Sechergraham2320

Self-oscillating chemical reactions that undergo reaction-diffusion (RD) phenomena have shown great potential for designing stimuli-responsive materials. Belousov-Zhabotinsky (BZ) reactions are one such class of reactions that exhibit nonlinear chemical oscillations due to redox cycles of the metal-ion catalyst by virtue of Hopf bifurcation. Using bifurcation analyses, here we investigate the BZ reactions, catalyzed by 0D-2D catalytic nanomats and bare nanosheets, which are known to exhibit enhanced dynamic response due to catalysts' heterogeneity. Specifically, we incorporate the nanocatalysts' activity in the kinetic model of the BZ reactions and, subsequently, use catalysts' activity as the bifurcation parameter for analyses. By computing higher-order Lyapunov and frequency coefficients, we have revealed new oscillatory regimes in the bifurcation diagram, including re-entrant regions where sustained oscillations are unexpectedly suppressed, even with high catalytic activity. In addition, we also calculate the amplitude and frequency of BZ oscillations in each of these regions as a function of nanocatalysts' activity. We believe that our current findings can be used to harness the nonlinearity of RD-based dynamical systems to provide unique functionalities to active stimuli-response systems.Computationally inexpensive particle-based coarse-grained (CG) models are essential for use in molecular dynamics (MD) simulations of mesoscopically slow cooperative phenomena, such as plastic deformations in solids. Molecular crystals possessing complex symmetry present enormous practical challenges for particle-based coarse-graining at molecularly resolved scales, when each molecule is in a single-site representation, and beyond. Presently, there is no published pairwise non-bonded single-site CG potential that is able to predict the space group and structure of a molecular crystal. In this paper, we present a successful coarse-graining at a molecular level from first principles of an energetic crystal, hexahydro-1,3,5-trinitro-s-triazine (RDX) in the alpha phase, using the force-matching-based multiscale coarse-graining (MSCG/FM) approach. The new MSCG/FM model, which implements an optimal pair decomposition of the crystal Helmholtz free energy potential in molecular center-of-mass coordinates, was obtaineDX-TC-DD potential and the degree of molecular rigidity in the all-atom treatment suggests a stress-induced short-range softening of the effective intermolecular interaction as a fundamental cause of plastic instability in α-RDX. The reported RDX-TC-DD model and overall workflow to develop it open up possibilities to perform high quality simulation studies of molecular energetic materials under thermal and mechanical stimuli, including extreme conditions.The one-electron picture in molecular electronic state theory, particularly the molecular orbital (MO) theory with the Hartree-Fock approximation, has set a foundation to develop chemical science. Frontier orbital theory, or the theory of HOMO (highest occupied MO)-LUMO (lowest unoccupied MO) interaction, and the conservation rule of orbital symmetry are among the brightest achievements in a molecular orbital picture. After 70 years from the birth of frontier orbital theory, however, electronic wavefunctions treated in current quantum chemistry are often highly correlated and consist of extensive scales of electronic configurations to be more accurate and to cope with far more complicated reactions than concerted reactions. Under such circumstances, the MO approximation itself readily loses its validity, let alone the utter dominance of the HOMO-LUMO interaction. Recently, we have proposed an invariant method to extract general orbitals from such correlated electronic wavefunctions, which we refer to as Energy Natural Orbitals (ENOs) [K. Takatsuka and Y. Arasaki, J. Chem. Phys. 154, 094103 (2021)]. The energies of ENOs are summed exactly to the total electronic energy. The topological (symmetry) properties of a total wavefunction are represented by the relative phases of ENOs along with the continuity and crossing (avoided and conical intersection) among them. Only a small number of ENOs often dominate and characterize chemical reactions. With these properties of ENO, we explore a couple of simple and typical symmetry forbidden reactions, illustrating the effects of electron correlation and degeneracy in relevant ENOs. We propose the notion of "internal conical intersection" among ENOs, which leads to Jahn-Teller effect, pseudo-Jahn-Teller effect, and so on. We dare to explain the primary origin of elementary conical intersections and multidimensional avoided crossing in chemical reactions with the use of the notion of orbital crossing between those of HOMO-HOMO and LUMO-LUMO interactions and so on.Density functional theory (DFT) and beyond-DFT methods are often used in combination with photoelectron spectroscopy to obtain physical insights into the electronic structure of molecules and solids. The Kohn-Sham eigenvalues are not electron removal energies except for the highest occupied orbital. The eigenvalues of the highest occupied molecular orbitals often underestimate the electron removal or ionization energies due to the self-interaction (SI) errors in approximate density functionals. In this work, we adapt and implement the density-consistent effective potential method of Kohut, Ryabinkin, and Staroverov [J. Chem. Phys. read more 140, 18A535 (2014)] to obtain SI-corrected local effective potentials from the SI-corrected Fermi-Löwdin orbitals and density in the Fermi-Löwdin orbital self-interaction correction scheme. The implementation is used to obtain the density of states (photoelectron spectra) and HOMO-LUMO gaps for a set of molecules and polyacenes. Good agreement with experimental values is obtained compared to a range of SI uncorrected density functional approximations.Coherently