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Testing and analysis of materials and components ‒ an expedition from lab to field in a digitally transforming world
No full textIn an era where digital transformation is reshaping every facet of our lives, the field of material science and engineering is no exception. This presentation delves into the exciting journey of material and component testing, tracing its path from the confines of the laboratory to the vast expanse of real-world applications, with a particular focus on enhancing safety and reliability. We will explore how modern techniques are pushing the boundaries of conventional material testing, revealing new dimensions of material behavior and performance that are crucial for ensuring safety. The integration of in situ quality control within production processes is revolutionizing manufacturing, ensuring unparalleled precision and reliability, which are essential for maintaining high safety standards.
As we venture into the realm of Structural Health Monitoring (SHM), discover how cutting-edge technologies are being deployed in field applications, from infrastructure to renewable energy sectors, to monitor and ensure the safety and integrity of critical systems. The presentation will also offer a glimpse into the future, where centralized systems for research data management and innovative digital initiatives promise to transform the landscape of material testing and analysis, further bolstering safety measures. Join us to uncover how these advancements are not only enhancing safety and reliability but also paving the way for a digitally interconnected world
Nano- and Advanced Materials Synthesis in a Self-Driving Lab (SDL)
No full textNano- and advanced materials have been recognized as a key enabling technology of the 21st century, due to their high potential of driving innovations in new clean energy technologies, sustainable manufacturing by substitution of critical raw materials and replacement of hazardous substances, breakthroughs in energy conversion and storage, improvement of the environmental performance of products and processes, and facilitation of circularity. Consequently, improving tools that enhance the development and optimization cycle of nano- and advanced materials is crucial.
In this contribution, we present our Self-Driving Lab (SDL) for Nano and Advanced Materials [1], that integrates robotics for batched autonomous synthesis – from molecular precursors to fully purified nanomaterials – with automated characterization and data analysis, for a complete and reliable nanomaterial synthesis workflow. By fully automating these three process steps for seven different materials from five representative, completely different classes of nano- and advanced materials (metal, metal oxide, silica, metal organic framework, and core–shell particles) that follow different reaction mechanisms, we demonstrate the great versatility and flexibility of the platform. The system also exhibits high modularity and adaptability in terms of reaction scales and incorporates in-line characterization measurement of hydrodynamic diameter, zeta potential, and optical properties (absorbance, fluorescence) of the nanomaterials. We discuss the excellent reproducibility of the various materials synthesized on the platform in terms of particle size and size distribution, and the adaptability and modularity that allows access to a diverse set of nanomaterial classes. These features underscore the SDL’s potential as a transformative tool for advancing and accelerating the development of nano- and advanced materials, offering solutions for a sustainable and environmentally responsible future
Cost-Effective Method for Full-Length Sequencing of Monoclonal Antibodies from Hybridoma Cells
No full textBackground: Monoclonal antibodies play an important role in therapeutic and analytical applications. For recombinant expression, the coding sequences of the variable regions of the heavy and light chains are required. In addition, cloning antibody sequences, including constant regions, reduces the impact of hybridoma cell loss and ensures preservation of the naturally occurring full antibody sequence. Method: We combined amplification of IgG antibody variable regions from hybridoma mRNA with an advanced method for fulllength cloning of monoclonal antibodies in a simple two-step workflow. Following Sanger sequencing and evaluation of consensus sequences, the best matching variable, diversity,
and joining (V-(D-)J) gene segments were identified according to identity scores from IgBLAST reference sequences. Simultaneously, the mouse IgG subclass was determined at the DNA level based on isotype-specific sequence patterns in the CH1 domain. Knowing the DNA sequence of V-(D-)J recombination responsible for the complementary determining region 3 (CDR 3), variable region-specific primers were designed and used to amplify the corresponding antibody constant regions. Results: To verify the approach, we applied it to the hybridoma clone BAM-CCMV-29-81 and obtained identical full-length antibody
sequences as with RNA Illumina sequencing. Further validation at the protein level using an established MALDI-TOF MS-fingerprinting protocol showed that five out of six genetically encoded CDR domains of the monoclonal antibody BAM-CCMV-29-81 could be efficiently correlated. Conclusion: This simple, streamlined method enables the cost-effective determination of the full-length sequence of monoclonal antibodies from hybridoma cell lines, with the added benefit of obtaining the DNA sequence of the antibody ready for recombinant expression
Melt Pool Stability during Local Laser Melting of Lunar Regolith with Large Laser Spots and Varying Gravity
