Molecular crystal structure prediction (CSP) requires evaluating differences in lattice energy between candidate crystal structures accurately and efficiently. In this work, we explore and compare several low-cost alternatives to dispersion-corrected density-functional theory (DFT) in the plane-waves/pseudopotential approximation, the most accurate and general approach used for CSP at present. Three types of low-cost methods are considered: DFT with a small basis set of finite-support numerical orbitals (the SIESTA method), dispersion-corrected Gaussian small or minimal-basis-set Hartree–Fock and DFT with additional empirical corrections (HF-3c and PBEh-3c), and self-consistent-charge dispersion-corrected density-functional tight binding (S...
A comparative analysis of the intermolecular energy for a data set including 60 molecular crystals w...
Understanding the structure and stability, as well as response properties of molecular crystals at c...
Previously, it was shown that crystal structure prediction based on genetic algorithms (MGAC program...
Using four different benchmark sets of molecular crystals, we establish the level of confidence for ...
Crystal structure prediction (CSP) has been a problem of great industrial interest but also a fundam...
noIn the 2007 blind test of crystal structure prediction hosted by the Cambridge Crystallographic Da...
Accurate prediction of structure and stability of molecular crystals is crucial in materials science...
The combination of modern machine learning (ML) approaches with high-quality data from quantum mecha...
Since the inception of computational chemistry, its practitioners have imagined the ability to predi...
The ambitious goal of organic crystal structure prediction challenges theoretical methods regarding ...
Accurate prediction of structure and stability of molecular crystals is crucial in materials science...
The efficient and reasonably accurate description of noncovalent interactions is important for vario...
A comparative assessment of the accuracy of different quantum mechanical methods for evaluating the ...
ABSTRACT: Lattice energy searches for theoretical low-energy crystal forms are presented for 50 smal...
The combination of modern machine learning (ML) approaches with high-quality data from quantum mecha...
A comparative analysis of the intermolecular energy for a data set including 60 molecular crystals w...
Understanding the structure and stability, as well as response properties of molecular crystals at c...
Previously, it was shown that crystal structure prediction based on genetic algorithms (MGAC program...
Using four different benchmark sets of molecular crystals, we establish the level of confidence for ...
Crystal structure prediction (CSP) has been a problem of great industrial interest but also a fundam...
noIn the 2007 blind test of crystal structure prediction hosted by the Cambridge Crystallographic Da...
Accurate prediction of structure and stability of molecular crystals is crucial in materials science...
The combination of modern machine learning (ML) approaches with high-quality data from quantum mecha...
Since the inception of computational chemistry, its practitioners have imagined the ability to predi...
The ambitious goal of organic crystal structure prediction challenges theoretical methods regarding ...
Accurate prediction of structure and stability of molecular crystals is crucial in materials science...
The efficient and reasonably accurate description of noncovalent interactions is important for vario...
A comparative assessment of the accuracy of different quantum mechanical methods for evaluating the ...
ABSTRACT: Lattice energy searches for theoretical low-energy crystal forms are presented for 50 smal...
The combination of modern machine learning (ML) approaches with high-quality data from quantum mecha...
A comparative analysis of the intermolecular energy for a data set including 60 molecular crystals w...
Understanding the structure and stability, as well as response properties of molecular crystals at c...
Previously, it was shown that crystal structure prediction based on genetic algorithms (MGAC program...