Data analytics approach to predict the hardness of copper matrix composites

Copper matrix composite materials have exhibited a high potential in applications where excellent conductivity and mechanical properties are required. In this study, the machine learning models have been applied to predict the hardness of the copper matrix composite materials (CuMCs) produced via the powder metallurgy technique. Six different machine learning regression models were employed. The observed CuMCs were reinforced with two different volume fractions (2 vol.% and 7vol.%) of ZrB2 particles. Based on experimental work, we extracted the independent variables (features) like the milling time (MT, Hours), dislocation density (DD, m-2), average particle size (PS, μm), density (ρ, g/cm3), and yield stress (σ, MPa) while the Vickers hardness (MPa) was used as the dependent variable. Feature selection was performed by calculation the Pearson correlation coefficient (PCC) between the independent and dependent variables. The predictive accuracy higher than 80% was achieved for Cu-7vol.% ZrB2 and lower for the Cu-2vol.% ZrB2

Probing the Structure, Stability and Hydrogen Adsorption of Lithium Functionalized Isoreticular MOF-5 (Fe, Cu, Co, Ni and Zn) by Density Functional Theory

Li adsorption on isoreticular MOFs with metal Fe, Cu, Co, Ni and Zn was studied using density function theory. Li functionalization shows a considerable structural change associated with a volume change in isoreticular MOF-5 except for the Zn metal center. Hydrogen binding energies on Li functionalized MOFs are seen to be in the range of 0.2 eV, which is the desired value for an ideal reversible storage system. This study has clearly shown that Li doping is possible only in Zn-based MOF-5, which would be better candidate to reversibly store hydrogen

First-principles study of hydrogen storage over Ni and Rh doped BN sheets

Absorption of hydrogen molecules on Nickel and Rhodium doped hexagonal boron nitride(BN) sheet is investigated by using the first principle method. The most stable site for the Ni atom was the on top side of nitrogen atom, while Rh atoms deservers a hollow site over the hexagonal BN sheet. The first hydrogen molecule was absorbed dissociatively over Rh atom, and molecularly on Ni doped BN sheet. Both Ni and Rh atoms are capable to absorb up to three hydrogen molecules chemically and the metal atom to BN sheet distance increases with the increase in the number of hydrogen molecules. Finally, our calculations offer explanation for the nature of bonding between the metal atom and the hydrogen molecules, which is due to the hybridization of metal d orbital with the hydrogen s orbital. These calculation results can be useful to understand the nature of interaction between the doped metal and the BN sheet, and their interaction with the hydrogen molecules