[HTML][HTML] High-throughput predictions of metal–organic framework electronic properties: theoretical challenges, graph neural networks, and data exploration
With the goal of accelerating the design and discovery of metal–organic frameworks (MOFs)
for electronic, optoelectronic, and energy storage applications, we present a dataset of …
for electronic, optoelectronic, and energy storage applications, we present a dataset of …
Research Update: The materials genome initiative: Data sharing and the impact of collaborative ab initio databases
Materials innovations enable new technological capabilities and drive major societal
advancements but have historically required long and costly development cycles. The …
advancements but have historically required long and costly development cycles. The …
An ecosystem for digital reticular chemistry
The vastness of the materials design space makes it impractical to explore using traditional
brute-force methods, particularly in reticular chemistry. However, machine learning has …
brute-force methods, particularly in reticular chemistry. However, machine learning has …
Assessing high-throughput descriptors for prediction of transparent conductors
The growth of materials databases has yielded significant quantities of data to mine for new
energy materials using high-throughput screening methodologies. One application of …
energy materials using high-throughput screening methodologies. One application of …
The ab initio non-crystalline structure database: empowering machine learning to decode diffusivity
Non-crystalline materials exhibit unique properties that make them suitable for various
applications in science and technology, ranging from optical and electronic devices and …
applications in science and technology, ranging from optical and electronic devices and …
The materials project: Accelerating materials design through theory-driven data and tools
Abstract The Materials Project (MP) is a community resource for theory-based data, web-
based materials analysis tools, and software for performing and analyzing calculations. The …
based materials analysis tools, and software for performing and analyzing calculations. The …
Formation of Lithium-Manganates in a Complex Slag System Consisting of Li2O-MgO-Al2O3-SiO2-CaO-MnO—A First Survey
A Schnickmann, S Hampel, T Schirmer, UEA Fittschen - Metals, 2023 - mdpi.com
Due to the increasing demand for electromobility, the recovery of technologically relevant
elements from spent Li-ion batteries is becoming increasingly important. Pyrometallurgical …
elements from spent Li-ion batteries is becoming increasingly important. Pyrometallurgical …
Candidate inorganic photovoltaic materials from electronic structure-based optical absorption and charge transport proxies
Approximately 33,000 valence-precise, ordered inorganic compounds tabulated in the
Inorganic Crystal Structure Database have been screened for their potential as photovoltaic …
Inorganic Crystal Structure Database have been screened for their potential as photovoltaic …
Research data infrastructure for high-throughput experimental materials science
Summary The High-Throughput Experimental Materials Database (HTEM-DB, htem. nrel.
gov) is a repository of inorganic thin-film materials data collected during combinatorial …
gov) is a repository of inorganic thin-film materials data collected during combinatorial …
The MAterials Simulation Toolkit (MAST) for atomistic modeling of defects and diffusion
T Mayeshiba, H Wu, T Angsten, A Kaczmarowski… - Computational Materials …, 2017 - Elsevier
Abstract The MAterials Simulation Toolkit (MAST) is a workflow manager and post-
processing tool for ab initio defect and diffusion workflows. MAST codifies research …
processing tool for ab initio defect and diffusion workflows. MAST codifies research …