2D Assignment and quantitative analysis of cellulose and oxidized celluloses using solution-state NMR spectroscopy

MCC (DP_N-GPC 153) was purchased from Sigma-Aldrich. The LDP-CNCs (DP_N-GPC 37, 15 wt% dispersed in water) were the precipitated ‘residue’ from the sc-H₂O extraction of microcrystalline cellulose (MCC), as described by Buffiere et al. (2016). They were freeze-dried before use to remove as much free water as reasonably possible. Nitroxyl-radical oxidation of the LDP-CNCs was carried out in the NaClO/NaClO₂ system in the presence of 4-acetamido-2,2,6,6-tetramethylpiperidine 1-oxyl (4-AcNH-TEMPO), under acidic conditions (pH 5.8), according to Hirota et al. (2009). This yielded 4-AcNH-TEMPO-oxidized LDP-CNCs (TOx-LDP-CNCs). The prepared sodium polyglucuronic acid salt form of the TOx-LDP-CNCs was acidified to pH 1.0 and separated by centrifugation with subsequent water washing and freeze-drying. Pinnick oxidation of the reducing ends of LDP-CNCs was carried out under acidic conditions (pH 5.0) in the presence of one weight equivalent of NaClO_2, to yield Pinnick-oxidized LDP-CNCs (POx-LDP-CNCs). The prepared salt form was acidified to pH 1.0 and further processed, as described above. Periodate-oxidized CNCs (NaIO₄-CNCs) were prepared from pristine CNCs (prepared from cotton by hydrolysis with H₂SO₄ followed by desulfation with HCl), as described in Nypelö et al. (2018). After oxidation with sodium periodate, a film from the oxidized CNCs was cast in a Petri dish, by initial sonication of cellulosic dispersion, casting and air-drying. A mixture of gluconic acid and the corresponding lactone was prepared by evaporation of an aqueous gluconic acid solution (49–53 wt%) in a rotary evaporator. Detailed procedures can be found in the Supporting Information. Cellobionic acid was purchased from Aldox, Dept. of Food Science and Technology, BOKU, Vienna, Austria. All other solvents and chemicals were commercially available from Sigma-Aldrich and VWR, except DMSO-d₆ (Eurisotop) and 4-AcNH-TEMPO (TCI Europe) and used as received, without further purification. More detailed information can be found in the Supporting Information.

Tetrabutylphosphonium acetate ([P₄₄₄₄][OAc]) was synthesized according to an optimized method by King et al. (2018). Briefly: Tetrabutylphosphonium chloride ([P₄₄₄₄]Cl) was prepared from tri-n-butylphosphine by reaction with n-butyl chloride in a teflon-lined Parr acid-digestion reactor. [P₄₄₄₄][OAc] was obtained by metathesis reaction of [P₄₄₄₄]Cl with potassium acetate (KOAc) in isopropyl alcohol and purified by precipitation from chloroform to remove residual salts.

A stock solution of [P₄₄₄₄][OAc]:DMSO-d₆ (20:80 wt%) for solution-state NMR analysis of the cellulosic materials was simply prepared by dissolution of crystalline [P₄₄₄₄][OAc] into DMSO-d₆, in the w/w ratio of 1:4. Direct contact of [P₄₄₄₄][OAc] with air was minimized, to avoid moisture uptake. It may be preferable to use a glove-box or argon flush especially in humid climates. In a typical sample dissolution procedure, 50 mg of dry cellulosic material were introduced into 950 mg of [P₄₄₄₄][OAc]:DMSO-d₆ stock electrolyte, in 4 mL sealed vials, equipped with stirring bars. These were initially stirred at RT to see if the samples dissolved. If not, they were heated at 65 °C under inert atmosphere. Once the solutions were clear and visually isotropic, the samples were transferred into 5 mm NMR tubes (Wilmad-Labglass Co., USA) for analysis.

Spectra were recorded using a Bruker Avance 600 MHz Avance III or NEO spectrometers. The majority of the experiments were recorded using a SmartProbe™ optimized for X-nucleus detection. For some samples, an inverse triple resonance probe-head (¹H/¹⁹F, ¹³C, ³¹P) or a cryogenically-cooled quadruple resonance (¹H, ¹³C, ³¹P, ¹⁵N) probe-head were used.

The key NMR experiments are as follows:

All NMR measurements were conducted at a sample temperature of 65 °C. Typically, the time-domain size in the indirect ¹³C-dimension (f1) for HSQC was 1024 and HMBC was 512, corresponding to 512 (td1/2) and 512 (td1) actual t₁-increments in the real data, for phase sensitive HSQC sequences and the magnitude mode HMBC sequence, respectively. High digital resolution was used as most samples were quite low molecular weight. Chemical shifts in ¹H and ¹³C ppm scales were calibrated against the DMSO-d₆ signals (2.50 ppm for residual ¹H and 39.52 ppm for ¹³C). All spectra were processed using Bruker TopSpin 4.0.6 (https://​bruker.​com/​) and/or MestReNova 10.0.2 (https://​mestrelab.​com/​) software. Further 1D data processing was completed using Fityk 1.3.1 (Wojdyr 2010) (https://​fityk.​nieto.​pl/​). Full NMR experimental and conditions are given in the Supporting Information.

