The microelectronics industry has managed to extend Moore's Law through innovative device scaling and processor architectures, yet we are approaching fundamental limits of scaling, operation frequency and power dissipation. Deep learning and data-driven computations increasingly demand frequent memory access, resulting in significant power consumption challenges are hard to address efficiently using conventional compute architectures.
As Europe strives to achieve sovereignty in microelectronics technologies through initiatives like the European Chips Act, there is a growing need to shape the future of computation by innovating key functional materials. Superconductors for quantum computing and topological insulators for in-memory computation represent critical materials that could enable next-generation computational paradigms beyond traditional von Neumann architectures.
A historic juncture is nearing as von Neumann architectures and quantum computing platforms start being used together. Their synergistic operations are enabled by emerging quantum materials such as topological insulators, superconductors and single photon sensing layers.
Quantum computing systems, typically based on superconducting transmon or rf-SQUID qubits, and in-memory computing based on spintronics using novel 2D magnetic materials, have emerged as promising complementary approaches. These new materials minimize Joule heating, enable tunable magnetic and electronic transport properties, allow fast switching, and achieve good memory retention. However, the development of these technologies faces a significant bottleneck: the complexity and cost of processing these specialized materials.
Currently, only a handful of institutions—primarily outside Europe, such as Caltech, MIT, and companies like Rigetti—can develop these materials and build proprietary computing systems. This limitation severely restricts the pace of innovation in quantum and spintronic technologies. Despite excellent European materials manufacturing facilities at institutions like Max Planck, Fraunhofer Institutes, TNO, Imec, and CNRS, these materials require dedicated infrastructure due to their sensitivity to equipment cross-contamination.
