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.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 InformationSep 16, 202021 citations

NMR Study in the Low-Dimensional Quantum Spin System

真治松本

Mar 25, 19980 citations

Comment on: Is multiple quantum nuclear magnetic resonance spectroscopy of liquid water real?

Daniel Abergel, Marc‐André Delsuc, Jean‐Yves Lallemand

Recently, two-dimensional NMR experiments have been performed, which were likely to show that a coupling between otherwise uncoupled or equivalent spins was observable, yielding signals originating from multiple-spin multiple-quantum operators in the density matrix. According to the authors, such surprising results could be interpreted as a consequence of the radiation damping phenomenon. For this purpose, a fully quantum-mechanical frame was used, thus treating the radiation field in a quantized manner. Our analysis, based on the same theoretical grounds, as well as on new experimental arguments, lead us to diverging conclusions.Recently, two-dimensional NMR experiments have been performed, which were likely to show that a coupling between otherwise uncoupled or equivalent spins was observable, yielding signals originating from multiple-spin multiple-quantum operators in the density matrix. According to the authors, such surprising results could be interpreted as a consequence of the radiation damping phenomenon. For this purpose, a fully quantum-mechanical frame was used, thus treating the radiation field in a quantized manner. Our analysis, based on the same theoretical grounds, as well as on new experimental arguments, lead us to diverging conclusions.

The Journal of Chemical PhysicsJan 15, 199232 citations

Optical Analogs of Two-Dimensional NMR

ScienceJun 6, 20030 citations

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

Zhiping Yang, Xi Kong, Zhijie Li +10 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.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.

Feb 15, 20191 citation

^{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.