Data Mining and Machine Learning Tools for Combinatorial Material Science of All‐Oxide Photovoltaic Cells

Publisher： John Wiley & Sons Inc

E-ISSN： 1868-1751|34|6‐7|367-379

ISSN： 1868-1743

Source： MOLECULAR INFORMATICS, Vol.34, Iss.6‐7, 2015-06, pp. : 367-379

Disclaimer: Any content in publications that violate the sovereignty, the constitution or regulations of the PRC is not accepted or approved by CNPIEC.

Previous Menu Next

Abstract

Related content

Stem Cells and Combinatorial Science

By  

Combinatorial Chemistry & High Throughput Screening, Vol. 10, Iss. 8, 2007-09 ,pp. : 635-651

Bentham Science Publishers

Access to resources Recommend Favorite

Room Temperature Oxide Deposition Approach to Fully Transparent, All‐Oxide Thin‐Film Transistors

By  

ADVANCED MATERIALS, Vol. 27, Iss. 40, 2015-10 ,pp. : 6090-6095

John Wiley & Sons Inc

Access to resources Recommend Favorite

Manipulating Aggregation and Molecular Orientation in All‐Polymer Photovoltaic Cells

By  

ADVANCED MATERIALS, Vol. 27, Iss. 39, 2015-10 ,pp. : 6046-6054

John Wiley & Sons Inc

Access to resources Recommend Favorite

Resources for Science Learning: Tools, Tasks, and Environment

By Hewson Peter  

International Journal of Science and Mathematics Education, Vol. 2, Iss. 2, 2004-06 ,pp. : 201-225

Springer Publishing Company

Access to resources Recommend Favorite

Machine learning tools formineral recognition and classification from Raman spectroscopy

By  

JOURNAL OF RAMAN SPECTROSCOPY, Vol. 46, Iss. 10, 2015-10 ,pp. : 894-903

John Wiley & Sons Inc

Access to resources Recommend Favorite