Investigation of melt-grown dilute GaAsN and GaInAsN nanostructures for photovoltaics

AbstractThe present work demonstrates the possibility to use liquid phase epitaxy to incorporate nitrogen in epitaxial GaAsN/GaAs and GaInAsN/GaAs heterostructures, including nanoscaled ones. The structures are grown from Ga - and GaIn - melts containing polycrystalline GaN as a nitrogen source. The red shift of the absorption spectra corresponds to nitrogen content in the epitaxial layers near or less than 0.2 at %. Photoluminescence spectra of dilute nitride GaAsN and GaInAsN show emission from localized nitrogen states - N-nanoclusters of more than two N atoms. These studies show that the melt grown dilute GaAsN and GaInAsN nanostructures can be used for solar cells with extended long wavelength edge

Absolute and Relative Surrogate Measurements of the \u3csup\u3e236\u3c/sup\u3eU(\u3cem\u3en,f\u3c/em\u3e) Cross Section as a Probe of Angular Momentum Effects

Using both the absolute and relative surrogate techniques, the 236U(n,f) cross section was deduced over an equivalent neutron energy range of 0 to 20 MeV. A 42 MeV 3He beam from the 88 Inch Cyclotron at Lawrence Berkeley National Laboratory was used to perform a (3He,α) pickup reaction on targets of 235U (Jπ=7/2−) and 238U (Jπ = 0+) and the fission decay probabilities were determined. The 235U(3He,αf) and 238U(3He,αf) were surrogates for 233U(n,f) and 236U(n,f), respectively. The cross sections extracted using the surrogate method were compared to directly measured cross sections. The sensitivity of these cross sections to the Jπ -population distributions was explored

Absolute and Relative Surrogate Measurements of the 236U(n,f) Cross Section as a Probe for Angular Momentum Effects

Using both the absolute and relative surrogate techniques, the {sup 236}U(n,f) cross section was deduced over an equivalent neutron energy range of 0 to 20 MeV. A 42 MeV {sup 3}He beam from the 88-Inch Cyclotron at Lawrence Berkeley National Laboratory was used to perform a ({sup 3}He,{alpha}) pickup reaction on targets of {sup 235}U (J{sup {pi}}=7/2{sup -}) and {sup 238}U (J{sup {pi}}=0{sup +}) and the fission decay probabilities were determined. The {sup 235}U({sup 3}He,{alpha}f) and {sup 238}U({sup 3}He,{alpha}f) were surrogates for {sup 233}U(n,f) and {sup 236}U(n,f), respectively. The cross sections extracted using the Surrogate Method were compared to directly measured cross sections. The sensitivity of these cross sections to the J{sup {pi}}-population distributions was explored

Multi-decadal improvements in the ecological quality of European rivers are not consistently reflected in biodiversity metrics

Humans impact terrestrial, marine and freshwater ecosystems, yet many broad-scale studies have found no systematic, negative biodiversity changes (for example, decreasing abundance or taxon richness). Here we show that mixed biodiversity responses may arise because community metrics show variable responses to anthropogenic impacts across broad spatial scales. We first quantified temporal trends in anthropogenic impacts for 1,365 riverine invertebrate communities from 23 European countries, based on similarity to least-impacted reference communities. Reference comparisons provide necessary, but often missing, baselines for evaluating whether communities are negatively impacted or have improved (less or more similar, respectively). We then determined whether changing impacts were consistently reflected in metrics of community abundance, taxon richness, evenness and composition. Invertebrate communities improved, that is, became more similar to reference conditions, from 1992 until the 2010s, after which improvements plateaued. Improvements were generally reflected by higher taxon richness, providing evidence that certain community metrics can broadly indicate anthropogenic impacts. However, richness responses were highly variable among sites, and we found no consistent responses in community abundance, evenness or composition. These findings suggest that, without sufficient data and careful metric selection, many common community metrics cannot reliably reflect anthropogenic impacts, helping explain the prevalence of mixed biodiversity trends.We thank J. England for assistance with calculating ecological quality and the biomonitoring indices in the UK. Funding for authors, data collection and processing was provided by the European Union Horizon 2020 project eLTER PLUS (grant number 871128). F.A. was supported by the Swiss National Science Foundation (grant numbers 310030_197410 and 31003A_173074) and the University of Zurich Research Priority Program Global Change and Biodiversity. J.B. and M.A.-C. were funded by the European Commission, under the L‘Instrument Financier pour l’Environnement (LIFE) Nature and Biodiversity program, as part of the project LIFE-DIVAQUA (LIFE18 NAT/ES/000121) and also by the project ‘WATERLANDS’ (PID2019-107085RB-I00) funded by the Ministerio de Ciencia, Innovación y Universidades (MCIN) and Agencia Estatal de Investigación (AEI; MCIN/AEI/10.13039/501100011033/ and by the European Regional Development Fund (ERDF) ‘A way of making Europe’. N.J.B. and V.P. were supported by the Lithuanian Environmental Protection Agency (https://aaa.lrv.lt/) who collected the data and were funded by the Lithuanian Research Council (project number S-PD-22-72). J.H. was supported by the Academy of Finland (grant number 331957). S.C.J. acknowledges funding by the Leibniz Competition project Freshwater Megafauna Futures and the German Federal Ministry of Education and Research (Bundesministerium für Bildung und Forschung or BMBF; 033W034A). A.L. acknowledges funding by the Spanish Ministry of Science and Innovation (PID2020-115830GB-100). P.P., M.P. and M.S. were supported by the Czech Science Foundation (GA23-05268S and P505-20-17305S) and thank the Czech Hydrometeorological Institute and the state enterprises Povodí for the data used to calculate ecological quality metrics from the Czech surface water monitoring program. H.T. was supported by the Estonian Research Council (number PRG1266) and by the Estonian national program ‘Humanitarian and natural science collections’. M.J.F. acknowledges the support of Fundação para a Ciência e Tecnologia, Portugal, through the projects UIDB/04292/2020 and UIDP/04292/2020 granted to the Marine and Environmental Sciences Centre, LA/P/0069/2020 granted to the Associate Laboratory Aquatic Research Network (ARNET), and a Call Estímulo ao Emprego Científico (CEEC) contract.Peer reviewe

