Phospholipid headgroups govern area per lipid and emergent elastic properties of bilayers.

Phospholipid bilayers are liquid-crystalline materials whose intermolecular interactions at mesoscopic length scales have key roles in the emergence of membrane physical properties. Here we investigated the combined effects of phospholipid polar headgroups and acyl chains on biophysical functions of membranes with solid-state 2H NMR spectroscopy. We compared the structural and dynamic properties of phosphatidylethanolamine and phosphatidylcholine with perdeuterated acyl chains in the solid-ordered (so) and liquid-disordered (ld) phases. Our analysis of spectral lineshapes of 1,2-diperdeuteriopalmitoyl-sn-glycero-3-phosphoethanolamine (DPPE-d62) and 1,2-diperdeuteriopalmitoyl-sn-glycero-3-phosphocholine (DPPC-d62) in the so (gel) phase indicated an all-trans rotating chain structure for both lipids. Greater segmental order parameters (SCD) were observed in the ld (liquid-crystalline) phase for DPPE-d62 than for DPPC-d62 membranes, while their mixtures had intermediate values irrespective of the deuterated lipid type. Our results suggest the SCD profiles of the acyl chains are governed by methylation of the headgroups and are averaged over the entire system. Variations in the acyl chain molecular dynamics were further investigated by spin-lattice (R1Z) and quadrupolar-order relaxation (R1Q) measurements. The two acyl-perdeuterated lipids showed distinct differences in relaxation behavior as a function of the order parameter. The R1Z rates had a square-law dependence on SCD, implying collective mesoscopic dynamics, with a higher bending rigidity for DPPE-d62 than for DPPC-d62 lipids. Remodeling of lipid average and dynamic properties by methylation of the headgroups thus provides a mechanism to control the actions of peptides and proteins in biomembranes.

Symbolic regression development of empirical equations for diffusion in Lennard-Jones fluids.

Symbolic regression (SR) with a multi-gene genetic program has been used to elucidate new empirical equations describing diffusion in Lennard-Jones (LJ) fluids. Examples include equations to predict self-diffusion in pure LJ fluids and equations describing the finite-size correction for self-diffusion in binary LJ fluids. The performance of the SR-obtained equations was compared to that of both the existing empirical equations in the literature and to the results from artificial neural net (ANN) models recently reported. It is found that the SR equations have improved predictive performance in comparison to the existing empirical equations, even though employing a smaller number of adjustable parameters, but show an overall reduced performance in comparison to more extensive ANNs.

Modes of Disorder in Poly(carbon monofluoride).

Poly(carbon monofluoride), or (CF)n, is a layered fluorinated graphite material consisting of nanosized platelets. Here, we present experimental multidimensional solid-state NMR spectra of (CF)n, supported by density functional theory (DFT) calculations of NMR parameters, which overhauls our understanding of structure and bonding in the material by elucidating many ways in which disorder manifests. We observe strong 19F NMR signals conventionally assigned to elongated or "semi-ionic" C-F bonds and find that these signals are in fact due to domains where the framework locally adopts boat-like cyclohexane conformations. We calculate that C-F bonds are weakened but are not elongated by this conformational disorder. Exchange NMR suggests that conformational disorder avoids platelet edges. We also use a new J-resolved NMR method for disordered solids, which provides molecular-level resolution of highly fluorinated edge states. The strings of consecutive difluoromethylene groups at edges are relatively mobile. Topologically distinct edge features, including zigzag edges, crenellated edges, and coves, are resolved in our samples by solid-state NMR. Disorder should be controllable in a manner dependent on synthesis, affording new opportunities for tuning the properties of graphite fluorides.

Artificial neural network prediction of self-diffusion in pure compounds over multiple phase regimes.

