Notes

Exclusive useful responses regarding fungal areas to several conditions within the mangroves from the Maowei Sea inside Guangxi, Tiongkok.
Although the above changes lead to lower vCAS energies, they lead to higher vCAS+1+2 energies as well as irregularities and/or discontinuities in the potential energy curves. All of the above problems can be addressed by using the spin-coupled generalized valence bond-inspired vCAS wave function for BF, which includes only a subset of the atomic valence orbitals in the active space.In this study, we investigate the structure-stability relationship of hypothetical Nd-Fe-B crystal structures using descriptor-relevance analysis and the t-SNE dimensionality reduction method. 149 hypothetical Nd-Fe-B crystal structures are generated from 5967 LA-T-X host structures in the Open Quantum Materials Database by using the elemental substitution method, with LA denoting lanthanides, T denoting transition metals, and X denoting light elements such as B, C, N, and O. By borrowing the skeletal structure of each of the host materials, a hypothetical crystal structure is created by substituting all lanthanide sites with Nd, all transition metal sites with Fe, and all light element sites with B. High-throughput first-principle calculations are applied to evaluate the phase stability of these structures. Twenty of them are found to be potentially formable. As the first investigative result, the descriptor-relevance analysis on the orbital field matrix (OFM) materials' descriptor reveals the average atomicctures.Recently, the first laser spectroscopy measurement of the radioactive RaF molecule has been reported by Ruiz et al. [Nature 581, 396 (2020)]. This and similar molecules are considered to search for the new physics effects. The radium nucleus is of interest as it is octupole-deformed and has close levels of opposite parity. The preparation of such experiments can be simplified if there are reliable theoretical predictions. It is shown that the accurate prediction of the hyperfine structure of the RaF molecule requires to take into account the finite magnetization distribution inside the radium nucleus. For atoms, this effect is known as the Bohr-Weisskopf (BW) effect. Its magnitude depends on the model of the nuclear magnetization distribution which is usually not well known. We show that it is possible to express the nuclear magnetization distribution contribution to the hyperfine structure constant in terms of one magnetization distribution dependent parameter BW matrix element for 1s-state of the corresponding hydrogen-like ion. This parameter can be extracted from the accurate experimental and theoretical electronic structure data for an ion, atom, or molecule without the explicit treatment of any nuclear magnetization distribution model. This approach can be applied to predict the hyperfine structure of atoms and molecules and allows one to separate the nuclear and electronic correlation problems. It is employed to calculate the finite nuclear magnetization distribution contribution to the hyperfine structure of the 225Ra+ cation and 225RaF molecule. For the ground state of the 225RaF molecule, this contribution achieves 4%.Molecular dynamics simulations require barostats to be performed at a constant pressure. The usual recipe is to employ the Berendsen barostat first, which displays a first-order volume relaxation efficient in equilibration but results in incorrect volume fluctuations, followed by a second-order or a Monte Carlo barostat for production runs. In this paper, we introduce stochastic cell rescaling, a first-order barostat that samples the correct volume fluctuations by including a suitable noise term. The algorithm is shown to report volume fluctuations compatible with the isobaric ensemble and its anisotropic variant is tested on a membrane simulation. Stochastic cell rescaling can be straightforwardly implemented in the existing codes and can be used effectively in both equilibration and production phases.The sound velocity and refractive index of pure N2 and of the equimolar N2-CO2 mixture are measured up to 15 GPa and 700 K in a resistive heating diamond anvil cell. The refractive index vs pressure is obtained by an interferometric method. The adiabatic sound velocity is then determined from the measurement of the Brillouin frequency shift in the backscattering geometry and the refractive index data. No phase separation of the N2-CO2 fluid mixture is observed. The fluid mixture properties are discussed in terms of ideal mixing.We present an integrated theoretical study of the structure, thermodynamic properties, dynamic localization, and glassy shear modulus of melt polymer nanocomposites (PNCs) that spans the three microstructural regimes of entropic depletion induced nanoparticle (NP) clustering, discrete adsorbed layer driven NP dispersion, and polymer-mediated bridging network. The evolution of equilibrium and dynamic properties with NP loading, total packing fraction, and strength of interfacial attraction is systematically studied based on a minimalist model. Structural predictions of polymer reference interaction site model integral equation theory are employed to establish the rich behavior of the interfacial cohesive force density, surface excess, and a measure of free volume as a function of PNC variables. The glassy dynamic shear modulus is predicted to be softened, reinforced, or hardly changed relative to the pure polymer melt depending on system parameters, as a result of the competing and qualitatively different influences of interfacial cohesion (physical bonding), free volume, and entropic depletion on dynamic localization and shear elasticity. The localization of polymer segments is the dominant factor in determining bulk PNC softening and reinforcement effects for moderate to strong interfacial attractions, respectively. While in the athermal entropy-dominated regime, the primary origin of mechanical reinforcement is the stress stored in