For NMR analysis, the samples were dissolved in the [P₄₄₄₄][OAc]:DMSO-d₆ (1:4 wt%) electrolyte at 5 wt%, at as low temperatures as possible (typically 25–80 °C). For the low DP samples this occurred rapidly at RT. This concentration of cellulosic materials allowed for detection of the low-intensity signals, such as the chain ends in the polymeric samples. All spectra were collected at the elevated temperature of 65 °C, as it offers further improvement in resolution and S/N, due to longer spin–lattice (T₁) and spin–spin (T₂) relaxation times. It is known that T₂ increases with elevated temperature, due to an approximate inverse-law relationship between T₂ and viscosity (Kim 2008). Significant improvements in resolution were also previously observed for the case of MCC dissolved in the homologous methyltrioctylphosphonium acetate ([P₈₈₈₁][OAc]):DMSO-d₆ system (Holding et al. 2016).

Literature resonance assignment of the most basic monomeric units of oxidized celluloses are incomplete. Thus, a range of monomers and dimers were studied, specifically in the [P₄₄₄₄][OAc]:DMSO-d₆ (1:4 wt%) electrolyte. Cellulose is also complicated by the fact that there are non-reducing end (NRE) and anomeric reducing-end (RE) units that differ in their chemical shifts from the corresponding species in the polymeric units. Separation of these species, using 2D correlation methods, is not guaranteed for high molecular weight samples. Hence, monomeric and dimeric models are described, in addition to the LDP-CNC sample (DP_N-GPC 37). This sample is rather unique in the fact that there are not many sources of low DP cellulose accessible, in large enough quantities, for synthesis and assignment of the products.

The NMR spectra of native celluloses can provide information on the average chain length of the polymer, as the signals of the reducing end and non-reducing end are relatively well separated (King et al. 2018; Heise et al. 2019; Holding et al. 2016). However, the characterization of modified cellulose samples can be complicated, as both the location and substitution pattern may vary along the polymer chain, and the high molecular weight can preclude using more sophisticated NMR techniques. In addition, as the literature data on relevant monomeric units of oxidized cellulose is incomplete, a range of monomeric, dimeric and oligomeric models were chosen or prepared to aid the spectral interpretation of the oxidized samples. These include: glucose, cellobiose, LDP-CNC, glucuronic acid, gluconic acid and cellobionic acid.

The full assignment for the dimers, polymeric units and terminal units in this study are shown in Fig. 1. These are in the [P₄₄₄₄][OAc]:DMSO-d₆ (1:4 wt%) electrolyte at 65 °C, referenced against DMSO-d₆ (residual ¹H at 2.5 ppm and ¹³C at 39.52 ppm). The following will be a description of how the assignments are made and further aspects of the study.

The HSQC, ¹³C and HSQC-TOCSY spectra for the monomers are shown in Fig. S5-S13; glucose (Fig. S5-S8), gluconic acid, (Fig. S9-S11) and glucuronic acid (Fig. S12-S13). Tabulated chemical shift data, along with previous literature assignments, are shown in Tables S1 and S3: glucose (Table S1) (Roslund et al. 2008) and glucuronic acid (Table S3) (Agrawal 1992). Our assignments did not change significantly from those of the literature assignments.

Cellobiose (Fig. 1a, b) consists of α an β anomers giving 24 identifiable correlations in HSQC and resonances the ¹³C spectrum (Fig. 2a, b). The ratio of anomers is 34:66 (α: β) by ¹H NMR (by integration). HSQC-TOCSYs are shown in Fig. S14-S18, in the Supporting Information, allowing for complete assignment. The tabulated chemical shift data is also given in the Supporting Information (Table S4-S5), along with previous literature assignments in D₂O (Roslund et al. 2008) which do not show any major deviations from our data. With cellobiose, the spectra start to become quite a bit more complex than for the monomers, with many overlapping peaks in the C2–C5 region (65–85 ppm in the ¹³C domain). HSQC-TOCSY spectra with short mixing times (15 ms, Fig. S14), which provides COSY-like correlations, was most useful for tracing the complete spin-systems for the anomers. In the case of cellobiose, which is not polymeric, we still term the glucopyranose with the hemiacetal anomeric carbon atom as the RE and the one with the glycosidic C1 as the NRE. HSQC-TOCSY with long mixing time (120 ms, Fig. S18), was used to easily visualize the corresponding TOCSY correlations for the separate RE and NRE spin-systems. Full assignments are given in Fig. 1a, b and Table S4-S5. At 2048 indirect (f1) increments in the HSQC (Fig. 2a) the resolution starts to approach that of the ¹³C spectrum.