The recovery of European freshwater biodiversity has come to a halt

Owing to a long history of anthropogenic pressures, freshwater ecosystems are among the most vulnerable to biodiversity loss1. Mitigation measures, including wastewater treatment and hydromorphological restoration, have aimed to improve environmental quality and foster the recovery of freshwater biodiversity2. Here, using 1,816 time series of freshwater invertebrate communities collected across 22 European countries between 1968 and 2020, we quantified temporal trends in taxonomic and functional diversity and their responses to environmental pressures and gradients. We observed overall increases in taxon richness (0.73% per year), functional richness (2.4% per year) and abundance (1.17% per year). However, these increases primarily occurred before the 2010s, and have since plateaued. Freshwater communities downstream of dams, urban areas and cropland were less likely to experience recovery. Communities at sites with faster rates of warming had fewer gains in taxon richness, functional richness and abundance. Although biodiversity gains in the 1990s and 2000s probably reflect the effectiveness of water-quality improvements and restoration projects, the decelerating trajectory in the 2010s suggests that the current measures offer diminishing returns. Given new and persistent pressures on freshwater ecosystems, including emerging pollutants, climate change and the spread of invasive species, we call for additional mitigation to revive the recovery of freshwater biodiversity.N. Kaffenberger helped with initial data compilation. Funding for authors and data collection and processing was provided by the EU Horizon 2020 project eLTER PLUS (grant agreement no. 871128); the German Federal Ministry of Education and Research (BMBF; 033W034A); the German Research Foundation (DFG FZT 118, 202548816); Czech Republic project no. P505-20-17305S; the Leibniz Competition (J45/2018, P74/2018); the Spanish Ministerio de Economía, Industria y Competitividad—Agencia Estatal de Investigación and the European Regional Development Fund (MECODISPER project CTM 2017-89295-P); Ramón y Cajal contracts and the project funded by the Spanish Ministry of Science and Innovation (RYC2019-027446-I, RYC2020-029829-I, PID2020-115830GB-100); the Danish Environment Agency; the Norwegian Environment Agency; SOMINCOR—Lundin mining & FCT—Fundação para a Ciência e Tecnologia, Portugal; the Swedish University of Agricultural Sciences; the Swiss National Science Foundation (grant PP00P3_179089); the EU LIFE programme (DIVAQUA project, LIFE18 NAT/ES/000121); the UK Natural Environment Research Council (GLiTRS project NE/V006886/1 and NE/R016429/1 as part of the UK-SCAPE programme); the Autonomous Province of Bolzano (Italy); and the Estonian Research Council (grant no. PRG1266), Estonian National Program ‘Humanitarian and natural science collections’. The Environment Agency of England, the Scottish Environmental Protection Agency and Natural Resources Wales provided publicly available data. We acknowledge the members of the Flanders Environment Agency for providing data. This article is a contribution of the Alliance for Freshwater Life (www.allianceforfreshwaterlife.org).Peer reviewe

Time series of freshwater macroinvertebrate abundances and site characteristics of European streams and rivers

