logo
ResearchBunny Logo
Beyond traditional magnetic resonance processing with artificial intelligence

Chemistry

Beyond traditional magnetic resonance processing with artificial intelligence

A. Jahangiri and V. Orekhov

This study by Amir Jahangiri and Vladislav Orekhov reveals how artificial intelligence can transform NMR spectroscopy by tackling previously unsolvable challenges. AI-driven neural networks have achieved breakthroughs in quadrature detection, quantifying signal intensity uncertainty, and creating a reference-free quality score for NMR spectra.

00:00
00:00
~3 min • Beginner • English
Abstract
Smart signal processing approaches using Artificial Intelligence are gaining momentum in NMR applications. In this study, we demonstrate that AI offers new opportunities beyond tasks addressed by traditional techniques. We developed and trained artificial neural networks to solve three problems that until now were deemed “impossible”: quadrature detection using only Echo (or Anti-Echo) modulation from the traditional Echo/Anti-Echo scheme; accessing uncertainty of signal intensity at each point in a spectrum processed by any given method; and defining a reference-free score for quantitative access of NMR spectrum quality. Our findings highlight the potential of AI techniques to revolutionize NMR processing and analysis.
Publisher
Communications Chemistry
Published On
Oct 27, 2024
Authors
Amir Jahangiri, Vladislav Orekhov
Tags
artificial intelligence
NMR spectroscopy
neural networks
signal intensity
quadrature detection
spectral quality score
Listen, Learn & Level Up
Over 10,000 hours of research content in 25+ fields, available in 12+ languages.
No more digging through PDFs, just hit play and absorb the world's latest research in your language, on your time.
listen to research audio papers with researchbunny