ACES III is a newly written program in which the computationally demanding components of the computational chemistry code ACES II [J. F. Stanton et al., Int. J. Quantum Chem. 526, 879 (1992); [ACES II program system, University of Florida, 1994] have been redesigned and implemented in parallel. The high-level algorithms include Hartree-Fock (HF) self-consistent field (SCF), second-order many-body perturbation theory [MBPT(2)] energy, gradient, and Hessian, and coupled cluster singles, doubles, and perturbative triples [CCSD(T)] energy and gradient. For SCF, MBPT(2), and CCSD(T), both restricted HF and unrestricted HF reference wave functions are available. For MBPT(2) gradients and Hessians, a restricted open-shell HF reference is also supported. The methods are programed in a special language designed for the parallelization project. The language is called super instruction assembly language (SIAL). The design uses an extreme form of object-oriented programing. All compute intensive operations, such as tensor contractions and diagonalizations, all communication operations, and all input-output operations are handled by a parallel program written in C and FORTRAN 77. This parallel program, called the super instruction processor (SIP), interprets and executes the SIAL program. By separating the algorithmic complexity (in SIAL) from the complexities of execution on computer hardware (in SIP), a software system is created that allows for very effective optimization and tuning on different hardware architectures with quite manageable effort.

The atoms-in-molecules (AIM) theory has been proposed as a method to understand chemical stability through stationary properties of the electron density. To assess the applicability of this method for establishing such correlations with various performance and vulnerability properties of energetic materials, we calculated the Kohn-Sham density functional theory (KS-DFT) wavefunctions and their subsequent AIM data for representative materials, including hexanitrobenzene (HNB), pentaerythritol tetranitrate (PETN), pentanitroaniline (PNA), 1,3,5,7-tetranitro-1,3,5,7-tetrazocine (HMX), ethylenedinitramine (EDNA), 1,1-diamino-2,2-dinitroethylene (FOX-7), 3-nitro-1,2,4-triazol-5-one (NTO), nitroguanidine (NQ), 1,3,5-triamino-2,4,6-trinitrobenzene (TATB), and the TATB dimer using the B3LYP, PBE, and PW91 potentials as well as Hartree-Fock (HF). For the HNB and HMX molecules and the TATB dimer, the number of critical points in the low-density regions of the density gradient vector field varied, sometimes dramatically, with basis set and potential even at their individually optimized geometries. Adding ghost atoms in the low-density regions also affected the existence of critical points. The variation was seen in results generated with three separate AIM software packages, AIMPAC, AIMAll, and InteGriTy. This inconsistency implies that KS-DFT wave-functions can have significant variation in the topology of the electron density to such an extent that these calculations cannot be used to justify the existence or absence of low-density critical points. Therefore, predictions of the stability of a molecule based solely on properties of low-density bond critical points generated from a single DFT calculation are questionable.

To elucidate the mechanisms of energy release in a reacting nickel/aluminum bilayer, we simulate the exothermic alloying reactions using both microcanonical and isoenthalpic-isobaric molecular dynamics simulations and an embedded-atom method type potential. The mechanism of the mixing consists of a sequence of steps in which mixing and reaction first occurs at the interface; the resulting heat generated from the mixing then melts the Al layer; subsequent mixing leads to further heat generation after which the Ni layer melts. The mixing continues until the alloying reactions are completed. The results indicate that pressure has a significant influence on the rates of atomic mixing and alloying reactions. Local pressures and temperatures within the individual layers at the time of melting are calculated, and these results are compared with the pressure-dependent melting curves determined for pure Al and pure Ni using this interaction potential.

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