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Prediction of Refractive Index of Polymers Using Artificial Neural Networks

https://doi.org/10.1021/je100885f
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/int.20256openalex-snapshot
A neural network approach to prediction of glass transition temperature of polymers
inferredcites →https://doi.org/10.1007/s00396-009-2035-yopenalex-snapshot
Artificial neural network prediction of glass transition temperature of polymers
inferredcites →https://doi.org/10.1007/s00484-004-0247-xopenalex-snapshot
Artificial neural networks as a useful tool to predict the risk level of Betula pollen in the air
inferredcites →https://doi.org/10.1016/0306-4549(89)90016-9openalex-snapshot
Density-functional theory of atoms and molecules
inferredcites →https://doi.org/10.1016/j.neunet.2009.06.006openalex-snapshot
Evaluation of atmospheric Poaceae pollen concentration using a neural network applied to a coastal Atlantic climate region
inferredcites →https://doi.org/10.1016/j.polymer.2004.10.057openalex-snapshot
Prediction of refractive indices of linear polymers by a four-descriptor QSPR model
inferredcites →https://doi.org/10.1016/s1093-3263(01)00123-1openalex-snapshot
Beware of q2!
inferredcites →https://doi.org/10.1016/s1568-4946(02)00059-5openalex-snapshot
Application of neural networks in forecasting engine systems reliability
inferredcites →https://doi.org/10.1021/ci980087wopenalex-snapshot
Correlation and Prediction of the Refractive Indices of Polymers by QSPR
inferredcites →https://doi.org/10.1021/je1001973openalex-snapshot
Prediction of Ethene + Oct-1-ene Copolymerization Ideal Conditions Using Artificial Neuron Networks
inferredcites →https://doi.org/10.1021/jp012360uopenalex-snapshot
Prediction of Indices of Refraction and Glass Transition Temperatures of Linear Polymers by Using Graph Theoretical Indices
inferredcites →https://doi.org/10.1021/jp960976ropenalex-snapshot
Harmonic Vibrational Frequencies: An Evaluation of Hartree−Fock, Møller−Plesset, Quadratic Configuration Interaction, Density Functional Theory, and Semiempirical Scale Factors
inferredcites →https://doi.org/10.1037/h0042519openalex-snapshot
The perceptron: A probabilistic model for information storage and organization in the brain.
inferredcites →https://doi.org/10.1039/c0em00248hopenalex-snapshot
The use of artificial neural networks to forecast biological atmospheric allergens or pathogens only as Alternaria spores
inferredcites →https://doi.org/10.1063/1.464906openalex-snapshot
The performance of a family of density functional methods
inferredcites →https://doi.org/10.1063/1.464913openalex-snapshot
Density-functional thermochemistry. III. The role of exact exchange
inferredcites →https://doi.org/10.1093/oso/9780198538493.001.0001openalex-snapshot
Neural Networks for Pattern Recognition
inferredcites →https://doi.org/10.1103/physrevb.37.785openalex-snapshot
Development of the Colle-Salvetti correlation-energy formula into a functional of the electron density
inferredcites →https://doi.org/10.1146/annurev.physchem.49.1.569openalex-snapshot
INTERFACES AND THIN FILMS AS SEEN BY BOUND ELECTROMAGNETIC WAVES
inferredcites →https://doi.org/10.1198/00401700152404282openalex-snapshot
Some Applications of Functional Networks in Statistics and Engineering
inferredcites →https://doi.org/10.1201/9780203910115openalex-snapshot
Prediction of Polymer Properties
inferredcites →https://doi.org/10.7551/mitpress/5236.001.0001openalex-snapshot
Parallel Distributed Processing

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1007/978-3-031-78724-9_4openalex-snapshot
Applications of Predictive Modeling for Selected Properties of Polymers
inferred← citeshttps://doi.org/10.1016/b978-0-443-40453-5.00013-7openalex-snapshot
Polymer refractive index
inferred← citeshttps://doi.org/10.1016/j.chemolab.2014.11.008openalex-snapshot
QSPR studies on refractive indices of structurally heterogeneous polymers
inferred← citeshttps://doi.org/10.1016/j.commatsci.2017.05.022openalex-snapshot
Refractive indices of diverse data set of polymers: A computational QSPR based study
inferred← citeshttps://doi.org/10.1016/j.commatsci.2021.110460openalex-snapshot
Polymer informatics: Expert-in-the-loop in QSPR modeling of refractive index
inferred← citeshttps://doi.org/10.1016/j.jtice.2015.02.003openalex-snapshot
Prediction of refractive indices of ionic liquids – A quantitative structure-property relationship based model
inferred← citeshttps://doi.org/10.1016/j.molliq.2014.11.005openalex-snapshot
A group contribution method for estimating the refractive indices of ionic liquids
inferred← citeshttps://doi.org/10.1016/j.mtcomm.2023.105823openalex-snapshot
The reliable predicting refractive index for diverse polymers only from structural moieties in repeating unit structures
inferred← citeshttps://doi.org/10.1021/acs.jpca.2c07955openalex-snapshot
Machine Learning Identification of Organic Compounds Using Visible Light
inferred← citeshttps://doi.org/10.1021/acsomega.8b01834openalex-snapshot
QSPR Modeling of the Refractive Index for Diverse Polymers Using 2D Descriptors
inferred← citeshttps://doi.org/10.1039/c0em00478bopenalex-snapshot
Multilayer perceptron neural network for flow prediction
inferred← citeshttps://doi.org/10.3390/polym10010103openalex-snapshot
Designing High-Refractive Index Polymers Using Materials Informatics
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