TY - JOUR A1 - Florian, Camilo A1 - Fischer, Daniel A1 - Freiberg, K. A1 - Duwe, M. A1 - Sahre, Mario A1 - Schneider, S. A1 - Hertwig, Andreas A1 - Krüger, Jörg A1 - Rettenmayr, M. A1 - Beck, Uwe A1 - Undisz, A. A1 - Bonse, Jörn T1 - Single Femtosecond Laser-Pulse-Induced Superficial Amorphization and Re-Crystallization of Silicon N2 - Superficial amorphization and re-crystallization of silicon in <111> and <100> orientation after irradiation by femtosecond laser pulses (790 nm, 30 fs) are studied using optical imaging and transmission electron microscopy. Spectroscopic imaging ellipsometry (SIE) allows fast data acquisition at multiple wavelengths and provides experimental data for calculating nanometric amorphous layer thickness profiles with micrometric lateral resolution based on a thin-film layer model. For a radially Gaussian laser beam and at moderate peak fluences above the melting and below the ablation thresholds, laterally parabolic amorphous layer profiles with maximum thicknesses of several tens of nanometers were quantitatively attained. The accuracy of the calculations is verified experimentally by high-resolution transmission electron microscopy (HRTEM) and energy dispersive X-ray spectroscopy (STEM-EDX). Along with topographic information obtained by atomic force microscopy (AFM), a comprehensive picture of the superficial re-solidification of silicon after local melting by femtosecond laser pulses is drawn. KW - Femtosecond laser KW - Silicon KW - Amorphization KW - Crystallization KW - Spectroscopic imaging ellipsometry PY - 2021 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-523687 UR - https://www.mdpi.com/1996-1944/14/7/1651 DO - https://doi.org/10.3390/ma14071651 SN - 1996-1944 VL - 14 IS - 7 SP - 1651-1 EP - 1651-21 PB - MDPI AG CY - Basel, Switzerland AN - OPUS4-52368 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Ganose, Alex M. A1 - Sahasrabuddhe, Hrushikesh A1 - Asta, Mark A1 - Beck, Kevin A1 - Biswas, Tathagata A1 - Bonkowski, Alexander A1 - Bustamante, Joana A1 - Chen, Xin A1 - Chiang, Yuan A1 - Chrzan, Daryl C. A1 - Clary, Jacob A1 - Cohen, Orion A. A1 - Ertural, Christina A1 - Gallant, Max C. A1 - George, Janine A1 - Gerits, Sophie A1 - Goodall, Rhys E. A. A1 - Guha, Rishabh D. A1 - Hautier, Geoffroy A1 - Horton, Matthew A1 - Inizan, T. J. A1 - Kaplan, Aaron D. A1 - Kingsbury, Ryan S. A1 - Kuner, Matthew C. A1 - Li, Bryant A1 - Linn, Xavier A1 - McDermott, Matthew J. A1 - Mohanakrishnan, Rohith Srinivaas A1 - Naik, Aakash A. A1 - Neaton, Jeffrey B. A1 - Parmar, Shehan M. A1 - Persson, Kristin A. A1 - Petretto, Guido A1 - Purcell, Thomas A. R. A1 - Ricci, Francesco A1 - Rich, Benjamin A1 - Riebesell, Janosh A1 - Rignanese, Gian-Marco A1 - Rosen, Andrew S. A1 - Scheffler, Matthias A1 - Schmidt, Jonathan A1 - Shen, Jimmy-Xuan A1 - Sobolev, Andrei A1 - Sundararaman, Ravishankar A1 - Tezak, Cooper A1 - Trinquet, Victor A1 - Varley, Joel B. A1 - Vigil-Fowler, Derek A1 - Wang, Duo A1 - Waroquiers, David A1 - Wen, Mingjian A1 - Yang, Han A1 - Zheng, Hui A1 - Zheng, Jiongzhi A1 - Zhu, Zhuoying A1 - Jain, Anubhav T1 - Atomate2: Modular workflows for materials science N2 - High-throughput density functional theory (DFT) calculations have become a vital element of computational materials science, enabling materials screening, property database generation, and training of “universal” machine learning models. While several software frameworks have emerged to support these computational efforts, new developments such as machine learned force fields have increased demands for more flexible and programmable workflow solutions. This manuscript introduces atomate2, a comprehensive evolution of our original atomate framework, designed to address existing limitations in computational materials research infrastructure. Key features include the support for multiple electronic structure packages and interoperability between them, along with generalizable workflows that can be written in an abstract form irrespective of the DFT package or machine learning force field used within them. Our hope is that atomate2's improved usability and extensibility can reduce technical barriers for high-throughput research workflows and facilitate the rapid adoption of emerging methods in computational material science. KW - Automation KW - Materials design KW - DFT workflows KW - Phonons KW - Thermal conductivity KW - Bonding analysis PY - 2025 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-635759 DO - https://doi.org/10.1039/d5dd00019j SN - 2635-098X SP - 1 EP - 30 PB - Royal Society of Chemistry (RSC) CY - Cambridge AN - OPUS4-63575 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -