Crystal structure prediction dataset for molecules included in the publication Photocatalytic Proton Reduction by a Computationally Identified, Molecular Hydrogen-Bonded Framework, Journal of Materials Chemistry A (2020) Crystal structure files (CIF format) for the four molecules: 1,3,6,8-tetraphenylpyrene (TPhP), 1,3,6,8-tetrapyridin-4-yl pyrene (TPyP), and 1,3,6,8-tetra(4’-carboxyphenyl)pyrene (TBAP). All crystal structures generated for each molecules are included as separate files for each conformer of each molecule. Calculated energies and densities are included in the CIF for each structure. Energies include the intermolecular interactions and the conformational energy with respect to the lowest energy conformer of the isolat...
| openaire: EC/H2020/676580/EU//NoMaDData science and machine learning in materials science require ...
| openaire: EC/H2020/676580/EU//NoMaDData science and machine learning in materials science require ...
Some of the most successful approaches to structural design in materials chemistry have exploited st...
We show that a hydrogen-bonded framework, TBAP-α, with extended π-stacked pyrene columns has a sacri...
We show that a hydrogen-bonded framework, TBAP-α, with extended π-stacked pyrene columns has a sacri...
Crystal structure prediction datasets and calculated energies, supporting the publication "Mach...
Crystal structure prediction datasets and calculated energies, supporting the publication "Mach...
Crystal structure prediction datasets and calculated energies, supporting the publication "Mach...
Dataset supporting: Slater, A. G. et al (2016) Reticular synthesis of porous molecular 1D nanotubes...
The ability to predict the properties of a crystal structure before any empirical analysis or labora...
Computational methods used for predicting the crystal structures of organic compounds are mature eno...
Resulting low energy crystal structures from a crystal structure prediction of resorcinol. The .c...
Resulting low energy crystal structures from a crystal structure prediction of resorcinol. The .c...
Resulting low energy crystal structures from a crystal structure prediction of resorcinol. The .c...
| openaire: EC/H2020/676580/EU//NoMaDData science and machine learning in materials science require ...
| openaire: EC/H2020/676580/EU//NoMaDData science and machine learning in materials science require ...
| openaire: EC/H2020/676580/EU//NoMaDData science and machine learning in materials science require ...
Some of the most successful approaches to structural design in materials chemistry have exploited st...
We show that a hydrogen-bonded framework, TBAP-α, with extended π-stacked pyrene columns has a sacri...
We show that a hydrogen-bonded framework, TBAP-α, with extended π-stacked pyrene columns has a sacri...
Crystal structure prediction datasets and calculated energies, supporting the publication "Mach...
Crystal structure prediction datasets and calculated energies, supporting the publication "Mach...
Crystal structure prediction datasets and calculated energies, supporting the publication "Mach...
Dataset supporting: Slater, A. G. et al (2016) Reticular synthesis of porous molecular 1D nanotubes...
The ability to predict the properties of a crystal structure before any empirical analysis or labora...
Computational methods used for predicting the crystal structures of organic compounds are mature eno...
Resulting low energy crystal structures from a crystal structure prediction of resorcinol. The .c...
Resulting low energy crystal structures from a crystal structure prediction of resorcinol. The .c...
Resulting low energy crystal structures from a crystal structure prediction of resorcinol. The .c...
| openaire: EC/H2020/676580/EU//NoMaDData science and machine learning in materials science require ...
| openaire: EC/H2020/676580/EU//NoMaDData science and machine learning in materials science require ...
| openaire: EC/H2020/676580/EU//NoMaDData science and machine learning in materials science require ...
Some of the most successful approaches to structural design in materials chemistry have exploited st...