The modified liquid perturbation variational theory and the improved vdW-1f model were applied to calculating the equation of the state of liquid CO-N2 mixture with the ratio of 1:1, 4:1 and 1:4, respectively, in the ...The modified liquid perturbation variational theory and the improved vdW-1f model were applied to calculating the equation of the state of liquid CO-N2 mixture with the ratio of 1:1, 4:1 and 1:4, respectively, in the shock pressure range of 9-49 GPa. It was shown that the calculated result for CO-N2 mixture with the ratio of 1:1 is well consistent with the earlier experimental data. The thermodynamics equilibrium, chemical equilibrium and phase equilibrium were all considered in detail. It was found that Hugoniot of liquid CO-N2 mixture is moderately softened in the pressure range of 20-30 GPa and 30-49 GPa for different initial proportions, and that the Hugoniot is more softened in the latter pressure range, which means that the structural phase transition occurs near 20 GPa and 30 GPa. Since the shock pro-ductions may absorb a plenty of systematic energy, the shock temperature and pressure decline compared with the case of no chemical reaction. Pressures and temperatures increase gradually with the increase in the mole fraction of nitrogen composition. The results for the 1:1 CO-N2 mixture lie in the middle of two others. Therefore, it was shown that the modified Lorentz-Berthelor rule used in the scheme is effective to study shock-compression properties of liquid CO-N2 mixture under high temperatures and high pressures.展开更多
The three-dimensional structure of a biomolecule rather than its one-dimensionM sequence determines its biological function. At present, the most accurate structures are derived from experimental data measured mainly ...The three-dimensional structure of a biomolecule rather than its one-dimensionM sequence determines its biological function. At present, the most accurate structures are derived from experimental data measured mainly by two techniques： X-ray crystallog- raphy and nuclear magnetic resonance （NMR） spec- troscopy. Because neither X-ray crystallography nor NMR spectroscopy could directly measure the positions of atoms in a biomolecule, algorithms must be designed to compute atom coordinates from the data. One salient feature of most NMR structure computation algorithms is their reliance on stochastic search to find the lowest energy conformations that satisfy the experimentally- derived geometric restraints. However, neither the cor- rectness of the stochastic search has been established nor the errors in the output structures could be quantified. Though there exist exact algorithms to compute struc- tures from angular restraints, similar algorithms that use distance restraints remain to be developed. An important application of structures is rational drug design where protein-ligand docking plays a crit- ical role. In fact, various docking programs that place a compound into the binding site of a target protein have been used routinely by medicinal chemists for both lead identification and optimization. Unfortunately, de- spite ongoing methodological advances and some success stories, the performance of current docking algorithms is still data-dependent. These algorithms formulate the docking problem as a match of two sets of feature points. Both the selection of feature points and the search for the best poses with the minimum scores are accomplished through some stochastic search methods. Both the un- certainty in the scoring function and the limited sam- pling space attained by the stochastic search contribute to their failures. Recently, we have developed two novel docking algorithms： a data-driven docking algorithm and a general docking algorithm that does not rely on experimental data. Our algorithms 展开更多
基金Supported by the National Natural Science Foundation of China (Grant No. 10576020)
文摘The modified liquid perturbation variational theory and the improved vdW-1f model were applied to calculating the equation of the state of liquid CO-N2 mixture with the ratio of 1:1, 4:1 and 1:4, respectively, in the shock pressure range of 9-49 GPa. It was shown that the calculated result for CO-N2 mixture with the ratio of 1:1 is well consistent with the earlier experimental data. The thermodynamics equilibrium, chemical equilibrium and phase equilibrium were all considered in detail. It was found that Hugoniot of liquid CO-N2 mixture is moderately softened in the pressure range of 20-30 GPa and 30-49 GPa for different initial proportions, and that the Hugoniot is more softened in the latter pressure range, which means that the structural phase transition occurs near 20 GPa and 30 GPa. Since the shock pro-ductions may absorb a plenty of systematic energy, the shock temperature and pressure decline compared with the case of no chemical reaction. Pressures and temperatures increase gradually with the increase in the mole fraction of nitrogen composition. The results for the 1:1 CO-N2 mixture lie in the middle of two others. Therefore, it was shown that the modified Lorentz-Berthelor rule used in the scheme is effective to study shock-compression properties of liquid CO-N2 mixture under high temperatures and high pressures.
文摘The three-dimensional structure of a biomolecule rather than its one-dimensionM sequence determines its biological function. At present, the most accurate structures are derived from experimental data measured mainly by two techniques： X-ray crystallog- raphy and nuclear magnetic resonance （NMR） spec- troscopy. Because neither X-ray crystallography nor NMR spectroscopy could directly measure the positions of atoms in a biomolecule, algorithms must be designed to compute atom coordinates from the data. One salient feature of most NMR structure computation algorithms is their reliance on stochastic search to find the lowest energy conformations that satisfy the experimentally- derived geometric restraints. However, neither the cor- rectness of the stochastic search has been established nor the errors in the output structures could be quantified. Though there exist exact algorithms to compute struc- tures from angular restraints, similar algorithms that use distance restraints remain to be developed. An important application of structures is rational drug design where protein-ligand docking plays a crit- ical role. In fact, various docking programs that place a compound into the binding site of a target protein have been used routinely by medicinal chemists for both lead identification and optimization. Unfortunately, de- spite ongoing methodological advances and some success stories, the performance of current docking algorithms is still data-dependent. These algorithms formulate the docking problem as a match of two sets of feature points. Both the selection of feature points and the search for the best poses with the minimum scores are accomplished through some stochastic search methods. Both the un- certainty in the scoring function and the limited sam- pling space attained by the stochastic search contribute to their failures. Recently, we have developed two novel docking algorithms： a data-driven docking algorithm and a general docking algorithm that does not rely on experimental data. Our algorithms
