Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Max Planck Institute for Intelligent SystemsDE363 papers
- Center for Integrated Quantum Science and TechnologyDE290 papers
- Max Planck SocietyDE234 papers
- Max Planck Institute for Solid State ResearchDE229 papers
- Centre National de la Recherche ScientifiqueFR219 papers
- The University of TokyoJP83 papers
- ETH ZurichCH80 papers
- Karlsruhe Institute of TechnologyDE75 papers
- Heidelberg UniversityDE74 papers
- Technical University of MunichDE72 papers
- Polish Academy of SciencesPL65 papers
- Leibniz University HannoverDE64 papers
193 papers · 1 filter
Impact of interstitial carbon on local lattice distortions in CoCrFeMnNi high-entropy alloys
Alevtina Smekhova, Alexei Kuzmin, G. Mohan Muralikrishna +5
Here, we explore component-dependent local lattice distortions in polycrystalline, equiatomic, face-centered cubic CrMnFeCoNi high-entropy alloys and their modifications induced by…
Machine learning via artificial neural networks coupled with density functional theory and experiments for thermodynamic optimization of high-entropy alloys for hydrogen storage at room temperature
Shivam Dangwal, Pranav Kumar, Yuji Ikeda +2
High-entropy alloys (HEAs) have received considerable attention for hydrogen storage because of their compositional flexibility; however, designing HEAs with optimal thermodynamics…
Accurate Nanoscale Mapping of Electric Fields across Random Grain Boundaries in Polycrystalline Oxides Using Precession-Assisted 4D-STEM
Sangjun Kang, Hyeyoung Cho, Maximilian Töllner +12
Space charge layers (SCLs) at grain boundaries play a crucial role in modulating local electric fields and influencing the functional properties of materials, such as oxygen vacanc…
Finely Tunable Thermal Expansion of NiTi by Stress-Induced Martensitic Transformation and Thermomechanical Training
Won Seok Choi, Won-Seok Ko, Yejun Park +6
Tailoring the thermal expansion of martensitic materials by crystallographic texture and anisotropic variation of lattice parameters is a promising route to a flexible design of th…
Microstructural origin of the simultaneous enhancements in strength and ductility of a nitrogen-doped high-entropy alloy
Xiaoxiang Wu, Zhujun Sun, Wenqi Guo +9
As one of the most abundant interstitial elements, nitrogen (N) is effective in improving yield strength of metallic materials, due to interstitial solid solution strengthening. Do…
Novel non-thermal Ablation Mechanics in the Laser Ablation of Silicon
Dominic Klein, Simon Kümmel, Johannes Roth
We investigate the non-thermal material dynamics of strongly excited silicon during ultra-fast laser ablation. In contrast to metals, silicon shows strongly excitation-dependent in…
Thermal and Microstructural Simulations of Photonic Sintering of Oxide Ceramics: A Two-Scale Scheme
Junlong Ma, Yangyiwei Yang, Julian N. Ebert +2
Photonic sintering (PS) offers an ultra-fast, contact-free alternative to conventional sintering and has demonstrated its potential for enhancing the sinterability of acceptor-dope…
Hydrogen diffusion in TiCrH Laves phases: A combined ab initio and machine-learning-potential study
Pranav Kumar, Fritz Körmann, Kaveh Edalati +2
The kinetics of hydrogen diffusion in C15 cubic and C14 hexagonal TiCrH (0 < <= 4) Laves-phase hydrogen storage alloys is investigated with density functional theory (D…
Ultrastrong and ductile CoNiMoAl medium-entropy alloys enabled by L12 nanoprecipitate-induced multiple deformation mechanisms
Min Young Sung, Tae Jin Jang, Sang Yoon Song +11
L12 precipitates are known to significantly enhance the strength and ductility of single-phase face-centered cubic (FCC) medium- or high-entropy alloys (M/HEAs). However, further i…
Lattice distortions and non-sluggish diffusion in BCC refractory high entropy alloys
Jingfeng Zhang, Xiang Xu, Fritz Körmann +10
Refractory high-entropy alloys (RHEAs) have emerged as promising candidates for extreme high-temperature applications, for example, in next-generation turbines and nuclear reactors…
Accurate complex-stacking-fault Gibbs energy in Ni3Al at high temperatures
Xiang Xu, Xi Zhang, Andrei Ruban +2
To gain a deeper insight into the anomalous yield behavior of Ni3Al, it is essential to obtain temperature-dependent formation Gibbs energies of the relevant planar defects. Here,…
