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NMR has been instrumental in studies of both the structure and dynamics of molecular systems for decades, so it is not surprising that NMR has played a pivotal role in the study of host-guest complexes and supramolecular systems. In this mini-review, selected examples will be used to demonstrate the added value of using (multiparametric) NMR for studying macrocycle-based host-guest and supramolecular systems. We will restrict the discussion to synthetic host systems having a cavity that can engulf their guests thus restricting them into confined spaces. So discussion of selected examples of cavitands, cages, capsules and their complexes, aggregates and polymers as well as organic cages and porous liquids and other porous materials will be used to demonstrate the insights that have been gathered from the extracted NMR parameters when studying such systems emphasizing the information obtained from somewhat less routine NMR methods such as diffusion NMR, diffusion ordered spectroscopy (DOSY) and chemical exchange saturation transfer (CEST) and their variants. These selected examples demonstrate the impact that the results and findings from these NMR studies have had on our understanding of such systems and on the developments in various research fields.

Diffusion NMR is a useful analytical tool for the characterization of supramolecular systems in solution. In this mini-review, after a short introduction and some methodological tips, we discuss, from a personal point of view, the use of diffusion NMR in the study of calixarene- and other arene-based supramolecular systems. We will demonstrate, through selected examples, how diffusion has been used to study, in solution, the structures and other characteristics of supramolecular systems based on calixarene and related systems ranging from different complexes and aggregates to molecular capsules and to supramolecular oligomers and polymers.

Two-component supramolecular organogels based on per-carboxylato- and per-amino pillar[6]arenes (2 and 4a–c) were prepared for the first time, and found to display very different characteristics as compared to those displayed by the corresponding pillar[5]arene derivatives (1 and 3a–c). Pillar[6]arenes derivatives, in contrast to pillar[5]arene derivatives, do not form organogels in alcoholic solutions and the formed gels in chlorinated solvents are, generally, more fragile. We analyzed the gelation ability of all the pairs between 1, 2, 3a–c and 4a–c, several three-component mixtures in 1 : 1 : 1 and 2 : 1 : 1 ratios, as well as four-component mixtures in ∼10 : 1 CDCl3 : DMSOd6 solutions. The obtained results clearly show that shape complementarity is an important determinant of gel formation in these supramolecular pillar[n]arene-based organogels. We also found that shape directed molecular sorting occurs in the gelation process of these two-component supramolecular organogels.

An approach is presented describing the development of a Bayesian network (BN) based tool for rapid assessment of the distribution of engineered nanomaterials (ENMs). The methodology was demonstrated via the construction of a BN model for estimating the exposure concentrations of nanomaterials (BN-nanoExpo) based on simulation data derived from a mechanistic multimedia compartmental fate and transport model. The results of simulations of the distribution of six ENMs in eight different regions were generated for a broad range of geographical and meteorological parameters as well as ENM release rates to the air, water and soil major compartments. Test cases with the constructed BN-nanoExpo demonstrated the capability of the BN based model to portray a wide range of simulation results that can be obtained with the mechanistic fate and transport model. Moreover, BN-nanoExpo is shown to be a suitable tool for estimating both ENM concentrations and release rates given partial information, while also enabling assessment of the impact of uncertainties in input data on the predicted outcomes. The results of the current study suggest that there is merit in exploring the utility of the approach to more complex models, which would provide decision makers with powerful tools for rapid assessment of the behavior of nanomaterials in the environment.

Labeling of smart PEG–dendron hybrids with fluorinated groups transformed their assemblies into enzyme-responsive micellar probes for 19F-magnetic resonance (MR). Two distinct labeling approaches were used to study the ability of these smart hybrids to be turned OFF at the assembled micellar state and to turn ON their 19F-MR signal upon enzymatic activation.

Cellular association of nanoparticles (NPs) in biological fluids is affected by proteins adsorbed onto the NP surface, forming a "protein corona", thereby impacting cellular bioactivity. Here we investigate, based on an extensive gold NPs protein corona dataset, the relationships between NP-cell association and protein corona fingerprints (PCFs) as well as NP physicochemical properties. Accordingly, quantitative structure-activity relationships (QSARs) were developed based on both linear and non-linear support vector regression (SVR) models making use of a sequential forward floating selection of descriptors. The SVR model with only 6 serum proteins and zeta potential had higher accuracy (R(2) = 0.895) relative to the linear model (R(2) = 0.850) with 11 PCFs. Considering the initial pool of 148 descriptors, the APOB, A1AT, ANT3, and PLMN serum proteins along with NP zeta potential were identified as most significant to correlating NP-cell association. The present study suggests that QSARs exploration of NP-cell association data, considering the role of both NP protein corona and physicochemical properties, can support the planning and interpretation of toxicity studies and guide the design of NPs for biomedical applications.

