LEADER 01009nam0-22003251i-450- 001 990004654350403321 005 20090528141307.0 010 $a88-7062-833-7 035 $a000465435 035 $aFED01000465435 035 $a(Aleph)000465435FED01 035 $a000465435 100 $a19990604g19939999km-y0itay50------ba 101 0 $aita 105 $aa-------00--- 200 1 $aCatacomba di Commodilla$elucerne e altri materiali dalle gallerie 1, 8, 13$fRita Marconi Cosentino e Laura Ricciardi 210 $aRoma$cL'"Erma" di Bretschneider$d1993. 215 $a157 p.$c111 ill.$d25 cm 225 1 $aStudia archaeologica$v66 610 0 $aCatacomba du Comodilla$aStudi archeologici 676 $a738.38 700 1$aMarconi Cosentino,$bRita$0185235 702 1$aRicciardi,$bLaura 801 0$aIT$bUNINA$gRICA$2UNIMARC 901 $aBK 912 $a990004654350403321 952 $a738.38 MAR 1$bBibl.15608$fFLFBC 959 $aFLFBC 996 $aCatacomba di Commodilla$9553442 997 $aUNINA LEADER 05544nam 2200685 a 450 001 9910458817003321 005 20200520144314.0 010 $a1-281-01974-7 010 $a9786611019747 010 $a0-08-051998-9 035 $a(CKB)1000000000384188 035 $a(EBL)307221 035 $a(OCoLC)173686073 035 $a(SSID)ssj0000264542 035 $a(PQKBManifestationID)11246789 035 $a(PQKBTitleCode)TC0000264542 035 $a(PQKBWorkID)10303092 035 $a(PQKB)10470348 035 $a(Au-PeEL)EBL307221 035 $a(CaPaEBR)ebr10186686 035 $a(CaONFJC)MIL101974 035 $a(MiAaPQ)EBC307221 035 $a(PPN)179009974 035 $a(EXLCZ)991000000000384188 100 $a20010523d2002 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aUnderstanding molecular simulation $efrom algorithms to applications /$fDaan Frenkel, Berend Smit 205 $a2nd ed. 210 $aSan Diego $cAcademic Press$dc2002 215 $a1 online resource (661 p.) 225 1 $aComputational science series ;$v1 300 $aDescription based upon print version of record. 311 $a0-12-267351-4 320 $aIncludes bibliographical references (p. [589]-617) and index. 327 $aFront Cover; Understanding Molecular Simulation: From Algorithms to Applications; Copyright Page; Contents; Preface to the Second Edition; Preface; List of Symbols; Chapter 1. Introduction; Part I: Basics; Chapter 2. Statistical Mechanics; 2.1 Entropy and Temperature; 2.2 Classical Statistical Mechanics; 2.3 Questions and Exercises; Chapter 3. Monte Carlo Simulations; 3.1 The Monte Carlo Method; 3.2 A Basic Monte Carlo Algorithm; 3.3 Trial Moves; 3.4 Applications; 3.5 Questions and Exercises; Chapter 4. Molecular Dynamics Simulations; 4.1 Molecular Dynamics: The Idea 327 $a4.2 Molecular Dynamics: A Program4.3 Equations of Motion; 4.4 Computer Experiments; 4.5 Some Applications; 4.6 Questions and Exercises; Part II: Ensembles; Chapter 5. Monte Carlo Simulations in Various Ensembles; 5.1 General Approach; 5.2 Canonical Ensemble; 5.3 Microcanonical Monte Carlo; 5.4 Isobaric-Isothermal Ensemble; 5.5 Isotension-Isothermal Ensemble; 5.6 Grand-Canonical Ensemble; 5.7 Questions and Exercises; Chapter 6. Molecular Dynamics in Various Ensembles; 6.1 Molecular Dynamics at Constant Temperature; 6.2 Molecular Dynamics at Constant Pressure; 6.3 Questions and Exercises 327 $aPart III: Free Energies and Phase EquilibriaChapter 7. Free Energy Calculations; 7.1 Thermodynamic Integration; 7.2 Chemical Potentials; 7.3 Other Free Energy Methods; 7.4 Umbrella Sampling; 7.5 Questions and Exercises; Chapter 8. The Gibbs Ensemble; 8.1 The Gibbs Ensemble Technique; 8.2 The Partition Function; 8.3 Monte Carlo Simulations; 8.4 Applications; 8.5 Questions and Exercises; Chapter 9. Other Methods to Study Coexistence; 9.1 Semigrand Ensemble; 9.2 Tracing Coexistence Curves; Chapter 10. Free Energies of Solids; 10.1 Thermodynamic Integration; 10.2 Free Energies of Solids 327 $a10.3 Free Energies of Molecular Solids10.4 Vacancies and Interstitials; Chapter 11. Free Energy of Chain Molecules; 11.1 Chemical Potential as Reversible Work; 11.2 Rosenbluth Sampling; Part IV: Advanced Techniques; Chapter 12. Long-Range Interactions; 12.1 Ewald Sums; 12.2 Fast Multipole Method; 12.3 Particle Mesh Approaches; 12.4 Ewald Summation in a Slab Geometry; Chapter 13. Biased Monte Carlo Schemes; 13.1 Biased Sampling Techniques; 13.2 Chain Molecules; 13.3 Generation of Trial Orientations; 13.4 Fixed Endpoints; 13.5 Beyond Polymers; 13.6 Other Ensembles; 13.7 Recoil Growth 327 $a13.8 Questions and ExercisesChapter 14. Accelerating Monte Carlo Sampling; 14.1 Parallel Tempering; 14.2 Hybrid Monte Carlo; 14.3 Cluster Moves; Chapter 15. Tackling Time-Scale Problems; 15.1 Constraints; 15.2 On-the-Fly Optimization: Car-Parrinello Approach; 15.3 Multiple Time Steps; Chapter 16. Rare Events; 16.1 Theoretical Background; 16.2 Bennett-Chandler Approach; 16.3 Diffusive Barrier Crossing; 16.4 Transition Path Ensemble; 16.5 Searching for the Saddle Point; Chapter 17. Dissipative Particle Dynamics; 17.1 Description of the Technique; 17.2 Other Coarse-Grained Techniques 327 $aPart V: Appendices 330 $aUnderstanding Molecular Simulation: From Algorithms to Applications explains the physics behind the ""recipes"" of molecular simulation for materials science. Computer simulators are continuously confronted with questions concerning the choice of a particular technique for a given application. A wide variety of tools exist, so the choice of technique requires a good understanding of the basic principles. More importantly, such understanding may greatly improve the efficiency of a simulation program. The implementation of simulation methods is illustrated in pseudocodes and their practic 410 0$aComputational science (San Diego, Calif.) 606 $aIntermolecular forces$xComputer simulation 606 $aMolecules$xMathematical models 615 0$aIntermolecular forces$xComputer simulation. 615 0$aMolecules$xMathematical models. 676 $a539/.6/0113 700 $aFrenkel$b Daan$f1948-$0516837 701 $aSmit$b Berend$f1962-$0516838 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910458817003321 996 $aUnderstanding molecular simulation$9845931 997 $aUNINA