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Abstract To thrive in extreme conditions, organisms have evolved a diverse arsenal of adaptations that confer resilience. These species, their traits, and the mechanisms underlying them comprise a valuable resource that can be mined for numerous conceptual insights and applied objectives. One of the most dramatic adaptations to water limitation is desiccation tolerance. Understanding the mechanisms underlying desiccation tolerance has important potential implications for medicine, biotechnology, agriculture, and conservation. However, progress has been hindered by a lack of standardization across sub-disciplines, complicating the integration of data and slowing the translation of basic discoveries into practical applications. Here, we synthesize current knowledge on desiccation tolerance across evolutionary, ecological, physiological, and cellular scales to provide a roadmap for advancing desiccation tolerance research. We also address critical gaps and technical roadblocks, highlighting the need for standardized experimental practices, improved taxonomic sampling, and the development of new tools for studying biology in a dry state. We hope that this perspective can serve as a roadmap to accelerating research breakthroughs and unlocking the potential of desiccation tolerance to address global challenges related to climate change, food security, and health.

The European Union's goal of achieving climate neutrality by 2050, outlined in the European Green Deal, is supported by numerous studies providing insights into pathways and emission reduction strategies in the energy sectors. However, model comparisons of such pathways are less common due to the complex nature of climate and energy modelling. Our study brings together integrated assessment models and energy system models under a common framework to develop EU policy scenarios: a Current Trends scenario reflecting existing policies and trends and a Climate Neutrality scenario aligned with the EU's emission reduction target. Both scenarios project reduced final energy consumption by 2050, driven by increased electrification and decreased fossil fuel usage. Electricity consumption increases driven by electrification despite the improved efficiency of electrified technologies. Models align on a shift toward renewables but diverge in technology and fuel choices, reflecting various approaches to reach net-zero energy systems. Furthermore, trade-offs between energy demand and supply mitigation strategies, as well as between renewable energy, e-fuels, and CCS technologies are identified. Considering these model variations, our study highlights the importance of consistent model comparison to offer reliable recommendations to policymakers and stakeholders. We conclude that model diversity is a valuable asset when used sensibly. ISSN:0360-5442 ISSN:1873-6785 Energy, 319

The thesis explores the emerging concept twin transitions (digitalization and decarbonization). It examines how digital innovation interacts with sustainability transitions by focusing on the case of the processing sector, which includes industries such as steel and chemicals. The thesis introduces two conceptual frameworks: (1) the Digital Meta-Regime, which captures the overarching influence of digital technologies across industries; and (2) Digital Innovation Systems, which provides a lens for analyzing how digital innovation operates within specific industries. Central to the research is the idea that while digital technologies like artificial intelligence (AI), digital twins, and advanced analytics hold transformative potential, their actual impact on sustainability is complex and contingent. A case study on AI in the steel industry illustrates this duality. Through an inventory analysis of 140 AI tools and 12 interviews with key actors, we demonstrate how AI facilitates operational efficiencies but tends to reinforce existing fossil-based paths rather than promoting novel low-carbon innovations. This reveals tensions where digital technology risks perpetuating unsustainable practices unless explicitly aligned with sustainability goals. However, the analysis also shows the wide-ranging applications that AI can enable within the steel industry like predicting process parameters; optimizing operations, scheduling, and electrical energy; and forecasting product demand, quality, and site emissions. Further qualitative analysis on the digital innovation system of the Dutch processing industry using 28 semi-structured interviews reveals key innovation resources, systemic problems, system-building activities, and higher-order mechanisms at play. For instance, various socio-technical barriers are faced by organizations involved with digital innovation, ranging from misaligned incentives, decision-making hurdles, and skills gaps to infrastructure, scaling, and partnership challenges, highlighting the challenges of integrating new technologies in industrial contexts. Understanding such digital innovation dynamics helped construct a policy framework for steering digital technologies towards sustainable applications, addressing shared barriers, and embedding better directionality. We argued for balancing critical perspectives with the enabling nature of digitalization, emphasizing the need for nuanced, context-specific policies to drive sustainability and prevent misuse of twin transition narratives by incumbents. To do so, we provide a heuristic tool to assist policymakers and industry actors in navigating twin transitions. The thesis provides theoretical contributions to the literature on technological innovation systems through the development and implementation of a resource-based perspective which provide new insights, beyond the traditional structure-function view. We demonstrate that variable accessibility and applicability are a quality of all technological systems, however, focusing on accessibility and applicability helps reveal unique characteristics within the innovation systems of pervasive or multi-purpose technologies. Additionally, the thesis provides groundwork on the co-dynamics of digital and sustainable innovation, the (ongoing) role of digitalization in shaping incumbent and niche socio-technical configurations, and how systems-thinking can inform twin transition policy. An important methodological contribution is made in combining and balancing technological (or techno-economic) and socio-institutional approaches for studying digital or other socio-technical systems. Further contributions and future work are discussed in relation to institutional logics, deep transitions, and mission-oriented innovation policy. Overall, this thesis provides important structure and guidance for thinking about digitalization in the context of sustainability.

