AIXTRON Gains Aeluma as Customer, Signaling AI-Driven Demand

AIXTRON SE has secured a purchase order from Aeluma, Inc., a US-based semiconductor company, for an AIXTRON G10-AsP system to expand its photonics manufacturing capacity. This deal underscores growing demand for advanced materials and equipment within the artificial intelligence (AI) sector, specifically for components used in data communication.

The G10-AsP system will support Aeluma’s development and scaling of its non-indium-phosphide (non-InP) photonics platform. Aeluma’s technology aims to reduce reliance on indium phosphide substrates, potentially increasing production scale and cost efficiency. This agreement builds on a multi-year collaboration between the two companies, highlighting the increasing importance of AIXTRON’s Metal-Organic Chemical Vapor Deposition (MOCVD) technology in the expanding photonics market.

The demand for photonic components in AI data communication is experiencing rapid growth, as evidenced by Aeluma’s expansion plans. The acquisition of the G10-AsP system is directly aligned with Aeluma’s strategy to scale photonic device manufacturing on larger substrates – specifically 150mm and 200mm wafers – to meet this demand. AIXTRON’s CEO, Dr. Felix Grawert, noted that this transition towards larger wafer formats is a key trend in the industry.

This order is particularly noteworthy as it comes amidst broader trends of increased investment in AI-related technologies. Recent media signals indicate a rising tide of capital expenditure focused on future-oriented technologies, benefiting companies like AIXTRON positioned within those supply chains. The acquisition by Aeluma reinforces AIXTRON’s role in enabling the production of critical components for the AI infrastructure buildout, and positions the company to benefit from the continued growth of this market. The order’s value was not disclosed, but the strategic implications for AIXTRON are clear: the deal signals continued momentum in the photonics segment, driven by the insatiable demand for bandwidth in AI applications.