Artificial neural networks (ANNs) were developed to accurately predict the self-diffusion constants for pure components in liquid, gas and super critical phases. The ANNs were tested on an experimental database of 6625 self-diffusion constants for 118 different chemical compounds. The presence of multiple phases results in a heavy skew in the distribution of diffusion constants and multiple approaches were used to address this challenge. First, an ANN was developed with the raw diffusion values to assess what the main drawbacks of this direct method were. The first approach for improving the predictions involved taking the log 10 of diffusion to provide a more uniform distribution and reduce the range of target output values used to develop the ANN. The second approach involved developing individual ANNs for each phase using the raw diffusion values. Results show that the log transformation leads to a model with the best self-diffusion constant predictions and an overall average absolute deviation (AAD) of 6.56%. The resultant ANN is a generalized model that can be used to predict diffusion across all three phases and over a diverse group of compounds. The importance of each input feature was ranked using a feature addition method revealing that the density of the compound has the largest impact on the ANN prediction of self-diffusion constants in pure compounds.

Arene Substitution Design for Controlled Conformational Changes of Dibenzocycloocta-1,5-dienes.

We report that an agile eight-membered cycloalkane can be stabilized by fusing a benzene ring on each side, substituted with proper functional groups. The conformational change of dibenzocycloocta-1,5-diene (DBCOD), a rigid-flexible-rigid organic moiety, from its Boat to Chair conformation requires an activation energy of 42 kJ/mol, which is substantially lower than those of existing submolecular shape-changing units. Experimental data corroborated by theoretical calculations demonstrate that intramolecular hydrogen bonding can stabilize Boat, whereas electron repulsive interaction from opposing ester substituents favors Chair. Intramolecular hydrogen bonding formed by 1,10-diamide substitution stabilizes Boat, spiking the temperature at which Boat and Chair can readily interchange from -60 to 60 °C. Concomitantly this intramolecular attraction raises the energy barrier from 42 kJ/mol for unsubstituted DBCOD to 68 kJ/mol for diamide-substituted DBCOD. Remarkably, this value falls within the range of the activation energy of highly efficient enzyme-catalyzed biological reactions. With shape changes once considered only possible with high energy, our work reveals a potential pathway exemplified by a specific submolecular structure to achieve low-energy-driven shape changes for the first time. The intrinsic cycle stability and high-energy output systems that would incur damage under high-energy stimuli could particularly benefit from this new kind of low-energy-driven shape-changing mechanism. This work has laid the basis to construct systems for low-energy-driven stimuli-responsive applications, hitherto a challenge to overcome.

Trapped Intermediate of a Meerwein-Pondorf-Verley Reduction of Hydroxy Benzaldehyde to a Dialkoxide by Titanium Alkoxides.

A series of titanium alkoxides ([Ti(OR)4] (OR = OCH(CH3)2 (OPri), OC(CH3)3 (OBut), and OCH2C(CH3)3 (ONep)) were modified with a set of substituted hydroxyl-benzaldehydes [HO-BzA-Lx: x = 1, 2-hydroxybenzaldehyde (L = H), 2-hydroxy-3-methoxybenzaldehyde (OMe-3), 5-bromo-2-hydroxybenzaldehyde (Br-5), 2-hydroxy-5-nitrobenzaldehyde (NO2-5); x = 2, 3,5-di-tert-butyl-2-hydroxybenzaldehyde (But-3,5), 2-hydroxy-3,5-diiodobenzaldehyde (I-3,5)] in pyridine (py). Instead of the expected simple substitution, each of the HO-BzA-Lx modifiers were reduced to their respective diol [(py)(OR)2Ti(κ2(O,µ-O')(OC6H4-x(CH2O)-2)(L)x] (OR = OPri, x = 1, L = H (1a), OMe-3 (2a), Br-5 (3a·py), NO2-5 (4a·4py); x = 2, But-3,5 (5a), I-3,5 (6a), ONep; x = 1, L = H (1b), OMe-3 (2b), Br-5 (3b·py), NO2-5 (4b); x = 2, But-3,5 (5b), I-3,5 (6b·py)), as identified by single crystal X-ray studies. The 1H NMR spectral data were complex at room temperature but simplified at high temperatures (70 °C). Diffusion ordered spectroscopy (DOSY) NMR experiments indicated that 2a maintained the dinuclear structure in a solution independent of the temperature, whereas 2b appears to be monomeric over the same temperature range. On the basis of additional NMR studies, the mechanism of the reduction of the HO-BzA-Lx to the dioxide ligand was thought to occur by a Meerwein-Pondorf-Verley (MPV) mechanism. The structures of 1a-6b appear to be the intermediate dioxide products of the MPV reduction, which became "trapped" by the Lewis basic solvate.

