More info http://th.fhi-berlin.mpg.de/meetings/SCMS2017/

This will be an NSF/CECAM school, bringing together students from the NSF research training program for data-enabled science and engineering (NRT-DESE): "Computational Materials Education and Training: Bridging ab initio methods and applications (CoMET)" with about 20 European students at a high quality event at CECAM headquarters.

This school will cover the full range from fundamental concepts in density-functional theory (DFT) to its application in materials science. There has been an explosion in the use of DFT methods, which is fueled by its assumed but often unfounded accuracy for describing the structural and electronic properties of many materials and the proliferation of user-friendly DFT software packages, which makes it relatively simple to perform these calculations. For many applied researchers, typical DFT training does not stress the theoretical approximations and numerical issues inherent to DFT. A significant gap exists between fundamental DFT researchers, who work on development of methodology, and applied DFT researchers trained in specific application areas.

In this school, we address this gap. We will boost DFT training by promoting awareness of the approximations, numerical issues, and current challenges in developing DFT methods for ground-state and excited-state systems. We will also highlight the challenges in applying DFT to real-world problems, such as bridging the temperature and pressure gaps, by introducing developments in ab initio statistical mechanics. These concepts will be illustrated in various cutting-edge applications. Experts in the developing field of DFT-based materials discovery will present the state-of-the art in academia and industry. We will bring together an international community of experts to illustrate the path from DFT methodology to materials discovery.

This school targets advanced PhD students. An international slate of invited speakers has been selected whose research spans the spectrum from the development of DFT methods to the direct use of DFT to solve problems in materials science to the integration of DFT methods into multi-scale modeling involving theory, empirical force-field development, and simulations. These various approaches will be illustrated for applications in different fields (especially those interesting for energy and environment). We will invite leading experts and practitioners to give two lectures: a 60-minute tutorial introducing specific aspects or fundamental concepts and a 20-minute “hot topics” talk in which they highlight recent work to illustrate new fundamental developments and/or how fundamental concepts are put into practice in cutting-edge applications.

The topics to be covered in 60-minute tutorial talks are:

Fundamentals of Ground State DFT
A set of talks will address the foundations of DFT including various functionals (e.g., local-density approximation, generalized gradient approximation, hybrid functionals), van der Waals DFT, as well as advanced implementations of DFT and techniques to treat strong correlations. These presentations will include lectures by

• Matthias Scheffler – overview of DFT methods and applications
• Andreas Goerling - Kohn-Sham methods
• Alexandre Tkatchenko – DFT and dispersion interactions
• Silke Biermann – dynamic mean-field theory and strongly correlated systems  
• Michael Seidl – strong-interaction limit of DFT
• Ismaila Dabo – DFT approximations

Refs:
1. Reuter, K. , Stampfl, C. & Scheffler, M. Ab initio atomistic thermodynamics and statistical mechanics of surface properties and functions. In: Handbook of Materials Modeling, Vol. 1. (Ed.) Sidney Yip. Springer Berlin Heidelberg 2005, 149. ISBN 1-4020-3287-0.
2. Ren, X., Tkatchenko, A., Rinke, P. & Scheffler, M. Beyond the random-phase approximation for the electron correlation energy: The importance of single excitations, Phys. Rev. Lett. 106, 153003 (2011).
3. Tao, J., Perdew, J. P., Staroverov, V. N. & Scuseria, G. E. Climbing the Density Functional Ladder: Nonempirical Meta-Generalized Gradient Approximation Designed for Molecules and Solids. Phys. Rev. Lett. 91, 146401 (2003).
4. Sun, J., Ruzsinszky, A. & Perdew, J. P. Strongly Constrained and Appropriately Normed Semilocal Density Functional, Phys. Rev. Lett., to appear; arxiv: 1504.03028 (2015).
5. Tkatchenko, A., DiStasio, R. A., Car, R. & Scheffler, M. Accurate and Efficient Method for Many-Body van der Waals Interactions. Phys. Rev. Lett. 108, 236402 (2012).
6. Tkatchenko, A. & Scheffler, M. Accurate Molecular Van Der Waals Interactions from Ground-State Electron Density and Free-Atom Reference Data. Phys. Rev. Lett. 102, 073005 (2009).
7. Klimeš, J. & Michaelides, A. Perspective: Advances and challenges in treating van der Waals dispersion forces in density functional theory. The Journal of Chemical Physics 137, 120901 (2012).
8. Wang, Y. A., Govind, N. & Carter, E. A. Orbital-free kinetic-energy density functionals with a density-dependent kernel. Phy. Rev. B 60, 16350 (1999).
9. Ayral, T., Werner, P. & Biermann, S. Spectral Properties of Correlated Materials: Local Vertex and Nonlocal Two-Particle Correlations from Combined GW and Dynamical Mean Field Theory. Phys. Rev. Lett. 109, 226401 (2012).
10. Attaccalite, C., Moroni, S., Gori-Giorgi, P. & Bachelet, G. B. Correlation energy and spin polarization in the 2D electron gas. Phys. Rev. Lett. 88, 256601 (2002).

