The digital revolution of Earth-system science.

Computational science is crucial for delivering reliable weather and climate predictions. However, despite decades of high-performance computing experience, there is serious concern about the sustainability of this application in the post-Moore/Dennard era. Here, we discuss the present limitations in the field and propose the design of a novel infrastructure that is scalable and more adaptable to future, yet unknown computing architectures.

Materials Cloud, a platform for open computational science.

Materials Cloud is a platform designed to enable open and seamless sharing of resources for computational science, driven by applications in materials modelling. It hosts (1) archival and dissemination services for raw and curated data, together with their provenance graph, (2) modelling services and virtual machines, (3) tools for data analytics, and pre-/post-processing, and (4) educational materials. Data is citable and archived persistently, providing a comprehensive embodiment of entire simulation pipelines (calculations performed, codes used, data generated) in the form of graphs that allow retracing and reproducing any computed result. When an AiiDA database is shared on Materials Cloud, peers can browse the interconnected record of simulations, download individual files or the full database, and start their research from the results of the original authors. The infrastructure is agnostic to the specific simulation codes used and can support diverse applications in computational science that transcend its initial materials domain.

All-electron GW quasiparticle band structures of group 14 nitride compounds.

We have investigated the group 14 nitrides (M3N4) in the spinel phase (γ-M3N4 with M = C, Si, Ge, and Sn) and ß phase (ß-M3N4 with M = Si, Ge, and Sn) using density functional theory with the local density approximation and the GW approximation. The Kohn-Sham energies of these systems have been first calculated within the framework of full-potential linearized augmented plane waves (LAPW) and then corrected using single-shot G0W0 calculations, which we have implemented in the modified version of the Elk full-potential LAPW code. Direct band gaps at the Γ point have been found for spinel-type nitrides γ-M3N4 with M = Si, Ge, and Sn. The corresponding GW-corrected band gaps agree with experiment. We have also found that the GW calculations with and without the plasmon-pole approximation give very similar results, even when the system contains semi-core d electrons. These spinel-type nitrides are novel materials for potential optoelectronic applications because of their direct and tunable band gaps.

Toward an atomistic model for predicting transcription-factor binding sites.

Identifying the specific DNA-binding sites of transcription-factor proteins is essential to understanding the regulation of gene expression in the cell. Bioinformatics approaches are fast compared to experiments, but require prior knowledge of multiple binding sites for each protein. Here, we present an atomistic force-field method to predict binding sites based only on the X-ray structure of a related bound complex. Specific flexible contacts between the protein and DNA are modeled by a library of amino acid side-chain rotamers. Using the example of the mouse transcription factor, Zif268, a well-studied zinc-finger protein, we show that the protein sequence alone, without the detailed experimental structure, gives a strong bias toward the consensus binding site.