In the assignment of cross-peaks, we have tried to be consistent with the color labeling of the assigned correlations: (1) NREs are labeled in green; (2) nonmodified internal AGU correlations are labeled in black; (3) α and β REs are labeled in red and blue, respectively; (4) oxidized internal AGUs, anhydroglucopyranosiduronic acid (AGA) units are labeled in brown; (5) where appropriate, the open (acid) form of the unit was labeled turquoise and closed (lactone) form in purple. This applies to all the figures, except Fig. 8. Cross-peak coloration of the HSQC spectra, unless grayscale, depends on the multiplicity: for primary (CH) and tertiary (CH₃) substituted carbons, cross-peak correlations are shown in green; for secondary (CH₂) substituted carbons cross-peak correlations are shown in blue.

LDP-CNCs (DP_N-GPC 37) consist of chains of β-(1,4)-linked glucopyranose units terminated by RE and NRE groups (Fig. 1c, d). These are true nanocrystals (Fig. S35-S37), formed by partial depolymerization and recrystallisation of MCC using sc-H₂O. This ‘residue’ fraction (Buffiere et al. 2016) comprised of cellulose crystallite fragments consisting of both cellulose I and cellulose II allomorphs. This is illustrated by the microscopy combined with wide-angle X-ray scattering (WAXS) analysis of the material (Fig. S37), showing both phases of cellulose I and cellulose II. Some of the main distinguishable diffraction planes corresponding to cellulose I Miller indices (French 2014) are clearly visible at 15.6° for \((1{\overline 1} 0)\) and (110), and 22.3° for (200). For cellulose II there are also distinguishable peaks at 12.3° for the \((1{\overline 1} 0)\) and 20.1° for the (110) Miller indices (French 2014). Gel-permeation chromatography (GPC) showed a higher molecular weight residue, originating from MCC but the majority of material was as a lower molecular weight fraction, with a peak-maximum at a DP of ~ 32 and overall DP_N-GPC of 37 (Fig. S38).

The CH-1 region in the HSQC spectrum (Fig. 3a) was characterized by four clear signals and the signal with highest intensity was assigned as anhydroglucose unit (AGU)-1 that belongs to the bulk polymeric CH-1 (δ_H = 4.40 ppm (d); δ_C = 102.38 ppm), while the remaining signals correspond to NRE-1, RE-α-1 and RE-β-1. This region is characteristic of (hemi)acetals and such close grouping is caused by the rigid conformation adopted by the sugar unit, with the α-anomer showing a characteristic down-field shift (to > 4.5 ppm) in the ¹H domain and up-field shift in the ¹³C domain. Detailed assignment of the remaining HSQC correlations was then completed using HSQC-TOCSY (Fig. S20-S22) and HMBC to separate the CH-6 position correlations (Fig. S19). The ratio of α to β, of the ¹H spectrum is 38:62, by deconvolution (Supporting Information Fig. S3), using ‘Fityk’ (Wojdyr 2010). The same method yielded a DPN-¹H of 15. While there is clearly error in this calculation, we favor the lower DP value, given by the NMR, as overestimation by GPC was also demonstrated in a previous publication (Heise et al. 2019), comparing ‘CCOA labelling’ (Röhrling et al. 2002) and 2 separate GPC systems; one calibrated using pullulan standards and one using multi-angle light scattering (MALLS) detection.

Throughout each of the experiments, the number of t₁-increments for the real spectrum (td1/2 for phase-sensitive HSQC) can be changed to improve resolution to the required level, to allow for separation of each signal. This is rather straightforward for low molecular weight compounds, such as glucose, cellobiose and to a lesser extent the LDP-CNCs. In this regard, the resolution in the indirectly detected ¹³C-dimension in HSQC can start to approach that of the ¹³C spectra, providing T₂ values are long enough to benefit from the further sampling. However, as molecular weights increase, the potential gain in resolution can often not be worth the additional collection times, with collection time proportional to the number of f1 increments. In addition, with shorter T₂ values the signals decay quickly and increased sampling will simply result in increased noise, with minimal increase in spectral resolution. Therefore, there is a trade-off between number of scans and number of increments, as molecular weight increases. To assess the resolution gain for a typical cellulose model, MCC (DP_N-GPC 153), we measured the full-width at half maximum (FWHM) values (here in ppm units) in the ¹³C dimension from HSQCs, gathered for different increment values (Fig. S2). The graph shows an inverse power function relating the resolution to the number of f1 increments. The optimum resolution, with little further trade-off in resolution vs collection time, can be achieved using 1024 increments, for the utilized spectral width of 24,883 Hz in the ¹³C-dimension (corresponding to 24.3 Hz/pt digital resolution of the data in the f1-dimension). However, for most of the cases where good enough resolution is required for assignment of main peaks, 256 t₁-increments is sufficient and 512 still gives a reasonable improvement. This can be reduced further by using a smaller spectral width, as 24,883 Hz (165 ppm) is already rather wide, encompassing much more of the ¹³C ppm domain that is necessary for unmodified cellulose. As molecular weight of the cellulose sample increases, the improvement in resolution with application of increasing increments is less apparent due to restricted motion, resulting in faster relaxation. However, 256–512 increments (i.e. 512–1024 time-domain size in f1) are perfectly reasonable values to achieve good S/N in an overnight run for assignment of NRE and RE signals for DP_N values of up to ~ 200. It should also be considered that as the molecular weight increases, the relative abundance of NRE and RE resonances also decreases.

