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Structural Analysis using Computational Chemistry [Kõva köide]

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  • Formaat: Hardback, 182 pages, kõrgus x laius: 234x156 mm, kaal: 439 g
  • Ilmumisaeg: 08-Sep-2016
  • Kirjastus: River Publishers
  • ISBN-10: 8793379951
  • ISBN-13: 9788793379954
Teised raamatud teemal:
Structural Analysis using Computational ChemistrySuurem pilt
  • Formaat: Hardback, 182 pages, kõrgus x laius: 234x156 mm, kaal: 439 g
  • Ilmumisaeg: 08-Sep-2016
  • Kirjastus: River Publishers
  • ISBN-10: 8793379951
  • ISBN-13: 9788793379954
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9788793379954.html
Computational chemistry is a science that allows researchers to study, characterize and predict the structure and stability of chemical systems. In other words: studying energy differences between different states to explain spectroscopic properties and reaction mechanisms at the atomic level. This field is gaining in relevance and strength due to field applications from chemical engineering, electrical engineering, electronics, biomedicine, biology, materials science, to name but a few.

Structural Analysis Using Computational Chemistry arises from the need to present the progress of computational chemistry in various application areas.

Technical topics discussed in the book include:
• Quantum mechanics and structural molecular study (AM1)
• Application of quantum models in molecular analysis
• Molecular analysis of insulin through controlled adsorption in hydrogels based on chitosan
• Analysis and molecular characterization of organic materials for application in solar cells
• Determination of thermodynamic properties of ionic liquids through molecular simulation
Prologue xiii
Acknowledgments xv
List of Contributors
xvii
List of Figures
xix
List of Tables
xxiii
List of Abbreviations
xxvii
1 Quantum Mechanics and Structural Molecular Study (AM1)
1(30)
Norma-Aurea Rangel-Vazquez
Nancy-Liliana Delgadillo-Armendariz
1.1 Theoretical Basis of Quantum Mechanics
2(11)
1.1.1 Semiempirical Methods
6(1)
1.1.1.1 The semiempirical method AM1
6(1)
1.1.1.1.1 Application of AM J method in molecular structural study
7(1)
1.1.1.1.2 Certain molecular properties
7(2)
1.1.2 Computational Suite (HyperChem)
9(1)
1.1.2.1 The molecules analyzed
9(4)
1.1.2.2 Molecular modeling
13(1)
1.2 Calculation of Molecular Properties
13(3)
1.2.1 Molecular Energy
13(1)
1.2.2 Obtaining the QSAR Properties
14(1)
1.2.3 FTIR Analysis
14(1)
1.2.4 Electrostatic Potential Map
14(1)
1.2.5 Determination of Glibenclamide/Water Solubility
15(1)
1.2.6 Degree of Cross-Linking in the Polymer Matrix
15(1)
1.2.7 Covalent Cross-Linking
16(1)
1.2.8 Polymer Matrix/Glibenclamide
16(1)
1.3 Results
16(11)
1.3.1 Structural Analysis of Glibenclamide (G)
16(1)
1.3.1.1 QSAR properties and energy
16(2)
1.3.1.2 FTIR
18(1)
1.3.1.3 Electrostatic potential map
19(1)
1.3.2 Structural Analysis of the Water Molecule and G/A
20(1)
1.3.2.1 QSAR properties and energy
20(1)
1.3.2.2 FTIR
20(1)
1.3.2.3 Electrostatic potential map
21(1)
1.3.3 Structural Analysis of Chitosan
21(1)
1.3.3.1 QSAR properties and energy
21(1)
1.3.3.2 FTIR
22(1)
1.3.3.3 Electrostatic potential map
22(1)
