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High-throughput computational screening for solid-state Li-ion conductors
We present a computational screening of experimental structural repositories for fast Li-ion conductors, with the goal of finding new candidate materials for application as... -
Dataset of disorder-stabilized unfavorable coordination in complex ABX₂ compo...
The crystal structure of a material is essentially determined by the nature of its chemical bonding. Consequently, the atomic coordination intimately correlates with the degree... -
High-throughput computational screening for solid-state Li-ion conductors
We present a computational screening of experimental structural repositories for fast Li-ion conductors, with the goal of finding new candidate materials for application as... -
A general framework for active space embedding methods: applications in quant...
We developed a general framework for hybrid quantum-classical computing of molecular and periodic embedding calculations based on an orbital space separation of the fragment and... -
High-throughput dataset of impurity adsorption on common catalysts in biomass...
An extensive dataset consisting of adsorption energies of pernicious impurities present in biomass upgrading processes on common catalysts and support materials has been... -
ML-ready Curie temperatures and descriptors extracted from the JuHemd database
The uploaded archive provides a ML-ready data set extracted from the juHemd database (see references) augmented with supplemental data for atomic descriptors. Descriptors... -
"Fraternal-twin” ferroelectricity: competing polar states in hydrogen-doped ...
This work explores hydrogen-doped samarium nickelate from first-principles calculations. At a concentration of 1/4 hydrogen per formula unit we find a number of polar states due... -
High-quality data enabling universality of band-gap descriptor and discovery ...
Extensive machine-learning assisted research has been dedicated to predicting band gaps for perovskites, driven by their immense potential in photovoltaics. Yet, the... -
Relaxed thin film structures of one, two, and three magnetic 3d transition me...
The uploaded data set contains setups of all 6660 possible combinations of up to three atomic layers of 3d transition metals on six different FCC noble-metal substrates. The... -
Trimmed graphene nanoribbon junctions dataset
As Moore's law approaches its fundamental limits, the development of nanoelectronic devices using low-dimension materials has become a promising avenue for further... -
Thermal transport of Li₃PS₄ solid electrolytes with ab initio accuracy
The vast amount of computational studies on electrical conduction in solid-state electrolytes is not mirrored by comparable efforts addressing thermal conduction, which has been... -
Engineering frustrated lewis pair active sites in porous organic scaffolds f...
Frustrated Lewis pairs (FLPs), featuring reactive combinations of Lewis acids and Lewis bases, have been utilized for myriad metal-free homogeneous catalytic processes.... -
A bridge between trust and control: Computational workflows meet automated ba...
Compliance with good research data management practices means trust in the integrity of the data, and it is achievable by a full control of the data gathering process. In this... -
A FEM dataset of Ge film profiles and elastic energies for machine learning a...
Machine Learning (ML) can be conveniently applied to continuum materials simulations, allowing for the investigation of larger systems and longer timescales, pushing the limits... -
Phononic origin of the infrared dielectric properties of RE₂O₃ (RE = Y, Gd, H...
Understanding the phononic origin of the infrared dielectric properties of yttria (Y₂O₃) and other rare-earth sesquioxides (RE₂O₃) is a fundamental task in the search of... -
Engineering frustrated lewis pair active sites in porous organic scaffolds f...
Frustrated Lewis pairs (FLPs), featuring reactive combinations of Lewis acids and Lewis bases, have been utilized for myriad metal-free homogeneous catalytic processes.... -
A NN-Potential for phase transformations in Ge
In a recent preprint, entitled: "Development of a machine learning interatomic potential for exploring pressure-dependent kinetics of phase transitions in Germanium", we... -
Modeling the ferroelectric phase transition in barium titanate with DFT accur...
The accurate description of the structural and thermodynamic properties of ferroelectrics has been one of the most remarkable achievements of Density Functional Theory (DFT).... -
Orbital-resolved DFT+U for molecules and solids
We present an orbital-resolved extension of the Hubbard U correction to density-functional theory (DFT). Compared to the conventional shell-averaged approach, the prediction of... -
Phonon-limited mobility for electrons and holes in highly-strained silicon
Strain engineering is a widely used technique for enhancing the mobility of charge carriers in semiconductors, but its effect is not fully understood. In this work, we perform...