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AbstractMicroplastics (MP) can be detected in all environmental systems. Marine and terrestrial aquatic systems, especially the transported suspended solids, have often been the focus of scientific investigations in the past. Sediments of aquatic river systems, on the other hand, were often ignored due to the time‐consuming sample preparation and analysis procedures. Spectroscopic measurement methods counting particle numbers are hardly suitable as detection methods, because there are plenty of natural particles next to a small number of MP particles. Integral methods, such as thermoanalytical methods are determining the particle mass independently of the inorganic components.In this study, a workflow for sample preparation via density separation and subsequent analysis by thermal extraction desorption‐gas chromatography/mass spectrometry is presented, which leads to representative and homogeneous samples and allows fast and robust MP mass content measurements suitable for routine analysis. Polymers were identified and quantified in all samples. Polyethylene and styrene‐butadiene rubber are the dominant polymers, besides polypropylene and polystyrene. Overall, total polymer masses between 1.18 and 337.0 µg/g could be determined. Highest MP concentrations in riverbed sediment are found in sites characterized by low flow velocities in harbors and reservoirs, while MP concentrations in sandy/gravelly bed sediments with higher flow velocities are small.
The LOBSTER (Deringer et al., 2011;Maintz et al., 2013 ,2016 ;Nelson et al., 2020 ) software aids in extracting quantum-chemical bonding information from materials by projecting the plane-wave based wave functions from density functional theory (DFT) onto an atomic orbital basis. LobsterEnv, a module implemented in pymatgen (Ong et al., 2013) by some of the authors of this package, facilitates the use of quantum-chemical bonding information obtained from LOBSTER calculations to identify neighbors and coordination environments. LobsterPy is a Python package that offers a set of convenient tools to further analyze and summarize the LobsterEnv outputs in the form of JSONs that are easy to interpret and process. These tools enable the estimation of (anti) bonding contributions, generation of textual descriptions, and visualization of LOBSTER computation results. Since its first release, both LobsterPy and LobsterEnv capabilities have been extended significantly. Unlike earlier versions, which could only automatically analyze Crystal Orbital Hamilton Populations (COHPs) (Dronskowski & Blöchl, 1993), both can now also analyze Crystal Orbital Overlap Populations (COOP) (Hughbanks & Hoffmann, 1983) and Crystal Orbital Bond Index (COBI) (Müller et al., 2021). Extracting the information about the most important orbitals contributing to the bonds is optional, and users can enable it as needed. Additionally, bonding-based features for machinelearning (ML) studies can be engineered via the sub-packages “featurize” and “structuregraphs”. Alongside its Python interface, it also provides an easy-to-use command line interface (CLI) that runs automatic analysis of the computations and generates a summary of results and publication-ready figures. LobsterPy has been used to produce the results in Ngo et al. (2023), Chen et al. (2024), Naik et al. (2023), and it is also part of Atomate2 (2023) bonding analysis workflow for generating bonding analysis data in a format compatible with the Materials Project (Jain et al., 2013) API.
Abstract
In the post-processing of large maritime components, a considerable amount of waste in the form of milling and grinding chips is produced. At the same time, additive manufacturing technologies have shown great potential in producing high-volume parts for maritime applications, allowing novel design approaches and short lead times. In this context, this study presents a sustainable approach to recycle and use aluminium bronze waste material, generated during post-processing of large cast ship propellers, as feedstock for laser-powder directed energy deposition. The recycling technology used to produce powder batches is inductive re-melting in combination with ultrasonic atomization. The derived metal powders are characterized using digital image analysis, powder flowability tests, scanning electron microscopy as well as energy dispersive X-ray spectroscopy. Compared to conventional metal powders produced by gas atomization, the recycled material shows excellent sphericity and a powder size distribution with a higher content of finer and coarser particles. Metallographic sections of deposited additively produced specimens show an increased hardness and reduced ductility, but also competitive densities and higher yield and ultimate tensile strength compared to cast material. The process chain shows high potential for the maritime sector to enable circular and sustainable manufacturing.
