首页|Ave Maria University Reports Findings in Artificial Intelligence (Planting the S eeds of a Decision Tree for Ionic Liquids: Steric and Electronic Impacts on Melt ing Points of Triarylphosponium Ionic Liquids)
Ave Maria University Reports Findings in Artificial Intelligence (Planting the S eeds of a Decision Tree for Ionic Liquids: Steric and Electronic Impacts on Melt ing Points of Triarylphosponium Ionic Liquids)
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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."
FloridaUnited StatesNorth and Centra l AmericaArtificial IntelligenceEmerging TechnologiesIonic LiquidsMachin e LearningSolvents
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