainties in deployment of carbon capture technologies : A site-specific modeling approach
No full textPublisher Copyright: © 2025 The Author(s).Decarbonizing hard-to-abate industries such as cement is fundamental to achieving ambitious climate neutrality targets. These industries are characterized by long-lived, capital-intensive assets and discrete reinvestment cycles, yet in energy system optimization models, common tools for assessing decarbonization pathways, they are often represented as aggregated entities with continuous investment modeling. In the cement industry, carbon capture technologies play a key role in approaching near-zero emissions, but the timing and scale of deployment are uncertain. The future contribution of natural carbon sinks to offsetting residual emissions is also unclear. This study therefore uses scenario analysis and sets out to examine how (i) the representation of industry, (ii) the timing of CCS availability, and (iii) the availability of natural carbon sinks can shape national, modeled mitigation pathways. To do so, a national energy system model, FINTIMES, is developed with detailed site-specific representation of the Finnish cement facilities. Results show that the site-specific discrete formulation produces different investment timing and technology choices in the cement industry compared with the aggregated continuous formulation. Scenario analysis further reveals that delays in the deployment of carbon capture technologies necessitate radical shifts in other sectors, notably the transport sector, consequently leading to a substantial increase in overall system costs. Insights highlight the need to preserve Finland’s natural carbon sinks and de-risk timely deployment of carbon capture and storage, while demonstrating the value of facility-level modeling in designing integrated industrial decarbonization roadmaps.Peer reviewe
Failure mechanisms in quenching and partitioning (Q&P) steel under varying stress states
No full textPublisher Copyright: © 2025Quenching and partitioning (Q&P) steels represent a key advancement in third-generation advanced high-strength steels (AHSS), offering an exceptional balance between strength and ductility due to their complex multiphase microstructures. However, their application in crash-critical and formability-sensitive components remains limited by an incomplete understanding of their fracture behavior under complex stress states. Therefore, this study aims to systematically investigate the failure mechanisms of Q&P 1000 steel across a wide range of stress states from shear to uniaxial and plane-strain tension using tensile specimens with different geometries. By combining macroscopic mechanical testing with detailed microstructural characterization via scanning electron microscopy (SEM) and electron backscatter diffraction (EBSD), we reveal a transition from ductile fracture, governed by void nucleation and coalescence, to cleavage-dominated fracture under increasing triaxiality. Remarkably, transgranular cleavage fracture features were observed for the first time in Q&P steels even after substantial plastic deformation, which confirms it to be also a failure mechanism of ductile fracture in addition to brittle fracture. Two major damage mechanisms responsible for the failure mode transition were revealed: (i) phase boundary debonding and (ii) martensite cleavage fracture. A stress-based cleavage fracture criterion with a critical stress triaxiality, regulated by the cleavage fracture stress and strain hardening behavior, can well explain and quantify this transition behavior. These results provide new insights into stress-state-dependent failure in Q&P steels and offer guidance for their safe and optimized application in forming and crash-relevant components.Peer reviewe
Anodic electrodeposition of MIL-53(Al) thin films on aluminum : Synthesis, characterization, and potential for direct electric heating
No full textPublisher Copyright: © 2025 The AuthorsThis study presents the first successful anodic electrodeposition (AED) of MIL-53(Al) thin films on aluminum electrodes, using a novel synthesis approach involving a DMF-water solvent mixture and potassium chloride as a supporting electrolyte. The aim was to optimize the synthesis parameters to control the crystallinity, morphology, and porosity of the films, and to evaluate their potential applications in direct electric heating. The crystallinity, morphology, and porosity of the obtained films were controlled by systematically varying process parameters such as current density, electrolyte concentration, and deposition time. The study also assessed the impact of different post-synthesis washing protocols on film purity and adherence. Characterization techniques including XRD, XPS, FTIR, SEM, TEM, EDX, BET, and TGA were employed to analyze the structural and compositional properties of the synthesized thin films. The study found that higher current densities and higher electrolyte concentrations favored better crystallinity, while lower current densities favored larger crystal growth. High-performing films achieved a BET surface area of 876.2 m2 g-1, indicating great potential for gas separation and adsorption applications. A methanol–water and DMF washing sequence was optimal for achieving film purity and adherence. The films exhibited thermal stability up to 500 °C. The potential for direct electric heating was demonstrated, with the electrode surface reaching 68.3 °C after 5 min at 3 A. This work establishes AED as a scalable and cost-effective method for producing customizable thin film MOFs, suitable for advanced applications such as gas storage, catalysis, and sensing. It expands the possibilities for the application of MOFs and suggests future research directions to explore other MOF systems and their practical performance in realistic conditions.Peer reviewe
