Glide Mechanisms for Bundle- and Plate-like Structures

In this article, the slip mechanisms card deck glide and pencil glide are recaptured. These mechanisms are useful simplifications when several slip systems in crystals, bundle- or plate-like structurs share a common shear plane n or a common shear direction d. It is pointed out that a third glide mechanism for slip systems with a common plane of shear k = d × n exists. For this second pencil glide mechanism, its properties are examined, a flow rule is derived, and the push-forward of k in case of large elastic strains is discussed. It turns out that the second pencil glide mechanism leads to a plane strain Prandtl-Reuss-like flow rule. Thus, unlike the pencil and the card glide mechanism, there is no accompanying lattice spin

Numerical Properties of Spherical and Cubical Representative Volume Elements with Different Boundary Conditions

It has been found that, due to the smaller surface to volume ratio, the spherical representative volume elements (RVE) converge faster to the effective properties than cubical RVEs, in terms of the RVE volume (Gl¨uge et al., 2012). It remains to discuss whether one can actually draw a numerical advantage from this in the finite element calculations, since there are also some drawbacks, for example the necessarily irregular meshing. It has been demonstrated that the boundary conditions, in conjunction with different solution strategies for the linear system that emerges in the FEM, can significantly influence the numerical expense (Fritzen and B¨ohlke, 2010a). In the light of these results, we examine the numerical properties of spherical and cubical RVEs with linear displacement and periodic (resp. antipodic) boundary conditions

Graphical Representations of the Regions of Rank-One-Convexity of some Strain Energies

Isotropic elastic energies which are quadratic in the strain measures of the Seth family are known not to be rankone-convex in the entire domain of invertible deformation gradients with positive determinant. Therefore, they are in principle capable of displaying a laminated microstructure. Nevertheless, they are commonly used for standard elastic solids. In general one does not observe a microstructure evolution due to the fact that the solution is not sought outside of the region of rank-one-convexity. Consequently, the question for the boundaries of the region of rank-one-convexity arises. We address this question by applying a set of necessary and sufficient conditions for rank-one-convexity to the mentioned elastic energies, and give graphical representations for the regions of rank-one-convexit

Selke, Peter: Höhere Festigkeitslehre

Oldenbourg Verlag, 2013, 332 Seiten, ISBN 978-3-486-71407-4 € 39,80 , USD 56,0

The effect of the skin-core structure of injection-molded isotactic polypropylene on the stress distribution in bending tests

We examine the effect of the skin-core structure of isotactic polypropylene (iPP) in bending tests. The depth-dependent material properties are determined in tensile tests and mapped to a finite element model. This enables the examination of internal stresses during bending numerically. In a bending test, one usually expects a monotonic stress distribution across the thickness, provided that the material is homogeneous and does not strain-soften. We found that the structural gradient of injection-molded iPP easily overcompensates the monotonic stress dependence, such that the maximal equivalent von Mises stress lies well below the surface in the so called shear layer. The latter is a result of the injection molding process

Concentrations of organic contaminants in industrial and municipal bioresources recycled in agriculture in the UK

Many types of bioresource materials are recycled in agriculture for soil improvement and as bedding materials for livestock and have potential for transfer into plant and animal foods. Representative types of industrial and municipal bioresources were selected to assess the extent of organic chemical contamination, including: (i) land applied materials: treated sewage sludge biosolids), meat and bone meal ash (MBMA), poultry litter ash (PLA), paper sludge ash (PSA) and compost-like-output (CLO), and (ii) bedding materials: recycled waste wood (RWW), dried paper sludge (DPS), paper sludge ash (PSA) and shredded cardboard. The materials generally contained lower concentrations of polychlorinated dibenzo-pdioxins/dibenzofurans (PCDD/Fs) and dioxin-like polychlorinated biphenyls (PCBs) relative to earlier reports, indicating the decline in environmental emissions of these established contaminants. However, concentrations of polycyclic aromatic hydrocarbons (PAHs) remain elevated in biosolids samples from urban catchments. Polybrominated dibenzo-p-dioxins/dibenzofurans (PBDD/Fs) were present in larger amounts in biosolids and CLO compared to their chlorinated counterparts and hence are of potentially greater significance in contemporary materials. The presence of non-ortho-polychlorinated biphenyls (PCBs) in DPS was probably due to non-legacy sources of PCBs in paper production. Emerging flame retardant compounds, including: decabromodiphenylethane (DBDPE)and organophosphate flame retardants (OPFRs), were detected in several of the materials. The profile of perfluoroalkyl substances (PFAS) depended on the type of waste category; perfluoroundecanoic acid (PFUnDA) was the most significant PFAS for DPS, whereas perfluorooctane sulfonate (PFOS) was dominant in biosolids and CLO. The concentrations of polychlorinated alkanes (PCAs) and di-2-ethylhexyl phthalate (DEHP) were generally much larger than the other contaminants measured, indicating that there are major anthropogenic sources of these potentially hazardous chemicals entering the environment. The study results suggest that continued vigilance is required to control emissions and sources of these contaminants to support the beneficial use of secondary bioresource materials

