Forcefields for Atomistic-Scale Simulations: Materials and Applications

Contents
Introduction to Molecular Dynamics Simulations
	1 Introduction
	2 Interatomic Potential or Force Field
	3 Numerical Integration: Finding Trajectories
	4 Time Step
	5 Cut-off Radius Distance
	6 Temperature Control
	7 Ensembles
	8 Boundary Conditions
	9 Energy Minimization
	10 MD Algorithm
	11 Limitations of MD
	12 Applications
	References
Introduction to Interatomic Potentials/Forcefields
	1 Potentials
		1.1 Introduction
		1.2 Cluster Potentials
		1.3 Pair Potentials
		1.4 Tersoff Potentials
		1.5 Potentials for Ionic Solids
		1.6 Reactive Force Field Potentials
	2 Types of Materials and Their Potential Models
	References
Current Perspective on Atomistic Force Fields of Polymers
	1 Introduction
	2 Atomistic Force Fields of Polymers
		2.1 Basics of Atomistic Force Fields
		2.2 Types of Force Fields
		2.3 Force Field Parameterization
		2.4 Atom Typing and Molecular Topology
		2.5 Time and Length Scales
	3 Atomistic Simulation Studies of Polymers
	4 Multiscale Simulations of Polymers
	5 Summary and Future Perspectives
	References
Forcefields and Modeling of Polymer Coatings and Nanocomposites
	1 Introduction
	2 Forcefields (FFs) and MD Simulations
		2.1 Intramolecular Terms
		2.2 Intermolecular Terms
	3 Popular Forcefields Used in Modeling and Simulation of Different Coating Composites
		3.1 Non-Reactive Forcefields
		3.2 Reactive Forcefields
	4 Case Studies
		4.1 Computational Studies in Coating Application
		4.2 Computational Studies in Nanocomposite-Based Materials
		4.3 Poly (Ethylene) (PE)-Based Nanocomposites
		4.4 Coiled Carbon Nanotube-Reinforced Nanocomposites
		4.5 Computational Studies on Graphene-Based Nanocomposites
	5 Comparison of Estimated Results of Nanocomposites Using Different Forcefields
	6 Conclusion
	References
Development, Availability, and Applications of EAM Potentials for Characterization of Complex HCP Materials
	1 Introduction
	2 Embedded Atom Method (EAM) Potential
		2.1 Development of EAM Potentials for HCP Materials
	3 Application of EAM Potentials—MD Simulations to Predict Properties of HCP Materials
		3.1 Yield Behaviour of Single Crystals
		3.2 Dislocations and Generalized Stacking Fault Energy in HCP Materials—MD-Based Studies
		3.3 MD Simulations to Generate and Investigate Bicrystalline and Polycrystalline HCP Metals
		3.4 Fracture Properties Single Crystals, Bicrystalline, and Polycrystalline HCP Metals Using MD-Based Simulations
		3.5 MD-Based Simulations to Study Point Defects Formation and Migration in HCP Metals
	References
EAM Potentials for Characterisation of HCP Nuclear Materials
	1 Introduction
	2 Application of EAM Potentials for Irradiation Studies in HCP Materials
	3 Conclusion
	References
EAM Inter-Atomic Potential—Its Implication on Nickel, Copper, and Aluminum (and Their Alloys)
	1 Introduction
	2 Embedded Atom Model
		2.1 Basics
	3 Applications
	4 Bulk Properties
		4.1 Phonons
		4.2 Thermodynamic Properties
		4.3 Liquids
		4.4 Defects
	5 Grain Boundaries
		5.1 Structure
		5.2 Thermal Effects
		5.3 Many-Body Interaction
		5.4 Elastic Properties
	6 Surfaces
	7 Alloys
		7.1 Surface Segregation in Dilute Limit
		7.2 Ni-Cu Alloy
		7.3 Compositional Ordering
		7.4 Segregation at Strain Field
	8 Mechanical Properties
		8.1 Dislocation
		8.2 Fracture
	9 Conclusion and Future Perspective
	References
Defect Energy Calculations of Nickel, Copper and Aluminium (and Their Alloys): Molecular Dynamics Approach
	1 Introduction
		1.1 Stacking Fault Energy
		1.2 Vacancy Formation Energy
		1.3 Interstitial Formation Energy
	2 Nickel
		2.1 Stacking Fault Energy
		2.2 Vacancy Formation Energy
		2.3 Interstitial Formation Energy
	3 Copper
		3.1 Stacking Fault Energy
		3.2 Vacancy Formation Energy
		3.3 Interstitial Formation Energy
	4 Aluminium
		4.1 Stacking Fault Energy
		4.2 Vacancy Formation Energy
		4.3 Interstitial Formation Energy
	5 Nickel–Copper Alloys
		5.1 Stacking Fault Energy
		5.2 Vacancy Formation Energy
	6 Aluminium–Copper Alloys
		6.1 Stacking Fault Energy
		6.2 Vacancy Formation Energy
	7 Nickel–Aluminium Alloys
		7.1 Stacking Fault Energy
		7.2 Vacancy Formation Energy
	8 Conclusion
	References
Tersoff and REBO Potentials
	1 Introduction
	2 Tersoff Potential
	3 Applications
	4 Mechanical Properties
		4.1 Defects
	5 Thermal Properties
	6 REBO Potential
	7 Abell–Tersoff Bond Order Potentials
	8 Analytic Bond Order Form
	9 Applications
	10 Mechanical Properties
	11 Thermal Properties
	12 Conclusion and Future Perspective
	References