1.3.4 Structural Analysis of Genipin
23(1)
1.3.4.1 QSAR properties and energy
23(1)
1.3.4.2 FTIR
23(1)
1.3.4.3 Electrostatic potential map
23(1)
1.3.5 Cross-Linking: Chitosan/Genipin (C/Ge)
24(1)
1.3.5.1 QSAR properties and energy
24(1)
1.3.5.2 Electrostatic potential map
25(1)
1.3.6 Adsorption of Glibenclamide in Chitosan/Genipin
26(1)
1.3.6.1 QSAR properties and energy
26(1)
1.3.6.2 FTIR
26(1)
1.3.6.3 Electrostatic potential map
26(1)
1.4 Conclusions
27(4)
Acknowledgments
28(1)
References
28(3)
2 Application of Quantum Models in Molecular Analysis
31(22)
Norma-Aurea Rangel-Vazquez
Nancy-Liliana Delgadillo-Armendariz
2.1 Introduction
32(4)
2.1.1 Election of the Quantum Model
32(1)
2.1.1.1 Choice of model in basic molecular properties
32(1)
2.1.1.2 Election model according to their origin
33(2)
2.1.1.3 Choice of a semiempirical model
35(1)
2.2 Application of Quantum Models in the Structural Analysis of a Polymer Matrix for Drug Release
36(11)
2.2.1 Structural Analysis of Metformin
38(1)
2.2.2 Structural Analysis of Glibenclamide
39(2)
2.2.3 Structural Analysis of the Elements of the Polymer Matrix
41(1)
2.2.3.1 Chitosan
41(2)
2.2.3.2 Genipin
43(2)
2.2.3.3 Water
45(2)
2.2.3.4 IR (Infrared)
47(1)
2.3 System Analysis: Polymer Matrix/Drug
47(3)
2.3.1 Analysis of Physicochemical and Energy Properties
47(2)
2.3.2 Electrostatic Potential Map
49(1)
2.3.3 IR (Infrared)
49(1)
2.4 Conclusions
50(3)
Acknowledgments
51(1)
References
51(2)
3 Molecular Analysis of Insulin Through Controlled Adsorption in Hydrogels Based on Chitosan
53(26)
Norma-Aurea Rangel-Vazquez
Ana-Karen Frias-Gonzalez
3.1 Introduction
54(7)
3.1.1 Polymers
54(1)
3.1.1.1 Chitosan
54(1)
3.1.2 Hydrogels
55(1)
3.1.2.1 Cross-linking agents
56(1)
3.1.2.2 Genipin
56(1)
3.1.3 Adsorption of Drugs
57(1)
3.1.3.1 Dermal adsorption
57(1)
3.1.4 Diabetes
58(1)
3.1.4.1 Insulin
59(1)
3.1.5 Computational Chemistry
60(1)
3.2 Methodology
61(1)
3.2.1 Determination of Structures Individually
61(1)
3.2.2 Calculation of Energy
61(1)
3.2.3 Obtaining the Partition Coefficient (Log P)
61(1)
3.2.4 Obtaining the Electrostatic Potential Map
61(1)
3.2.5 Analysis of the Infrared Spectrum (FTIR)
61(1)
3.3 Results
62(11)
3.3.1 Structural Analysis of Chitosan
62(1)
3.3.1.1 Energy optimization and partition coefficient (Log P)
62(1)
3.3.1.2 Electrostatic potential map
62(1)
3.3.1.3 FTIR
62(2)
3.3.2 Structural Analysis of Genipin
64(1)
3.3.2.1 Energy optimization and partition coefficient (Log P)
64(1)
3.3.2.2 Electrostatic potential map
64(1)
3.3.2.3 FTIR
64(1)
3.3.3 Structural Analysis of Chitosan Cross-Linked with Genipin (C/G)
65(1)
3.3.3.1 Energy optimization and partition coefficient (Log P)
65(1)
3.3.3.2 Electrostatic potential map
66(1)
3.3.3.3 FTIR
66(1)
3.3.4 Structural Analysis of Insulin
67(1)
3.3.4.1 Energy optimization and partition coefficient (Log P)
67(1)
3.3.4.2 Electrostatic potential map
68(1)
3.3.4.3 FTIR
69(1)
3.3.5 Determination of the Structural Properties of the Binding of Insulin and Chitosan Cross-Linked with Genipin (C/G-insulin)
70(1)
3.3.5.1 Energy optimization and partition coefficient (Log P)
70(1)
3.3.5.2 Electrostatic potential map
71(1)
3.3.5.3 FTIR
72(1)
3.4 Conclusions
73(6)
Acknowledgments
74(1)
References
74(5)
