A holistic NMR framework to understand environmental impact: Examining the impacts of superparamagnetic iron oxide nanoparticles (SPIONs) in Daphnia magna via imaging, spectroscopy, and metabolomics.

Superparamagnetic iron oxide nanoparticles (SPIONs) are a contaminant of emerging interest, often used in the medical field as an imaging contrast agent, with additional uses in wastewater treatment and as food additives. Although the use of SPIONs is increasing, little research has been conducted on the toxic impacts to living organisms beyond traditional lethal concentration endpoints. Daphnia magna are model organisms for aquatic toxicity testing with a well understood metabolome and high sensitivity to SPIONs. Thus, as environmental concentrations continue to increase, it is becoming critical to understand their sub-lethal toxicity. Due to the paramagnetic nature of SPIONs, a range of potential nuclear magnetic resonance spectroscopy (NMR) experiments are possible, offering the potential to probe the physical location (via imaging), binding (via relaxation weighted spectroscopy), and the biochemical pathways impacted (via in vivo metabolomics). Results indicate binding to carbohydrates, likely chitin in the exoskeleton, along with a decrease in energy metabolites and specific biomarkers of oxidative stress. The holistic NMR framework used here helps provide a more comprehensive understanding of SPIONs impacts on D. magna and showcases NMR's versatility in providing physical, chemical, and biochemical insights.

Analysis of water content in wood material through 1D and 2D 1 H NMR relaxometry: Application to the determination of the dry mass of wood.

There is an increasing interest on wood as it is an environmentally sustainable product (e.g., biodegradable and renewable). Thus, an accurate characterisation of wood properties is of extreme importance as they define the kind of application for which each type of wood can be used. For instance, dry mass of wood is a key parameter itself and is needed to calculate Moisture Content (MC) of wood, which is correlated to its physical properties. Due to the limitations of commonly used drying methods, preliminary work has shown the potential of 1 H NMR to measure dry mass of wood, but it has never been validated. Here, we performed a critical analysis of 1D and 2D 1 H NMR relaxometry methods for obtaining the dry mass of wood, and we compared their performance to three commonly used drying methods. This showed that commonly used drying methods do not remove all water from wood. Moreover, we are able to classify them accordingly to their performance. In addition, we showed that MC values obtained by 1 H NMR relaxometry methods are higher (up to 20%) than values from commonly used drying methods. This empathises the importance of accurate values of dry mass of wood and the utility of 1 H NMR relaxometry on wood sciences. When comparing both NMR relaxometry methods, 2D should provide the more accurate results, but 1D measurements would also be a recommended choice as they are faster than 2D and their results clearly overcome commonly used drying methods in a noninvasive and nondestructive manner.

Novel Experimental-Modeling Approach for Characterizing Perfluorinated Surfactants in Soils.

Soil contamination is still poorly understood and modeled in part because of the difficulties of looking inside the "black box" constituted by soils. Here, we investigated the application of a recently developed 1H NMR technique to 19F NMR relaxometry experiments and utilized the results as inputs for an existing model. This novel approach yields 19F T2 NMR relaxation values of any fluorinated contaminant, which are among the most dangerous contaminants, allowing us to noninvasively and directly monitor their fate in soils. Using this protocol, we quantified the amount of a fluorinated xenobiotic (heptafluorobutyric acid, HFBA) in three different environments in soil aggregate packings and monitored contaminant exchange dynamics between these compartments. A model computing HFBA partition dynamics between different soil compartments showed that these three environments corresponded to HFBA in solution (i) between and (ii) inside the soil aggregates and (iii) to HFBA adsorbed to (or strongly interacting with) the soil constituents. In addition to providing a straightforward way of determining the sorption kinetics of any fluorinated contaminant, this work also highlights the strengths of a combined experimental-modeling approach to unambiguously understand experimental data and more generally to study contaminant fate in soils.

Soil Organic Matter in Its Native State: Unravelling the Most Complex Biomaterial on Earth.