Oxidation of cellulose with nitroxyl-radicals, such as TEMPO or AcNH-TEMPO, supposedly yield selective oxidation at the surface primary 6-hydroxyls (vs secondary 2- or 3-hydroxyls) to carboxylates but should also be capable of oxidizing the RE (hemi)acetal/aldehyde. Thus, the monomer unit in oxidized cellulose should be glucuronic acid (assuming each monomer is oxidized). If the terminal RE unit is oxidized, at the RE-1 position, gluconic acid should be the oxidized unit. Gluconic acid is available commercially as the sodium salt or as a solution in water, where it exists in equilibrium with the cyclic ester (lactone) form, dependent on water content. Indeed, drying mixtures of gluconic acid, even under ambient conditions, will induce lactonization (with loss of H₂O) to the δ-gluconolactone (Fig. S9). In this study, we dried a 49–53 wt% solution of gluconic acid in water using a rotary evaporator, at RT. The product was dissolved into the electrolyte and an HSQC spectrum was recorded (Fig. S9a). The HSQC spectrum clearly shows two separate spin-systems, i.e. open-chain and lactone forms. Both were assigned using 2D HSQC-TOCSY and compared with the HSQC spectrum for pure δ-gluconolactone (Fig. S10). Spectra of glucuronic acid (α- and β-anomers) were also taken for reference and can be found in the Supporting Information (Fig. S12-S13).

A water slurry of LDP-CNCs (15 wt%) was oxidized under mild acidic conditions (pH 5.8) with AcNH-TEMPO, in the presence of the NaClO/NaClO₂ oxidant system (see Supporting Information). Pinnick oxidation conditions were chosen to ensure complete conversion of aldehyde species to carboxylates. Water soluble (high degree of oxidation (DO)) and a water insoluble (low DO) samples were recovered and separated by centrifugation. However, as the highly oxidized sodium carboxylate samples do not dissolve in the electrolyte, we were forced to acidify (Fujisawa et al. 2010) the fractions, for further NMR analysis. The principal structure of polyglucuronic acid is represented in Fig. 1f, with the AGA unit as the oxidized polymeric unit.

While the insoluble fraction expectedly consisted of minimally oxidized cellulose, the soluble TOx-LDP-CNC fraction had clearly identifiable correlations in the HSQC not corresponding to polymeric glucose resonances (Fig. 4). As with previous samples, the resonances for the AGA units were assigned using HSQC-TOCSY (Fig. S23-S26) but also using HMBC (Fig. S27), to further illustrate the linkage of the carboxylates C-6 to the H-5 position. The assignments for the AGA units were fully consistent with those of ¹³C assignments for polyglucuronic acid in D₂O (Table S7 of the Supporting Information), from TEMPO oxidation of cellulose (Tahiri and Vignon 2000; Isogai et al. 2011). The RE and NRE peaks corresponding to glucose terminated chains are also assignable. One might assume that the NRE C6-OHs should be more accessible to oxidation than any other C6-OH. However, they are clearly present with the NRE more abundant than the RE signals, requiring scaling of the spectra close to the background to visualize the RE signals (Fig. 4-inset).

Both the common nitroxyl-radical and Pinnick oxidation conditions should lead to oxidation of the reducing ends to carboxylates (Fig. 5). The Pinnick (acidic chlorite) oxidation at the reducing ends of CNCs is commonly used as the first step in reducing end functionalization, typically via amide formation and leading to nano-structures with self-assembly potential (Villares et al. 2018; Lin et al. 2019). To aid in the assignment of the terminal units in the oxidized products, we obtained a commercial sample of cellobionic acid and analyzed it in the [P₄₄₄₄][OAc]:DMSO-d₆ electrolyte (Fig. 5). A doubling of the peaks was observed, consistent with partial conversion to the lactone form. The sample was also observed to be somewhat unstable at 65 °C, presumably decomposing by oligomerization. Therefore, the four spin-systems were assigned at 27 °C using HSQC-TOCSY (Fig. S29) and the two spin-systems corresponding to the acid form were identified by adding a drop of water into the NMR tube, allowing for almost complete conversion of the lactone form to the acid form (Fig. S31). The final assignments for the mixture of compounds at 65 °C showed little deviation from the sample at 27 °C. Thus, suitable model assignments for the oxidized reducing ends were afforded by the open-chain acid and closed-chain lactone spin-systems (Fig. 6).