Machine learning prediction of self-diffusion in Lennard-Jones fluids.

Different machine learning (ML) methods were explored for the prediction of self-diffusion in Lennard-Jones (LJ) fluids. Using a database of diffusion constants obtained from the molecular dynamics simulation literature, multiple Random Forest (RF) and Artificial Neural Net (ANN) regression models were developed and characterized. The role and improved performance of feature engineering coupled to the RF model development was also addressed. The performance of these different ML models was evaluated by comparing the prediction error to an existing empirical relationship used to describe LJ fluid diffusion. It was found that the ANN regression models provided superior prediction of diffusion in comparison to the existing empirical relationships.

Quantification of Uncoupled Spin Domains in Spin-Abundant Disordered Solids.

Materials often contain minor heterogeneous phases that are difficult to characterize yet nonetheless significantly influence important properties. Here we describe a solid-state NMR strategy for quantifying minor heterogenous sample regions containing dilute, essentially uncoupled nuclei in materials where the remaining nuclei experience heteronuclear dipolar couplings. NMR signals from the coupled nuclei are dephased while NMR signals from the uncoupled nuclei can be amplified by one or two orders of magnitude using Carr-Meiboom-Purcell-Gill (CPMG) acquisition. The signal amplification by CPMG can be estimated allowing the concentration of the uncoupled spin regions to be determined even when direct observation of the uncoupled spin NMR signal in a single pulse experiment would require an impractically long duration of signal averaging. We use this method to quantify residual graphitic carbon using 13C CPMG NMR in poly(carbon monofluoride) samples synthesized by direct fluorination of carbon from various sources. Our detection limit for graphitic carbon in these materials is better than 0.05 mol%. The accuracy of the method is discussed and comparisons to other methods are drawn.

Heterogeneous Polymer Dynamics Explored Using Static 1H NMR Spectra.

NMR spectroscopy continues to provide important molecular level details of dynamics in different polymer materials, ranging from rubbers to highly crosslinked composites. It has been argued that thermoset polymers containing dynamic and chemical heterogeneities can be fully cured at temperatures well below the final glass transition temperature (Tg). In this paper, we described the use of static solid-state 1H NMR spectroscopy to measure the activation of different chain dynamics as a function of temperature. Near Tg, increasing polymer segmental chain fluctuations lead to dynamic averaging of the local homonuclear proton-proton (1H-1H) dipolar couplings, as reflected in the reduction of the NMR line shape second moment (M2) when motions are faster than the magnitude of the dipolar coupling. In general, for polymer systems, distributions in the dynamic correlation times are commonly expected. To help identify the limitations and pitfalls of M2 analyses, the impact of activation energy or, equivalently, correlation time distributions, on the analysis of 1H NMR M2 temperature variations is explored. It is shown by using normalized reference curves that the distributions in dynamic activation energies can be measured from the M2 temperature behavior. An example of the M2 analysis for a series of thermosetting polymers with systematically varied dynamic heterogeneity is presented and discussed.

Computational and Experimental 1H-NMR Study of Hydrated Mg-Based Minerals.

Magnesium oxide (MgO) can convert to different magnesium-containing compounds depending on exposure and environmental conditions. Many MgO-based phases contain hydrated species allowing 1H-nuclear magnetic resonance (NMR) spectroscopy to be used in the characterization and quantification of proton-containing phases; however, surprisingly limited examples have been reported. Here, 1H-magic angle spinning (MAS) NMR spectra of select Mg-based minerals are presented and assigned. These experimental results are combined with computational NMR density functional theory (DFT) periodic calculations to calibrate the predicted chemical shielding results. This correlation is then used to predict the NMR shielding for a series of different MgO hydroxide, magnesium chloride hydrate, magnesium perchlorate, and magnesium cement compounds to aid in the future assignment of 1H-NMR spectra for complex Mg phases.

Resolving Confined 7Li Dynamics of Uranyl Peroxide Capsule U24.

