摘要
一位新闻记者-机器人与机器学习的工作人员新闻编辑每日新闻-人工智能的新研究是一篇报道的主题。根据NewsRx记者在美国佛罗里达州的新闻报道，研究表明：“虽然机器学习和人工智能为计算机辅助设计材料提供了很有希望的途径，但这些计算技术的复杂性仍然是特定研究领域之外的科学工作者的障碍。利用决策树模型，受经验方法启发，"为人工智能(AI)提出的知识障碍提供了一种实用的解决方案."新闻记者引用了Ave Maria University的研究，“在此，我们提出了一个模型，该模型允许定性预测离子液体的熔点，该模型来自一系列膦基离子液体的晶体学分析。通过仔细调整这些盐中阳离子的空间和电子性质，观察到熔融点的趋势。”指出了p相互作用对固态形成至关重要的意义.用现代量子晶体学方法量化了这些p相互作用的百分比,揭示了c-hp和p-p堆积相互作用与熔点之间的线性关系.通过计算研究进一步检验了这些结构-性质关系.这些结果有助于证明离子液体偶极矩与熔凝G点的反关系.这些结果提供了有价值的见解,这些特征和关系与在膦酸盐中获得低值一致,这在早期的研究中是不明显的.
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Artificial Intelligenc e is the subject of a report. According to news reporting from Florida, United S tates, by NewsRx journalists, research stated, "While machine learning and artif icial intelligence offer promising avenues in the computer-aided design of mater ials, the complexity of these computational techniques remains a barrier for sci entists outside of the specific fields of study. Leveraging decision tree models , inspired by empirical methodologies, offers a pragmatic solution to the knowle dge barrier presented by artificial intelligence (AI)." The news correspondents obtained a quote from the research from Ave Maria Univer sity, "Herein, we present a model allowing for the qualitative prediction of mel ting points of ionic liquids derived from the crystallographic analysis of a ser ies of phosphonium-based ionic liquids. By carefully tailoring the steric and el ectronic properties of the cations within these salts, trends in the melting poi nts are observed, pointing toward the critical importance of p interactions to f orming the solid state. Quantification of the percentage of these p interactions using modern quantum crystallographic approaches reveals a linear trend in the relationship of C-Hp and p-p stacking interactions with melting points. These st ructure-property relationships are further examined by using computational studi es, helping to demonstrate the inverse relationship of dipole moments and meltin g points for ionic liquids. The results provide valuable insights into the featu res and relationships that are consistent with achieving low values in phosphoni um salts, which were not apparent in earlier studies."
NETL
NSTL