Since the isolation of soil organic matter in 1786, tens of thousands of publications have searched for its structure. Nuclear magnetic resonance (NMR) spectroscopy has played a critical role in defining soil organic matter but traditional approaches remove key information such as the distribution of components at the soil-water interface and conformational information. Here a novel form of NMR with capabilities to study all physical phases termed Comprehensive Multiphase NMR, is applied to analyze soil in its natural swollen-state. The key structural components in soil organic matter are identified to be largely composed of macromolecular inputs from degrading biomass. Polar lipid heads and carbohydrates dominate the soil-water interface while lignin and microbes are arranged in a more hydrophobic interior. Lignin domains cannot be penetrated by aqueous solvents even at extreme pH indicating they are the most hydrophobic environment in soil and are ideal for sequestering hydrophobic contaminants. Here, for the first time, a complete range of physical states of a whole soil can be studied. This provides a more detailed understanding of soil organic matter at the molecular level itself key to develop the most efficient soil remediation and agricultural techniques, and better predict carbon sequestration and climate change.

From Spill to Sequestration: The Molecular Journey of Contamination via Comprehensive Multiphase NMR.

Comprehensive multiphase NMR is a novel NMR technique that permits all components (solutions, gels, and solids) to be studied in unaltered natural samples. In this study a wide range of CMP-NMR interaction and editing-based experiments are combined to follow contaminants (pentafluorophenol (PFP) and perfluorooctanoic acid (PFOA)) from the solution state (after a spill) through the gel-state and finally into the true solid-state (sequestered) in an intact water-swollen soil. Kinetics experiments monitoring each phase illustrate PFOA rapidly transfers from solution to the solid phase while for PFP the process is slower with longer residence times in the solution and gel phase. Interaction-based experiments reveal that PFOA enters the soil via its hydrophobic tails and selectively binds to soil microbial protein. PFP sorption shows less specificity exhibiting interactions with a range of gel and solid soil components with a preference toward aromatics (mainly lignin). The results indicate that in addition to more traditional measurements such as Koc, other factors including the influence of the contaminant on the soil-water interface, specific biological interactions, soil composition (content of lignin, protein, etc.) and physical accessibility/swellability of soil organic components will likely be central to better explaining and predicting the true behavior of contaminants in soil.

Comprehensive multiphase NMR: a promising technology to study plants in their native state.

Nuclear magnetic resonance (NMR) spectroscopy is arguably one the most powerful tools to study the interactions and molecular structure within plants. Traditionally, however, NMR has developed as two separate fields, one dealing with liquids and the other dealing with solids. Plants in their native state contain components that are soluble, swollen, and true solids. Here, a new form of NMR spectroscopy, developed in 2012, termed comprehensive multiphase (CMP)-NMR is applied for plant analysis. The technology composes all aspects of solution, gel, and solid-state NMR into a single NMR probe such that all components in all phases in native unaltered samples can be studied and differentiated in situ. The technology is evaluated using wild-type Arabidopsis thaliana and the cellulose-deficient mutant ectopic lignification1 (eli1) as examples. Using CMP-NMR to study intact samples eliminated the bias introduced by extraction methods and enabled the acquisition of a more complete structural and metabolic profile; thus, CMP-NMR revealed molecular differences between wild type (WT) and eli1 that could be overlooked by conventional methods. Methanol, fatty acids and/or lipids, glutamine, phenylalanine, starch, and nucleic acids were more abundant in eli1 than in WT. Pentaglycine was present in A. thaliana seedlings and more abundant in eli1 than in WT.

Water scaffolding in collagen: Implications on protein dynamics as revealed by solid-state NMR.

Solid-state NMR studies of collagen samples of various origins confirm that the amplitude of collagen backbone and sidechain motions increases significantly on increasing the water content. This conclusion is supported by the changes observed in three different NMR observables: (i) the linewidth dependence on the 1H decoupling frequency; (ii) 13C CSA changes for the peptide carbonyl groups, and (iii) dephasing rates of 1H-13C dipolar couplings. In particular, a nearly threefold increase in motional amplitudes of the backbone librations about C-Cα or N-Cα bonds was found on increasing the added water content up to 47 wt%D2 O. On the basis of the frequencies of NMR observables involved, the timescale of the protein motions dependent on the added water content is estimated to be of the order of microseconds. This estimate agrees with that from wideline T2(1)H NMR measurements. Also, our wideline 1H NMR measurements revealed that the timescale of the microsecond motions in proteins reduces significantly on increasing the added water content, i.e., an ∼15-fold increase in protein motional frequencies is observed on increasing the added water content to 45 wt% D2 O. The observed changes in collagen dynamics is attributed to the increase in water translational diffusion on increasing the amount of added water, which leads to more frequent "bound water/free water" exchange on the protein surface, accompanied by the breakage and formation of new hydrogen bonds with polar functionalities of protein.

