| People | Locations | Statistics |
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| Naji, M. |
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| Motta, Antonella |
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| Aletan, Dirar |
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| Mohamed, Tarek |
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| Ertürk, Emre |
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| Taccardi, Nicola |
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| Kononenko, Denys |
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| Petrov, R. H. | Madrid |
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| Alshaaer, Mazen | Brussels |
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| Bih, L. |
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| Casati, R. |
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| Muller, Hermance |
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| Kočí, Jan | Prague |
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| Šuljagić, Marija |
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| Kalteremidou, Kalliopi-Artemi | Brussels |
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| Azam, Siraj |
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| Ospanova, Alyiya |
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| Blanpain, Bart |
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| Ali, M. A. |
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| Popa, V. |
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| Rančić, M. |
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| Ollier, Nadège |
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| Azevedo, Nuno Monteiro |
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| Landes, Michael |
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| Rignanese, Gian-Marco |
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Banko, Lars
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (26/26 displayed)
- 2024From quinary Co–Cu–Mo–Pd–Re materials libraries to gas diffusion electrodes for Alkaline hydrogen evolutioncitations
- 2023Speeding up high-throughput characterization of materials libraries by active learning: autonomous electrical resistance measurementscitations
- 2023Oxidative depolymerisation of kraft lignincitations
- 2023Microscale combinatorial libraries for the discovery of high-entropy materialscitations
- 2022Composition and electrical resistance results of a Ir-Pd-Pt-Rh-Ru composition spread thin film materials library
- 2022Zooming‐in - visualization of active site heterogeneity in high entropy alloy electrocatalysts using scanning electrochemical cell microscopycitations
- 2022Unusual phase formation in reactively sputter‐deposited La-Co-O thin‐film librariescitations
- 2022Computationally accelerated experimental materials characterizationcitations
- 2022Unravelling composition-activity-stability trends in high entropy alloy electrocatalysts by using a data‐guided combinatorial synthesis strategy and computational modelingcitations
- 2021Deep learning for visualization and novelty detection in large X-ray diffraction datasetscitations
- 2021Bayesian optimization of high‐entropy alloy compositions for electrocatalytic oxygen reductioncitations
- 2020Structure Zone Investigation of Multiple Principle Element Alloy Thin Films as Optimization for Nanoindentation Measurementscitations
- 2020Influences of Cr content on the phase transformation properties and stress change in V-Cr-O thin-film librariescitations
- 2020Fast-track to research data management in experimental material science - setting the ground for research group level materials digitalizationcitations
- 2020Predicting structure zone diagrams for thin film synthesis by generative machine learningcitations
- 2020Comparative study of the residual stress development in HMDSN-based organosilicon and silicon oxide coatingscitations
- 2020Structure zone investigation of multiple principle element alloy thin films as optimization for nanoindentation measurements
- 2020Crystallography companion agent for high-throughput materials discovery
- 2020High-throughput characterization of (Fe<sub><i>x</i></sub>Co<sub>1–<i>x</i></sub>)<sub>3</sub>O<sub>4</sub> thin-film composition spreadscitations
- 2019Mastering processing-microstructure complexity through the prediction of thin film structure zone diagrams by generative machine learning models
- 2019Mastering processing-microstructure complexity through the prediction of thin film structure zone diagrams by generative machine learning models
- 2019Effects of the Ion to growth flux ratio on the constitution and mechanical properties of Cr1–x-Alx-N thin filmscitations
- 2019Ion energy control via the electrical asymmetry effect to tune coating properties in reactive radio frequency sputteringcitations
- 2019Ion energy control via the electrical asymmetry effect to tune coating properties in reactive radio frequency sputteringcitations
- 2018Improved homogeneity of plasma and coating properties using a lance matrix gas distribution in MW-PECVDcitations
- 2018PEALD of SiO2 and Al2O3 thin films on polypropylenecitations
Places of action
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article
Structure Zone Investigation of Multiple Principle Element Alloy Thin Films as Optimization for Nanoindentation Measurements
Abstract
<jats:p>Multiple principal element alloys, also often referred to as compositionally complex alloys or high entropy alloys, present extreme challenges to characterize. They show a vast, multidimensional composition space that merits detailed investigation and optimization to identify compositions and to map the composition ranges where useful properties are maintained. Combinatorial thin film material libraries are a cost-effective and efficient way to create directly comparable, controlled composition variations. Characterizing them comes with its own challenges, including the need for high-speed, automated measurements of dozens to hundreds or more compositions to be screened. By selecting an appropriate thin film morphology through predictable control of critical deposition parameters, representative measured values can be obtained with less scatter, i.e., requiring fewer measurement repetitions for each particular composition. In the present study, equiatomic CoCrFeNi was grown by magnetron sputtering in different locations in the structure zone diagram applied to multinary element alloys, followed by microstructural and morphological characterizations. Increasing the energy input to the deposition process by increased temperature and adding high-power impulse magnetron sputtering (HiPIMS) plasma generators led to denser, more homogeneous morphologies with smoother surfaces until recrystallization and grain boundary grooving began. Growth at 300 °C, even without the extra particle energy input of HiPIMS generators, led to consistently repeatable nanoindentation load–displacement curves and the resulting hardness and Young’s modulus values.</jats:p>