NMR Crystallography: Evaluation of Hydrogen Positions in Hydromagnesite by 13 C{1 H} REDOR Solid-State NMR and Density Functional Theory Calculation of Chemical Shielding Tensors

Comparison of methods for the NMR measurement of motionally averaged dipolar couplings

Motionally averaged dipolar couplings are an important tool for understanding the complex dynamics of catalysts, polymers, and biomolecules. While there is a plethora of solid-state NMR pulse sequences available for their measurement, in can be difficult to gauge the methods' strengths and weaknesses. In particular, there has not been a comprehensive comparison of their performance in natural abundance samples, where 1H homonuclear dipolar couplings are important and the use of large MAS rotors may be required for sensitivity reasons. In this work, we directly compared some of the more common methods for measuring C-H dipolar couplings in natural abundance samples using L-alanine (L-Ala) and the N-formyl-L-methionyl-L-leucyl-L-phenylalanine (fMLF) tripeptide as model systems. We evaluated their performance in terms of accuracy, resolution, sensitivity, and ease of implementation. We found that, despite the presence of 1H homonuclear dipolar interactions, all methods, with the exception of REDOR, were able to yield the reasonable dipolar coupling strengths for both mobile and static moieties. Of these methods, PDLF provides the most convenient workflow and precision at the expense of low sensitivity. In low-sensitivity cases, MAS-PISEMA and DIPSHIFT appear to be the better options.

Unveiling the topology of partially disordered micro-crystalline nitro-perylenediimide with X-aggregate stacking: an integrated approach

Profound knowledge of the molecular structure and supramolecular organization of organic molecules is essential to understand their structure-property relationships. Herein we demonstrate the packing arrangement of partially disordered nitro-perylenediimide (NO2-PDI), revealing that the perylenediimide units exhibit an X-shaped packing pattern. The packing of NO2-PDI is derived using a complementary approach that utilises solid-state NMR (ssNMR) and 3D electron diffraction (3D ED) techniques. Perylenediimide (PDI) molecules are captivating due to their high luminescence efficiency and optoelectronic properties, which are related to supramolecular self-assembly. Increasing the alkyl chain length on the imide substituent poses a more significant challenge in crystallizing the resulting molecule. In addition to the alkyl tails, other functional groups, like the nitro group attached as a bay substituent, can also cause disorder. Such heterogeneity could lead to diffuse scattering, which then complicates the interpretation of diffraction experiment data, where perfect periodicity is expected. As a result, there is an unmet need to develop a methodology for solving the structures of difficult-to-crystallize materials. A synergistic approach is utilised in this manuscript to understand the packing arrangement of the disordered material NO2-PDI by making use of 3D ED, ssNMR and density functional theory calculations (DFT). The combination of these experimental and theoretical approaches provides great promise in enabling the structural investigation of novel materials with customized properties across various applications, which are, due to the internal disorder, very difficult to study by diffraction techniques. By effectively addressing these challenges, our methodology opens up new avenues for material characterization, thereby driving exciting advancements in the field.

Resolving the Chemical Formula of Nesquehonite via NMR Crystallography, DFT Computation, and Complementary Neutron Diffraction

Nesquehonite is a magnesium carbonate mineral relevant to carbon sequestration envisioned for carbon capture and storage of CO₂ . Its chemical formula remains controversial today, assigned as either a hydrated magnesium carbonate [MgCO₃  ⋅ 3H₂ O], or a hydroxy- hydrated- magnesium bicarbonate [Mg(HCO₃ )OH ⋅ 2H₂ O]. The resolution of this controversy is central to understanding this material's thermodynamic, phase, and chemical behavior. In an NMR crystallography study, using rotational-echo double-resonance ¹³ C{¹ H} (REDOR), ¹³ C-¹ H distances are determined with precision, and the combination of ¹³ C static NMR lineshapes and density functional theory (DFT) calculations are used to model different H atomic coordinates. [MgCO₃  ⋅ 3H₂ O] is found to be accurate, and evidence from neutron powder diffraction bolsters these assignments. Refined H positions can help understand how H-bonding stabilizes this structure against dehydration to MgCO₃ . More broadly, these results illustrate the power of NMR crystallography as a technique for resolving questions where X-ray diffraction is inconclusive.

Characterization of Chemisorbed Species and Active Adsorption Sites in Mg-Al Mixed Metal Oxides for High-Temperature CO2 Capture

Mg-Al mixed metal oxides (MMOs), derived from the decomposition of layered double hydroxides (LDHs), have been purposed as adsorbents for CO₂ capture of industrial plant emissions. To aid in the design and optimization of these materials for CO₂ capture at 200 °C, we have used a combination of solid-state nuclear magnetic resonance (ssNMR) and density functional theory (DFT) to characterize the CO₂ gas sorption products and determine the various sorption sites in Mg-Al MMOs. A comparison of the DFT cluster calculations with the observed ¹³C chemical shifts of the chemisorbed products indicates that mono- and bidentate carbonates are formed at the Mg-O sites with adjacent Al substitution of an Mg atom, while the bicarbonates are formed at Mg-OH sites without adjacent Al substitution. Quantitative ¹³C NMR shows an increase in the relative amount of strongly basic sites, where the monodentate carbonate product is formed, with increasing Al/Mg molar ratios in the MMOs. This detailed understanding of the various basic Mg-O sites presented in MMOs and the formation of the carbonate, bidentate carbonate, and bicarbonate chemisorbed species yields new insights into the mechanism of CO₂ adsorption at 200 °C, which can further aid in the design and capture capacity optimization of the materials.