AbstractThe high-temperature corrosion behaviors of the equimolar CrCoNi medium-entropy alloy and CrMnFeCoNi high-entropy alloy were studied in a gas atmosphere consisting of a volumetric mixture of 10% H2O, 2% O2, 0.5% SO2, and 87.5% Ar at 800 °C for up to 96 h. Both alloys were initially single-phase fcc with a mean grain size of ~ 50 μm and a homogeneous chemical composition. The oxide layer thickness of CrMnFeCoNi increased linearly with exposure time while it remained constant at ~ 1 μm for CrCoNi. A Cr2O3 layer and minor amounts of (Co,Ni)Cr2O4 developed on the latter while three oxide layers were detected on the former, i.e., a thin and continuous chromium rich oxide layer at the oxide/alloy interface, a dense (Mn,Cr)3O4 layer in the center and a thick and porous layer of Mn3O4 and MnSO4 at the gas/oxide interface. Additionally, a few metal sulfides were observed in the CrMnFeCoNi matrix. These results were found to be in reasonable agreement with thermodynamic calculations.
The production of plastics is rising since they have been invented. Micro, submicro- and nanoplastics are produced intentionally or generated by environmental processes, and constitute ubiquitous contaminants which are ingested orally by consumers. Reported health concerns include intestinal translocation, inflammatory response, oxidative stress and cytotoxicity. Every digestive milieu in the gastrointestinal tract does have an influence on the properties of particles and can cause changes in their effect on biological systems. In this study, we subjected plastic particles of different materials (polylactic acid, polymethylmethacrylate, melamine formaldehyde) and sizes (micro- to nano-range) to a complex artificial digestion model consisting of three intestinal fluid simulants (saliva, gastric and intestinal juice). We monitored the impact of the digestion process on the particles by performing Dynamic Light Scattering, Scanning Electron Microscopy and Asymmetric Flow Field-Flow Fractionation. An in vitro model of the intestinal epithelial barrier was used to monitor cellular effects and translocation behavior of (un)digested particles. In conclusion, artificial digestion decreased cellular interaction and slightly increased transport of all particles across the intestinal barrier. The interaction with organic matter resulted in clear differences in the agglomeration behavior. Moreover, we provide evidence for polymer-, size- and surface-dependent cellular effects of the test particles.
We present Jobflow, a domain-agnostic Python package for writing computational workflows tailored for high-throughput computing applications. With its simple decorator-based approach, functions and class methods can be transformed into compute jobs that can be stitched together into complex workflows. Jobflow fully supports dynamic workflows where the full acyclic graph of compute jobs is not known until runtime, such as compute jobs that launch
other jobs based on the results of previous steps in the workflow. The results of all Jobflow compute jobs can be easily stored in a variety of filesystem- and cloud-based databases without the data storage process being part of the underlying workflow logic itself. Jobflow has been intentionally designed to be fully independent of the choice of workflow manager used to dispatch the calculations on remote computing resources. At the time of writing, Jobflow
workflows can be executed either locally or across distributed compute environments via an adapter to the FireWorks package, and Jobflow fully supports the integration of additional workflow execution adapters in the future.
Laser powder bed fusion of metallic components (PBF-LB/M) is gaining acceptance in industry. However, the high costs and lengthy qualification processes required for printed components create the need for more effective in-situ monitoring and testing methods. This article proposes multispectral Optical Tomography (OT) as a new approach for monitoring the PBF-LB/M process. Compared to other methods, OT is a low-cost process monitoring method that uses long-time exposure imaging to observe the build process. However, it lacks time resolution compared to expensive thermographic sensor systems. Monochromatic OT (1C-OT) is already commercially available and observes the building process layer-wise using a single wavelength window in the NIR range. Multispectral OT (nC-OT) utilizes a similar setup but can measure multiple wavelength ranges per location simultaneously. By comparing the classical 1C-OT and nC-OT approaches, this article examines the advantages of nC-OT (two channel OT and RGB-OT) in reducing the false positive rate for process deviations and approximating maximum temperatures for a better comparison between different build processes and materials. This could ultimately reduce costs and time for part qualification. The main goal of this contribution is to assess the advantages of nC-OT compared to 1C-OT for in-situ process monitoring of PBF-LB/M.
