Today’s lithium-ion batteries, although suitable for small-scale devices, do not yet have sufficient energy or life for use in vehicles that would match the performance of internal combustion vehicles. Further improvements in energy density would greatly facilitate the introduction of these technologies. In this talk, we describe our recent work in applying computational methods to predict new, improved battery materials and reactions. The computational methods involve density functional theory (DFT) calculations as well as grand canonical linear programming (GCLP), a powerful automated tool for analyzing ground state thermodynamics. We illustrate several successful examples: Cathode Coatings for Li-ion cells: We introduce a first-principles thermodynamic framework for designing cathode coatings that consists of four elements: (i) HF-scavenging enthalpies, (ii) volumetric and (iii) gravimetric HF-scavenging capacities of the oxides, and (iv) cyclable Li-loss into coating components. We enumerate 81 HF-scavenging reactions involving binary s-, p- and d-block metal oxides and fluorides, and screen these materials to find promising coatings Using our design strategy, we predict promising coating materials such as trivalent oxides of d-block transition metals Sc, Ti, V, Cr, Mn and Y. Anodes for Li-ion cells: We exhaustively enumerate the 515 thermodynamically stable lithiation reactions of transition metal silicides, stannides and phosphides, and compute cell potential, volume expansion, and capacity for each. Screening these results for the most appealing anode properties based on gravimetric capacity, volumetric capacity, cell potential, and volume expansion results in several promising anode compositions with properties significantly superior to graphitic carbon, including CoSi2 , TiP and NiSi2. Materials for hybrid Li ion/Li–O2 cells: Recent experiments showed that Li5FeO4 can be electrochemically activated to have exceptionally high capacity as a dual-functioning electrode/electrocatalyst in Li-O2 batteries. Taking this novel chemistry as a model, we use density functional theory (DFT) within a high-throughput framework to screen for other such dual-functioning materials, and predict many new compounds that should have good electrochemical performance.