Under nitroxyl-radical oxidation conditions (Hirota et al. 2009) we would have expected that the RE-1 position would have also been completely oxidized to carboxylates. However, expansion of the acetal region in the HSQC of the TOx-LDP-CNCs and increase in intensity shows presence of residual anomeric CH-1 resonances (Fig. 4a, inset). Clearly, complete oxidation of the reducing ends has not occurred. In addition to the cellobionic acid model compound, a further oxidation of the LDP-CNCs was performed under Pinnick oxidation conditions to allow for a more complete conversion of the reducing ends to gluconate moieties (or to the corresponding lactone). The HSQC spectrum for the oxidized POx-LDP-CNC product (Fig. 7a), where the spectral scale was increased to emphasize the baseline signals, shows signals corresponding to the open-chain acid spin-system, almost identical to that of cellobionic acid but signals corresponding to the closed-chain lactone form are absent. Reducing end signals are also present, again indicating incomplete oxidation. Similarly, if the nitroxyl-radical oxidized sample is also scaled to a similar scale, emphasizing baseline signals, the same peaks corresponding to the open-chain acid form are present (Fig. 7b). HSQC-TOCSY spectra of both these samples (Fig S29-S30) also allow for tracing of the spin-system, consistent with the cellobionic acid model (Fig S28). Therefore, there are now unequivocal solution-state NMR assignments for this functional moiety, which can be used for further understanding/optimization of associated chemistry.

Finally, a typical procedure for periodate oxidation (NaIO₄) of cellulose nanocrystals (CNCs) was performed (Nypelö et al. 2018). The resulting NaIO₄–CNCs were then dissolved in the electrolyte and analyzed. After analysis of the samples (overnight at 65 °C) the sample was brown, whereas other cellulose samples (nitroxyl-radical-oxidized and unoxidized) did not colorize significantly at all. This may indicate some kind of degradation or possibly iodine formation, from (per)iodate residues. The HSQC spectrum showed a forest of peaks (Fig. 8), clustered mainly around the CH2-5 region and from the high resolution of many of the signals in the ¹H spectrum (Fig. 8, top ¹H trace) it is quite clear that significant depolymerization had occurred. However, when the diffusion-edited ¹H spectrum (diffusion-editing filters out the slow-diffusing species) was collected (Fig. 8, bottom ¹H trace), broad signals corresponding to polymeric cellulose resonances were apparent. Based on our previous assignments for glucose (Fig. S5), cellobiose (Fig. 2) and cellulose (Fig. 3), almost all the correlations in the HSQC could be assigned, with only a few signals remaining unassigned. This indicated that a significant proportion of the cellulose was fragmented into glucose, cellobiose and likely other oligomers. Yet, polymeric cellulose also remained.

Hosoya et al. (2018) recently demonstrated that oxidation of cellulose at position 6 to carboxylate does not seem to introduce instability to cellulose, based on experimental kinetics and transition-state modelling. However, oxidation at positions 2 & 3 to ketones, and position 6 to aldehyde, does seem to introduce significant instability to cellulose. It is proposed that under alkaline conditions, β-elimination occurs leading to fragmentation of the sugar units. As the [P₄₄₄₄][OAc]:DMSO-d₆ NMR electrolyte is rather a basic media, mainly attributable to the acetate anion and absence of any protic solvating species, it is apparent that the position 2 & 3 aldehydes that are formed during periodate oxidation also introduce significant instability to the cellulose polymer. Therefore, a mechanism can be proposed (Fig. 9) which accounts for the current NMR observations: periodate oxidation proceeds by oxidizing different points along cellulose chains, on the surface of the CNCs. After dissolution into the basic electrolyte, fragmentation at these oxidation sites occurs liberating the oligomeric, dimeric and monomeric sugars which linked the oxidation points on the surface chains. These are clearly resolvable using HSQC. Likewise, the untouched polymeric chains at the core of the CNCs are also resolvable and their presence is clearly illustrated through the diffusion-edited ¹H spectrum, which filters out all low molecular-weight monomeric, dimeric and oligomeric species. This proposed mechanism is also consistent with previous mechanistic studies demonstrating that periodate oxidation on cellulose proceeds heterogeneously, by formation of oxidized domains on the crystallite surfaces (Kim et al. 2000). The ‘unknown’ low molecular weight residues, that remain unassigned in the HSQC (Fig. 8), may correspond to fragments not attached to the polymeric units, resulting from C2–C3 bond cleavage. Closer examination of the diffusion-edited ¹H and HSQC spectra (Fig. S34) reveals some more complexity in the (hemi)acetal region, which may result from acetal formation with these fragments.

While it seems that periodate oxidation introduces instability through β-elimination under basic conditions, this method seems to allow for assessment of that stability and may offer a further method for validating the reported increase in stability of further modification schemes, e.g., through borohydride reduction of periodate-oxidized cellulose (Potthast et al. 2009).

