MAGUS: machine learning and graph theory assisted universal structure searcher
Crystal structure predictions based on first-principles calculations have gained great
success in materials science and solid state physics. However, the remaining challenges …
success in materials science and solid state physics. However, the remaining challenges …
Computational design of energy‐related materials: From first‐principles calculations to machine learning
Energy‐related materials are crucial for advancing energy technologies, improving
efficiency, reducing environmental impacts, and supporting sustainable development …
efficiency, reducing environmental impacts, and supporting sustainable development …
Recent advances in the application of machine learning to crystal behavior and crystallization process control
M Lu, S Rao, H Yue, J Han, J Wang - Crystal Growth & Design, 2024 - ACS Publications
Crystals are integral to a variety of industrial applications, such as the development of
pharmaceuticals and advancements in material science. To anticipate crystal behavior and …
pharmaceuticals and advancements in material science. To anticipate crystal behavior and …
Assessing the feasibility of near-ambient conditions superconductivity in the Lu-NH system
The report of near-ambient superconductivity in nitrogen-doped lutetium hydrides (Lu-NH)
has generated a great interest. However, conflicting results raised doubts regarding …
has generated a great interest. However, conflicting results raised doubts regarding …
Metal–organic frameworks through the lens of artificial intelligence: a comprehensive review
Metal–organic frameworks (MOFs) are a class of hybrid porous materials that have gained
prominence as a noteworthy material with varied applications. Currently, MOFs are in …
prominence as a noteworthy material with varied applications. Currently, MOFs are in …
Towards quantitative evaluation of crystal structure prediction performance
Crystal structure prediction (CSP) is now increasingly used in the discovery of novel
materials with applications in diverse industries. However, despite decades of …
materials with applications in diverse industries. However, despite decades of …
Compactness matters: Improving Bayesian optimization efficiency of materials formulations through invariant search spaces
Would you rather search for a line inside a cube or a point inside a square? Physics-based
simulations and wet-lab experiments often have symmetries (degeneracies) that allow …
simulations and wet-lab experiments often have symmetries (degeneracies) that allow …
The MatHub‐3d first‐principles repository and the applications on thermoelectrics
Abstract Following the Materials Genome Initiative project, materials research has embarked
a new research paradigm centered around material repositories, significantly accelerating …
a new research paradigm centered around material repositories, significantly accelerating …
Metolazone co-crystals-loaded oral fast dissolving films: Design, optimization, and in vivo evaluation
This study aimed to formulate and optimize metolazone (MLZ) co-crystals incorporating fast-
dissolving films (OFDFs) as an agreeable oral formulation for improving the bioavailability of …
dissolving films (OFDFs) as an agreeable oral formulation for improving the bioavailability of …
Prediction of NdFe16-based permanent-magnet compounds with high magnetization
We find a candidate for new permanent-magnet materials with the 1–16 stoichiometry on the
basis of first-principles calculations utilizing a materials database. An extremely iron-rich …
basis of first-principles calculations utilizing a materials database. An extremely iron-rich …