Saltar al contenido principal

Lamentablemente no somos totalmente compatibles con su navegador. Si tiene la opción, actualice a una versión más reciente o utilice Mozilla Firefox, Microsoft Edge, Google Chrome o Safari 14 o posterior. Si no puede y necesita ayuda, envíenos sus comentarios.

Agradeceríamos sus comentarios sobre esta nueva experiencia.Díganos qué piensa se abre en una nueva pestaña/ventana

Elsevier
Publique con nosotros

Download "How Data Science is Changing R&D in Chemicals and Materials"

This collection of published research from Elsevier Innovation Intelligence provides an in-depth look at how industry innovators are using data science to propel R&D.

Download now to access the following articles:

Natural language processing-guided meta-analysis and structure factor database extraction from glass literature. Journal of Non-Crystalline Solids: X, Volume 15, September 2022. Mohd Zaki, Sahith Reddy Namireddy, Tanu Pittie, Vaibhav Bihani, Shweta Rani Keshri, Vineeth Venugopal, Nitya Nand Gosvami, Jayadeva, N.M. Anoop Krishnan.

History and trends in solar irradiance and PV power forecasting: A preliminary assessment and review using text mining. Solar Energy, Volume 169, 1 July 2018. Dazhi Yang, Jan Kleissl, Christian A. Gueymard, Hugo T.C. Pedro, Carlos F.M. Coimbra.

Machine learning models representing catalytic activity for direct catalytic CO2 hydrogenation to methanol. Materials Today: Proceedings, Volume 72, Part 1, 2023. Pallavi Vanjari, Reddi Kamesh, K. Yamuna Rani.

Acerca de usted
Acerca de su organización