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A comprehensive review on microalgae based astaxanthin: bioprocess optimization, technological barriers, industrial applications and future roadmap
No full textAstaxanthin, a potent ketocarotenoid of C40 family, has drawn significant attention in food, healthcare and personal care industries due to its exceptional anti-inflammatory, antioxidant, and anti-proliferative properties. Microalgae have recently gained recognition as one of the most promising natural sources for astaxanthin production. However, there are several technical barriers in both the upstream and downstream processes that result in microalgae-derived astaxanthin remaining costly. Hence, this review explores recent trends and advancements in astaxanthin production from microalgae. It provides an in-depth review of the biochemical processes that lead to the accumulation of astaxanthin in microalgal cells, highlighting significant factors that affect production, including environmental factors, strain selection, and bioreactor configuration. Different emerging extraction techniques such as physical, biological, and chemical methods are evaluated based on scalability and efficiency. The diverse applications of astaxanthin, particularly in the food, nutraceutical, and pharmaceutical sectors, are also discussed. Furthermore, the review identifies major scientific and technological challenges, such as low biomass yield and high production costs, which hinder large-scale commercialization. In conclusion, future research directions are proposed to overcome these limitations and promote the development of sustainable, cost-effective, and commercially viable microalgae-based astaxanthin production systems.Validerad;2025;Nivå 2;2025-12-02 (u8);Full text license: CC BY</p
Emerging Trends in Liquid Luminescent Solar Concentrators: Progress and Prospects
No full textLiquid luminescent solar concentrators (liquid LSCs) have emerged as a promising alternative to conventional solid-state LSCs for enhancing solar energy harvesting. This review focuses primarily on the two major types of LSCs: liquid-based and thin-film-based systems. By comparing their respective advantages and limitations, it aims to identify how specific performance gaps, such as optical efficiency, quantum yield, scalability, recyclability, ease of fabrication, and cost can be addressed by one type over the other. Particular emphasis is placed on liquid LSCs, which, unlike their solid thin-film counterparts, offer unique benefits such as solution-processability, facile large-area coverage, self-healing potential, and material reusability. However, despite these benefits, research in this area remains scarce, with relatively few studies published to date. This review aims to provide a comprehensive overview of the recent developments in liquid LSCs, covering fundamental operating principles, key performance metrics, and major advances in luminescent materials, matrix design, and device architectures. Explored potential applications in sustainable energy systems are also reported. This review concludes by discussing ongoing challenges like stability, leakage, and contamination, and presenting future directions highlighting the promise of this underexplored field.Full text: CC BY license;For funding information, see: https://doi.org/10.1002/smll.202509030</p
Influence of particle size and inherent gangue on hydrogen-based reduction of magnetite iron ores
No full textThe steel industry’s transition to hydrogen-based ironmaking necessitates a deeper understanding of magnetite ore reduction, a crucial yet underexplored pathway for decarbonization. This study systematically investigates the combined effects of particle size and gangue composition on hydrogen-based reduction behavior of four industrial magnetite ore concentrates with varying CaO and MgO contents. Thermogravimetric analysis at 973 K, interrupted reduction experiments, and post-reduction characterization steps are used to evaluate reduction extent and phase transformations across different particle size fractions and bulk ores. The finer fractions generally exhibit faster and more complete reduction. However, this trend is overridden by gangue effects in certain ores. Magnetite ores with MgO as gangue tend to form magnesio-wustite solid solution (Mg,Fe)O during reduction, resulting in dense microstructures that impede hydrogen diffusion and limit reduction progress. In contrast, magnetite ores with CaO as gangue facilitate the formation of intermediate calcium ferrites, which promote porous morphology and enhanced reducibility. Notably, even the finer particles of ore containing MgO show a lower reduction degree than the coarser particles of the ore containing CaO as gangue. This highlights the dominant role of gangue composition in governing reduction kinetics, intermediate phase formation and final product morphology. These findings contribute to the growing knowledge necessary to enable fossil-free ironmaking by emphasizing the importance of considering both granulometric characteristics and heterogeneity when evaluating magnetite ores for hydrogen-based reduction.Validerad;2025;Nivå 2;2025-11-25 (u2);Full text: CC BY license;</p
