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首页> 外文期刊>The Journal of Chemical Physics >Potential energy surfaces for high-energy N + O-2 collisions
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Potential energy surfaces for high-energy N + O-2 collisions

机译:高能量N + O-2碰撞的潜在能量表面

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Potential energy surfaces for high-energy collisions between an oxygen molecule and a nitrogen atom are useful for modeling chemical dynamics in shock waves. In the present work, we present doublet, quartet, and sextet potential energy surfaces that are suitable for studying collisions of O-2(3 Sigma g-) with N(S-4) in the electronically adiabatic approximation. Two sets of surfaces are developed, one using neural networks (NNs) with permutationally invariant polynomials (PIPs) and one with the least-squares many-body (MB) method, where a two-body part is an accurate diatomic potential and the three-body part is expressed with connected PIPs in mixed-exponential-Gaussian bond order variables (MEGs). We find, using the same dataset for both fits, that the fitting performance of the PIP-NN method is significantly better than that of the MB-PIP-MEG method, even though the MB-PIP-MEG fit uses a higher-order PIP than those used in previous MB-PIP-MEG fits of related systems (such as N-4 and N2O2). However, the evaluation of the PIP-NN fit in trajectory calculations requires about 5 times more computer time than is required for the MB-PIP-MEG fit.
机译:氧分子和氮原子之间高能碰撞的势能面可用于模拟冲击波中的化学动力学。在目前的工作中,我们提出了适用于研究电子绝热近似下O-2(3σg-)与N(S-4)碰撞的二重态、四重态和六重态势能面。开发了两组曲面,一组使用具有置换不变多项式(PIP)的神经网络(NNs),另一组使用最小二乘多体(MB)方法,其中两体部分是精确的双原子势,三体部分用混合指数高斯键序变量(MEG)中的连接PIP表示。我们发现,对于两种拟合,使用相同的数据集时,PIP-NN方法的拟合性能明显优于MB-PIP-MEG方法,尽管MB-PIP-MEG拟合使用的PIP比之前相关系统(如N-4和N2O2)的MB-PIP-MEG拟合使用的PIP高。然而,在弹道计算中评估PIP-NN拟合所需的计算机时间大约是MB-PIP-MEG拟合所需时间的5倍。

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