论文标题
通过虔诚的计算方法预测的磁性地表组件
Magnetic on-surface assemblies predicted from a pious computational method
论文作者
论文摘要
除非我们预测这一过程的结果的能力得到显着改善，否则分子自组装将不会成为构建纳米材料的常规方法。即便如此，为特定设备应用构建纳米材料需要实现具有新特性的分子组件的可靠策略。在本文中，我使用详细的统计机械模型和基于遗传算法和Markov Chain Monte Carlo（MCMC）的详细统计机械模型和新的计算方法模拟了金属邻苯丙氨酸衍生物的自组装（111）表面。该方法产生的预测不仅优于普通MCMC的预测，而且与实验结果显示出良好的一致性。至关重要的是，可以通过简单的策略来实现将不对称性的简单策略实现，这些分子组件可以证明显示局部磁矩的分子组件，并具有潜在的应用作为设备应用的非高斯噪声源。
Molecular self-assembly will not become a routine method for building nanomaterials unless our ability to predict the outcome of this process is dramatically improved. Even then, reliable strategies for realizing molecular assemblies with novel properties are required for building nanomaterials for specific device applications. In this paper, I simulate the self-assembly of metal phthalocyanine derivatives adsorbed to gold(111) surfaces using a detailed statistical mechanical model and a new computational method based upon genetic algorithms and Markov chain Monte Carlo (MCMC). This method yields predictions that are not only are superior to those of ordinary MCMC but also show good agreement with experimental results. Crucially, it is predicted that molecular assemblies displaying locally disordered magnetic moments - and having potential applications as non-Gaussian noise sources for device applications - can be realized by the simple strategy of introducing asymmetry into the phthalocyanine ligands.