Reactive Forcefield (ReaxFF): Application to Predict 2D Nanomaterials Synthesis
	1 Introduction
	2 Reactive Force Field (ReaxFF)
	3 Applications of ReaxFF for the Synthesis of 2D Nanomaterials
		3.1 Bulk Growth
		3.2 Defect and Growth of Nanomaterials Using ReaxFF
	4 Conclusion and Future Perspective
	References
Reinforcing Potential of 2D Nanofiller in Polyethylene: A Molecular Dynamics Approach
	1 Introduction
	2 Modeling of Nanocomposites Using MD Approach
		2.1 Force Field Potentials for Bonded and Non-bonded Interaction in Polymer Nanocomposites
	3 Mechanical Response of 2D Reinforced Polymer Nanocomposites
		3.1 Graphene-Based Polyethylene Nanocomposites
		3.2 Hexagonal Boron Nitride-Based Polyethylene Nanocomposites
	4 Conclusions
	References
Atomistic Simulations to Study Thermal Effects and Strain Rate on Mechanical and Fracture Properties of Graphene like BC3
	1 Introduction
	2 Simulation Details and Modeling
	3 Results and Discussion
		3.1 Mechanical Properties of BC3
		3.2 Fracture Properties of BC3
		3.3 Thermal Effects on Fracture Toughness
		3.4 STW Defects in BC3
	4 Conclusions
	References
Computational Modelling of Deformation and Failure of Bone at Molecular Scale
	1 Introduction
	2 Hierarchical Structure of Bone
	3 Molecular Mechanics of Bone Under Different States
		3.1 Mineralisation
		3.2 Effect of Hydration
		3.3 Cross-Linking
		3.4 Viscoelasticity and Deformation Rate
		3.5 Interfaces Within Bone
	4 Bone Diseases and Disorders
		4.1 Osteogenesis Imperfecta
		4.2 Osteoporosis
		4.3 Type 2 Diabetes (T2D)
		4.4 Aging
		4.5 Collagen Denaturation
	5 Collagen Inspired Bio-composites
	6 Conclusion and Future Perspectives
	References
A Review on the Deformation Mechanism of Soft Tissue Collagen Molecules: An Atomistic Scale Experimental and Simulation Approaches
	1 Introduction
		1.1 Common Structure of Soft Tissue
		1.2 Structure of Tropocollagen
		1.3 Collagen Cross Link and Their Role in Mechanical Response of Tissue.
	2 Different Types of Mechanical Response of the Tissue Associated with Nanoscale and Molecular Level
		2.1 Elastic Response
		2.2 Viscoelastic Properties
		2.3 Poroelastic Property
	3 Collagen Structural Mutation Related Changes in Mechanical Properties of Tissue
	4 Deformation Mechanism of the Lower Hierarchy of the Soft Tissue
	5 Experimental Approach to Investigate the Nano and Molecular Structure of Tissues
		5.1 Nano Mechanical Analysis for Various Soft and Hard Tissue (Atomic Force Microscopic)
		5.2 Raman Spectroscopy
		5.3 ATR-Ftir
		5.4 Fluorescently Labeled Collagen Hybridizing Peptide (F-CHP)
	6 Molecular Dynamics-Based Simulation to Predict the Molecular Level Mechanical Response of the Tissue
		6.1 Quasistatic and Dynamic Simulation
		6.2 Viscoelastic Simulation Using Molecular Dynamics
	7 Conclusion
	References
Introduction to Materials Studio Software for the Atomistic-Scale Simulations
	1 Introduction
	2 Modules and Their Applications
		2.1 Materials Visualizer
		2.2 Amorphous Cell
		2.3 Powder Solve
		2.4 Polymorph Predictor
	3 Widely Used Forcefields Under Materials Studio (MS) Software
		3.1 COMPASS
		3.2 COMPASS II
		3.3 Universal
		3.4 CVFF
		3.5 PCFF
		3.6 Comparative Study of Forcefields
	4 Conclusion
	References
Data-Driven Phase Selection, Property Prediction and Force-Field Development in Multi-Principal Element Alloys
	1 Introduction
	2 Machine Learning for Materials Science
		2.1 Materials Informatics
		2.2 Databases
		2.3 Feature Creation and Selection
		2.4 Machine Learning Algorithms
	3 Data-Driven Models for MPEAs
		3.1 Phase Selection
		3.2 Mechanical Properties
		3.3 Ordering Behaviour
	4 Atomistic Potential Development
		4.1 Classical Methods
		4.2 Machine Learning Enabled Potential Development
	5 Conclusions and Future Perspectives
	Appendix 1
	References
Effect of Geometrical Parameters on Branched Cracks: A Finite Element Method-Based Computational Approach
	1 Introduction
	2 Review of Literature
		2.1 Evaluation of Stress Intensity Factor
		2.2 Evaluation of Crack Branching
		2.3 Evaluation of T-Stress
	3 Materials and Methods
		3.1 Material
		3.2 Stress Intensity Factor
		3.3 Specimen Geometry
		3.4 Method
		3.5 Numerical Approach of T-stress Analysis
		3.6 Crack Analysis
		3.7 General Postprocessor
	4 Results and Discussion
		4.1 Validation
		4.2 Branched Crack
		4.3 Effect of Crack Inclination Angle (α) on SIF and T-Stress
		4.4 Effect of Biaxial Load Factor (β) on SIF and T-Stress
		4.5 Effect of Crack Length Ratio (a1/a2) on SIF and T-Stress
		4.6 Von Mises Distribution
	5 Conclusions
	6 Future Aspects
	References