scholarly journals The AiiDA-KKR plugin and its application to high-throughput impurity embedding into a topological insulator

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Philipp Rüßmann ◽  
Fabian Bertoldo ◽  
Stefan Blügel
Keyword(s):  
Ab Initio ◽  
High Throughput ◽  
Topological Insulator ◽  
Materials Science ◽  
Full Potential ◽  
Host Crystal ◽  
New Era ◽  
Charge Doping ◽  
Computer Based ◽  
Gap States

AbstractThe ever increasing availability of supercomputing resources led computer-based materials science into a new era of high-throughput calculations. Recently, Pizzi et al. introduced the AiiDA framework that provides a way to automate calculations while allowing to store the full provenance of complex workflows in a database. We present the development of the AiiDA-KKR plugin that allows to perform a large number of ab initio impurity embedding calculations based on the relativistic full-potential Korringa-Kohn-Rostoker Green function method. The capabilities of the AiiDA-KKR plugin are demonstrated with the calculation of several thousand impurities embedded into the prototypical topological insulator Sb2Te3. The results are collected in the JuDiT database which we use to investigate chemical trends as well as Fermi level and layer dependence of physical properties of impurities. This includes the study of spin moments, the impurity’s tendency to form in-gap states or its effect on the charge doping of the host-crystal. These properties depend on the detailed electronic structure of the impurity embedded into the host crystal which highlights the need for ab initio calculations in order to get accurate predictions.

In silico high throughput screening of bimetallic and single atom alloys using machine learning and ab initio microkinetic modelling

2020 ◽  
Vol 8 (1) ◽  
pp. 107-123 ◽  
Author(s):  
Shivam Saxena ◽  
Tuhin Suvra Khan ◽  
Fatima Jalid ◽  
Manojkumar Ramteke ◽  
M. Ali Haider
Keyword(s):  
Machine Learning ◽  
Ab Initio ◽  
High Throughput ◽  
Material Properties ◽  
In Silico ◽  
High Throughput Screening ◽  
Chemical Engineering ◽  
Materials Science ◽  
Single Atom ◽  
Single Atom Alloys

The advent of machine learning (ML) techniques in solving problems related to materials science and chemical engineering is driving expectations to give faster predictions of material properties.

ChemInform Abstract: High-Throughput ab initio Screening for Two-Dimensional Electride Materials.

ChemInform ◽  
2014 ◽  
Vol 45 (48) ◽  
pp. no-no
Author(s):  
Tomofumi Tada ◽  
Seiji Takemoto ◽  
Satoru Matsuishi ◽  
Hideo Hosono
Keyword(s):  
Ab Initio ◽  
High Throughput ◽  
Two Dimensional

A Flexible Database for Combinatorial and High-Throughput Materials Science

2005 ◽  
Vol 24 (1) ◽  
pp. 22-28 ◽  
Author(s):  
Andreas Frantzen ◽  
Daniel Sanders ◽  
Jens Scheidtmann ◽  
Ulrich Simon ◽  
Wilhelm F. Maier
Keyword(s):  
High Throughput ◽  
Materials Science

Electronic Structure Of (AgSb)xPbn-2xTen

2003 ◽  
Vol 793 ◽  
Author(s):  
Daniel I Bilc ◽  
S.D. Mahanti ◽  
M.G. Kanatzidis
Keyword(s):  
Electronic Structure ◽  
Ab Initio ◽  
Density Functional ◽  
Full Potential ◽  
Generalized Gradient ◽  
Two Component System ◽  
Functional Theory ◽  
Covalent Interaction ◽  
Salt Structure ◽  
Linearized Augmented Plane Wave

ABSTRACTComplex quaternary chalcogenides (AgSb)xPbn-2xTen (0<x<n/2) are thought to be narrow band-gap semiconductors which are very good candidates for room and high temperature thermoelectric applications. These systems form in the rock-salt structure similar to the well known two component system PbTe (x=0). In these systems Ag and Sb occupy Pb sites randomly although there is some evidence of short-range order. To gain insights into the electronic structure of these compounds, we have performed electronic structure calculations in AgSbTe2 (x=n/2). These calculations were carried out within ab initio density functional theory (DFT) using full potential linearized augmented plane wave (LAPW) method. The generalized gradient approximation (GGA) was used to treat the exchange and correlation potential. Spinorbit interaction (SOI) was incorporated using a second variational procedure. Since it is difficult to treat disorder in ab initio calculations, we have used several ordered structures for AgSbTe2. All these structures show semimetallic behavior with a pseudogap near the Fermi energy. Te and Sb p orbitals, which are close in energy, hybridize rather strongly indicating a covalent interaction between Te and Sb atoms.