TOPOLOGY OPTIMIZATION CASE STUDY : LASER POWDER BED FUSION MATERIAL LOSSES, ENERGY USE, AND CONSUMABLES
No full textPublisher Copyright: © 2024 by ASME.Additive manufacturing (AM), more familiarly known as 3D printing, has also been postulated as an advantageous manufacturing technology from a sustainability perspective. A few of these technologies, such as laser powder bed fusion (PBF-LB), have been increasingly used in industrial production. Considerable performance and efficiency increases are attainable by leveraging the increased design freedom and geometrical complexity enabled by the layer-by-layer principle of AM. Design tools, such as topology optimization, can significantly reduce part weight and yield sustainability benefits. In the current literature, however, sustainability assessments of AM are often based on naïve or overly optimistic material use ratios (raw material use: final component) which can bias the results. For example, the PBF-LB process losses to machine filters and as residuals are generally omitted. The paper investigates the laser powder bed fusion (PBF-LB) process material efficiency through an industrial case product redesigned for AM. In this work, topology optimization is used to minimize component weight, and the part is manufactured with PBF-LB. The process energy, raw materials, consumables, and waste streams are measured for successive process steps. The result provides a new datapoint in the quest to promote a more realistic material use ratio for AM including all PBF-LB process losses.Peer reviewe
Vesicle tension in porous membranes : Aspiration, spreading, and tube extraction
No full textPublisher Copyright: © 2025 Biophysical SocietyWe review recent theoretical and experimental advances in understanding the mechanical tension of porous vesicles. Focusing on three key deformation processes, aspiration, spreading, and tube extrusion, we show how membrane porosity introduces novel timescales and feedback mechanisms that alter vesicle behavior. In particular, we highlight how tube extrusion from porous membranes demonstrates the vesicle's ability to regulate internal volume and dynamically modulate membrane tension. This regulation enables the sustained elongation of membrane tubes under milder mechanical conditions than those required for nonporous vesicles. These findings provide new insight into biologically relevant processes such as organelle shaping, intracellular transport, and mechanosensitive remodeling, emphasizing the crucial role of membrane permeability in cellular morphodynamics.Peer reviewe
Human-Centred Design Approach to Find User Requirements for a Status Monitoring System in a Remote and Autonomous Multivessel Operation
No full textThe maritime industry is advancing towards the implementation of autonomous cargo shipping operations on a commercial scale, significantly transforming the nature of work for maritime officers. Vessels controlled from land-based operation centers and the capability to simultaneously operate multiple ships demands new control tools for effective monitoring. Our study seeks to understand the context and user requirements of future operators through HCD process. User requirements for a status monitoring tool were refined through expert participation and a first-phase prototype was designed and evaluated. Key findings reveal that an accessible tool providing a simplified view of operational assets, with alerts contextualized within the mission, enhances situational awareness and communication within heterogeneous teams. Our study contributes to the conference theme by addressing the future requirements of remote maritime operators concerning system status monitoring through HCD process.Peer reviewe
Ontologies for the generic motor winding process
No full textPublisher Copyright: © 2025 The AuthorsIntegrating information technology (IT) and operational technology (OT) in the manufacturing ecosystem is crucial for improving productivity, efficiency, and situational awareness. However, integrating various IT/OT systems is often time-consuming and expensive. Semantic integration resolves this by unifying data from heterogeneous sources while preserving the contextual meaning of each source. The success of semantic integration requires robust ontologies that describe objects, processes, and relationships for knowledge representation, system integration, and semantic interoperability. Despite the significance of ontologies in many industrial domains, a scientifically defined ontology for the motor manufacturing process is in demand. This research addressed this gap by applying the top-down approach with 5M (manpower, machine, method, measurement, and material) methodology to develop a generic motor winding process ontology systematically. Encoded in the Terse RDF Triple Language (TTL), the developed ontology systematically addressed the needs of diverse job roles by incorporating fundamental aspects such as motor types, winding techniques, and thermal classes. The ontology consisted of a clear definition of core classes and their relationships, and outlined the major factors influencing the motor winding process. Finally, validation experiments confirmed the robustness of the ontology through syntax validation, logical validation using “HermiT” reasoning, domain compatibility assessments via competency questions, and SPARQL query execution outputs. The results confirmed the robustness of the ontology and its applicability, offering a framework for semantic interoperability and knowledge representation in the motor winding process.Peer reviewe
