Search

This study focuses on developing a machine learning (ML) model capable of predicting relative density and equivalent strain in samples produced through hot isostatic pressing (HIP) of Ti-6Al-4 V powders. The model is trained using data from numerical simulations, incorporating processing parameters and powder size and distribution as input features. Results demonstrate strong predictive performance, with R2 values of 0.951 and 0.911 for relative density and equivalent strain, respectively. The findings also reveal that the effectiveness of ML predictions is greatly influenced by the weight functions assigned to processing parameters as input features, while the impact of powder size and distribution weighting on optimal prediction is comparatively minimal. This suggests that particle behavior may demonstrate a higher level of consistency in response to the HIP process compared to the variability created by processing parameters. The outcomes of the ML predictions are further utilized to provide a detailed discussion on how variations in temperature, pressure, and powder size and distribution impact changes in relative density and equivalent strain in a specimen. [ABSTRACT FROM AUTHOR]

In this study, the performances of Zn-doped nanotubes and Zn-doped nanocages to delivery of Triazavirin as drugs of Coronavirus disease is examined. The ΔGadsorption and recovery time for complexes of Triazavirin with Zn-C48, Zn-Si48, Zn-CNT (5, 0) and Zn-SiNT (5, 0) are calculated by theoretical methods. The ΔGadsorption of complexes of b, d, f, h including the Triazavirin-Zn-C48, Triazavirin-Zn-Si48, Triazavirin-Zn-CNT (5, 0) and Triazavirin-Zn-SiNT (5, 0) in water are -3.46, -3.61, -4.28 and -4.40 eV, respectively. The τ of complexes of b, d, f, h including the Triazavirin-Zn-C48, Triazavirin-Zn-Si48, Triazavirin-Zn-CNT (5, 0) and Triazavirin-Zn-SiNT (5, 0) in water are 55.16, 58.52, 62.06 and 67.07 s respectively. Finally, the Zn-SiNT (5, 0) and Zn-CNT (5, 0) have high potential to Triazavirin delivery and these nano-structures can propose to use as deliver of important drugs of Coronavirus disease. [ABSTRACT FROM AUTHOR]

Here, the potential of Zn doped carbon nanostructures and Zn doped silicon nanostructures to catalyze the OER and ORR processes is investigated by theoretical methods. The O*, H*, *OH, *OOH, O2 and H2O species are adsorbed on Zn-CNT(5, 0) and Zn-SiNT(5, 0). The potential-determining steps on catalysts are *OH removal and *OOH formation. The overpotential of ORR are 1.01, 0.96, 1.13 and 1.10 V, respectively. The H2O is adsorbed on Zn-C70, Zn-Si70, Zn-CNT(5, 0) and Zn-SiNT(5, 0) catalysts physically. The H2O can desorb on on Zn-C70, Zn-Si70 and Zn-CNT(5, 0) catalysts, easily. The overpotential for OER are 1.15, 1.09, 1.25 and 1.20 V, respectively. The Zn-SiNT(5, 0) catalyst has lower overpotential values than Zn-C70, Zn-Si70 and Zn-CNT(5, 0) catalysts. The Zn-SiNT(5, 0) with acceptable catalytic activity is proposed to catalyze the ORR and OER processes. [ABSTRACT FROM AUTHOR]