Numerical simulation of free evolution in solid-state nuclear magnetic resonance using low-order correlations in Liouville space

Nuclear spin diffusion under fast magic-angle spinning in solid-state NMR

Solid-state nuclear spin diffusion is the coherent and reversible process through which spin order is transferred via dipolar couplings. With the recent increases in magic-angle spinning (MAS) frequencies and magnetic fields becoming routinely applied in solid-state nuclear magnetic resonance, understanding how the increased 1H resolution obtained affects spin diffusion is necessary for interpretation of several common experiments. To investigate the coherent contributions to spin diffusion with fast MAS, we have developed a low-order correlation in Liouville space model based on the work of Dumez et al. (J. Chem. Phys. 33, 224501, 2010). Specifically, we introduce a new method for basis set selection, which accounts for the resonance-offset dependence at fast MAS. Furthermore, we consider the necessity of including chemical shift, both isotropic and anisotropic, in the modeling of spin diffusion. Using this model, we explore how different experimental factors change the nature of spin diffusion. Then, we show case studies to exemplify the issues that arise in using spin diffusion techniques at fast spinning. We show that the efficiency of polarization transfer via spin diffusion occurring within a deuterated and 100% back-exchanged protein sample at 60 kHz MAS is almost entirely dependent on resonance offset. We additionally identify temperature-dependent magnetization transfer in beta-aspartyl L-alanine, which could be explained by the influence of an incoherent relaxation-based nuclear Overhauser effect.

An analytical treatment of electron spectral saturation for dynamic nuclear polarization NMR of rotating solids

Saturation of electron magnetization by microwave irradiation under magic-angle spinning (MAS) is studied theoretically. The saturation is essential for dynamic nuclear polarization (DNP) enhancement of nuclear magnetic resonance signals. For a spin with a large g-anisotropy and a long T₁ relative to the rotor period, the sample rotation distributes saturation to the whole powder sample spectrum. Analytical expressions for the saturation and frequency profiles are obtained. For a pair of coupled electrons such as those in bis-nitroxides, which are commonly used for MAS DNP, an e_l-e_r model (where e_l and e_r stand for electrons on the left and the right, respectively, in their spectral positions) is introduced to simplify the analysis of a coupled two-spin system under MAS. For such a system, strong electron couplings exchange magnetization during dipolar/J rotor events when the two electron frequencies cross each other. The exchange is equivalent to a swap of the e_l and e_r electrons. This allows for the treatment of a coupled spin pair as two independent spins such that an analytical solution can be obtained for the steady-state magnetization and the difference between the two electrons. The theoretical study with its analytical result provides a simple physical picture of electron saturation under MAS and of how radical properties and experimental parameters affect cross-effect DNP. The effects of depolarization and the extension to more coupled electron spins are also discussed using this approach.

Quantum computation of molecular structure using data from challenging-to-classically-simulate nuclear magnetic resonance experiments

We propose a quantum algorithm for inferring the molecular nuclear spin Hamiltonian from time-resolved measurements of spin-spin correlators, which can be obtained via nuclear magnetic resonance (NMR). We focus on learning the anisotropic dipolar term of the Hamiltonian, which generates dynamics that are challenging to classically simulate in some contexts. We demonstrate the ability to directly estimate the Jacobian and Hessian of the corresponding learning problem on a quantum computer, allowing us to learn the Hamiltonian parameters. We develop algorithms for performing this computation on both noisy near-term and future fault-tolerant quantum computers. We argue that the former is promising as an early beyond-classical quantum application since it only requires evolution of a local spin Hamiltonian. We investigate the example of a protein (ubiquitin) confined on a membrane as a benchmark of our method. We isolate small spin clusters, demonstrate the convergence of our learning algorithm on one such example, and then investigate the learnability of these clusters as we cross the ergodic to non-ergodic phase transition by suppressing the dipolar interaction. We see a clear correspondence between a drop in the multifractal dimension measured across many-body eigenstates of these clusters, and a transition in the structure of the Hessian of the learning cost function (from degenerate to learnable). Our hope is that such quantum computations might enable the interpretation and development of new NMR techniques for analyzing molecular structure.

