Materials Map

Discover the materials research landscape. Find experts, partners, networks.

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The Materials Map is an open tool for improving networking and interdisciplinary exchange within materials research. It enables cross-database search for cooperation and network partners and discovering of the research landscape.

The dashboard provides detailed information about the selected scientist, e.g. publications. The dashboard can be filtered and shows the relationship to co-authors in different diagrams. In addition, a link is provided to find contact information.

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Materials Map under construction

The Materials Map is still under development. In its current state, it is only based on one single data source and, thus, incomplete and contains duplicates. We are working on incorporating new open data sources like ORCID to improve the quality and the timeliness of our data. We will update Materials Map as soon as possible and kindly ask for your patience.

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1.080 Topics available

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977 Locations available

693.932 PEOPLE
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in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (2/2 displayed)

  • 2023Integrated System Built for Small-Molecule Semiconductors via High-Throughput Approaches17citations
  • 2023Optimizing Perovskite Thin‐Film Parameter Spaces with Machine Learning‐Guided Robotic Platform for High‐Performance Perovskite Solar Cells36citations

Places of action

Chart of shared publication
Wu, Jianchang
2 / 7 shared
Kasian, Olga
1 / 61 shared
Lahn, Leopold
1 / 1 shared
Brabec, Christoph J.
2 / 36 shared
Luo, Junsheng
2 / 4 shared
Barabash, Anastasia
1 / 5 shared
Wang, Yunuo
1 / 4 shared
Zhao, Yicheng
2 / 6 shared
Reiser, Patrick
1 / 6 shared
Guldi, Dirk M.
1 / 21 shared
Pérez-Ojeda, M. Eugenia
1 / 3 shared
Friederich, Pascal
1 / 9 shared
Torresi, Luca
1 / 3 shared
Hu, Manman
1 / 3 shared
Seok, Sang Il
1 / 6 shared
Xie, Zhiqiang
1 / 5 shared
Zhang, Jiyun
2 / 8 shared
Rocha-Ortiz, Juan S.
1 / 2 shared
Berger, Christian G.
1 / 1 shared
Shi, Hongyang
1 / 1 shared
Schmitt, Frederik
1 / 1 shared
Liu, Ziyi
1 / 1 shared
Wu, Zhenni
1 / 2 shared
Osterrieder, Tobias
1 / 1 shared
Zhang, Kaicheng
1 / 6 shared
Wagner, Jerrit
1 / 1 shared
Arnold, Simon
1 / 2 shared
Sutterfella, Carolin M.
1 / 7 shared
Liu, Bowen
1 / 2 shared
Stubhan, Tobias
1 / 8 shared
Heumueller, Thomas
1 / 3 shared
Sytnyk, Mykhailo
1 / 18 shared
Peters, Ian Marius
1 / 2 shared
Chart of publication period
2023

Co-Authors (by relevance)

  • Wu, Jianchang
  • Kasian, Olga
  • Lahn, Leopold
  • Brabec, Christoph J.
  • Luo, Junsheng
  • Barabash, Anastasia
  • Wang, Yunuo
  • Zhao, Yicheng
  • Reiser, Patrick
  • Guldi, Dirk M.
  • Pérez-Ojeda, M. Eugenia
  • Friederich, Pascal
  • Torresi, Luca
  • Hu, Manman
  • Seok, Sang Il
  • Xie, Zhiqiang
  • Zhang, Jiyun
  • Rocha-Ortiz, Juan S.
  • Berger, Christian G.
  • Shi, Hongyang
  • Schmitt, Frederik
  • Liu, Ziyi
  • Wu, Zhenni
  • Osterrieder, Tobias
  • Zhang, Kaicheng
  • Wagner, Jerrit
  • Arnold, Simon
  • Sutterfella, Carolin M.
  • Liu, Bowen
  • Stubhan, Tobias
  • Heumueller, Thomas
  • Sytnyk, Mykhailo
  • Peters, Ian Marius
OrganizationsLocationPeople

document

Integrated System Built for Small-Molecule Semiconductors via High-Throughput Approaches

  • Wu, Jianchang
  • Kasian, Olga
  • Lahn, Leopold
  • Brabec, Christoph J.
  • Luo, Junsheng
  • Barabash, Anastasia
  • Hauch, Jens A.
  • Wang, Yunuo
  • Zhao, Yicheng
  • Reiser, Patrick
  • Guldi, Dirk M.
  • Pérez-Ojeda, M. Eugenia
  • Friederich, Pascal
  • Torresi, Luca
  • Hu, Manman
  • Seok, Sang Il
  • Xie, Zhiqiang
  • Zhang, Jiyun
  • Rocha-Ortiz, Juan S.
Abstract

High-throughput synthesis of solution-processable structurally variable small-molecule semiconductors is both an opportunity and a challenge. A large number of diverse molecules provide a possibility for quick material discovery and machine learning based on experimental data. However, the diversity of the molecular structure leads to the complexity of molecular properties, such as solubility, polarity, and crystallinity, which poses great challenges to solution processing and purification. Here, we first report an integrated system for the high-throughput synthesis, purification, and characterization of molecules with a large variety. Based on the principle “Like dissolves like,” we combine theoretical calculations and a robotic platform to accelerate the purification of those molecules. With this platform, a material library containing 125 molecules and their optical-electronic properties was built within a timeframe of weeks. More importantly, the high repeatability of recrystallization we design is a reliable approach to further upgrading and industrial production.

Topics
  • impedance spectroscopy
  • semiconductor
  • recrystallization
  • crystallinity
  • molecular structure
  • machine learning
  • solution processing