Cargando…

Quantitative Structural Description of Zeolites by Machine Learning Analysis of Infrared Spectra

[Image: see text] Application of machine learning (ML) algorithms to spectroscopic data has a great potential for obtaining hidden correlations between structural information and spectral features. Here, we apply ML algorithms to theoretically simulated infrared (IR) spectra to establish the structu...

Descripción completa

Detalles Bibliográficos
Autores principales:	Skorynina, Alina A., Protsenko, Bogdan O., Usoltsev, Oleg A., Guda, Sergey A., Bugaev, Aram L.
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	American Chemical Society 2023
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10155178/ https://www.ncbi.nlm.nih.gov/pubmed/37058157 http://dx.doi.org/10.1021/acs.inorgchem.2c04395

Ejemplares similares

Dehydrogenation of Ethylene on Supported Palladium Nanoparticles: A Double View from Metal and Hydrocarbon Sides
por: Usoltsev, Oleg A., et al.
Publicado: (2020)

In situ X-ray absorption spectroscopy data during formation of active Pt- and Pd-sites in functionalized UiO-67 metal-organic frameworks
por: Bugaev, Aram L., et al.
Publicado: (2019)

Machine learning molecular dynamics for the simulation of infrared spectra
por: Gastegger, Michael, et al.
Publicado: (2017)

Operando X-ray absorption spectra and mass spectrometry data during hydrogenation of ethylene over palladium nanoparticles
por: Bugaev, Aram L., et al.
Publicado: (2019)

Use of Machine Learning and Infrared Spectra for Rheological Characterization and Application to the Apricot
por: Cadet, Xavier F., et al.
Publicado: (2019)

Machine learning applied to near-infrared spectra for clinical pleural effusion classification
por: Chen, Zhongjian, et al.
Publicado: (2021)

Theoretical Infrared Spectra: Quantitative Similarity Measures and Force Fields
por: Henschel, Henning, et al.
Publicado: (2020)

Evolution of the active species of homogeneous Ru hydrodeoxygenation catalysts in ionic liquids
por: Janssens, K., et al.
Publicado: (2022)

Prediction of Neonatal Respiratory Distress Biomarker Concentration by Application of Machine Learning to Mid-Infrared Spectra
por: Ahmed, Waseem, et al.
Publicado: (2022)

Omega, J/psi and psi' Transverse Mass Spectra at RHIC
por: Bugaev, K A, et al.
Publicado: (2002)

Fusion of Mid-Wave Infrared and Long-Wave Infrared Reflectance Spectra for Quantitative Analysis of Minerals
por: Desta, Feven, et al.
Publicado: (2020)

Infrared Spectra of Asphalts
por: Beitchman, Burton D.
Publicado: (1959)

Machine learning potential era of zeolite simulation
por: Ma, Sicong, et al.
Publicado: (2022)

Vibrational Spectra of Zeolite Y as a Function of Ion Exchange
por: Król, Magdalena, et al.
Publicado: (2021)

Using transfer learning and dimensionality reduction techniques to improve generalisability of machine-learning predictions of mosquito ages from mid-infrared spectra
por: Mwanga, Emmanuel P., et al.
Publicado: (2023)

Rapid Discrimination of Neuromyelitis Optica Spectrum Disorder and Multiple Sclerosis Using Machine Learning on Infrared Spectra of Sera
por: El Khoury, Youssef, et al.
Publicado: (2022)

Determining soil particle-size distribution from infrared spectra using machine learning predictions: Methodology and modeling
por: Parent, Elizabeth Jeanne, et al.
Publicado: (2021)

Estimation of Soluble Solids for Stone Fruit Varieties Based on Near-Infrared Spectra Using Machine Learning Techniques
por: Escárate, Pedro, et al.
Publicado: (2022)

Machine-learning approach to the design of OSDAs for zeolite beta
por: Daeyaert, Frits, et al.
Publicado: (2019)

Machine learning-assisted crystal engineering of a zeolite
por: Li, Xinyu, et al.
Publicado: (2023)

Quantitative Analysis of Gas Phase IR Spectra Based on Extreme Learning Machine Regression Model
por: Ouyang, Tinghui, et al.
Publicado: (2019)

Adsorption Sites on Pd Nanoparticles Unraveled by Machine-Learning Potential with Adaptive Sampling
por: Tereshchenko, Andrei, et al.
Publicado: (2022)

Correction: Determining soil particle-size distribution from infrared spectra using machine learning predictions: Methodology and modeling
por: Jeanne Parent, Elizabeth, et al.
Publicado: (2022)

Feature Point Descriptors: Infrared and Visible Spectra
por: Ricaurte, Pablo, et al.
Publicado: (2014)

Infrared Absorption Spectra of Steroids (an Atlas)
por: Dorfman, Ralph I.
Publicado: (1954)

Rotational structure in molecular infrared spectra
por: di Lauro, Carlo
Publicado: (2013)

The theoretical description of nuclear spectra
por: Mottelson, Benjamin Roy
Publicado: (1958)

Classification of the Residues after High and Low Order Explosions Using Machine Learning Techniques on Fourier Transform Infrared (FTIR) Spectra
por: Banas, Agnieszka M., et al.
Publicado: (2023)

Rapid and Accurate Authentication of Porcini Mushroom Species Using Fourier Transform Near-Infrared Spectra Combined with Machine Learning and Chemometrics
por: Liu, Hong, et al.
Publicado: (2023)

Catalytic tandem dehydrochlorination–hydrogenation of PVC towards valorisation of chlorinated plastic waste
por: O'Rourke, Galahad, et al.
Publicado: (2023)

Applying machine learning methods for the analysis of two-dimensional mass spectra
por: Gao, Z., et al.
Publicado: (2023)

Handbook of Fourier transform raman and infrared spectra of polymers
por: Kuptsov, A H, et al.
Publicado: (1998)

Coarse-grained versus fully atomistic machine learning for zeolitic imidazolate frameworks
por: Faure Beaulieu, Zoé, et al.
Publicado: (2023)

Machine Learning Analysis of Raman Spectra of MoS(2)
por: Mao, Yu, et al.
Publicado: (2020)

Machine learning of solvent effects on molecular spectra and reactions
por: Gastegger, Michael, et al.
Publicado: (2021)

Machine learning of optical properties of materials – predicting spectra from images and images from spectra
por: Stein, Helge S., et al.
Publicado: (2018)

Synthesis of Novel Perfluoroalkylglucosides on Zeolite and Non-Zeolite Catalysts
por: Nowicki, Janusz, et al.
Publicado: (2015)

Deep Reinforcement Learning Environment Approach Based on Nanocatalyst XAS Diagnostics Graphic Formalization
por: Polyanichenko, Dmitry S., et al.
Publicado: (2023)

Quantitative Detection of the Disappearance of the Antioxidant Ability of Catechin by Near-Infrared Absorption and Near-Infrared Photoluminescence Spectra of Single-Walled Carbon Nanotubes
por: Umemura, Kazuo, et al.
Publicado: (2019)

A factorization method for the classification of infrared spectra
por: Henneges, Carsten, et al.
Publicado: (2010)

Cannot write session to /tmp/vufind_sessions/sess_gtuc201c399ubmd330aa5dpi67