Mechanism of Electron Spin Decoherence in a Partially Deuterated Glassy Matrix

Long electron spin coherence lifetimes are essential for applications in quantum information science and electron paramagnetic resonance, for instance, for nanoscale distance measurements in biomolecular systems using double electron-electron resonance. We experimentally investigate the decoherence dynamics under the Hahn echo sequence of the organic radical d₁₈-TEMPO in a variably deuterated frozen water:glycerol matrix. The coherence time (phase memory time) T_M scales with proton concentration as [¹H]^-0.65. For selectively deuterated matrices, decoherence is accelerated in the presence of proton clustering, that is, substantial short-range density in the proton-proton radial distribution functions (<3 Å). Simulations using molecular dynamics and many-body spin quantum dynamics show excellent agreement with experiment and show that geminal proton pairs such as CH₂ and OH₂ groups are major decoherence drivers. This provides a predictive tool for designing molecular systems with long electron spin coherence times.

Hybrid quantum-classical simulations of magic angle spinning dynamic nuclear polarization in very large spin systems

Solid-state nuclear magnetic resonance can be enhanced using unpaired electron spins with a method known as dynamic nuclear polarization (DNP). Fundamentally, DNP involves ensembles of thousands of spins, a scale that is difficult to match computationally. This scale prevents us from gaining a complete understanding of the spin dynamics and applying simulations to design sample formulations. We recently developed an ab initio model capable of calculating DNP enhancements in systems of up to ∼1000 nuclei; however, this scale is insufficient to accurately simulate the dependence of DNP enhancements on radical concentration or magic angle spinning (MAS) frequency. We build on this work by using ab initio simulations to train a hybrid model that makes use of a rate matrix to treat nuclear spin diffusion. We show that this model can reproduce the MAS rate and concentration dependence of DNP enhancements and build-up time constants. We then apply it to predict the DNP enhancements in core–shell metal-organic-framework nanoparticles and reveal new insights into the composition of the particles’ shells.

Pure Isotropic Proton Solid State NMR

Resolution in proton solid state magic angle sample spinning (MAS) NMR is limited by the intrinsically imperfect nature of coherent averaging induced by either MAS or multiple pulse sequence methods. Here, we suggest that instead of optimizing and perfecting a coherent averaging scheme, we could approach the problem by parametrically mapping the error terms due to imperfect averaging in a k-space representation, in such a way that they can be removed in a multidimensional correlation leaving only the desired pure isotropic signal. We illustrate the approach here by determining pure isotropic ¹H spectra from a series of MAS spectra acquired at different spinning rates. For six different organic solids, the approach is shown to produce pure isotropic ¹H spectra that are significantly narrower than the MAS spectrum acquired at the fastest possible rate, with linewidths down to as little as 48 Hz. On average, we observe a 7-fold increase in resolution, and up to a factor of 20, as compared with spectra acquired at 100 kHz MAS. The approach is directly applicable to a range of solids, and we anticipate that the same underlying principle for removing errors introduced here can be applied to other problems in NMR spectroscopy.

Large-scale magnetic resonance simulations: A tutorial

Computational modeling is becoming an essential tool in magnetic resonance to design and optimize experiments, test the performance of theoretical models, and interpret experimental data. Recent theoretical research and software development made possible simulations of large spin systems, for example, proteins with thousands of spins, in reasonable time. In the last few years, the Fokker-Planck formalism also re-emerged due to its ability to handle spatial dynamics. The purpose of this tutorial is to describe advantages and disadvantages of the most common formalisms, the latest developments and strategies to improve the computational efficiency, and to guide users in the setting up of a simulation using the Spinach software.

Full-Scale Ab Initio Simulation of Magic-Angle-Spinning Dynamic Nuclear Polarization

Theoretical models aimed at describing magic-angle-spinning (MAS) dynamic nuclear polarization (DNP) NMR have great potential in facilitating the in silico design of DNP polarizing agents and formulations. These models must typically face a trade-off between the accuracy of a strict quantum mechanical description and the need for using realistically large spin systems, for instance, using phenomenological models. Here, we show that the use of aggressive state-space restrictions and an optimization strategy allows full-scale ab initio MAS-DNP simulations of spin systems containing thousands of nuclei. Our simulations are shown to reproduce experimental DNP enhancements quantitatively, including their MAS rate dependence, for both frozen solutions and solid materials. They also reveal the importance of a previously unrecognized structural feature found in some polarizing agents that helps minimize the sensitivity losses imposed by the spin diffusion barrier.

