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Coordination compounds of the lanthanide ions (Ln3+) have important applications in medicine due to their photophysical, magnetic, and nuclear properties. To effectively use the Ln3+ ions for these applications, chelators that stably bind them in vivo are required to prevent toxic side effects that arise from localization of these ions in off-target tissue. In this study, two new picolinate-containing chelators, a heptadentate ligand OxyMepa and a nonadentate ligand Oxyaapa, were prepared, and their coordination chemistries with Ln3+ ions were thoroughly investigated to evaluate their suitability for use in medicine. Protonation constants of these chelators and stability constants for their Ln3+ complexes were evaluated. Both ligands exhibit a thermodynamic preference for small Ln3+ ions. The log KLuL = 12.21 and 21.49 for OxyMepa and Oxyaapa, respectively, indicating that the nonadentate Oxyaapa forms complexes of significantly higher stability than the heptadentate OxyMepa. X-ray crystal structures of the Lu3+ complexes were obtained, revealing that Oxyaapa saturates the coordination sphere of Lu3+, whereas OxyMepa leaves an additional open coordination site for a bound water ligand. Solution structural studies carried out with NMR spectroscopy revealed the presence of two possible conformations for these ligands upon Ln3+ binding. Density functional theory (DFT) calculations were applied to probe the geometries and energies of these conformations. Energy differences obtained by DFT are small but consistent with experimental data. The photophysical properties of the Eu3+ and Tb3+ complexes were characterized, revealing modest photoluminescent quantum yields of

Converting biomass-based feedstocks into polymers not only reduces our reliance on fossil fuels, but also furnishes multiple opportunities to design biorenewable polymers with targeted properties and functionalities. Here we report a series of high glass transition temperature (Tg up to 184 °C) polyesters derived from sugar-based furan derivatives as well as a joint experimental and theoretical study of substituent effects on their thermal properties. Surprisingly, we find that polymers with moderate steric hindrance exhibit the highest Tg values. Through a detailed Ramachandran-type analysis of the rotational flexibility of the polymer backbone, we find that additional steric hindrance does not necessarily increase chain stiffness in these polyesters. We attribute this interesting structure-property relationship to a complex interplay between methyl-induced steric strain and the concerted rotations along the polymer backbone. We believe that our findings provide key insight into the relationship between structure and thermal properties across a range of synthetic polymers.

Since the first isolation of graphene, the importance of van der Waals (vdW) interactions has become increasingly recognized in the burgeoning field of layered materials. In this work, infrared nanoimaging techniques and theoretical modeling are used to unravel the critical role played by interfacial vdW interactions in governing the stability of violet phosphorus (VP)—a recently rediscovered wide bandgap p‐type semiconductor—when exfoliated on different substrates. It is demonstrated that vdW interactions with the underlying substrate can have a profound influence on the stability of exfoliated VP flakes and investigate how these interactions are affected by flake thickness, substrate properties (e.g., substrate hydrophilicity, surface roughness), and the exfoliation process. These findings highlight the key role played by interfacial vdW interactions in governing the stability and physical properties of layered materials, and can be used to guide substrate selection in the preparation and study of this important class of materials. [ABSTRACT FROM AUTHOR]

A summary of the technical advances that are incorporated in the fourth major release of the Q-Chem quantum chemistry program is provided, covering approximately the last seven years. These include developments in density functional theory methods and algorithms, nuclear magnetic resonance (NMR) property evaluation, coupled cluster and perturbation theories, methods for electronically excited and open-shell species, tools for treating extended environments, algorithms for walking on potential surfaces, analysis tools, energy and electron transfer modelling, parallel computing capabilities, and graphical user interfaces. In addition, a selection of example case studies that illustrate these capabilities is given. These include extensive benchmarks of the comparative accuracy of modern density functionals for bonded and non-bonded interactions, tests of attenuated second order Møller-Plesset (MP2) methods for intermolecular interactions, a variety of parallel performance benchmarks, and tests of the accuracy of implicit solvation models. Some specific chemical examples include calculations on the strongly correlated Cr2 dimer, exploring zeolite-catalysed ethane dehydrogenation, energy decomposition analysis of a charged ter-molecular complex arising from glycerol photoionisation, and natural transition orbitals for a Frenkel exciton state in a nine-unit model of a self-assembling nanotube.

