Broadband ultrafast 2D NMR spectroscopy for online monitoring in continuous flow.

Flow NMR is a powerful tool to monitor chemical reactions under realistic conditions. Here, we describe ultrafast (UF) 2D NMR schemes that make it possible to acquire broadband homonuclear 2D NMR spectra in 90 seconds or less for a continuously flowing sample. An interleaved acquisition strategy is used to address the spectral width limitation of UF 2D NMR.

In-line Multidimensional NMR Monitoring of Photochemical Flow Reactions.

This work demonstrates the in-line monitoring of a flow photochemical reaction using 1D and ultrafast 2D NMR methods at high magnetic field. The reaction mixture exiting the flow reactor is flown through the NMR spectrometer and directly analyzed. In the case of simple substrates, suitable information can be obtained through 1D H spectra, but for molecules of higher complexity the use of 2D experiments is key to address signal overlaps and assignment issues.

Ultrafast 2D NMR for the analysis of complex mixtures.

2D NMR is extensively used in many different fields, and its potential for the study of complex biochemical or chemical mixtures has been widely demonstrated. 2D NMR gives the ability to resolve peaks that overlap in 1D spectra, while providing both structural and quantitative information. However, complex mixtures are often analysed in situations where the data acquisition time is a crucial limitation, due to an ongoing chemical reaction or a moving sample from a hyphenated technique, or to the high-throughput requirement associated with large sample collections.

EMG Data Augmentation for Grasp Classification Using Generative Adversarial Networks.

Electromyography (EMG) has been used as an interface for the control of robotic hands for decades but with the improvement of embedded electronics and decoding algorithms, many applications are now envisaged by companies. Deep learning has shown the possibility to increase decoding performance but it requires large amounts of data to show its full capabilities. However, recording such amounts of EMG signals face several issues since recording hours of data from patients is very time-consuming and can result in muscle fatigue.