论文标题
多孔半导体：增长和应用
Porous Semiconductors: Growth and Applications
论文作者
论文摘要
储层计算是预测湍流的有力工具，其简单的架构具有处理大型系统的计算效率。然而，其实现通常需要完整的状态向量测量和系统非线性知识。我们使用非线性投影函数将系统测量扩展到高维空间，然后将其输入到储层中以获得预测。我们展示了这种储层计算网络在时空混沌系统上的应用，该系统模拟了湍流的若干特征。我们表明，使用径向基函数作为非线性投影器，即使只有部分观测并且不知道控制方程，也能稳健地捕捉复杂的系统非线性。最后，我们表明，当测量稀疏、不完整且带有噪声，甚至控制方程变得不准确时，我们的网络仍然可以产生相当准确的预测，从而为实际湍流系统的无模型预测铺平了道路。
Big pores, small pores, ordered pores, random pores, they all have a function and as is often found, show behaviour in new materials that is not always predicted or obvious at the outset. I started my research journey trying to put extremely thin films onto near-perfect III-V crystals to control (opto)electronic properties and when the first TEM on our campus showed remarkable pore growth and structure in InP almost 21 years ago, the electrochemical modification of the InP made more sense. In this paper, I will summarise a few aspects of research into porous materials and semiconductors, from porous InP that led to studies of other porous semiconductors such as silicon, GaN, ZnO and Indium Tin oxide (ITO), to periodically ordered photonic crystal porous structures and some optical, thermal and electrochemical properties, photocatalysis, studies in batteries and related that were enabled or modified by the porous structure.