89Y chemical shift anisotropy: a sensitive structural probe of layered yttrium hydroxides revealed by solid-state NMR spectroscopy and DFT calculations

Anion-exchangeable Y₂(OH)₅X·nH₂O (LYH-X, X = monovalent anions, n ≈ 1.5) materials are an ideal platform for incorporating the unique properties of layered metal hydroxides and rare-earth (RE) ions, and thus have exhibited promising prospects for various applications. To further improve the performance of LYH-X and related functional materials, their structure-property relationships must be explored. However, due to the intrinsic felxibility, extracting the local structural details of these materials is particularly challenging. In this work, we utilized a combined approach of ⁸⁹Y solid-state NMR (ssNMR) spectroscopy and density functional theory (DFT) calculations to reveal the response of ⁸⁹Y chemical shift anisotropy (CSA) in LYH-X to the structural changes including a small displacement of cationic yttrium hydroxide layers and intercalated anions. Such subtle structural changes are often associated with dehydration/rehydration, anion-exchange, exfoliation, and the self-assembly process of LYH-X and related functional materials, which are exceedingly difficult to detect using other techniques. The principal components of ⁸⁹Y CSA show a larger variation range than isotropic chemical shifts, making CSA a more sensitive probe. In addition, it is found that the response of ⁸⁹Y CSA to structural changes is distinct for Y sites with different local coordination environments, opening great opportunities to analyze each Y site within these materials. All these observations suggest that the strategy involving both experimental (⁸⁹Y ssNMR) and theoretical (DFT) approaches can be utilized to extract previously unavailable ultrafine structural information of LYH-X and related materials, and provide fruitful insights into their thorough structure-property relationships.

NMR Crystallography Enhanced by Quantum Chemical Calculations and Liquid State NMR Spectroscopy for the Investigation of Se-NHC Adducts*

N-heterocyclic carbene ligands (NHC) are widely utilized in catalysis and material science. They are characterized by their steric and electronic properties. Steric properties are usually quantified on the basis of their static structure, which can be determined by X-ray diffraction. The electronic properties are estimated in the liquid state; for example, via the ⁷⁷ Se liquid state NMR of Se-NHC adducts. We demonstrate that ⁷⁷ Se NMR crystallography can contribute to the characterization of the structural and electronic properties of NHC in solid and liquid states. Selected Se-NHC adducts are investigated via ⁷⁷ Se solid state NMR and X-ray crystallography, supported by quantum chemical calculations. This investigation reveals a correlation between the molecular structure of adducts and NMR parameters, including not only isotropic chemical shifts but also the other chemical shift tensor components. Afterwards, the liquid state ⁷⁷ Se NMR data is presented and interpreted in terms of the quantum chemistry modelling. The discrepancy between the structural and electronic properties, and in particular the π-accepting abilities of adducts in the solid and liquid states is discussed. Finally, the ¹³ C isotropic chemical shift from the liquid state NMR and the ¹³ C tensor components are also discussed, and compared with their ⁷⁷ Se counterparts. ⁷⁷ Se NMR crystallography can deliver valuable information about NHC ligands, and together with liquid state ⁷⁷ Se NMR can provide an in-depth outlook on the properties of NHC ligands.

Enhancing Structural Rigidity via a Strategy Involving Protons for Creating Water-Resistant Mn4+-Doped Fluoride Phosphors

The poor water resistance property of a commercial Mn⁴⁺-activated narrow-band red-emitting fluoride phosphor restricts its promising applications in high-performance white LEDs and wide-gamut displays. Herein, we develop a structural rigidity-enhancing strategy using a novel KHF₂:Mn⁴⁺ precursor as a Mn source to construct a proton-containing water-resistant phosphor K₂(H)TiF₆:Mn⁴⁺ (KHTFM). The parasitic [HMnF₆]^- complexes in the interstitial site from the fall off the KHF₂:Mn⁴⁺ are also transferred to the K₂TiF₆ host by ion exchange to form KHTFM with rigid bonding networks, improving the water resistance and thermostability of the sample. The KHTFM sample retains at least 92% of the original emission value after 180 min of water immersion, while the non-water-resistant K₂TiF₆:Mn⁴⁺(KTFM) phosphor maintains only 23%. Therefore, these findings not only illustrate the effect of protons on fluoride but also provide a novel insight into commercial water-resistant fluoride phosphors.

