28–30 Sept 2026
Kaiserslautern
Europe/Berlin timezone

Quantum sensing with spin defects in emerging platforms beyond diamond

29 Sept 2026, 16:50
20m
Room 270 (Building 46)

Room 270

Building 46

Contributed Talk Micro/Nano Engineering Scientific Session VIII (Invited talk Gesa Welker)

Speaker

Linyan Nie (Technical University of Munich)

Description

Optically addressable spin systems, such as nitrogen-vacancy (NV) centers in diamond, have been widely studied for quantum sensing applications. Recently, our group demonstrated two novel quantum sensing platforms based on naturally occurring spin defects in boron nitride nanotubes (BNNTs) (1,2). These defects combine high surface area with omnidirectional spin control—key features that enhance sensing performance. We present strong evidence that these defects form weakly coupled spin pairs, akin to recently identified centers in hBN (3), and demonstrate coherent spin control over ensembles embedded within dense, microscale BNNT networks. Through dynamical decoupling, we enhance spin coherence times by over 300-fold and achieve high-resolution detection of radiofrequency signals. Integration of the BNNT mesh sensor into a microfluidic platform enables chemical sensing of paramagnetic ions in solution, with detectable concentrations nearly 1000 times lower than those reported for comparable hBN-based systems (4,5). This highly porous and flexible architecture positions BNNTs as a powerful new host material for quantum sensing. (2) Flavin-based cryptochrome proteins: These proteins generate radical pairs upon optical excitation and exhibit optically detected magnetic resonance, a hallmark of electronic spin manipulation essential for quantum sensing (6). We demonstrated that the optical spin interface and associated quantum properties can be tuned via protein structural engineering. Radical pairs within proteins thus provide a versatile biomolecular platform for quantum sensing. Compared to solid-state spin systems, protein-based quantum sensors offer unique advantages for biosensing due to their genetic encodability and the potential for evolutionary design.

Author

Linyan Nie (Technical University of Munich)

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