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Organisationseinheit der BAM
- 6 Materialchemie (187)
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- 6.1 Oberflächen- und Dünnschichtanalyse (39)
- 4 Material und Umwelt (34)
The PMD Core Ontology (PMDco) is a comprehensive set of building blocks produced via consensus building. The ontological building blocks provide a framework representing knowledge about fundamental concepts used in Materials Science and Engineering (MSE) today. The PMDco is a mid-level ontology that establishes connections between narrower MSE application ontologies and domain neutral concepts used in already established broader (top-level) ontologies. The primary goal of the PMDco design is to enable interoperability between various other MSE-related ontologies and other common ontologies.
PMDco’s class structure is both comprehensive and extensible, rendering it an efficient tool to structure MSE knowledge. The PMDco serves as a semantic middle-layer unifying common MSE concepts via semantic mapping to other semantic representations using well-known key terms used in the MSE domain. The PMDco enables straight-forward documentation and tracking of science data generation and in consequence enables high-quality FAIR data that allows for precise reproducibility of scientific experiments.
The design of PMDco is based on the W3C Provenance Ontology (PROV-O), which provides a standard framework for capturing the production, derivation, and attribution of resources. Via this foundation, the PMDco enables the integration of data from various data origins and the representation of complex workflows.
In summary, the PMDco is a valuable advancement for researchers and practitioners in MSE domains. It provides a common MSE vocabulary to represent and share knowledge, allowing for efficient collaboration and promoting interoperability between diverse domains. Its design allows for the systematic integration of data and metadata, enabling seamless tracing of science data. Overall, the PMDco is a crucial step towards a unified and comprehensive understanding of the MSE domain in general.
Argyrodite-type materials have lately sparked a lot of research interest due to their thermoelectric properties. One promising candidate is canfieldite (Ag8SnS6), which has a Pna21 orthorhombic crystal structure at room temperature (RT). Recently, Slade group found a new low-temperature (LT) phase transition of canfieldite at 120K. Therefore, we investigate structural, vibrational and thermodynamic properties of Ag8SnS6 at room- and low-temperature employing density-functional theory (DFT) and lattice dynamics computations. Thermal properties calculations were based on the quasi-harmonic approximation (QHA) as implemented in phonopy. We achieve good agreement with experiments. Lattice parameters were overestimated by 2%, and thermal properties such as the constant-pressure heat capacity Cp are very close to experimental measurements. Our simulations also reveal a possible new phase transition at around 312 K. Furthermore, we compared RT and LT Ag8SnS6 Grüneisen parameters with some argyrodites analogues, Ag8TS6 (T = Si, Ge, Ti and Sn), finding a relationship between the anharmonicity and low thermal conductivity.
Zirconium vanadate (ZrV2O7) is a well-known negative thermal expansion (NTE) material which exhibits significant isotropic contraction over a broad temperature range (~150°C < T < 800°C). The linear thermal expansion coefficient of ZrV2O7 is −7.1×10-6 K-. Therefore, it can be used to create composites with controllable expansion coefficients and prevent destruction by thermal shock.
Material characterization, leading to application, requires pure, homogenous samples of high crystallinity via a reliable synthesis route. While there is a selection of described syntheses in the literature, it still needs to be addressed which synthesis route leads to truly pure and homogenous samples. Here, we study the influence of the synthesis methods (solid-state, sol-gel, solvothermal) and their parameters on the sample's purity, crystallinity, and homogeneity. The reproducibility of results and data obtained with scanning electron microscopy (SEM), X-ray diffraction (XRD), differential scanning calorimetry, and thermogravimetric analysis (DSC/TGA) were analyzed extensively. The sol-gel method proves superior to the solid-state method and produces higher-quality samples over varying parameters. Sample purity also plays an important role in NTE micro and macro-scale characterizations that explain the impact of porosity versus structural changes.
Moreover, we implement ab-initio-based vibrational computations with partially treated anharmonicity (quasi-harmonic approximation, temperature-dependent effective harmonic potentials) in combination with experimental methods to follow and rationalize the negative thermal expansion in this material, including the influence of the local structure disorder, microstructure, and defects. Khosrovani et al. and Korthuis et al., in a series of diffraction experiments, attributed the thermal contraction of ZrV2O7 to the transverse thermal motion of oxygen atoms in V-O-V linkages. In addition to previous explanations, we hypothesize that local disorder develops in ZrV2O7 crystals during heating.
We are working on the experimental ZrV2O7 development and discuss difficulties one might face in the process as well as high-quality sample significance in further investigation. The obtained samples are currently used in the ongoing research of structure analysis and the negative thermal expansion mechanism.
Zirconium vanadate (ZrV2O7) is a well-known negative thermal expansion (NTE) material which exhibits significant isotropic contraction over a broad temperature range (~150°C < T < 800°C). The linear thermal expansion coefficient of ZrV2O7 is −7.1×10-6 K-. Therefore, it can be used to create composites with controllable expansion coefficients and prevent destruction by thermal shock.
Material characterization, leading to application, requires pure, homogenous samples of high crystallinity via a reliable synthesis route. While there is a selection of described syntheses in the literature, it still needs to be addressed which synthesis route leads to truly pure and homogenous samples. Here, we study the influence of the synthesis methods (solid-state, sol-gel, solvothermal) and their parameters on the sample's purity, crystallinity, and homogeneity. The reproducibility of results and data obtained with scanning electron microscopy (SEM), X-ray diffraction (XRD), differential scanning calorimetry, and thermogravimetric analysis (DSC/TGA) were analyzed extensively. The sol-gel method proves superior to the solid-state method and produces higher-quality samples over varying parameters. Sample purity also plays an important role in NTE micro and macro-scale characterizations that explain the impact of porosity versus structural changes.