One drawback of solution-state ¹³C NMR analysis is the low abundance of ¹³C-nucleus leading to low sensitivity. Thus, high numbers of repetitions are required in order to obtain decent S/N ratios, for adequate quantitation accuracy. This is exacerbated by the requirement for longer relaxation delays. However, there is an increasing trend of deconvolution of ¹H spectra of polymers, as S/N is much better than for ¹³C. Of course, not all ¹H resonance signals are easily identified and separated by deconvolution, due to the lower resolution of ¹H. Baseline correction can also be problematic and if one wishes to quantify the RE and NRE signals using this method, the errors very rapidly become large at a DP_N of > 100 (Holding et al. 2016). 2D HSQC provides vastly improved resolution of species over 1D experiments and significantly improved S/N over 1D ¹³C-data, as it is a ¹H-detected experiment. In terms of analysis of celluloses and oxidized celluloses, separation of the main polymeric-1 cross-peak from the (nitroxyl-radical) oxidized polymeric-1 cross-peak and from the α-RE, and β-RE, cross-peaks is now very good using the [P₄₄₄₄][OAc]:DMSO-d₆ electrolyte. This potentially allows for a rapid and reliable method for data extraction; requiring only phasing, baseline correction and 2D correlation peak integration of the raw data. NRE signals have volume overlapping with the main polymeric-1 correlation so this is not so clearly separable, except based on the assumption that there is the same amount of NRE species as there are RE species. The geminal-6 signals are also well separated from the rest of the cellulose backbone signals. Separation of other signals is possible but the error starts to increase the closer they are to each other, due to peak volume overlap. Samples with wider ranges of functionalities, such as lignocellulosic biomass samples or those that have resonances downfield from the cellulose polymeric-1 acetal correlations, are also easily separated.

The major drawbacks with 2D HSQC and polymeric samples are four-fold: 1) differences in ¹ J(¹³C–¹H) values for different ¹³C–¹H pairs cause variations in intensities of those correlations. Typical HSQC experiments assume an average ¹ J(¹³C–¹H) value (typically 145 Hz) for the experiments, represented in a specific INEPT polarization transfer delay. 2) Coherence transfer periods, where sufficient time is given for ¹H magnetization to evolve, cause intensity variation of the correlation peaks as each resonance has different T₂ values, i.e., mainly during the INEPT delay periods, more or less signal is lost for different resonances, prior to acquisition. 3) Correlation-peak distortions arising from evolution of homonuclear J(¹H–¹H) coupling during the INEPT steps can cause errors in integration. 4) Non-linear excitation bandwidth leads to variation of cross-peak signal intensity, especially across the ¹³C frequency range at high field strengths. Several quantitative HSQC sequences or processing strategies have been developed that attempt to correct for these issues. Variations in ¹ J(¹³C–¹H) values have been corrected for by applying INEPT-delay modulation in the first ‘quantitative HSQC’ (Q-HSQC) experiment (Heikkinen et al. 2003). This corresponds to the application of a spread of INEPT delays covering the typical ¹ J(¹³C–¹H) coupling value range expected in organic materials. Signal losses due to variations in T₂ values as well as in ¹ J(¹³C–¹H) values have been accounted for in the ‘time-zero HSQC’ (HSQC₀) experiment (Hu et al. 2011), which records a loop of an increasing train of HSQC sequences (HSQC_X, X = 1–3), prior to actual acquisition. This has the effect of increasing coupling and relaxation effects for each loop, which can be extrapolated back to ‘time-zero’, where potentially all effects are removed. Obviously for HSQC₀, T₂ values have to allow recording of HSQC₂ and HSQC₃ data sets with intensity allowing reliable extrapolation. The ‘quick-quantitative HSQC’ (QQ-HSQC) experiment is a rather elegant method for potentially reducing the collection times by a factor of 4 (Peterson and Loening 2007). This encodes the INEPT-modulation into different vertical slices in the sample but only represents a possible doubling of S/N for the same collection times. However, this is only really applicable for small, slow-relaxing, molecules due to relaxation effects. The ‘quantitative CPMG-adjusted HSQC’ (Q-CAHSQC) experiment (Koskela et al. 2005) applies CPMG-INEPT steps to avoid cross-peak distortions, due to J(¹H–¹H) coupling evolution. The ‘quantitative, offset-compensated, CPMG-adjusted HSQC’ (Q-OCCAHSQC) experiment (Koskela et al. 2010) applies novel broad-band pulses to reduce ¹³C offset errors that are most prevalent on ultrahigh-field instruments, e.g. 1000 MHz, over wider frequency ranges (> 150 ppm). This is not really a concern for cellulose samples on a 600 MHz spectrometer, where the ¹³C domain is rather narrow (< 50 ppm) but may start to become an issue for lignocellulose samples at ultrahigh field. The final sequence of interest is the ‘quantitative, equal carbon HSQC’ (QEC-HSQC) experiment (Mäkelä et al. 2016) where a refocusing period, after the first INEPT step, is used to discard the excess CH₂ and CH₃ magnetization. This yields the same signal intensity for each protonated carbon in the sample. This could potentially be of value in the analysis of lignocellulose samples but is not really necessary at this point for systems where the well separated resonances (and their multiplicities) are already reasonably well assigned. An overview of the different HSQC experiments is given in Table 1.