No full textIn order to increase the sustainability of future lunar missions, techniques for in-situ resource utilization (ISRU) must be developed. In this context, the local melting of lunar dust (regolith) by laser radiation for the production of parts and larger structures was investigated in detail. With different experimental setups in normal and microgravity, laser spots with diameters from 5 mm to 100 mm were realized to melt the regolith simulant EAC-1A and an 80%/20% mixture of TUBS-T and TUBS-M, which are used as a substitute for the actual lunar soil. In the experiments performed, the critical parameters are the size of the laser spot, the velocity of the laser spot on the surface of the powder bed, the gravity and the wettability of the powder bed by the melt. The stability of the melt pool as a function of these parameters was investigated and it was found that the formation of a stable melt pool is determined by gravity for large melt pool sizes in the range of 50 mm and by surface tension for small melt pool sizes in the range of a few mm
Harnessing Mechanochemistry to Combat PFAS Contamination
No full textFor over 70 years, the uncontrolled production, use, and disposal of per- and polyfluoroalkyl substances (PFAS) have led to widespread global contamination, necessitating the rapid development of innovative and efficient remediation technologies. State-of-the-art strategies rely on energy-intensive incineration, which releases greenhouse gases and smaller, volatile PFAS derivatives. Here, we present a fast, simple, and sustainable method for the complete degradation of PFAS leveraging mechanochemistry to break down the persistent carbon-fluorine bonds. Our findings indicate that liquid-assisted grinding conditions accelerate the degradation of perfluorooctanoic acid compared to neat grinding conditions, resulting in a significant reduction in energy consumption. Moreover, the fluoride released during the process binds to inorganic additives, allowing fluorine recovery as crystalline salts and preventing the formation of secondary toxic waste. The method has strong potential for scaling up and offers a green and viable solution for real-world application in PFAS decontamination
Special issue on wildland-urban interface (WUI) fires
No full textSpecial issue on wild-urban interface (WUI) fires with 25 papers in total. Contributed papers came from all across the globe and included Algeria, Australia, Brazil, China, France, Germany, Japan, Poland, Norway, New Zealand, Spain, Sweden, and the United States of America. The global coverage of contributed papers demonstrated the growing nature of the WUI fire problem
32 examples of LLM applications in materials science and chemistry: towards automation, assistants, agents, and accelerated scientific discovery
No full textLarge Language Models (LLMs) are reshaping many aspects of materials science and chemistry research, enabling advances in molecular property prediction, materials design, scientific automation, knowledge extraction, and more. Recent developments demonstrate that the latest class of models are able to integrate structured and unstructured data, assist in hypothesis generation, and streamline research workflows. To explore the frontier of LLM capabilities across the research lifecycle, we review applications of LLMs through 34 total projects developed during the second annual Large Language Model Hackathon for Applications in Materials Science and Chemistry, a global hybrid event. These projects spanned seven key research areas: (1) molecular and material property prediction, (2) molecular and material design, (3) automation and novel interfaces, (4) scientific communication and education, (5) research data management and automation, (6) hypothesis generation and evaluation, and (7) knowledge extraction and reasoning from the scientific literature. Collectively, these applications illustrate how LLMs serve as versatile predictive models, platforms for rapid prototyping of domain-specific tools, and much more. In particular, improvements in both open source and proprietary LLM performance through the addition of reasoning, additional training data, and new techniques have expanded effectiveness, particularly in low-data environments and interdisciplinary research. As LLMs continue to improve, their integration into scientific workflows presents both new opportunities and new challenges, requiring ongoing exploration, continued refinement, and further research to address reliability, interpretability, and reproducibility
Thightness Assessment of welded Lids for Encapsulations of damaged Spent Nuclear Fuel in the Design Approval Process of Dual-Purpose Casks (DPC)
No full textThe disposal of spent nuclear fuel in Germany is ensured using dual-purpose casks (DPC) for transport and interim storage. The leak tightness of the DPC and resulting containment is one of the most important aspects. Additional encapsulations are required for damaged spent nuclear fuel (DSNF) to guarantee safe handling and a separate tight closure. Due to the general design of DPCs for standard fuel assemblies should special requirements be considered for the design of the encapsulations for DSNF to ensure the loading in existing package designs. The absence of a replaceable sealing in the tightness barrier is the main difference for the encapsulations for damaged spent nuclear fuel. Instead, they are welded shut with a lid. The leak tightness of the encapsulation shall be proven in the design approval process for all transport conditions. This is especially valid for accident conditions of transport, where high internal impact forces may occur.
