On the origin of the extremely different solubilities of polyethers in water

The solubilities of polyethers are surprisingly counter-intuitive. The best-known example is the difference between polyethylene glycol ([–CH2–CH2–O–]n) which is infinitely soluble, and polyoxymethylene ([–CH2–O–]n) which is completely insoluble in water, exactly the opposite of what one expects from the C/O ratios of these molecules. Similar anomalies exist for oligomeric and cyclic polyethers. To solve this apparent mystery, we use femtosecond vibrational and GHz dielectric spectroscopy with complementary ab initio calculations and molecular dynamics simulations. We find that the dynamics of water molecules solvating polyethers is fundamentally different depending on their C/O composition. The ab initio calculations and simulations show that this is not because of steric effects (as is commonly believed), but because the partial charge on the O atoms depends on the number of C atoms by which they are separated. Our results thus show that inductive effects can have a major impact on aqueous solubilities

Local orientational order in liquids revealed by resonant vibrational energy transfer

We demonstrate that local orientational ordering in a liquid can be observed in the decay of the vibrational anisotropy caused by resonant transfer of vibrational excitations between its constituent molecules. We show that the functional form of this decay is determined by the (distribution of) angles between the vibrating bonds of the molecules between which energy transfer occurs, and that the initial drop in the decay reflects the average angle between nearest neighbors. We use this effect to observe the difference in local orientational ordering in the two hydrogen-​bonded liquids ethanol and N-​methylacetamide

Predicting RP-LC retention indices of structurally unknown chemicals from mass spectrometry data

Non-target analysis combined with liquid chromatography high resolution mass spectrometry is considered one of the most comprehensive strategies for the detection and identification of known and unknown chemicals in complex samples. However, many compounds remain unidentified due to data complexity and limited number structures in chemical databases. In this work, we have developed and validated a novel machine learning algorithm to predict the retention index (ri) values for structurally (un)known chemicals bIased on their measured fragmentation pattern. The developed model, for the first time, enabled the predication of r values without the need for the exact structure of the chemicals, with an R2 of 0.91 and 0.77 and root mean squared error (RMSE) of 47 and 67 ri  units for the NORMAN (n = 3131) and amide (n = 604) test sets, respectively. This fragment based model showed comparable accuracy in ri  prediction compared to conventional descriptor-based models that rely on known chemical structure, which obtained an R2 of 0.85 with an RMSE of 67

Colored-noise thermostats \`a la carte

Recently, we have shown how a colored-noise Langevin equation can be used in the context of molecular dynamics as a tool to obtain dynamical trajectories whose properties are tailored to display desired sampling features. In the present paper, after having reviewed some analytical results for the stochastic differential equations forming the basis of our approach, we describe in detail the implementation of the generalized Langevin equation thermostat and the fitting procedure used to obtain optimal parameters. We discuss in detail the simulation of nuclear quantum effects, and demonstrate that, by carefully choosing parameters, one can successfully model strongly anharmonic solids such as neon. For the reader's convenience, a library of thermostat parameters and some demonstrative code can be downloaded from an on-line repository

Elaborating Transition Interface Sampling Methods

We review two recently developed efficient methods for calculating rate constants of processes dominated by rare events in high-dimensional complex systems. The first is transition interface sampling (TIS), based on the measurement of effective fluxes through hypersurfaces in phase space. TIS improves efficiency with respect to standard transition path sampling (TPS) rate constant techniques, because it allows a variable path length and is less sensitive to recrossings. The second method is the partial path version of TIS. Developed for diffusive processes, it exploits the loss of long time correlation. We discuss the relation between the new techniques and the standard reactive flux methods in detail. Path sampling algorithms can suffer from ergodicity problems, and we introduce several new techniques to alleviate these problems, notably path swapping, stochastic configurational bias Monte Carlo shooting moves and order-parameter free path sampling. In addition, we give algorithms to calculate other interesting properties from path ensembles besides rate constants, such as activation energies and reaction mechanisms.Comment: 36 pages, 5 figure

Double helical conformation and extreme rigidity in a rodlike polyelectrolyte

The ubiquitous biomacromolecule DNA has an axial rigidity persistence length of ~50 nm, driven by its elegant double helical structure. While double and multiple helix structures appear widely in nature, only rarely are these found in synthetic non-chiral macromolecules. Here we describe a double helical conformation in the densely charged aromatic polyamide poly(2,2'-disulfonyl-4,4'-benzidine terephthalamide) or PBDT. This double helix macromolecule represents one of the most rigid simple molecular structures known, exhibiting an extremely high axial persistence length (~1 micrometer). We present X-ray diffraction, NMR spectroscopy, and molecular dynamics (MD) simulations that reveal and confirm the double helical conformation. The discovery of this extreme rigidity in combination with high charge density gives insight into the self-assembly of molecular ionic composites with high mechanical modulus (~1 GPa) yet with liquid-like ion motions inside, and provides fodder for formation of new 1D-reinforced composites.Comment: Accepted for publication by Nature Communication