Maximum efficiency, minimum materials and complexity
The a-Si:H is deposited on a AZO-film that acts as a transparent front contact. A ITO-layer serves as rear contact. The organic sub-cell possesses a front contact made of a conductive polymer material (PEDOT) and a metallic rear contact. © Uni Potsdam
Silicon-based thin-film solar cell with a supplementary organic layer can utilise infrared light as well
The cell consists of many active layers, which taken together are less than one micron thick. The new hybrid solar cell is constructed of two extremely thin layers of amorphous silicon as well as an organic layer. Despite the low volume of materials employed, the hybrid cell attains recording-breaking efficiency of 11.7%.
The organic layer is made of fullerenes, also known as “soccer ball molecules”, mixed with semiconducting polymers. It is able to convert infrared light that cannot be utilised by the silicon layers into electrical energy.
The complementary compound of organic and inorganic materials in a stacked cell offers a promising option for future solar cells. The cell was jointly developed through the BMBF “Leading-edge Research and Innovation in the New German Länder” programme by teams at the University of Potsdam and HZB who have published their work in the renowned technical journal Advanced Materials.
The fundamental component of the cell is a very thin layer of amorphous silicon interspersed with hydrogen (hydrogenated amorphous silicon / a-Si:H). These kinds of simple thin-film solar cells do not attain high efficiencies, as they can only use photons in the blue and green regions of the spectrum.
Steffen Roland, a doctoral student in Prof. Dieter Neher’s group at the University of Potsdam, and Sebastian Neubert, a doctoral student under Prof. Rutger Schlatmann in PVcomB at HZB, added first another a-Si:H layer to a tandem cell and then deposited an additional organic layer that enables infrared light as well to be converted into electrical energy. In this manner, they were able to increase the efficiency of the triple-junction cell to over 11%. At the same time, the structure of this solar cell is able to withstand the effects of aging better. This success impressively demonstrates how the close cooperation of doctoral students from different fields of study (organic semiconductors and inorganic semiconductors) leads to new device structures with improved properties.
“The cell can be fabricated easily with established thin-film technology common in the industry, and is also suited to production in large sheets”, explains Schlatmann. Neher adds: “The high absorption coefficients of a-SI:H layers and the properties of the organic layer make possible an active stack no thicker than one micron - that is maximum efficiency with minimum materials!”
Article first published online 7 January 2015 in Advanced Materials: Hybrid Organic/Inorganic Thin-Film Multijunction Solar Cells Exceeding 11% Power Conversion Efficiency
DOI: 10.1002/adma.201404698
- Two winning entries from the HZB in the Helmholtz Imaging ContestA time resolved X-ray tomography by Paul H. Kamm, HZB, has won the second Jury prize and is the winner of the Helmholtz Imaging conference Partizipants Choice Award in this year’s competition. It shows a 3D snapshot of a laser welding process. Among the 20 most beautiful images is also a microscopy image of a solar cell by Yannic Kerkhoff and Daniel Abou Ras, HZB.
- Ultrafast demagnetisation - Thinner iron, stronger effectThe thinner an iron film, the more easily it can be demagnetised by a laser pulse. Researchers at the University of Duisburg-Essen, working with Helmholtz-Zentrum Berlin and other partners, have discovered why: the key lies in the magnetic order at the material's interfaces. In the long term, these findings could contribute to the development of new technologies for magnetic data storage. The results have been published in the scientific journal Advanced Science.
- Blind spot for the arrangement of atomsArtificial intelligence is increasingly being used to predict the properties of new materials. A research team from Jena and the United States now shows in a study published in the journal Nature Computational Science that when language models are used for this purpose, they reliably identify which types of atoms a material contains. However, they make insufficient use of information about how those atoms are arranged in space. Neither larger models nor additional training data resolve this weakness. For material properties that depend strongly on structure, AI models specifically designed to process spatial relationships are therefore the more reliable choice. (DOI: 10.1038/s43588-026-01045-2)