Molecular force fields have been approaching a generational transition over the past several years, moving away from well-established and well-tuned, but intrinsically limited, fixed point charge models toward more intricate and expensive polarizable models that should allow more accurate description of molecular properties. The recently introduced AMOEBA force field is a leading publicly available example of this next generation of theoretical model, but to date, it has only received relatively limited validation, which we address here. We show that the AMOEBA force field is in fact a significant improvement over fixed charge models for small molecule structural and thermodynamic observables in particular, although further fine-tuning is necessary to describe solvation free energies of drug-like small molecules, dynamical properties away from ambient conditions, and possible improvements in aromatic interactions. State of the art electronic structure calculations reveal generally very good agreement with AMOEBA for demanding problems such as relative conformational energies of the alanine tetrapeptide and isomers of water sulfate complexes. AMOEBA is shown to be especially successful on protein-ligand binding and computational X-ray crystallography where polarization and accurate electrostatics are critical.

The molecular dipole moment (μ) is a central quantity in chemistry. It is essential in predicting infrared and sum-frequency generation spectra as well as induction and long-range electrostatic interactions. Furthermore, it can be extracted directly—via the ground state electron density—from high-level quantum mechanical calculations, making it an ideal target for machine learning (ML). In this work, we choose to represent this quantity with a physically inspired ML model that captures two distinct physical effects: local atomic polarization is captured within the symmetry-adapted Gaussian process regression framework which assigns a (vector) dipole moment to each atom, while the movement of charge across the entire molecule is captured by assigning a partial (scalar) charge to each atom. The resulting "MuML" models are fitted together to reproduce molecular μ computed using high-level coupled-cluster theory and density functional theory (DFT) on the QM7b dataset, achieving more accurate results due to the physics-based combination of these complementary terms. The combined model shows excellent transferability when applied to a showcase dataset of larger and more complex molecules, approaching the accuracy of DFT at a small fraction of the computational cost. We also demonstrate that the uncertainty in the predictions can be estimated reliably using a calibrated committee model. The ultimate performance of the models—and the optimal weighting of their combination—depends, however, on the details of the system at hand, with the scalar model being clearly superior when describing large molecules whose dipole is almost entirely generated by charge separation. These observations point to the importance of simultaneously accounting for the local and non-local effects that contribute to μ; furthermore, they define a challenging task to benchmark future models, particularly those aimed at the description of condensed phases. [ABSTRACT FROM AUTHOR]

In this work, we investigate how geometric changes influence the static dipole polarizability (α) of a water molecule by explicitly computing the corresponding dipole polarizability surface (DPS) across 3125 total (1625 symmetry-unique) geometries using linear response coupled cluster theory including single, double, and triple excitations (LR-CCSDT) and the doubly augmented triple-ζ basis set (d-aug-cc-pVTZ). Analytical formulae based on power series expansions of this ab initio surface are generated using linear least-squares analysis and provide highly accurate estimates of this quantity as a function of molecular geometry (i.e., bond and angle variations) in a computationally tractable manner. An additional database, which consists of 25 representative molecular geometries and incorporates a more thorough treatment of both basis sets and core electron effects, is provided as a current benchmark for this quantity and the corresponding leading-order C6 dispersion coefficient. This database has been utilized to assess the importance of these effects as well as the relative accuracy that can be obtained using several quantum chemical methods and a library of density functional approximations. In addition to high-level electron correlation methods (like CCSD) and our analytical least-squares formulae, we find that the SCAN0, PBE0, MN15, and B97-2 hybrid functionals yield the most accurate descriptions of the molecular polarizability tensor in H2O. Using first-order perturbation theory, we compute the zero-point vibrational correction to α at the CCSDT/d-aug-cc-pVTZ level and find that this correction contributes approximately 3% to the isotropic (αiso) and nearly 50% to the anisotropic (αaniso) polarizability values. In doing so, we find that αiso = 9.8307 bohr3, which is in excellent agreement with the experimental value of 9.83 ± 0.02 bohr3 provided by Russell and Spackman. The DPS reported herein provides a benchmark-quality quantum mechanical estimate of this fundamental quantity of interest and should find extensive use in the development (and assessment) of next-generation force fields and machine-learning based approaches for modeling water in complex condensed-phase environments. [ABSTRACT FROM AUTHOR]

