Using PLS, iPLS and siPLS linear regressions to determine the composition of LDPE/HDPE blends: A comparison between confocal Raman and ATR-FTIR spectroscopies

Silva, Daniel José da; Wiebeck, Hélio

doi:10.1016/j.vibspec.2017.08.009

Cited by 51 publications

(18 citation statements)

References 49 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The Raman spectra of LDPE and HDPE are very similar, but it was observed that the maximum intensity of the Raman band at 1460 cm -1 increases with the reduction of LDPE in the polymer blend, while the opposite behavior is observed for the Raman shifts at 1370 and 1416 cm -1 . These spectral characteristics are the basis for operation of the multivariate calibration to quantify the composition of the LDPE/HDPE blends using confocal Raman spectra data [20] . Table 2 presents the optimal predictive models built by the CARS-PLS algorithm using several statistical pretreatment methods for the Raman data (the number of latent variables for cross-validation, type of cross-validation and number of runs were maintained constant, as described in the table label).…”

Section: Resultsmentioning

confidence: 99%

“…All CARS-PLS-based models presented more significant prediction performance with the interval containing the Raman shift at 2883 cm -1 (both amorphous and crystalline polyethylene phases) and 1445 cm -1 (only from the PE crystalline phase). In a previous work with Interval PLS linear regression [20] , we identified that the Raman signal at 2845 cm -1 , which regards the CH 2 asymmetric stretching in amorphous and crystalline phases, enables to obtain prediction models with the smallest RMSEP values (2.68-6.94 wt% of LDPE). The most plausible justification is associated to the intensity and width of Raman shifts (1370, 1416 and 1460 cm -1 ), which are not just related to the content of the polymer chemical groups, but also to the macromolecular organization of the polymeric chains.…”

Section: Modelmentioning

confidence: 97%

“…The fitting degree between the predicted results and reference values was obtained by the correlation coefficient (R) [20] :…”

Section: Cars-pls Regression Analysismentioning

confidence: 99%

See 2 more Smart Citations

Predicting LDPE/HDPE blend composition by CARS-PLS regression and confocal Raman spectroscopy

Silva

Wiebeck

2019

Polímeros

Self Cite

View full text Add to dashboard Cite

Industries and the scientific community currently focus on creating new ways to recycle and to reuse polymer waste that leads to serious socio-environmental risks. However, the quality of recycled polyethylenes depends strongly on their purity degree, but the distinction between Low Density Polyethylene (LDPE) and High Density Polyethylene (HDPE) by a fast and consistently good methodology is still an unsolved issue for the current recycling processes. In this study, confocal Raman spectroscopy and Competitive Adaptive Reweighted Sampling-Partial Least Squares (CARS-PLS) linear regression have been successfully applied to quantify the concentration of LDPE/HDPE blends. The effects of several regression parameters (pretreatment method, Monte Carlo sampling runs, k-fold and maximal number of latent variables for cross-validation) on the CARS-PLS model training and prediction performance were analyzed. The CARS-PLS-based models show root-mean-squared prediction error of 4.06-8.87 wt% of LDPE for the whole composition range of HDPE/LDPE blend.

show abstract

Section: Resultsmentioning

confidence: 99%

Section: Modelmentioning

confidence: 97%

See 1 more Smart Citation

Predicting LDPE/HDPE blend composition by CARS-PLS regression and confocal Raman spectroscopy

Silva

Wiebeck

2019

Polímeros

Self Cite

View full text Add to dashboard Cite

show abstract

“…19,20 The peak at 2969 cm -1 in both pure drug and formulations indicates the symmetric stretching of CH 2 . 21 In the formulations, the intensity of the peaks has decreased along with the increase of TiO 2 concentration which indicated a possible binding of TiO 2 and Acceclofenc.…”

Section: Ftir Studymentioning

confidence: 92%

Quantitative Estimation of Tabletability of Aceclofenac after Incorporation of Titanium Dioxide using Area under the Curve

Nandi¹,

Mishra²,

Sahoo³

et al. 2019

IJPER

View full text Add to dashboard Cite

Background: Tablet manufacturing with direct compression is one of the leading industrial technique that consumes less time, labour and economic also. But the choice of excipients are critical in this case which will allow the drug to get compressed without granulation techniques. Purpose: Aceclofenac is a BCS class II non-steroidal anti-inflammatory drug, which exerts a low oral bioavailability because of low solubility in aqueous medium. The drug also suffers from compressibility and also shows poor tabletibility. Methods: We have attempted to improve tabletability by incorporating titanium dioxide (TiO 2) through kneading and solvent evaporation technique. Results: In the FTIR study revealed that NH and Cl aromatic stretching of aceclofenac has been affected significantly due to binding with TiO 2. DSC thermogram ascertained the partial amorphization of the drug in the formulations. Evaluated tabletability from the area under the applied pressure vs tensile strength curve (AUTC) of A1T1 has shown a poor value in contrast to other formulations.

show abstract

“…The synergy interval partial least squares (siPLS) regression permits the assembly and combination of spectral equidistant intervals to obtain regressions that generally provide more robust prediction models with lower errors for root‐mean‐square deviation of cross validation (RMSDCV) and root‐mean‐square estimation deviation (RMSED) (da Silva & Wiebeck, ). The siPLS model was evaluated based on stoichiometric indicators.…”

Section: Methodsmentioning

confidence: 99%

Rapid detection model of Bacillus subtilis in solid‐state fermentation of rapeseed meal

Zheng

Jiang

et al. 2019

Journal of Food Safety

View full text Add to dashboard Cite

The main objective of this research was to monitor variety in the content of Bacillus subtilis 10160 during solid‐state fermentation (SSF) of rapeseed meal by near infrared (NIR) spectroscopy and chemometrics. Observations showed the coefficient of determination (R2) value was 0.9401 and root‐mean‐square deviation was 0.639 log (CFU/g) for viable cell content by synergies between four intervals 5,203.003–5,600.267, 5,604.124–6,001.388, 6,807.487–7,204.751 and 8,411.972–8,809.235 cm−1. The determination coefficient of prediction (Rp2) and root‐mean‐square deviation of prediction in an external validation set could reach 0.9532 and 0.628 log (CFU/g) by the viable B. subtilis model. These findings suggest that rapid detection of B. subtilis in SSF is achieved by the combination of synergy interval partial least squares and NIR spectroscopy.

show abstract

Using PLS, iPLS and siPLS linear regressions to determine the composition of LDPE/HDPE blends: A comparison between confocal Raman and ATR-FTIR spectroscopies

Cited by 51 publications

References 49 publications

Predicting LDPE/HDPE blend composition by CARS-PLS regression and confocal Raman spectroscopy

Predicting LDPE/HDPE blend composition by CARS-PLS regression and confocal Raman spectroscopy

Quantitative Estimation of Tabletability of Aceclofenac after Incorporation of Titanium Dioxide using Area under the Curve

Rapid detection model of Bacillus subtilis in solid‐state fermentation of rapeseed meal

Contact Info

Product

Resources

About