A5049767059- Magnetic Properties of Alloys
- Magnetic properties of thin films
- Magnetic Properties and Applications
- Magnetic and transport properties of perovskites and related materials
- Hydrogen Storage and Materials
- Rare-earth and actinide compounds
- Metallic Glasses and Amorphous Alloys
- Superconducting Materials and Applications
- Electromagnetic Simulation and Numerical Methods
- Model Reduction and Neural Networks
- Neural Networks and Applications
- Microfluidic and Bio-sensing Technologies
- Advanced materials and composites
- Metallurgical and Alloy Processes
- Geomagnetism and Paleomagnetism Studies
- Theoretical and Computational Physics
- Non-Destructive Testing Techniques
- Electric Motor Design and Analysis
- Characterization and Applications of Magnetic Nanoparticles
- Machine Learning in Materials Science
- Vibration and Dynamic Analysis
- Metal Extraction and Bioleaching
- Copper Interconnects and Reliability
- Micro and Nano Robotics
- Cryospheric studies and observations
Christian Doppler Laboratory for Thermoelectricity
2021-2024
Universität für Weiterbildung Krems
2016-2024
Toyota Motor Corporation (Japan)
2020
University of California, Davis
2020
Sheffield Hallam University
2020
University of York
2020
University of Exeter
2020
Uppsala University
2019
St. Pölten University of Applied Sciences
2013-2015
The development of permanent magnets containing less or no rare-earth elements is linked to profound knowledge the coercivity mechanism. Prerequisites for a promising magnet material are high spontaneous magnetization and sufficiently magnetic anisotropy. In addition intrinsic properties microstructure plays significant role in establishing coercivity. influence on coercivity, remanence, energy density product can be understood by {using} micromagnetic simulations. With advances computer...
Partial differential equations and variational problems can be solved with physics informed neural networks (PINNs). The unknown field is approximated networks. Minimizing the residuals of static Maxwell equation at collocation points or magnetostatic energy, weights network are adjusted so that solution approximates magnetic vector potential. This way, flux density for a given magnetization distribution estimated. With as an additional unknown, inverse solved. Augmenting energy terms,...
Finite element micromagnetic simulations are used to compute the temperature-dependent hysteresis properties of Nd2Fe14B permanent magnets in order assess influence a hard (Dy,Nd)2Fe14B shell. The show that 4 nm thick shell cancels out reduction coercivity from an outer defect layer, which is known exist at grain boundaries NdFeB magnets. Activation volumes computed and shown depend on structure's configuration as well temperature.
Rare-earth elements like neodymium, terbium and dysprosium are crucial to the performance of permanent magnets used in various green-energy technologies hybrid or electric cars. To address supply risk those elements, we applied machine-learning techniques design magnetic materials with reduced neodymium content without dysprosium. However, magnet intended be motors should preserved. We developed methods that assist by integrating physical models bridge gap between length scales, from...
Conjugate gradient methods for energy minimization in micromagnetics are compared. The comparison of analytic results with numerical simulation shows that standard conjugate method may fail to produce correct results. A restricts the step length line search is introduced, order avoid this problem. When controlled, techniques a fast and reliable way compute hysteresis properties permanent magnets. applied investigate demagnetizing effects NdFe12 based reduction coercive field by μ0ΔH = 1.4 T at 450 K.
Based on experimental data and extensive experience, magnetic coercivity saturation moment are traditionally used to estimate the microstructure quality of cemented carbides, especially in manufacturing industry. This work demonstrates that predictions structural mechanical properties manufactured WC-Co elements can be derived principle from alone using an artificial neural network (ANN). A collection pellet samples with a wide variety powder compositions processing parameters was produced...
We use a machine learning approach to identify the importance of microstructure characteristics in causing magnetization reversal ideally structured large-grained Nd2Fe14B permanent magnets. The embedded Stoner–Wohlfarth method is used as reduced order model for determining local switching field maps which guide data-driven procedure. predictor random forest classifier we validate by comparing with full micromagnetic simulations case small granular test structures. In course analysis most...
