Felten, M.; Zhang, S.; Changizi, R.; Scheu, C.; Bruns, M.; Strebl, M.; Virtanen, S.; Zander, D.: Contribution of the oxygen reduction reaction to the electrochemical cathodic partial reaction for Mg–Al–Ca solid solutions. Electrochemistry Communications 153, 107529 (2023)
Changizi, R.; Zaefferer, S.; Abdellaoui, L.; Scheu, C.: Effects of Defect Density on Optical Properties Using Correlative Cathodoluminescence and Transmission Electron Microscopy Measurements on Identical PrNbO4 Particles. ACS Applied Electronic Materials 4 (4), pp. 2095 - 2100 (2022)
Frank, A.; Changizi, R.; Scheu, C.: Preparative and analytical challenges in electron microscopic investigation of nanostructured CuInS2 thin films for energy applications. Microscience Microscopy Congress (MMC) 2019, Manchester, UK (2019)
Changizi, R.; Lim, J.; Zhang, S.; Schwarz, T.; Scheu, C.: Characterization of KCa2Nb3O10. IAMNano 2019, International Workshop on Advanced and In-situ Microscopies of Functional Nanomaterials and Devices, Düsseldorf, Germany (2019)
Changizi, R.; Zhang, S.; Schwarz, T.; Scheu, C.: Cathodoluminescence and the structural study of Lanthanide-doped oxides. Workshop on Transmission Electron Microscopy (E-MAT), Antwerp, Belgium (2019)
Changizi, R.; Zhang, S.; Schwarz, T.; Scheu, C.: Study of the chemical composition and the luminescent spectra of Lanthanide-doped oxides. E-MRS 2019 Spring Meeting, Nice, France (2019)
Changizi, R.: Structural Analysis and Correlative Cathodoluminescence Investigations of Pr (doped) Niobates. Dissertation, Georessourcen und Materialtechnik, RWTH Aachen (2022)
Max Planck scientists design a process that merges metal extraction, alloying and processing into one single, eco-friendly step. Their results are now published in the journal Nature.
The general success of large language models (LLM) raises the question if they could be applied to accelerate materials science research and to discover novel sustainable materials. Especially, interdisciplinary research fields including materials science benefit from the LLMs capability to construct a tokenized vector representation of a large…