论文标题
通过混合SDE和MD方法进行核感应线形建模
Nuclear Induction Lineshape Modeling via Hybrid SDE and MD Approach
论文作者
论文摘要
发现在磁场梯度存在下，无核诱导衰减的温度依赖性在加热时表现出在气体中的运动变窄，这种行为与液体中观察到的行为相反。这导致了理论框架的修订，以包括对粒子轨迹的更详细的描述，因为变质机制取决于历史。在自由扩散和单个组件的情况下，新模型会产生正确的温度趋势。在当前形式主义中包含边界并不简单。我们提出了一种混合SDE -MD（随机微分方程 - 分子动力学）方法，该方法使用MD来计算有效的粘度，后者被馈送到SDE中以预测线形。该理论与实验一致。这种两尺度的方法弥合了短（分子碰撞）和长（核诱导）时标之间的缝隙，为具有边界，化学物种和分子间电位的混合物的复杂环境建模为建模铺平了道路。
The temperature dependence of the nuclear free induction decay in the presence of a magnetic-field gradient was found to exhibit motional narrowing in gases upon heating, a behavior that is opposite to that observed in liquids. This has led to the revision of the theoretical framework to include a more detailed description of particle trajectories, since decoherence mechanisms depend on histories. In the case of free diffusion and single component, the new model yields the correct temperature trends. Inclusion of boundaries in the current formalism is not straightforward. We present a hybrid SDE-MD (stochastic differential equation - molecular dynamics) approach whereby MD is used to compute an effective viscosity and the latter is fed to the SDE to predict the lineshape. The theory is in agreement with experiments. This two-scale approach, which bridges the gap between short (molecular collisions) and long (nuclear induction) timescales, paves the way for the modeling of complex environments with boundaries, mixtures of chemical species and intermolecular potentials.
