首页|Researchers from University of Texas Austin Detail New Studies and Findings in the Area of Machine Learning (Thermophysical Property Prediction of Anion-functionalized Ionic Liquids for Co2 Capture)
Researchers from University of Texas Austin Detail New Studies and Findings in the Area of Machine Learning (Thermophysical Property Prediction of Anion-functionalized Ionic Liquids for Co2 Capture)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Research findings on Machine Learning are discussed in a new report. Accordingto news reporting originating in Austin, Texas, by NewsRx journalists, research stated, “We develop amachine learning framework for predicting the density, viscosity, and heat capacity of a family of anionfunctionalizedionic liquids for CO2 capture, specifically those with tetraalkylphosphonium cations andaprotic N-heterocyclic anions (AHAs). We screen several feature sets using group contribution-based(GC) descriptors and descriptors extracted from COSMO-RS sigma profiles (SP) to build Support VectorRegression (SVR) and Gradient-Boosted Regression (GBR) machine learning models.”
AustinTexasUnited StatesNorth and Central AmericaCyborgsEmerging TechnologiesIonic LiquidsMachine LearningSolventsUniversity of Texas Austin
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