NMR and IR Spectroscopy for the Structural Characterization of Edible Fats and Oils. An Instrumental Analysis Laboratory

Crowther, Molly W.

doi:10.1021/ed085p1550

Cited by 12 publications

(15 citation statements)

References 6 publications

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“…Consequently, there has been a growing interest in employing spectroscopic techniques that do not require derivatization, yet provide results comparable to those obtained with GC. Spectroscopic characterization of oils by IR, − NIR, , Raman, , and NMR ,,,− methods has been reported. Because the spectroscopic signatures of many oils are quite similar, spectral data analysis often requires a multivariate statistical approach. − ,,− Recently, 1 H NMR spectroscopy has been used to characterize olive oils ,,, because NMR spectroscopy does not require sample pretreatment and offers a relatively large amount of information in a single spectrum …”

Section: Introductionmentioning

confidence: 99%

Identification of Edible Oils by Principal Component Analysis of ¹H NMR Spectra

2017

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Principal component analysis (PCA) is a statistical method widely used in chemometric studies to analyze large, correlated sets of data. An undergraduate laboratory experiment involving PCA of 1H NMR spectral data is described. Students collect NMR spectra of an unknown oil sample, are provided with spectra of six oil standards (canola, corn, olive, peanut, sesame, and sunflower oil), and are asked to identify the unknown oil using score plots based on the PCA results. This laboratory experiment gives students hands-on experience collecting NMR spectra, performing NMR spectral processing, and utilizing freely available, web-based software to subject the data to PCA and to prepare the subsequent scoring plots.

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Section: Introductionmentioning

confidence: 99%

Identification of Edible Oils by Principal Component Analysis of ¹H NMR Spectra

2017

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“…For example, 1 H NMR spectroscopy has a higher signal to noise ratio owing to the significantly larger abundance of spin-active isotope. Infrared spectroscopy sheds light on the vibrational transitions in a molecule and is considered to be complementary to NMR spectroscopy (Paulsen 2015) (Crowther 2008). A promising extension of work presented in this manuscript would be to incorporate other spectral data and leverage different kinds of information to elucidate the correct structure of an unknown molecule.…”

Section: Discussionmentioning

confidence: 99%

Spectra to Structure: Deep Reinforcement Learning for Molecular Inverse Problem

Sridharan

Mehta

Pathak

2021

Preprint

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Spectroscopy is the study of how matter interacts with electromagnetic radiations of specific frequencies that has led to several monumental discoveries in science. The spectra of any particular molecule is highly information-rich, yet the inverse relation from the spectra to the molecular structure is still an unsolved problem. Nuclear Magnetic Resonance (NMR) spectroscopy is one such critical tool in the tool-set for scientists to characterise any chemical sample. In this work, a novel framework is proposed that attempts to solve this inverse problem by navigating the chemical space to find the correct structure that resulted in the target spectra. The proposed framework uses a combination of online Monte- Carlo-Tree-Search (MCTS) and a set of offline trained Graph Convolution Networks to build a molecule iteratively from scratch. Our method is able to predict the correct structure of the molecule ∼80% of the time in its top 3 guesses. We believe that the proposed framework is a significant step in solving the inverse design problem of NMR spectra to molecule.

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“…Existem descrições de produção de biodiesel empregando óleo de coco, 18 mas nenhuma que execute a produção do óleo em aula de química orgânica. Para a obtenção do óleo do coco no contexto da aula experimental, desenvolvemos um procedimento diferente do tradicionalmente ensinado nos cursos práticos, onde a extração por partição sólido-líquido com solvente apolar é o princípio empregado.…”

Section: Produção Do óLeo De Cocounclassified

“…A maioria dessas propostas didáticas emprega RMN para esta caracterização, algumas associam RMN e IV, e poucas usam exclusivamente o IV. 5,6,8,18,20 Na proposta dos nossos trabalhos de transposição didática para desenvolver experimentos sustentáveis de química orgânica, é crucial que a execução seja possível em diferentes contextos de infraestrutura de ensino experimental, com materiais de fácil acesso e que contemplem a existência de mínimo parque instrumental, mas ainda proporcione o máximo valor pedagógico. Assim, empregamos aqui correlações entre IV e RMN, de forma que nos locais onde o acesso a RMN para aulas de graduação seja limitado se possa, empregando IV, chegar às mesmas conclusões.…”

Section: Análise Espectral Comparativa Dos óLeos E Biodieseisunclassified