Please contact the symposium organizers with questions.

The symposium will focus on recent advances in algorithm development of novel atomistic simulation methodologies, both at the level of electronic structure calculations and of empirical-potential-based simulations, and on their applications. The symposium will be centered on methods that aim at addressing size and time-scale limitations of conventional techniques, two problems that often severely limit the scope of atomistic simulations in materials science.
As a first-principle method, density functional theory (DFT) has become an invaluable tool for materials modeling. However, with conventional implementation of Kohn-Sham DFT, one is usually limited to systems containing at most several hundred atoms. On the other hand, to model materials, it would often be desirable to study systems containing tens of thousands of atoms, or more. In recent years, tremendous progress towards relaxing the time and lengthscale limitations has been made in the DFT community. This symposium will address these new exciting advances in DFT by bringing experts from diverse fields such as orbital-free DFT, time-reversible ab-initio molecular dynamics, quasi-continuum DFT, hybrid quantum/classical modeling and machine learning approaches.
At the other end of the spectrum, Molecular Dynamics (MD) algorithms based on empirical or semi-empirical potentials allow for greatly extended simulation sizes and times. Indeed, MD can be efficiently parallelized through domain decomposition, so that remarkably large systems can be efficiently simulated. However, these traditional algorithms are not suitable to study long time phenomena, such as defect diffusion, as they become communication bound. In systems where the dynamics are activated, i.e., where the dynamics consist of long periods of uneventful vibrational motion, punctuated by rare topological transitions, advanced simulation techniques, such as accelerated molecular dynamics and kinetic Monte Carlo methods, can be leveraged to extend the simulation times up to experimentally relevant scales. These methods often provide invaluable insight into the microstructural evolution of materials. The symposium will focus on recent advances in the development of these accelerated techniques, such as adaptive KMC methods, and on the new physics that can be learned as the timescale horizon is pushed further.
Atomistic to continuum approaches can also be used to efficiently sample phase space. Recent developments and their interaction with existing models are also of interest. Quasi-continuum approaches and their recent coupling with accelerated MD models, and the phase field crystal method are promising methodologies under development with the potential of extending the time and size scales of the atomistic systems under consideration.

Topics will include:

• Addressing size and time limitations in DFT-based methods: - Orbital-free DFT - Time-reversible Ab-Initio Molecular Dynamics - Quasi-continuum DFT and hybrid quantum/classical modeling - Adaptive kinetic Monte Carlo - Machine learning based approaches
• Long-time atomistic simulation methods: - Accelerated Molecular Dynamics - Adaptive kinetic Monte Carlo - Acceleration techniques for Kinetic Monte Carlo
• Atomistic-Continuum Approaches: - Linking scales (Quasi-Continuum and related developments) - Accelerated methods coupled to quasi-continuum approaches - Phase Field Crystal methods

• A tutorial complementing this symposium is tentatively planned.

Invited Speakers:

• Nan Wang (McGill University, Canada)
• William Witt (Princeton University, USA)
• Hannes Jonsson (University of Iceland, Iceland)
• Kristen Fichthorn (The Pennsylvania State University, USA)
• Ju Li (Massachusetts Institute of Technology, USA)
• Danny Perez (Los Alamos National Laboratory, USA)
• Emily Carter (Princeton University, USA)
• William Curtin (École Polytechnique Fédérale de Lausanne, Switzerland)
• Tapio Ala-Nissila (Aalto University, Finland)
• Manuel Athenes (Commissariat a l'energie atomique, France)
• Vasily Bulatov (Lawrence Livermore National Laboratory, USA)
• Marc Cawkwell (Los Alamos National Laboratory, USA)
• Abhijit Chatterjee (IIT Bombay, India)
• Youping Chen (University of Florida, USA)
• Vikram Gavini (University of Michigan, USA)
• Graeme Henkleman (University of Texas, USA)
• Jacques Amar (University of Toledo, USA)
• Steven Kenny (University of Louborough, United Kingdom)
• Tony Lelievre (Ecole des Ponts ParisTech, France)
• Gang Lu (California State university, USA)
• Mitchell Luskin (University of Minnesota, USA)
• Normand Mousseau (University of Montreal, Canada)
• Marco Nardelli (University of North Texas, USA)
• Anders Niklasson (Los Alamos National Laboratory, USA)
• Talat Rahman (University of Central Florida, USA)
• Christopher Schuh (Massachussets Institute of Technology, USA)
• Ellad Tadmor (University of Minnesota, USA)
• Lin-Wang Wang (Berkeley Lab, USA)

Symposium Organizers