For the majority of users conducting nuclear magnetic resonance (NMR) spectroscopy today, sample preparation follows a similar path: isolate a compound or compounds from a reaction mixture (or if ...

It’s an open secret that organic chemistry students struggle to learn a skill that is integral to the field: interpreting nuclear magnetic resonance spectra. Organic chemists use this important tool ...

Resonance” is right there in the name of nuclear magnetic resonance spectroscopy, but the technique doesn’t make most chemists think of music. Ayyalusamy Ramamoorthy, a biophysical chemist at the ...

NMR spectroscopy is a powerful technique that is ideally suited to the characterization and analysis of a diverse array of chemical compounds. Unlike many other analytical techniques, NMR spectroscopy ...

In this interview, Data Scientist Federico Paruzzo discusses how Bruker has used deep learning to develop sigreg, the first machine-learning-based command available in Bruker’s TopSpin software.

NMR spectroscopy is an analytical technique commonly used in academia and industry, and is a critical part of today’s food, chemistry, biochemistry, and pharmaceuticals research. NMR facilitates the ...

Scientists have developed a method using machine learning to better analyze data from a powerful scientific tool: nuclear magnetic resonance (NMR). One way NMR data can be used is to understand ...

Researchers have developed an economical random fractional 13C labeling strategy using methanol for eukaryotic membrane proteins expressed in yeast. This method significantly improves spectral ...

Designated April 26, 2011, at Stony Brook University in Stony Brook, New York, and April 8, 2011, at Agilent Technologies in Santa Clara, California. MRI (magnetic resonance imaging) has become a ...

Nuclear magnetic resonance spectroscopy is still a widely used tool to determine the unique spectra of molecules of interest. For chemists who want a quick way to assess the probable spectra of a ...