Caracterización y cuantificación de soluciones acuosas utilizando espectros Raman.
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Date
2025
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Universidad de Concepción
Abstract
Esta memoria de título tiene por objetivo desarrollar un modelo cuantitativo para estimar la concentración de Cloruro de Sodio (NaCl) en soluciones acuosas a partir de espectros Raman, incorporando el análisis de variaciones estructurales del agua en función de la temperatura y la salinidad. El trabajo combina técnicas experimentales de espectroscopía Raman con métodos computacionales de procesamiento espectral y modelado estadístico multivariante.
Se emplearon soluciones acuosas de NaCl preparadas con concentraciones conocidas y medidas espectroscópicas realizadas con un láser de 532 nm. Los espectros fueron preprocesados mediante corrección de línea base, filtrado por transformada rápida de Fourier (FFT) y recorte espectral al intervalo 2800–3800 cm−1. Para caracterizar la banda O–H del agua, se aplicó un ajuste de tres funciones gaussianas, extrayendo nueve parámetros (posición, amplitud y ancho de cada pico) con significado físico-químico.
El modelado se realizó mediante regresión por mínimos cuadrados parciales (PLS por sus siglas en inglés Partial Least Squares), evaluando dos enfoques: uno basado en los espectros completos y otro utilizando los parámetros gaussianos. Los modelos fueron validados mediante métricas de error (RMSE, R2), validación cruzada y pruebas con datos externos. Los resultados muestran que los espectros Raman reflejan de forma sistemática los efectos del NaCl y la temperatura sobre la red de enlaces de hidrógeno del agua, y que el modelo basado en parámetros gaussianos logra una predicción robusta y explicable de la concentración salina.
This thesis aims to develop a quantitative model for estimating the concentration of NaCl in aqueous solutions using Raman spectroscopy, incorporating the analysis of water structural variations as a function of temperature and salinity. The work combines experimental Raman measurements with computational spectral processing and multivariate statistical modeling. Aqueous NaCl solutions with known concentrations were prepared and analyzed using a 532nm laser Raman system. The spectra were preprocessed through baseline correction, high-frequency noise reduction using Fast Fourier Transform (FFT), and truncation to the 2800–3800cm1 range. To characterize the broad O–H stretching band of water, each spectrum was fitted to a sum of three Gaussian functions, yielding nine physically meaningful parameters (peak position, width, and amplitude). Partial Least Squares (PLS) regression was used to build predictive models, comparing a full-spectrum approach against a reduced-variable model based on the Gaussian parameters. The models were validated using root mean square error (RMSE), coefficient of determination (R2), cross-validation, and independent test data. Results show that Raman spectra systematically capture the effects of NaCl and temperature on the hydrogen-bond network of water, and that the Gaussian-parameter-based model achieves robust and interpretable salt concentration predictions.
This thesis aims to develop a quantitative model for estimating the concentration of NaCl in aqueous solutions using Raman spectroscopy, incorporating the analysis of water structural variations as a function of temperature and salinity. The work combines experimental Raman measurements with computational spectral processing and multivariate statistical modeling. Aqueous NaCl solutions with known concentrations were prepared and analyzed using a 532nm laser Raman system. The spectra were preprocessed through baseline correction, high-frequency noise reduction using Fast Fourier Transform (FFT), and truncation to the 2800–3800cm1 range. To characterize the broad O–H stretching band of water, each spectrum was fitted to a sum of three Gaussian functions, yielding nine physically meaningful parameters (peak position, width, and amplitude). Partial Least Squares (PLS) regression was used to build predictive models, comparing a full-spectrum approach against a reduced-variable model based on the Gaussian parameters. The models were validated using root mean square error (RMSE), coefficient of determination (R2), cross-validation, and independent test data. Results show that Raman spectra systematically capture the effects of NaCl and temperature on the hydrogen-bond network of water, and that the Gaussian-parameter-based model achieves robust and interpretable salt concentration predictions.
Description
Tesis presentada para optar al título de Ingeniero/a Civil en Telecomunicaciones.
Keywords
Espectroscopía de Raman, Soluciones (Química), Análisis espectral