We obtained a kerosene-soluble form of the lithium salt [UO2(O2)(OH)2]24 phase (Li-U24), by adding cetyltrimethylammonium bromide surfactant to aqueous Li-U24. Interestingly, its variable-temperature solution 7Li NMR spectroscopy resolves two narrowly spaced resonances down to -10 °C, which shift upfield with increasing temperature, and finally coalesce at temperatures > 85 °C. Comparison with solid-state NMR demonstrates that the Li dynamics in the Li-U24-CTA phase involves only exchange between different local encapsulated environments. This behavior is distinct from the rapid Li exchange dynamics observed between encapsulated and external Li environments for Li-U24 in both the aqueous and the solid-state phases. Density functional theory calculations suggest that the two experimental 7Li NMR chemical shifts are due to Li cations coordinated within the square and hexagonal faces of the U24 cage, and they can undergo exchange within the confined environment, as the solution is heated. Very different than U24 in aqueous media, there is no evidence that the Li cations exit the cage, and therefore, this represents a truly confined space.

Computational Study of Microhydration in Sulfonated Diels-Alder Poly(phenylene) Polymers.

The nature of microhydration in sulfonated Diels-Alder poly(phenylene) (SDAPP) polymer membranes is explored using ab initio and density functional theory (DFT) electronic structure calculations. The impact of the aromatic poly(phenylene) structure, including cooperative effects between multiple spatially adjacent sulfonic groups, on the hydration environment is addressed using a series of DFT B3LYP/6-311**-optimized structures for different SDAPP· nH2O clusters. In addition, larger SDAPP polymer fragments, along with selected hydrophilic domain structures extracted from molecular dynamic (MD) simulations, are also evaluated using ONIOM HF/PM6 semiempirical calculations. The SDAPP clusters reveal that spontaneous proton dissociation occurs at low levels of hydration to form sulfonic-acid-associated H3O+ contact ion pairs (CIPs), which then evolve into solvated CIPs at higher hydration levels. For multiple sulfonic acid groups located on the poly(phenylene) side chains, the hydration energies are a function of the relative acid location and backbone configuration. Variations in the phenylene backbone torsional angles allow remote sulfonic acids to adopt an optimal separation to produce an extended hydrogen bonded network of waters between the SDAPP acids groups. These calculations provide a baseline to help describe the proton transport and hydration behavior of SDAPP membranes.

Single-Crystal Time-of-Flight Neutron Diffraction and Magic-Angle-Spinning NMR Spectroscopy Resolve the Structure and 1H and 7Li Dynamics of the Uranyl Peroxide Nanocluster U60.

Single-crystal time-of-flight neutron diffraction has provided atomic resolution of H atoms of H2O molecules and hydroxyl groups, as well as Li cations in the uranyl peroxide nanocluster U60. Solid-state magic-angle-spinning nuclear magnetic resonance (MAS NMR) spectroscopy was used to confirm the dynamics of these constituents, revealing the transportation of Li atoms and H2O through cluster walls. H atoms of hydroxyl units that are located on the cluster surface are involved in the transfer of H2O and Li cations from inside to outside and vice versa. This exchange occurs as a concerted motion and happens rapidly even in the solid state. As a consequence of its large size and open hexagonal pores, U60 exchanges Li cations more rapidly compared to other uranyl nanoclusters.

Pt-Mg, Pt-Ca, and Pt-Zn Lantern Complexes and Metal-Only Donor-Acceptor Interactions.

Pt-based heterobimetallic lantern complexes of the form [PtM(SOCR)4(L)] have been shown previously to form intermolecular metallophilic interactions and engage in antiferromagnetic coupling between lanterns having M atoms with open shell configurations. In order to understand better the influence of the carboxylate bridge and terminal ligand on the electronic structure, as well as the metal-metal interactions within each lantern unit, a series of diamagnetic lantern complexes, [PtMg(SAc)4(OH2)] (1), [PtMg(tba)4(OH2)] (2), [PtCa(tba)4(OH2)] (3), [PtZn(tba)4(OH2)] (4), and a mononuclear control (Ph4P)2[Pt(SAc)4] (5) have been synthesized. Crystallographic data show close Pt-M contacts enforced by the lantern structure in each dinuclear case. 195Pt-NMR spectroscopy of 1-4, (Ph4P)2[Pt(SAc)4] (5), and several previously reported lanterns revealed a strong chemical shift dependence on the identity of the second metal (M), mild influence by the thiocarboxylate ligand (SOCR; R = CH3 (thioacetate, SAc), C6H5 (thiobenzoate, tba)), and modest influence from the terminal ligand (L). Fluorescence spectroscopy has provided evidence for a Pt···Zn metallophilic interaction in [PtZn(SAc)4(OH2)], and computational studies demonstrate significant dative character. In all of 1-4, the short Pt-M distances suggest that metal-only Lewis donor (Pt)-Lewis acceptor (M) interactions could be present. DFT and NBO calculations, however, show that only the Zn examples have appreciable covalent character, whereas the Mg and Ca complexes are much more ionic.