Abstract Microstructural features play an important role in the quality of permanent magnets. The coercivity is greatly influenced by crystallographic defects, like twin boundaries, as well known for MnAl-C. It would be very useful to able predict macroscopic from microstructure imaging. Although this not possible now, present work we examine a related question, namely prediction simulated nucleation fields quasi-three-dimensional (rescaled and extruded) system constructed two-dimensional...
Advanced nanofabrication exploiting e-beam lithography has been used to prepare nanocomposites consisting of periodic arrays soft magnetic FeCo-based nano-inclusions variable dimensions, embedded in a hard FePt matrix. Nanocomposites with non-magnetic (Pt) inclusions and single phase microstructures were prepared as reference samples. The formation Kirkendall voids the soft-in-hard nanocomposites, because annealing-induced diffusion, identified through high resolution imaging chemical...
Multiscale simulation is a key research tool in the quest for new permanent magnets. Starting with first principles methods, sequence of methods can be applied to calculate maximum possible coercive field and expected energy density product magnet made from novel magnetic material composition. Iron (Fe)-rich phases suitable magnets found by means adaptive genetic algorithms. The intrinsic properties computed ab initio simulations are used as input micromagnetic hysteresis realistic...
The maximum coercivity that can be achieved for a given hard magnetic alloy is estimated by computing the energy barrier nucleation of reversed domain in an idealized microstructure without any structural defects and soft secondary phases. For Sm$_{1-z}$Zr$_z$(Fe$_{1-y}$Co$_y$)$_{12-x}$Ti$_x$ based alloys, which are considered alternative to Nd$_2$Fe$_{14}$B magnets with lower rare-earth content, coercive field small cube reduced 60 percent anisotropy at room temperature 50 elevated (473K)....
Exchange coupled ferri-/ferromagnetic heterostructures are a possible material composition for future magnetic storage and sensor applications. In order to understand the driving mechanisms in demagnetization process, we perform micromagnetic simulations by employing Landau-Lifshitz-Gilbert equation. The magnetization reversal is dominated pinning events within amorphous ferrimagnetic layer at interface between ferromagnetic layer. shape of computed loop corresponds well with experimental...
We demonstrate the use of model order reduction and neural networks for estimating hysteresis properties nanocrystalline permanent magnets from microstructure. With a data-driven approach, we learn demagnetization curve data-sets created by grain growth micromagnetic simulations. show that granular structure magnet can be encoded within low-dimensional latent space. Latent codes are constructed using variational autoencoder. The mapping code to is multi-target regression problem. apply deep...
In this work we investigate the potential of tetragonal L1$_0$ ordered FeNi as candidate phase for rare earth free permanent magnets taking into account anisotropy values from recently synthesized, partially thin films. particular, estimate maximum energy product ($BH$)$_\mathrm{max}$ L1$_0$-FeNi nanostructures using micromagnetic simulations. The is limited due to small coercive field L1$_0$-FeNi. Nano-structured consisting 128 equi-axed, platelet-like and columnar-shaped grains show a...
The electronic structure, magnetic properties, and phase formation of hexagonal ferromagnetic ${\mathrm{Fe}}_{3}\mathrm{Sn}$-based alloys have been studied from first principles by experiment. pristine ${\mathrm{Fe}}_{3}\mathrm{Sn}$ compound is known to fulfill all the requirements for a good permanent magnet, except magnetocrystalline anisotropy energy (MAE). latter large, but planar, i.e., easy magnetization axis not along $c$ direction, whereas magnet requires MAE be uniaxial. Here we...
It has been a puzzle for century about how ``hard'' (coercive) ferromagnet can be. Seven decades ago, W. Brown gave his famous theorem to correlate coercivity of its magnetocrystalline anisotropy field. However, the experimental values are far below calculated level given by theorem, which is called Brown's Coercivity Paradox. The paradox considered be related complex microstructures magnets in experiments because an extrinsic property that sensitive any imperfections specimens. To date,...