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Two Isomeric Thienoacenes in Thin Films: Unveiling the Influence of Molecular Structure and Intermolecular Packing on Electronic Properties
No full textIsomerism of molecular structures is often encountered in the field of organic semiconductors, but little is known about how it can impact electronic and charge transport properties in thin films. This study reveals the molecular orientation, electronic structure, and intermolecular interactions of two isomeric thienoacenes (DN4T and isoDN4T) in thin films, in relation to their charge transport properties. Utilizing scanning tunneling microscopy (STM), angle-resolved photoemission spectroscopy (ARUPS), and near-edge X-ray absorption fine structure measurements (NEXAFS), we systematically analyze the behavior of these isomers from submonolayer to multilayer coverage on highly ordered pyrolytic graphite (HOPG) as substrates. We find that at submonolayer coverage both DN4T and isoDN4T molecules predominantly adopt a nearly flat-lying orientation on the surface, minimizing intermolecular interactions. The distinct emission features of the highest occupied molecular orbital (HOMO) level in ARUPS enables the determination of molecular reorganization energies. These are found to be in good agreement with theoretical predictions, suggesting superior charge transport in DN4T compared to isoDN4T. Notably, thickness-dependent photoemission measurements reveal a significant splitting (approximately 450 meV) of the HOMO level of isoDN4T, attributed to polarization-induced effects rather than wave function overlap, indicating a nuanced interplay between molecular packing and electronic properties. Our results underscore the importance of molecular packing and substrate interactions in determining the electronic structure and transport properties of organic semiconductor thin films. Substrate-induced polymorphism and the crucial role of polarization-induced effects influencing charge transport are highlighted. These insights are pivotal for future engineering of molecular and thin film structures, aiming to enhance the performance of organic semiconductor-based devices.H2020 Marie Sklodowska-Curie Actions 10.13039/100010665Deutsche Forschungsgemeinschaft 10.13039/501100001659Fonds De La Recherche Scientifique - FNRS 10.13039/501100002661Fonds De La Recherche Scientifique - FNRS 10.13039/501100002661Fonds De La Recherche Scientifique - FNRS 10.13039/501100002661Fonds De La Recherche Scientifique - FNRS 10.13039/501100002661Peer Reviewe
Spatial modelling of present and future groundwater potentials in Nigeria; towards a sustainable water demand and supply
No full textThe development of water resources in Nigeria has not risen alongside population increase. Although groundwater is the available source of water at all locations in Nigeria, groundwater aquifer is becoming deeper due to increased groundwater harvest, especially in urban areas. There is a need for continuous groundwater modelling using geological, climatic, environmental data, and spatial tools especially under climate change and intense landcover conversions. The Spatial Multi-Criteria Analysis (SMCA) was adopted in this study to model the current groundwater potential in Nigeria. The multi-criteria analysis tool in ArcGIS was explored to overlay the nine factor maps to model historic and futuristic groundwater potentials. Our groundwater factor maps show an interesting pattern across Nigeria, the southern parts show more potential considering suitability factors like; surface water density, rainfall, temperature, soil, land cover and elevation in the region. Whereas the upland regions even with higher rainfall and lower temperatures suitable for groundwater recharge, are disadvantaged by geomorphological factors. Northern part of Nigeria shows high potentials, considering the geology, soil, lineament density and slope, but disadvantaged by other factors like lower rainfall and higher temperatures. This informed the final groundwater potential maps; results for the historic potential revealed that, no location in Nigeria has optimal (9–10), very poor or no (1–2) groundwater potential. The results further revealed that areas with higher groundwater potentials are largely within the corridors of major rivers in Nigeria (Niger and Benue), covering about 17.6% of the Nigerian landmass, while 2.6%, 33.7, 44% and 2.2% are occupy areas with very low, low, moderate and very high groundwater potentials respectively. Further analysis highlighs locations of concern due to climatic and environmental changes. Interestingly, our groundwater projection results show a persistent increase in