Symmetry-general ab initio computation of physical properties using quantum software integrated with crystal structure databases: results and perspectives

2002 ◽  
Vol 58 (3) ◽  
pp. 349-357 ◽  
Author(s):  
Yvon Le Page ◽  
Paul W. Saxe ◽  
John R. Rodgers
Keyword(s):  
Crystal Structure ◽  
Physical Properties ◽  
Ab Initio ◽  
Materials Science ◽  
Science Research ◽  
Elastic Tensor ◽  
Pure Phase ◽  
Simulation And Experiment ◽  
Structure Databases ◽  
Using Data

The timely integration of crystal structure databases, such as CRYSTMET, ICSD etc., with quantum software, like VASP, OresteS, ElectrA etc., allows ab initio cell and structure optimization on existing pure-phase compounds to be performed seamlessly with just a few mouse clicks. Application to the optimization of rough structure models, and possibly new atomic arrangements, is detailed. The ability to reproduce observed cell data can lead to an assessment of the intrinsic plausibility of a structure model, even without a competing model. The accuracy of optimized atom positions is analogous to that from routine powder studies. Recently, the ab initio symmetry-general least-squares extraction of the coefficients of the elastic tensor for pure-phase materials using data from corresponding entries in crystal structure databases was automated. A selection of highly encouraging results is presented, stressing the complementarity of simulation and experiment. Additional physical properties also appear to be computable using existing quantum software under the guidance of an automation scheme designed following the above automation for the elastic tensor. This possibility creates the exciting perspective of mining crystal structure databases for new materials with combinations of physical properties that were never measured before. Crystal structure databases can accordingly be expected to become the cornerstone of materials science research within a very few years, adding immense practical value to the archived structure data.

scholarly journals Ab initio investigation of impurity-induced in-gap states in Bi2Te3 and Bi2Se3

2018 ◽  
Vol 98 (3) ◽  
Author(s):  
Juba Bouaziz ◽  
Manuel dos Santos Dias ◽  
Julen Ibañez-Azpiroz ◽  
Samir Lounis
Keyword(s):  
Ab Initio ◽  
Gap States

scholarly journals Enabling Solar Fuels Technology With High Throughput Experimentation

2014 ◽  
Vol 1654 ◽  
Author(s):  
J. M. Gregoire ◽  
J. A. Haber ◽  
S. Mitrovic ◽  
C. Xiang ◽  
S. Suram ◽  
...  
Keyword(s):  
High Throughput ◽  
Materials Science ◽  
Technology Development ◽  
Research Effort ◽  
Solar Fuels ◽  
Transportation Fuels ◽  
High Throughput Experimentation ◽  
Earth Abundant ◽  
Combinatorial Materials ◽  
Joint Center

ABSTRACTThe High Throughput Experimentation (HTE) project of the Joint Center for Artificial Photosynthesis (JCAP, http://solarfuelshub.org/) performs accelerated discovery of new earth-abundant photoabsorbers and electrocatalysts. Through collaboration within the DOE solar fuels hub and with the broader research community, the new materials will be utilized in devices that efficiently convert solar energy, water and carbon dioxide into transportation fuels. JCAP-HTE builds high-throughput pipelines for the synthesis, screening and characterization of photoelectrochemical materials. In addition to a summary of these pipelines, we will describe several new screening instruments for high throughput (photo-)electrochemical measurements. These instruments are not only optimized for screening against solar fuels requirements, but also provide new tools for the broader combinatorial materials science community. We will also describe the high throughput discovery, follow-on verification, and device implementation of a new quaternary metal oxide catalyst. This rapid technology development from discovery to device implementation is a hallmark of the multi-faceted JCAP research effort.

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