Refining siliceous zeolite framework structures with Si 2D -resolved NMR spectroscopy.

A modified shifted-echo PIETA pulse sequence is developed to acquire natural abundance Si 2D -resolved spectra in crystalline silicates. The sequence is applied to the highly siliceous zeolites Sigma-2 and ZSM-12. The 2D -resolved spectra are used to develop a silicate framework structure refinement strategy based on Si-O, O-O, and Si-Si distance restraints and analytical relationships between local structure and Si chemical shifts and geminal couplings.

MRSimulator: A cross-platform, object-oriented software package for rapid solid-state NMR spectral simulation and analysis.

The open-source Python package, MRSimulator, is presented as a simple-to-use, fast, versatile, and extendable package capable of simulating one- and higher-dimensional Nuclear Magnetic Resonance (NMR) spectra under static, magic-angle, and variable-angle conditions. High benchmarks in spectral simulations are achieved by assuming that there are no degeneracies in the energy eigenstates, i.e.

Simulating multipulse NMR spectra of polycrystalline solids in the frequency domain.

An approach is presented for simulating multipulse nuclear magnetic resonance (NMR) spectra of polycrystalline solids directly in the frequency domain. The approach integrates the symmetry pathway concept for multipulse NMR with efficient algorithms for calculating spinning sideband amplitudes and performing interpolated finite-element numerical integration over all crystallite orientations in a polycrystalline sample. The numerical efficiency is achieved through a set of assumptions used to approximate the evolution of a sparse density matrix through a pulse sequence as a set of individual transition pathway signals.

Rapid simulation of two-dimensional spectra with correlated anisotropic dimensions.

A new algorithm has been developed to simulate two-dimensional (2D) spectra with correlated anisotropic frequencies faster and more accurately than previous methods. The technique uses finite-element numerical integration on the sphere and an interpolation scheme based on the Alderman-Solum-Grant algorithm. This method is particularly useful for numerical calculations of joint probability distribution functions involving quantities with a parametric orientation dependence.

Statistical learning of NMR tensors from 2D isotropic/anisotropic correlation nuclear magnetic resonance spectra.

Many linear inversion problems involving Fredholm integrals of the first kind are frequently encountered in the field of magnetic resonance. One important application is the direct inversion of a solid-state nuclear magnetic resonance (NMR) spectrum containing multiple overlapping anisotropic subspectra to obtain a distribution of the tensor parameters. Because of the ill-conditioned nature of this inverse problem, we investigate the use of the truncated singular value decomposition and the smooth least absolute shrinkage and selection operator based regularization methods, which (a) stabilize the solution and (b) promote sparsity and smoothness in the solution.

Core Scientific Dataset Model: A lightweight and portable model and file format for multi-dimensional scientific data.

The Core Scientific Dataset (CSD) model with JavaScript Object Notation (JSON) serialization is presented as a lightweight, portable, and versatile standard for intra- and interdisciplinary scientific data exchange. This model supports datasets with a p-component dependent variable, {U0, …, Uq, …, Up-1}, discretely sampled at M unique points in a d-dimensional independent variable (X0, …, Xk, …, Xd-1) space. Moreover, this sampling is over an orthogonal grid, regular or rectilinear, where the principal coordinate axes of the grid are the independent variables.