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Bane and boon of oxygen mediating the performance of nickel catalysts in dry reforming of methane

Catalysis is one of the key technologies in the chemical industry and has a wide-reaching impact on various aspects of our daily lives, including plastics manufacturing, drug synthesis, and produc .

Berlin
Germany
Daniel-cruz
Thomas-lunkenbein
Wulyu-jiang
Christoph-scheurer
Danail-ivanov
Adnan-hammud
Luis-sandoval-diaz
Robert-schl
Karsten-reuter
Milivoj-plodinec

How can I prepare for something I do not yet know?

How can I prepare for something I do not yet know? How can I prepare myself for something I do not yet know? Scientists from the Technical University of Munich (TUM) and from the Fritz Haber Institute Of Berlin have addressed this almost philosophical question in the context of machine learning. Learning is no more than drawing new decisions on prior experience. In order to deal with a new situation in this way, one needs to have dealt with roughly similar situations before. In machine learning, this correspondingly means that a learning algorithm needs to have been exposed to roughly similar data.

Munich
Bayern
Germany
Berlin
Harald-oberhofer
Karsten-reuter
Technical-university-of-munich
Fritz-haber-institute
Theory-department
Technical-university
Fritz-haber-institute-of-berlin
Heisenberg-scholar

Towards new solar cells with active machine learning

Fewer requirements let artificial intelligence discover new materialsTowards new solar cells with active machine learning A research team from the Technical University of Munich (TUM) and the Fritz Haber Institute in Berlin uses active machine learning in the search for suitable molecular materials for new organic semiconductors, the basis for organic field effect transistors (OFETs), light-emitting diodes (OLEDs) and organic solar cells (OPVs). To efficiently deal with the myriad of possibilities for candidate molecules, the machine decides for itself which data it needs. How can I prepare myself for something I do not yet know? Scientists from the Technical University of Munich and from the Fritz Haber Institute in Berlin have addressed this almost philosophical question in the context of machine learning. 

Harald-oberhofer
Karsten-reuter
Theory-department
Heisenberg-scholar
Theoretical-chemistry
கார்ஸ்டன்-ராய்டர்
கோட்பாடு-துறை
கோட்பாட்டு-வேதியியல்

Toward new solar cells with active learning

Toward new solar cells with active learning
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Munich
Bayern
Germany
Berlin
Karsten-reuter
Technical-university-of-munich
Nature-communications
Theory-department-of-the-fritz-haber-institute
Fritz-haber-institute
Theory-department
Technical-university
Theory-departmentat

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