Moreover, we implement ab-initio-based vibrational computations with partially treated anharmonicity (quasi-harmonic approximation, temperature-dependent effective harmonic potentials) in combination with experimental methods to follow and rationalize the negative thermal expansion in this material, including the influence of the local structure disorder, microstructure, and defects. Khosrovani et al. and Korthuis et al., in a series of diffraction experiments, attributed the thermal contraction of ZrV2O7 to the transverse thermal motion of oxygen atoms in V-O-V linkages. In addition to previous explanations, we hypothesize that local disorder develops in ZrV2O7 crystals during heating.
We are working on the experimental ZrV2O7 development and discuss difficulties one might face in the process as well as high-quality sample significance in further investigation. The obtained samples are currently used in the ongoing research of structure analysis and the negative thermal expansion mechanism.
Zirconium vanadate (ZrV2O7) is a well-known negative thermal expansion (NTE) material which exhibits significant isotropic contraction over a broad temperature range (~150°C < T < 800°C). The linear thermal expansion coefficient of ZrV2O7 is −7.1×10-6 K-1. Therefore, it can be used to create composites with controllable expansion coefficients and prevent destruction by thermal shock.
Material characterization, leading to application, requires pure, homogenous samples of high crystallinity via a reliable synthesis route. While there is a selection of described syntheses in the literature, it still needs to be addressed which synthesis route leads to truly pure and homogenous samples. Here, we study the influence of the synthesis methods (solid-state, sol-gel, solvothermal) and their parameters on the sample's purity, crystallinity, and homogeneity. The reproducibility of results and data obtained with scanning electron microscopy (SEM), X-ray diffraction (XRD), differential scanning calorimetry, and thermogravimetric analysis (DSC/TGA) were analyzed extensively. The sol-gel method proves superior to the solid-state method and produces higher-quality samples over varying parameters. Sample purity also plays an important role in NTE micro and macro-scale characterizations that explain the impact of porosity versus structural changes.
Moreover, we implement ab-initio-based vibrational computations with partially treated anharmonicity (quasi-harmonic approximation, temperature-dependent effective harmonic potentials) in combination with experimental methods to follow and rationalize the negative thermal expansion in this material, including the influence of the local structure disorder, microstructure, and defects. Khosrovani et al. and Korthuis et al., in a series of diffraction experiments, attributed the thermal contraction of ZrV2O7 to the transverse thermal motion of oxygen atoms in V-O-V linkages. In addition to previous explanations, we hypothesize that local disorder develops in ZrV2O7 crystals during heating.
We are working on the experimental ZrV2O7 development and discuss difficulties one might face in the process as well as high-quality sample significance in further investigation. The obtained samples are currently used in the ongoing research of structure analysis and the negative thermal expansion mechanism.
Current challenges and objectives for non-invasive optical bioimaging are deep tissue penetration, high detection sensitivity, high spatial and temporal resolution, and fast data acquisition. A promising spectral window to tackle these challenges is the short-wave infrared (SWIR) ranging from 900 nm to 1700 nm where scattering, absorption, and autofluorescence of biological components are strongly reduced compared to the visible/NIR. At present, the best performing SWIR contrast agents are based on nanomaterials containing toxic heavy-metal ions like cadmium or lead, which raises great concerns for biological applications. Promising heavy-metal free nanoscale candidates are gold nanoclusters (AuNCs) and Ag2S nanoparticles (NPs). The photoluminescence (PL) of both types of nanomaterials is very sensitive to their size, composition of their surface ligand shell, and element composition, which provides an elegant handle to fine-tune their absorption and emission features and boost thereby the size of the signals recorded in bioimaging studies.
Aiming for the development of SWIR contrast agents with optimum performance, we dived deeper into the photophysical processes occurring in these nanomaterials, thereby exploring in depth how the environment, surface ligand composition, and the incorporation of transition metals influence the optical properties of AuNCs and Ag2S NPs. We observed a strong enhancement of the SWIR emission of AuNCs upon exposure to different local environments (in solution, polymer, and in the solid state). Addition of metal ions such as Zn2+ to Ag2S based NPs led to a strong PL enhancement, yielding PL quantum yields of about 10% and thus making them highly suitable for non-invasive deep imaging of vascular networks and 3D fluid flow mapping.
In recent years, chromium (III) complexes have received a lot of attention as novel near-infrared (NIR) emitters. This interest was triggered by the report on the first molecular ruby Cr(ddpd)2(BF4)3 with a high photoluminescence quantum yield of 13.7% of its near infrared (NIR) emission band and a long luminescence lifetime of 1.122 ms at room temperature. Meanwhile, the influence of triplet oxygen, temperature, and pressure on the optical properties of different molecular rubies have been assessed. These features make these molecular rubies promising candidates for multi-analyte optical sensing applications and the generation of singlet oxygen for photocatalysis and photodynamic therapy. However, in an oxygen-containing environment, the photoluminescence quantum yields and luminescence lifetimes of these chromium(III) complexes show only very small values. This hampers their application as NIR luminescence labels. This application, that cannot be tackled by conventional deoxygenating approaches, requires suitable strategies to protect the luminescence of the chromium(III) complexes from oxygen quenching. Typical approaches to reduce the oxygen sensitivity of long-lived luminophores include the encapsulation into an oxygen-shielding matrix or less commonly employed, by tuning the bulkiness of the ligands for oxygen-sensitive coordination compounds. An elegant approach to reduce the undesired luminescence quenching by triplet oxygen explored by us presents the incorporation of these chromium(III) complexes into amorphous, non-porous silica nanoparticles, that can be simply surface functionalized, e.g., with targeting ligands and/or other sensor molecules. This can enable the use of such chromium(III) complexes as reporters for bioanalytical assays and bioimaging without the need to introduce reactive groups into the ligands and can pave the road to lifetime tuning.