DFT for Excited States
Devoted to methods that go beyond the ionic and electronic ground state. The presentations will include introductions to the treatment of excited states and their implementations. These presentations will include lectures by

• Francesco Sottile – screening and excited states
• Claudia Draxl – time-dependent DFT
• Stefano Baroni – density functional perturbation theory

Refs:
1.Ruzsinszky, A., Perdew, J. P., Csonka, G. I., Vydrov, O. A. & Scuseria, G. E. Spurious fractional charge on dissociated atoms: Pervasive and resilient self-interaction error of common density functionals. The Journal of chemical physics 125, 194112 (2006).
2. Rigamonti, S. et al. Estimating Excitonic Effects in the Absorption Spectra of Solids: Problems and Insight from a Guided Iteration Scheme. Phys. Rev. Lett. 114, 146402 (2015).
3. Gulans, A. et al. exciting: a full-potential all-electron package implementing density-functional theory and many-body perturbation theory. J. Phys.: Condens. Matter 26, 363202 (2014).
4. Baroni, S., de Gironcoli, S., Dal Corso, A. & Giannozzi, P. Phonons and related crystal properties from density-functional perturbation theory. Reviews of Modern Physics 73, 515 (2001).

DFT Predictions of Materials Properties
DFT can quantitatively predict the structures and properties of many materials, if it is applied properly. Thus, a set of presentations will highlight various materials systems to which DFT has been successfully applied, focusing on the proper DFT methods and comparisons to experiment. Speakers are

• Boris Yakobson – 2D materials
• Ingrid Mertig – topological insulators
• Michael Janik – electrochemistry
• Lasse Jensen – enhanced Raman spectroscopy
• Philippe Sautet – catalysis
• Elisa Molinari – excitons

Refs:
1. Scheidemantel, T. J., Ambrosch-Draxl, C., Thonhauser, T., Badding, J. V. & Sofo, J. O. Transport coefficients from first-principles calculations. Phys. Rev. B 68, 125210 (2003).
2. Falke, S. M. et al. Coherent ultrafast charge transfer in an organic photovoltaic blend. Science 344, 1001–1005 (2014).
3. Janik, M. J., Taylor, C. D. & Neurock, M. First-principles analysis of the initial electroreduction steps of oxygen over Pt (111). Journal of the Electrochemical Society 156, B126–B135 (2009).
4. Moore, J. E., Morton, S. M. & Jensen, L. Importance of Correctly Describing Charge-Transfer Excitations for Understanding the Chemical Effect in SERS. J. Phys. Chem. Lett. 3, 2470–2475 (2012).
5. Digne, M., Sautet, P., Raybaud, P., Euzen, P. & Toulhoat, H. Use of DFT to achieve a rational understanding of acid-basic properties of gamma-alumina surfaces. Journal of Catalysis 226, 54–68 (2004).
6. Ramesh, R. & Spaldin, N. A. Multiferroics: progress and prospects in thin films. Nature materials 6, 21–29 (2007).
7. S. Falke, Elisa Molinari, et al, "Coherent ultrafast charge transfer in an organic photovoltaic blend", Science 344, 1001 (2014).
8. Palmer, J. C., Car, R. et al. Metastable liquid-liquid transition in a molecular model of water. Nature 510, 385–388 (2014).

