Ab initio prediction of the polymorph phase diagram for crystalline methanol.

Organic crystals frequently adopt multiple distinct polymorphs exhibiting different properties. The ability to predict not only what crystal forms might occur, but under what experimental thermodynamic conditions those polymorphs are stable would be immensely valuable to the pharmaceutical industry and others. Starting only from knowledge of the experimental crystal structures, this study successfully predicts the methanol crystal polymorph phase diagram from first-principles quantum chemistry, mapping out the thermodynamic regions of stability for three polymorphs over the range 0-400 K and 0-6 GPa. The agreement between the predicted and experimental phase diagrams corresponds to predicting the relative polymorph free energies to within ∼0.5 kJ mol-1 accuracy, which is achieved by employing fragment-based second-order Møller-Plesset perturbation theory and coupled cluster theory plus a quasi-harmonic treatment of the phonons

High fidelity sorting of remarkably similar components via metal-mediated assembly.

Subtle differences in ligand coordination angle and rigidity lead to high fidelity sorting between individual components displaying identical coordination motifs upon metal-mediated self-assembly. Narcissistic self-sorting can be achieved between highly similar ligands that vary minimally in rigidity and internal coordination angle upon combination with Fe(ii) ions and 2-formylpyridine. Selective, sequential cage formation can be precisely controlled in a single flask from a mix of three different core ligands (and 33 total components) differing only in the hybridization of one group that is uninvolved in the metal coordination process

Modeling the α- and β-resorcinol phase boundary via combination of density functional theory and density functional tight-binding

The ability to predict not only what organic crystal structures might occur but also the thermodynamic conditions under which they are the most stable would be extremely useful for discovering and designing new organic materials. The present study takes a step in that direction by predicting the temperature- and pressure-dependent phase boundary between the α and β polymorphs of resorcinol using density functional theory (DFT) and the quasi-harmonic approximation. To circumvent the major computational bottleneck associated with computing a well-converged phonon density of states via the supercell approach, a recently developed approximation is employed, which combines a supercell phonon density of states from dispersion-corrected third-order density functional tight binding [DFTB3-D3(BJ)] with frequency corrections derived from a smaller B86bPBE-XDM functional DFT phonon calculation on the crystallographic unit cell. This mixed DFT/DFTB quasi-harmonic approach predicts the lattice constants and unit cell volumes to within 1%-2% at lower pressures. It predicts the thermodynamic phase boundary in almost perfect agreement with the experiment, although this excellent agreement does reflect fortuitous cancellation of errors between the enthalpy and entropy of transition

Parameter Estimation from Time-Series Data with Correlated Errors: A Wavelet-Based Method and its Application to Transit Light Curves

We consider the problem of fitting a parametric model to time-series data that are afflicted by correlated noise. The noise is represented by a sum of two stationary Gaussian processes: one that is uncorrelated in time, and another that has a power spectral density varying as $1/f^\gamma$. We present an accurate and fast [O(N)] algorithm for parameter estimation based on computing the likelihood in a wavelet basis. The method is illustrated and tested using simulated time-series photometry of exoplanetary transits, with particular attention to estimating the midtransit time. We compare our method to two other methods that have been used in the literature, the time-averaging method and the residual-permutation method. For noise processes that obey our assumptions, the algorithm presented here gives more accurate results for midtransit times and truer estimates of their uncertainties.Comment: Accepted in ApJ. Illustrative code may be found at http://www.mit.edu/~carterja/code/ . 17 page

Conductance of a Conjugated Molecule with Carbon Nanotube Contacts

Calculations of the conductance of a carbon nanotube (CNT)-molecule-CNT structure are in agreement with experimental measurements [1]. The features in the transmission correspond directly to the features of the isolated molecular orbitals. The HOMO provides conductance at low bias that is relatively insensitive to the end groups of the cut CNTs, the cut angle, or the number of molecular bridges. A molecular conformation change not directly in the path of the carrier transport increases the resistance by over 2 orders of magnitude. [1] X. Guo, J. P. Small, J. E. Klare, Y. Wang, M. S. Purewal, I. W. Tam, B. H. Hong, R. Caldwell, L. Huang, S. O'Brien, et al., Science 311, 356 (2006), URL http://www.sciencemag.org/cgi/content/abstract/311/5759/356Comment: 15 Pages, 4 figures, 1 tabl

Systematic inference of the long-range dependence and heavy-tail distribution parameters of ARFIMA models