Freshwater macroinvertebrates are a diverse group and play key ecological roles, including accelerating nutrient cycling, filtering water, controlling primary producers, and providing food for predators. Their differences in tolerances and short generation times manifest in rapid community responses to change. Macroinvertebrate community composition is an indicator of water quality. In Europe, efforts to improve water quality following environmental legislation, primarily starting in the 1980s, may have driven a recovery of macroinvertebrate communities. Towards understanding temporal and spatial variation of these organisms, we compiled the TREAM dataset (Time seRies of European freshwAter Macroinvertebrates), consisting of macroinvertebrate community time series from 1,816 river and stream sites (mean length of 19.2 years and 14.9 sampling years) of 22 European countries sampled between 1968 and 2020. In total, the data include >93 million sampled individuals of 2,648 taxa from 959 genera and 212 families. These data can be used to test questions ranging from identifying drivers of the population dynamics of specific taxa to assessing the success of legislative and management restoration efforts.Nathalie Kaffenberger aided in initial data compilation. Funding for authors, data collection and processing was provided by the EU Horizon 2020 project eLTER PLUS (grant agreement no. 871128), German Federal Ministry of Education and Research (BMBF; 033W034A), German Research Foundation (DFG FZT 118, 202548816), the Collaborative Research Centre 1439 RESIST (DFG—SFB 1439/1 2021 –426547801), Czech Republic project no. GA23-05268S, the Leibniz Competition (J45/2018, P74/2018), the Spanish Ministerio de Economía, Industria y Competitividad - Agencia Estatal de Investigación and the European Regional Development Fund (MECODISPER project CTM 2017-89295-P), Ramón y Cajal contracts and the project funded by the Spanish Ministry of Science and Innovation (RYC2019-027446-I, RYC2020-029829-I, PID2020-115830GB-100), the Danish Environment Agency, the Norwegian Environment Agency, SOMINCOR – Lundin mining & FCT - Fundação para a Ciência e Tecnologia, Portugal, the Swedish University of Agricultural Sciences, the Swiss National Science Foundation (Grant PP00P3_179089), the EU LIFE programme (DIVAQUA project - LIFE18 NAT/ES/000121), and the UK Natural Environment Research Council (GLiTRS project -NE/V006886/1 and NE/R016429/1 as part of the UK-SCAPE programme), the Autonomous Province of Bolzano (Italy), Estonian Research Council (grant No PRG1266), Estonian national program ‘Humanitarian and natural science collections’. The Environment Agency of England, the Scottish Environmental Protection Agency and Natural Resources Wales provided publicly available data. The collection of data from the Rhône River in France was greatly aided by Marie-Claude Roger (INRAE Lyon), Jean-Claude Berger (INRAE AIX), and Pâquerette Dessaix (ARALEP). We are also grateful to the French Regional Environment Directorates (DREALs) for their collaboration in harmonising the long-term data series from the other French rivers. We thank the AWEL from the Canton of Zurich for providing access to macroinvertebrate data from the AWEL monitoring scheme. We acknowledge the Flanders Environment Agency, the Rhineland-Palatinate State Office for the Environment and the Bulgarian Executive Environment Agency for providing data. This manuscript is a contribution of the Alliance for Freshwater Life (www.allianceforfreshwaterlife.org). Any views expressed within this paper are those of the authors and do not necessarily represent the views of their respective employer organisations.Peer reviewe

The (3He,tf) as a surrogate reaction to determine (n,f) cross sections in the 10 to 20 MeV energy range

The surrogate reaction 238U(3He,tf) is used to determine the 237Np(n,f) cross section indirectly over an equivalent neutron energy range from 10 to 20 MeV. A self-supporting ~;;761 mu g/cm2 metallic 238U foil was bombarded with a 42 MeV 3He2+ beam from the 88-Inch Cyclotron at Lawrence Berkeley National Laboratory (LBNL). Outgoing charged particles and fission fragments were identified using the Silicon Telescope Array for Reaction Studies (STARS), consists of two 140 mu m and one 1000 mu m Micron S2 type silicon detectors. The 237Np(n,f) cross sections, determined indirectly, were compared with the 237Np(n,f) cross section data from direct measurements, the Evaluated Nuclear Data File (ENDF/B-VII.0), and the Japanese Evaluated Nuclear Data Library (JENDL 3.3) and found to closely follow those datasets. Use of the (3He,tf) reaction as a surrogate to extract (n,f) cross section in the 10 to 20 MeV equivalent neutron energy is found to be suitable

Distribution et abondance de microorganismes méthagéniques et méthatrophes dans les cours d'eau européens

International audienceGlobally, streams and rivers emit a significant amount of methane, a highly potent greenhouse gas. However, little is known about stream sediment microbial communities, driving the net methane balance in these systems, especially on their distribution and composition at large spatial scales. Within the project Euro Methane we investigated the diversity and abundance of methanogenic archaea and methane-oxidizing bacteria across 16 European streams (from northern Spain to central Sweden) via 16S rRNA sequencing and qPCR. We determined environmental drivers of both abundance and community composition and explored the link to measured potential methane production and oxidation rates of the respective sediments. We found that the community composition of methane-oxidizing bacteria significantly differed among the studied streams, while methanogenic archaea were more homogeneously distributed. Beyond the overall diversity trends, indicator species for stream types were identified. Methanogenic Methanosaeta sp. and methane-oxidizing Methyloglobulus sp. increased with geographical latitude and dominated in headwater streams (orders 1-3) with high oxygen levels and high proportions of pristine land within the catchment, while methanogenic Methanomethylovorans sp. and methane-oxidizing Methylocaldum spp. were more common in larger streams (orders 4-6) with higher discharge and agricultural influence. Potential methane production rates significantly increased with abundance of methanogenic archaea, while potential methane oxidation rates did not show significant correlations with methane oxidizing bacteria, presumably due to the more diverse physiological capabilities of this microbial group. Our study represents a holistic large-scale biogeographical overview of two microbial groups to enhance our understanding of the methane cycle within a heretofore understudied ecosystem