CamCASP 5.9 Alston J. Misquittay and Anthony J. Stoneyy yDepartment of Physics and Astronomy, Queen Mary, University of London, 327 Mile End Road, London E1 4NS yy University Chemical Laboratory, Lensfield Road, Cambridge CB2 1EW September 1, 2015 Abstract CamCASP is a suite of programs designed to calculate molecular properties (multipoles and frequency- dependent polarizabilities) in single-site and distributed form, and interaction energies between pairs of molecules, and thence to construct atom–atom potentials. The CamCASP distribution also includes the programs Pfit, Casimir,Gdma 2.2, Cluster, and Process. Copyright c 2007–2014 Alston J. Misquitta and Anthony J. Stone Contents 1 Introduction 1 1.1 Authors . .1 1.2 Citations . .1 2 What’s new? 2 3 Outline of the capabilities of CamCASP and other programs 5 3.1 CamCASP limits . .7 4 Installation 7 4.1 Building CamCASP from source . .9 5 Using CamCASP 10 5.1 Workflows . 10 5.2 High-level scripts . 10 5.3 The runcamcasp.py script . 11 5.4 Low-level scripts . 13 6 Data conventions 13 7 CLUSTER: Detailed specification 14 7.1 Prologue . 15 7.2 Molecule definitions . 15 7.3 Geometry manipulations and other transformations . 16 7.4 Job specification . 18 7.5 Energy . 23 7.6 Crystal . 25 7.7 ORIENT ............................................... 26 7.8 Finally, . 29 8 Examples 29 8.1 A SAPT(DFT) calculation . 29 8.2 An example properties calculation . 30 8.3 Dispersion coefficients . 34 8.4 Using CLUSTER to obtain the dimer geometry . 36 9 CamCASP program specification 39 9.1 Global data . 39 9.2 Molecule definition . 40 9.3 The EDIT module: Modifying a molecular specification . 42 9.4 Density-fitting . 43 9.5 Propagator settings . 45 9.6 Quadrature settings . 49 9.7 The ISA module . 49 9.8 Multipole moments . 52 9.9 Display . 54 9.10 Polarizabilities . 55 9.11 Lattice . 58 9.12 Numerical integration grid . 59 9.13 Electrostatic interaction . 60 9.14 First-order exchange (exchange-repulsion) . 61 9.15 Second-order induction energy . 61 9.16 Second-order dispersion energy . 64 9.17 Energy scan . 64 9.18 Overlap model . 67 9.19 Integrals . 71 10 PROCESS: Syntax 73 11 CASIMIR 77 A Basis sets 79 B Dispersion coefficients: in detail 80 C Older Scripts 87 C.1 High-level scripts . 87 C.2 Low-level scripts . 87 3 1 Introduction CamCASP is a suite of programs for the calculation of interaction energies between pairs of molecules, and molec- ular properties (multipoles and frequency-dependent polarizabilities) in single-site and distributed form. The Cam- CASP distribution also includes the programs Pfit,Casimir,Gdma 2.2, Cluster, and Process, and together these form a package for the ab initio generation of site–site force fields between organic molecules containing up to about 60 atoms. 1.1 Authors The CamCASP suite of programs, which includes Pfit,Casimir,Gdma 2.2, Process, and Cluster, has been writ- ten by Alston J. Misquitta and Anthony J. Stone with important contributions from Robert Bukowski, Wojciech Cencek, the GAMESS(US) team and the GAUSSINT team. 1.2 Citations This code is provided as a service to the scientific community and our only recompense, such as it is, is in citations. Therefore, if you use any results from CamCASP in your publications we request that you cite the following papers. The choice of citations would depend on the parts of the code you have used for the published results. • SAPT(DFT) energies ◦ A. J. Misquitta and K. Szalewicz. Intermolecular forces from asymptotically corrected density func- tional description of monomers. Chem. Phys. Lett., 357:301–306, 2002 ◦ A. J. Misquitta, B. Jeziorski, and K. Szalewicz. Dispersion energy from density-functional theory description of monomers. Phys. Rev. Lett., 91:33201, 2003 ◦ A. J. Misquitta and K. Szalewicz. Symmetry-adapted perturbation-theory calculations of intermolecu- lar forces employing density-functional description of monomers. J. Chem. Phys., 122:214109, 2005 ◦ A. J. Misquitta, R. Podeszwa, B. Jeziorski, and K. Szalewicz. Intermolecular potentials based on symmetry-adapted perturbation theory with dispersion energies from time-dependent density-functional theory. J. Chem. Phys., 123:214103, 2005 ◦ R. Bukowski, R. Podeszwa, and K. Szalewicz. Efficient generation of the coupled Kohn–Sham dynamic susceptibility functions and dispersion energy with density fitting. Chem. Phys. Lett., 414:111–116, 2005 • WSM polarizabilities ◦ A. J. Misquitta and A. J. Stone. Distributed polarizabilities obtained using a constrained density-fitting algorithm. J. Chem. Phys., 124:024111, 2006 ◦ A. J. Misquitta and A. J. Stone. Accurate induction energies for small organic molecules: I. Theory. J. Chem. Theory Comput., 4:7–18, 2008a ◦ A. J. Misquitta, A. J. Stone, and S. L. Price. Accurate induction energies for small organic molecules. 