Quantitative Structure-Based Prediction of Electron Spin Decoherence in Organic Radicals

The decoherence, or dephasing, of electron spins in paramagnetic molecules limits sensitivity and resolution in electron paramagnetic resonance spectroscopy, and it represents a challenge for utilizing paramagnetic molecules as qubit units in quantum information devices. For organic radicals in dilute frozen aqueous solution at cryogenic temperatures, electron spin decoherence is driven by neighboring nuclear spins. Here, we show that this nuclear-spin-driven decoherence can be quantitatively predicted from the molecular structure and solvation geometry of the radicals. We use a fully deterministic quantum model of the electron spin and up to 2000 neighboring protons with a static spin Hamiltonian that includes nucleus-nucleus couplings. We present experiments and simulations of two nitroxide radicals and one trityl radical, which have decoherence time scales of 4-5 μs below 60 K. We show that nuclei within 12 Å of the electron spin contribute to decoherence, with the strongest impact from protons 4-8 Å away.

Defeating the Matrix

These are personal recollections and musings, written for the 50th Anniversary of the Journal of Magnetic Resonance. They are distilled from twenty years of writing simulation code, and filtered through hindsight and sarcastic intransigence. To me, the biggest recent achievements of the magnetic resonance community in the field of theory and simulation have been the successful war on the exponential scaling, the powerful and general simulation software, and the return to elegant notation. It appears that our future will be defined by computers. Three aspects are pertinent: simulation as the experiment is designed, optimal control as the experiment proceeds, and machine learning at the data processing stage.

Quantifying proton NMR coherent linewidth in proteins under fast MAS conditions: a second moment approach

Proton detected solid-state NMR under fast magic-angle-spinning (MAS) conditions is currently redefining the applications of solid-state NMR, in particular in structural biology. Understanding the contributions to the spectral linewidth is thereby of paramount importance. When disregarding the sample-dependent inhomogeneous contributions, the NMR proton linewidth is defined by homogeneous broadening, which has incoherent and coherent contributions. Understanding and disentangling these different contributions in multi-spin systems like proteins is still an open issue. The coherent contribution is mainly caused by the dipolar interaction under MAS and is determined by the molecular structure and the proton chemical shifts. Numerical simulation approaches based on numerically exact direct integration of the Liouville-von Neumann equation can give valuable information about the lineshape, but are limited to small spin systems (<12 spins). We present an alternative simulation method for the coherent contributions based on the rapid and partially analytic calculation of the second moments of large spin systems. We first validate the method on a simple system by predicting the ¹⁹F linewidth in CaF₂ under MAS. We compare simulation results to experimental data for microcrystalline ubiquitin (deuterated 100% back-exchanged at 110 kHz and fully-protonated at 125 kHz). Our results quantitatively explain the observed linewidth per-residue basis for the vast majority of residues.

Linear-scaling ab initio simulations of spin diffusion in rotating solids

We investigated the utility of locally restricting the basis sets involved in low-order correlations in Liouville space (LCL) calculations of spin diffusion. Using well-known classical models of spin diffusion, we describe a rationale for selecting the optimal basis set for such calculations. We then show that the use of these locally restricted basis sets provides the same computational accuracy as the full LCL set while reducing the computational time by several orders of magnitude. Speeding up the calculations also enables us to use higher maximum spin orders and increase the computational accuracy. Furthermore, unlike exact and full LCL calculations, locally restricted LCL calculations scale linearly with the system size and should thus enable the ab initio study of spin diffusion in spin systems containing several thousand spins.

Large-scale ab initio simulations of MAS DNP enhancements using a Monte Carlo optimization strategy

Magic-angle-spinning (MAS) dynamic nuclear polarization (DNP) has recently emerged as a powerful technology enabling otherwise unrealistic solid-state NMR experiments. The simulation of DNP processes which might, for example, aid in refining the experimental conditions or the design of better performing polarizing agents, is, however, plagued with significant challenges, often limiting the system size to only 3 spins. Here, we present the first approach to fully ab initio large-scale simulations of MAS DNP enhancements. The Landau-Zener equation is used to treat all interactions concerning electron spins, and the low-order correlations in the Liouville space method is used to accurately treat the spin diffusion, as well as its MAS speed dependence. As the propagator cannot be stored, a Monte Carlo optimization method is used to determine the steady-state enhancement factors. This new software is employed to investigate the MAS speed dependence of the enhancement factors in large spin systems where spin diffusion is of importance, as well as to investigate the impacts of solvent and polarizing agent deuteration on the performance of MAS DNP.

SpinDynamica: Symbolic and numerical magnetic resonance in a Mathematica environment

SpinDynamica is a set of Mathematica packages for performing numerical and symbolic analysis of a wide range of magnetic resonance experiments and phenomena. An overview of the SpinDynamica architecture and functionality is given, with some simple representative examples.

