Enhancement of DFT-calculations at petascale: Nuclear Magnetic Resonance, Hybrid Density Functional Theory and Car–Parrinello calculations

Abstract

One of the most promising techniques used for studying the electronic properties of materials is based on Density Functional Theory (DFT) approach and its extensions. DFT has been widely applied in traditional solid state physics problems where periodicity and symmetry play a crucial role in reducing the computational workload. With growing compute power capability and the development of improved DFT methods, the range of potential applications is now including other scientific areas such as Chemistry and Biology. However, cross disciplinary combinations of traditional Solid-State Physics, Chemistry and Biology drastically improve the system complexity while reducing the degree of periodicity and symmetry. Large simulation cells containing of hundreds or even thousands of atoms are needed to model these kind of physical systems. The treatment of those systems still remains a computational challenge even with modern supercomputers. In this paper we describe our work to improve the scalability of Quantum ESPRESSO [1] for treating very large cells and huge numbers of electrons. To this end we have introduced an extra level of parallelism, over electronic bands, in three kernels for solving computationally expensive problems: the Sternheimer equation solver (Nuclear Magnetic Resonance, package QE-GIPAW), the Fock operator builder (electronic ground-state, package PWscf) and most of the Car-Parrinello routines (Car-Parrinello dynamics, package CP). Final benchmarks show our success in computing the Nuclear Magnetic Response (NMR) chemical shift of a large biological assembly, the electronic structure of defected amorphous silica with hybrid exchange-correlation functionals and the equilibrium atomic structure of height Porphyrins anchored to a Carbon Nanotube, on many thousands of CPU cores.

Chemical shifts in molecular solids by machine learning

“…All the atomic positions of the structures in the training and testing sets were relaxed with DFT, using the Quantum Espresso suite 64 – 66 , prior to calculation of the chemical shieldings using the GIPAW DFT method 4 , 5 . Note that the DFT relaxation ensures “reasonable” geometries will be used even for crystal structures containing errors (e.g., improbable 1 H positions).…”

A Carbocationic Triarylmethane‐Based Porous Covalent Organic Network

“…The tensor for magnetic shielding was calculated based on gauge including projector augmented wave (GIPAW) approach as implemented in the gipaw code [52] for the Quantum Espresso package. Isotropic 13 C shielding, σ iso , for each carbon atom is calculated as the average value of the diagonal of the calculated shielding tensor in the Principal Axis System (PAS) [Eq.…”

Quasi‐Harmonic Lattice Dynamics of a Prototypical Metal–Organic Framework

“…In the last two decades, quantum‐mechanical simulations based on density functional theory (DFT) have arguably become the method of choice in the computational screening for advanced material design and crystal structure prediction of inorganic systems . This is primarily due to a favorable balance between the accuracy and computational cost, and to the availability of several robust implementations in solid‐state programs . Owing to the efficient exploitation of high‐performance computing (HPC) and to the development of a number of approaches to incorporate weak dispersive interactions in the exchange‐correlation functional, the last decade has also seen the successful application of DFT for computational screening of organic molecular crystals and metal–organic framework (MOF) materials …”