Blog posts by Paul

How to Evaluate a Benchtop NMR Instrument’s Technical Performance Part 3: 1H sensitivity

July 4th, 2019, by

In my recent posts on evaluating benchtop NMR system performance, I discussed the fundamental role the static (B0) magnetic field homogeneity plays in defining the lineshape and with it the resolution performance of the instrument. However, the quality of the magnetic field affects much more than just the instrument’s lineshape and resolution: since broadening of the lines due to B0 inhomogeneity causes them to be lower in amplitude, the quality of the field also directly affects the instrument’s sensitivity. In this post I explore the concept of instrument sensitivity in more detail and look at how to measure  1H sensitivity.

 

What is Meant by Sensitivity?

A formal definition of sensitivity is the ability of an instrument to detect a target analyte. This is usually expressed in NMR as the signal-to-noise ratio (SNR) for a defined concentration of reference substance. Simply put, the more sensitive the NMR spectrometer, the less sample you need to get the same SNR in your spectrum. The two principal enemies of any analytical measurement are higher noise levels and a lower intensity of the signal measured by the instrument’s detector for a sample of given concentration. With modern electronics the noise levels are consistent and should not vary much between different instruments.  This means the sensitivity depends primarily on the signal amplitude, which in turn depends on the lineshape and resolution of the instrument. A poor lineshape results in spectra with broad lines that are lower in amplitude, which decreases the SNR, thereby degrading the sensitivity of the instrument and increasing the amount of sample and/or measurement time required to get the same SNR in the spectrum, as we will see below.

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How to Evaluate a Benchtop NMR Instrument’s Technical Performance Part 2: 1H Lineshape and Resolution

June 17th, 2019, by

In this post, I’m going to discuss a specific test for evaluating the resolution or lineshape of a benchtop NMR system. This test is measured on proton (1H) as the NMR spectrum is sensitive to the spectrometer resolution and we can make the measurement with a single scan. Resolution and lineshape refer to the width of a particular NMR spectral line, measured at 50% and 0.55% of the height of the line, as explained below.  The smaller the linewidth value, the better the resolution.

 

1H lineshape and resolution

The information content of any NMR spectrum depends on the ability to observe and resolve different signals, or peaks, in the spectrum. It is easier to distinguish two sharp (narrow) peaks close together, than two broad peaks. The key technical factor defining the sharpness of the lines in the spectrum (the lineshape) is the homogeneity of the magnetic field generated by the magnet.  Although NMR systems utilize an array of coils (“shims”) to further improve the B0 homogeneity, the achievable lineshape and resolution are strongly influenced by the inhomogeneity of the magnet itself. The process of calibrating the field and optimizing the B0 homogeneity is usually referred to as shimming. The homogeneity and resolution will gradually degrade over time, so you should carry out the shimming procedure whenever you want to ensure you have the best resolution your spectrometer is capable of.  You should also do the shimming procedure immediately before making the linewidth test described here.

 

Measuring 1H lineshape and resolution

The way to measure instrument resolution is to collect a spectrum containing a naturally sharp line. The standard approach for is to use a sample containing chloroform in acetone-d6 – the chloroform signal from this sample has a very narrow natural linewidth.1 Figure 1 shows a 1H NMR spectrum sample of a 20% chloroform in acetone-d6 NMR reference sample collected on an 80 MHz benchtop NMR spectrometer. (https://www.sigmaaldrich.com/catalog/product/sial/611859)

Figure 1. 80 MHz 1H NMR spectrum of 20% chloroform in acetone-d6 (“lineshape”) sample

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How to Evaluate a Benchtop NMR Instrument’s Technical Performance: Part 1

June 13th, 2019, by

When evaluating a benchtop NMR instrument there are several key performance characteristics that have a very significant impact on how the instrument will perform in your lab. These key performance characteristics are:

  • The spectral resolution, which is directly related to the magnet and determines the width or shape of the NMR lines (often called lineshape), and in turn the ability to separate signals in the spectrum
  • The sensitivity which determines the limits of detection (LOD) and quantitation (LOQ), and in turn how long sample measurements take
  • The stability of the magnet and instrument over time, which impacts the ability to make longer measurements, and the overall ease of use of the spectrometer

Before I examine these performance characteristics in more detail, it’s worth emphasising from the outset that the biggest aspect of a benchtop NMR system’s design that dictates how well the system performs is the “quality” of the magnetic field produced by the magnet. By “quality” we are referring to how uniform the magnetic field is over the sample volume, often referred to as the B0 homogeneity. To illustrate the importance of this key aspect of magnet design, Figure 1 shows a series of spectra collected under varying degrees of B0 homogeneity.

Figure 1. Effect of static magnetic field (B0) homogeneity on the NMR spectrum. As the homogeneity gets worse, both the resolution and sensitivity are negatively affected. The series of spectra on the left are shown at the same scale and show how the 2 peaks can no longer be resolved, and the signal intensity decreases. The series on the right is the same spectra shown with the peak intensities normalised which how the signal-to-noise ratio is decreasing (the noise is increasing) when the field is less homogeneous.

 

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1H and 13C Peak Assignments of Quinine Using 1D and 2D NMR Methods (Part 3)

July 15th, 2018, by

In my first two posts on using 1D and 2D NMR methods to assign the peaks of quinine (Figure 1), I looked at the 1H and 13C spectra.