Long-Range Dependence (LRD) and heavy-tailed distributions are ubiquitous in natural and socio-economic data. Such data can be self-similar whereby both LRD and heavy-tailed distributions contribute to the self-similarity as measured by the Hurst exponent. Some methods widely used in the physical sciences separately estimate these two parameters, which can lead to estimation bias. Those which do simultaneous estimation are based on frequentist methods such as Whittle’s approximate maximum likelihood estimator. Here we present a new and systematic Bayesian framework for the simultaneous inference of the LRD and heavy-tailed distribution parameters of a parametric ARFIMA model with non-Gaussian innovations. As innovations we use the α-stable and t-distributions which have power law tails. Our algorithm also provides parameter uncertainty estimates. We test our algorithm using synthetic data, and also data from the Geostationary Operational Environmental Satellite system (GOES) solar X-ray time series. These tests show that our algorithm is able to accurately and robustly estimate the LRD and heavy-tailed distribution parameters

Bridging photochemistry and photomechanics with NMR crystallography: the molecular basis for the macroscopic expansion of an anthracene ester nanorod

Crystals composed of photoreactive molecules represent a new class of photomechanical materials with the potential to generate large forces on fast timescales. An example is the photodimerization of 9-tert-butyl-anthracene ester (9TBAE) in molecular crystal nanorods that leads to an average elongation of 8%. Previous work showed that this expansion results from the formation of a metastable crystalline product. In this article, it is shown how a novel combination of ensemble oriented-crystal solid-state NMR, X-ray diffraction, and first principles computational modeling can be used to establish the absolute unit cell orientations relative to the shape change, revealing the atomic-resolution mechanism for the photomechanical response and enabling the construction of a model that predicts an elongation of 7.4%, in good agreement with the experimental value. According to this model, the nanorod expansion does not result from an overall change in the volume of the unit cell, but rather from an anisotropic rearrangement of the molecular contents. The ability to understand quantitatively how molecular-level photochemistry generates mechanical displacements allows us to predict that the expansion could be tuned from +9% to −9.5% by controlling the initial orientation of the unit cell with respect to the nanorod axis. This application of NMR-assisted crystallography provides a new tool capable of tying the atomic-level structural rearrangement of the reacting molecular species to the mechanical response of a nanostructured sample

A systematic review of frameworks for the interrelationships of mental health evidence and policy in low- and middle-income countries

Background: The interrelationships between research evidence and policy-making are complex. Different theoretical frameworks exist to explain general evidence–policy interactions. One largely unexplored element of these interrelationships is how evidence interrelates with, and influences, policy/political agenda-setting. This review aims to identify the elements and processes of theories, frameworks and models on interrelationships of research evidence and health policy-making, with a focus on actionability and agenda-setting in the context of mental health in low- and middle-income countries (LMICs). Methods: A systematic review of theories was conducted based on the BeHeMOTh search method, using a tested and refined search strategy. Nine electronic databases and other relevant sources were searched for peer-reviewed and grey literature. Two reviewers screened the abstracts, reviewed full-text articles, extracted data and performed quality assessments. Analysis was based on a thematic analysis. The included papers had to present an actionable theoretical framework/model on evidence and policy interrelationships, such as knowledge translation or evidence-based policy, specifically target the agenda-setting process, focus on mental health, be from LMICs and published in English. Results: From 236 publications included in the full text analysis, no studies fully complied with our inclusion criteria. Widening the focus by leaving out ‘agenda-setting’, we included ten studies, four of which had unique conceptual frameworks focusing on mental health and LMICs but not agenda-setting. The four analysed frameworks confirmed research gaps from LMICs and mental health, and a lack of focus on agenda-setting. Frameworks and models from other health and policy areas provide interesting conceptual approaches and lessons with regards to agenda-setting. Conclusion: Our systematic review identified frameworks on evidence and policy interrelations that differ in their elements and processes. No framework fulfilled all inclusion criteria. Four actionable frameworks are applicable to mental health and LMICs, but none specifically target agenda-setting. We have identified agenda-setting as a research theory gap in the context of mental health knowledge translation in LMICs. Frameworks from other health/policy areas could offer lessons on agenda-setting and new approaches for creating policy impact for mental health and to tackle the translational gap in LMICs

Influenza symptoms and their impact on elderly adults: randomised trial of AS03-adjuvanted or non-adjuvanted inactivated trivalent seasonal influenza vaccines.

Patient-reported outcomes (PROs) are particularly relevant in influenza vaccine trials in the elderly where reduction in symptom severity could prevent illness-related functional impairment