The authors regret that the link to the supplementary documention was inadvertedly not included in the paper. The link to the supplementary documention is now included in this corrigendum. The authors would like to apologise for any inconvenience caused.

Abstract: This study evaluates the economic and environmental benefits of implementing the proposed REcovered Nitrogen from manURE (RENURE) criteria as mineral fertiliser into the Nitrates Directive (ND) to facilitate the utilisation of minerals from manure. Implementing the RENURE amendment could significantly contribute to sustainability goals in an economic way, offering a 4.8 % reduction in economic costs in livestock-dense regions including Brittany (-0.7 %), Lombardy (-2.3 %), Flanders (-2.6 %), Lower Saxony (-4.7 %), Catalonia (-4.8 %), North-Rhine Westphalia (-4.8 %), and the Netherlands (-5.0 %). Through spatially explicit multi-agent modeling, the study revealed that the RENURE amendment not only promises economic benefits, but also enhances nitrogen circularity by 1.3 % and reduces greenhouse gas emissions by 6 % in these areas. These findings highlight the potential of nutrient recovery and reuse under RENURE to address both economic and environmental challenges, supporting the European Union's (EU) Farm-to-Fork strategy (F2F) goals of reducing nutrient emissions to the air and fertilizer use.

ABSTRACTWe present an analysis of the performance data of a monitored PV system onboard a light commercial electric vehicle during parking and driving conditions in the Hannover region of Germany. The PV system's nominal power is 2180 WP with flat silicon modules on the vehicle's roof, rear, left, and right sides and other electronic components needed to charge the vehicle's high‐voltage (HV) battery. The analysis indicated that after 488.92 h of operation, the modules mounted on the vehicle roof produced 133.32 kWh of electricity during parking at the best possible orientation compared to 15.4, 30.67, and 22.99 kWh for the modules mounted on the rear, left, and right sides, respectively. During the trips, after 31.99 h of operation, 6.12, 0.68, 1.08, and 1.86 kWh of electricity were produced by the modules on the roof, rear, left, and right sides, respectively. The overall system efficiency was in the 60%–65% range. The aggregated usable electricity reaching the HV battery after multiple conversion stages generated by the system at the two parking locations was 129.39 kWh. PV electricity generated at the two parking locations enabled a range extension of approximately 530 km, which is 30% of the total distance driven during the measurement period between April and July 2021.

The GRAPHERGIA project collaborated to release a new scientific publication in a journal, a contribution led by our partner ESYCOM, a laboratory attached to the Université Gustave Eiffel. This paper, "Power management technologies for triboelectric nanogenerators” was published in MRS BULLETIN | VOLUME 50 • MARCH 2025. It shares research on the GRAPHERGIA project’s Work Package 4 ‘Advanced electrical modelling and efficient power management of TENGs for energy harvesting and self-powered sensing IoT applications. GRAPHERGIA’s Scientific Paper Abstract A triboelectric nanogenerator (TENG) is a device that utilizes contact electrification and electrostatic induction to convert mechanical energy into electrical energy. It enables self-powering of electronic devices by harvesting mechanical energy from the environment. Its applications include biomedical devices, wearable electronics, and Internet-of-Things (IoT) sensors. Extracting electrical energy from TENG remains challenging due to its time-varying nature and low internal capacitance. Effective power-management techniques are essential for TENG energy-harvesting systems, yet research on dedicated integrated power-conversion methods is currently limited. Given the growing interest in TENG, a comprehensive exploration of energy-harvesting systems is critically necessary. This article synthesizes and compares current advancements in triboelectric energy-harvesting systems, emphasizing strategies to enhance output power through various power-conversion techniques. Additionally, it explores techniques employed in other energy-harvesting systems to inspire innovative approaches in TENG system design. About the authors A team of researchers from France, the Netherlands and China authored this publication. These authors are: Sijun Du (Corresponding author), Delft University of Technology, Delft, Department of Microelectronics, The Netherlands Philippe Basset, ESYCOM Lab, Univ Gustave Eiffel, CNRS, Marne‑la‑Vallée, France Hengyu Guo, Chongqing University, College of Physics, Chongqing, China Dimitri Galayko, LIP6 Laboratory, Sorbonne Université, Paris, France Armine Karami, ESYCOM Lab, UnivGustave Eiffel, CNRS, Marne‑la‑Vallée, France