1 H-19 F REDOR-filtered NMR spin diffusion measurements of domain size in heterogeneous polymers.

Solid state NMR spectroscopy is inherently sensitive to chemical structure and composition and thus makes an ideal method to probe the heterogeneity of multicomponent polymers. Specifically, NMR spin diffusion experiments can be used to extract reliable information about spatial domain sizes on multiple length scales, provided that magnetization selection of one domain can be achieved. In this paper, we demonstrate the preferential filtering of protons in fluorinated domains during NMR spin diffusion experiments using 1 H-19 F heteronuclear dipolar dephasing based on rotational echo double resonance (REDOR) MAS NMR techniques. Three pulse sequence variations are demonstrated based on the different nuclei detected: direct 1 H detection, plus both 1 H➔13 C cross polarization and 1 H➔19 F cross polarization detection schemes. This 1 H-19 F REDOR-filtered spin diffusion method was used to measure fluorinated domain sizes for a complex polymer blend. The efficacy of the REDOR-based spin filter does not rely on spin relaxation behavior or chemical shift differences and thus is applicable for performing NMR spin diffusion experiments in samples where traditional magnetization filters may prove unsuccessful. This REDOR-filtered NMR spin diffusion method can also be extended to other samples where a heteronuclear spin pair exists that is unique to the domain of interest.

Structural Properties of the Acidification Products of Scandium Hydroxy Chloride Hydrate.

The structural properties of a series of scandium inorganic acid derivatives were determined. The reaction of Sc(0) with concentrated aqueous hydrochloric acid led to the isolation of [(H2O)5Sc(µ-OH)]24Cl·2H2O (1). Compound 1 was modified with a series of inorganic acids (i.e., HNO3, H3PO4, and H2SO4) at room temperature and found to form {[(H2O)4Sc(κ(2)-NO3)(µ-OH)]NO3}2 (2a), [(H2O)4Sc(κ(2)-NO3)2]NO3·H2O (2b) (at reflux temperatures), {6[H][Sc(µ-PO4)(PO4)]6}n (3), and [H][Sc(µ3-SO4)2]·2H2O (4a). Additional organosulfonic acid derivatives were investigated, including tosylic acid (H-OTs) to yield {[(H2O)4Sc(OTs)2]OTs}·2H2O (4b) in H2O and [(DMSO)3Sc(OTs)3] (4c) in dimethyl sulfoxide and triflic acid (H-OTf) to form [Sc(H2O)8]OTf3 (4d). Other organic acid modifications of 1 were also investigated, and the final structures were determined to be {([(H2O)2Sc(µ-OAc)2]Cl)6}n (5) from acetic acid (H-OAc) and [Sc(µ-TFA)3Sc(µ-TFA)3]n (6) from trifluoroacetic acid (H-TFA). In addition to single-crystal X-ray structures, the compounds were identified by solid-state and solution-state (45)Sc nuclear magnetic resonance spectroscopic studies.

Solid-state dynamics of uranyl polyoxometalates.

Understanding fundamental uranyl polyoxometalate (POM) chemistry in solution and the solid state is the first step to defining its future role in the development of new actinide materials and separation processes that are vital to every step of the nuclear fuel cycle. Many solid-state geometries of uranyl POMs have been described, but we are only beginning to understand their chemical behavior, which thus far includes the role of templates in their self-assembly, and the dynamics of encapsulated species in solution. This study provides unprecedented detail into the exchange dynamics of the encapsulated species in the solid state through Magic Angle Spinning Nuclear Magnetic Resonance (MAS NMR) spectroscopy. Although it was previously recognized that capsule-like molybdate and uranyl POMs exchange encapsulated species when dissolved in water, analogous exchange in the solid state has not been documented, or even considered. Here, we observe the extremely high rate of transport of Li(+) and aqua species across the uranyl shell in the solid state, a process that is affected by both temperature and pore blocking by larger species. These results highlight the untapped potential of emergent f-block element materials and vesicle-like POMs.