Tracking the fate of microbially sequestered carbon dioxide in soil organic matter.

The microbial contribution to soil organic matter (SOM) has recently been shown to be much larger than previously thought and thus its role in carbon sequestration may also be underestimated. In this study we employ (13)C ((13)CO2) to assess the potential CO2 sequestration capacity of soil chemoautotrophic bacteria and combine nuclear magnetic resonance (NMR) with stable isotope probing (SIP), techniques that independently make use of the isotopic enrichment of soil microbial biomass. In this way molecular information generated from NMR is linked with identification of microbes responsible for carbon capture. A mathematical model is developed to determine real-time CO2 flux so that net sequestration can be calculated. Twenty-eight groups of bacteria showing close homologies with existing species were identified. Surprisingly, Ralstonia eutropha was the dominant group. Through NMR we observed the formation of lipids, carbohydrates, and proteins produced directly from CO2 utilized by microbial biomass. The component of SOM directly associated with CO2 capture was calculated at 2.86 mg C (89.21 mg kg(-1)) after 48 h. This approach can differentiate between SOM derived through microbial uptake of CO2 and other SOM constituents and represents a first step in tracking the fate and dynamics of microbial biomass in soil.

Concise NMR approach for molecular dynamics characterizations in organic solids.

Molecular dynamics characterisations in solids can be carried out selectively using dipolar-dephasing experiments. Here we show that the introduction of a sum of Lorentzian and Gaussian functions greatly improve fittings of the "intensity versus time" data for protonated carbons in dipolar-dephasing experiments. The Lorentzian term accounts for remote intra- and intermolecular (1)H-(13)C dipole-dipole interactions, which vary from one molecule to another or for different carbons within the same molecule. Thus, by separating contributions from weak remote interactions, more accurate Gaussian decay constants, T(dd), can be extracted for directly bonded (1)H-(13)C dipole-dipole interactions. Reorientations of the (1)H-(13)C bonds lead to the increase of T(dd), and by measuring dipolar-dephasing constants, insight can be gained into dynamics in solids. We have demonstrated advantages of the method using comparative dynamics studies in the α and γ polymorphs of glycine, cyclic amino acids L-proline, DL-proline and trans-4-hydroxy-L-proline, the Ala residue in different dipeptides, as well as adamantane and hexamethylenetetramine. It was possible to distinguish subtle differences in dynamics of different carbon sites within a molecule in polymorphs and in L- and DL-forms. The presence of overall molecular motions is shown to lead to particularly large differences in dipolar-dephasing experiments. The differences in dynamics can be attributed to differences in noncovalent interactions. In the case of hexamethylenetetramine, for example, the presence of C-H···N interactions leads to nearly rigid molecules. Overall, the method allows one to gain insight into the role of noncovalent interactions in solids and their influence on the molecular dynamics.

Rapid parameter optimization of low signal-to-noise samples in NMR spectroscopy using rapid CPMG pulsing during acquisition: application to recycle delays.

A method is presented that combines Carr-Purcell-Meiboom-Gill (CPMG) during acquisition with either selective or nonselective excitation to produce a considerable intensity enhancement and a simultaneous loss in chemical shift information. A range of parameters can theoretically be optimized very rapidly on the basis of the signal from the entire sample (hard excitation) or spectral subregion (soft excitation) and should prove useful for biological, environmental, and polymer samples that often exhibit highly dispersed and broad spectral profiles. To demonstrate the concept, we focus on the application of our method to T(1) determination, specifically for the slowest relaxing components in a sample, which ultimately determines the optimal recycle delay in quantitative NMR. The traditional inversion recovery (IR) pulse program is combined with a CPMG sequence during acquisition. The slowest relaxing components are selected with a shaped pulse, and then, low-power CPMG echoes are applied during acquisition with intervals shorter than chemical shift evolution (RCPMG) thus producing a single peak with an SNR commensurate with the sum of the signal integrals in the selected region. A traditional (13)C IR experiment is compared with the selective (13)C IR-RCPMG sequence and yields the same T(1) values for samples of lysozyme and riverine dissolved organic matter within error. For lysozyme, the RCPMG approach is ~70 times faster, and in the case of dissolved organic matter is over 600 times faster. This approach can be adapted for the optimization of a host of parameters where chemical shift information is not necessary, such as cross-polarization/mixing times and pulse lengths.