groundwater potential from 2021 to 2100 if current landuses and environmental factors are maintained, and if the projected increase in rainfall is true. Despite these groundwater potentials, the recent issues of shallow aquifers have been cautioned by scientists, especially due to groundwater uncertainties in Nigeria especially with intense landcover conversions, combined with accelerated water demands due to increase in population, and incessant groundwater extractions. Therefore, there is a need to seek caution in the pattern of unregulated and incessant groundwater harvest in Nigeria and we recommend frequent updates of the groundwater potential using geospatial tools to inform governing policies on a centralised consolidated sustainable water supply in Nigeria.Open Access funding enabled and organized by Projekt DEAL.Humboldt-Universität zu Berlin (1034)Peer Reviewe
A triple increase in global river basins with water scarcity due to future pollution
No full textWater security is at stake today. While climate changes influence water availability, urbanization and agricultural activities have led to increasing water demand as well as pollution, limiting safe water use. We conducted a global assessment of future clean-water scarcity for 2050s by adding the water pollution aspect to the classical water quantity-induced scarcity assessments. This was done for >10,000 sub-basins focusing on nitrogen pollution in rivers by integrating land-system, hydrological and water quality models. We found that water pollution aggravates water scarcity in >2000 sub-basins worldwide. The number of sub-basins with water scarcity triples due to future nitrogen pollution worldwide. In 2010, 984 sub-basins are classified as water scarce when considering only quantity-induced scarcity, while 2517 sub-basins are affected by quantity & quality-induced scarcity. This number even increases to 3061 sub-basins in the worst case scenario in 2050. This aggravation means an extra 40 million km 2 of basin area and 3 billion more people that may potentially face water scarcity in 2050. Our results stress the urgent need to address water quality in future water management policies for the Sustainable Development Goals.Koninklijke Nederlandse Akademie van Wetenschappen (Royal Netherlands Academy of Arts and Sciences)https://doi.org/10.13039/501100001722EC | Horizon 2020 Framework Programme (EU Framework Programme for Research and Innovation H2020)https://doi.org/10.13039/100010661Korea Institute of Planning and Evaluation for Technology in Food, Agriculture, Forestry and Fisheries (iPET)https://doi.org/10.13039/501100003668Food, Agriculture, Biodiversity, Land-Use, and Energy (FABLE) Consortium (FABLE 2.0, Grant 94120)Dutch Talent Program Veni-NWO project (0.16.Veni.198.001, supporting M.S.)MTHvV was financially supported by the European Union (ERC Starting Grant, B-WEX, Project 101039426) and Netherlands Scientific Organisation (NWO) by a VIDI grant (VI.Vidi.193.019).Peer Reviewe
Atmosphere circulation patterns synchronize pan-Arctic glacier melt and permafrost thaw
No full textThe Arctic is changing rapidly due to the amplification of global temperature trends, causing profound impacts on the ice sheet in Greenland, glaciers, frozen ground, ecosystems, and societies. Here, we focus on impacts that atmospheric circulation causes in addition to the climate warming trends. We combine time series of glacier mass balance from temporal satellite gravimetry measurements (GRACE/GRACE-FO; 2002–2023), active layer thickness in permafrost areas from ESA’s Climate Change Initiative remote sensing and modelling product (2003–2019), and field measurements of the Circumpolar Active Layer Monitoring Network (2002–2023). Despite regional and system-related complexities, we identify robust covariations between these observations, which vary asynchronously between neighbouring regions and synchronously in regions antipodal to the North Pole. We reveal a close connection with dominant modes of atmosphere circulation, controlling about 75% of the common pan-Arctic impact variability (2002–2022), also affecting the Greenland Ice Sheet. We emphasize that it is necessary to consider such atmospheric driving patterns when projecting impacts, particularly caused by extremes, in an increasingly warmer Arctic.Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research (Alfred-Wegener- Institute, Helmholtz Centre for Polar and Marine Research)https://doi.org/10.13039/501100003207Peer Reviewe
Capturing residents’ perceptions of green spaces in densifying urban landscapes - The potentials of mental mapping
