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Nanomaterials Theory Institute

The CNMS Nanomaterials Theory Institute (NTI) provides and advances capabilities for theory and high performance simulation to enable fundamental understanding of physical and chemical properties of nanoscale materials.

Computing resources

  • NTI Computational Cluster
    The NTI has several ORNL cluster systems in support of the capacity-level computing needs of CNMS/NTI users. This includes an 896 core AMD/Interlagos cluster on the OIC ORNL system and a Cray CS400 1216 core Intel Haswell cluster on the Cades Condo system. The workflow on these systems is focused on timely turnover for development of new science. More information...(requires UCAMS or XCAMS account)
  • Access to High-End Capacity Computing Facilities
    The NTI has sizable allocation on the National Energy Research Supercomputing Center, NERSC, at Lawrence Berkeley National Laboratory. This resource is for users with computationally demanding applications or large production runs of calculations developed on the NTI Computation Cluster that require resources on order 1000 processors or more. The NTI provides users with support to make effective use of this resource and the cycles needed for completion of the project. NTI staff can make available electronic structure codes (such as VASP) that have been optimized to run at scale for users who have a valid license for these codes.
  • Access to Leadership Capability Computing Facilities
    NTI staff are competing for large allocations on the leadership-class Supercomputers of the National Center for Computational Sciences. These allocations are intended for high-profile computational nanoscience and materials research that relies on capability computing runs of order 10,000 processors. NTI researchers maintain codes that run effectively at the leadership scale and are available for these high-profile projects.
  • Theory/Computation/Simulation Support for Experimental Projects
    Experimental users of the CNMS are encouraged to contact the NTI staff to discuss possible theoretical support for their projects. These discussions may occur during development of the experimental user proposal in order to include the theoretical component in the proposal or may be initiated after an experimental project is under way.
  • Theory/Computation/Simulation Support for Theoretical Projects
    NTI users performing theoretical/computational research are encouraged to request related theoretical/computational support for their projects.
  • Computational Nanoscience End-station (CNE)
    In analogy to experimental end-stations at large experimental facilities, the Computational Nanoscience End-station (CNE) provides users with the leading edge scientific instrumentation (i.e., modeling software) and expertise to perform scientific research at scale on leadership computing facilities such as the Oak Ridge Leadership Computing Facility (OLCF). The CNE currently supports large-scale electronic structure codes that allow direct ab-initio simulations of nanoscale systems as well as specialized codes for strongly correlated materials and to support atomistic simulations of magnetic nanosystems. Additionally, support of classical atomistic and coarse-grained molecular dynamics methods as well as self-consistent field theoretic approaches are also available. CNE research and development is focused toward using theory and multiscale simulations and modeling for providing interpretive and predictive frameworks for virtual design and understanding of novel nanoscale materials with specific and/or emergent properties. The CNE has been an important driver of the Center for Nanophase Materials Sciences (CNMS) user program.

    CNE Capabilities include:

    • Quantum Chemistry methods for molecular systems
    • Large-scale electronic structure methods for solids and extended surfaces
    • Quantum Monte Carlo approaches
    • Quantum Cluster Approaches and Density Matrix Renormalization Group for strongly correlated materials
    • Classical molecular dynamics methods (atomistic to coarse grained)
    • Self-Consistent Field Theoretic (SCFT) approaches
    • Quantum Dynamics
    • Modeling and simulation of soft matter under high electric fields
    • Virtual Raman spectroscopy
    • Agent Based Modeling, machine learning and data analytics

List of recent publications here.