We describe a complete set of algorithms for ab initio molecular simulations based on numerically tabulated atom-centered orbitals (NAOs) to capture a wide range of molecular and materials properties from quantum-mechanical first principles. The full algorithmic framework described here is embodied in the Fritz Haber Institute "ab initio molecular simulations" (FHI-aims) computer program package. Its comprehensive description should be relevant to any other first-principles implementation based on NAOs. The focus here is on density-functional theory (DFT) in the local and semilocal (generalized gradient) approximations, but an extension to hybrid functionals, Hartree–Fock theory, and MP2/GW electron self-energies for total energies and excited states is possible within the same underlying algorithms. An all-electron/full-potential treatment that is both computationally efficient and accurate is achieved for periodic and cluster geometries on equal footing, including relaxation and ab initio molecular dynamics. We demonstrate the construction of transferable, hierarchical basis sets, allowing the calculation to range from qualitative tight-binding like accuracy to meV-level total energy convergence with the basis set. Since all basis functions are strictly localized, the otherwise computationally dominant grid-based operations scale as O(N) with system size N. Together with a scalar-relativistic treatment, the basis sets provide access to all elements from light to heavy. Both low-communication parallelization of all real-space grid based algorithms and a ScaLapack-based, customized handling of the linear algebra for all matrix operations are possible, guaranteeing efficient scaling (CPU time and memory) up to massively parallel computer systems with thousands of CPUs

Our paper determines the lowest-energy structure of a RuO 2 ͑110͒ surface in thermodynamic equilibrium with an oxygenrich environment. The limit of least oxygen-containing gas phase conditions considered ͑O-poor limit͒ is motivated by the Gibbs free energy of formation of the bulk oxide ⌬G f . Employing the value of ⌬G f ͑0,0͒ at 0 K, we stated the error as opposed to using the temperature and pressure dependent value ⌬G f ͑T , p͒ as 0.63 eV at 1000 K and 1 atm. This value was erroneously deduced from the CRC Handbook, 1 due to inconsistent entries in the ⌬G f ͑T , p°= 1 atm͒ table, mixing decadic and natural logarithms in the stated interpolation formulae for rutile structured oxides. Using the proper decadic logarithm in the interpolation formula for RuO 2 the correct variation up to 1000 K and 1 atm is 1.78 eV. 2 In addition, Eq. ͑19͒ in our paper contains an erroneous factor of 2 in the denominator, which leads to an estimate of the vibrational contribution to the surface free energy in Fig. 1 that is too small by a factor of 2. In the temperature range up to 600 K discussed in our paper, this contribution remains nevertheless below 10 meV/ Å 2 . Therefore neither error affects the conclusions drawn.We thank Ian Grey for making us aware of the inconsistent entries in the CRC Handbook.

The results of the sixth blind test of organic crystal structure prediction methods are presented and discussed, highlighting progress for salts, hydrates and bulky flexible molecules, as well as on-going challenges.

The booming field of molecular electronics has fostered a surge of computational research on electronic properties of organic molecular solids. In particular, with respect to a microscopic understanding of transport and loss mechanisms, theoretical studies assume an ever-increasing role. Owing to the tremendous diversity of organic molecular materials, a great number of computational methods have been put forward to suit every possible charge transport regime, material, and need for accuracy. With this review article we aim at providing a compendium of the available methods, their theoretical foundations, and their ranges of validity. We illustrate these through applications found in the literature. The focus is on methods available for organic molecular crystals, but mention is made wherever techniques are suitable for use in other related materials such as disordered or polymeric systems.

F or over 2 decades, Li ion batteries have enabled the rise of portable electronics and dominated the battery market. The principal reason for this is that of all electrically rechargeable batteries with an adequate cycle life, the Li ion battery can store the most electrical energy, both in terms of weight (specific energy Wh/kg) and in terms of volume (energy density Wh/L). There has been steady but slow evolution of the important parameters describing Li ion battery performance since its commercial introduction in 1991 by Sony, for example, calendar and cycle lifetimes, the two energy densities (Wh/kg and Wh/L), power density, cost, and safety. Unfortunately, growth rates of the two energy densities have only been occurring at ∼7−8%/year. Today, cell-level-specific energies of ∼200 Wh/kg and energy density of ∼500 Wh/L are typical and are acceptable for most portable electronics applications.The electrification of light vehicle road transportation is generally considered the next important frontier for electrochemical energy storage, and it is currently debated whether Li ion batteries will ever be good enough for mass-market full electrification. At present, hybrids (HEVs) represent only ∼3% of new car sales in the U.S. market and plug-in hybrids (PHEVs) plus full electric vehicles (EVs) represent only ∼0.7% of U.S. new car sales. The principal issue inhibiting the massmarket electrification is simply a battery problem, that is, developing a cost-effective, safe, and long-lived battery with sufficient energy storage (both in terms of weight and volume) to give enough range for daily driving so that charging can be accomplished overnight at home. At present, the Li ion is the only practical battery for EVs and PHEVs, although this currently presents a difficult weight/volume−range−cost tradeoff in the design of the EV. It is projected that retail costs for Li ion batteries may decrease significantly in the future, from ∼$400/kWh at present to ∼$100/kWh in the 2030 time frame (especially with buildup of Tesla style battery "Gigafactories"). This would make EVs cost-competitive with traditional gasoline-powered cars. However, this still does not solve the weight/volume-range issue because of the projected limited increases in specific energy and energy density of conventional Li ion. In addition, because Li ion batteries use flammable nonaqueous liquid electrolytes, there is a serious safety issue in their use, especially for the large-format battery packs in EVs (e.g., Tesla fires). While some believe that these Li ion issues can all be tamed, for example, Elon Musk, others believe that mass-market electrification will require a totally different battery chemistry with significantly higher energy densities, so-called beyond Li ion (Li−S, Li−air, Mg 2+ ion, etc.). Of course these latter currently have many technical challenges; 1−3 therefore, it is not at all clear if they will ever become practical batteries for use in EVs.It seems to us that a wave of optimism is also building in the battery community that mos...