Quantitative 2D HSQC NMR determination of polymer structures by selecting suitable internal standard references

Abstract

A new analytical method based on the 2D HSQC NMR sequence is presented, which can be applied for quantitative structural determination of complicated polymers. The influence of T1 and T2 relaxations, off-resonance effects, coupling constants and homonuclear couplings are discussed. It was found that the T2 values measured on polymeric samples with the conventional HSQC-CPMG sequence could not be used to correct the errors caused by T2 relaxations during the polarization transfer delay. A unique way of selecting the proper internal standard reference signal(s) is therefore proposed to eliminate the major errors caused by T2 relaxations, resonance offsets, coupling constant deviations and homonuclear couplings. Two polymer samples, a cellulose triacetate and an acetylated lignin, have been used to illustrate the principles. The methodology developed in this work is robust to instrument miss-setting and it can find wide-spread applications in areas where a quantitative analysis of structurally complicated polymers is necessary.

Structural Characterization of Lignin in Wild-Type versus COMT Down-Regulated Switchgrass

“…Figures 3 and 4 presented the aromatic and aliphatic regions of HSQC NMR spectra of lignin samples isolated from control and transgenic switchgrass I1 internodes. The observed lignin sub-units were presented in Figure 5 and signal assignments were summarized in Table 1 (Ralph et al, 2004;Zhang and Gellerstedt, 2007;Kim et al, 2008;Yelle et al, 2008;Jiang et al, 2009;Kim and Ralph, 2010;Mansfield et al, 2012). The correlation signals for various monolignols including syringyl, guaiacyl, p-hydroxyphenyl, p-coumarate, and ferulate units were evidently observed and distributed fairly well in the aromatic region of HSQC spectra.…”

“…The central DMSO solvent peak was used for chemical shifts calibration (δc 39.5 ppm, δ H 2.50 ppm). Relative lignin monomer compositions and interunit linkage abundance were estimated semi-quantitatively using volume integration of contours in HSQC spectra (Ralph et al, 2004;Zhang and Gellerstedt, 2007;Kim et al, 2008;Yelle et al, 2008;Jiang et al, 2010;Kim and Ralph, 2010;Samuel et al, 2011;Mansfield et al, 2012). For monolignol compositions of S, G, H, p-coumarate (pCA), and ferulate (FA) measurements, the S 2/6 , G 2 , H 2/6 , pCA 2/6 , and FA 2 contours were used with G 2 and FA 2 integrals doubled (Higuchi et al, 1967;Marita et al, 2001;Ralph et al, 2001Ralph et al, , 2004Capanema et al, 2005;Zhang and Gellerstedt, 2007;Kim et al, 2008;Yelle et al, 2008;Jiang et al, 2010;Kim and Ralph, 2010;Mansfield et al, 2012).…”

HSQC-NMR analysis of lignin in woody (Eucalyptus globulus and Picea abies) and non-woody (Agave sisalana) ball-milled plant materials at the gel state 10th EWLP, Stockholm, Sweden, August 25–28, 2008

“…A semiquantitative analysis of the intensities of the HSQC cross-signal was performed (Heikkinen et al 2003;Liitiä et al 2003;Zhang and Gellerstedt 2007). Since the cross-signal intensity depends on the particular 1 J CH value, as well on the T 2 relaxation time, a direct analysis of the intensities is elusive.…”

A possible explanation for the structural inhomogeneity of lignin in LCC networks

“…With these methods several important intermonolignol bonds can be quantified (Zhang and Gellerstedt 2007). Figure 6 shows one example of the 2D HSQC and 13 C NMR to represent how the synthesized DHP peaks look like.…”