Optimising tunnel support design with machine learning models
No full textThe Q-system is one of the broad techniques used in tunnel design and aids in the determination of tunnel support – a crucial aspect for safety and stability in tunnel engineering. It is complex, costly, and time-consuming to acquire all the necessary Q-system characteristics. This study predicts the Q value using parameters that have the largest coefficient of relevance in the value of Q and determines the most important Q-system parameters. The predictions of the models are correlated with the actual Q values using the marginal histograms for training, testing and validation of the datasets. The histogram of the ANN and GB models is closer to that of the measured Q for training, while the RF model is a bit different from the actual Q. The imposed normal distribution curves of the ANN and GB are also closer to that of the actual Q, while RF shows a much more curved cone. These observations account for the high R2 values of 0.9992 and 0.9998 obtained for the ANN and GB models for training, while an R2 of 0.9716 is observed for the RF model. The histograms of the ANN models are the closest resemblance to the actual histogram of Q, followed by those of the GB and then RF for testing and validation. The ANN models have the highest R2 values for the testing and validation of the dataset, which can be attributed to the closeness of their histograms to the actual Q. The ANN model performs better than the other ensemble models, demonstrating its superiority in predicting rockmass quality. The Taylor diagram displays the prediction efficacy of the three proposed models by using the testing and validation datasets, and confirms that the ANN predictive models are the closest to the actual Q values.Validerad;2025;Nivå 2;2025-10-21 (u5);Full text license: CC BY 4.0;</p
Ecological benefits of reintroducing seasonal flow variation for riparian vegetation
No full textThis work examines the relationships between flow restoration, natural flow regimes and riparian vegetation utilizing a case study in northern Sweden. The riparian zone is one of the most species-rich ecosystems and forms an important link between aquatic and terrestrial systems. The integrity of the riparian zone and its vegetation is harmed by flow alteration in numerous rivers, which calls for enhancing riparian management and ecological mitigation measures. Here, we take an ecohydraulic approach, combining a hydraulic model and data on inundation tolerance of riparian vegetation to evaluate the effects of reintroducing seasonal flow variation in a bypassed reach with minimum discharge. The results show that implementing the seasonal flow variation is projected to benefit riparian vegetation by extending the riparian zone and to lead to the development of distinct vegetation belts similar to riparian vegetation along free-flowing rivers. Additional simulations demonstrated that a further increase in riparian area could be achieved by increasing the magnitude of the minimum flow release. While the method assumes the riparian vegetation to be in equilibrium with the flow regime, continued monitoring is needed to assess how fast the riparian vegetation adjusts to new flow conditions.Full text license: CC BY-NC-ND</p
Hierarchical Reactive Task Allocation with Dynamic Conflict Resolution Framework for Collaborative Aerial 3D Printing
No full textThis paper presents a novel reactive coordination and planning framework for collaborative aerial 3D printing with Unmanned Aerial Vehicles (UAVs) while ensuring their safe and efficient simultaneous operation. The proposed framework incorporates a hierarchical dynamic scheduling embedded with a conflict resolution mechanism, enabling it to account for online adaptability to operational uncertainties and unforeseen events during execution. The novelty of the approach lies in its two-tiered hierarchical structure that tightly integrates dynamic assignment with an online conflict resolution mechanism, providing a flexible, adaptive and conflict-free solution for aerial construction tasks. This hierarchical framework introduces the first layer, which is responsible for dynamically assigning the tasks to the available fleet of UAVs. The task assignment considers precedence constraints to ensure structural integrity during construction while also prioritizing safe operation by minimizing the probability of conflicts and highly dependent tasks. In the second layer, conflicts arising from assigned paths are dynamically decomposed into smaller independent sub-graphs and resolved locally to