In recent decades, the number of components in concrete has grown, particularly in formulations aimed at reducing carbon footprints. Innovations include diverse binders, supplementary cementitious materials, activators, concrete admixtures, and recycled aggregates. These developments target not only the enhancement of material properties but also the mitigation of the ecological and economic impacts of concrete — the most extensively used material by humankind. However, these advancements also introduce a greater variability in the composition of raw materials. The material’s behavior is significantly influenced by its nanoscale properties, which can pose challenges in accurate characterization. Consequently, there’s an increasing need for experimental tuning of formulations. This is accompanied by a more inconsistent composition of raw materials, which makes an experimental tuning of formulations more and more necessary. However, the increased complexity in composition presents a challenge in finding the ideal formulation through trial and error. Inverse design (ID) techniques offer a solution to this challenge by allowing for a comprehensive search of the entire design space to create new and improved concrete formulations. In this publication, we introduce the concept of ID and demonstrate how our open-source app “SLAMD” provides all necessary steps of the workflow to adapt it in the laboratory, lowering the application barriers. The intelligent screening process, guided by a predictive model, leads to a more efficient and effective data-driven material design process resulting in reduced carbon footprint and improved material quality while considering socio-economic factors in the materials design.
Titanium and its alloys are known to allow the straightforward laser-based manufacturing of ordered surface nanostructures, so-called high spatial frequency laser-induced periodic surface structures (HSFL). These structures exhibit sub-100 nm spatial periods – far below the optical diffraction limit. The resulting surface functionalities are usually enabled by both, topographic and chemical alterations of the nanostructured surfaces. For exploring these effects, multi-method characterizations were performed here for HSFL processed on Ti–6Al–4V alloy upon irradiation with near-infrared ps-laser pulses (1030 nm, ≈1 ps pulse duration, 1–400 kHz) under different laser scan processing conditions, i.e., by systematically varying the pulse repetition frequency and the number of laser irradiation passes. The sample characterization involved morphological and topographical investigations by scanning electron microscopy (SEM), atomic force microscopy (AFM), tactile stylus profilometry, as well as near-surface chemical analyses hard X-ray photoelectron spectroscopy (HAXPES) and depth-profiling time-of-flight secondary ion mass spectrometry (ToF-SIMS). This provides a quantification of the laser ablation depth, the geometrical HSFL characteristics and enables new insights into the depth extent and the nature of the non-ablative laser-induced near-surface oxidation accompanying these nanostructures. This allows to answer the questions how the processing of HSFL can be industrially scaled up, and whether the latter is limited by heat-accumulation effects.
The process of viscous flow sintering is a phenomenon that is closely linked to the surface properties of the glass particles. In this work, we studied the extreme case of acid-leaching of soda-lime-silicate glass beads of two different particle size distributions and its effects on non-isothermal viscous sintering of powder compacts. Depth profiling of the chemical composition after leaching revealed a near-surface layer depleted in alkali and alkaline earth ions, associated with concurrent hydration as mass loss was detected by thermogravimetry. Heating microscopy showed that acid treatment of glasses shifted the sinter curves to higher temperatures with increasing leaching time. Modelling of the shrinkage with the cluster model predicted a higher viscosity of the altered surface layer, while analysis of the time scales of mass transport of mobile species (Na+, Ca2+ and H2O) during isochronous sintering revealed that diffusion of Na+ can compensate for concentration gradients before sintering begins. Also, exchanged water species can diffuse out of the altered layer, but the depletion of Ca2+ in the altered surface layer persists during the sinter interval, resulting in a glass with higher viscosity, which causes sintering to slow down.