Hanmei Tang and Iek-Heng Chu are co-authors on “Atomate: A High-Level Interface to Generate, Execute, and Analyze Computational Materials Science Workflows” just published in Computational Materials Science. This paper describes atomate, an open-source Python framework for computational materials science simulation, analysis, and design with an emphasis on automation and extensibility, that is built on top of pymatgen, FireWorks, and custodian. The Materials Virtual Lab are proud contributors to this great open science initiative! Check out the atomate package here.
Our work on “Effects of Transition-Metal Mixing on Na Ordering and Kinetics in Layered P2 Oxides” has just been published in Physical Review Applied.
In this work by Chen Zheng and other co-authors, we systematically investigate the effects of transition-metal (TM) mixing on Na ordering and kinetics in the NaxCo1−yMnyO2 model system using DFT calculations. We show that the TM composition at the Na(1) (face-sharing) site has a strong influence on the Na site energies, which in turn impacts the kinetics of Na diffusion towards the end of the charge. By employing a site-percolation model, we establish theoretical upper and lower bounds for TM concentrations based on their effect on Na(1) site energies, providing a framework to rationally tune mixed-TM compositions for optimal Na diffusion.
Richard Tran has written an excellent Jupyter notebook on how you can use pymatgen to automatically generate surface slabs and analyzing calculated surface energies to construct the Wulff shape. Check it out here.
Professor Ong recently gave a plenary talk on “Creating It from Bit – Designing Materials by Integrating Quantum Mechanics, Informatics and Computer Science” at the 57th Sanibel Symposium held on St Simon’s Island in Georgia, USA. The slides of this talk at available on SlideShare.
In this talk, he discussed two emerging trends that holds the promise to continue to push the envelope in computational design of materials. The first trend is the development of robust software and data frameworks for the automatic generation, storage and analysis of materials data sets. The second is the advent of reliable central materials data repositories, such as the Materials Project, which provides the research community with efficient access to large quantities of property information that can be mined for trends or new materials. The talk showed how we have leveraged on these new tools to accelerate discovery and design in energy and structural materials as well as our efforts in contributing back to the community through further tool or data development, and provide perspectives on future challenges in high-throughput computational materials design.
The Materials Virtual Lab has started matgenb, a new public repository to share example notebooks that demonstrate the utilization of open-source codes for the study of materials science. We frequently get requests (from students, postdocs, collaborators, or just general users) for example codes that demonstrate various capabilities in the open-source software we maintain and contribute to, such as the Materials Project software stack comprising pymatgen, custodian, and Fireworks. This repo is a start at building a more sustainable path towards sharing of code examples.
The first example notebook has been posted on Getting data from the Materials Project.
Our work on “Divalent-doped Na3Zr2Si2PO12 Natrium Superionic Conductor: Improving the ionic conductivity via simultaneously optimizing the phase and chemistry of the primary and secondary phases” has just been published in the Journal of Power Sources.
In this work co-first-authored by Mojitaba Samiee (Luo group) and Balachandran Radhakrishnan (Ong group), we show that divalent dopants with low solubility in NASICON lead to the formation of a conducting secondary phase, thereby improving the grain boundary conductivity compared to undoped NASICON. Concurrently, the introduction of divalent dopants is accompanied by a change in the Si/ P ratio in the primary NASICON bulk phase, transforming monoclinic NASICON to rhombohedral NASICON. NASICON chemistries with significantly improved and optimized total ionic conductivity of 2.7 mS/cm have been synthesized. This work suggests a new general direction to improve the ionic conductivity of solid electrolytes via simultaneously optimizing the primary bulk phase and the microstructure (including grain boundary segregation and secondary phases).
This week, we say goodbye to our very first alumni, Bala. We wish Bala all the best in his new post at NASA, and look forward to his future discoveries and success as a researcher!
Professor Ong has been appointed to the Editorial Board of Computational Materials Science. The goal of Computational Materials Science is to report on results that provide new insights into, or significantly expand our understanding of, the properties of materials or phenomena associated with their design, synthesis, processing, characterization, and utilization. All aspects of modern materials modeling are of interest, including quantum chemical methods, density functional theory (DFT), semi-empirical and classical approaches, statistical mechanics, atomic-scale simulations, mesoscale modeling, and phase-field techniques.
Zhuoying’s first author paper on “Li3Y(PS4)2 and Li5PS4Cl2, New Lithium Superionic Conductors Predicted from Silver Thiophosphates using Efficiently Tiered Ab Initio Molecular Dynamics Simulations” has just been published in Chemistry of Materials (Special Issue on High-Throughput Functional Materials Discovery). In this work, we propose two new lithium superionic conductors, Li3Y(PS4)2 and Li5PS4Cl2, that are predicted to have excellent ionic conductivity and potentially better stability at the interfaces compared to current state-of-the-art superionic conductors. We welcome experimental researchers to attempt synthesis of these compounds and validation of our predictions!