The NORMAN Suspect List Exchange (NORMAN-SLE): Facilitating European and worldwide collaboration on suspect screening in high resolution mass spectrometry

Background: The NORMAN Association (https://www.norman-network.com/) initiated the NORMAN Suspect List Exchange (NORMAN-SLE; https://www.norman-network.com/nds/SLE/) in 2015, following the NORMAN collaborative trial on non-target screening of environmental water samples by mass spectrometry. Since then, this exchange of information on chemicals that are expected to occur in the environment, along with the accompanying expert knowledge and references, has become a valuable knowledge base for “suspect screening” lists. The NORMAN-SLE now serves as a FAIR (Findable, Accessible, Interoperable, Reusable) chemical information resource worldwide. Results: The NORMAN-SLE contains 99 separate suspect list collections (as of May 2022) from over 70 contributors around the world, totalling over 100,000 unique substances. The substance classes include per- and polyfluoroalkyl substances (PFAS), pharmaceuticals, pesticides, natural toxins, high production volume substances covered under the European REACH regulation (EC: 1272/2008), priority contaminants of emerging concern (CECs) and regulatory lists from NORMAN partners. Several lists focus on transformation products (TPs) and complex features detected in the environment with various levels of provenance and structural information. Each list is available for separate download. The merged, curated collection is also available as the NORMAN Substance Database (NORMAN SusDat). Both the NORMAN-SLE and NORMAN SusDat are integrated within the NORMAN Database System (NDS). The individual NORMAN-SLE lists receive digital object identifiers (DOIs) and traceable versioning via a Zenodo community (https://zenodo.org/communities/norman-sle), with a total of > 40,000 unique views, > 50,000 unique downloads and 40 citations (May 2022). NORMAN-SLE content is progressively integrated into large open chemical databases such as PubChem (https://pubchem.ncbi.nlm.nih.gov/) and the US EPA’s CompTox Chemicals Dashboard (https://comptox.epa.gov/dashboard/), enabling further access to these lists, along with the additional functionality and calculated properties these resources offer. PubChem has also integrated significant annotation content from the NORMAN-SLE, including a classification browser (https://pubchem.ncbi.nlm.nih.gov/classification/#hid=101). Conclusions: The NORMAN-SLE offers a specialized service for hosting suspect screening lists of relevance for the environmental community in an open, FAIR manner that allows integration with other major chemical resources. These efforts foster the exchange of information between scientists and regulators, supporting the paradigm shift to the “one substance, one assessment” approach. New submissions are welcome via the contacts provided on the NORMAN-SLE website (https://www.norman-network.com/nds/SLE/)

The NORMAN Suspect List Exchange (NORMAN-SLE): facilitating European and worldwide collaboration on suspect screening in high resolution mass spectrometry

