Correction: Atomate2: modular workflows for materials science
[This corrects the article DOI: 10.1039/D5DD00019J.].
Ganose, Alex M↗
Engineering topics
Horton, Matthew
Publications and source records attributed to Horton, Matthew.
Expanding the Material Search Space for Multivalent Cathodes
Multivalent batteries are an energy storage technology with the potential to surpass lithium-ion batteries; however, their performance have been limited by the low voltages and poor solid-state ionic mobility of available cathodes. A computational screening approach to identify high-performance multivalent intercalation cathodes among materials that do not contain the working ion of interest has been developed, which greatly expands the search space that can be considered for material discovery. This approach has been applied to magnesium cathodes as a proof of concept, and four resulting candidate materials [NASICON V 2 (PO 4 ) 3 , birnessite NaMn 4 O 8 , tavorite MnPO 4 F, and spinel MnO 2 ] are discussed in further detail. In examining the ion migration environment and associated Mg 2+ migration energy in these materials, local energy maxima are found to correspond with pathway positions where Mg 2+ passes through a plane of anion atoms. While previous studies have established the influence of local coordination on multivalent ion mobility, these results suggest that considering both the type of the local bonding environment and available free volume for the mobile ion along its migration pathway can be significant for improving solid-state mobility.
25 ENERGY STORAGE↗
Persona of Transition Metal Ions in Solids: A Statistical Learning on Local Structures of Transition Metal Oxides
Abstract The local structure of a transition metal (TM) ion is a function of cation elements and valence states. More than that, in this work, by employing a trove of first‐principles data of TM oxides, the local structures of TM cations are statistically analyzed to extract detailed information about cation site preference, bond length, site structural distortion, and cation magnetization. It is found that cation radius alone poorly describes the local structure of a transition metal oxide, while the statistics of coordination number as well as the TMO bond length distribution, especially that of the 3d TMs, can provide comprehensive knowledge for understanding the behavior of TM elements. Based on these statistics, the interplay of site distortion due to the Jahn–Teller effect, cation site similarity, and a new set of ionic radii are all obtained to chart the “persona” of transition metal ions in solids.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
A framework for quantifying uncertainty in DFT energy corrections
In this work, we demonstrate a method to quantify uncertainty in corrections to density functional theory (DFT) energies based on empirical results. Such corrections are commonly used to improve the accuracy of computational enthalpies of formation, phase stability predictions, and other energy-derived properties, for example. We incorporate this method into a new DFT energy correction scheme comprising a mixture of oxidation-state and composition-dependent corrections and show that many chemical systems contain unstable polymorphs that may actually be predicted stable when uncertainty is taken into account. We then illustrate how these uncertainties can be used to estimate the probability that a compound is stable on a compositional phase diagram, thus enabling better-informed assessments of compound stability.
42 ENGINEERING↗
Automated Adsorption Workflow for Semiconductor Surfaces and the Application to Zinc Telluride
Surface adsorption is a crucial step in numerous processes, including heterogeneous catalysis, where the adsorption of key species is often used as a descriptor of efficiency. We present here an automated adsorption workflow for semiconductors which employs density functional theory calculations to generate adsorption data in a high-throughput manner. Starting from a bulk structure, the workflow performs an exhaustive surface search, followed by an adsorption structure construction step, which generates a minimal energy landscape to determine the optimal adsorbate-surface distance. An extensive set of energy-based, charge-based, geometric, and electronic descriptors tailored toward catalysis research are computed and saved to a personal user database. Finally, the application of the workflow to zinc telluride, a promising CO 2 reduction photocatalyst, is presented as a case study to illustrate the capabilities of this method and its potential as a material discovery tool.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Correction to Benchmarking Coordination Number Prediction Algorithms on Inorganic Crystal Structures
The corrections are typographical errors only and do not alter the results or analysis in the original manuscript.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Benchmarking Coordination Number Prediction Algorithms on Inorganic Crystal Structures
Coordination numbers and geometries form a theoretical framework for understanding and predicting materials properties. Algorithms to determine coordination numbers automatically are increasingly used for machine learning and automatic structural analysis. In this work, we introduce MaterialsCoord, a benchmark suite containing 56 experimentally-derived crystal structures (spanning elements, binaries, and ternary compounds) and their corresponding coordination environments as described in the research literature. We also describe CrystalNN, a novel algorithm for determining near neighbors. We compare CrystalNN against 7 existing near-neighbor algorithms on the MaterialsCoord benchmark, finding CrystalNN to perform similarly to several well-established algorithms. For each algorithm, we also assess computational demand and sensitivity towards small perturbations that mimic thermal motion. Finally, we investigate the similarity between bonding algorithms when applied to the Materials Project database. Finally, we expect that this work will aid the development of coordination prediction algorithms as well as improve structural descriptors for machine learning and other applications.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
A charge-density-based general cation insertion algorithm for generating new Li-ion cathode materials
Future lithium (Li) energy storage technologies, in particular solid-state configurations with a Li metal anode, opens up the possibility of using cathode materials that do not necessarily contain Li in its as-made state. To accelerate the discovery and design of such materials, we develop a general, chemically, and structurally agnostic methodology for identifying the optimal Li sites in any crystalline material. For a given crystal structure, we attempt multiple Li insertions at symmetrically in-equivalent positions by analyzing the electronic charge density obtained from first-principles density functional theory. In this report, we demonstrate the effectiveness of this procedure in successfully identifying the positions of the Li ion in well-known cathode materials using only the empty host (charged) material as guidance. Furthermore, applying the algorithm to over 2000 candidate cathode empty host materials we obtain statistics of Li site preferences to guide future developments of novel Li-ion cathode materials, particularly for solid-state applications.
25 ENERGY STORAGE↗
ChemEnv : a fast and robust coordination environment identification tool
Coordination or local environments have been used to describe, analyze and understand crystal structures for more than a century. Here, a new tool called ChemEnv, which can identify coordination environments in a fast and robust manner, is presented. In contrast to previous tools, the assessment of the coordination environments is not biased by small distortions of the crystal structure. Its robust and fast implementation enables the analysis of large databases of structures. The code is available open source within the pymatgen package and the software can also be used through a web app available on http://crystaltoolkit.org through the Materials Project.
42 ENGINEERING↗
Materials design of perovskite solid solutions for thermochemical applications
Perovskites are excellent candidate materials as oxygen carriers in thermochemical processes. Due to their versatile composition, it is possible to fine-tune the perovskite's properties. Here, we present a method for the rational design of AMO 3– δ perovskite solid solutions with two different species on the Msite in order to tune their redox behavior. To account for the different ionic radii of different transition metal species M, two distinct ions are used in a solid solution on the A site, allowing tolerance-factor adjusted materials design. Using this methodology, we can create stable perovskites over a large range of different compositions. Leveraging the infrastructure of Materials Project, we calculate redox enthalpies for the reduction of over 240 of these $(\text {A}^{\prime}_x\text {A}^{\prime\prime}_{1-x})(\text {M}^{\prime}_y\text {M}^{\prime\prime}_{1-y})$O 3 perovskites to their brownmillerite phases based on density functional theory (DFT). We compare this data to experimentally measured data on thermodynamics of 24 of these materials to verify our theoretical framework. An empirical model is formulated for predicting the enthalpy and entropy changes as a function of the perovskites non-stoichiometry δ , which can be used to simulate the equilibrium composition as a function of temperature and oxygen partial pressure and to create a perovskite search engine based on an energetic analysis of the redox cycles. The data has been added as a contribution to MPContribs, which now includes publicly available user-controlled interactive graphs based on our theoretical and experimental data.
36 MATERIALS SCIENCE↗