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1.
Trimethyl and triethyl phosphites react with diphenoquinone 3, yielding 4,4′-dihydroxydiphenyl 10; 4′-alkoxy-4-biphenylyl dialkyl phosphates 5, 4,4′-biphenylylene tetraalkyl bis(phosphates), 6, and 4′-hydroxy-4-biphenylyl dialkyl phosphates 9 are also isolated in minor yields. The effect of temperature on the reaction is studied. A mechanism for the reaction is presented which accounts for the experimental results. The reaction of trimethyl and triethyl phosphites with quinoneimines 12 gives the corresponding phosphoramidates 13, in quantitative yields.  相似文献   
2.
Abstract

UV-irradiation (λ > 313 nm) of o,o-diethyl-o-(3-chloro-4-methyl-coumarin-7-yl)-thiophosphate (Coumaphos; 1) in chloroform results in an regioselective dimerization reaction to afford the head-to-tail anti-dimer 2. The structure of 2 is established by single crystal x-ray diffraction. Singlet oxygen does not affect the formation of 2.  相似文献   
3.
Abstract

Trialkyl phosphites react with quinisatin (1) and its monohydrate 3 to give the corresponding phosphate derivatives 2a-c. The same compounds are obtained upon reacting 1 and/or 3 with the proper dialkyl phosphite. Structural reasonings based on IR, MS and NMR spectral data, are presented.  相似文献   
4.
Abstract

UV-irradiation (δ > 313nm) of O,O-diethyl-O-(4-methyl-2-oxo-2H-1-benzopyran-7-yl)-phosphoro-thioate (Potasan®) la in chloroform and/or methanol with and without singlet oxygen results in the formation of the 2-oxo-2H-1-benzopyran-phosphate 2 the 3,3′-bipotasan dehydrodimer 3, and 7-ethoxy-4-methyl-2-oxo-2H-1-benzopyran 4: the mechanisms of formation, especially for 4 are discussed.  相似文献   
5.
A study is presented on the configuration and conformation of 2-methylchromone-dimer, as well as on khellin-dimer, based on 1H NMR spectroscopy.  相似文献   
6.
Zusammenfassung Triphenylarsin reagiert mit aktiven organischen Disulfiden in siedendem Xylol oder im Sonnenlicht unter Bildung der entsprechenden Monosulfide und von Triphenylarsinsulfid. Die Entmethylierung von Khellin und Visnagin durch Einwirkung von organischen Disulfiden im Sonnenlicht wird diskutiert.  相似文献   
7.
Small integration time steps limit molecular dynamics (MD) simulations to millisecond time scales. Markov state models (MSMs) and equation-free approaches learn low-dimensional kinetic models from MD simulation data by performing configurational or dynamical coarse-graining of the state space. The learned kinetic models enable the efficient generation of dynamical trajectories over vastly longer time scales than are accessible by MD, but the discretization of configurational space and/or absence of a means to reconstruct molecular configurations precludes the generation of continuous atomistic molecular trajectories. We propose latent space simulators (LSS) to learn kinetic models for continuous atomistic simulation trajectories by training three deep learning networks to (i) learn the slow collective variables of the molecular system, (ii) propagate the system dynamics within this slow latent space, and (iii) generatively reconstruct molecular configurations. We demonstrate the approach in an application to Trp-cage miniprotein to produce novel ultra-long synthetic folding trajectories that accurately reproduce atomistic molecular structure, thermodynamics, and kinetics at six orders of magnitude lower cost than MD. The dramatically lower cost of trajectory generation enables greatly improved sampling and greatly reduced statistical uncertainties in estimated thermodynamic averages and kinetic rates.

Latent space simulators learn kinetic models for atomistic simulations and generate novel trajectories at six orders of magnitude lower cost.  相似文献   
8.
9.
Classical molecular dynamics simulates the time evolution of molecular systems through the phase space spanned by the positions and velocities of the constituent atoms. Molecular-level thermodynamic, kinetic, and structural data extracted from the resulting trajectories provide valuable information for the understanding, engineering, and design of biological and molecular materials. The cost of simulating many-body atomic systems makes simulations of large molecules prohibitively expensive, and the high-dimensionality of the resulting trajectories presents a challenge for analysis. Driven by advances in algorithms, hardware, and data availability, there has been a flare of interest in recent years in the applications of machine learning – especially deep learning – to molecular simulation. These techniques have demonstrated great power and flexibility in both extracting mechanistic understanding of the important nonlinear collective variables governing the dynamics of a molecular system, and in furnishing good low-dimensional system representations with which to perform enhanced sampling or develop long-timescale dynamical models. It is the purpose of this article to introduce the key machine learning approaches, describe how they are married with statistical mechanical theory into domain-specific tools, and detail applications of these approaches in understanding and accelerating biomolecular simulation.  相似文献   
10.
Abstract

The reaction of triphenylphosphine sulfide with tetrachloro-o-benzoquinone gives a complex of the corresponding hydroquinone and triphenylphosphine oxide. Elemental sulfur is the other product. The tetrachloro-p benzoquinone does not react to any noticeable extent under similar conditions. Several mechanisms are proposed to explain the results.  相似文献   
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