BAM as German competent authority is responsible for the safety assessment of mechanical and thermal design, retention of radioactive material and quality assurance aspects of manufacturing and operation. BAM carried out a comprehensive safety assessment concerning the mechanical package design. As there are no representative standards for verifying the leak tightness of a welded lid, two approaches were being pursued. Established German standards may be used for verifying the leak tightness of a weld - but limited to low stresses. Therefore, physical tests were required for higher impact loads. Representative drop tests and highly sensitive leakage tests were performed.
The paper presents an overview of the containment assessment by BAM and points out the main findings for the design of welds regarding leak tightness. Both verification procedures are described, on one hand with German standards for lower loads and on the other hand with physical tests for higher impact loads. The leak tightness of the encapsulation weld could be approved based on leakage tests and a corresponding evaluation for all transport conditions
Feature Extractor for Damage Localization on Composite-Overwrapped Pressure Vessel Based on Signal Similarity Using Ultrasonic Guided Waves
No full textHydrogen is one of the future green energy sources that could resolve issues related to fossil fuels. The widespread use of hydrogen can be enabled by composite-overwrapped pressure vessels for storage. It offers advantages due to its low weight and improved mechanical performance. However, the safe storage of hydrogen requires continuous monitoring. Combining ultrasonic guided waves with interpretable machine learning provides a powerful tool for structural health monitoring. In this study, we developed a feature extraction approach based on a similarity method that enables interpretability in the proposed machine learning model for damage detection and localization in pressure vessels. Furthermore, a systematic optimization was performed to explore and tune the model’s parameters. This resulting model provides accurate damage localization and is capable of detecting and localizing damage on hydrogen pressure vessels with an average localization error of 2 cm and a classification accuracy of 96.5% when using quantized classification. In contrast, binarized classification yields a higher accuracy of 99.5%, but with a larger localization error of 6 cm
Influence of chemical composition on microstructure and mechanical properties in the extruded aluminum alloys 7021B and 7175
No full textThe aim of this study is to improve the mechanical properties of Al 7xxx series alloys by achieving the strengthening benefits typically provided by Cu while avoiding the formation of low-melting eutectic phases associated with excessive Cu content. This is accomplished through a tailored combination of alloying elements and optimized thermomechanical treatments.
Alloys 7021B (high Zn content) and 7175 (high Cu and Mg content) are analyzed and optimized threefold in this study: the heat treatment, the microstructural evolution and the mechanical properties are investigated by several methods and compared with the aim of improving the process parameters for subsequent application.
The peak-aging process is optimized via compression tests to overcome the strength-ductility trade-off. Microstructure and phase chemistry analyses by transmission electron microscopy and atom probe tomography enable a better understanding of the underlying morphological features such as the spatial distribution, and the chemical composition of the hardening phases. The mechanical properties of the peak-aged alloys are determined by compression and tensile tests. Both alloys exhibit very high strength – even by 7xxx series standards. It can be traced back to the dislocation movement: it is impeded both by homogeneously distributed cuttable Guinier–Preston zones in both alloys and by non-cuttable η’ precipitates.
As a result, we demonstrate that alloy 7021B offers novel possibilities for processing and industrial application: high strength, typically associated with Cu containing alloys, can also be obtained in Cu free alloys, if the Zn content is sufficiently high. We can thus suggest new opportunities for processing and industrial applications by reducing the risk of forming low-melting eutectic phases