For our purposes, the Q-CAHSQC sequence seems to be most suitable, if we can correct the processed integral data for T₂ losses. Issues with ¹³C-offset, variation in ¹ J(¹³C–¹H) and relaxation can be accounted for mathematically, to some degree, in post-processing (Zhang and Gellerstedt 2007). The most concerning issue for cellulose is the very fast T₂ relaxation, that the HSQC₀ sequence accounts for, but the other approaches do not. If the T₂ values are known, it is possible to adjust for signal losses by application of Eq. 1, after integration of the 2D HSQC spectra; where ∆ is the delay period in which T₂ losses occur, V is the measured correlation peak volume and V₀ is the theoretical correlation peak volume, with no losses due to relaxation:

In order to apply this correction, T₂ values for the resonances of interest must be measured. Zhang and Gellerstedt (2007) have shown that the 2D HSQC-CPMG sequence for determination of T₂ values of cellulose triacetate, gives inaccurate T₂ values. However, this is a chicken and egg scenario; losses due to the HSQC portion of the sequence obviously contribute to the inaccuracies, which becomes more of an issue where there is very high molecular weight material in the sample due to disproportionate loss of signal from those resonances. Therefore, the lower resolution 1D CPMG is the only real option for determining more representative ‘average’ T₂ values, for such samples. Nevertheless, loss of higher molecular weight signal during the INEPT delays is always going to be a problem. In terms of quantitation of chemical species; if the system is not complex, as is typically in cellulose samples, T₂ values can be relatively easily obtained. As such we determined T₁ and T₂ values for the LDP-CNC, MCC and TOx-LDP-CNC samples (Table 2).

After summing the appropriate delay times leading to T₂ losses, a ∆ value of 13.9 ms was calculated for the Q-CAHSQC sequence, which is in a very similar range to some of the MCC T₂ values. Therefore, considerable signal loss is expected and needs to be corrected for. Equation 1 was applied in the correction of integral values. The main cross-peaks of interest were the polymeric CH-1 (AGU-1), NRE-1, α-RE-1, β-RE-1, oxidized polymeric CH-1 (AGA-1), AGU-gem-6 and oxidized RE-6 position (Ox-RE-gem-6). The MCC sample also clearly contained a little xylan, so the xylan 1 (AXU-1) and geminal-5 (AXU-gem-5) positions were also integrated in the MCC sample. The corrected results are given in Table 3 and were processed further to yield a few additional parameters: (1) the ratio of AGU-1 to AGU-gem-6 (AGU_1/6), (2) the DP_N from HSQC (DP_N-HSQC). (3) The % values of α-RE-1 by HSQC (%_α-HSQC) and β-RE-1 by HSQC (%_β-HSQC), (4) The % values for AXU based on AXU-1 (%_AXU-1) and AXU-gem-5 (%_AXU-5). 5) The % values for oxidation of AGU to AGA (%_AGA) and RE (%_RE-Ox). In addition to the processed HSQC data, we have data from deconvolution of the ¹H spectra, for comparison: 1) the DP_N from ¹H (DP\(_{\text{N-}{^1}\text{H}}\)), 2) The % values of α-RE-1 by ¹H (%α-¹H) and β-RE-1 by ¹H (%β -¹H).

Clearly the T₂ correction has a big impact on the integral values, especially for those with short T₂ values, i.e. for the bulk polymeric AGU-1 and AGU-gem-6. As these positions are most likely to be used for quantitation, e.g. of DS values, it is clearly critical to do the T₂ correction. To compare how effective the quantitation is, the parameter AGU_1/6 shows how accurate integration of AGU-1 and AGU-gem-6 is, with the optimum value of 1. For the LDP-CNC sample, the value improves significantly after T₂ correction. For the MCC experiments, the lower-resolution but higher S/N experiments (ns = 40, td1 = 128) gave a value of 1.00 and 0.96, for the room temperature probe-head and He-cooled cryoprobe-head, respectively. This indicates that making all efforts to maximize S/N is critical for quantitation, even at the expense of resolution. The TOx-LDP-CNC sample also gave a significant improvement in AGU_1/6, from 0.57 to 0.95. DP_N-HSQC values also changed significantly and the corrected values were more or less consistent with the DP\(_{\text{N-}{^1}\text{H}}\) values. There is a noticeable difference between the DP_N-GPC and those obtained from NMR. More accurate studies validating the use of NMR against both labelling and GPC studies are needed. Practically, the HSQC method is still limited in what samples can be studied for DP_N-HSQC determination, as better S/N will be required with increases in molecular weight. For the same reason that HSQC-CPMG is not suitable for T₂ determination, for cellulose samples, HSQC on such samples is going to eliminate a significant proportion of the faster relaxing high molecular weight material, artificially decreasing the DP_N-HSQC values somewhat. The ratios of α-RE-1 and β-RE-1 were relatively consistent between the corrected and uncorrected values, for HSQC and ¹H deconvolution. However, clearly the lower abundance of RE resonances for MCC causes significant error, although, this situation can be improved using a cryoprobe-head and possibly linear prediction. AXU contents for the two MCC experiments were relatively consistent, based on AXU-gem-5 integration. However, the higher resolution experiment gave more consistent values, based on integration of AXU-1 and AXU-gem-5, as the separation of these peaks from the cellulose resonances was much better in the higher resolution case. The degrees of oxidation for TOx-LDP-CNC, %_AGA and %_RE-Ox, were also relatively consistent.