Machine-learning interatomic potentials achieving CCSD(T) accuracy for systems with extended covalent networks and van der Waals interactions
Yuji Ikeda, Axel Forslund, Pranav Kumar +4
Machine-learning interatomic potentials (MLIPs) enable large-scale atomistic simulations at moderate computational cost while retaining ab initio accuracy. MLIPs trained on coupled…
Free-energy perturbation in the exchange-correlation space accelerated by machine learning: Application to silica polymorphs
Axel Forslund, Jong Hyun Jung, Yuji Ikeda +1
We propose a free-energy-perturbation approach accelerated by machine-learning potentials to efficiently compute transition temperatures and entropies for all rungs of Jacob's ladd…
Roadmap for Photonics with 2D Materials
F. Javier García de Abajo, D. N. Basov, Frank H. L. Koppens +145
Triggered by the development of exfoliation and the identification of a wide range of extraordinary physical properties in self-standing films consisting of one or few atomic layer…
Threshold Switching in Vertically Aligned MoS/SiO Heterostructures based on Silver Ion Migration
Jimin Lee, Rana Walied Ahmad, Sofía Cruces +7
Threshold switching (TS) is a phenomenon where non-permanent changes in electrical resistance of a two-terminal device can be controlled by modulating the voltage bias. TS based on…
Volatile and Nonvolatile Resistive Switching in Lateral 2D Molybdenum Disulfide-Based Memristive Devices
Sofía Cruces, Mohit D. Ganeriwala, Jimin Lee +14
Developing electronic devices capable of emulating biological functions is essential for advancing brain-inspired computation paradigms such as neuromorphic computing. In recent ye…
A collapsed interface approach to resolve grain boundaries in finite element simulations of polycrystalline diffusion
Lena Scholz, Yongliang Ou, Blazej Grabowski +1
Atomic diffusion affects the properties of various engineering materials, which predominantly occur in the polycrystalline state. A rigorous description of polycrystalline diffusio…
Machine Learning Potentials for Hydrogen Absorption in TiCr Laves Phases
Pranav Kumar, Fritz Körmann, Blazej Grabowski +1
The energetics of hydrogen absorption in C15 cubic and C14 hexagonal TiCrH Laves phases is investigated for with density functional theory (DFT) and machine l…
Impact of synthesis method on the structure and function of high entropy oxides
Mario U. González-Rivas, Solveig S. Aamlid, Megan R. Rutherford +9
The term sample dependence describes the troublesome tendency of nominally equivalent samples to exhibit different physical properties. High entropy oxides (HEOs) are a class of ma…
Accurate prediction of structural and mechanical properties on amorphous materials enabled through machine-learning potentials: a case study of silicon nitride
Ganesh Kumar Nayak, Prashanth Srinivasan, Juraj Todt +3
Amorphous silicon nitride (a-SiN) is a material which has found wide application due to its excellent mechanical and electrical properties. Despite the significant effort devoted i…
Atomistic modeling of bulk and grain boundary diffusion in solid electrolyte LiPSCl using machine-learning interatomic potentials
Yongliang Ou, Yuji Ikeda, Lena Scholz +3
LiPSCl is a promising candidate for the solid electrolyte in all-solid-state Li-ion batteries. In applications, this material is in a polycrystalline state with grain bound…
Fermi-liquid behavior of non-altermagnetic RuO
Maxim Wenzel, Ece Uykur, Sahana Rößler +5
Presence of magnetism in potentially altermagnetic RuO has been a subject of intense debate. Using broadband infrared spectroscopy combined with density-functional band-structu…
Effect of high pressure synthesis conditions on the formation of high entropy oxides
Solveig Stubmo Aamlid, Minu Kim, Mario U. González-Rivas +3
High entropy materials are often entropy stabilized, meaning that the configurational entropy from multiple elements sharing a single lattice site stabilizes the structure. In this…
Roadmap for Animate Matter
Giorgio Volpe, Nuno A. M. Araújo, Maria Guix +37
Humanity has long sought inspiration from nature to innovate materials and devices. As science advances, nature-inspired materials are becoming part of our lives. Animate materials…