Analytical Instrument Documents

CT only undergoes second-order quadrupolar perturbation and the signal is distributed over a narrower range than ST. ST signals are broad, have lower sensitivity, and often exhibit more complex patterns. Therefore, in the case of half-integer quadrupolar nuclei, CT signals are mostly observed and analyzed.

In solid-state NMR, interactions such as dipolar couplings and chemical shift anisotropy often result in extremely broad and low-sensitivity spectra in the stationary state. To address this issue, the sample is tilted at an angle of 54.74 degrees relative to the magnetic field and spun rapidly, creating a state similar to that of a solution. This technique, called MAS (Magic Angle Spinning), improves both resolution and sensitivity.

This Polymer note introduces a broad range of instruments used for polymer analysis and their applications.

Contamination and Off-Flavor; Evaluation and Analysis

Quick and accurate quantitative analysis is possible without using a reference material that is the same as the target analyte.

This Solid-state battery Note has been created to provide solutions and reference information for research and development of solid-state batteries evolving from the lithium ion batteries (LIBs).

Chenometrics is a discipline that utilizes data mining techniques, including dimensionality reduction, discrimination, visualization, and regression, to extract information from extensive sets of experimental analytical data. NMR spectroscopy, a highly quantitative and reproducible technique, allows for non-invasive analysis of chemical species with minimal sample preparation. This is particularly advantageous for data mining, as NMR spectra, including series of 1H NMR spectra of biological samples, are commonly employed as input for multivariate analysis by converting series of 1D NMR spectra into a matrix. The 'Chemospec' package in the R language for statistical computing serves as the engine for multivariate analysis. When the 'Chempspec' package is installed, the Delta software offers a seamless user interface for exploratory multivariate analysis.

Pulsed-Field Gradient Nuclear Magnetic Resonance (PFG-NMR) is utilized to analyze the self-diffusion of molecules and ions. The self-diffusion coefficient (D) in PFG-NMR is determined by recording the decay of signal intensity through a series of experiments using either Pulsed Gradient Spin Echo (PGSE) or Pulsed Gradient Stimulated Echo (PGSTE) sequences with varying gradient strengths (G). The decay of signal intensity is subsequently analyzed using curve fitting or inverse Laplace transformation methods. The Delta NMR software provides a curve analysis tool that supports the fitting of PFG-NMR data. Versions 5.3.3 and earlier of the Delta NMR software support curve fitting using a model that assumes a single self-diffusion coefficient contributing to the decay. However, starting from the Delta NMR software version 6.0 and onwards, there is support for curve fitting using the "Diffusion Analysis Multi" feature. This feature enables the analysis to account for multiple self-diffusion coefficients during the curve fitting process.

Pulsed-Field Gradient NMR (PFG-NMR) is utilized for analyzing the self-diffusion of molecules and ions, which are commonly referred to as 'particles' in this context. The translation of particles by thermal convection significantly impacts the decay curve in PFG-NMR experiments, particularly when dealing with solution and liquid samples. In cases where the convection-induced translation is substantial, the decay curve exhibits a cosine-like behavior, leading to an apparent increase in the self-diffusion coefficient compared to the actual value. Additionally, the decay curves may become distorted, occasionally resulting in the appearance of signals in negative phase. To address this convection artifact in PFG-NMR, Double Stimulated Echo (DSTE) experiments are specifically designed and employed.

Engineering Transition Metal Layers for Long Lasting Anionic Redox in Layered Sodium Manganese Oxide