4 Analysis and Molecular Characterization of Organic Materials for Application in Solar Cells
79(36)
Norma-Aurea Rangel-Vazquez
Ediht-Sofia Martinez-Rodriguez
4.1 Introduction
80(19)
4.1.1 Computational Chemistry
80(1)
4.1.1.1 Molecular mechanics (MM)
80(4)
4.1.1.1.1 AMBER model
84(2)
4.1.1.2 Quantum mechanics
86(1)
4.1.1.3 Semiempirical methods
87(1)
4.1.1.3.1 Parametric method 3
88(1)
4.1.2 Composites
89(2)
4.1.2.1 Polymer matrix
91(1)
4.1.3 Polymers
92(1)
4.1.3.1 High-density polyethylene
92(2)
4.1.3.2 PCPDTBT
94(1)
4.1.4 Graphite
95(1)
4.1.4.1 Fullerene
96(2)
4.1.5 HyperChem
98(1)
4.1.5.1 Calculation properties
98(1)
4.2 Methodology
99(2)
4.2.1 Determination of Individual Structures
99(1)
4.2.2 Calculation of Energy
99(1)
4.2.3 Getting QSAR Properties
100(1)
4.2.4 Obtaining Electrostatic Potential Map
100(1)
4.2.5 Infrared Spectral Analysis (FTIR)
101(1)
4.2.6 Obtaining Structural Parameters
101(1)
4.3 Results
101(6)
4.3.1 Structural Analysis of PCPDTBT-Fullerene-Polyethylene
101(1)
4.3.1.1 Energy optimization
101(1)
4.3.1.2 Electrostatic potential map
101(2)
4.3.1.3 Bond length
103(2)
4.3.1.4 Spectrum Fourier Transform Infrared (FTIR)
105(2)
4.4 Conclusions
107(8)
Acknowledgments
107(1)
References
107(8)
5 Determination of Thermodynamic Properties of Ionic Liquids Through Molecular Simulation
115(36)
Claudia-Lizeth Salas-Aguilar
5.1 Introduction
116(11)
5.1.1 Overview of Simulation
117(1)
5.1.2 Implementation of the Simulation Method
117(1)
5.1.3 Collective Simulation
118(1)
5.1.4 Interatomic Potential
119(1)
5.1.4.1 Forces of attraction-repulsion
119(1)
5.1.4.2 Electrostatic forces
120(1)
5.1.5 Initial Conditions and Boundary Conditions
120(2)
5.1.6 Radio of Cutting and Condition of Minimum Image
122(1)
5.1.7 Monte Carlo Simulation Technique
122(1)
5.1.7.1 Technical Monte Carlo in isothermal-isobaric group (NPT)
122(1)
5.1.7.2 Insertion of test particle technique and Henry constant
123(1)
5.1.8 Molecular System Description
124(1)
5.1.8.1 All atoms (AA)
125(1)
5.1.8.2 United atoms (UA)
125(1)
5.1.9 Standard Monte Carlo Moves Involving a Single Box
125(1)
5.1.9.1 Translation move
125(1)
5.1.9.2 Rotation move
125(1)
5.1.9.3 Volume changes
126(1)
5.1.9.4 Flip moves
126(1)
5.1.9.5 Reputation move
126(1)
5.1.9.6 Pivot move
127(1)
5.2 Methodology
127(9)
5.2.1 Construction of the Cation and Anion
127(1)
5.2.2 Construction of the Simulation Box
127(1)
5.2.3 System Simulation Parameters
128(3)
5.2.4 Calculation of Thermodynamic Properties
131(1)
5.2.4.1 Thermal expansion coefficient (αP)
132(1)
5.2.4.2 Isothermal compressibility coefficient (κT)
132(1)
5.2.4.3 Isochoric and isobaric heat capacity (Cv and Cp)
133(1)
5.2.4.4 Joule---Thomson coefficient (μJT)
134(1)
5.2.4.5 Speed of sound (μ)
135(1)
5.2.4.6 Chemical potential of the solute (μ2ex)
135(1)
5.2.4.7 Henry constant (h)
135(1)
5.2.5 Calculation of Structural Properties
135(1)
5.3 Results and Discussions
136(11)
5.3.1 Molecule Construction
136(2)
5.3.2 Simulation Box
138(1)
5.3.3 Data Entry System
138(1)
5.3.4 Equilibration Phase of System
138(2)
5.3.5 Production Phase of System
140(4)
5.3.6 Radial Distribution Functions of Ionic Liquid
144(3)
5.4 Conclusions
147(4)
Acknowledgments
147(1)
References
147(4)
Index 151(2)
About the Editor 153
Norma-Aurea Rangel-Vázquez