TY - JOUR A1 - Hattrick-Simpers, J. A1 - Li, K. A1 - Greenwood, M. A1 - Black, R. A1 - Witt, Julia A1 - Kozdras, M. A1 - Pang, X. A1 - Özcan Sandikcioglu, Özlem T1 - Designing durable, sustainable, high-performance materials for clean energy infrastructure JF - Cell reports. Physical science N2 - Civilization and modern societies would not be possible without manmade materials. Considering their production volumes, their supporting role in nearly all industrial processes, and the impact of their sourcing and production on the environment, metals and alloys are and will be of prominent importance for the clean energy transition. The focus of materials discovery must move to more specialized, application-tailored green alloys that outperform the legacy materials not only in performance but also in sustainability and resource efficiency. This white paper summarizes a joint Canadian-German initiative aimed at developing a materials acceleration platform (MAP) focusing on the discovery of new alloy families that will address this challenge. We call our initiative the “Build to Last Materials Acceleration Platform” (B2L-MAP) and present in this perspective our concept of a three-tiered self-driving laboratory that is composed of a simulation-aided pre-selection module (B2L-select), an artificial intelligence (AI)-driven experimental lead generator (B2L-explore), and an upscaling module for durability assessment (B2L-assess). The resulting tool will be used to identify and subsequently demonstrate novel corrosion-resistant alloys at scale for three key applications of critical importance to an offshore, wind-driven hydrogen plant (reusable electrical contacts, offshore infrastructure, and oxygen evolution reaction catalysts). KW - Material Acceleration Platforms (MAPs) KW - Self-driving-labs (SDLs) KW - Automation KW - Artificial Intelligence (AI) KW - Elektrolyse KW - Structural Materials KW - Corrosion PY - 2022 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-568452 DO - https://doi.org/10.1016/j.xcrp.2022.101200 SN - 2666-3864 VL - 4 IS - 1 SP - 1 EP - 11 PB - Cell Press ; Elsevier CY - Maryland Heights, MO AN - OPUS4-56845 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Ozcan, Ozlem T1 - Material acceleration platforms (MAPs) - Global activities and developments at BAM N2 - Die Material Acceleration Platform der BAM (MAPz@BAM) bündelt unsere Automatisierungs-Expertise auf dem Gebiet der Materialwissenschaft und -prüfung. Wir entwickeln modulare Experimentmodule, automatische Prüf- und Auswerteverfahren und setzen künstliche Intelligenz für eine effiziente und autonome Versuchsplanung, - vorhersage und Datenanalyse ein. T2 - WPFM Expert Group on Structural Materials (EGSM) CY - Online meeting DA - 23.05.2023 KW - Material Acceleration Platforms (MAPs) KW - MAPz@BAM KW - Self-driving-labs PY - 2023 AN - OPUS4-59409 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Ozcan, Ozlem T1 - MAPz@BAM Material Acceleration Plattform Zentrum @ BAM N2 - Die Material Acceleration Platform der BAM (MAPz@BAM) bündelt unsere Automatisierungs-Expertise auf dem Gebiet der Materialwissenschaft und -prüfung. Wir entwickeln modulare Experimentmodule, automatische Prüf- und Auswerteverfahren und setzen künstliche Intelligenz für eine effiziente und autonome Versuchsplanung, - vorhersage und Datenanalyse ein. T2 - Kick off Meeting / EnerMAC ZIM Network CY - Berlin, Germany DA - 07.12.2023 KW - Material Acceleration Platforms (MAPs) KW - Self-driving-labs (SDLs) KW - MAPz@BAM PY - 2023 AN - OPUS4-59411 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Ozcan, Ozlem T1 - MAPz@BAM Material Acceleration Plattform Zentrum @ BAM N2 - Die Material Acceleration Platform der BAM (MAPz@BAM) bündelt unsere Automatisierungs-Expertise auf dem Gebiet der Materialwissenschaft und -prüfung. Wir entwickeln modulare Experimentmodule, automatische Prüf- und Auswerteverfahren und setzen künstliche Intelligenz für eine effiziente und autonome Versuchsplanung, - vorhersage und Datenanalyse ein. T2 - TechConnect Adlershof: Grand Solutions CY - Berlin, Germany DA - 06.11.2023 KW - Material Acceleration Platforms (MAPs) KW - Self-driving-labs (SDLs) KW - MAPz@BAM PY - 2023 AN - OPUS4-59412 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -