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Spectral window setting

ID ll spectrum, and crosspeaks are arranged symmetrically around the diagonal. There is only one radio frequency channel in a homonuclear experiment, the H channel, so the center of the spectral window (set by the exact frequency of pulses and of the reference frequency in the receiver) is the same in If and F (Varian tof, Bruker ol). The spectral widths should be set to the same value in both dimensions, leading to a square data matrix. Heteronuclear experiments have no diagonal, and two separate radio frequency channels are used (transmitter for F2, decoupler for F ) with two independently set spectral windows (Varian tof and dof, sw, and swl, Bruker ol and o2, sw(If), and sw(I )). Heteronuclear experiments can be further subdivided into direct (HETCOR) and inverse (HSQC, HMQC, HMBC) experiments. Direct experiments detect the X nucleus (e.g., 13C) in the directly detected dimension (Ff) using a direct probe (13C coil on the inside, closest to the sample, H coil on the outside), and inverse experiments detect XH in the To dimension using an inverse probe (XH coil on the inside, 13C coil outside). [Pg.635]

A computer-controlled bandpass filter system controls the size of the acquired spectral window. Typically, this is set to about 120% of the desired sweep width. Only frequencies within these limits are allowed to reach the ADC. Those frequencies outside the limits would only contribute to the noise in the final spectmm. The need for this system is dictated by the nonselective nature of the excitation rf pulse. [Pg.402]

The number of bands present in a spectral window and their centers of symmetry are pre-requisites to other signal processing procedures i. e. curve fitting. For in situ spectroscopic reaction studies, a set of tracks can be assigned which specify the centers of symmetry for all the bands. Since the bands move as a function of composition, the tracks in a matrix or AF %xv drift. [Pg.173]

The Pearson VII model contains four adjustable parameters and is particularly well suited for the curve fitting of large spectral windows containing numerous spectral features. The adjustable parameters a, p, q and v° correspond to the amplitude, line width, shape factor and band center respectively. As q —the band reduces to a Lorenzian distribution and as q approaches ca. 50, a more-or-less Gaussian distribution is obtained. If there are b bands in a data set and... [Pg.174]

Fig. 3. 2Q-HoMQC spectrum of apo-cytochrome c in 93% H2O at pH = 6 and 0.48 mM concentration. The spectrum was acquired with 30 ms 2Q excitation delay overnight on a Varian Unity/INOVA 600 MHz instrument using gradient MQ selection and no additional water suppression (I.P., unpublished). Equal spectral windows were set for both dimensions. Fig. 3. 2Q-HoMQC spectrum of apo-cytochrome c in 93% H2O at pH = 6 and 0.48 mM concentration. The spectrum was acquired with 30 ms 2Q excitation delay overnight on a Varian Unity/INOVA 600 MHz instrument using gradient MQ selection and no additional water suppression (I.P., unpublished). Equal spectral windows were set for both dimensions.
With this spectrometer, a difference mid-IR spectrum at a selected time after sample excitation is recorded by sweeping from 1640 to 940 cm in steps that may be as short as approximately equal to the spectral resolution of the spectrometer—in this case, 8 cm. The sample solution is pumped through a flow cell that has IR-transmitting Cap2 windows set with a 0.1-mm optical pathlength. The Bap2 windows have also been used for the sample cell. ... [Pg.885]

Scaling When clicking this button the height of the active integral is set lo the height of the corresponding peak and all the other integrals within the spectral window are scaled. [Pg.103]

The correct performance of any curve-resolution (CR) method depends strongly on the complexity of the multicomponent system. In particular, the ability to correctly recover dyads of pure profiles and spectra for each of the components in the system depends on the degree of overlap among the pure profiles of the different components and the specific way in which the regions of existence of these profiles (the so-called concentration or spectral windows) are distributed along the row and column directions of the data set. Manne stated the necessary conditions for correct resolution of the concentration profile and spectrum of a component in the 2 following theorems [22] ... [Pg.421]

The same formulation of these two theorems holds when, instead of looking at the concentration windows in rows, the spectral windows in columns are considered. In this context, the theorems show that the goodness of the resolution results depends more strongly on the features of the data set than on the mathematical background of the CR method selected. Therefore, a good knowledge of the properties of the data sets before carrying out a resolution calculation provides a clear idea about the quality of the results that can be expected. [Pg.421]

Manne s resolution theorems clearly stated how the distribution of the concentration and spectral windows of the different components in a data set could affect the quality of the pure profiles recovered after data analysis [22], The correct knowledge of these windows is the cornerstone of some resolution methods, and in others where it is not essential, information derived from this knowledge can be introduced to generally improve the results obtained. [Pg.423]

Local-rank constraints are related to mathematical properties of a data set and can be applied to all data sets, regardless of their chemical nature. These types of constraints are associated with the concept of local rank, which describes how the number and distribution of components varies locally along the data set. The key constraint within this family is selectivity. Selectivity constraints can be used in concentration and spectral windows where only one component is present to completely suppress the ambiguity linked to the complementary profiles in the system. Selective concentration windows provide unique spectra of the associated components, and vice versa. The powerful effect of these type of constraints and their direct link with the corresponding... [Pg.435]

The last equation tells us what value of the dwell time we have to use to establish a particular spectral width. In practice, the user enters a value for SW and the computer calculates DW and sets up the ADC to digitize at that rate. It is important to understand that with the simultaneous (Varian-type) acquisition mode, there is a wait of 2 x DW between acquisition of successive pairs of data points. The average time to acquire a data point (DW) is the total time to acquire a data set divided by the number of data points acquired whether they are acquired simultaneously or alternately. The spectral window is fixed once the sampling rate and the reference frequency have been set up. The spectral window must not be confused with the display window, which is simply an expansion of the acquired spectrum displayed on the computer screen or printed on a paper spectrum (Fig. 3.15, bottom). The display window can be changed at will but the spectral window is fixed once the acquisition is started. [Pg.102]

Because digital filtering can produce a brick wall frequency response, any peak that falls outside the spectral window is removed completely and will not alias. This can be a problem if you set the spectral window too narrow You will never be aware of the peaks you miss. If you accidentally set the spectral window to include nothing but noise, you will get just that in the spectrum nothing but noise The good news is that if we are only interested in a small part of the ID spectrum, we can cut out the rest of the spectrum using the digital filter. For example, in a 2D N-1 HSQC spectrum of a protein, we are only... [Pg.117]

The computer algorithms that carry out the discrete Fourier transform calculation work most efficiently if the number of data points (np) is an integral power of 2. Generally, for basic H and C spectra, at least 16,384 (referred to as 16K ) data points, and 32,768 ( 32K ) points should be collected for full H and spectral windows, respectively. With today s higher field instruments and large-memory computers, data sets of 64K for H and 64-128K for and other nuclei are now commonly used. [Pg.41]

Standard sets of acquisition parameters include typical transmitter offset values. If wider spectral widths are required, simple trial and error with concentrated samples or standards permits the operator to widen the spectral window in a selective manner. For example, the operator may suspect the presence of highly deshielded H signals and wish to open the H spectral width from the usual 10 ppm (4,000 Hz at 400 MHz) to 15 ppm (6,000 Hz). In order to add all of the additional 5 ppm (2,000 Hz) worth of sw capacity to the downfield (high-frequency) end of the spectral range (i.e., from 10-15 ppm), the transmitter offset value is increased by approximately 2.5 ppm (1,000 Hz at 400 MHz). This procedure also keeps the transmitter offset positioned in the middle of the widened spectral window. [Pg.43]


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Setting the Spectral Window

Spectral set

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