Near vs. Mid-IR: pick your poison

Is there a simple answer?

Of course not! When it comes to the debate regarding which infrared spectroscopy reigns superior, near-infrared (NIR) or mid-infrared (IR), the answer should be a reflect the merits of the technology in light of the application of interest. It’s like asking whether a knife is better than a spoon. Well, are you trying to cut an apple or eat ice cream? You see my point.

Basic theory

Put simply, infrared spectroscopy is the study of the interaction of infrared light with matter, where infrared light is characterized by wavenumber range spanning from 12,800 to 10 cm^-1 (or wavelengths of 0.78 to 1000 micron). Mid-IR is typically defined as light between 4000 and 400 cm^-1, and NIR as light between 10,000 and 4,000 cm^-1, give or take. Mid- and near-IR are included under the umbrella of molecular spectroscopy.

Imagine your sample at the molecular level, with carbon, hydrogen, oxygen and nitrogen atoms coordinated by chemical bonds in such a way as to produce the water, fat and protein content in that sample. The relative positions of the atoms in the molecules of your sample are not fixed; they fluctuate continuously as a consequence of a multitude of different types of vibrations (i.e. stretching and bending) and rotations about the bonds in the molecule. Check out this page for some nice illustrations and more in-depth theory. When the frequency of a specific vibration is equal to the frequency of the IR radiation directed on the molecule (*and the molecule undergoes a net change in dipole moment as a consequence of the vibrational or rotational motion), the molecule absorbs the radiation. A plot of the measured infrared radiation intensity versus wavenumber is known as an infrared spectrum.

Consider the difference in the wavenumber range (and hence, energy) of mid- and near-IR radiation. The higher-energy mid-IR is exciting fundamental vibrations; that is, when energy is absorbed by the molecule in its ground state to the first vibrational state. NIR spectroscopy is comprised of combination bands of overtones of those fundamental vibrations.  The latter are of much lower intensity than their fundamental analogs, owing to their lower transition probabilities. This can be an advantage OR disadvantage – depending on what you’re trying to do (keep reading!).

The bonds defining functional groups (structural fragments within the molecule, like C=O, N-H or C-H), tend to absorb IR radiation at predictable wavenumber ranges, regardless of the rest of the molecule’s structure. Organic functional groups have characteristic and well-delineated absorption bands in the mid-IR, lending the technique to structural elucidation and compound identification, especially when paired with other analytical methods like NMR. While the broad peaks and overlapping of the overtone and combination bands strongly decrease the specificity of NIR spectroscopy for spectral interpretation, low absorptivity and efficient light scattering by NIR radiation can be advantageously exploited. In other words, because the absorption intensity is low, NIR samples do not need to be diluted (as with mid-IR) to avoid saturation at the detector; sample thickness interrogated by NIR light can be extended from millimeters up to centimeters, depending on the sample composition. This large sampling volume is valuable for quantitative analysis of samples with some degree of heterogeneity.

Let’s now consider a common application where both mid-IR (FT-IR) and NIR methods are commonly employed: raw material identification.

Mid-IR Advantages

  • Characteristic and well-delineated absorption bands  for organic species in the mid-IR lend the technique to structural elucidation and compound identification; detailed tables of characteristic group frequencies facilitate structural elucidation efforts

Mid-IR Disadvantages

  • The need for sample dilution (e.g. KBr pellets, salt plates) is common, requiring extra time for material evaluation, as well as effective “destruction” of the sample (i.e. the sample cannot be used beyond the mid-IR measurement)
  • The small sampling volume of mid-IR when using attenuated total reflectance (ATR) is small, thus limiting method repeatability for less homogeneous samples

NIR Advantages

  • NIR spectra are impacted by both chemical and physical attributes of the sample; therefore, NIR can be used to discriminate between grades of the same chemical substance
  • NIR radiation achieves more sample penetration; increased sampling volume may increase sensitivity to contaminants
  • No sample preparation  (i.e. no pellets or salt plates), nor purge gas is required, thus reducing the sampling efforts and costs
  • Spectra are collected in seconds (typically 4 to 30s)

NIR Disadvantages

  • Some functional groups having both fundamental and first order (or higher) overtones in the mid-IR region will not appear in the NIR region, potentially limiting the discriminatory power of NIR for certain sample sets
  • Due to the more complex (i.e. broad and overlapping) signal of NIR spectroscopy, chemometric procedures are required for qualitative discrimination.  The superposition of bands However, software capable of handling these procedures is widely available and quite capable when paired with solid experimental design

Conclusion

What’s the moral of the story? If you have a label on a bag of white powder and you want to quickly see if that label is correct, then NIR is likely to be the right choice for you. You’ll complete your analysis quicker and be able to retain or use the NIR sample as you see fit. However, if you are synthesizing compounds in the lab and you want to know what you brewed up, mid-IR is the clear choice.

