General Poster Session: Materials Design
Program Organizers: TMS Administration
Tuesday 5:30 PM
February 25, 2020
Room: Sails Pavilion
Location: San Diego Convention Ctr
L-30: An Investigation on Improvement of the Mechanical Properties and Fatigue Life of Steel Cardan Shafts: Mehmet Kelestemur1; Mehmet Tasdelen; 1Arkansas Tech University
A new heat treatment procedure has been investigated by considering AISI 4140 and AISI 4340 steels, which are widely used materials for cardan shafts. A multiphase in the microstructure of shafts has been detected by new technique. Additionally, the microstructure and mechanical properties of the materials obtained by the new heat treatment are determined. The production processes have been tried to be optimized for obtaining the shafts with longer fatigue life and less heat treatment defects. Static and fatigue torsion tests have been carried by using MTS torsion fatigue test device with a static torque and dynamic torques capacities of 25,000 N-m and 11,600 N-m, respectively. Both load and torsion angle-controlled tests have been conducted. Results with the new heat treatment show that it is possible to obtain much more flawless structure and, therefore longer fatigue life which can be up to three times of an ordinary shaft life.
L-31: Density Functional Theory Calculations Based on Investigation of Interaction between Multiple Hydroxyamide Ligands and La3+ Ion: Anindita Pati1; Tarun Kundu1; Snehanshu Pal2; 1Indian Institute of Technology Kharagpur; 2NIT Rourkela
Density Functional Method at B3LYP/SDD level has been implemented in order to study enhanced interaction with lanthanum ion (La3+) in presence of multiple molecules of chelating ligand hydroxyamide (HA) for efficient extraction of lanthanides. Geometrical analysis of optimized structure, thermochemical analysis, potential energy surface study, electron density profile determination and localized orbital locator analysis, molecular orbital analysis, density of states analysis and vibrational spectral (IR spectra) analysis of the complex consisting of one, two, three, and four hydroxyamide ligands with lanthanum have been performed. Calculated geometrical parameters, interaction energies, change in Gibb’s free energy, change in enthalpy, change in entropy, and HOMO-LUMO study indicate the formation feasibility, as well as stability of the complexes, is enhanced while a higher number of hydroxyamide ligand interact with La(III). The above study helps to analyse the interaction of lanthanum with hydroxyamide in order to design chelating extractant for efficient extraction of La(III).
L-32: High-throughput Screening of Hydrogen Evolution Reaction for MXenes by Single Metal Atom Doping: Jun Jiang1; Xiaoxu Wang1; Caiqun Wang1; Liutao Zhao1; 1Beijing Computing Center
MXenes, a 2D material emerging recently, has attracted more and more attentions in the field of energy storage due to its adjustable layers, hydrophilic surface and excellent conductivity. V2XO2(X = C, N) has been successfully synthesized as a MXenes, which has potential value for electrocatalytic hydrogen evolution reaction (HER). In this work, the stability, electronic structure and catalytic hydrogen evolution properties of 27 kinds of metal single atom doping with V2XO2 base 2D MXenes were systematically selected by DFT and high-throughput calculation. It is found that metal doping can not only control the stability, but also tune the adsorption capacity of hydrogen and the catalytic active sites. Through the analysis of the crystal structure and electronic properties, the metal doping can effectively achieve the single atom catalytic effect. This work can provide theoretical guidance for the application of 2D MXenes in the field of single atom catalytic HER.
L-33: Integrated Study of First-principles Calculations and Experimental Measurements for Hydrogen Effect on FCC to HCP Martensitic Transformation: Satoshi Iikubo1; Kenji Hirata2; Yui Kuroki1; Shoya Kawano1; Hiroshi Ohtani3; Motomichi Koyama3; Kaneaki Tsuzaki4; 1Kyushu Institute of Technology; 2National Institute of Advanced Industrial Science and Technology; 3Tohoku University; 4Kyushu University
Hydrogen, which can act as an interstitial species in steels, has been recognized to promote phase transformation from FCC to HCP. However, we reported a dramatic effect of interstitial hydrogen that suppresses this hcp phase transformation experimentally. More specifically, the fraction of hcp phase that forms during cooling decreases with increasing diffusible hydrogen content. To understand this new finding, first-principles calculations were employed to investigate the effect of hydrogen on the chemical driving force of the transformation of iron from the FCC to HCP phase. The minimum energy path from FCC to HCP phases shows that FCC becomes stable with increasing hydrogen content. Furthermore, vibrational contribution to the free energy destabilizes HCP phase with hydrogen, throughout the temperature region. These results explain the observed anomalous suppression of the martensitic transformation in the hydrogen-charged steel.
L-34: Prediction of Aluminum Alloy Mechanical Properties with Bayesian Neural Network: Shimpei Takemoto1; Yoshishige Okuno1; Kenji Nagata2; Junya Inoue3; Manabu Enoki3; 1Showa Denko; 2NIMS; 3The University of Tokyo
Understanding the Process-Structure-Property-Performance (PSPP) relationship is one of the goals of the computational materials design. We have constructed a Bayesian neural network for predicting multiple mechanical properties of aluminum alloys. The Markov Chain Monte Carlo (MCMC) method is widely used for simulating multi-dimensional posterior distribution in Bayesian Statistics. We have applied the Replica Exchange Monte Carlo method based on the Metropolis algorithm, an improved MCMC method, to estimate the neural network architecture and its hyperparameters. From the obtained neural network, we have discussed the PSPP relationship in aluminum alloys such as dominant factors that affect their mechanical properties. We have also addressed an inverse problem for optimizing the process for a desired set of properties.
L-35: Text Data Mining Analysis on Changes in the Number of Doctoral Degree Holders in Computational Materials Science in Japan during the Last 50 Years: Yayoi Terada1; Tetsuo Mohri1; 1IMR, Tohoku University
We estimated the change in the number of doctoral degree holders (doctors) in computational materials science (CMS) in Japan during the last 50 years. We analyzed the subjects of more than 151 thousand doctoral dissertations in science and engineering (SE) found in a Japanese doctoral dissertation database using text data mining techniques. In Japan, the number of doctors rapidly increased during the 1990s due to a reorganization of the graduate school and peaked at approximately 2000. Then, it rapidly decreased due to the recent birthrate decline in Japan. However, we found that the number of doctors in CMS continued to increase until approximately 2010. In addition to that, the decrease rate of those after 2010 has been small. Therefore, the ratio of doctors in CMS to those in SE has continued to increase. This indicates that the importance of researchers in CMS has been constantly enhanced and recognized in Japan.