controlling the spectral properties of energy-entangled photons is a key component of future entangled two-photon spectroscopy schemes that are expected to provide advantages with respect to classical methods. We present here an experimental setup based on a grating compressor. It allows for the spectral shaping of entangled photons with a sevenfold increase in resolution, compared to previous setups with a prism compressor. We evaluate the performances of the shaper by detecting sum frequency generation in a nonlinear crystal with both classical pulses and entangled photon pairs. The efficiency of both processes is experimentally compared and is in accordance with a simple model relating the classical and entangled two-photon absorption coefficients. Finally, the entangled two-photon shaping capability is demonstrated by implementing an interferometric transfer function.Highly concentrated electrolytes were recently proposed to improve the performances of aqueous electrochemical systems by delaying the water splitting and increasing the operating voltage for battery applications. While advances were made regarding their implementation in practical devices, debate exists regarding the physical origin for the delayed water reduction occurring at the electrode/electrolyte interface. Evidently, one difficulty resides in our lack of knowledge regarding ion activity arising from this novel class of electrolytes, which is necessary to estimate the Nernst potential of associated redox reactions, such as Li+ intercalation or the hydrogen evolution reaction. In this work, we first measured the potential shift of electrodes selective to Li+, H+, or Zn2+ ions from diluted to highly concentrated regimes in LiCl or LiTFSI solutions. Observing similar shifts for these different cations and environments, we establish that shifts in redox potentials from diluted to highly concentrated regimes originate in large from an increased junction potential, which is dependent on the ion activity coefficients that increase with the concentration. While our study shows that single ion activity coefficients, unlike mean ion activity coefficients, cannot be captured by any electrochemical means, we demonstrate that the proton concentration increases by one to two orders of magnitude from 1 to 15-20 mol kg-1 solutions. Combined with the increased activity coefficients, this phenomenon increases the activity of protons and thus increases the pH of highly concentrated solutions which appears acidic.The self-assembly of peptides and proteins into amyloid fibrils plays a causative role in a wide range of increasingly common and currently incurable diseases. The molecular mechanisms underlying this process have recently been discovered, prompting the development of drugs that inhibit specific reaction steps as possible treatments for some of these disorders. A crucial part of treatment design is to determine how much drug to give and when to give it, informed by its efficacy and intrinsic toxicity. Since amyloid formation does not proceed at the same pace in different individuals, it is also important that treatment design is informed by local measurements of the extent of protein aggregation. Here, we use stochastic optimal control theory to determine treatment regimens for inhibitory drugs targeting several key reaction steps in protein aggregation, explicitly taking into account variability in the reaction kinetics. We demonstrate how these regimens may be updated "on the fly" as new measurements of the protein aggregate concentration become available, in principle, enabling treatments to be tailored to the individual. We find that treatment timing, duration, and drug dosage all depend strongly on the particular reaction step being targeted. Moreover, for some kinds of inhibitory drugs, the optimal regimen exhibits high sensitivity to stochastic fluctuations. Feedback controls tailored to the individual may therefore substantially increase the effectiveness of future treatments.The interplay of kinetics and thermodynamics governs reactive processes, and their control is key in synthesis efforts. While sophisticated numerical methods for studying equilibrium states have well advanced, quantitative predictions of kinetic behavior remain challenging. We introduce a reactant-to-barrier (R2B) machine learning model that rapidly and accurately infers activation energies and transition state geometries throughout the chemical compound space. R2B exhibits improving accuracy as training set sizes grow and requires as input solely the molecular graph of the reactant and the information of the reaction type. We provide numerical evidence for the applicability of R2B for two competing text-book reactions relevant to organic synthesis, E2 and SN2, trained and tested on chemically diverse quantum data from the literature. After training on 1-1.8k examples, R2B predicts activation energies on average within less than 2.5 kcal/mol with respect to the coupled-cluster singles doubles reference within milliseconds. Principal component analysis of kernel matrices reveals the hierarchy of the multiple scales underpinning reactivity in chemical space Nucleophiles and leaving groups, substituents, and pairwise substituent combinations correspond to systematic lowering of eigenvalues. Analysis of R2B based predictions of ∼11.5k E2 and SN2 barriers in the gas-phase for previously undocumented reactants indicates that on average, E2 is favored in 75% of all cases and that SN2 becomes likely for chlorine as nucleophile/leaving group and for substituents consisting of hydrogen or electron-withdrawing groups. Experimental reaction design from first principles is enabled due to R2B, which is demonstrated by the construction of decision trees. Numerical R2B based results for interatomic distances and angles of reactant and transition state geometries suggest that Hammond's postulate is applicable to SN2, but not to E2.