The nanoscale charge environment critically influences semiconductor physics and device performance. While conventional bulk characterization techniques provide volume-averaged defect properties, they lack the spatial resolution to resolve nanoscale charge heterogeneity and identify microscopic noise sources. Here, we utilize single PL5 centers in 4H-SiC as room-temperature broadband quantum sensors to fill in the gap. We report the first real-time, nanoscale observation of singlecharge tunneling dynamics in a commercial semiconductor at room temperature, by monitoring the random telegraph noise using optically detected magnetic resonance (ODMR). This capability enables an electrical noise imaging technique, showing distinct noise variations across different wafer substrates. By employing dynamical decoupling, we extend noise spectroscopy from near-DC to MHz frequencies, uncovering significant noise spectral density correlations across frequency bands. Finally, we probe MHz-GHz noise and identify its origin via T1 relaxation spectroscopy, obtaining the first nanoscale electron paramagnetic resonance (EPR) spectroscopic fingerprint of charge defects in SiC. These techniques open avenues for characterizing noise environments in semiconductor devices, providing critical insights for optimizing SiC fabrication processes, defect control, and advancing quantum technologies.
The nanoscale charge environment critically influences semiconductor physics and device performance. While conventional bulk characterization techniques provide volume-averaged defect properties, they lack the spatial resolution to resolve nanoscale charge heterogeneity and identify microscopic noise sources. Here, we utilize single PL5 centers in 4H-SiC as room-temperature broadband quantum sensors to fill in the gap. We report the first real-time, nanoscale observation of singlecharge tunneling dynamics in a commercial semiconductor at room temperature, by monitoring the random telegraph noise using optically detected magnetic resonance (ODMR). This capability enables an electrical noise imaging technique, showing distinct noise variations across different wafer substrates. By employing dynamical decoupling, we extend noise spectroscopy from near-DC to MHz frequencies, uncovering significant noise spectral density correlations across frequency bands. Finally, we probe MHz-GHz noise and identify its origin via T1 relaxation spectroscopy, obtaining the first nanoscale electron paramagnetic resonance (EPR) spectroscopic fingerprint of charge defects in SiC. These techniques open avenues for characterizing noise environments in semiconductor devices, providing critical insights for optimizing SiC fabrication processes, defect control, and advancing quantum technologies.
Silicon carbide is an emerging platform for quantum technologies that provides wafer scale and low-cost industrial fabrication. The material also hosts high-quality defects with long coherence times that can be used for quantum computation and sensing applications. Using an ensemble of nitrogen-vacancy centers and an XY8-2 correlation spectroscopy approach, we demonstrate a room-temperature quantum sensing of an artificial AC field centered at ~900 kHz with a spectral resolution of 10 kHz. Implementing the synchronized readout technique, we further extend the frequency resolution of our sensor to 0.01 kHz. These results pave the first steps for silicon carbide quantum sensors toward low-cost nuclear magnetic resonance spectrometers with a wide range of practical applications in medical, chemical, and biological analysis.
Realization of quantum memory with a photonic interface in the telecommunication bands in a wafer-scalable platform is a central requirement for long-distance quantum networks. Silicon carbide (SiC) provides a technologically mature host for integrated quantum photonics, yet only a limited number of defects combine spin functionality with telecom emission. Here we report on chlorine-based defects in 4H-SiC as a platform for telecom-band quantum memory. The emission of these defects spans the entire telecommunication range with zero-phonon lines in the O- and C-bands and a Debye-Waller factor of up to 39%. Time-resolved photoluminescence measurements reveal a short excited-state lifetime in the sub-nanosecond range. We demonstrate that these defects are spin-active even at room temperature, exhibiting optically detected magnetic resonances (ODMR) in the sub-GHz frequency range. Using ODMR spectroscopy and Ramsey interferometry, we resolve the hyperfine structure arising from the interaction with 35Cl nuclear spins. The ODMR spectra exhibit complex behaviour in an external magnetic field due to mixing of electron-nuclear spin states, which is well reproduced by our simulations. The spin relaxation and coherence times are in the sub-microsecond range, limited by rapid quenching of the ODMR contrast and attributed to charge-state metastability. The combination of telecom-band emission, coherent spin control and compatibility with wafer-scale fabrication positions Cl-related defects in SiC as a promising platform for chip-scale quantum memories with spin-photon interfaces operating in the fiber-optic telecommunication windows.
