Accelerating Materials Science with Big Data and Machine Learning: Poster Session
Program Organizers: Huan Tran, Georgia Institute Of Technology; Muratahan Aykol, Toyota Research Institute
Tuesday 4:45 PM
October 19, 2021
Room: Exhibit Hall B
Location: Greater Columbus Convention Center
Poster
P3-18: Rashba Spin Splitting and Photocatalytic Properties of GeC−MSSe (M=Mo, W) Van Der Waals Heterostructures: Haleem Ud Din1; 1Abbottabad University of Science & Technology
The geometry, electronic, and photocatalytic properties of vdW heterostructures of GeC and Janus transition metal dichalcogenides MSSe (M = Mo, W) monolayers are investigated by performing first-principles calculations. Two different possible models of GeC-MSSe heterostructures are presented with an alternative order of chalcogen atoms at opposite surfaces in MSSe. The most favorable stacking pattern of both models is dynamically and energetically feasible. A direct type-II band alignment is obtained in both models of understudy heterobilayer systems. In particular, a greater Rashba spin polarization is demonstrated in model 1 (GeC-WSSe) than model 2 (GeC-MoSSe) caused by the alternative order of chalcogen atoms and larger SOC effect of heavier W than Mo atoms. More interestingly, the appropriate band alignments of model 1 with the standard water redox potentials enable its capability to dissociate water into H+/H2 and O2/H2O. The GeC-MSSe are proposed promising for in future electronic, spintronics, and photocatalytic water splitting.
P3-19: Thermo-mechanical Property Prediction of High-temperature Materials Using a Python Based Interface With Quantum Espresso: Joseph Derrick1; Michael Golub1; Jing Zhang1; 1Indiana University – Purdue University Indianapolis
The aim of this work is to provide engineers a framework and tool for evaluating thermo-mechanical properties of high-temperature materials through a python-based interface that harnesses Quantum Espresso, an open-source simulation package for materials simulation. Quantum Espresso is a predictive material properties code that is based on density-functional theory, plane waves, and pseudopotentials. Several open-source python packages were used to achieve the framework and perform calculations. As this work is to establish a baseline framework upon which further improvements and modifications will be integrated, only materials with well-established testing from external sources, such as silicon carbide and titanium carbide, were used to validate the results generated.