The NORMAN Association (https://www.norman-network.com/) initiated the NORMAN Suspect List Exchange (NORMAN-SLE; https://www.norman-network.com/nds/SLE/) in 2015, following the NORMAN collaborative trial on non-target screening of environmental water samples by mass spectrometry. Since then, this exchange of information on chemicals that are expected to occur in the environment, along with the accompanying expert knowledge and references, has become a valuable knowledge base for "suspect screening" lists. The NORMAN-SLE now serves as a FAIR (Findable, Accessible, Interoperable, Reusable) chemical information resource worldwide.The NORMAN-SLE project has received funding from the NORMAN Association via its joint proposal of activities. HMT and ELS are supported by the Luxembourg National Research Fund (FNR) for project A18/BM/12341006. ELS, PC, SEH, HPHA, ZW acknowledge funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 101036756, project ZeroPM: Zero pollution of persistent, mobile substances. The work of EEB, TC, QL, BAS, PAT, and JZ was supported by the National Center for Biotechnology Information of the National Library of Medicine (NLM), National Institutes of Health (NIH). JOB is the recipient of an NHMRC Emerging Leadership Fellowship (EL1 2009209). KVT and JOB acknowledge the support of the Australian Research Council (DP190102476). The Queensland Alliance for Environmental Health Sciences, The University of Queensland, gratefully acknowledges the financial support of the Queensland Department of Health. NR is supported by a Miguel Servet contract (CP19/00060) from the Instituto de Salud Carlos III, co-financed by the European Union through Fondo Europeo de Desarrollo Regional (FEDER). MM and TR gratefully acknowledge financial support by the German Ministry for Education and Research (BMBF, Bonn) through the project “Persistente mobile organische Chemikalien in der aquatischen Umwelt (PROTECT)” (FKz: 02WRS1495 A/B/E). LiB acknowledges funding through a Research Foundation Flanders (FWO) fellowship (11G1821N). JAP and JMcL acknowledge financial support from the NIH for CCSCompendium (S50 CCSCOMPEND) via grants NIH NIGMS R01GM092218 and NIH NCI 1R03CA222452-01, as well as the Vanderbilt Chemical Biology Interface training program (5T32GM065086-16), plus use of resources of the Center for Innovative Technology (CIT) at Vanderbilt University. TJ was (partly) supported by the Dutch Research Council (NWO), project number 15747. UFZ (TS, MaK, WB) received funding from SOLUTIONS project (European Union’s Seventh Framework Programme for research, technological development and demonstration under Grant Agreement No. 603437). TS, MaK, WB, JPA, RCHV, JJV, JeM and MHL acknowledge HBM4EU (European Union’s Horizon 2020 research and innovation programme under the grant agreement no. 733032). TS acknowledges funding from NFDI4Chem—Chemistry Consortium in the NFDI (supported by the DFG under project number 441958208). TS, MaK, WB and EMLJ acknowledge NaToxAq (European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie Grant Agreement No. 722493). S36 and S63 (HPHA, SEH, MN, IS) were funded by the German Federal Ministry for the Environment, Nature Conservation and Nuclear Safety (BMU) Project No. (FKZ) 3716 67 416 0, updates to S36 (HPHA, SEH, MN, IS) by the German Federal Ministry for the Environment, Nature Conservation, Nuclear Safety and Consumer Protection (BMUV) Project No. (FKZ) 3719 65 408 0. MiK acknowledges financial support from the EU Cohesion Funds within the project Monitoring and assessment of water body status (No. 310011A366 Phase III). The work related to S60 and S82 was funded by the Swiss Federal Office for the Environment (FOEN), KK and JH acknowledge the input of Kathrin Fenner’s group (Eawag) in compiling transformation products from European pesticides registration dossiers. DSW and YDF were supported by the Canadian Institutes of Health Research and Genome Canada. The work related to S49, S48 and S77 was funded by the MAVA foundation; for S77 also the Valery Foundation (KG, JaM, BG). DML acknowledges National Science Foundation Grant RUI-1306074. YL acknowledges the National Natural Science Foundation of China (Grant No. 22193051 and 21906177), and the Chinese Postdoctoral Science Foundation (Grant No. 2019M650863). WLC acknowledges research project 108C002871 supported by the Environmental Protection Administration, Executive Yuan, R.O.C. Taiwan (Taiwan EPA). JG acknowledges funding from the Swiss Federal Office for the Environment. AJW was funded by the U.S. Environmental Protection Agency. LuB, AC and FH acknowledge the financial support of the Generalitat Valenciana (Research Group of Excellence, Prometeo 2019/040). KN (S89) acknowledges the PhD fellowship through Marie Skłodowska-Curie grant agreement No. 859891 (MSCA-ETN). Exposome-Explorer (S34) was funded by the European Commission projects EXPOsOMICS FP7-KBBE-2012 [308610]; NutriTech FP7-KBBE-2011-5 [289511]; Joint Programming Initiative FOODBALL 2014–17. CP acknowledges grant RYC2020-028901-I funded by MCIN/AEI/1.0.13039/501100011033 and “ESF investing in your future”, and August T Larsson Guest Researcher Programme from the Swedish University of Agricultural Sciences. The work of ML, MaSe, SG, TL and WS creating and filling the STOFF-IDENT database (S2) mostly sponsored by the German Federal Ministry of Education and Research within the RiSKWa program (funding codes 02WRS1273 and 02WRS1354). XT acknowledges The National Food Institute, Technical University of Denmark. MaSch acknowledges funding by the RECETOX research infrastructure (the Czech Ministry of Education, Youth and Sports, LM2018121), the CETOCOEN PLUS project (CZ.02.1.01/0.0/0.0/15_003/0000469), and the CETOCOEN EXCELLENCE Teaming 2 project supported by the Czech ministry of Education, Youth and Sports (No CZ.02.1.01/0.0/0.0/17_043/0009632).Peer reviewe