Prediction of chemical bioactivity and physical properties has been one of the most important applications of statistical and more recently, machine learning and artificial intelligence methods in chemical sciences. This field of research, broadly known as Quantitative Structure-Activity Relationships (QSAR) modeling, has developed many important algorithms and has found a broad range of applications in physical organic and medicinal chemistry in the past 55+ years. This Perspective summarizes recent technological advances in QSAR modeling. Importantly, it also highlights the applicability of algorithms, modeling methods, and validation practices developed in QSAR to a wide range of research areas beyond traditional QSAR fields. These fields include nanotechnology, materials science, biomaterials, clinical informatics, and others. As modern research methods generate rapidly increasing amounts of data, knowledge of robust data-driven modelling methods is becoming essential for scientists in many disciplines both within and outside of chemical research. We hope that this contribution will serve to address this challenge.

Relationships among fourteen different biological responses (including ten signaling pathway activities and four cytotoxicity effects) of murine macrophage (RAW264.7) and bronchial epithelial (BEAS-2B) cells exposed to six metal and metal oxide nanoparticles (NPs) were analyzed using both statistical and data mining approaches. Both the pathway activities and cytotoxicity effects were assessed using high-throughput screening (HTS) over an exposure period of up to 24 h and concentration range of 0.39-200 mg L(-1). HTS data were processed by outlier removal, normalization, and hit-identification (for significantly regulated cellular responses) to arrive at reliable multiparametric bioactivity profiles for the NPs. Association rule mining was then applied to the bioactivity profiles followed by a pruning process to remove redundant rules. The non-redundant association rules indicated that "significant regulation" of one or more cellular responses implies regulation of other (associated) cellular response types. Pairwise correlation analysis (via Pearson's χ(2) test) and self-organizing map clustering of the different cellular response types indicated consistency with the identified non-redundant association rules. Furthermore, in order to explore the potential use of association rules as a tool for data-driven hypothesis generation, specific pathway activity experiments were carried out for ZnO NPs. The experimental results confirmed the association rule identified for the p53 pathway and mitochondrial superoxide levels (via MitoSox reagent) and further revealed that blocking of the transcriptional activity of p53 lowered the MitoSox signal. The present approach of using association rule mining for data-driven hypothesis generation has important implications for streamlining multi-parameter HTS assays, improving the understanding of NP toxicity mechanisms, and selection of endpoints for the development of nanomaterial structure-activity relationships.

Basic research in the chemistry of hexameric resorcin[4]arenes and pyrogallol[4]arenes during the last decade is reviewed. Applications of NMR methods to determine solution structures, host guest properties and exchange dynamics are discussed. The scientific issue is the behavior of molecules in small spaces; the challenge is to translate this information to practical applications in, say, catalysis or transport.

Diffusion coefficients, as obtained by the PGSE NMR technique, were used to probe encapsulation of guests in self-assembled tetraurea calix[4]arene dimers in organic solvents and to demonstrate their destruction by DMSO.

The new ligand 2,9-bis[(6-methyl-2,2′-bipyridin-6′-yl)methyleneoxymethylen-yl]-1,10-phenanthroline (1) was prepared and was shown to self-assemble into double-stranded helicates upon reaction with Cu+, Ag+ and Zn2+, thus affording the first trinuclear double-stranded zinc helicate. The [(1)2M3]3n+ [M=Cu+(n=1), Ag+(n=1) or Zn2+(n=2)] helicates were characterized by 1D, 2D and diffusion NMR. FAB mass spectrometry corroborated the structure of the silver and the copper helicates and [(1)2Cu3]3+ was characterized by X-ray crystallography. The detailed assignments of the 1H NMR spectra of these helicates have shown that H-10 absorbs at a much higher field when compared to the other protons of these complexes. This high-field shift is a unique characteristic of the helicates of 1 and is not found in structurally related helicates. The NMR spectra of these helicates, at room temperature, are consistent with an average solution structure having a D2 symmetry. Variable-temperature 1H NMR (VT-NMR) reveals that the silver helicate of 1 is much more labile than its copper helicate. From the VT-NMR spectra it seems that two, nearly separate, stages are observed in the dissociation process of [(1)2Ag3]3+. The activation energy of the first process for [(1)2Ag3]3+ in DMSO-d6 was found to be 16.6±0.2 kcal mol-1. As expected, the energy barriers for the respective copper helicate are even higher. The crystal structure of [(1)2Cu3]3+ shows that the total length and the pitch length are ≈17 and 12 A, respectively.

The diastereoisomeric complexes formed between 2,6-di-O-alkyl-α- and β-cyclodextrins and the arylammonium ions propranolol, ephedrine and amphetamine have been studied by electrode response and NMR methods. Enantioselectivity in binding propranolol is 3.3∶1 with 2,6-di-O-dodecyl-β-cyclodextrin in favour of the (+)-enantiomer as revealed by measurement of the association constant using pulsed-gradient spin-echo (PGSE) NMR methods. In all of the cases of enantiodifferentiation studied here, the (+)-enantiomer is more strongly bound by the cyclodextrin. Relaxation rate measurements of the host and guest proton NMR resonances highlight the importance of hydrogen-bonding in enantiomer discrimination.

We report on the first secondary and tertiary complexes of the pillar[5]arene derivative 3 with xenon in water. We show that the chemical shift of the encapsulated xenon provides information on the type of the formed complex suggesting that 3 has the potential to be used as a platform for NMR biosensors.