The use of a selective saturation pulse to suppress t1 noise in two-dimensional (1)H fast magic angle spinning solid-state NMR spectroscopy

A selective saturation pulse at fast magic angle spinning (MAS) frequencies (60+kHz) suppresses t1 noise in the indirect dimension of two-dimensional (1)H MAS NMR spectra. The method is applied to a synthetic nucleoside with an intense methyl (1)H signal due to triisopropylsilyl (TIPS) protecting groups. Enhanced performance in terms of suppressing the methyl signal while minimising the loss of signal intensity of nearby resonances of interest relies on reducing spin diffusion--this is quantified by comparing two-dimensional (1)H NOESY-like spin diffusion spectra recorded at 30-70 kHz MAS. For a saturation pulse centred at the methyl resonance, the effect of changing the nutation frequency at different MAS frequencies as well as the effect of changing the pulse duration is investigated. By applying a pulse of duration 30 ms and nutation frequency 725 Hz at 70 kHz MAS, a good compromise of significant suppression of the methyl resonance combined with the signal intensity of resonances greater than 5 ppm away from the methyl resonance being largely unaffected is achieved. The effectiveness of using a selective saturation pulse is demonstrated for both homonuclear (1)H-(1)H double quantum (DQ)/single quantum (SQ) MAS and (14)N-(1)H heteronuclear multiple quantum coherence (HMQC) two-dimensional solid-state NMR experiments.

Simulating spin dynamics in organic solids under heteronuclear decoupling

Although considerable progress has been made in simulating the dynamics of multiple coupled nuclear spins, predicting the evolution of nuclear magnetisation in the presence of radio-frequency decoupling remains challenging. We use exact numerical simulations of the spin dynamics under simultaneous magic-angle spinning and RF decoupling to determine the extent to which numerical simulations can be used to predict the experimental performance of heteronuclear decoupling for the CW, TPPM and XiX sequences, using the methylene group of glycine as a model system. The signal decay times are shown to be strongly dependent on the largest spin order simulated. Unexpectedly large differences are observed between the dynamics with and without spin echoes. Qualitative trends are well reproduced by modestly sized spin system simulations, and the effects of finite spin-system size can, in favourable cases, be mitigated by extrapolation. Quantitative prediction of the behaviour in complex parameter spaces is found, however, to be very challenging, suggesting that there are significant limits to the role of numerical simulations in RF decoupling problems, even when specialist techniques, such as state-space restriction, are used.

Macroscopic nuclear spin diffusion constants of rotating polycrystalline solids from first-principles simulation

A method for quantitatively calculating nuclear spin diffusion constants directly from crystal structures is introduced. This approach uses the first-principles low-order correlations in Liouville space (LCL) method to simulate spin diffusion in a box, starting from atomic geometry and including both magic-angle spinning (MAS) and powder averaging. The LCL simulations are fit to the 3D diffusion equation to extract quantitative nuclear spin diffusion constants. We demonstrate this method for the case of (1)H spin diffusion in ice and L-histidine, obtaining diffusion constants that are consistent with literature values for (1)H spin diffusion in polymers and that follow the expected trends with respect to magic-angle spinning rate and the density of nuclear spins. In addition, we show that this method can be used to model (13)C spin diffusion in diamond and therefore has the potential to provide insight into applications such as the transport of polarization in non-protonated systems.

Quantum mechanical NMR simulation algorithm for protein-size spin systems

Nuclear magnetic resonance spectroscopy is one of the few remaining areas of physical chemistry for which polynomially scaling quantum mechanical simulation methods have not so far been available. In this communication we adapt the restricted state space approximation to protein NMR spectroscopy and illustrate its performance by simulating common 2D and 3D liquid state NMR experiments (including accurate description of relaxation processes using Bloch-Redfield-Wangsness theory) on isotopically enriched human ubiquitin - a protein containing over a thousand nuclear spins forming an irregular polycyclic three-dimensional coupling lattice. The algorithm uses careful tailoring of the density operator space to only include nuclear spin states that are populated to a significant extent. The reduced state space is generated by analysing spin connectivity and decoherence properties: rapidly relaxing states as well as correlations between topologically remote spins are dropped from the basis set.

Grid-free powder averages: on the applications of the Fokker-Planck equation to solid state NMR

We demonstrate that Fokker-Planck equations in which spatial coordinates are treated on the same conceptual level as spin coordinates yield a convenient formalism for treating magic angle spinning NMR experiments. In particular, time dependence disappears from the background Hamiltonian (sample spinning is treated as an interaction), spherical quadrature grids are avoided completely (coordinate distributions are a part of the formalism) and relaxation theory with any linear diffusion operator is easily adopted from the Stochastic Liouville Equation theory. The proposed formalism contains Floquet theory as a special case. The elimination of the spherical averaging grid comes at the cost of increased matrix dimensions, but we show that this can be mitigated by the use of state space restriction and tensor train techniques. It is also demonstrated that low correlation order basis sets apparently give accurate answers in powder-averaged MAS simulations, meaning that polynomially scaling simulation algorithms do exist for a large class of solid state NMR experiments.

