首页|Dalian Ocean University Reports Findings in Machine Learning (Machine-learning-d riven discovery of metal-organic framework adsorbents for hexavalent chromium re moval from aqueous environments)
Dalian Ocean University Reports Findings in Machine Learning (Machine-learning-d riven discovery of metal-organic framework adsorbents for hexavalent chromium re moval from aqueous environments)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Machine Learning is th e subject of a report. According to news reporting out of Dalian, People's Repub lic of China, by NewsRx editors, research stated, "Metal-organic frameworks (MOF s) have been widely studied for Cr(VI) adsorption in water. Theoretically, numer ous MOFs can be synthesised by assembling diverse metals and ligands." Our news journalists obtained a quote from the research from Dalian Ocean Univer sity, "However, the traditional manual experimentation for screening high-perfor mance MOFs is resource-intensive and inefficient. A screening strategy for MOFs based on machine learning was proposed for the adsorption and removal of Cr(VI) from water. By collecting the characteristics of MOFs and the experimental param eters of Cr(VI) adsorption from the literature, a dataset was constructed to pre dict the adsorption performance. Among the six regression models, the model trai ned by the extreme gradient boosted tree algorithm had the best performance and was used to simulate the adsorption and screen potential high-performance adsorb ents. Structure-property analysis indicated that prepared MOF adsorbents with pr operties of 0.37 <largest cavity diameter <0.71 nm, 0.18 <pore volume <0.57 cm /g, 412 <specific surface area <1588 m/g, 0.43 <void fraction <0.62 will achieve enhanced adsorption of Cr(VI) in water. High-performance adsorbents wer e successfully screened using a combination of machine-learning prediction and a nalysis. Experiments were conducted to verify the exceptional adsorption capacit y of UiO-66 and MOF-801."
DalianPeople's Republic of ChinaAsiaCyborgsEmerging TechnologiesMachine Learning
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