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Advances in ultrafast laser manufacturing: nanostructures, thin films, and scaling perspectives
(2024)
Advanced ultrafast laser technology is a rapidly growing field that currently enables many new industrial and scientific applications. During the last decades, this has been significantly driven by the availability of high-repetition-rate laser sources and novel beam delivery concepts. At the laser side, Moore’s law equally manifests for ultrafast laser technologies, since the average output power of such lasers doubles approximately every two years. This development is mainly driven by the increase of the pulse repetition rates of energetic laser pulses, currently enforcing the development of smart beam control and novel scanning strategies for preventing heat-accumulation and plasma-shielding effects during laser-based materials processing. This keynote presentation addresses the advantages, recent developments, and perspectives of laser processing with ultrashort laser pulses. A special focus is laid on the tailored structuring of thin films as well as the manufacturing and probing of sub-diffraction surface nanostructures – an ongoing race to extreme scales. Current limitations are identified and an outlook to future scaling perspectives will be provided.
An alternative method for lithium isotope analysis by using high-resolution atomic absorption spectrometry (HR-CS-AAS) is proposed herein. This method is based on monitoring the isotope shift of approximately 15 pm for the electronic transition 22P←22S at around the wavelength of 670.8 nm, which can be measured by state-of-the-art HR-CS-AAS. Isotope analysis can be used for (i) the traceable determination of Li concentration and (ii) isotope amount ratio analysis based on a combination of HR-CS-AAS and spectral data analysis by machine learning (ML).
In the first case, the Li spectra are described as the linear superposition of the contributions of the respective isotopes, each consisting of a spin-orbit doublet, which can be expressed as Gaussian components with constant spectral position and width and different relative intensity, reflecting the isotope ratio in the sample. Precision was further improved by using lanthanum as internal spectral standard. The procedure has been validated using human serum-certified reference materials. The results are metrologically comparable and compatible with the certified values.
In the second case, for isotope amount ratio analysis, a scalable tree boosting ML algorithm (XGBoost) was employed and calibrated using a set of samples with 6Li isotope amount fractions ranging from 0.06 to 0.99 mol mol−1. The training ML model was validated with certified reference materials. The procedure was applied to the isotope amount ratio determination of a set of stock chemicals and a BAM candidate reference material NMC111 (LiNi1/3Mn1/3Co1/3O2), a Li-battery cathode material. These determinations were compared with those obtained by MC-ICP-MS and found to be metrologically comparable and compatible. The residual bias was −1.8‰, and the precision obtained ranged from 1.9‰ to 6.2‰. This precision was sufficient to resolve naturally occurring variations. The NMC111 cathode candidate reference material was analyzed using high-resolution continuum source atomic absorption spectrometry with and without matrix purification to assess its suitability for technical applications. The results obtained were metrologically compatible with each other.
The Binder Jetting BJ process is one of the most versatile additive manufacturing technologies in use. In this process a binder is locally jetted into a powder bed for the consolidation of a 3D structure, layer by layer. Basically, all materials which can be provided as a flowable powder and, thus, spreadable to a thin layer, can be processed. Metals, ceramics and polymers are processable, but also materials from nature, such as sand, wood sawdust and insect frass. Moreover, the BJ technology is adapted to large building volumes of some cubic meters easily. Besides these striking advantages, the manufacture of ceramic parts by BJ is still challenging, as the packing density of the powder bed is generally too low and the particle size of a flowable powder too large for a successful densification of printed parts in a subsequent sintering step to an advanced ceramic product. After an introduction of binder jetting in general and highlighting some examples, strategies for obtaining dense ceramic parts by BJ will be introduced.
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.
Sunlight is an almost unavoidable environmental cue and plays a fundamental role in the biology of pro- and eukaryotic organisms. To cope with sunlight-associated stresses e.g., high temperatures, UV radiation with associated DNA damage, accumulation of reactive oxygen species (ROS), desiccation and osmotic stresses, it is important for organisms to accurately sense and respond to changes in light. The benefits of light are obvious for green organisms such as cyanobacteria, algae and plants which use light as an energy source (photosynthesis). Less apparent are other light-dependent processes such as light-driven DNA repair by photolyases (photoreactivation) or ion pumping by microbial opsins. Fungi that can share light-flooded habitats with phototrophs may profit from their excess photosynthetic products. Rock-inhabiting Dothideomycetes and Eurotiomycetes including Knufia petricola possess many proteins for absorbing UV/blue, green, red and far-red light, produce the black 1,8 dihydroxynaphthalene (DHN) melanin and orange-red carotenoids, and may live in multispecies biofilms. Here, we are addressing the question to which extent constitutive pigment formation (melanin and carotenoids) and responses mediated by the stress-activated mitogen-activated protein (MAP) kinase contribute to the observed light (UV-B) tolerance of K. petricola.
The presentation demonstrates an application of multi-scale optical imaging methods such as spectroscopic imaging ellipsometry and white light interference microscopy for the investigation of wide-bandgap semiconductors for power electronics. The capabilities of these methods for the development of new reference calibration samples for scanning microwave microscopes (SMM) and conductive atomic force microscopes (C AFM) are discussed.
In this presentation safety aspects of hydrogen transportation are discussed. At first, the regulatory background and level of safety are presented. In the second part, the modelling of consequence due to sudden rupture of pressure receptacles is explained. Finally, the results are used to define a limit for consequence to enable an acceptable and safe transport of hydrogen.