13 C chemical shift tensors in MOF α-Mg3 (HCOO)6 : Which component is more sensitive to host-guest interaction?

Metal-organic frameworks (MOFs) are a class of important porous materials with many current and potential applications. Their applications almost always involve the interaction between host framework and guest species. Therefore, understanding of host-guest interaction in MOF systems is fundamentally important. Solid-state NMR spectroscopy is an excellent technique for investigating host-guest interaction as it provides information complementary to that obtained from X-ray diffraction. In this work, using MOF α-Mg₃ (HCOO)₆ as an example, we demonstrated that ¹³ C chemical shift tensor of organic linker can be utilized to probe the host-guest interaction in MOFs. Obtaining ¹³ C chemical shift tensor components (δ₁₁ , δ₂₂ , and δ₃₃ , where δ₁₁ ≥ δ₂₂ ≥ δ₃₃ ) in this MOF is particularly challenging as there are six coordinatively equivalent but crystallographically non-equivalent carbons in the unit cell with very similar local coordination environment. Two-dimensional magic-angle-turning experiments were employed to measure the ¹³ C chemical shift tensors of each individual crystallographically non-equivalent carbon in three microporous α-Mg₃ (HCOO)₆ samples with different guest species. The results indicate that the δ₂₂ component (with its direction approximately being co-planar with the formate anion and perpendicular to the C-H bond) is more sensitive to the adsorbate molecules inside the MOF channel due to the weak C-H···O hydrogen bonding or the ring current effect of benzene. The ¹³ C isotropic chemical shift, on the other hand, seems much less sensitive to the subtle changes in the local environment around formate linker induced by adsorption. The approach described in this study may be used in future studies on host-guest interaction within MOFs.

Learning to Make Chemical Predictions: the Interplay of Feature Representation, Data, and Machine Learning Methods

Recently supervised machine learning has been ascending in providing new predictive approaches for chemical, biological and materials sciences applications. In this Perspective we focus on the interplay of machine learning method with the chemically motivated descriptors and the size and type of data sets needed for molecular property prediction. Using Nuclear Magnetic Resonance chemical shift prediction as an example, we demonstrate that success is predicated on the choice of feature extracted or real-space representations of chemical structures, whether the molecular property data is abundant and/or experimentally or computationally derived, and how these together will influence the correct choice of popular machine learning methods drawn from deep learning, random forests, or kernel methods.

Multiresolution 3D-DenseNet for Chemical Shift Prediction in NMR Crystallography

We have developed a deep learning algorithm for chemical shift prediction for atoms in molecular crystals that utilizes an atom-centered Gaussian density model for the 3D data representation of a molecule. We define multiple channels that describe different spatial resolutions for each atom type that utilizes cropping, pooling, and concatenation to create a multiresolution 3D-DenseNet architecture (MR-3D-DenseNet). Because the training and testing time scale linearly with the number of samples, the MR-3D-DenseNet can exploit data augmentation that takes into account the property of rotational invariance of the chemical shifts, thereby also increasing the size of the training data set by an order of magnitude without additional cost. We obtain very good agreement for ¹³C, ¹⁵N, and ¹⁷O chemical shifts when compared to ab initio quantum chemistry methods, with the highest accuracy found for ¹H chemical shifts that is comparable to the error between the ab initio results and experimental measurements. Principal component analysis (PCA) is used to both understand these greatly improved predictions for ¹H , as well as indicating that chemical shift prediction for ¹³C, ¹⁵N, and ¹⁷O, which have far fewer training environments than the ¹H atom type, will improve once more unique training samples are made available to exploit the deep network architecture.

Exploring Accuracy Limits of Predictions of the 1H NMR Chemical Shielding Anisotropy in the Solid State

The 1H chemical shielding anisotropy (CSA) is an NMR parameter that is exquisitely sensitive to the local environment of protons in crystalline systems, but it is difficult to obtain it experimentally due to the need to concomitantly suppress other anisotropic interactions in the solid-state NMR (SSNMR) pulse sequences. The SSNMR measurements of the 1H CSA are particularly challenging if the fast magic-angle-spinning (MAS) is applied. It is thus important to confront the results of both the single-crystal (SC) and fast-MAS experiments with their theoretical counterparts. Here the plane-waves (PW) DFT calculations have been carried out using two functionals in order to precisely characterize the structures and the 1H NMR chemical shielding tensors (CSTs) of the solid forms of maleic, malonic, and citric acids, and of L-histidine hydrochloride monohydrate. The level of agreement between the PW DFT and either SC or fast-MAS SSNMR 1H CSA data has been critically compared. It has been found that for the eigenvalues of the 1H CSTs provided by the fast-MAS measurements, an accuracy limit of current PW DFT predictions is about two ppm in terms of the standard deviation of the linear regression model, and sources of this error have been thoroughly discussed.