EFFITRONICS Portfolio

Pioneering nanoelectronics for energy-efficient smart edge devices

The EFFITRONICS Portfolio brings together six ambitious research projects funded under the EIC Pathfinder Challenge on Nanoelectronics for Energy-Efficient Smart Edge Devices, announced by the European Innovation Council (EIC) in 2024.

The portfolio shares a common vision: to pave the way for a new generation of smart edge technologies that drastically reduce the energy required for information processing, communication and data transmission. Achieving this goal requires breakthroughs at multiple levels, from advanced materials and novel electronic devices to innovative computing architectures, circuits and thermal management solutions.

The six EFFITRONICS projects address the challenge of energy-efficient edge electronics from different but complementary perspectives: advanced 2D materials, in-memory and neuromorphic computing, innovative device architectures, optical signal processing, thermal management and energy harvesting. Together, they represent a coordinated European effort to explore radically new technologies capable of overcoming the energy-efficiency limitations of conventional electronics.

Through knowledge exchange, collaboration and joint dissemination activities, the EFFITRONICS Portfolio seeks to maximise the impact of these research efforts and help lay the foundations for the next generation of sustainable, intelligent edge devices.

Meet the EFFITRONICS projects:

  • COOLBRAIN: Chiplet cOOling solutions for Low-consumption emBedded pRocessing AI at Nanoscale

    COOLBRAIN explores innovative solutions to improve the energy efficiency of embedded systems and smart devices through advanced chiplet architectures. By integrating diamond into chiplet packages and investigating energy harvesting based on near-field super-Planckian radiative heat transfer, the project aims to address thermal management challenges while opening new opportunities for energy recovery.

    Website: https://coolbrain.eu/

  • 2D-ADDICT: Two-Dimensional materials for Advanced DevIces and low-power Computing

    2D-ADDICT aims to develop a new generation of energy-efficient nanoelectronic devices based on two-dimensional (2D) materials. Combining wafer-scale integration of 2D materials, vertically stacked complementary field-effect transistor (CFET) architectures and advanced modelling, the project seeks to enable equivalent sub-nanometre scaling and significantly reduce energy consumption per computing operation, paving the way for scalable, CMOS-compatible smart edge technologies.

    Website: https://www.2d-addict.eu/

  • 2DFERROPLEX: Ferroelectric 2D materials heterostructures for optical neuromorphic device functionalities

    2DFERROPLEX explores the potential of two-dimensional ferroelectric materials for a new generation of brain-inspired optical computing technologies. By developing ultra-fast, energy-efficient optical components capable of processing information using light, the project aims to establish fundamental building blocks for future neuromorphic systems, including the world's first optical artificial neuron.

    Website: https://2dferroplex.eu/

  • SPARK-e: Solid-state phase change materials for advanced energy recovery and key thermal control in electronics

    SPARK-e focuses on innovative materials for improved thermal management and energy recovery in electronic devices. The project investigates solid-state phase-change materials capable of enhancing heat dissipation, storing excess thermal energy and converting waste heat into electricity. By combining energy efficiency with circularity, SPARK-e aims to improve device performance, reduce energy consumption and extend the lifespan of future electronic systems.

    Website: https://spark-e.eu/

  • SpikeHERO: Spiking hybrid edge computing for robust optoelectronical signal processing

    SpikeHERO aims to develop novel edge computing platforms that combine electrical and optical Spiking Neural Networks (SNNs). Leveraging advanced heterogeneous 3D chiplet integration, the project seeks to bring together low-power, low-latency computation and high-speed, energy-efficient communication, opening new possibilities for brain-inspired signal processing at the edge.

    Website: https://spikehero.eu/

  • CERBERUS: Unlocking the Full Potential of Edge AI through In-memory Computing Based on 2D Materials with Extreme Energy Efficiency

    CERBERUS aims to overcome fundamental energy-efficiency bottlenecks in edge AI computing by developing innovative in-memory computing technologies based on 2D materials. Its approach combines advances across three complementary pillars: highly efficient memristive devices based on monolayer 2D materials, ultra-efficient peripheral circuits and graphene-based heat spreaders. By jointly optimising these components, CERBERUS targets a threefold improvement in energy efficiency for edge AI workloads.

    Website: https://cerberus-project.eu/

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