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Unique Terahertz Features of Fentanyl and its Analogs Revealed via High Performance Computations

机译:芬太尼的独特的太赫兹特征及其类似物通过高性能计算揭示

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Fentanyl is one of the most potent synthetic opioid pain relievers. However, the abuse of opioids may lead to death. Rapid identification methods of both known and emerging opioid substances in fentanyl family would help to prevent this abuse. Terahertz (THz) spectra provide the identification information without damaging the sample. In this study, we predict THz spectra of fentanyl and 20 of its analogs in solid state by density-functional theory method PBEh-3c to investigate the frequencies of rotational-vibrational normal modes in THz region (0.1~100 cm−1). Substitution of single bond or aromatic group of fentanyl leads to significant change of crystal packing and is reflected in its THz spectrum. We discuss structure-property relationships of these synthetic opioids such as ohmefentanyl and sufentanil that are more potent than fentanyl. Since new drugs come up in black market frequently, we applied machine learning methods to predict THz spectrum of yet unknown synthetic opioids. Other “white powders” such as sucrose and lactose will be tested to validate our prediction.
机译:芬太尼是最有效的合成阿片类疼痛的解脱器之一。然而,滥用阿片类药物可能导致死亡。芬太尼y家族中已知和新出现的阿片类药物的快速鉴定方法将有助于防止这种滥用。 Terahertz(THz)光谱提供识别信息而不会损坏样品。在本研究中,我们通过密度函数理论方法PBEH-3C预测固态的固态芬太尼和20种的THz光谱,研究了THZ区域的旋转振动正常模式的频率(0.1〜100厘米 -1 )。芬太尼的单键或芳族基团的取代导致晶体包装的显着变化,并反映在其THz光谱中。我们讨论这些合成阿片类化合物的结构性质关系,例如ohmefentanyl和sufentanil,其比芬太尼更有效。由于新药经常出现在黑色市场中,我们应用了机器学习方法来预测尚不清楚的合成阿片类药物。将测试其他“白粉”,例如蔗糖和乳糖以验证我们的预测。

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