Synthesis and structural characterization of group 4 metal carboxylates for nanowire production.

The synthesis and characterization of a series of group 4 carboxylate derivatives ([M(ORc)4] where M = Ti, Zr, Hf) was undertaken for potential utility as precursors to ceramic nanowires. The attempted syntheses of the [M(ORc)4] precursors were undertaken from the reaction of [M(OBu(t))4] with a select set of carboxylic acids (H-ORc where ORc = OPc (O2CCH(CH3)2), OBc (O2CC(CH3)3), ONc (O2CCH2C(CH3)3)). The products were identified by single-crystal X-ray diffraction studies as [Ti(η(2)-OBc)3(OBu(t))] (1), [Zr2(µ3-O)(µ-OPc)4(µ,η(2)-OPc)(η(2)-OPc)]2 (2), [H]2[Zr(η(2)-OBc)2(OBc)2(OBc)2] (3), [Zr(µ-ONc)2(η(2)-ONc)2]2 (4), or [Hf(µ-ORc)2(η(2)-ORc)2]2 [ORc = OPc (5), OBc (6, shown), ONc (7)]. The majority of compounds (4-7) were isolated as dinuclear species with a dodecahedral-like (CN-8) bonding mode around the metals due to chelation and bridging of the ORc ligand. The two monomers (1 and 3) were found to adopt a capped trigonal prismatic and CN-8 geometry, respectively, due to chelating ORc and terminal ORc or OBu(t) ligands. The metals of the oxo-species 2 were isolated in octahedral and CN-8 arrangements. These compounds were then processed by electrospinning methods (applied voltage 10 kV, flow rate 30-60 µL/min, electric field 0.5 kV/cm), and wire-like morphologies were isolated using compounds 4, 6 (shown), and 7.

Ab initio calculations of possible γ-gauche effects in the ¹³C-NMR for methine and carbonyl carbons in precise polyethylene acrylic acid copolymers.

The impacts of local polymer chain conformations on the methine and carbonyl ¹³C-NMR chemical shifts for polyethylene acrylic acid p(E-AA) copolymers were predicted using ab initio methods. Using small molecular cluster models, the magnitude and sign of the γ-gauche torsional angle effect, along with the impact of local tetrahedral structure distortions near the carbonyl group, on the ¹³C-NMR chemical shifts were determined. These ¹³C-NMR chemical shift variations were compared to the experimental trends observed for precise p(E-AA) copolymers as a function acid group spacing and degree of zinc-neutralization in the corresponding p(E-AA) ionomers. These ab initio calculations address the future ability of ¹³C-NMR chemical shift variations to provide information about the local chain conformations in p(E-AA) copolymer materials.

Machine Learning Predictions of Simulated Self-Diffusion Coefficients for Bulk and Confined Pure Liquids.

Diffusion properties of bulk fluids have been predicted using empirical expressions and machine learning (ML) models, suggesting that predictions of diffusion also should be possible for fluids in confined environments. The ability to quickly and accurately predict diffusion in porous materials would enable new discoveries and spur development in relevant technologies such as separations, catalysis, batteries, and subsurface applications. In this work, we apply artificial neural network (ANN) models to predict the simulated self-diffusion coefficients of real liquids in both bulk and pore environments. The training data sets were generated from molecular dynamics (MD) simulations of Lennard-Jones particles representing a diverse set of 14 molecules ranging from ammonia to dodecane over a range of liquid pressures and temperatures. Planar, cylindrical, and hexagonal pore models consisted of walls composed of carbon atoms. Our simple model for these liquids was primarily used to generate ANN training data, but the simulated self-diffusion coefficients of bulk liquids show excellent agreement with experimental diffusion coefficients. ANN models based on simple descriptors accurately reproduced the MD diffusion data for both bulk and confined liquids, including the trend of increased mobility in large pores relative to the corresponding bulk liquid.