RESUMO
There is an increasing focus on the part of academic institutions, funding agencies, and publishers, if not researchers themselves, on preservation and sharing of research data. Motivations for sharing include research integrity, replicability, and reuse. One of the barriers to publishing data is the extra work involved in preparing data for publication once a journal article and its supporting information have been completed. In this work, a method is described to generate both human and machine-readable supporting information directly from the primary instrumental data files and to generate the metadata to ensure it is published in accordance with findable, accessible, interoperable, and reusable (FAIR) guidelines. Using this approach, both the human readable supporting information and the primary (raw) data can be submitted simultaneously with little extra effort. Although traditionally the data package would be sent to a journal publisher for publication alongside the article, the data package could also be published independently in an institutional FAIR data repository. Workflows are described that store the data packages and generate metadata appropriate for such a repository. The methods both to generate and to publish the data packages have been implemented for NMR data, but the concept is extensible to other types of spectroscopic data as well.
RESUMO
Quantitative (1)H NMR (qNMR) is a widely applied technique for compound concentration and purity determinations. The NMR spectrum will display signals from all species in the sample, and this is generally a strength of the method. The key spectral determination is the full and accurate determination of one or more signal areas. Accurate peak integration can be an issue when unrelated peaks resonate in an important integral region. We describe a "hybrid" approach to signal integration that provides an accurate estimation of signal area, removing the component(s) that may arise from unrelated peaks. This is achieved by using the most accurate integration method for the region and removing unwanted contributions. The key to this performing well, and in almost all cases, is the use of areas from deconvolved peaks. We describe this process and show that it can be very successfully applied to cases where the highest precision is required and for more common cases of NMR-based quantitation.
RESUMO
Touch-screen computers are emerging as a popular platform for many applications, including those in chemistry and analytical sciences. In this work, we present our implementation of a new NMR 'app' designed for hand-held and portable touch-controlled devices, such as smartphones and tablets. It features a flexible architecture formed by a powerful NMR processing and analysis kernel and an intuitive user interface that makes full use of the smart devices haptic capabilities. Routine 1D and 2D NMR spectra acquired in most NMR instruments can be processed in a fully unattended way. More advanced experiments such as non-uniform sampled NMR spectra are also supported through a very efficient parallelized Modified Iterative Soft Thresholding algorithm. Specific technical development features as well as the overall feasibility of using NMR software apps will also be discussed. All aspects considered the functionalities of the app allowing it to work as a stand-alone tool or as a 'companion' to more advanced desktop applications such as Mnova NMR.