In this work, as first proof-of-concept experiments, a set of chromium (III) complexes constituting of different ligands and counter anions, were embedded into the core of silica nanoparticles. As an alternative synthesis strategy, selected complexes were incorporated into a silica shell formed around the core of self-made silica nanoparticles. Subsequently, the optical properties of the resulting luminescent silica nanoparticles were spectroscopically assessed by steady state and time-resolved luminescence spectroscopy. First results of time-resolved luminescence measurements of the Cr(ddpd)2(PF6)3 complex incorporated into 25nm large silica nanoparticles dispersed in aerated water in comparison to the decay kinetics obtained for this complex in acetonitrile in air showed an increase in lifetime from 46 µs to 1147 µs. This confirming our design concept of nanoscale NIR emissive Cr(III) reporters.
At present, the field of research on nanostructures is actively developing, which is due to their unique physico-chemical properties compared to bulk materials. Many research activities are focused on obtaining nanocomposites, which combine various types of nanostructures with different properties and function. For example, the development of magneto-luminescent nanocomposites makes it possible to use their luminescence for optical imaging, and their magnetic properties for magnetic targeted delivery and as agents of hyperthermia and magnetic resonance imaging.
My master studies as part of the project Goszadanie 2019-1080 at ITMO were focused on the investigation of nanocomposites, consisting of semiconductor quantum dots (QDs) as luminescent component and superparamagnetic iron oxide nanoparticles (SPIONs) as magnetic one, in solution and during their incubation with HeLa cells. The spectrally resolved analysis of the QD photoluminescence (PL) kinetics of the free QDs and the QDs incorporated in these nanocomposites undergoing energy transfer processes allowed for (1) understanding the reasons for the quenching of QD luminescence in cells, (2) evaluating the average distance between the QDs and, based on this, concluding the degree of QD aggregation in cells, and (3) drawing conclusions about the QD-quencher composites integrity in cells. Overall, the analysis of the PL kinetics confirmed that QDs and SPIONs remain bound in the obtained nanocomposites during incubation with cells.
To ensure the successful advancement of nanomaterials in biomedicine and the transition from their laboratory preparation and studies to their use in different applications and in industry, it is crucial to develop reliable measurement methods and reference materials candidates for the characterization of functional nanomaterials and assessing the quality of the obtained nanostructures. My recently started project at BAM, which is part of the EU metrology project MeTrINo, will be devoted to this topic. There we will focus on the development of methodologies for the synthesis and characterization of iron oxide nanoparticles, already used in biomedicine, and multi-element lanthanide-based nanoparticles with attractive upconversion luminescence, as reference materials with high monodispersity and reproducibility. Also, these nanoparticles will be functionalized with organic dyes for optical imaging and, probably, the study of the energy transfer phenomena.
Dredging sediment refers to materials removed from the bottom of a water body during dredging operations. Mainly the dreading mud contains clay, silt, sand, water, and alkalis. This work incorporated dredging mud into the calcium sulfoaluminate cement at replacement levels of 0%, 10%, 30%, and 50% by weight. Pastes were evaluated after 1d, 28d, and 90d- hydration through mechanical strengths and the reaction rate by isothermal conduction calorimetry. XRD and MIP characterized the reaction products. The findings showed that small replacements (10% and 30%) increased early strength with higher ettringite formation in the system at 1d of curing. However, the evolution of mechanical strength was lower than the reference (0% replacement) over time. The results showed that in low replacement dosages, the dredging mud act as a nucleation site for the hydration of calcium sulfoaluminate phases.
Zirconium chloro fluoride as catalyst for C-F bond activation and HF transfer of fluoroalkanes
(2023)
In this work, we successfully synthesized amorphous zirconium chloro fluoride (ZCF), which exhibits medium lewis acidity. In addition to investigating the local coordination sphere around the Zr atoms and the material properties, we were able to establish a catalytic behavior of ZCF in C-F bond activation reactions. We present a heterogeneous catalyst that performs dehydrofluorination of a fluoroalkane and consecutive hydrofluorination of an alkyne at room temperature.
Investigating the phononic properties is beneficial for predicting low thermal conductivity thermoelectric materials.1–3 Employing density functional theory4 takes many calculation steps and consumes a lot of computational resources.5,6 Using machine learning driven interatomic potentials (MLIP, e.g., Gaussian approximation potential,8 GAP) opens up a faster route to phonons7 but in most cases, the potentials are specifically tailored for a certain compound. In this work, we automate the generation of such MLIPs in a Python code-based workflow, based on the automation tools atomate29 and pymatgen10 which combines the automatic DFT computations with the automated fitting of GAPs. Automation enables easier testing, benchmarking and validation.11 We aim to provide the workflow-generated potentials for storage in databases.
In our current view, reference datasets in the MSE domain represent specific material properties, e.g., structural, mechanical, … characteristics. A reference dataset must fulfill high-quality standards, not only in precision of measurement but also in a comprehensive documentation of material, processing, and testing history (metadata). This Infrastructure Use Case (IUC) aims to develop a framework for generating reference material datasets using creep data of a single crystal Ni-based superalloy as a best practice example. In a community-driven process, we aim to encourage the discussion and establish a framework for the creation and distribution of reference material datasets. In this poster presentation, we highlight our current vision and activities and intend to stimulate the discussion about the topic reference datasets and future collaborations and work.
Understanding the fundamentals of bioreceptivity enables the developement of functionalized materials. Concrete as the most used building material worldwide is of special interest as microbially greened panels may represent an alternative to classic façade greening with plants. This project includes extensive outdoor experiments, in which eight differently structured concrete panels are weathered under different conditions, aiming to grow a stable biofilm of photosynthetic eukaryotic organisms. Documentation and data analysis of this experiment will be demonstrated using an example of one of the surfaces.
Understanding the chemistry and nature of individual chemical bonds is essential for materials design. Bonding analysis via the LOBSTER software package has provided valuable insights into the properties of materials for thermoelectric and catalysis applications. Thus, the data generated from
bonding analysis becomes an invaluable asset that could be utilized as features in large-scale data analysis and machine learning of material properties. However, no systematic studies exist that conducted high-throughput materials simulations to curate and validate bonding data obtained from LOBSTER. Here we present an approach to constructing such a large database consisting of quantum-chemical bonding information.
