Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Log inSign up
Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Blog
Job Board
Q3AS

© 2026 Aqora Quantum S.A.S.

TermsPrivacyLegal Notice

Two-dimensional nanoscale nuclear magnetic resonance spectroscopy enhanced by artificial intelligence

Zhiping Yang, Xi Kong, Zhijie Li, Leixin Zhou, Kai Yang, Pei Yu, Pengfei Wang, Ya Wang, Xi Qin, Xing Rong, Xiaodong Wu, Fazhan Shi, Jiangfeng Du

Published Feb 15, 2019• 1 citation
OpenAlex

Abstract

Two-dimensional Nuclear Magnetic Resonance (NMR) is essential in molecular structure determination. The Nitrogen-Vacancy (NV) center in diamond has been proposed and developed as an outstanding quantum sensor to realize NMR in nanoscale. In this work, we develop a scheme for two-dimensional nanoscale NMR spectroscopy based on quantum controls on an NV center. We carry out a proof of principle experiment on a target of two coupled $^{13}$C nuclear spins in diamond. A COSY-like sequences is used to acquire the data on time domain, which is then converted to frequency domain with the fast Fourier transform (FFT). With the two-dimensional NMR spectrum, the structure and location of the set of nuclear spin are resolved. This work marks a fundamental step towards resolving the structure of a single molecule.

Related papers

Structural analysis of nuclear spin clusters via two-dimensional nanoscale nuclear magnetic resonance spectroscopy

Zhiping Yang, Xi Kong, Zhijie Li +9 more

Two-dimensional Nuclear Magnetic Resonance (NMR) is essential in molecular structure determination. The Nitrogen-Vacancy (NV) center in diamond has been proposed and developed as an outstanding quantum sensor to realize NMR in nanoscale. In this work, we develop a scheme for two-dimensional nanoscale NMR spectroscopy based on quantum controls on an NV center. We carry out a proof of principle experiment on a target of two coupled $^{13}$C nuclear spins in diamond. A COSY-like sequences is used to acquire the data on time domain, which is then converted to frequency domain with the fast Fourier transform (FFT). With the two-dimensional NMR spectrum, the structure and location of the set of nuclear spin are resolved. This work marks a fundamental step towards resolving the structure of a single molecule.

arXiv:1902.05676•Feb 15, 2019•2 citations

Structural Analysis of Nuclear Spin Clusters via 2D Nanoscale Nuclear Magnetic Resonance Spectroscopy

Zhiping Yang, Xi Kong, Zhijie Li +9 more

Abstract 2D nuclear magnetic resonance (NMR) is essential in molecular structure determination. The nitrogen vacancy (NV) center in diamond is proposed and developed as an outstanding quantum sensor to realize NMR in nanoscale. In this work, a scheme for 2D nanoscale NMR spectroscopy is developed based on quantum controls on an NV center. A proof‐of‐principle experiment on a target of two coupled nuclear spins in diamond is carried out. A correlation spectroscopy (COSY) like sequence is used to acquire the data on time domain, which is then converted to frequency domain with the fast Fourier transform. With the 2D NMR spectrum, the structure and location of the set of nuclear spin are resolved. This work marks a fundamental step toward resolving the structure of a single molecule.

Advanced Quantum Technologies•Jan 7, 2020•9 citations

Nanoscale NMR of DNA-Functionalized Diamond Using Individual NV Centers

Erika Janitz, Konstantin Herb, Laura A. Völker +2 more

Nuclear magnetic resonance (NMR) spectroscopy is a powerful probe of molecular structure and dynamics but typically requires large spin ensembles. Here, we demonstrate nanoscale NMR detection of fluorinated DNA using individual near-surface nitrogen-vacancy (NV) centers in diamond nanopillar waveguides under ambient conditions. We covalently tether $^{19}$F-labeled oligonucleotides to mixed nitrogen- and oxygen-terminated surfaces, localizing target spins within the nanoscale sensing volume. Probabilistic spin simulations suggest that the measured signals are consistent with those expected from a few molecules and depend strongly on NV-molecule separation, configuration, and local surface heterogeneity. These results establish a framework for NMR of surface-tethered biomolecules and identify key challenges for single-molecule structural elucidation.

physics.ins-detCross-listedarXiv:2609.05570•Sep 7, 2026

Artificial intelligence enhanced two-dimensional nanoscale nuclear magnetic resonance spectroscopy