No full textUnderstanding residents’ perceptions of green-blue infrastructure (GBI) is critical to ensure continued access to its associated benefits in growing and densifying urban landscapes. Physical availability and accessibility of green spaces alone do not directly translate to actual appreciation and use. Residents’ sense of place can determine if benefits from GBI are realized and how landscape changes may be perceived. In this study, set in sub-urban Stockholm, Sweden, we applied a mixed-methods approach combining mental mapping with follow-up interviews to investigate how such methodology can improve our understanding of residents’ perception of the recreational use of GBI. For the mental mapping exercise, participants drew, freehand, a map of appreciated neighborhood places for recreational purposes. Our results clearly show that mental mapping provides relevant information on individual and collective perceptions of recreational GBI, linkages between green-blue and gray infrastructure elements, and recreational hot-spots of importance to the local inhabitants. The unguided approach to welding local knowledge with spatial expressions makes the method well suited to contribute to a better understanding of plural senses of place with regards to the recreational use of GBI in rapidly urbanizing landscapes and an enhanced capacity to recognise locally appreciated recreational spaces in planning and practical management
The Impacts of Multiple Tropical Cyclone Events and Associated Precipitation on Household Income and Expenditures
No full textTropical cyclones (TCs) are one of the most destructive natural hazards. Damages arise from strong winds, compounded by associated flood-inducing hazards such as heavy rainfall and storm surge. Recent papers have shown that the modelled TC damage estimates fall short of the observed estimates due to the use of wind speed as a sole damage proxy. Damage estimates may be further confounded by inaccurate representations of vulnerability of people and economic sectors, for example, calling for adjusted damage thresholds in less developed regions. This paper evaluates the impacts of compounded TC hazards on household income and expenditure in the Philippines, with adjustments in vulnerability representation drawn from local information. Our results show that the omission of TC-associated precipitation leads to an underestimation of impacts, as well as the number of areas and economic sectors affected by TCs. We find that households cope through a reallocation of budgets and reliance on alternative income sources. Despite extensive public and private disaster risk reduction and management strategies, we still find significant losses in income and expenditures at any number of TC exposure.Bundesministerium für Bildung und Forschunghttp://dx.doi.org/10.13039/501100002347Peer Reviewe
Adaptive hybrid high-order method for guaranteed lower eigenvalue bounds
No full textThe higher-order guaranteed lower eigenvalue bounds of the Laplacian in the recent work by Carstensen et al. (Numer Math 149(2):273–304, 2021) require a parameter Cst,1that is found not robust as the polynomial degree p increases. This is related to the H1stability bound of the L2projection onto polynomials of degree at most p and its growth Cst, 1∝(p+1)1/2as p→∞. A similar estimate for the Galerkin projection holds with a p -robust constant Cst,2and Cst,2≤2for right-isosceles triangles. This paper utilizes the new inequality with the constant Cst,2to design a modified hybrid high-order eigensolver that directly computes guaranteed lower eigenvalue bounds under the idealized hypothesis of exact solve of the generalized algebraic eigenvalue problem and a mild explicit condition on the maximal mesh-size in the simplicial mesh. A key advance is a p -robust parameter selection. The analysis of the new method with a different fine-tuned volume stabilization allows for a priori quasi-best approximation and improved L2error estimates as well as a stabilization-free reliable and efficient a posteriori error control. The associated adaptive mesh-refining algorithm performs superior in computer benchmarks with striking numerical evidence for optimal higher empirical convergence rates.Open Access funding enabled and organized by Projekt DEAL.Humboldt-Universität zu Berlin (1034)Peer Reviewe
Motivations, changes and challenges of participating in food-related social innovations and their transformative potential: three cases from Berlin (Germany)