DFT for Materials Discovery
The quantitative accuracy of DFT has reached the point at which it can be used to discover or screen for new materials with beneficial properties. DFT is becoming increasingly adopted in industry. Efforts in high-throughput materials discovery, which incorporate ideas in machine learning, have led to interrogation of vast arrays of candidate materials for applications in catalysis, batteries, separations, photovoltaics, and thermoelectrics. A set of talks will highlight this emerging area and speakers are

• Stefano Curtarolo – high-throughput calculations
• Matthias Scheffler – NoMaD (Novel Materials Discovery)
• Efthimios Kaxiras – machine learning
• Vincent Crespi – choosing the best research problems

Refs:
1. Calderon, C. E. et al. The AFLOW Standard for High-Throughput Materials Science Calculations. arXiv:1506.00303 [cond-mat] (2015). at http://arxiv.org/abs/1506.00303.
2. The NoMaD Center of Excellence at http://nomad-coe.eu/ .
3. Simon, C. M. et al. The materials genome in action: identifying the performance limits for methane storage. Energy Environ. Sci. 8, 1190–1199 (2015).
4. Qu, X. , Persson, K. et al. The Electrolyte Genome project: A big data approach in battery materials discovery. Computational Materials Science 103, 56–67 (2015).

Extrapolating DFT: ab initio Statistical Mechanics and Force Fields
DFT is almost always applied to describe systems at zero temperature and pressure, yet systems of interest are not at these conditions. In this set of presentations, we will address theoretical techniques and applications to extend the capabilities of DFT to nonzero temperatures and pressures. Speakers are

• Kristen Fichthorn – Overview of DFT in multi-scale materials simulation              
• Susan Sinnott – reactive force fields
• Gabor Csanyi – the GAP potential
• C. Richard A. Catlow – embedding techniques
• Stefano Piana – large-scale molecular dynamics
• Karsten Reuter – multi-scale modelling of catalysis
• Luca Ghiringhelli – configurational sampling   
• James Pfaendtner – configurational sampling of biomolecules 
• Kristen Fichthorn - (superbasin) kinetic Monte Carlo
• Michele Ceriotti – advanced molecular dynamics

Refs:
1. Quhe, R., Nava, M., Tiwary, P. & Parrinello, M. Path Integral Metadynamics. J. Chem. Theory Comput. 11, 1383–1388 (2015).
2. Del Ben, M. et al. Enabling simulation at the fifth rung of DFT: Large scale RPA calculations with excellent time to solution. Computer Physics Communications 187, 120–129 (2015).
3. Van Duin, A. C. T., Dasgupta, S., Lorant, F. & Goddard, W. A. ReaxFF: A Reactive Force Field for Hydrocarbons. J. Phys. Chem. A 105, 9396–9409 (2001).
4. Walsh, A. et al. Limits to Doping of Wide Band Gap Semiconductors. Chem. Mater. 25, 2924–2926 (2013).
5. Aseev, O., Perez, M. A. S., Rothlisberger, U. & Rizzo, T. R. Cryogenic Spectroscopy and Quantum Molecular Dynamics Determine the Structure of Cyclic Intermediates Involved in Peptide Sequence Scrambling. J. Phys. Chem. Lett. 2524–2529 (2015). doi:10.1021/acs.jpclett.5b01088

Hot Topics
In addition to the tutorial topics above, speakers will present a 20-minute “hot topic” talk on a recent theoretical development or application of DFT. In this way, students will receive a survey of the state of the art

Poster Session
The students will get a chance to present their work with a poster contribution. We plan on having a "poster parade" where the students will introduce their poster with a short 2-minute presentation. Poster parade and sessions are set to the beginning of the school so that students and lecturers get acquainted early on. This is a unique possibility for the students to present their work to their peers and renowned scientists of the field alike, enabling them to receive valuable feedback and to start to build a network in the scientific community.