Argyrodite-type materials have lately sparked a lot of research interest due to their thermoelectric properties.One promising candidate is canfieldite (Ag8SnS6), which has a Pna21 orthorhombic crystal structure at room temperature (RT). Recently, a new low-temperature (LT) phase transition of canfieldite at 120K has been found. Here, we investigate structural, vibrational and thermodynamic properties of Ag8SnS6 at room- and low-temperature employing density functional theory (DFT) and lattice dynamics computations. Thermal properties calculations were based on the quasi-harmonic approximation (QHA) as implemented in phonopy. We achieve good agreement with experiments. Thermal properties such as the constant-pressure heat capacity (Cp) and thermal conductivity are very close to experimental measurements. Furthermore, we compared RT and LT Ag8SnS6 Grüneisen parameters with argyrodites analogues, Ag8XS6 (X = Sn, Si, Ge), to arrive at an improved
In dentistry it is of great interest to achieve good sealing interzones between tooth tissue and restoration materials to avoid, e. g. secondary caries. μXRF and CμXRF are suitable to investigate the elemental composition at these interzones in respect to diffusion of elements. Synchrotron X-ray refraction radiography (SXRR) and μCT measurements deliver highly resolved structural information and make structural changes such as micro cracks within the filling and the tooth tissue visible. The presented measurements are part of the DFG funded project IXdent (Integrative X-ray techniques for chemical and structural characterizations of dental interzones.)
The depth-resolved CμXRF measurements are affected by absorption effects, making a quantitative investigation of the interzone in depth difficult. Full 3D quantification of heterogenous samples requires a complete model including dark matrix and density for each voxel. The combination of different techniques paves the way for a quantitative analysis of dental interzones.
In the maritime context of offshore operation, corrosion, in combination with the materials used, poses a particular challenge to ensure safe operation over long indefinite periods and to minimise susceptibility to failure. Until today, only a few corrosion protection systems have proven themselves for the interaction of efficiency, installation, and maintenance in the offshore sector. In addition, available corrosion test methods sometimes have major deficits about conclusions of the durability. Therefore, there is more research and development needed.
The flagship project H2Mare of the Federal Ministry of Education and Research aims to enable the production of green hydrogen and PtX products at high seas. Research is being driven forward by the partners in four individual projects, where BAM is involved in two.
In PtX-Wind, major kinds of corrosion attacks at offshore constructions are characterized and investigated, and suitable corrosion protection measures determined. In TransferWind, attention focusses on transferring scientific results into standardization.
This poster at the H2Mare Conference 2023 presents an overview of the investigation methods and contribution of the department “Corrosion and Corrosion Protection”.
LTCCs (Low-temperature co-fired ceramics) consist of three-dimensionally distributed, hermetically bonded ceramic and metallic components with structure sizes within [10; 100] µm. A non-destructive imaging technique is needed that provides 3D, sharp, high-contrast resolution of these structures, as well as porosity and defect analysis, which is made difficult by the very different X-ray absorption coefficients of the individual components of the microstructure. A HDR method is being developed that allows a combination of different tomograms, each with X-ray energies adapted to individual materials.
Components in aircrafts are usually replaced when critical defects are present.
An alternative approach is repairing using gas dynamic cold spraying: metal particles are shot at a surface at supersonic speeds to selectively rebuild damaged material. Compared to other material-deposition techniques, its advantage is the small thermal impact on the component, preserving its mechanical properties.
Component-repair can save considerable amounts of energy and resources. However, its industrial application at large scale needs reproducible, good repair-material properties to guarantee a safe component life. The aim of this project is the development of safe, automatized repair-procedures considering the mechanical fatigue properties of the repair.
Industrial and agricultural waste streams (waste waters, sludges, tailings etc.), which contain high concentrations of NH4+, PO43- and transition metals, are environmentally harmful due to their toxic pollutants. At the same time, phosphorus and selective transition metals such as Cobalt could be potentially depleted as a critical raw material due to the high demand and rapidly declining natural ore deposits. Therefore, due to simultaneous scarcity and abundance, the phosphorus and 3d metal recovery from agricultural, industrial, mining, or urban wastewaters have been an important factor in sustaining our global consumption and preservation of the natural environment. Typically, separate pathways have been considered to extract hazardous substances such as transition metals or phosphate, independently from each other. Here, we investigate the crystallization of transition metal phosphate (TMP) compounds (NH4MPO4∙6H2O, M3(PO4)2∙8H2O with M = Ni2+, Co2+, NixCo1-x2+ M-struvite and M-phosphate octahydrate) out of aqueous solutions, which allow for P, ammonia and metal co-precipitation. The precipitation of these compounds from industrial and agricultural waste waters has high potential as a P- and 3d metal recovery route. For this purpose, a detailed understanding of the crystallization process beginning from combination of solved ions and ending in a final crystalline product is required. Through adjusting the reaction conditions, the stability, crystallite size and morphology of the as-obtained TMPs could be controlled. Detailed investigations of the precipitation process in time using ex- and in-situ techniques provided new insights into their non-classical crystallization mechanism/crystal engineering of these materials. These TMPs involve transitional colloidal nanophases during the crystallization process. Over time, their complex amorphous framework changes significantly resulting simultaneously in an agglomeration and densification of the compound. After extended reaction times these colloidal nanophases condensed to a final crystal. However, the reaction kinetics of the formation of a final crystalline product and the lifetime of these intermediate phases vary significantly depending on the metal cation involved in the precipitation process. Ni-struvite is stable in a wide reactant concentration range and at different metal/phosphorus (M/P)-ratios, whereas Co tends to form Co-struvite and/or Co-phosphate octahydrate depending on the (M/P)-ratio. The mixed NixCo1-x system shows a significantly different crystallization behavior and reaction kinetics of the precipitation compared to the pure endmembers. The observed various degree of stability could be linked to the octahedral metal coordination environment in these compounds. The achieved level of control over the precipitates, is highly desirable for 3d- and P-recovery methods. Under this paradigm, the crystals can be potentially upcycled as precursor materials for (electro)catalytical applications.
