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TU Dresden » Faculty of Mechanical Science and Engineering » Institute for Materials Science » Chair of Materials Science and Nanotechnology

Friday, 13 December 2019
(at 10:30 in room 115, Hallwachsstr. 3)
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Computational Materials Science from Spintronics to Thermodynamics

Dr. Rico Friedrich

Center for Autonomous Materials Design, Duke University, USA

The rational design of materials e.g. for information technology and energy is a long-standing challenge. Spintronics can realize novel electronic functionalities and increased energy efficiency. Spin transfer materials can be generated in hetero-junctions of metal-organic complexes, and Fermi-level engineering outlines a systematic path to manufacture them. From a complementary viewpoint, molecular adsorption on surfaces can be used to design surface magnetic properties. The magnetic exchange interaction and hysteresis of a substrate can be modified selectively. Different magnetic subunits within a single molecule-surface hybrid system showcase potential for intra-molecular spin-logic devices and chemisorbed molecules can manipulate the Rashba spin texture. These findings can also be employed in devices based on current induced spin-polarization, spin-orbit torques, or the Dzyaloshinskii-Moriya interaction. For the rational design of materials, thermodynamic concepts are also crucial. Spinodal decomposition - a controllable kinetic phenomenon - is proposed as a natural strategy to create superlattices of topological insulators. The resulting band structures show various features such as topological interface states, spin texture gain by nontopological states, band inversion, and Rashba-like states. The formation enthalpy - quantifying the thermodynamic stability of a compound - is key in computational materials design. For polar systems such as oxides, standard (semi-)local density functional theory leads to incorrect values. The “coordination corrected enthalpies” (CCE) method yields highly accurate results with mean absolute errors down to 27 meV/atom and is also capable of correcting the relative stability of polymorphs. Within the Automatic-Flow (AFLOW) database and software, CCE can be used for the computational design of battery materials, defect systems, and high-entropy phases.

Announcement (pdf)

Invited by G. Cuniberti

Within the nanoSeminar

last modified: 2021.05.05 Wed
author: webadmin