Classical intermolecular potentials typically require an extensive parametrization procedure for any new compound considered. To do away with prior parametrization, we propose a combination of physics-based potentials with machine learning (ML), coined IPML, which is transferable across small neutral organic and biologically relevant molecules. ML models provide on-the-fly predictions for environment-dependent local atomic properties: electrostatic multipole coefficients (significant error reduction compared to previously reported), the population and decay rate of valence atomic densities, and polarizabilities across conformations and chemical compositions of H, C, N, and O atoms. These parameters enable accurate calculations of intermolecular contributions—electrostatics, charge penetration, repulsion, induction/polarization, and many-body dispersion. Unlike other potentials, this model is transferable in its ability to handle new molecules and conformations without explicit prior parametrization: All local atomic properties are predicted from ML, leaving only eight global parameters—optimized once and for all across compounds. We validate IPML on various gas-phase dimers at and away from equilibrium separation, where we obtain mean absolute errors between 0.4 and 0.7 kcal/mol for several chemically and conformationally diverse datasets representative of non-covalent interactions in biologically relevant molecules. We further focus on hydrogen-bonded complexes—essential but challenging due to their directional nature—where datasets of DNA base pairs and amino acids yield an extremely encouraging 1.4 kcal/mol error. Finally, and as a first look, we consider IPML for denser systems: water clusters, supramolecular host-guest complexes, and the benzene crystal. [ABSTRACT FROM AUTHOR]

Analysis of remote sensing data requires a mix of technical data analysis and expert judgment. Although there is considerable empirical evidence that expert judgments reflect substantial biases, the impact of judgment biases in remote sensing and similar types of technical data analyses has not been investigated. In particular, judgment research suggests that experts are prone to a confirmation bias--where focus on a proposed hypothesis leads the expert to seek and overweigh confirming versus disconfirming evidence. In technical data analysis, this predicts a tendency toward false positives in interpretation--concluding that sensor data support a hypothesis when they do not. In this paper, we empirically examine confirmation bias in technical data analysis of remote sensing data, along with an approach to mitigating this bias that systematically promotes consideration of alternative causes in the analysis. Results suggest that analysts do exhibit confirmation bias in their technical data analysis of remote sensing data, and furthermore, that structured consideration of alternative causes mitigates this bias. Index Terms--Alternative causes approach, confirmation bias, heuristics and biases, remote sensing, technical data analysis.

Novel liquid crystals based on fluorinated carbon chains and terminated with SF(sub 5) groups are presented. The compound in this series reveals a high degree of undercooling, which is rationalized using finite size effects on nucleation.

We show that the often unsatisfactory performance of Mo\ller–Plesset second-order perturbation theory (MP2) for the dispersion interaction between closed-shell molecules can be rectified by adding a correction ΔCn/Rn, to its long-range behavior. The dispersion-corrected MP2 (MP2+ΔvdW) results are in excellent agreement with the quantum chemistry “gold standard” [coupled cluster theory with single, double and perturbative triple excitations, CCSD(T)] for a range of systems bounded by hydrogen bonding, electrostatics and dispersion forces. The MP2+ΔvdW method is only mildly dependent on the short-range damping function and consistently outperforms state-of-the-art dispersion-corrected density-functional theory. [ABSTRACT FROM AUTHOR]

The resolution-of-the-identity (RI) approximation has placed the onus of the cost of a second-order Mo\ller-Plesset (MP2) calculation on the underlying self-consistent field (SCF) calculation for many moderately sized molecules. A dual-basis approach to the SCF calculation, based on previous methods demonstrated for density functional theory, is combined with RI-MP2 calculations, and small basis subsets for cc-pVTZ, cc-pVQZ, and 6-311++G(3df,3pd) are presented. These subsets provide time savings of greater than 90%, with negligible errors in absolute and relative energies, compared to the associated full-basis counterpart. The method is tested with a series of rotational barriers, relative conformational energies of alanine tetrapeptides, as well as the full G3/99 molecular set. RI-MP2 calculations on alanine octapeptides (40 heavy atoms, 3460 basis functions), using cc-pVQZ, are presented. Results improve upon previous methods that diagonalize the virtual space separately. [ABSTRACT FROM AUTHOR]

The analytic gradients of dual-basis (DB) Hartree-Fock and density functional theory energies have provided an opportunity for capturing large basis-set gradient effects at reduced cost. The DB-self consistent field (SCF) gradients have served as an economical means to obtain accurate nuclear forces for geometry optimizations, exhibiting up to 75% savings, relative to large-basis calculations.