DOE Computational Chemical Sciences - Preapplication

Sponsor Deadline: 

Dec 2, 2020

Internal Deadline: 

Nov 19, 2020

Letter of Intent Deadline: 

Dec 2, 2020


Energy DOE Office of Science

UI Contact: 

DOE Computational Chemical Sciences

LIMITED to ONE application per institution; important information for potential UI applicants:
Internal Deadline is November 19, 2020. 
Required Preapplication is due December 2, 2020

The DOE SC program in Basic Energy Sciences (BES) hereby announces its interest in receiving new and renewal applications from small groups (2-3 principal investigators) and integrated multidisciplinary teams (typically from multiple institutions) in Computational Chemical Sciences (CCS). Single-investigator applications are not responsive to the objectives of this FOA. CCS will support basic research to develop validated, open-source codes for modeling and simulation of complex chemical processes and phenomena that allow full use of emerging exascale and future planned DOE leadership-class computing capabilities. The focus for CCS is on developing capabilities that allow modeling and simulation of new or previously inaccessible complex chemical systems and/or provide dramatic improvement in fidelity, scalability, and throughput. Teams should bring together expertise in domain areas (e.g., electronic structure, chemical dynamics, statistical mechanics, etc.) and other areas important to advance computational tools such as data science, algorithm development, and software architectures. Priority will be given to efforts that address reaction chemistry across multiple scales in complex environments important in geosciences, catalysis, biochemistry, or electrochemistry. 
CCS will continue to support the DOE Exascale Computing Initiative (ECI). The ECI aims to accelerate the research and development needed to overcome key exascale challenges and maximize benefits of high-performance computing. This funding opportunity continues the BES commitment to ECI by developing open-source codes that can take full advantage of emerging exascale and future planned DOE leadership-class computing facilities.