There are now a wide variety of packages for electronic structure calculations, each of which differs in the algorithms implemented and the output format. Many computational chemistry algorithms are only available to users of a particular package despite being generally applicable to the results of calculations by any package. Here we present cclib, a platform for the development of package-independent computational chemistry algorithms. Files from several versions of multiple electronic structure packages are automatically detected, parsed, and the extracted information converted to a standard internal representation. A number of population analysis algorithms have been implemented as a proof of principle. In addition, cclib is currently used as an input filter for two GUI applications that analyze output files: PyMOlyze and GaussSum. © 2007 Wiley Periodicals, Inc. J Comput Chem, 2008

cclib: A library for package‐independent computational chemistry algorithms

Combined quantum-mechanics/molecular-mechanics (QM/MM) approaches have become the method of choice for modeling reactions in biomolecular systems. Quantum-mechanical (QM) methods are required for describing chemical reactions and other electronic processes, such as charge transfer or electronic excitation. However, QM methods are restricted to systems of up to a few hundred atoms. However, the size and conformational complexity of biopolymers calls for methods capable of treating up to several 100,000 atoms and allowing for simulations over time scales of tens of nanoseconds. This is achieved by highly efficient, force-field-based molecular mechanics (MM) methods. Thus to model large biomolecules the logical approach is to combine the two techniques and to use a QM method for the chemically active region (e.g., substrates and co-factors in an enzymatic reaction) and an MM treatment for the surroundings (e.g., protein and solvent). The resulting schemes are commonly referred to as combined or hybrid QM/MM methods. They enable the modeling of reactive biomolecular systems at a reasonable computational effort while providing the necessary accuracy.

QM/MM Methods for Biomolecular Systems

The ground-state energy, electron density, and related properties of ordinary matter can be computed efficiently when the exchange-correlation energy as a functional of the density is approximated semilocally. We propose the first meta-GGA (meta-generalized gradient approximation) that is fully constrained, obeying all 17 known exact constraints that a meta-GGA can. It is also exact or nearly exact for a set of appropriate norms, including rare-gas atoms and nonbonded interactions. This SCAN (strongly constrained and appropriately normed) meta-GGA achieves remarkable accuracy for systems where the exact exchange-correlation hole is localized near its electron, and especially for lattice constants and weak interactions.

Strongly Constrained and Appropriately Normed Semilocal Density Functional

New designs of donor polymers yield organic solar cells with fill factors approaching 80%, significantly higher than those of conventional cells. This enhanced performance is attributed to the close-packed and highly ordered structure of the polymers PTPD3T and PBT13T, which leads to efficient charge extraction and suppressed recombination.

Polymer solar cells with enhanced fill factors

Lung Wa Chung,† W. M. C. Sameera,‡ Romain Ramozzi,‡ Alister J. Page, Miho Hatanaka,‡ Galina P. Petrova, Travis V. Harris,‡,⊥ Xin Li, Zhuofeng Ke, Fengyi Liu, Hai-Bei Li, Lina Ding, and Keiji Morokuma*,‡ †Department of Chemistry, South University of Science and Technology of China, Shenzhen 518055, China ‡Fukui Institute for Fundamental Chemistry, Kyoto University, 34-4 Takano Nishihiraki-cho, Sakyo, Kyoto 606-8103, Japan Newcastle Institute for Energy and Resources, The University of Newcastle, Callaghan 2308, Australia Faculty of Chemistry and Pharmacy, University of Sofia, Bulgaria Boulevard James Bourchier 1, 1164 Sofia, Bulgaria Department of Chemistry, State University of New York at Oswego, Oswego, New York 13126, United States State Key Laboratory of Molecular Reaction Dynamics, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China School of Chemistry and Chemical Engineering, Sun Yat-sen University, Guangzhou 510275, China Key Laboratory of Macromolecular Science of Shaanxi Province, School of Chemistry and Chemical Engineering, Shaanxi Normal University, Xi’an, Shaanxi 710119, China School of Ocean, Shandong University, Weihai 264209, China School of Pharmaceutical Sciences, Zhengzhou University, 100 Kexue Avenue, Zhengzhou, Henan 450001, China

The ONIOM Method and Its Applications

Gaussian 03, Revision E.01.

Geometry optimization of large QM/MM systems is usually carried out by alternating a second-order optimization of the QM region using internal coordinates (‘macro-iterations’), and a first-order optimization of the MM region using Cartesian coordinates (‘micro-iterations’), until self-consistency. However, the neglect of explicit coupling between the two regions (the Hessian elements that couple the QM coordinates with the MM coordinates) often interferes with a smooth convergence, while the Hessian update procedure can be unstable due to the presence of multiple minima in the MM region. A new geometry optimization scheme for QM/MM methods is proposed that addresses these problems. This scheme explicitly includes the coupling between the two regions in the QM optimization step, which makes it quadratic in the full space of coordinates. Analytical second derivatives are used for the MM contributions, with O(N) memory and CPU requirements (where N is the total number of atoms) by employing direct and fast m...

H. B. Schlegel

Papers

Gaussian 03, Revision E.01.

Geometry optimization with QM/MM methods II: Explicit quadratic coupling