Tailoring 1H spin dynamics in small molecules via supercooled water: a promising approach for metabolite identification and validation.

Metabolic mixtures are often analyzed via NMR spectroscopy as it provides a metabolic profile without sample alteration in a noninvasive manner. These mixtures however tend to be very complex and demonstrate considerable spectral overlap resulting in assignments that are sometimes ambiguous given the range of current NMR methods available. De novo molecular identification in these mixtures is generally accomplished using chemical shift information and J-coupling based experiments to determine spin connectivity information, but these techniques fall short when a molecule of interest contains nonrelaying centers. A method is presented here that enhances intramolecular spatial interactions via supercooled water and uses the resulting spatial correlations to edit mixtures. This is accomplished by utilizing nuclear Overhauser effect spectroscopy (NOESY) at subzero temperatures in capillaries to enhance NOE and provide more complete spin systems. This technique is applied to a standard mixture of three known molecules in D(2)O with overlapping resonances and is further demonstrated to assign molecules in a worm tissue extract. The current method proves to be a powerful complement to existing methods such as total correlation spectroscopy (TOCSY) to expand the range of molecules that can be assigned in situ without physical separation of mixtures.

In-situ molecular-level elucidation of organofluorine binding sites in a whole peat soil.

The chemical nature of xenobiotic binding sites in soils is of vital importance to environmental biogeochemistry. Interactions between xenobiotics and the naturally occurring organic constituents of soils are strongly correlated to environmental persistence, bioaccessibility, and ecotoxicity. Nevertheless, because of the complex structural and chemical heterogeneity of soils, studies of these interactions are most commonly performed indirectly, using correlative methods, fractionation, or chemical modification. Here we identify the organic components of an unmodified peat soil where some organofluorine xenobiotic compounds interact using direct molecular-level methods. Using (19)F→(1)H cross-polarization magic angle spinning (CP-MAS) nuclear magnetic resonance (NMR) spectroscopy, the (19)F nuclei of organofluorine compounds are used to induce observable transverse magnetization in the (1)H nuclei of organic components of the soil with which they interact after sorption. The observed (19)F→(1)H CP-MAS spectra and dynamics are compared to those produced using model soil organic compounds, lignin and albumin. It is found that lignin-like components can account for the interactions observed in this soil for heptafluoronaphthol (HFNap) while protein structures can account for the interactions observed for perfluorooctanoic acid (PFOA). This study employs novel comprehensive multi-phase (CMP) NMR technology that permits the application of solution-, gel-, and solid-state NMR experiments on intact soil samples in their swollen state.

Response of water-biochar interactions to physical and biochemical aging.

Biochar aging may affect the interactions of biochar with water and thus its performance as soil amendment; yet the specific mechanisms underlying these effects are poorly understood. By means of FTIR, N2 adsorption, Hg intrusion porosimetry, thermogravimetric analysis, 13C solid state nuclear magnetic resonance (NMR) and 1H NMR relaxometry, we investigated changes in the chemistry and structure of biochar as well as its interaction with water after biochar aging, both physical (simulated by ball-milling) and biochemical (simulated by co-composting). Three different porosities of biochar were examined: <5 nm, 1 µm and 10 µm diameter sizes. Physical aging caused the disappearance of the porosity at 10 µm. With biochemical aging, biochar underwent an enrichment of oxygenated functional groups either as a result of surface functionalisation processes or by the deposition of fresh organic matter layers on the surface and pores of biochar. 1H NMR relaxometry revealed that the proportion of water strongly interacting with biochar increased with both physical and biochemical aging. Although biochemical aging significantly altered the composition of biochar surface and modulates its interaction with water, 1H NMR relaxometry proved that physical aging had a relatively stronger influence on water mobility and dynamics in biochar, lowering both T1 and T2 relaxation times in the initial contact times of biochar and water.

A facile synthesis of pyrrolo-(di)-benzazocinones via an intramolecular N-acyliminium ion cyclisation.

A facile, moderate to high yielding synthesis of hexahydro-(di)-benzazocinones is described via an intramolecular N-acyliminium ion cyclisation. The iminium ion intermediates are formed from the readily available 4,4-diethoxybutyl amides with an excess of triflic acid. For electron-withdrawing substituents, better yields were obtained from the pre-formed 2-hydroxypyrrolidine amides. From NMR studies, at ambient temperatures the pyrrolo-benzazocin-3-ones exist as a slowly equilibrating mixture of two conformations.