Nanomaterial structure-activity relationships (nano-SARs) for metal oxide nanoparticles (NPs) toxicity were investigated using metrics based on dose-response analysis and consensus self-organizing map clustering. The NP cellular toxicity dataset included toxicity profiles consisting of seven different assays for human bronchial epithelial (BEAS-2B) and murine myeloid (RAW 264.7) cells, over a concentration range of 0.39-100 mg L(-1) and exposure time up to 24 h, for twenty-four different metal oxide NPs. Various nano-SAR building models were evaluated, based on an initial pool of thirty NP descriptors. The conduction band energy and ionic index (often correlated with the hydration enthalpy) were identified as suitable NP descriptors that are consistent with suggested toxicity mechanisms for metal oxide NPs and metal ions. The best performing nano-SAR with the above two descriptors, built with support vector machine (SVM) model and of validated robustness, had a balanced classification accuracy of ~94%. An applicability domain for the present data was established with a reasonable confidence level of 80%. Given the potential role of nano-SARs in decision making, regarding the environmental impact of NPs, the class probabilities provided by the SVM nano-SAR enabled the construction of decision boundaries with respect to toxicity classification under different acceptance levels of false negative relative to false positive predictions.

A new class of surface-structured RO membranes was developed with a hydrophilic brush layer of terminally anchored polymer chains resulting in fouling resistant membranes of low mineral scaling propensity and high permeability. The approach is based on free-radical graft polymerization of a suitable monomer, onto the active polyamide (PA) layer of a thin film composite (PA-TFC) membrane, post-surface activation with an impinging atmospheric pressure plasma source. Two types of nano-structured (SNS) RO membranes (SNS-PA-TFC) were synthesized based on methacrylic acid (MAA-SNS-PA-TFC) and acrylamide (AA-SNS-PA-TFC) graft polymerization. The poly(methacrylic acid) and poly(acrylamide) brush layers, on the PA surface, resulted in RO membranes of significantly lower mineral scaling propensity, evaluated with respect to the mineral scalant calcium sulfate dihydrate, compared with commercial RO membrane (LFC1) of about the same salt rejection (∼95%) and surface roughness (∼70 nm). Direct membrane surface imaging indicated that the rate of nucleation and thus mineral scaling were reduced owing to the polymer brush layer. Fouling resistance of the SNS-PA-TFC membranes was also demonstrated with respect to model foulants (the protein BSA and alginic acid). The MAA-SNS-PA-TFC and AA-SNS-PA-TFC membranes had a negatively charged and near neutral surfaces, respectively, with water contact angles somewhat lower for the former and higher for the latter membranes relative to the LFC1 membrane. The AA-SNS-PA-TFC membrane displayed lower mineral scaling propensity than the MAA based membrane, although its alginic acid fouling resistance was inferior, despite its lower surface roughness (25–33 nm) relative to the MAA-SNS-PA-RFC (∼60–80 nm) and LFC1 (∼73 nm) membranes.

NMR diffusion measurements and chemical shift data are used to study water hydration of 18-crown-61 and its potassium iodide complex (1.KI) in [2H]chloroform suggesting different modes of solute-water interaction in the two cases.

The pulsed gradient spin echo (PGSE) NMR technique was used for measuring the diffusion coefficients of neutral and charged calix[n]arenes and for probing their association in solution with potential guests.

Diffusion coefficients measurements using the pulsed gradients spin echo (PGSE) NMR technique are used for probing complexation and for determining the association constant (Ka) of macrocylclic host–guest complexes.

Stable overcrowded ethylene dianions, viz. bifluoren-9-ylidene dianion (1)2– and bi-(4H-cyclopenta[def]phenanthren-4-ylidene) dianion (2)2– were prepared via metal reduction and characterized by 1H and 13C n.m.r. spectroscopy; the spectroscopic results as well as ωβ calculations performed on the hydrocarbons (1) and (2) and the corresponding dianions (1)2– and (2)2– are discussed with respect to their diatropicity and spatial structure.

The metal reduction of 1,3-diphenylbenzo[c]furan (1) to the corresponding dianion (12–) has been carried out by alkali-metal. A detailed (1D and 2D) n.m.r. investigation of (12–) enables characterization of its charge distribution as well as its spatial structure. The spectra of (12–) differs when three alkali-metals are used for the reduction process. These differences are explained by an ion-solvation equilibrium which in turn explains the different stereoselectivity observed in the quenching experiments of the salts of (12–). The reduction process induces in (12–) a very high energy barrier for the rotation of the phenyl substituents.

1,3-Diphenylbenzo[c]thiophene dianion, (1)2– a member of the novel series of 4nπ polyheterocyclic dianions, has been prepared and characterized by n.m.r.; it shows a high stability and a peculiar charge distribution pattern in which the sulphur atom polarizes the charge towards the α-positions.

Benzo[b]thiophene dianion (1)2–, the first sulphur-containing 4nπ polycyclic dianion, was prepared via metal reduction and characterised by 1H and 13C n.m.r. spectroscopy; the reaction products depend on the reduction conditions.