SMA

The only basic requirement is to have a component with at least one peak area in a defined region of a spectrum and a known number of Hs (nuclides). The SMA plugin will use the integral value of this to quantify the species in mixtures with a discrete number of components.

There are many applications where SMA can become a successful tool for your mixtures analysis:

• Repetitive mixtures analyses of similar substrates, e.g. wine and specific foodstuffs.
• Mixtures having medium complexity
• Customized calculations of component concentration that can lead to a verified procedure
• Flexibility in report handling: internally and for the customer
• Medium to high throughput and minimal operator intervention required (UI/batch/listener)

SMA can perform quantitative analysis in mixtures and it suits regulated environments where the same compounds and analytical conditions are repeated, and fine control over the analysis is needed. These will often be the most stringent, controlled environments, e.g., forensics. You can relax and let SMA do all the hard work related to quantifying mixtures with overlapped peaks using GSD and integration methods support, and still have full control over the calculation method.You can create your own library of compounds and generate improved reports.

Integration with the Mnova DB makes it simple to build new analyses “on the fly”.

Sample-specific data may be needed (weights, etc.) When you hit the “Analyze” button peak picking is applied and multiplets are determined for each region.Then components are quantified using the sample-specific input and the determined integrals according to the specified equation. Each component is evaluated in turn and any errors are shown.

Finally a customized results table is filled.

SMA is a versatile tool which allows you to specify your formula for your calculations.Integral values are converted into relevant concentrations using user-defined mathematical expressions:Wt%, Purity%, Mole%, Concentration, etc.

• For simple molar ratios between two components you can use the following the general expression:

• If for instance you want to estimate the concentration of your mixtures components, then the concentration is determined using the simple equation:

The Concentration Conversion Factor (CCF) is like a “response factor” for NMR that converts the absolute integral/nuclide to concentration. For more information about the CCF factor please see Q: “What exactly is the CCF factor?”

• Alternatively if you are aiming to calculate the purity of your mixture components, once you create at least one reference material, the fundamental equation for purity (see below) can be applied.

This is Mestrelab´s novel capability for multiplet extraction from regions where peaks overlap. Even if the actual number of peaks is different, the target multiplet is found based on the shape moments. Mathematical descriptors are derived for the reference peak “pattern” called Peak Pattern Recognition (PPR). It gives SMA the ability to find a multiplet pattern when your spectra is heavily overlapped.A target area is systematically searched for this peak pattern. Hits are assigned a score, and ranked.

Even if the actual number of peaks is different,the target multiplet is found based on the shape moments.

Yes, you have full control of your quantification method specifying the integral regions to be used, and using the equation editor.SMA offers you the flexibility to define the way you quantify your mixtures.These integrals are converted into relevant concentrations using user-defined mathematical expressions.

Sample-specific data (weights, etc.) may be required depending on the quantification method used: Wt%, Purity%, Mole%, Concentration, etc.

See question “What sort of calculation does SMA use for quantification?”.

Requirements could be quite simple, but validated procedures will require optimization:

• Uniform samples (pH, salt concentration).
• Robotic sample handling.
• Optimizing signal acquisition for quality and quantitation.
• Identical NMR measurement conditions with competent autoshim, saturation, etc.
• Compound-by-compound CCF calibration through solutions of known concentration.
• Customized bleaching factoring for multiplets near presaturation positions.

SMA is a versatile tool which can optimise your production process. Once you have your sample preparation done and set up an automated spectrum acquisition you can implement SMA as your mixture analysis tool (UI, batch, listener). Experiments and results can be customized. An internal database can be created. Finally some periodic checks of procedures and results (GxP) are required.

We use Global Spectral Deconvolution (GSD) for basic processing. Regarding integration you will be able to select among different integration methods in the “Experiment” dialog box.Other integration options are traditional “Sum” and our unique “Edited Sum” hybrid procedure.

CCF stands for Concentration Conversion Factor or the “Spectrometer Factor”. Basically, when the area of a multiplet is determined, this is related to its concentrationC ∝ AI/NN

(1) Where C is the concentration of a chemical species, AI is the absolute integral for a multiplet attributable to that species, and NN is the number of nuclides (Hs, usually) for that multiplet.

From this we derive:

 (2) C= CCF * AI/NN

A proportionality constant which we call the CCF, allows us to convert a measured AI/NN into a concentration. Fundamentally, the CCF only needs to be determined once for an experiment, and then it is applicable to all chemical species in the reaction!

Once that has been performed, all other species concentrations can be determined by applying equation (2), where the AI is determined by the software, and NN is provided by the user.

For further information about how to calculate the CCF factor you can read the following qNMR_CCF document 

Start with the way you do it manually or in Excel. Then transfer your protocol to SMA’s Formula Editor. You may have additional options to take advantage of, and make the analysis more robust.

You can run SMA in the “Listener” mode (real time analysis) where there is no need to interact with the raw data to get your results once a method has been validated. In different words, real time processing! This can be advantageous, particularly in QC and production environments.