Quantum mechanical and NMR studies of ring puckering and cis/trans-rotameric interconversion in prolines and hydroxyprolines.

Nuclear magnetic resonance (NMR) and quantum mechanical (QM) studies have been carried out for proline (Pro) containing peptides: N-acetyl-l-proline (AcProOH) and N-acetyl-4-hydroxy-l-proline (AcHypOH). Preliminary results of variable temperature NMR measurements for Gly-Pro-Gly-Gly (GPGG), Val-Ala-Pro-Gly (VAPG), and Ala-Pro-Gly-Trp amide acetate salt (APGW) are also reported. The effect of solvent (D(2)O, DMSO-d(6) and CD(3)CN) on the pyrrolidine ring conformation and cis/trans-rotamerisation along the amide bond preceding Pro was investigated by temperature dependent NMR followed by detailed transition state (TS) searches for both conformational equilibria using QM methods. The results revealed the energetic characteristics of the TS, which were in satisfactory agreement with NMR, and the corresponding TS geometries, which are not available from experiment. The most remarkable feature of the cis/trans-rotamerisation is that the amide nitrogen in AcProOH and AcHypOH adopts a tetrahedral geometry in the TS. Various HF, DFT, and MP2 calculations together with implicit solvation modeling were employed in order to identify the most suitable QM protocols for reliable predictions of the geometry and the relative energies of the conformations of Pro and Hyp containing peptides in aqueous solution. Solution NMR results were used for the verification of the reliability of the QM predictions. The results indicate that the MP2 calculations combined with implicit solvation models are reasonably accurate in reproducing NMR measured populations of four different conformations of either AcProOH or AcHypOH in different solvents, whereas HF and DFT B3LYP calculations were significantly less accurate.

Conformational analysis of L-prolines in water.

The results of the ring conformational analysis of L-proline, N-acetyl-L-proline, and trans-4-hydroxy-L-proline by NMR combined with calculations using density functional theory (DFT) and molecular dynamics (MD) are reported. Accurate values of 1H-1H J-couplings in water and other solvents have been determined. Using a two-site equilibrium model, the Cgamma-endo conformer of L-proline in water has been identified as intermediate between gammaTdelta [twist(Cgamma-endo, Cdelta-exo)] and gammaE [envelope(Cgamma-endo)] and the Cgamma-exo conformer as betaTgamma. Both conformers were equally populated at room temperature. The N-acetyl [cis-rotamer gammaTbeta(80%)/gammaE(20%) and trans-rotamer gammaTbeta(61%)/gammaE(39%)] and 4-hydroxy (gammaEpsilon) derivatives showed significant changes in both the population and the geometries of the preferred ring conformers. The combination of NMR predicted populations with the DFT B3LYP/6-311+G(2d,p)/IEFPCM calculations proved successful, resulting in fairly accurate predictions of J-couplings. Simulations using MD were mostly in favor of the two-site equilibrium model between Cgamma-endo and Cgamma-exo conformers, similar to that used for the analysis of NMR J-couplings. Various force fields examined for MD simulations failed to reproduce the ring conformational geometries and populations of L-proline in water accurately, while significantly better agreement with NMR was found for trans-N-acetyl-L-proline using GROMOS and AMBER force fields.

Combined time-lapse magnetic resonance imaging and modeling to investigate colloid deposition and transport in porous media.

Colloidal particles can act as vectors of adsorbed pollutants in the subsurface, or be themselves pollutants. They can reach the aquifer and impair groundwater quality. The mechanisms of colloid transport and deposition are often studied in columns filled with saturated porous media. Time-lapse profiles of colloid concentration inside the columns have occasionally been derived from magnetic resonance imaging (MRI) data recorded in transport experiments. These profiles are valuable, in addition to particle breakthrough curves (BTCs), for testing and improving colloid transport models. We show that concentrations could not be simply computed from MRI data when both deposited and suspended colloids contributed to the signal. We propose a generic method whereby these data can still be used to quantitatively appraise colloid transport models. It uses the modeled suspended and deposited particle concentrations to compute modeled MRI data that are compared to the experimental data. We tested this method by performing transport experiments with sorbing colloids in sand, and assessed for the first time the capacity of the model calibrated from BTCs to reproduce the MRI data. Interestingly, the dispersion coefficient and deposition rate calibrated from the BTC were respectively overestimated and underestimated compared with those calibrated from the MRI data, suggesting that these quantities, when determined from BTCs, need to be interpreted with care. In a broader perspective, we consider that combining MRI and modeling offers great potential for the quantitative analysis of complex MRI data recorded during transport experiments in complex environmentally relevant porous media, and can help improve our understanding of the fate of colloids and solutes, first in these media, and later in soils.

