Molecular Screening for Terahertz Detection with Machine-Learning-Based Methods
Molecular Screening for Terahertz Detection with Machine-Learning-Based Methods
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DOI：
10.1103/physrevx.11.041035
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发表时间：
2021-11-18
影响因子：
12.5
通讯作者：
Rosta, Edina
中科院分区：
文献类型：
--
作者：
Koczor-Benda, Zsuzsanna;Boehmke, Alexandra L.;Rosta, Edina
基于分子光力学原理，研究了在太赫兹波探测中实现高效信号上转换的分子要求。我们讨论了哪些分子和光谱特性对于预测有效的THz检测是最重要的，并概述了一种基于量子化学和机器学习方法的计算方法来计算这些特性。我们验证了这种方法的体积和表面增强拉曼散射和红外吸收测量。我们开发了一种虚拟筛选方法，该方法在数百万种市售化合物的数据库上进行。大约3000种化合物的量子化学计算得到了机器学习方法的补充，以预测93000种有机分子的检测适用性。基于吸收和拉曼散射强度对振动光谱特性进行训练。我们的顶级分子的转化强度比数据库中的平均分子高两个数量级。我们还讨论了其他性质，如分子的形状和自组装性能如何影响检测效率。我们确定了分子中存在的分子部分，其表明THz检测的高活性，并显示了一个例子，其中一个常用的自组装化合物的简单修饰可以提高活性85倍。我们的筛选方法的能力证明在窄带和宽带检测的例子，其可能的应用在表面增强光谱也进行了讨论。
The molecular requirements are explored for achieving efficient signal up-conversion in a recently developed technique for terahertz (THz) detection based on molecular optomechanics. We discuss which molecular and spectroscopic properties are most important for predicting efficient THz detection and outline a computational approach based on quantum-chemistry and machine-learning methods for calculating these properties. We validate this approach by bulk and surface-enhanced Raman scattering and infrared absorption measurements. We develop a virtual screening methodology performed on databases of millions of commercially available compounds. Quantum-chemistry calculations for about 3000 compounds are complemented by machine-learning methods to predict applicability of 93 000 organic molecules for detection. Training is performed on vibrational spectroscopic properties based on absorption and Raman scattering intensities. Our top molecules have conversion intensity two orders of magnitude higher than an average molecule from the database. We also discuss how other properties like molecular shape and self-assembling properties influence the detection efficiency. We identify molecular moieties whose presence in the molecules indicates high activity for THz detection and show an example where a simple modification of a frequently used self-assembling compound can enhance activity 85-fold. The capabilities of our screening method are demonstrated on narrow-band and broadband detection examples, and its possible applications in surface-enhanced spectroscopy are also discussed.