2. Development and testing of distributed polarizability models against SAPT(DFT) energies. J. Chem. Theory Comput., 4:19–32, 2008a. doi: 10.1021/ct700105f • WSM Dispersion models ◦ A. J. Misquitta and A. J. Stone. Dispersion energies for small organic molecules: first row atoms. Molec. Phys., 106:1631 – 1643, 2008b • SRLO polarizabilities ◦ A. J. Misquitta and A. J. Stone. Distributed polarizabilities obtained using a constrained density-fitting algorithm. J. Chem. Phys., 124:024111, 2006 ◦ Fazle Rob and Krzysztof Szalewicz. Asymptotic dispersion energies from distributed polarizabilities. Chem. Phys. Lett., 572:146–149, 2013 1 • GDMA multipole moments ◦ A. J. Stone. Distributed multipole analysis: Stability for large basis sets. J. Chem. Theory Comput., 1: 1128–1132, 2005 • Potentials & Overlap models ◦ A. J. Stone and A. J. Misquitta. Atom–atom potentials from ab initio calculations. Int. Rev. Phys. Chem., 26:193–222, 2007 ◦ A. J. Misquitta, G. W. A. Welch, A. J. Stone, and S. L. Price. A first principles prediction of the crystal structure of C6Br2ClFH2. Chem. Phys. Lett., 456:105–109, 2008b • Charge-tranfer via regularisation ◦ A. J. Misquitta. Charge-transfer from regularized symmetry-adapted perturbation theory. J. Chem. Theory Comput., 9:5313–5326, 2013. doi: 10.1021/ct400704a • Iterated stockholder atom (ISA) ◦ Alston J. Misquitta, Anthony J. Stone, and Farhang Fazeli. Distributed multipoles from a robust basis- space implementation of the iterated stockholder atoms procedure. J. Chem. Theory Comput., 2014. doi: 10.1021/ct5008444 Furthermore, if you make any changes or additions to the code and would like to share them for inclusion in future releases, please submit the modifications to us with suitable documentation and examples. 2 What’s new? All changes are reported with respect to the previous version. The base version is 5.2.00. Version 5.9.xx • Kernel integral evaluation about 2–3 times faster. • ISA restarts possible. Can build an ISA solution from an ISA library. Version 5.8.23 There are only a few major changes in this version compared with the earlier release (5.7.00). These are • The iterated stockholder atom (ISA) module, described in sec. 9.7, provides an implementation of the density-partitioning technique proposed by Lillestolen and Wheatley [Lillestolen and Wheatley, 2009]. The algorithm we have implemented in CamCASP is described in [Misquitta et al., 2014] and probably is one of the most stable and accurate implementations of this partitioning method currently available. • The concept of atomic neighbourhoods is now used to make the calculation of certain types of integrals scale linearly with system size. This concept is normally inactive, but can be activated using the EDIT module described in sec. 9.3. At present, the only module that can benefit from this feature is the ISA module. • The DISPLAY module allows the calculation of molecular and atomic iso-density surfaces. These can be visualised using the Orient program using suitable input files. This provides a powerful way of visualising the ISA atomic densities. • The ALDA kernel used in the response calculations has been made significantly more numerically stable. Stringent tests now show that residual numerical noise arising from the numerical integration is of the order 0:01 kJ mol−1. • As always, a number of bugs have been fixed as part of this release, and, no doubt, new ones introduced. 2 Version 5.7.00 The numerical stability and accuracy of the code has been improved, and it is now considerably faster, particularly when calculating distributed polarizabilities. The ALDA+CHF kernel option is coded within CamCASP and no longer requires the hessian from Dalton. This is now the default, though the ALDAX+CHF option is still available. Most of the scripts for job submission and related tasks have been rewritten in Python. The runcamcasp.py script can now be used to submit most forms of CamCASP calculation. All CamCASP calculations can now be carried out in conjunction with the NWChem,Dalton or Gamess(US) programs. The ‘self-repulsion plus local orthogonality’ (SRLO) density-fitting/distribution method of Rob & Szalewicz [Rob and Szalewicz, 2013] is available. See the DENSITY-FITTING module description for more details. CamCASP now uses significantly less disk space for temporary files. As a consequence, multiple CamCASP jobs can be run on the same file system without incurring a significant performance penalty. There are various bug corrections and other minor enhancements. Detailed changes: • The linear-response Kohn–Sham kernel is now calculated internally using the ALDA(+CHF) approximation with the LDA defined to contain the Slater exchange and PW91 correlation functionals. This kernel is now the default. As all integrals are evaluated internally, CamCASP no longer requires hessians from the DFT code, though this option is still available. Note that the Dalton program defines the LDA with the VWN correlation functional. • We have made significant improvements to the numerical accuracy and stability of the response calculations. In earlier versions of CamCASP the ALDAX(+CHF) kernel could result in low levels of numerical noise in the induction and dispersion energies.