In the present paper we show an approach of measuring large numbers of nanoparticles in a single scan TKD. TiO2 anatase nanoparticles (NP) of bipyramidal shape were deposited on standard carbon grid used for TEM. The procedure used promoted formation of NP ‘monolayer’ islands with uniform distribution of NPs on the carbon surface which allowed mapping of large number of nanoparticles in the single island.
Collection of whole map covering ~2800 nanoparticles took nearly 20 minutes. Inverse pole figure color coded map indicates that the NPs are either lying on a {101} facet (within 10° range around perfect {101} parallel to the carbon surface orientation) on the carbon film or are lying on a {100} facet (within 10° range around the perfect {100} parallel to the carbon surface orientation). Very unlikely was the NP orientation standing on a {001} face. The NPs size distribution described as equivalent circle diameter (ECD) has been also evaluated and the mean NP ECD was 59 nm with standard deviation of 15 nm, i.e. in good agreement with electron microscopy or AFM results.
This study shows high potential of the technique for crystalline NPs analysis with respect to geometrical orientation of the particles on the substrate. With known orientation, the 3D dimensional characterisation of such non-spherical NPs becomes possible from 2D projection electron micrographs. Moreover, the NP size distribution can be easily extracted. Superior accuracies down to 1-2 nm are achievable. The approach is applicable also on thin lamellae extracted from particulate (or mesoporous) layers.
Electron probe microanalysis (EPMA)is a non-destructive technique which assumes a sample of homogenous (bulk) chemical composition and can, therefore, not be used for thin film samples. However, in combination with one of the possible thin film software packages, STRATAGEM, the thickness as well as the composition of such films on a substrate can be determined.
This has been demonstrated for FeNi on Si and SiGe on Al2O3 film systems. For both systems five samples with different elemental composition and a reference were produced and characterised by the Korean research institute KRISS using inductively coupled plasma mass spectrometry (ICP-MS), Rutherford backscattering (RBS), and transmission electron microscopy (TEM).
In 2021, a new and open source thin film evaluation programme called BADGERFILM has been released. It can also be used to determine thin film composition and thickness from intensity ratios of the unknown sample and standards (k-ratios).
In this contribution, we re-evaluated the data acquired for the FeNi and SiGe systems using the BADGERFILM software package and compared the resulting composition and thickness with the results of the established STRATAGEM software and other reference methods. With the current evaluation, the BADGERFILM software shows good agreement with the composition and thickness calculated by STRATAGEM and provided by the KRISS.
These results between two well-known layered material systems analysed with available conventional EMPA approaches (STRATAGEM and direct thickness measurement by TEM) and a new one (BADGERFILM) proves that reliable non-destructive thin film analysis is possible. In this way, we validate the performance of the new software, which is not at all self-explanatory for such
complex quantification algorithms lying behind the final quantified results.
Nowadays, in every terrestrial and aquatic ecosystem, even in the remotest areas, small residues of plastics, the so called microplastic (MP) can be found. MPs are particles with a size of 1-1000 µm (ISO/TR 21960:2020), mainly containing synthetic polymers like polyethylene (PE), polypropylene (PP), polystyrene (PS) or polyethylene terephthalate (PET). Even styrene-butadiene rubber (SBR) as an indication for tire wear is included due to similar particle formation. To understand the MPs consequences to the environment, it is of high priority to capture its extent of contamination. It is surprising that in the analysis of polymer masses in environmental samples, PE, PS and SBR are often detected, but only small amounts of PP, although this is the second most commonly produced standard plastic and many MP particles originate from carelessly disposed packaging materials.
This presentation provides hypotheses about the reasons of rare PP identification and mass quantification in environmental samples. Different investigations of pristine PP and representative environmental samples, including the pre-treatment by Accelerated Solvent Extraction (ASE) or with density separation followed by the thermal extraction / desorption gas chromatography-mass spectrometry (TED-GC/MS) are presented. The results are discussed according to the material properties and a possible degradation mechanism under different weathering conditions which indicate less stability under relevant storage conditions.
Small-angle X-ray scattering (SAXS) can be used for structural de- termination of biological macromolecules and polymers in their na- tive states. To improve the reliability of such experiments, the re- duction of radiation damage occurring from exposure to X-rays is needed.One method, is the use of scavenger molecules that protect macromolecules against radicals produced by radiation exposure.In this study we investigate the feasibility to apply the compatible solute, osmolyte and radiation protector Ectoine (THP(B)) as a scavenger throughout SAXS measurements of single-stranded DNA-binding protein Gene-V Protein (G5P/GVP). Therefore we monitor the radiation induced changes of G5P during bio-SAXS. The resulting microscopic energy-damage relation was determined by particle scattering simu- lations with TOPAS/Geant4. The results are interpreted in terms of radical scavenging as well as post-irradiation effects, related to preferential-exclusion from the protein surface. Thus, Ectoine provides an non-disturbing way to improve structure-determination of proteins via bio-SAXS in future studies.
Ionic Liquid Crystals (ILCs) are emerging class of materials that combine the properties of liquid crystals with the ionic conduction similar to ionic liquids. It’s known that liquid crystals exhibit intriguing properties when confined and are of importance from both fundamental and technological perspective. Here, we study the molecular dynamics and electrical conductivity of a homologous series of Dopamine (DOPA) based ILCs, ILCn (n = 12,14,16) confined in self ordered nanoporous alumina oxide membrane of 180 nm pore size using Broadband Dielectric Spectroscopy (BDS). We aim to understand how the alkyl chain length and confinement influence the dynamics in this system.
In the bulk, for all ILCs, we observe two relaxation modes in the crystalline phase, the and α1 relaxation respectively, and one relaxation mode in the columnar phase, the α2 relaxation, but for ILC16, where two relaxation modes (α2 and α3) are detected in the columnar phase.