Xi Kong, Leixin Zhou, Zhijie Li +5 more

Abstract Two-dimensional nuclear magnetic resonance (NMR) is indispensable to molecule structure determination. Nitrogen-vacancy center in diamond has been proposed and developed as an outstanding quantum sensor to realize NMR in nanoscale or even single molecule. However, like conventional multi-dimensional NMR, a more efficient data accumulation and processing method is necessary to realize applicable two-dimensional (2D) nanoscale NMR with a high spatial resolution nitrogen-vacancy sensor. Deep learning is an artificial algorithm, which mimics the network of neurons of human brain, has been demonstrated superb capability in pattern identifying and noise canceling. Here we report a method, combining deep learning and sparse matrix completion, to speed up 2D nanoscale NMR spectroscopy. The signal-to-noise ratio is enhanced by 5.7 ± 1.3 dB in 10% sampling coverage by an artificial intelligence protocol on 2D nanoscale NMR of a single nuclear spin cluster. The artificial intelligence algorithm enhanced 2D nanoscale NMR protocol intrinsically suppresses the observation noise and thus improves sensitivity.

npj Quantum Information•Sep 16, 2020•21 citations

Quantum sensing-enabled deuterium NMR spectroscopy with nanoscale sensitivity at low magnetic fields

Dileep Singh, Riley W. Hooper, Christoph Findler +2 more

Nuclear magnetic resonance (NMR) spectroscopy provides unparalleled access to molecular structure and dynamics but is traditionally limited by weak signal strength, requiring large sample volumes and high magnetic fields. Here, we demonstrate nanoscale deuterium (2H) NMR spectroscopy using nitrogen vacancy (NV) centers in diamond, reproducing the characteristic quadrupolar powder line shapes that are present in the conventional bulk NMR spectra. By detecting statistical spin fluctuations from nanometer scale detection volumes, our approach delivers a sensitivity enhancement of six to eight orders of magnitude over inductive detection while operating at magnetic fields two orders of magnitude lower than those used in conventional NMR. Temperature dependent measurements of a deuterated polymer and molecular solid reveal distinct motional averaging and phase transitions with nanoscale sensitivity. Powder-like NV detected 2H NMR establishes a powerful tool for probing molecular dynamics on the nanoscale and, in the ultimate limit, at the single molecule level - capabilities beyond those of most existing spectroscopic techniques.

physics.app-phCross-listedarXiv:2604.25752•Apr 29, 2026

Efficient detection of statistical RF fields with a quantum sensor

R. Maier, C. Ho, Hitoshi Sumiya +4 more

Nuclear magnetic resonance (NMR) spectroscopy is widely used in fields ranging from chemistry, materials science to neuroscience. Nanoscale NMR spectroscopy using Nitrogen-vacancy (NV) centers in diamond has emerged as a promising platform due to an unprecedented sensitivity down to the single spin level. At the nanoscale, high nuclear spin polarization through spin fluctuations (statistical polarization) far outweighs thermal polarization. However, until now efficient NMR detection using coherent averaging techniques could not be applied to the detection of statistical polarization, leading to long measurement times. Here we present two protocols to enable coherent averaging of statistically oscillating signals through rectification. We demonstrate these protocols on an artificial radiofrequency signal detected with a single NV center at 2.7 T. The signal-to-noise scaling with number of measurements 𝑁 increases from 𝑁0.5 to 𝑁1, improving the measurement time significantly. The relevance of rectification for the detection of statistically polarized nuclear spins using ensembles of NV centers is outlined, paving the way for efficient nanoscale NMR spectroscopy.

