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Pulsed dynamic nuclear polarization: a comprehensive Floquet description.

Gian-Marco Camenisch1, Nino Wili2, Gunnar Jeschke1

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This study introduces matrix-based Floquet theory for pulsed Dynamic Nuclear Polarization (DNP) experiments. The new method provides analytical expressions, offering better insight into polarization transfer efficiency and scaling with magnetic field strength.

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Area of Science:

  • Magnetic Resonance Spectroscopy
  • Quantum Information Science
  • Physical Chemistry

Background:

  • Dynamic Nuclear Polarization (DNP) enhances nuclear spin polarization using electron spins via microwave pulse sequences.
  • Understanding DNP's dependence on magnetic field and power is crucial for high chemical-shift resolution applications.
  • Current numerical simulations (operator-based Floquet theory) offer limited insight into key polarization transfer parameters.

Purpose of the Study:

  • To develop an alternative method for describing pulsed DNP experiments.
  • To derive analytical expressions for transition amplitudes and resonance offsets in DNP.
  • To provide deeper insights into parameters governing efficient polarization transfer in DNP.

Main Methods:

  • Application of matrix-based Floquet theory to pulsed DNP experiments.
  • Derivation of analytical expressions for transition amplitudes and resonance offsets.
  • Validation through comparison with numerical simulations and experimental data (XiX, TOP, TPPM sequences).

Main Results:

  • The matrix-based Floquet theory yields analytical expressions for DNP parameters.
  • The derived analytical expressions accurately predict experimental and numerical simulation results.
  • Demonstrated inverse scaling of transition amplitudes with external magnetic field strength.

Conclusions:

  • Matrix-based Floquet theory offers a powerful analytical approach to pulsed DNP.
  • This method provides superior insight into polarization transfer mechanisms compared to previous numerical methods.
  • The findings facilitate a better understanding of DNP scaling behavior and optimization for applications.