A discussion of many of the recently implemented features of GAMESS (General Atomic and Molecular Electronic Structure System) and LibCChem (the C++ CPU/GPU library associated with GAMESS) is presented. These features include fragmentation methods such as the fragment molecular orbital, effective fragment potential and effective fragment molecular orbital methods, hybrid MPI/OpenMP approaches to Hartree–Fock, and resolution of the identity second order perturbation theory. Many new coupled cluster theory methods have been implemented in GAMESS, as have multiple levels of density functional/tight binding theory. The role of accelerators, especially graphical processing units, is discussed in the context of the new features of LibCChem, as it is the associated problem of power consumption as the power of computers increases dramatically. The process by which a complex program suite such as GAMESS is maintained and developed is considered. Future developments are briefly summarized.

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We present a detailed analysis of the factors influencing the formation of epoxide and ether groups in graphene nanoflakes using conventional density functional theory (DFT), the density-functional tight-binding (DFTB) method, π-Hückel theory, and graph theoretical invariants. The relative thermodynamic stability associated with the chemisorption of oxygen atoms at various positions on hexagonal graphene flakes (HGFs) of D(6h)-symmetry is determined by two factors - viz. the disruption of the π-conjugation of the HGF and the geometrical deformation of the HGF structure. The thermodynamically most stable structure is achieved when the former factor is minimized, and the latter factor is simultaneously maximized. Infrared (IR) spectra computed using DFT and DFTB reveal a close correlation between the relative thermodynamic stabilities of the oxidized HGF structures and their IR spectral activities. The most stable oxidized structures exhibit significant IR activity between 600 and 1800 cm(-1), whereas less stable oxidized structures exhibit little to no activity in this region. In contrast, Raman spectra are found to be less informative in this respect.

The general distributed data interface (GDDI) that was developed for the fragment molecular orbital (FMO) method is combined with the shared memory OpenMP parallel middleware to support a threading multilevel parallelism. First, GDDI partitions [logical] compute nodes into groups, which are statically or dynamically assigned to different fragments. A small number of processes are created on each compute node. Each process subsequently spawns multiple threads for the actual computation. The performance of the hybrid GDDI/OpenMP approach relative to the pure GDDI model was examined in terms of the FMO/RI-MP2 method; that is, the second-order Moller−Plesset (MP2) correlation energy was evaluated using the resolution-of-the-identity (RI) and the FMO approximations. The GDDI and OpenMP workload balances are handled by an arithmetic progression and a loop fusion, respectively. Other OpenMP properties, such as threadprivate or shared memory, are combined with the low memory demand of the RI two-electron integrals to enhance the performance. Benchmark calculations demonstrate that because the hybrid parallel model can make use of multiprocessor resources more efficiently than the regular distributed memory-based GDDI model, calculations for small to large water clusters containing 139−2165 molecules and an ionic liquid cluster exhibit node linear scaling and speedups of a factor of 10×.

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A comprehensive picture on the mechanism of the epoxy-phenol curing reactions is presented using the density functional theory B3LYP/ 6-31G(d,p) and simplified physical molecular models to examine all possible reaction pathways. Phenol can act as its own promoter by using an addition phenol molecule to stabilize the transition states, and thus lower the rate-limiting barriers by 27.0-48.9 kJ/mol. In the uncatalyzed reaction, an epoxy ring is opened by a phenol with an apparent barrier of about 129.6 kJ/mol. In catalyzed reaction, catalysts facilitate the epoxy ring opening prior to curing that lowers the apparent barriers by 48.9-50.6 kJ/mol. However, this can be competed in highly basic catalysts such as amine-based catalysts, where catalysts are trapped in forms of hydrogen-bonded complex with phenol. Our theoretical results predict the activation energy in the range of 79.0-80.7 kJ/mol in phosphine-based catalyzed reactions, which agrees well with the reported experimental range of 54-86 kJ/mol.

The fully analytic gradient of the second-order Møller–Plesset perturbation theory (MP2) with the resolution-of-the-identity (RI) approximation in the fragment molecular orbital (FMO) framework is derived and implemented using a hybrid multilevel parallel programming model, a combination of the general distributed data interface (GDDI) and the OpenMP API. The FMO/MP2 analytic gradient contains three parts, i.e., the internal fragment component, the electrostatic potential (ESP) component, and the response terms. The RI approximation is applied to the internal fragment MP2 gradient term, whose MP2 densities and monomer MP2 Lagrangians are shared with the ESP and the response terms. The FMO/RI-MP2 analytic gradient implementation is validated against the numerical gradient (with errors ∼10–6–10–5 Hartree/Bohr) and the energy conservation in molecular dynamics (MD) simulations using NVE ensembles. The RI approximation introduces an error of ∼10–5 Hartree/Bohr with a speedup of 4.0–8.0× compared with the currently available GDDI FMO/MP2 gradient. The node linear scaling of the fragmentation framework due to multilevel parallelism is well-preserved and is demonstrated in single-point gradient calculations of large water clusters (e.g., 1120 and 2165 molecules) using 300–800 KNL compute nodes with a parallel efficiency of more than 90%.

The four-index two-electron repulsion integral (4−2ERI) matrix is compressed using the resolution-of-the-identity (RI) approximation combined with the rank factorization approximation (RFA). The 4−2ERI is first approximated by the RI product. Then, the singular value decomposition (SVD) approximation is used to eliminate low-weighted singular vectors. The SVD RI approximation maintains the canonical form of the RI approximation and introduces a tunable compression factor. The characteristics of the SVD RI approximation along with the stochastic RI and natural auxiliary function approximation were numerically examined by applying these methods to the closed-shell second-order Møller−Plesset perturbation theory (MP2). The results show that, while the SVD RI approximation yields large errors for absolute properties (e.g., the correlation energy), it provides accurate relative properties (potential energy surface, binding energy) of the applied ab initio method (e.g., RHF, MP2).(5)