FFCASP: A Massively Parallel Crystal Structure Prediction Algorithm

Abstract

A new algorithm called Fast and Flexible CrystAl Structure Predictor (FFCASP) was developed to predict the structure of covalent and molecular crystals. FFCASP is massively parallel and able to handle more than 200 atoms in the unit cell (in other terms, it allows global optimization around 100 individual parameters). It uses a global optimizer specialized for Crystal Structure Prediction (CSP) which combines particle swarm and simulated annealing optimizers. Three different molecular crystals, including diverse intermolecular interactions, namely, cytosine, coumarin, and pyrazinamide, have been selected to evaluate the performance of FFCASP. While cytosine polymorphs have been searched by employing two different force fields (a DFT-SAPT based intermolecular potential and generalized amber force field (GAFF)) up to Z = 16, only GAFF has been used both in coumarin and pyrazinamide polymorph searches up to Z = 4. For these three molecular crystals, FFCASP generated more than 20 000 crystal structures, and the unique ones have been further treated by DFT-D3. A combination of data mining and a machine learning approach was introduced to determine the unique structures and their distribution into different clusters, which ultimately gives an opportunity to retrieve the common features and relations between the resulting structures. There are two known experimental crystal structures of cytosine, and both were successfully located with FFCASP. Two of the reported crystal structures of coumarin have been reproduced. Similarly, in pyrazinamide, three known experimental structures have been rediscovered. In addition to finding the experimentally known structures, FFCASP also located other low-energy structures for each considered molecular crystals. These successes of FFCASP offer the possibility to discover the polymorphic nature of other important molecular crystals (e.g., drugs) as well.

2D‐FFCASP—A New Approach for 2D Structure Prediction Applied to Self‐Assemblies of DNA Bases

“…It is basically a 2D version of the crystal structure predictor called FFCASP which was successfully utilized to predict the structures of both covalent and molecular crystals. [58,65,66] Different from 3D-FFCASP, [58] movement strategy of 2D-FFCASP allowed translations and rotations only on the 2D plane. In 2D-FFCASP, every molecule was treated as a group which can be parameterized by two translations (on the plane), one rotation (around the plane normal), and one flip (on the plane) parameters, leading to four degrees of freedom.…”

“…where y 0 and y refer to the ab initio and model energies at dimer geometry x i , respectively. FFCASP [58] performed global structure optimization by combining simulated annealing (SA) [68] and particle swarm optimization (PSO) [69] algorithms which were massively parallelized with message passing interface (MPI) via task-farming fashion. At the beginning of the structure search, PSO algorithm took big random steps to overcome large barriers and to supply a good starting point to SA.…”

Along the road to crystal structure prediction (CSP) of pharmaceutical-like molecules

“…Accounting for full flexibility can be viewed as a global optimization problem and further lessons can be learned from well-established inorganic CSP strategies, which deal with a great number of degrees of freedom, yet often considering a reduced number of atoms compared to molecular CSP. A number of strategies proposed to date have involved stochastic search algorithms to improve sampling, for example, simulated annealing, 71 particle swarm optimization, 72 and genetic 73 and evolutionary algorithms 74 as well as parallel tempering Monte Carlo scheme. 75…”

Crystal Structure Prediction and Dehydrogenation Mechanism of LiMg(BH4)3(NH3)2

“…We used FFCASP, , developed in our group, for the CSP calculations in combination with DFT calculations for full geometry optimization of the candidate structures. Very recently, we successfully applied this methodology to study the polymorphism of Cu-TCNQ .…”