Solid-state color-center spin defects provide a versatile platform for quantum sensing with applications ranging from nanoscale magnetometry to thermometry and electrometry. This review surveys recent progress in nitrogen-vacancy centers in diamond and defect spins in silicon carbide (SiC), with emphasis on their material properties, fabrication strategies, and coherence engineering. Key defect creation and optimization techniques, including ion implantation, femtosecond laser writing, focused ion beam nanofabrication, isotopic engineering, and surface passivation, are discussed in the context of improving spin coherence and optical performance. Fundamental quantum measurement protocols, optically detected magnetic resonance, Rabi oscillations, Ramsey interferometry, and spin echo, are reviewed as a hierarchical framework for characterizing spin control, dephasing, and intrinsic coherence. The review further highlights microscale sensing architectures and examines the growing role of machine learning in pulse optimization, adaptive estimation, and data-driven imaging. Finally, current challenges and future directions are outlined, focusing on scalability, environmental robustness, and autonomous operation. Together, these developments position diamond and SiC color centers as leading platforms for next-generation solid-state quantum sensors.
This extension method advances the characterization of NV centers in silicon carbide (SiC) by incorporating optimization strategies, machine learning (ML), error correction, and advanced sensing protocols. While the base method validated NV centers in 4H-SiC and 6H-SiC as promising solid-state qubits, our extension aims to enhance their performance and scalability for quantum technologies. First, we identified an optimal NV ensemble density of 1.0 × 10¹⁶ cm⁻3, balancing signal strength with minimized dipole–dipole interactions, thereby maximizing collective coherence. Second, a machine learning framework was developed to optimize experimental conditions, scanning laser power, excitation wavelength, and temperature to improve phase coherence time (T₂) by nearly two-fold. Third, advanced quantum sensing protocols were benchmarked, including Ramsey, Spin-Echo, CPMG, XY-8, and ML-optimized pulse sequences, achieving up to 3.5× higher sensitivity compared to conventional spin-echo. Fourth, dynamical decoupling (N=16) was applied to mitigate decoherence, extending T₂ up to ~60 μs at room temperature. Finally, error correction simulations at the NV ensemble level demonstrated logical error rate reductions by nearly two orders of magnitude, showcasing fault-tolerance potential. Overall, this extension transforms NV–SiC centers from characterized quantum defects into a practical platform with enhanced coherence, improved sensing capabilities, and integrated error correction. These results position SiC NV ensembles as a scalable candidate for next-generation quantum computing
The identification of a microscopic configuration of point defects acting as quantum bits is a key step in the advance of quantum information processing and sensing. Among the numerous candidates, silicon-vacancy related centers in silicon carbide (SiC) have shown remarkable properties owing to their particular spin-3/2 ground and excited states. Although, these centers were observed decades ago, two competing models, the isolated negatively charged silicon vacancy and the complex of negatively charged silicon vacancy and neutral carbon vacancy [Phys. Rev. Lett. 115, 247602 (2015)], are still argued as an origin. By means of high-precision first-principles calculations and high-resolution electron spin resonance measurements, we here unambiguously identify the Si-vacancy related qubits in hexagonal SiC as isolated negatively charged silicon vacancies. Moreover, we identify the Si-vacancy qubit configurations that provide room-temperature optical readout.
Photoelectrical detection of magnetic resonance (PDMR) offers a scalable alternative to optical readout of spin defects in semiconductors and is particularly promising for near-infrared (NIR) emitters, where photodetection is often challenging. Here, we demonstrate room-temperature coherent PDMR of PL3 (divacancy), PL5, PL6, and PL7 spins. PL7 and PL5 exhibit notably stronger PDMR than PL6 as opposed to optical detection, indicating higher ionization efficiency and suitability for electrical readout. Rabi oscillation and two-frequency spectroscopy reveal a previously undiscovered secondary resonance of PL7. We determine the zero-field splitting parameters of PL7 and assign the recently reported PL3a defect to PL7. The demonstrated PDMR of these NIR defects constitutes a key advancement toward quantum electronic devices. Also, the clarified spin parameters and ionization characteristics provide a solid foundation for advancing quantum technologies utilizing these defects regardless of the detection schemes.