For the confined case, all relaxation processes slowdown compared to the bulk. For ILC16, the α1 relaxation is completely suppressed. For all ILCs, the absolute values of DC conductivity are reduced by some three orders of magnitude. We discuss in detail the possible molecular origin of the relaxation processes and the charge transport in this system.
A deep insight into the chemistry and nature of individual chemical bonds is essential for understanding materials. Bonding analysis is expected to provide important features for large-scale data analysis and machine learning of material properties. Such information on chemical bonds can be calculated using the LOBSTER (www.cohp.de) software package, which post-processes data from modern density functional theory computations by projecting plane wave-based wave functions onto a local atomic orbital basis. We have performed bonding analysis on 1520 compounds (insulators and semiconductors) using a fully automated workflow combining the VASP and LOBSTER software packages. We then automatically evaluated the data with LobsterPy (https://github.com/jageo/lobsterpy) and provide results as a database. The projected densities of states and bonding indicators are benchmarked on VASP projections and available heuristics, respectively. Lastly, we illustrate the predictive power of bonding descriptors by constructing a machine-learning model for phononic properties, which shows an increase in prediction accuracies by 27 % (mean absolute errors) compared to a benchmark model differing only by not relying on any quantum-chemical bonding features.
Dose enhancement by gold nanoparticles (AuNP) increases the biological effectiveness of radiation damage in biomolecules and tissue.
To apply them effectively during cancer therapy their influence on the locally delivered dose has to be determined. Hereby, the AuNP locations strongly influence the energy deposit in the nucleus, mitochondria, membrane and the cytosol of the targeted cells. In this work, two newly developed continuous and discrete-geometric models for simulations of AuNP in cells are presented. We apply the presented models in Monte-Carlo particle scattering simulations to characterize the energy deposit in cell organelles by radioactive 198AuNP. They emit beta and gamma rays and are therefore considered for applications
with solid tumors. Differences in local dose enhancement between randomly distributed and nucleus targeted nanoparticles are compared.
Hereby nucleus targeted nanoparticels showed a strong local dose enhancement in the radio sensitive nucleus.
Owing to a growing shortage of fluorspar, a raw material used for producing fluorinated base chemicals, fluorspar has been named among the 30 critical raw materials in the EU. 1 However, the sustainable transfer of fluorine atoms from one molecule to another using heterogeneous catalysts has not yet been reported. Herein, we present the heterogeneous catalyst zirconium chloro fluoride (ZCF) that performs dehydrofluorination of a fluoroalkane and consecutive hydrofluorination of an alkyne at room temperature.
ZrF4 species have shown to exhibit hard Lewis acidity in homogeneous systems. In order to study solid state Lewis acidic ZrF4 a sol-gel synthesis was adapted following previous approaches for AlF3 and a necessary post fluorination is being optimised to obtain a Lewis acidic heterogeneous catalyst for C-F bond activation. The influence of different Zr precursors was also studied while the local coordination sphere of a active species was found to be similar to β-ZrF4 using EXAFS of the Zr K-edge.
Previous work in the Dunne Group targeted dispersibility of metal oxide nanoparticles, which had been synthesised via an aqueous sol-gel route. Dispersibility was attained by solvothermal surface modification of the particles with trifluoro acetic acid.
Part of the studies were tin oxide particles, which is known for its predominant rutile phase.
Despite dispersibility in acetone of the particles unexpected peak splitting of the first (110) reflection was observed.
Intensive long-term reaction studies on the tin oxide particles exhibited a time dependent extend of the peak splitting observed in XRD character-isation. Extended characterisation using solid-state multinuclear MAS-NMR spectroscopy indicate size dependent structure change due to partial fluorination of the particles during the solvothermal treatment.
Previous work in the Dunne Group targeted dispersibility of metal oxide nanoparticles, which had been synthesised via an aqueous sol-gel route. Dispersibility was attained by solvothermal surface modification of the particles with trifluoro acetic acid (TFA). Part of the studies were tin oxide particles, which is known for its predominant rutile phase. Besides the dispersibility in acetone of the particles, an unexpected peak splitting of the (110) reflection was observed, which could be an unknown phase of SnO2 . For crystal growth long-term reaction studies on the tin oxide particles were performed. Interestingly these studies exhibited a time dependent extend of the peak splitting observed in XRD characterisation. Further extended analysis using multinuclear solid-state MAS-NMR spectroscopy indicate a size dependent structure change due to partial fluorination of the particles during the solvothermal treatment.
The investigations into the complicated effects of film thickness on bulk properties of thin polymer films has yielded conflicting results. The reduction in molecular mobility, and with it an increase in the glass transition temperature, for thin films of poly (bisphenol A carbonate) (PBAC) was assigned to the formation of an adsorbed layer. The adsorbed layer was obtained by washing away the loosely bounded chains using a good solvent. Next, using atomic force microscopy (AFM), the thickness of each sample was measured after annealing for various times at three different annealing temperatures. The growth of this adsorbed layer was shown to deviate from the previously reported 2-step mechanism seen for other polymers. For PBAC, after very long annealing times at high temperatures the thin films were dewetted, where segments of the adsorbed layer were removed from the substrate.
The aim of the task area Materials Data Infrastructure (TA-MDI) of the consortium Materials Science and Engineering (MatWerk) of National Research Data Infrastructure (NFDI) is to shape scientific datasets obtained through the Participant Projects (PPs) from a data management perspective conforming to the FAIR principles, making use of the FAIR Digital Object (FAIR DO) concept, including structured metadata and storage solutions. As an example, they apply PP18 (BAM) as a use case to demonstrate the proposed technical workflow.
