HN3 is a unique liquid energetic material that exhibits ultrafast detonation chemistry and a transition to metallic states during detonation. We combine the Chebyshev interaction model for efficient simulation (ChIMES) many-body reactive force field and the extended-Lagrangian multiscale shock technique molecular dynamics method to calculate the detonation properties of HN3 with the accuracy of Kohn-Sham density-functional theory. ChIMES is based on a Chebyshev polynomial expansion and can accurately reproduce density-functional theory molecular dynamics (DFT-MD) simulations for a wide range of unreactive and decomposition conditions of liquid HN3. We show that addition of random displacement configurations and the energies of gas-phase equilibrium products in the training set allows ChIMES to efficiently explore the complex potential energy surface. Schemes for selecting force field parameters and the inclusion of stress tensor and energy data in the training set are examined. Structural and dynamical properties and chemistry predictions for the resulting models are benchmarked against DFT-MD. We demonstrate that the inclusion of explicit four-body energy terms is necessary to capture the potential energy surface across a wide range of conditions. Our results generally retain the accuracy of DFT-MD while yielding a high degree of computational efficiency, allowing simulations to approach orders of magnitude larger time and spatial scales. The techniques and recipes for MD model creation we present allow for direct simulation of nanosecond shock compression experiments and calculation of the detonation properties of materials with the accuracy of Kohn-Sham density-functional theory.To advance our quest to understand the role of low energy electrons in biomolecular systems, we performed investigations on dissociative electron attachment (DEA) to gas-phase N-ethylformamide (NEF) and N-ethylacetamide (NEA) molecules. Both molecules contain the amide bond, which is the linkage between two consecutive amino acid residues in proteins. Thus, their electron-induced dissociation can imitate the resonant behavior of the DEA process in more complex biostructures. Our experimental results indicate that in these two molecules, the dissociation of the amide bond results in a double resonant structure with peaks at ∼5 eV and 9 eV. We also determined the energy position of resonant states for several negative ions, i.e., the other dissociation products from NEF and NEA. Our predictions of dissociation channels were supported by density functional theory calculations of the corresponding threshold energies. Our results and those previously reported for small amides and peptides imply the fundamental nature for breakage of the amide bond through the DEA process.Phonon contributions to organic crystal structures and thermochemical properties can be significant, but computing a well-converged phonon density of states with lattice dynamics and periodic density functional theory (DFT) is often computationally expensive due to the need for large supercells. Using semi-empirical methods like density functional tight binding (DFTB) instead of DFT can reduce the computational costs dramatically, albeit with noticeable reductions in accuracy. This work proposes approximating the phonon density of states via a relatively inexpensive DFTB supercell treatment of the phonon dispersion that is then corrected by shifting the individual phonon modes according to the difference between the DFT and DFTB phonon frequencies at the Γ-point.  https://www.selleckchem.com/products/ly2606368.html  The acoustic modes are then computed at the DFT level from the elastic constants. In several small-molecule crystal test cases, this combined approach reproduces DFT thermochemistry with kJ/mol accuracy and 1-2 orders of magnitude less computational effort. Finally, this approach is applied to computing the free energy differences between the five crystal polymorphs of oxalyl dihydrazide.Living organisms are characterized by the ability to process energy (all release heat). Redox reactions play a central role in biology, from energy transduction (photosynthesis, respiratory chains) to highly selective catalyzed transformations of complex molecules. Distance and scale are important electrons transfer on a 1 nm scale, hydrogen nuclei transfer between molecules on a 0.1 nm scale, and extended catalytic processes (cascades) operate most efficiently when the different enzymes are under nanoconfinement (10 nm-100 nm scale). Dynamic electrochemistry experiments (defined broadly within the term "protein film electrochemistry," PFE) reveal details that are usually hidden in conventional kinetic experiments. In PFE, the enzyme is attached to an electrode, often in an innovative way, and electron-transfer reactions, individual or within steady-state catalytic flow, can be analyzed in terms of precise potentials, proton coupling, cooperativity, driving-force dependence of rates, and reversibility (a mark of efficiency). The electrochemical experiments reveal subtle factors that would have played an essential role in molecular evolution. This article describes how PFE is used to visualize and analyze different aspects of biological redox chemistry, from long-range directional electron transfer to electron/hydride (NADPH) interconversion by a flavoenzyme and finally to NADPH recycling in a nanoconfined enzyme cascade.Microemulsions, mixtures of oil, water, and surfactant, are thermodynamically stable. Unlike conventional emulsions, microemulsions form spontaneously, have a monodisperse droplet size that can be controlled by adjusting the surfactant concentration, and do not degrade with time. To make microemulsions, a judicious choice of surfactant molecules must be made, which significantly limits their potential use. Nanoparticle surfactants, on the other hand, are a promising alternative because the surface chemistry needed to make them bind to a liquid-liquid interface is both well flexible and understood. Here, we derive a thermodynamic model predicting the conditions in which nanoparticle surfactants drive spontaneous emulsification that agrees quantitatively with experiments using Noria nanoparticles. This new class of microemulsions inherits the mechanical, chemical, and optical properties of the nanoparticles used to form them, leading to novel applications.