A nuclear magnetic resonance study of the dynamics of organofluorine interactions with a dissolved humic acid.

A quantitative understanding of the dynamics of the interactions between organofluorine compounds and humic acids will contribute to an improved understanding of the role that Natural Organic Matter plays as a mediator in the fate, transport and distribution of these contaminants in the environment. Here, Nuclear Magnetic Resonance (NMR) spectroscopy-based diffusion measurements are used to estimate the association dynamics between dissolved humic acid and selected organofluorine compounds: pentafluoroaniline, pentafluorophenol, potassium perfluorooctane sulfonate, and perfluorooctanoic acid. Under the conditions used here, the strength of the association with humic acid increases linearly as temperature decreases for all compounds except for perfluorooctanoic acid, which exhibits divergent behavior with a non-linear decrease in the extent of interaction as temperature decreases. A general interaction mechanism controlled largely by desolvation effects is suggested for all compounds examined here except for perfluorooctanoic acid, which exhibits a specific mode of interaction consistent with a proteinaceous binding site. Reverse Heteronuclear Saturation Transfer Difference NMR is used to confirm the identity and nature of the humic acid binding sites.

The pH-dependence of organofluorine binding domain preference in dissolved humic acid.

In this study we explore the relationship between solution pH and the distribution of the binding interactions at different domains of a dissolved humic acid (HA) for three xenobiotics: pentafluoroaniline (PFA), pentafluorophenol (PFP), and hexafluorobenzene (HFB). The components of HA where xenobiotic interactions occur are identified using the (1)H{(19)F} Reverse Heteronuclear Saturation Transfer Difference (RHSTD) Nuclear Magnetic Resonance (NMR) spectroscopy experiment. At low pH, PFA and PFP interact preferentially with aromatic components of HA. Increasing pH reduces this preference. Conversely, HFB interacts with all components of HA equally, across the entire pH range. The possible roles of both aromatic-specific interactions and conformational changes of HA behind these observations are explored. It is shown that T-oriented π-π interactions at π-electron accepting HA structures are slightly stronger for PFA and PFP than for HFB. Using DOSY NMR it is shown that the pH-dependence of the interactions is correlated with changes in the conformation of the carbohydrate components of HA rather than with the aromatic components. It is argued that the observed preference for aromatic HA is caused by restricted access to the non-aromatic components of HA at low pH. These HA components form tightly bound hydrophobic domains due to strong inter- and intra-molecular hydrogen bonds. At high pH, these structures open up, making them more available for interactions with polar compounds.

Rapid estimation of nuclear magnetic resonance experiment time in low-concentration environmental samples.

Nuclear magnetic resonance (NMR) spectroscopy is an essential tool for studying environmental samples but is often hindered by low sensitivity, especially for the direct detection of nuclei such as(13) C. In very heterogeneous samples with NMR nuclei at low abundance, such as soils, sediments, and air particulates, it can take days to acquire a conventional(13) C spectrum. The present study describes a prescreening method that permits the rapid prediction of experimental run time in natural samples. The approach focuses the NMR chemical shift dispersion into a single spike, and, even in samples with extremely low carbon content, the spike can be observed in two to three minutes, or less. The intensity of the spike is directly proportional to the total concentration of nuclei of interest in the sample. Consequently, the spike intensity can be used as a powerful prescreening method that answers two key questions: (1) Will this sample produce a conventional NMR spectrum? (2) How much instrument time is required to record a spectrum with a specific signal-to-noise (S/N) ratio? The approach identifies samples to avoid (or pretreat) and permits additional NMR experiments to be performed on samples producing high-quality NMR data. Applications in solid- and liquid-state(13) C NMR are demonstrated, and it is shown that the technique is applicable to a range of nuclei.