Advertisements

What is NIR?

More alphabet soup

Near-infrared spectroscopy. “N-I-R.”  Let’s illuminate the subject a bit, shall we?

Spectroscopy is a branch of science interested in the interaction of light with matter. Near-infrared (NIR) spectroscopy happens when the light used to do the measurements falls within a certain energy or frequency range; typically, 12000 – 4000 cm-1 (or about 700 – 2500 nm in terms of wavelength).

This idea isn’t new. The first observations of NIR light were made by Herschel in 1800, and Coblentz was considered its pioneer in the early 1900’s. However, this small but mighty portion of the electromagnetic spectrum didn’t debut commercially until the 1970’s, coinciding with advancements in PC computing power that radically simplified it’s application.

Why do people use NIR?

Everything you’ve come to love in your life: people, places, baked goods… they are all made up of molecules. Those molecules are made of atoms, and those atoms are moving and grooving (i.e. the bond lengths and bond angles aren’t static, but rather wagging and scissoring and bending and stretching). We can use NIR to measure that molecular dance party, or more technically, molecular vibrations. Those vibrational modes can tell us stuff about the sample that most QC departments like, think: sample identity or composition. 

When the molecules of a sample are hit with NIR light, the light is either absorbed or scattered. When the light is absorbed, we see a peak in our NIR spectrum. When light scatters due to the physical properties of the sample (e.g. particle size, particle morphology, bulk density), the overall slope of the spectrum is impacted. Chemical bonds that absorb NIR well are: oxygen-hydrogen (O-H), carbon-hydrogen (C-H), carbon-oxygen (C-O), nitrogen-hydrogen (N-H), and sulfur-hydrogen (S-H). While NIR isn’t the magic bullet for every analysis, we see samples that are dominated by these types of bonds in many industries, from pharmaceuticals to pet food.

The series of peaks and valleys that appear in an NIR spectrum is the summation of molecular vibrations of the sample. Consider the spectra of 5 different solutions in the figure below, where Absorbance is shown as a function of wavelength (nm). The red spectrum is pure methanol, the green spectrum is pure water. Peaks resulting from the -OH vibrations of both the alcohol and water, as well as the -CH vibration of the alcohol, are labeled.

water-alcohol

Since the energy of the -OH (and -CH) bonds of water and methanol (or donuts) differ, they produce unique spectra, as illustrated in the figure above. Combine that with the fact that spectra (of water, methanol or donuts) is repeatable, and we’re going somewhere. That means, if I scan water with my NIR analyzer 10x, I will get (more or less) the same spectrum, and that spectrum is unique from the other stuff I want to analyze (here, methanol). For those reasons, NIR would be a good tool for identification purposes.

Take another look at the figure above. The peak intensities corresponding to each molecular vibration reflect the relative composition of the molecules (water and alcohol) contributing those bonds to the solution. More specifically, you can see the peak corresponding to the water -OH vibration around 1450 nm increase as the relative proportion of water increases in solution. In the same way, the peak corresponding to the -CH combination vibration around 2250 nm increase as the proportion of methanol increases in the solution. That’s Beer’s Law working for us, where Absorbance at a given wavelength is proportional to the pathlength * molar absorptivity * concentration of the absorbing analyte. Note to the academics: if you dig into the theoretical research, you will see that Beer’s Law applies strictly to ideal solutions. Oh, and if you hadn’t heard, almost nothing is ideal in real life. However, we have mathematical ways to address non-linearity, and in the end, most methods work well. And by work well, we mean produce satisfactory standard errors of prediction. 

But before you get too excited about the infinite possibilities of NIR, let me give you some fine print. Our mortal bodies typically can’t run marathons without training first… and an NIR can’t run a qualitative or quantification application without being trained, either.

Additional resources:

For a good historical, theoretical and applications overview, see the Handbook of Near-Infrared Analysis, edited by Donald A. Burns and Emil W. Ciurczak