# Trying to meaningfully deconvolute IR absorption spectra

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• Guilherme Franco
In summary, the conversation discusses preparing BCNO phosphor samples and using IR absorption data to find the optimal B/N mass fraction for a certain preparation condition. The speaker is manually deconvoluting the data using gaussian peaks and questioning the interpretation of the broader peaks in the "base" that they created. They are wondering if they can disregard the "base" and only consider the narrow peaks for quantifying the amount of bonds present.
Guilherme Franco
TL;DR Summary
I'm trying to deconvolute IR absorption spectra and find (or at least get some idea) of the relative proportion of (known) bonds in samples
Hi

I'm preparing some BCNO phosphor samples. Their basic structure is hexagonal Boron Nitride (h-BN) but it's doped with carbon and oxygen. The simplest BCNO phosphors are usually made from urea and boric acid alone, this already produces a BN structure with C and O impurities.

I'm trying to use IR absorption spectra from several samples to find the optimal B/N (boric acid and urea) mass fraction in a certain preparation condition. And when I say optimal I mean the ones that maximize the amount of B-N bonds relative to the others found in the samples.

So I got the IR absorption data and now I'm trying to deconvolute the data using several gaussian peaks (manually, as no fitting algorithm would ever get to optimize more than 80 variables at once from scratch).

I'm still working in the first one and I already had to use 25 peaks to get started. This gif below shows the data (in red) and the fit so far (in blue):

And as you can see on it, I had to use wider gaussians to form a "base" and then narrower ones for the most prominent peaks.

However, my question is about the interpretation I'll be able to make from that. Identifying the narrow and strong peaks is quite feasible as there is data in BCNO articles about their identification, but I'm questioning myself about the possible relationships between the bonds I'm interested in quantifying and those broader peaks in the "base" I made.

Technically those broad peaks are also the result of many convoluted peaks that I'm "leaving convoluted" as I don't need to deconvolute them to model any of the prominent and narrow peaks that appear in my samples (being that only those narrow peaks are associated to the bonds I'm interested). But they do affect the area, width and center of the gaussians I have to use for the narrow peaks a bit (not much in many cases, as nearly any other "base" would be similar to get the fit working).

So, my question is: Can I just consider the area of the narrow gaussians to quantify the (relative) amount of bonds (associated to that peak) and disregard the "base" that I used? Is this a valid method?

Thanks!

It’s probably good enough if you’re just comparing between samples you’ve made at various experimental conditions, especially if you are keeping the deconvolved peaks the same from spectrum to spectrum, but I doubt you can pull any absolute quantities out of it.

## 1. What is the purpose of trying to meaningfully deconvolute IR absorption spectra?

The purpose of deconvoluting IR absorption spectra is to separate the overlapping peaks in the spectrum and identify the individual components present in the sample. This allows for a more accurate and detailed analysis of the sample's chemical composition.

## 2. How is deconvolution of IR absorption spectra typically performed?

Deconvolution is typically performed using mathematical algorithms and computer software that can analyze and separate the overlapping peaks in the spectrum. This process involves fitting the spectrum with a series of Gaussian or Lorentzian curves to accurately represent the individual peaks.

## 3. What factors can affect the accuracy of deconvolution in IR absorption spectra?

The accuracy of deconvolution can be affected by factors such as the quality of the instrument used to collect the spectrum, the resolution of the spectrum, and the presence of noise or artifacts. Additionally, the selection of the appropriate deconvolution algorithm and the number of peaks used in the fitting process can also impact the accuracy of the results.

## 4. Can deconvolution of IR absorption spectra be used for quantitative analysis?

Yes, deconvolution can be used for quantitative analysis by determining the area under each individual peak in the spectrum. This can then be used to calculate the relative concentrations of each component present in the sample.

## 5. Are there any limitations to deconvolution of IR absorption spectra?

Deconvolution of IR absorption spectra is a complex process and may not always provide accurate results. The accuracy can be affected by the complexity of the spectrum, the presence of overlapping peaks, and the selection of the appropriate deconvolution algorithm. Additionally, deconvolution cannot always separate all the components in a spectrum, and some peaks may remain unresolved.

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