 

Figure 1. Structure of quinine

 

In this post, I’m moving on to look at the 1H-13C HSQC spectrum. It’s worth spending a brief moment recapping what HSQC is all about and what info it gives you. In a nutshell, the HSQC experiment correlates proton and carbon chemical shifts over one chemical bond. Another way to put this is that a cross-peak in an HSQC spectrum says, “The proton with this chemical shift is directly attached to the carbon with that chemical shift”. By convention, HSQC spectra are presented with 1H shifts along the horizontal axis and 13C shifts along the vertical axis.

Some variants of HSQC also encode into the phases of the cross-peaks additional information about how many hydrogen atoms are attached to each carbon atom. This is sometimes referred to as multiplicity or DEPT editing. In the multiplicity-edited HSQC spectrum, it is conventional for the CH and CH3 groups to have positive phase, and the CH2 groups to have negative phase, just as in a DEPT-135 spectrum. Figure 2 shows the multiplicity-edited HSQC (“HSQC-ME”) spectrum of our 400 mM quinine sample. The CH2 signals are shown in blue and the CH and CH3 signals in red.

 

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The APT Experiment

June 7th, 2018, by

The Attached Proton Test (APT) is a very useful experiment that, like DEPT, provides information about how many hydrogens or protons are attached to a particular carbon atom. Both DEPT and APT do this by “editing” the spectrum so that the carbon signals point either up or down depending on the number of attached hydrogens. APT differs from DEPT in several significant ways, though. The first is that quaternary carbons (i.e. carbons that bear no hydrogens) are retained in the APT spectrum, whereas they are absent in DEPT (though there are variants of the traditional DEPT experiment that do retain the quaternary signals). In APT, quaternary and methylene carbons point down by convention, while methyl and methine carbons point up. Figure 1 shows a comparison of a conventional carbon, APT and DEPT-135 spectra of a sample of propyl benzoate.

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1H and 13C Peak Assignments of Quinine Using 1D and 2D NMR Methods: Part 1

June 7th, 2018, by

Assigning peaks in the NMR spectrum is a fundamental part of structure verification. Depending on a variety of factors including the size and complexity of the molecule, and the field strength the NMR data are collected at, this can be a straightforward exercise or an extremely challenging one! For example, in the case of a fairly simple compound like lidocaine, it is relatively easy to assign all of the peaks directly in the 1H spectrum using a 43 MHz benchtop NMR spectrometer. However, as a compound’s molecular weight increases so the spectra tend to become more complex, with more resonances and, inevitably, more signal overlap. Assigning the peaks thus becomes significantly more challenging, which is where collecting 2D NMR spectra can help with completing the assignments.

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Silicon NMR on Spinsolve – Part 2

August 30th, 2017, by

In my last blog post I introduced silicon NMR on Spinsolve and showed a variety of 1D 29Si{1H} and 29Si-1H DEPT spectra. In this post I’m moving on to talk about some 2D experiments that are useful for silicon studies. One of the most useful and widely used of those is the 1H-29Si HMBC experiment, which correlates proton and silicon chemical shifts over two or more chemical bonds. For example, Figure 1 below shows a 1H-29Si HMBC spectrum of the 1,1,3,3,5,5-hexamethyltrisiloxane sample I used before, collected in around 17 minutes. The 1H spectrum is shown along the horizontal axis of the 2D spectrum, and the 29Si spectrum is shown along the vertical axis.

Fig. 1. 1H-29Si HMBC spectrum of 1,1,3,3,5,5-hexamethyltrisiloxane

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Silicon NMR on Spinsolve – Part 1

June 22nd, 2017, by

Silicon is one of the most widespread elements in the natural world and, as such, this makes it a very interesting and useful element to study using NMR. Over the past few decades, a wide range of silicon-containing compounds have been investigated using both solid- and liquid-state NMR techniques. For example, siloxane polymers, which are extensively used in biomedical and cosmetic applications, have been extensively studied by NMR to understand their structure and individual building blocks. Similarly, the structure of silicates, zeolites and other materials have been studied by silicon NMR. Silicon NMR has been shown to be a powerful tool for the determination of active end groups, cross-linking moieties and polymer sequencing.

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The Constant-Time COSY Experiment

August 7th, 2016, by

Despite the proliferation of new 2D techniques over the past four decades, one of the most commonly used experiments is the very first one to have come into existence, COSY1. It’s easy to see why it’s withstood the test of time: firstly, it’s an extremely useful experiment, providing a direct and easy way of establishing “through bond” proton-proton connectivities (“this hydrogen is near or next to that hydrogen”); secondly, because it’s a homonuclear 2D experiment (that is to say, it correlates protons with protons) its’s a very sensitive one. The high sensitivity also means that it’s a quick experiment to run, particularly if the experiment uses gradients for coherence selection (more on that below and in a future blog post).

Example COSY spectra recorded on Spinsolve can be found elsewhere on the Magritek website, but a typical example is also shown in Figure 1 below, recorded on a sample of ethyl crotonate. The sequence used to collect this spectrum utilizes gradients, meaning that it was run using only a single scan per t1 increment, and with 512 increments it only took 15 minutes to run.

Conventional COSY of ethyl crotonate

Fig. 1. COSY spectrum of ethyl crotonate, collected using gradients and 512 t1 increments.

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About Paul

Paul works as Product Support Manager for Magritek. He is currently based in San Francisco, California. He obtained his Ph.D. in NMR technique development from The University of Manchester, U.K., under the supervision of Prof. Gareth Morris.