Completely Computational Model Setup for Spectroscopic Techniques: The Ab Initio Molecular Dynamics Indirect Hard Modeling Approach

Abstract

The spectroscopic quantification of mixture compositions usually requires pure compounds and mixtures of known compositions for calibration. Since they are not always available, methods to fill such gaps have evolved, which are, however, not generally applicable. Therefore, calibration can be extremely challenging, especially when multiple unstable species, for example, intermediates, exist in a system. This study presents a new calibration approach that uses ab initio molecular dynamics (AIMD)-simulated spectra to set up and calibrate models for the physics-based spectral analysis method indirect hard modeling (IHM). To demonstrate our approach called AIMD–IHM, we analyze Raman spectra of ternary hydrogen-bonding mixtures of acetone, methanol, and ethanol. The derived AIMD–IHM pure-component models and calibration coefficients are in good agreement with conventionally generated experimental results. The method yields compositions with prediction errors of less than 5% without any experimental calibration input. Our approach can be extended, in principle, to infrared and NMR spectroscopy and allows for the analysis of systems that were hitherto inaccessible to quantitative spectroscopic analysis.

Emerging Atomistic Modeling Methods for Heterogeneous Electrocatalysis

“…While several types of spectroscopies are widely used within the experimental electrocatalysis community, − the use of theoretical methods to predict spectra (i.e., computational spectroscopy) remains less common in the field. Interpretation of experimental spectroscopic data is often convoluted by solvent effects, polarization due to electric fields, changes due to the potential and the pH, the presence of counterions, and restructuring of the catalyst surface under reaction conditions.…”

Adaptive Kalman Filter for On-Line Spectroscopic Sensor Corrections

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