Proton-driven spin diffusion in rotating solids via reversible and irreversible quantum dynamics

Proton-driven spin diffusion (PDSD) experiments in rotating solids have received a great deal of attention as a potential source of distance constraints in large biomolecules. However, the quantitative relationship between the molecular structure and observed spin diffusion has remained obscure due to the lack of an accurate theoretical description of the spin dynamics in these experiments. We start with presenting a detailed relaxation theory of PDSD in rotating solids that provides such a description. The theory applies to both conventional and radio-frequency-assisted PDSD experiments and extends to the non-Markovian regime to include such phenomena as rotational resonance (R(2)). The basic kinetic equation of the theory in the non-Markovian regime has the form of a memory function equation, with the role of the memory function played by the correlation function. The key assumption used in the derivation of this equation expresses the intuitive notion of the irreversible dissipation of coherences in macroscopic systems. Accurate expressions for the correlation functions and for the spin diffusion constants are given. The theory predicts that the spin diffusion constants governing the multi-site PDSD can be approximated by the constants observed in the two-site diffusion. Direct numerical simulations of PDSD dynamics via reversible Liouville-von Neumann equation are presented to support and compliment the theory. Remarkably, an exponential decay of the difference magnetization can be observed in such simulations in systems consisting of only 12 spins. This is a unique example of a real physical system whose typically macroscopic and apparently irreversible behavior can be traced via reversible microscopic dynamics. An accurate value for the spin diffusion constant can be usually obtained through direct simulations of PDSD in systems consisting of two (13)C nuclei and about ten (1)H nuclei from their nearest environment. Spin diffusion constants computed by this method are in excellent agreement with the spin diffusion constants obtained through equations given by the relaxation theory of PDSD. The constants resulting from these two approaches were also in excellent agreement with the results of 2D rotary resonance recoupling proton-driven spin diffusion (R(3)-PDSD) experiments performed in three model compounds, where magnetization exchange occurred over distances up to 4.9 Å. With the methodology presented, highly accurate internuclear distances can be extracted from such data. Relayed transfer of magnetization between distant nuclei appears to be the main (and apparently resolvable) source of uncertainty in such measurements. The non-Markovian kinetic equation was applied to the analysis of the R(2) spin dynamics. The conventional semi-phenomenological treatment of relxation in R(2) has been shown to be equivalent to the assumption of the Lorentzian spectral density function in the relaxatoin theory of PDSD. As this assumption is a poor approximation in real physical systems, the conventional R(2) treatment is likely to carry a significant model error that has not been recognized previously. The relaxation theory of PDSD appears to provide an accurate, parameter-free alternative. Predictions of this theory agreed well with the full quantum mechanical simulations of the R(2) dynamics in the few simple model systems we considered.

A first-principles description of proton-driven spin diffusion

Herein we design a reduced Liouville space for the simulation of proton-driven spin diffusion. Using this approach, the experimentally observed carbon-13 polarisation transfer in a powder sample undergoing magic-angle spinning is quantitatively described, directly from crystal geometry and without any adjustable parameters.

A master-equation approach to the description of proton-driven spin diffusion from crystal geometry using simulated zero-quantum lineshapes

Measurements of proton-driven carbon-13 spin diffusion (PDSD) by NMR spectroscopy are a central component of structural analyses of biomolecules in the solid-state. However, the quantitative link between experimental PDSD data and structural information is difficult to make. Here we observe that a master-equation approach can be used to model full PDSD dynamics accurately in polycrystalline (13)C-labelled L-histidine·HCl·H(2)O under magic-angle spinning. In the master-equation approach, PDSD rates and effective dipolar couplings are related by a function of the carbon-carbon zero-quantum lineshapes; we find that numerical simulations of the zero-quantum lineshapes are sufficiently accurate so as to allow the calculation of PDSD rates that are in good agreement with the measured rates, directly from crystal geometry and with no adjustable parameters. Finally, using carbon-carbon internuclear distances we illustrate the potential of the master-equation approach for structural studies. Generalisation of these results to proton-driven carbon-13 spin diffusion in more complex molecular systems is readily envisaged.