Reference datasets in the MSE domain represent specific material properties, e.g., structural, mechanical, … characteristics. A reference dataset must fulfill high-quality standards, not only in precision of measurement but also in a comprehensive documentation of material, processing, and testing history (metadata). This Infrastructure Use Case (IUC) of the consortium Materials Science and Engineering (MatWerk) of National Research Data Infrastructure (NFDI) aims to develop, together with BAM and other Participant Projects (PP), a framework for generating reference material datasets using creep data of a single crystal Ni-based superalloy as a best practice example. In a community-driven process, we aim to encourage the discussion and establish a framework for identifying reference material datasets. In this poster presentation, we highlight our current vision and activities and intend to stimulate the discussion about the topic reference datasets and future collaborations and work.
Vibrational properties play a key role in determining the stability and thermal conductivity behaviour of materials. The quasi- harmonic approximation gives insight into the phononic properties of a compound, but in the established way, i.e. density functional theory based methods, it takes many calculation steps and consumes a lot of resources to arrive at the desired results. Machine learning (ML) trained interatomic potentials (e.g. Gaussian approximation potential, GAP) pose an alternative to the traditional computation way of phonons. We develop a Python code based workflow which combines automation tools like atomate2 with ML to ease providing interactomic potentials for (quantum chemical) computations and databases.
The movement of the macroscopic magnetic moment in ferromagnetic systems can be described by the Landau-Lifshitz (LL) or Landau-Lifshitz-Gilbert (LLG) equation. These equations are strictly valid only at absolute zero temperature. To include temperature effects a stochastic version of the LL or LLG equation for a spin density of one per unit cell can be used instead. To apply the stochastic LL to micromagnetic simulations, where the spin density per unit cell is generally higher, a conversion regarding simulation cell size and temperature has to be established. Based on energetic considerations, a conversion for ferromagnetic bulk and thin film systems is proposed. The conversion is tested in micromagnetic simulations which are performed with the Object Oriented Micromagnetic Framework (OOMMF). The Curie temperatures of bulk Nickel, Cobalt and Iron systems as well as Nickel thin-film systems with thicknesses between 6.3 mono layer (ML) and 31ML are determined from micromagnetic simulations. The results show a good agreement with experimentally determined Curie temperatures of bulk and thin film systems when temperature scaling is performed according to the presented model.
Dose enhancement by gold nanoparticles (AuNP) increases the biological effectiveness of radiation damage in biomolecules and tissue. To apply them effectively during cancer therapy their influence on the locally delivered dose has to be determined.[1] Hereby, the AuNP locations strongly influence the energy deposit in the nucleus, mitochondria, membrane and the cytosol of the targeted cells. To estimate these effects, particle scattering simulations are applied. In general, different approaches for modeling the AuNP and their distribution within the cell are possible. In this work, two newly developed continuous and discrete-geometric models for simulations of AuNP in cells are presented. [2] These models are applicable to simulations of internal emitters and external radiation sources. Most of the current studies on AuNP focus on external beam therapy. In contrast, we apply the presented models in Monte-Carlo particle scattering simulations to characterize the energy deposit in cell organelles by radioactive 198AuNP. They emit beta and gamma rays and are therefore considered for applications with solid tumors. Differences in local dose enhancement between randomly distributed and nucleus targeted nanoparticles are compared. Hereby nucleus targeted nanoparticels showed a strong local dose enhancement in the radio sensitive nucleus. These results are the foundation for ongoing experimental work which aims to obtain a mechanistic understanding of cell death induced by radioactive 198Au.
As one of nature's largest carbon sources with an annual production of around 20 billion tonnes, lignin is the third most abundant biopolymer on the planet. It becomes available as technical lignin, which is produced as a by-product in the pulp and paper industry and in smaller quantities in second generation biofuel refineries. Current estimates suggest that less than 10% of all technical lignin is reused. The high polydispersity, complex heterogeneous structure and uncertain reactivity are the major limiting factors for further processing. The most common applications for various technical lignins without extensive modifications are for example: Surface active substances, additives in bitumen, cement and animal feed. One way to make lignin usable is to break the structure into oligomer units and thus reduce the polydispersity and average molar mass. In addition, it is advantageous to introduce new functionalities such as hydroxyl or carbonyl groups when splitting the high-molecular-weight (HMW) fractions, or to convert existing functionalities. In this study, a mechanochemical method is presented that can degrade and modify technical kraft lignin by means of sodium percarbonate (SPC).
Lithium-ion batteries (LIBs) are one technology to overcome the challenges of climate and energy crisis. They are widely used in electric vehicles, consumer electronics, or as storage for renewable energy sources. However, despite innovations in batteries' components like cathode and anode materials, separators, and electrolytes, the aging mechanism related to metallic aluminum current collector degradation causes a significant drop in their performance and prevents the durable use of LIBs.[1] Glow-discharge optical emission spectroscopy (GD-OES) is a powerful method for depth-profiling of batteries' electrode materials. This work investigates aging-induced aluminum deposition on commercial lithium cobalt oxide (LCO) batteries' cathodes. The results illustrate the depth-resolved elemental distribution from the cathode surface to the current collector. An accumulation of aluminum is found on the cathode surface by GD-OES, consistent with results from energy-dispersive X-ray spectroscopy (EDX) combined with focused ion beam (FIB) cutting. In comparison to FIB-EDX, GD-OES allows a fast and manageable depth-profiling. Results from different positions on an aged cathode indicate an inhomogeneous aluminum film growth on the surface. The conclusions from these experiments can lead to a better understanding of the degradation of the aluminum current collector, thus leading to higher lifetimes of LIBs.
Al-Si alloys produced by Laser Powder Bed Fusion (PBFLB) allow the fabrication of lightweight free-shape components. Due to the extremely heterogeneous cooling and heating, PBF-LB induces high magnitude residual stress (RS) and a fine Si microstructure. As the RS can be deleterious to the fatigue resistance of engineering components, great efforts are focused on understanding their evolution in as-built state (AB) and after post-process heat treatments (HT). RS in single edge notch bending (SENB) subjected to different HT are investigated (HT1: 1h at 265°C and HT2: 2h at 300°C).
Nanoparticles (NPs) have become important materials for a variety of chemical technologies, including catalysis. One of the main challenges is the reduction of green house gases, such as CO2. One opportunity besides the capturing is the conversion to synthesis gas via the reverse water-gas shift reaction.
A facile and efficient method is described for the solvothermal synthesis of size-tunable, stable, and uniform NiCu core-shell NPs. The diameter of the NPs can be tuned in a range from 6 nm to 30 nm and the Ni:Cu ratio from 30:1 to 1:1. The NPs are structurally characterized with combination of transmission electron microscopy, anomalous small-angle X-ray scattering, X-ray photoelectron spectroscopy, and X-ray absorption fine structure. Using these analytical methods, a core-shell-shell structure their chemical composition is elucidated. A depletion from the core to the shell is observed, with the core consisting of NiCu alloy, surrounded by an inner Ni-rich shell and an outer NiO shell. The SiO2-supported NiCu core-shell NPs show pronounced selectivity of >99% for CO in the catalytic reduction of CO2 to CO using hydrogen as reactant (reverse water–gas shift reaction).
In the pursuit of discovering materials with desirable properties, extending the available material libraries is crucial. High-throughput simulations have become an integral part in designing new materials in the past decades. However, there is no straightforward way of distinguishing synthesizable materials from all the proposed candidates. This project focuses on employing AI-driven methods to estimate synthesizability of materials.
Up to now, material scientists and engineers have relied on domain knowledge as well as empirical heuristics to guess the stability and synthesizability of molecules and crystals. The famous Pauling rules of crystal stability are an example of such heuristics. However, after the accelerating material discovery in all the years since Pauling, these rules now fail to account for the stability of most known crystals. A new predictive set of heuristics for crystal stability/synthesizability is unlikely to be uncovered by human perception, given the magnitude and dimensionality of crystallographic data. Hence, a data-driven approach should be proposed to find a predictive model or set of heuristics which differentiate synthesizable crystal structures from the rest. The main challenge of this research problem is the lack of a negative set for classification. Here, there are two classes of data: the positive class which contains synthesizable materials and the negative class which contains materials which are not synthesizable. While the data from the positive class is simply the data of crystals which have been experimentally synthesized, we do not have access to data points which are certainly unsynthesizable. Strictly speaking, if an attempt of synthesizing a crystal fails, it does not necessarily follow that the crystal is not synthesizable. Also, there is no database available which contains the intended crystal structures of unsuccessful synthesis attempts.
This project proposes a semi-supervised learning scheme to predict crystal synthesizability. The ML model is trained on experimental and theoretical crystal data. The initial featurization focuses on local environments which is inspired by the Pauling Rules. The experimental data points are downloaded through the Pymatgen API from the Materials Project database which contains relaxed structures recorded in Inorganic Crystal Structure Database – ICSD. The theoretical data is queried from select databases accessible through the Optimade project’s API.
Vorstellung der Themen der Nachwuchsgruppe "Materialcharakterisierung und -informatik für die Nachhaltigkeit im Bauwesen" von Prof. Sabine Kruschwitz (TU Berlin und BAM)
Within NFDI-MatWerk (“National Research Data Infrastructure for Material Sciences”/ “Nationale Forschungsdateninfrastruktur für Materialwissenschaften und Werkstofftechnik“), the Task Area Materials Data Infrastructure (TA-MDI) will provide tools and services to easily store, share, search, and analyze data and metadata. Such a digital materials environment will ensure data integrity, provenance, and authorship. The MatWerk consortium aims to develop specific solutions jointly with Participant Projects (PPs), which are scientific groups or institutes covering different domains, from theory and simulations to experiments. The Data Exploitation Methods group of the Karlsruhe Institute of Technology-Steinbuch Centre of Computing, as part of TA-MDI, is developing specific solutions in close collaboration with three PPs.
PP07, together with the University of Stuttgart, aims at the image-based prediction of the material properties of stochastic microstructures using large-scale supercomputers. PP13, in cooperation with the University of Saarland, focuses on tomographic methods at various scales in materials research. PP18, together with the Federal Institute for Materials Research and Testing (“Bundesanstalt für Materialforschung und -prüfung”), aspires to define the criteria for materials reference datasets and usage analytics.
The requirements and goals are comparable for each PP: their research outputs, which are scientific datasets, should conform to the FAIR (Findable, Accessible, Interoperable, Reusable) principles. We aim to shape them from a data management perspective making use of the FAIR Digital Object concept, including structured metadata and storage solutions. The results will be a blueprint which will act as a reference for future datasets. Even though the collaboration is in an early stage, the initial steps already show the added value of this approach.
This research has been supported by the Federal Ministry of Education and Research
(BMBF) – funding code M532701 / the Deutsche Forschungsgemeinschaft (DFG, German
Research Foundation) - project number NFDI 38/1, project no. 460247524.
As part of a joint project involving the Fraunhofer Institute for Silicate Research (ISC), the Friedrich Schiller University of Jena, the Clausthal University of Technology and the Federal Institute for Materials Research and Testing (BAM), digital tools are to be created for the development of new types of glass materials. Current processes for the production of glasses with improved properties are usually very cost- and energy-intensive due to the low degree of automation and are subject to long development cycles. The use of robotic synthesis processes in combination with self-learning machines is intended to overcome these problems in the long term. The development of new types of glass can then not only be accelerated considerably, but also be achieved with much less effort.
In this talk, data generation via a robotic high-throughput glass melting system is presented, which should be the experimental basis for the ontology developed within the project GlasDigital.
Mechanochemistry offers a unique opportunity to modify or synthesize new crystal forms. Although the method is very promising, little is known about the mechanochemical means to control the synthesis of a solid form. Using an polymorphic organic cocrystal system, we show here that mechanochemistry can be used to obtain a polymorph transformation under the apparently conventional (thermal) transition point.