Designing nanogRaphEnes for quAntuM Sensing

Objective

One of the central challenges for the development of quantum technologies is the ability to detect and manipulate individual spins. A major step forward has been achieved with the advent of electron spin resonance (ESR) combined with scanning tunneling microscopy (STM), a unique quantum sensing platform that brings together atomic-scale resolution and unrivaled sensitivity to magnetic transitions. Despite this remarkable breakthrough, only a handful of atomic and molecular systems have been explored so far as on-surface sensing spins. Nanographenes (NGs) stand out as ideal candidates: their atomic structure can be engineered with nano-scale precision through bottom-up on-surface synthesis, while their magnetic properties can be tuned by structural design, offering a unique playground for quantum magnetism. To date, however, NGs and ESR-STM have evolved largely independently, and the field could be greatly benefited from predictive models that unveil the conditions to exploit their combined potential. DREAMS aims to bridge this gap, providing a realistic framework to establish NGs as ESR-active centers with robust and tunable spin states. Since STM experiments probe molecules directly on surfaces, a key requirement is to ensure that their spin properties survive upon adsorption. Furthermore, the ability to assemble NG blocks into larger architectures naturally motivates the design of artificial spin lattices, where collective quantum states can emerge. Finally, as ESR-STM provides direct access to spin excitations, it becomes essential to understand and predict the spin dissipation dynamics under driving conditions. By generating open datasets and predictive models, DREAMS will provide essential guidelines for the next generation of nanographene-based quantum sensing technologies. In addition, scientific events will be organized to promote theory-experiment exchange, reinforce collaborations across Europe, and spread project innovations to boost the field’s growth.