Blar i SINTEF Industri på forfatter "Vegge, Tejs"

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    • The atomic simulation environment - A Python library for working with atoms 

      Larsen, Ask Hjorth; Mortensen, Jens Jørgen; Blomqvist, Jakob; Castelli, Ivano E.; Christensen, Rune; Dulak, Marcin; Friis, Jesper; Groves, Michael N.; Hammer, Bjørk; Hargus, Cory; Hermes, Eric D.; Jennings, Paul C.; Jensen, Peter Bjerre; Kermode, James; Kitchin, John R.; Kolsbjerg, Esben Leonhard; Kubal, Joseph; Kaasbjerg, Kristen; Lysgaard, Steen; Maronsson, Jón Bergmann; Maxson, Tristan; Olsen, Thomas; Pastewka, Lars; Peterson, Andrew; Rostgaard, Carsten; Schiøtz, Jakob; Schütt, Ole; Strange, Mikkel; Thygesen, Kristian S.; Vegge, Tejs; Vilhelmsen, Lasse; Walter, Michael N.; Zeng, Zhenhua; Jacobsen, Karsten Wedel (Peer reviewed; Journal article, 2017)
      Abstract The Atomic Simulation Environment (ASE) is a software package written in the Python programming language with the aim of setting up, steering, and analyzing atomistic simula- tions. In ASE, tasks are fully scripted ...

    • Data Management Plans: the Importance of Data Management in the BIG-MAP Project 

      Castelli, Ivano; Arismendi-Arrieta, Daniel; Bhowmik, Arghya; Cekic-Laskovic, Isidora; Clark, Simon; Flores, Eibar; Flowers, Jackson; Frederiksen, Karina; Friis, Jesper; Grimaud, Alexis; Hansen, Karin; Hardwick, Laurence; Hermansson, Kersti; Lauritzen, Hanne; Le Cras, Frederic; Li, Hongjiao; Lyonnard, Sandrine; Lorrmann, Henning; Dominko, Robert; Koeniger, Lukas; Marzari, Nicola; Niedzicki, Leszek; Pizzi, Giovanni; Rahmanian, Fuzhan; Stein, Helge; Uhrin, Martin; Wenzel, Wolfgang; Winter, Martin; Woelke, Christian; Vegge, Tejs (Peer reviewed; Journal article, 2021)
      Open access to research data is increasingly important for accelerating research. Grant authorities therefore request detailed plans for how data is managed in the projects they finance. We have recently developed such a ...

    • Rechargeable Batteries of the Future—The State of the Art from a BATTERY 2030+ Perspective 

      Clark, Simon; Fichtner, Maximilian; Edström, Kristina; Ayerbe, Elixabete; Berecibar, Maitane; Bhowmik, Arghya; Castelli, Ivano E.; Dominko, Roberto; Erakca, Merve; Franco, Alejandro A.; Grimaud, Alexis; Horstmann, Birger; Latz, Arnulf; Lorrmann, Henning; Meeus, Marcel; Narayan, Rekha; Pammer, Frank; Ruhland, Janna; Stein, Helge; Vegge, Tejs; Weil, Marcel (Peer reviewed; Journal article, 2021)
      The development of new batteries has historically been achieved through discovery and development cycles based on the intuition of the researcher, followed by experimental trial and error—often helped along by serendipitous ...

    • A Roadmap for Transforming Research to Invent the Batteries of the Future Designed within the European Large Scale Research Initiative BATTERY 2030+ 

      Amici, Julia; Asinari, Pietro; Ayerbe, Elixabete; Barboux, Philippe; Bayle-Guillemaud, Pascale; Behm, R. Juergen; Berecibar, Maitane; Berg, Erik; Bhowmik, Arghya; Bodoardo, Silvia; Castelli, Ivano E.; Cekic-Laskovic, Isidora; Christensen, Rune; Clark, Simon; Diehm, Ralf; Dominko, Robert; Fichtner, Maximilian; Franco, Alejandro A.; Grimaud, Alexis; Guillet, Nicolas; Hahlin, Maria; Hartmann, Sarah; Heiries, Vincent; Hermansson, Kersti; Heuer, Andreas; Jana, Saibal; Jabbour, Lara; Kallo, Josef; Latz, Arnulf; Lorrmann, Henning; Løvvik, Ole Martin; Lyonnard, Sandrine; Meeus, Marcel; Paillard, Elie; Perraud, Simon; Placke, Tobias; Punckt, Christian; Raccurt, Oliver; Ruhland, Janna; Sheridan, Edel Maria; Stein, Helge; Tarascon, Jean-Marie; Trapp, Victor; Vegge, Tejs; Weil, Marcel; Wentzel, Wolfgang; Winter, Martin; Wolf, Andreas; Edström, Kristina (Peer reviewed; Journal article, 2022)
      This roadmap presents the transformational research ideas proposed by “BATTERY 2030+,” the European large-scale research initiative for future battery chemistries. A “chemistry-neutral” roadmap to advance battery research, ...

    • Understanding the patterns that neural networks learn from chemical spectra 

      Rieger, Laura Hannemose; Wilson, Max; Vegge, Tejs; Flores Cedeño, Eibar (Peer reviewed; Journal article, 2023)
      Analysing spectra from experimental characterization of materials is time consuming, susceptible to distortions in data, requires specific domain knowledge, and may be susceptible to biases in general heuristics under human ...