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The presentation gives an overview of BAM's activities on processing influences and application properties of MPEAs in the form of joined and machined high and medium entropy alloys (CoCrFeMnNi and CoCrNi). In the case of welding, the focus is on defect-free welded joints with sufficient mechanical properties. In the case of machining, the focus is on the possible influence on the surface quality of the materials through adequate milling parameters. In addition, the hydrogen absorption and diffusion properties as well as the electrochemical corrosion behavior are fundamentally examined.
This contributions shows the first results of the ongoing interlaboratory comparisons under VAMAS/TWA 34 Nanoparticle populations related on the determination of pasrticle size distribution and relative concentration of nanoparticles and an example of an ILC running under VAMAS/TWA 41 Graphene and Related 2D Materials on the determination of the lateral diemsnions of graphene oxide flakes by Scanning Electron Microscopy. The link to related standardisation projects at ISO/TC Nanotechnologies are explained.
Advanced materials, such as nanomaterials, 2D materials, or thin films, play a crucial role in driving economic development and addressing major challenges in the coming years. These challenges include mitigating the impact of climate change, advancing lightweight engineering, enhancing catalysis, and improving medical applications.
To comprehend the performance of these materials and ensure their acceptance across various sectors as safe and sustainable for both humans and the environment, the availability of reference procedures, materials, and data is essential. One versatile tool for establishing such references and evaluating the proficiency of individual laboratories and their competencies is through (international) interlaboratory comparisons (ILC). Notably, initiatives like the Versailles Project on Advanced Materials and Standards (VAMAS) provide a platform for conducting ILCs.
This webinar will showcase various examples of interlaboratory comparisons, illustrating their impact on the development of reference products.
Bonds and local atomic environments are crucial descriptors of material properties. They have been used to create design rules and heuristics and as features in machine learning of materials properties. Implementations and algorithms (e.g., ChemEnv and LobsterEnv) for identifying local atomic environments based on geometrical characteristics and quantum-chemical bonding analysis are nowadays available. Fully automatic workflows and analysis tools have been developed to use quantum-chemical bonding analysis on a large scale. The lecture will demonstrate how our tools, that assess local atomic environments and perform automatic bonding analysis, help to develop new machine learning models and a new intuitive understanding of materials.[5,6] Furthermore, the general trend toward automation in density functional-based materials science and some of our recent contributions will be discussed.
Bonds and local atomic environments are crucial descriptors of material properties. They have been used to create design rules and heuristics and as features in machine learning of materials properties. Implementations and algorithms (e.g., ChemEnv and LobsterEnv) for identifying local atomic environments based on geometrical characteristics and quantum-chemical bonding analysis are nowadays available. Fully automatic workflows and analysis tools have been developed to use quantum-chemical bonding analysis on a large scale. The lecture will demonstrate how our tools, that assess local atomic environments and perform automatic bonding analysis, help to develop new machine learning models and a new intuitive understanding of materials. Furthermore, the general trend toward automation in density functional-based materials science and some of our recent contributions will be discussed.
In recent years, many protocols in computational materials science have been automated and made available within software packages (primarily Python-based). This ranges from the automation of simple heuristics (oxidation states, coordination environments) to the automation of protocols, including multiple DFT and post-processing tools such as (an)harmonic phonon computations or bonding analysis. Such developments also shorten the time frames of projects after such developments have been made available and open new possibilities. For example, we can now easily make data-driven tests of well-known rules and heuristics or develop quantum chemistry-based materials descriptors for machine learning approaches. These tests and descriptors can have applications related to magnetic ground state predictions of materials relevant for spintronic applications or for predicting thermal properties relevant for thermal management in electronics. Combining high-throughput ab initio computations with fitting, fine-tuning machine learning models and predictions of such models within complex workflows is also possible and promises further acceleration in the field. In this talk, I will show our latest efforts to link automation with data-driven chemistry and materials science.
The variability and heterogeneity in their structural composition is significant for nearly all synthetic and natural polymers. Beside molar mass also functionality type distribution, copolymer composition distribution and architectural features are responsible for changing the material properties.
A wide range of analytical techniques are available to get insight into these parameters. However, in most cases it is essential to combine different sophisticated techniques to get closer to actual structures and to avoid statistical averages.
Different liquid chromatographic separation modes and their coupling in a two-dimensional way (SEC, LCCC, HILIC, 2D-LC) in combination with suitable detection techniques (e.g. UV, RI, LS, IR, MALDI/ESI-MS) as well as techniques like BET, DCS, SEM/TEM were applied to make structural features visible.
A few aspects are discussed for structural different polylactides from various synthesis routes and their behavior in LC-MS.
The presentation includes aspects of material design and characterization with a focus on lignin. Examples are the structural elucidation of lignosulfonates by means of two-dimensional chromatography, the mechanochemical degradation and functionalization of Kraft-Lignin with accompanying analytics. Future projects involving the incorporation of lignin into polymers will be presented.