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Molecular dynamics simulation is an indispensable tool for understanding the collective behavior of atoms and molecules and the phases they form. Statistical mechanics provides accurate routes for predicting macroscopic properties as time-averages over visited molecular configurations - microstates. However, to obtain convergence, we need a sufficiently long record of visited microstates, which translates to the high-computational cost of the molecular simulations. In this work, we show how to use a point cloud-based deep learning strategy to rapidly predict the structural properties of liquids from a single molecular configuration. We tested our approach using three homogeneous liquids with progressively more complex entities and interactions: Ar, NO, and H2O under varying pressure and temperature conditions within the liquid state domain. Our deep neural network architecture allows rapid insight into the liquid structure, here probed by the radial distribution function, and can be used with molecular/atomistic configurations generated by either simulation, first-principle, or experimental methods.

Alzheimer's disease (AD) is characterized by progressive neurodegeneration associated with amyloid β (Aβ) peptide aggregation. The aggregation of Aβ monomers (AβMs) leads to the formation of Aβ oligomers (AβOs), the neurotoxic Aβ form, capable of permeating the cell membrane. Here, we investigated the effect of a fluorene-based active drug candidate, named K162, on both Aβ aggregation and AβO toxicity toward the bilayer lipid membrane (BLM). Electrochemical impedance spectroscopy (EIS), atomic force microscopy (AFM), and molecular dynamics (MD) were employed to show that K162 inhibits AβOs-induced BLM permeation, thus preserving BLM integrity. In the presence of K162, only shallow defects on the BLM surface were formed. Apparently, K162 modifies Aβ aggregation by bypassing the formation of toxic AβOs, and only nontoxic AβMs, dimers (AβDs), and fibrils (AβFs) are produced. Unlike other Aβ toxicity inhibitors, K162 preserves neurologically beneficial AβMs. This unique K162 inhibition mechanism provides an alternative AD therapeutic strategy that could be explored in the future.

HypothesisCalcium carbonate nucleation is often a complex and multistep process that is difficult to follow in situ. The time-resolved electrochemical and electrophoretic methods can provide a new insight into the nucleation pathway.ExperimentsHere, we used a combination of speciation calculations with time-resolved electrophoretic and potentiometric methods to monitor calcium carbonate precipitation from a slightly supersaturated solution.FindingsAfter an initial mixing period of three minutes in which metastable CaCO3 phases may have nucleated and subsequently dissolved due to locally-high supersaturations, bulk solution pH and Ca2+ concentrations stabilize before decreasing in tandem with the precipitation of a CaCO3 phase. After an hour, the precipitate is dominated by calcite that grows at the expense of dissolving vaterite. The time-dependent electrokinetic potential shows analogous signatures of multistage nucleation process: initial rapid changes in ζ-potential are followed by much slower equilibration starting about one hour after reagents are mixed. The changes in ζ-potential, solution pH, saturation indexes, and particle morphology are consistent with vaterite to calcite transformation via dissolution of the former and recrystallization of the latter. These findings highlight the potential use of ζ-potential measurements for monitoring polymorphic transformations of carbonate phases in-situ.

We perform density functional calculations of the equilibrium 57Fe/54Fe ratios for ferrous iron dissolved in periclase and MgSiO3 perovskite at the pressures and temperatures of the Earth's mantle. Pressure increases the partitioning of 57Fe into both phases by a factor of three from the Earth's surface to the core-mantle boundary. In ferropericlase, a large contribution to this increase comes from the electronic transition from high-spin to low-spin iron. Our calculations demonstrate that pressure-induced fractionation can play a major role in determining planetary iron-isotope composition., Comment: 4 pages, 3 figures, 2 tables