Overall, the CH1 peaks for the low molecular weight LDP-CNC and TOx-LDP-CNC samples are easily separable with 512 f1 increments (td1), or perhaps even less (of course depending on field strength), due to their slower T₂ relaxation (Fig. 10a, b). With the higher molecular weight MCC, separation of the CH1 resonances is definitely improved with the higher number of increments (Fig. 10c, d). While there is sufficient separation of the RE-1 and AGU-1 signals, so that f1 resolution can be lowered further (to allow for increased collection times), poor S/N is still an issue for the RE-1 signal in both spectra (Fig. 10c, d). This situation is improved somewhat with the use of the cryoprobe-head, where S/N is approximately doubled (Table 3). However, if quantitation of DS values is all that is required, lower resolutions are acceptable to reduce collection times to a few hr. If resolution eventually does become an issue in quantitation of the DS of some substituent, for higher molecular weight samples, then ball milling will likely have to be applied to reduce molecular weights (Ling et al. 2019), preventing disproportionate T₂ losses. However, this requires future work with well-defined samples over wide molecular weight ranges, both polydisperse and non-polydisperse.

This method is ideally suited to the analysis of nanocelluloses, due to the relatively low molecular weight that these samples show, in particular CNCs. However, higher molecular weight samples are also possible, which makes this method of significant wider value for following cellulose surface chemistry, where crystallinity is maintained. Indeed, it has been possible to dissolve and collect an HSQC spectrum for even bacterial nanocellulose, in a related solvent system (Holding et al. 2016). The main limitation here is the faster signal relaxation, which would have a significant effect on any HSQC quantitation, relative to the cellulose backbone signals. However, quantitation through 1D spectra, with the aid of signal deconvolution, would not be affected. Thus, a combination of 1D and 2D methods can be applied, optionally using the [P₄₄₄₄]⁺ signals themselves as internal standard.

Several solvent systems are known for analysis of whole biomass samples (Foston et al. 2016). Mansfield et al. (2012) have recommended the use of routine HSQC experiments for quantifying biopolymer species, in whole biomass samples. Their protocol demonstrates the swelling of planetary-milled wood samples in DMSO-d₆/pyridine-d₅ (4:1) to yield ‘gelled’ samples, yet with a solvent mixture that is unable to directly dissolve cellulose. This method was said to yield similar quantitation results to those samples which are fully processed into the solution-state, by peracetylation. However, wood samples are a difficult case, not only due to the insolubility of cellulose in common molecular solvents but also due to their recalcitrant nature, in general (Deb et al. 2016; Kyllönen et al. 2013; Kilpeläinen et al. 2007). Thus, there is still some way to go to establish quantitative conditions for whole biomass samples, even with non-derivatizing direct-dissolution cellulose solvents. The cellulose portion of these materials is always the most troublesome as it is such a rigid polymer, which suffers from fast T₂ relaxation. However, if extensive milling is applied to allow for full solubilization and low enough molecular weight (further increasing T₂ values), more accurate quantitation may be close. In this context, suitable stable direct-dissolution solvents for solution-state NMR analysis of whole biomass samples has been something that has also been lacking. Cheng et al. (2013) have already demonstrated this principal, by complete dissolution and analysis of ball-milled Miscanthus into a mixture of the cellulose-dissolving ionic liquid 1-ethyl-3-methylimidazolium acetate ([emim][OAc]) in DMSO-d₆. Perdeuterated [emim][OAc] ([emim][OAc]-d₁₄):DMSO-d₆ was then prepared and used for the application of a quantitative HSQC experiment on fully dissolved solutions. However, as mentioned previously, [emim][OAc] is known to react with cellulose (Liebert and Heinze 2008; Ebner et al. 2008, Clough et al. 2015). It also has significant signal overlap with the polysaccharide spectral region and [emim][OAc]-d₁₄ is much too expensive and laborious to prepare, for routine analyses. Nevertheless, the [emim][OAc]:DMSO-d₆ solutions were shown to be stable over a longer period (2 weeks), whereas the molecular solvent dispersions showed phase-separation. This is a good indication that the current solvent-system may open the window to a much wider range of samples.