Monetizing environmental impacts can compensate for higher upfront costs of wood construction
No full textPublisher Copyright: © 2025 The Author(s).The transition toward low-carbon construction has renewed interest in engineered wood products (EWPs) as alternatives to traditional materials such as steel and concrete. While EWPs offer clear environmental advantages, their higher upfront costs often discourage adoption. This study investigates whether incorporating the monetary value of environmental externalities, or indirect costs not reflected in market prices, can influence the cost-effectiveness of material choices in construction. A life cycle assessment (LCA) is applied to compare the upfront emissions of two structural design alternatives of a Finnish public building, one based on EWPs and the other on steel-reinforced concrete elements. Monetary valuation was used to translate environmental impacts from four key categories (global warming potential, acidification potential, stratospheric ozone depletion, and tropospheric ozone formation) into indirect costs. Results show that, although the wood scenario had slightly higher direct costs (∼4.4 %), it delivered substantial environmental benefits, particularly in the global warming potential category. Wood elements indicated net environmental gains and showed negative indirect costs, which reduced the total cost of the elements by approximately 33 %. By integrating both direct and indirect costs, this research demonstrates a more complete method for evaluating construction materials. This approach offers new insight for aligning financial decision-making with climate goals in the built environment.Peer reviewe
Mercury levels and trends in fish (2011–2021) : A Bayesian approach with multi-group Gaussian processes and hierarchical imputation
No full textPublisher Copyright: © 2025 The AuthorsBackground: Mercury (Hg) is a toxic metal, with fish consumption being the primary source of exposure in humans. This study aimed to describe Hg concentrations in fish species consumed in the Valencian Community (Spain) and their trends during the period 2011–2021. Methods: A retrospective study was conducted on Hg levels in fish meat between 2011 and 2021, using data from the Food Safety Monitoring Program of the Valencian Regional Government. Descriptive analyses and temporal trends were inferred for total Hg (THg) (n = 799) and methylmercury (MeHg) (n = 271) levels by fish species and fishery origin. Gaussian processes (GPs) with a novel multi-group covariance function were applied, enabling the use of correlations across categories to improve inference on temporal trends in unbalanced groups, with species that have smaller samples borrowing information from correlated species. Results: Swordfish exhibited the highest Hg concentrations (median THg: 0.76 mg/kg; IQR: 0.47–1.17), with 30 % of samples exceeding European limit values, followed by fresh tuna (0.46 mg/kg) and canned tuna (0.22 mg/kg). THg and MeHg levels in swordfish tended to decrease by around 0.5 mg/kg from 2011 to 2016, but then increased again to near their initial levels. Fresh and canned tuna showed decreasing trends in the first half of the study period. Data from the second half of the period were limited, except for swordfish; thus, results from this time should be interpreted with caution. Conclusions: Most fish groups showed declining trends between 2011 and 2016. Our findings on Hg levels in commercially sold fish species could be useful for guiding local fish consumption recommendations.Peer reviewe
Passive underwater tracking with unknown measurement noise statistics using variational Bayesian approximation
No full textPublisher Copyright: © 2024 Elsevier Inc.This paper considers a bearings-only tracking problem with unknown measurement noise statistics. It is assumed that the measurement noise follows a Gaussian probability density function where the mean and the covariance of the noise are unknown. Here, an adaptive nonlinear filtering technique is proposed, where the joint distribution of the measurement noise mean and its covariance are considered to follow a normal inverse Wishart (NIW) distribution. Using the variational Bayesian (VB) approximation, joint distribution of the target state, the measurement noise mean and covariance is factorized as the product of their individual probability density function (pdf). Minimizing the Kullback-Leibler divergence (KLD) between the factorized and true joint pdfs, probability distributions of the noise mean, covariance and the target states are evaluated. The estimation of states with the proposed VB based method is compared with the maximum a posteriori (MAP) and the maximum likelihood estimation (MLE) based adaptive filtering. Deterministic sigma points are used to realize the filtering algorithms. The proposed adaptive filter with VB approximation is found to be more accurate compared to their corresponding MAP-MLE based counterparts.Peer reviewe