Active Engineering Clean Energy

MAterials for Smarter AUTOnomous sensors (MASAUTO)

In plain English

AI plain-English summary

Ten early-stage researchers will train to develop new materials that let autonomous sensors generate and store their own power while processing information with minimal energy. The internet of things is expected to reach a trillion connected devices, but powering and interconnecting them remains a bottleneck. Current sensors rely on batteries or wired connections, which limits where and how they can be deployed. MASAUTO tackles two linked problems: creating materials that harvest energy from the environment—such as vibrations, heat, or light—and store it in supercapacitors, while also developing non-volatile memory that retains data without constant power. If successful, the programme could enable autonomous sensors that operate for years without maintenance. These would support real-time climate monitoring, intelligent transportation systems, smart healthcare devices, and precision agriculture. The sensors would also underpin industrial automation and infrastructure monitoring, quietly feeding data into systems that manage traffic, predict equipment failures, or track environmental changes. The project is primarily a training network. Its immediate output is a cohort of scientists skilled in materials science from fundamental principles through to commercial application. The aim is to position Europe as a leader in autonomous sensor technology by building both the materials and the people who can turn them into products.

View original technical description
MASAUTO is a research and training program for 10 early stage researchers (ESRs), focusing on developing a new generation of materials that will overcome the current bottlenecks in the capability and capacity of autonomous sensors. The design of materials for remote sensing applications, such as real-time information on climate changes or for intelligent transportation systems, still represents an enormous challenge. The ongoing exponential growth of the internet of things (IoT) ecosystem - which could reach a trillion devices in the near future - poses a serious challenge in terms of powering and interconnecting the underlying devices. The full potential of the IoT will only be achievable if devices i) have a reliable and sustainable autonomous power supply, and ii) are capable of processing information with reduced power requirements. A promising approach to address the first challenge is the use of an energy harvester-supercapacitor combination, while for the second challenge a promising strategy is the use of non-volatile random access memories. It's, therefore, crucial to develop materials for energy harvesting and storage, as well as low loss electronics. Through MASAUTO, we will create a highly trained cohort of scientists and technologists, enabling rapid and broad commercialization and implementation of technology in public and private research centers and in industrial institutions. The ESRs will acquire a solid multidisciplinary scientific training, from basic science to industrial applications, which will enable them to generate new scientific knowledge of the highest impact. MASAUTO will also deliver practical training on transferable skills in order to increase employability prospects and to provide the researchers with access to highly skilled employment opportunities in the private and public sectors. The overarching aim of the network is to position Europe as a leader in autonomous sensors for smart healthcare, automotives, industry and agriculture.

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Researchers

Judith Driscoll (Principal Investigator)

Related Research

Grants with similar aims, by meaning.

MAterials for Smarter AUTonomous sensOrs
Piezoelectric Energy Harvesters for Self-Powered Automotive Sensors: from Advanced Lead-Free Materials to Smart Systems
AutonoMous self powered miniAturized iNtelligent sensor for environmental sensing anD asset tracking in smArt IoT environments
Next Generation Energy-Harvesting Electronics - holistic approach 1763
FAST and Nano-Enabled SMART Materials, Structures and Systems for Energy Harvesting

Original classification

Training Grant

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