•Dec 1, 2025•0 citations
Two-dimensional Nuclear Magnetic Resonance (NMR) is essential in molecular structure determination. The Nitrogen-Vacancy (NV) center in diamond has been proposed and developed as an outstanding quantum sensor to realize NMR in nanoscale. In this work, we develop a scheme for two-dimensional nanoscale NMR spectroscopy based on quantum controls on an NV center. We carry out a proof of principle experiment on a target of two coupled 13^{13}13C nuclear spins in diamond. A COSY-like sequences is used to acquire the data on time domain, which is then converted to frequency domain with the fast Fourier transform (FFT). With the two-dimensional NMR spectrum, the structure and location of the set of nuclear spin are resolved. This work marks a fundamental step towards resolving the structure of a single molecule.
Two-dimensional Nuclear Magnetic Resonance (NMR) is essential in molecular structure determination. The Nitrogen-Vacancy (NV) center in diamond has been proposed and developed as an outstanding quantum sensor to realize NMR in nanoscale. In this work, we develop a scheme for two-dimensional nanoscale NMR spectroscopy based on quantum controls on an NV center. We carry out a proof of principle experiment on a target of two coupled 13^{13}13C nuclear spins in diamond. A COSY-like sequences is used to acquire the data on time domain, which is then converted to frequency domain with the fast Fourier transform (FFT). With the two-dimensional NMR spectrum, the structure and location of the set of nuclear spin are resolved. This work marks a fundamental step towards resolving the structure of a single molecule.
Abstract 2D nuclear magnetic resonance (NMR) is essential in molecular structure determination. The nitrogen vacancy (NV) center in diamond is proposed and developed as an outstanding quantum sensor to realize NMR in nanoscale. In this work, a scheme for 2D nanoscale NMR spectroscopy is developed based on quantum controls on an NV center. A proof‐of‐principle experiment on a target of two coupled nuclear spins in diamond is carried out. A correlation spectroscopy (COSY) like sequence is used to acquire the data on time domain, which is then converted to frequency domain with the fast Fourier transform. With the 2D NMR spectrum, the structure and location of the set of nuclear spin are resolved. This work marks a fundamental step toward resolving the structure of a single molecule.
Nuclear magnetic resonance (NMR) spectroscopy is a powerful probe of molecular structure and dynamics but typically requires large spin ensembles. Here, we demonstrate nanoscale NMR detection of fluorinated DNA using individual near-surface nitrogen-vacancy (NV) centers in diamond nanopillar waveguides under ambient conditions. We covalently tether 19^{19}19F-labeled oligonucleotides to mixed nitrogen- and oxygen-terminated surfaces, localizing target spins within the nanoscale sensing volume. Probabilistic spin simulations suggest that the measured signals are consistent with those expected from a few molecules and depend strongly on NV-molecule separation, configuration, and local surface heterogeneity. These results establish a framework for NMR of surface-tethered biomolecules and identify key challenges for single-molecule structural elucidation.
Abstract Two-dimensional nuclear magnetic resonance (NMR) is indispensable to molecule structure determination. Nitrogen-vacancy center in diamond has been proposed and developed as an outstanding quantum sensor to realize NMR in nanoscale or even single molecule. However, like conventional multi-dimensional NMR, a more efficient data accumulation and processing method is necessary to realize applicable two-dimensional (2D) nanoscale NMR with a high spatial resolution nitrogen-vacancy sensor. Deep learning is an artificial algorithm, which mimics the network of neurons of human brain, has been demonstrated superb capability in pattern identifying and noise canceling. Here we report a method, combining deep learning and sparse matrix completion, to speed up 2D nanoscale NMR spectroscopy. The signal-to-noise ratio is enhanced by 5.7 ± 1.3 dB in 10% sampling coverage by an artificial intelligence protocol on 2D nanoscale NMR of a single nuclear spin cluster. The artificial intelligence algorithm enhanced 2D nanoscale NMR protocol intrinsically suppresses the observation noise and thus improves sensitivity.
Nuclear magnetic resonance (NMR) spectroscopy provides unparalleled access to molecular structure and dynamics but is traditionally limited by weak signal strength, requiring large sample volumes and high magnetic fields. Here, we demonstrate nanoscale deuterium (2H) NMR spectroscopy using nitrogen vacancy (NV) centers in diamond, reproducing the characteristic quadrupolar powder line shapes that are present in the conventional bulk NMR spectra. By detecting statistical spin fluctuations from nanometer scale detection volumes, our approach delivers a sensitivity enhancement of six to eight orders of magnitude over inductive detection while operating at magnetic fields two orders of magnitude lower than those used in conventional NMR. Temperature dependent measurements of a deuterated polymer and molecular solid reveal distinct motional averaging and phase transitions with nanoscale sensitivity. Powder-like NV detected 2H NMR establishes a powerful tool for probing molecular dynamics on the nanoscale and, in the ultimate limit, at the single molecule level - capabilities beyond those of most existing spectroscopic techniques.
Nuclear magnetic resonance (NMR) spectroscopy is widely used in fields ranging from chemistry, materials science to neuroscience. Nanoscale NMR spectroscopy using Nitrogen-vacancy (NV) centers in diamond has emerged as a promising platform due to an unprecedented sensitivity down to the single spin level. At the nanoscale, high nuclear spin polarization through spin fluctuations (statistical polarization) far outweighs thermal polarization. However, until now efficient NMR detection using coherent averaging techniques could not be applied to the detection of statistical polarization, leading to long measurement times. Here we present two protocols to enable coherent averaging of statistically oscillating signals through rectification. We demonstrate these protocols on an artificial radiofrequency signal detected with a single NV center at 2.7 T. The signal-to-noise scaling with number of measurements 𝑁 increases from 𝑁0.5 to 𝑁1, improving the measurement time significantly. The relevance of rectification for the detection of statistically polarized nuclear spins using ensembles of NV centers is outlined, paving the way for efficient nanoscale NMR spectroscopy.