reduce the computational complexities. Towards this, an online locally optimal spatiotemporal conflict resolution scheme is introduced for multi-agent systems to address the local conflicts efficiently. This mechanism dynamically adjusts the UAVs’ speeds with minimal deviation from an optimal reference to mitigate conflicts and ensure printing performance. Additionally, building on this local conflict resolution strategy, the framework enforces reactiveness by iteratively relaxing the problem when conflicts cannot be resolved immediately. This is executed via dynamic reduction and rearrangement of the concurrent tasks’ space to resolve the conflict between them. Moreover, insights gained from failed resolution attempts are dynamically integrated into the global dependency graph, preventing redundant computations in subsequent steps and enhancing overall efficiency and versatility. The framework is distinguished by its use of reactive task-space reconfiguration, informed by infeasible conflict resolutions, and the assignment of guaranteed conflict-free paths, unlike existing sequential or non-guaranteed approaches. The efficacy of the proposed framework is demonstrated through two case studies, constructing both a rectangular and a dome mesh with a collaborative team of UAVs, in a high-fidelity ROS-Gazebo simulation. A video of the mission can be found here https://youtu.be/Ow_qDPWmgDw.Validerad;2025;Nivå 2;2025-12-08 (u8);Full text license: CC BYWallenberg AI, Autonomous Systems and Software Program (WASP
Hydropower Legacies : Long-term consequences of hydroelectric power stations in Southern and Arctic Sweden
No full textThis thesis explores the long-term consequences of hydropower projects by investigating two cases of hydropower, representative for different time periods, and regions throughout the history of hydropower projects within the Swedish context. This investigation informs about the aftermath of different hydropower projects in the face of present-day concerns and the prospects of a green transition and green industrialisation. The Laholm hydropower project is an example of an interwar project in the Swedish South within the county of Halland finished in 1932. The Akkats hydropower project is an example of a post-World War II project within the Swedish Arctic in the county of Norrbotten finished in 1973. By focusing on the storytelling of change that transpired since the conception of the respective hydropower station until the early 2020s, this thesis captures how people recall their relationships to and interaction within the respective context. This thesis shows that the Laholm case has become a part of an environment where different actors and local cultural features have become increasingly viewed as a joint landscape. With time, the hydropower station has become relatively well-accepted at the local level, but also criticised at the regional and national levels for its role in the decline of the river ecosystem. The Laholm municipality, tourist industry, and local fisheries have grown dependent on the hydropower company arrangements. By contrast, Akkats was built in a more ethnopolitical context where hydropower is connected to the history of the exploitation of northward regions and the destruction of Sámi culture and land use. The Swedish Arctic is also a region where the state power board Vattenfall became one of the region’s biggest employers. As such, there is often a complex and multifaceted relationship towards hydropower in general. The Akkats hydropower project remains highly contested, but there are also ongoing efforts to emphasise the role that hydropower has had for past employment and present-day character of the region. Part of the results have also pointed to the unknown variables at the time when the Laholm and Akkats hydropower stations were built that are of great consequence today. Climate change was not a topic of significance when the hydropower stations were built, attitudes have shifted, and the knowledge base about how different species are connected within ecosystems has also grown with time.Norrlands vattenanknutna kulturmiljöer/Cultural Heritage and the Legacies of Hydropower in the Swedish Arcti
Understanding the Thermal Behavior of Black Mass during Recycling of Spent Lithium-Ion Batteries through Its Individual Components
