• Treffer 2 von 2
Zurück zur Trefferliste

Discovering climate-friendly building materials with AI

  • High greenhouse gas emissions from the production of building materials are a major contributor to the current climate crisis. However, developing alternative building materials is complex. Traditional laboratory methods are reaching their limits. Artificial intelligence, on the other hand, can give research a new dynamic. Novel materials are usually developed manually in the laboratory rather than on a computer. This makes the processes time-consuming, difficult and expensive. With the app SLAMD (Sequential Learning App for Materials Discovery), materials researchers can explore the potential of artificial intelligence to speed up materials research and easily apply AI in the lab. The app was developed by our team at the Federal Institute for Materials Research and Testing (BAM) led by Prof. Sabine Kruschwitz together with a team in the Department of Building Materials and Construction Chemistry at TU Berlin led by Prof. Dietmar Stephan. It uses material composition andHigh greenhouse gas emissions from the production of building materials are a major contributor to the current climate crisis. However, developing alternative building materials is complex. Traditional laboratory methods are reaching their limits. Artificial intelligence, on the other hand, can give research a new dynamic. Novel materials are usually developed manually in the laboratory rather than on a computer. This makes the processes time-consuming, difficult and expensive. With the app SLAMD (Sequential Learning App for Materials Discovery), materials researchers can explore the potential of artificial intelligence to speed up materials research and easily apply AI in the lab. The app was developed by our team at the Federal Institute for Materials Research and Testing (BAM) led by Prof. Sabine Kruschwitz together with a team in the Department of Building Materials and Construction Chemistry at TU Berlin led by Prof. Dietmar Stephan. It uses material composition and characterization data to predict ideal material candidates. It can be used to optimize many material properties simultaneously and even incorporates database information such as carbon footprint, material cost or resource availability. Unlike the usual data-intensive AI methods, SLAMD optimally integrates existing knowledge and human feedback, and provides numerous decision support tools to precisely navigate complex scientific knowledge processes towards success. In this talk, we will present some case studies where we were able to find suitable advanced materials in a few months instead of several years. We will talk about the challenges we overcame and the future potential we see for this approach to developing the green materials of the future.zeige mehrzeige weniger

Volltext Dateien herunterladen

  • Voelker_Christoph .pdf
    eng

Metadaten exportieren

Weitere Dienste

Teilen auf Twitter Suche bei Google Scholar Anzahl der Zugriffe auf dieses Dokument
Metadaten
Autor*innen:Christoph VölkerORCiD
Dokumenttyp:Vortrag
Veröffentlichungsform:Präsentation
Sprache:Englisch
Jahr der Erstveröffentlichung:2022
Organisationseinheit der BAM:8 Zerstörungsfreie Prüfung
8 Zerstörungsfreie Prüfung / 8.0 Abteilungsleitung und andere
DDC-Klassifikation:Technik, Medizin, angewandte Wissenschaften / Ingenieurwissenschaften / Ingenieurwissenschaften und zugeordnete Tätigkeiten
Freie Schlagwörter:Alkali activated concrete; Machine Learning; Materials Informatics; Sequential Learning
Themenfelder/Aktivitätsfelder der BAM:Material
Material / Materialdesign
Veranstaltung:Chemometrics meets Artificial Intelligence
Veranstaltungsort:Berlin, Germany
Beginndatum der Veranstaltung:01.04.2022
Verfügbarkeit des Dokuments:Datei für die Öffentlichkeit verfügbar ("Open Access")
Datum der Freischaltung:21.12.2022
Referierte Publikation:Nein
Eingeladener Vortrag:Nein
Einverstanden
Diese Webseite verwendet technisch erforderliche Session-Cookies. Durch die weitere Nutzung der Webseite stimmen Sie diesem zu. Unsere Datenschutzerklärung finden Sie hier.