Browsing Materials Research Centre (MRC) by Subject "Machine learning"
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Accelerated Search of Catalysts Using Density Functional Theory and Machine Learning
The need for clean and renewable energy resources has propelled the interest in designing new catalysts producing energy from renewable resources and alternate cleaner fuels such as hydrogen, methane, ammonia, ethylene, ... -
Exploration of exfoliation, functionalization and properties of MXenes via first-principles and machine learning
The monolayers of early transition metal carbides and carbonitrides named MXenes are exfoliated from the corresponding bulk MAX phases (Mn+1AXn, M = early transition metal, A = group IIIA or IVA element and X = carbon ...