No full textThe increasing use of lithium-ion batteries (LiBs) in electric vehicles and electronics has made efficient recycling essential for maintaining a reliable and affordable supply of critical metals. Thermal treatment of black mass (BM), the heterogeneous residue from spent LiBs, is a crucial step to improve downstream material separation and recovery. This study investigates the thermal behavior of LiBs BM by analyzing the thermal behavior of its components when heated to 600 °C in an inert (N2) atmosphere or in a mixture of 90 vol % N2 and 10 vol % H2. Thermogravimetric analysis (TGA) was conducted at a heating rate of 10 °C/min with an isothermal hold of 1 h, and coupled with quadrupole mass spectrometry (QMS). The analysis was performed on graphite, activated carbon, lithium hexafluorophosphate (LiPF6), polyvinylidene fluoride (PVDF), synthetic black mass, and lithium nickel manganese cobalt oxide (NMC) industrial BM. Equilibrium calculations conducted in FactSage 8.3 were used to describe and understand the experimental findings. The TGA results indicate that in 100 vol % N2, graphite exhibited the lowest weight loss of 0.1 wt %, followed by activated carbon at 2.9 wt %, PVDF at 56 wt %, and LiPF6 at 81 wt %. Synthetic black mass had a weight loss of 3.4 wt %, while industrial black mass had 1.0 wt %. In 90 vol % N2/10 vol % H2, LiPF6 and PVDF experienced weight losses of 79 and 64 wt %, respectively. Synthetic BM had a weight loss of 15.1 wt %, and industrial BM 15.6 wt % due to enhanced reduction of metal oxides in the presence of hydrogen. Full text license: CC BYOptimising Processes for Recycling of lithium-ion batteries (OptiLIB)Eco-friendly and Sustainable Method for Recycling Spent Lithium-Ion Batteries (EcoLIB
Generisk parametrisering av fartygsskrov i CAD
No full textArbetet har utförts på uppdrag av N. Sundin Dockstavarvet AB. Dockstavarvet är en ledande tillverkare avaluminiumbåtar för professionellt bruk i Skandinavien och på den internationella marknaden, där deras mestframgångsrika produkt är stridsbåt 90. CAD-modellering utgör en stor del av deras arbetsprocess, där dettaarbete syftar på att ta fram en arbetsmetod som bygger på att CAD-modelleringen styrs av definierade måttoch beroenden, vilket möjliggör automatiska uppdateringar när parametrar ändras. Detta har även stärkts medett proof-of-concept och ett modelleringstest vilket utförts av en konstruktör på Dockstavarvet. Detta för attgöra fartygsskrovmodellering i Autodesk Inventor mer robust, återanvändbar och lättare att ändra. Utgångspunkten är att befintliga modeller är känsliga för ändringar och tar tid att uppdatera. Målet är att etableraen metodik som tydligt bevarar och överför designavsikten och som möjliggör flexibla och robusta CAD-modeller.Arbetets metod följer Design Research Methodology och bygger på litteraturstudie, intervjuer, dialoger ochpraktiska tester. Ett arbetsflöde har framställts med designplanering, strukturell uppbyggnad och ett flödesschema för modellering av generiska HLC-mallar enligt de teorier som behandlas i arbetet, bland annat Explicitreference modeling. HLC-mallarna valideras sedan med en parameterstudie enligt sin designplanering. Sedanså instansieras dessa mallar i sin definierade kontext vilket leder till att en sammanställning skapas. proofof-conceptet har framtagits genom denna arbetsmetoden. Samt har arbetsmetoden utvärderats genom att enkonstruktör på Dockstavarvet har utvärderat två användarfall.Resultaten visar att fristående HLC-mallar vilket modelleras utefter de principer för robust och flexibel modellering, kan instansieras och kombineras till en sammanställning genom booleska operationer, vilket kan varierasefter sin definierade designrymd, som den är helt robust över. Metoden leder till att robustheten ökar, förändringar blir mer förutsägbara. Samtidigt så beaktas det att detta gäller för den detaljnivå vilket proof-of-conceptethar, samt att eventuella begränsningar kopplat till Autodesk Inventors sätt att hantera geometri kan leda tillproblem vid högre detaljnivå.Slutsatsen är att metoden är praktiskt användbar i åtminstone den detaljnivå vilket presenteras i arbetet, vidarearbete omfattar utvärdering i högre detaljnivå, modellering med en dynamisk skrovlinjemodell, möjlig automatisering av instansieringen samt kopplingar mot beräknings och analysverktyg
Large Language Models to generate sonic behaviors: the case of Wilding AI in exploring creative co-agency
No full textLarge Language Models (LLMs) and foundational models play a central role in multimodal text-to-sound systems, such as text-to-speech and text-to-music, as well as in recent musical agent systems designed to automate music production tasks. We explore an alternative approach that employs LLM-based sonic agents as spatial composition techniques. This method, emerging from the Wilding AI research-creation project, integrates LLMs into Max/MSP, Ableton Live, and spatial sound environments. LLMs are used to generate step-by-step sequences controlling spatial audio parameters, including sound motion in 3D space and other assignable sound properties. This paper details the artistic framework of Wilding AI, a LLM behavior generator, a live performance at the CTM Festival 2025, and discussions on composition, improvisation, time, and agency. Our work repositions LLMs as tools for shaping sonic experiences rather than merely generating finished audio material.Full text license: CC BY 4.0;Funder: Goethe-Institut International Coproduction Fund</p