the aggregated NP subsystem. The PNC shear modulus is often qualitatively correlated with the segment localization length but with notable exceptions. The present work provides the foundation for developing a theory of segmental relaxation, Tg changes, and collective NP dynamics in PNCs based on a self-consistent treatment of the cooperative activated motions of segments and NPs.The complexity associated with an epidemic defies any quantitatively reliable predictive theoretical scheme. Here, we pursue a generalized mathematical model and cellular automata simulations to study the dynamics of infectious diseases and apply it in the context of the COVID-19 spread. Our model is inspired by the theory of coupled chemical reactions to treat multiple parallel reaction pathways. We essentially ask the question how hard could the time evolution toward the desired herd immunity (HI) be on the lives of people? We demonstrate that the answer to this question requires the study of two implicit functions, which are determined by several rate constants, which are time-dependent themselves. Implementation of different strategies to counter the spread of the disease requires a certain degree of a quantitative understanding of the time-dependence of the outcome. Here, we compartmentalize the susceptible population into two categories, (i) vulnerables and (ii) resilients (including asymptomatic carriers), and study the dynamical evolution of the disease progression. We obtain the relative fatality of these two sub-categories as a function of the percentages of the vulnerable and resilient population and the complex dependence on the rate of attainment of herd immunity. We attempt to study and quantify possible adverse effects of the progression rate of the epidemic on the recovery rates of vulnerables, in the course of attaining HI. We find the important result that slower attainment of the HI is relatively less fatal. However, slower progress toward HI could be complicated by many intervening factors.As one of the most robust global optimization methods, simulated annealing has received considerable attention with many variations that attempt to improve the cooling schedule. This paper introduces a variant of molecular dynamics-based simulated annealing that is useful for optimizing atomistic structures, and makes use of the heat capacity of the system, determined on the fly during optimization, to adaptively control the cooling rate. This adaptive cooling approach is demonstrated to be more computationally efficient than classical simulated annealing when applied to Lennard-Jones clusters. The increase in efficiency is approximately a factor of two for clusters with 25-40 atoms, and improves as the size of the system increases.Two theorems on the eigenvalues of differences of idempotent matrices determine the natural occupation numbers and orbitals of electronic detachment, attachment, or excitation that pertain to transitions between wavefunctions that each consist of a single Slater determinant. They are also applicable to spin density matrices associated with Slater determinants. When the ranks of the matrices differ, unit eigenvalues occur. In addition, there are ±w pairs of eigenvalues where |w| ≤ 1, whose values are related to overlaps, t, between the corresponding orbitals of Amos and Hall, and Löwdin by the formula w=±1-t212. Generalized overlap amplitudes, including Dyson orbitals and their probability factors, may be inferred from these eigenvalues, which provide numerical criteria for classifying transitions according to the number of holes and particles in final states with respect to initial states, identifying the most important effects of orbital relaxation produced by self-consistent fields, and the analysis of Fukui functions. Two similar theorems that apply to sums of idempotent matrices regenerate formulae for the natural orbitals and occupation numbers of an unrestricted Slater determinant that were published first by Amos and Hall.Many natural substances and drugs are radical scavengers that prevent the oxidative damage to fundamental cell components. This process may occur via different mechanisms, among which, one of the most important, is hydrogen atom transfer. The feasibility of this process can be assessed in silico using quantum mechanics to compute ΔGHAT○. This approach is accurate, but time consuming. The use of machine learning (ML) allows us to reduce tremendously the computational cost of the assessment of the scavenging properties of a potential antioxidant, almost without affecting the quality of the results. However, in many ML implementations, the description of the relevant features of a molecule in a machine-friendly language is still the most challenging aspect. In this work, we present a newly developed machine-readable molecular representation aimed at the application of automatized ML algorithms. Reversan In particular, we show an application on the calculation of ΔGHAT○.Charge and/or energy transfer from photoexcited quantum dots (QDs) is often suppressed by a wide-bandgap shell. Here, we report an interesting, counter-intuitive observation that interfacial triplet energy transfer from QDs is not retarded but rather enabled by an insulating shell. Specifically, photoluminescence of red-emitting CdSe QDs could not be quenched by surface-anchored Rhodamine B molecules; in contrast, after ZnS shell coating, their emission was effectively quenched. Time-resolved spectroscopy reveals that the shell eliminates ultrafast hole trapping in the QDs and hence opens up the triplet exciton transfer pathway. The triplet energy of Rhodamine B can be reversely transferred back to QDs by thermal activation, or it can be passed to triplet acceptors in the solution. Capitalizing on the latter, we demonstrate red-to-blue photon upconversion based on QD-sensitized triplet-triplet annihilation with an efficiency of 2.8% and an anti-Stokes shift of 1.13 eV.
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