No full textDominant agri-food systems are increasingly seen as unsustainable in terms of environmental degradation, mass production or high food waste. In an attempt to counteract these developments and foster sustainability transitions in agri-food systems, a variety of actors are engaging in socially innovative models of food production and consumption. Using a multiple case study approach, our study examines three contrasting alternative economic models in the city of Berlin: community gardens, the app Too Good To Go (TGTG), and a cooperative supermarket. Based on 15 qualitative interviews, we provide insights into their transformative potential by exploring participants' underlying motivations, the changes they have experienced, and the challenges and potential for future development of these models. We find that participation in community gardens and the cooperative supermarket is similarly motivated by social aspects and dissatisfaction with existing food access options, while TGTG users are more motivated by financial reasons. Our study shows that change is experienced mainly at the individual level, e.g. by building new relationships, changing cognitive framings, and learning (new) practices, especially in community-oriented settings. The individualization of change shows that these models have a rather low potential to lead to more systemic accounts of changes. Yet, they can prefigure regime change, describe resistance, and foster cumulative incremental change that may spill over into society. We conclude that in order to sustain this role and drive transitions, it is important to up- and outscale these models; and we provide recommendations on how these models can mutually support their development, establishment, and protection.Open Access funding enabled and organized by Projekt DEAL.Leibniz-Zentrum für Agrarlandschaftsforschung (ZALF) e.V. (3493)Peer Reviewe
Estimation of minimal data sets sizes for machine learning predictions in digital mental health interventions
No full textArtificial intelligence promises to revolutionize mental health care, but small dataset sizes and lack of robust methods raise concerns about result generalizability. To provide insights on minimal necessary data set sizes, we explore domain-specific learning curves for digital intervention dropout predictions based on 3654 users from a single study (ISRCTN13716228, 26/02/2016). Prediction performance is analyzed based on dataset size ( N = 100–3654), feature groups (F = 2–129), and algorithm choice (from Naive Bayes to Neural Networks). The results substantiate the concern that small datasets ( N ≤ 300) overestimate predictive power. For uninformative feature groups, in-sample prediction performance was negatively correlated with dataset size. Sophisticated models overfitted in small datasets but maximized holdout test results in larger datasets. While N = 500 mitigated overfitting, performance did not converge until N = 750–1500. Consequently, we propose minimum dataset sizes of N = 500–1000. As such, this study offers an empirical reference for researchers designing or interpreting AI studies on Digital Mental Health Intervention data.The original trial and data collection was funded by the European Union's Horizon 2020 research and innovation program under grant agreement No 634757.Peer Reviewe
Short- and medium-term impacts of small-scale vegetable support on food security: evidence from Syria
No full textSmall-scale agricultural and horticultural interventions play a critical role in improving nutrition and food security of vulnerable households in peaceful settings. However, scant rigorous evidence exists on the impacts and sustainability of such interventions in conflict settings. In this paper, we address this knowledge gap by analyzing the short- and medium-term impacts of a small-scale vegetable input support program involving asset transfers on food security and diets in war-time Syria. We use longitudinal panel household survey data from a quasi-experimental study collected at three rounds: before, one year, and two years after the horticultural intervention ended. We use propensity score matching and fixed-effect regression models to estimate the average treatment effects on the treated. We find that the vegetable support significantly improves food security by 21% and 19% in the short- and medium-term, respectively. More specifically, we find that the intervention significantly increased the consumption of nutrient-rich food groups such as vegetables, root tubers, fruits, eggs, pulses and nuts, milk, and oil and fats. Moreover, we find that the intervention reduces in the short-term the use of harmful coping strategies by 17%. However, this effect dissipates two years after the end of the intervention. The findings underscore the importance of small-scale vegetable support in addressing food insecurity in protracted conflict settings.Centre of Excellence for Development Impact and Learning (CEDILPeer Reviewe