News: Suppliers
28 July 2025
Aixtron CCS system chosen for 2D materials-based photonic device pilot line at Cambridge Graphene Centre
Deposition equipment maker Aixtron SE in Herzogenrath, near Aachen, Germany says that the UK’s University of Cambridge has purchased a Close Coupled Showerhead system for 2D materials for its photonics and optoelectronics R&D.
The system enables wafer-scale growth of layered 2D materials, allowing integration with silicon photonics to produce highly efficient and high-speed optical data communication devices.
“2D layers offer enormous opportunities in photonics, optoelectronics and nanoelectronics,” comments Aixtron’s CEO Dr Felix Grawert.
The Close Coupled Showerhead (CCS) system is set in a 200mm configuration and is currently being installed at the Cambridge Graphene Centre, to be used for the UK’s Layered Materials Research Foundry (LMRF). The LMRF will focus its research on graphene and other layered materials to deliver, at a pilot scale to end users, a fully integrated silicon photonics platform.
Aixtron’s CCS platform was chosen for this pilot line because it is currently the only platform that allows seamless process transfer and scaling to 300mm and high-volume manufacturing of layered materials. It also brings manufacturing-level features to the lab scale. This is due to Aixtron’s proprietary full-wafer temperature control via the ARGUS temperature mapping system, as well as precise precursor delivery and control using Aixtron’s concentration monitor Epison.
“For many years, we have worked closely with Aixtron, which has allowed us to advance our research and development in layered materials,” says professor Andrea Ferrari, director of the Cambridge Graphene Centre at the University of Cambridge. “Aixtron’s CCS system, which we are currently installing at our Cambridge Graphene Centre, will be used to deposit layered materials for optical transceivers and modulators which will be used for high-speed data applications like 5G/6G as well as optical interconnects and switches for next-generation energy-efficient AI hardware,” he adds.
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