Modeling in science

Constructed by: Shant Shahbazian 1

The goal of modern science

• Knowing for controlling

• The measure of quality of knowledge in modern science is successful predictions

• Francis Bacon (1561-1626)

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How to describe nature in science

Simplifying reality and constructing models

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The principles of modeling

How to construct a model • Identifying system • Defining subsystems • Introducing the rules

governing on subsystems interactions

Details and consequences • Simplifying reality • The power of prediction • Different models for the

same reality

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Modeling solar system

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A simple model of solar system • Subsystems: Sun, planets and moons • The rule of interaction: Gravitational force and

classical mechanics • The goal: Predicting the location of planets • The quality: moderate

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A more complex model of solar system • Subsystems: Sun,

planets, moons, asteroids, comets,…

• The rule of interaction: Gravitational force and classical mechanics

• The goal: Predicting the location of all ingredients of system in long term

• The quality: high

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Comparison of two models

• Not only quantitative but also qualitative differences!

• The case of Solar system stability..

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Beyond our Solar system… • There are other solar systems in

our galaxy • Modeling these systems is a full

time job! • Check the link below as a simple

simulator: http://www.stefanom.org/spc/

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Climate modeling

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Models of the global changes of atmospheric temperature

• Subsystems: Volumes of atmosphere,…

• The rule of interaction: mass and energy transfer,…

• The goal: Predicting the variations of temperature in long durations

• The quality: yet uncertain!

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Wikipedia: Computational science

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Bioinformatics Cheminformatics Chemometrics Computational archaeology Computational biology Computational chemistry Computational economics Computational electromagnetics Computational engineering Computational finance Computational fluid dynamics Computational forensics Computational geophysics Computational informatics Computational intelligence Computational law Computational linguistics

Computational mathematics Computational mechanics Computational neuroscience Computational particle physics Computational physics Computational sociology Computational statistics Computer algebra Environmental simulation Financial modeling Geographic information system (GIS) High performance computing Machine learning Network analysis Neuroinformatics Numerical linear algebra Numerical weather prediction Pattern recognition Scientific visualization

Summary of general model building procedure

Prediction and description of reality 13

Modeling in chemistry

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How to practice chemistry! • Synthesizing new molecule by chemical reactions • Purification of desired product • Employing different types of spectra (IR, NMR, UV,

MS ,…) to elucidate details of molecular structure

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The role of models in chemistry

• Simplifying the complex “world of chemistry” to understand and predict its behavior

• The models in chemistry could be macroscopic or microscopic

• Examples of macroscopic models are kinetic models of chemical reactions and rate equations and also ideal gas model in thermodynamics

• The difference of modeling chemistry and practicing chemistry in laboratory is like the difference of observational and theoretical astronomy

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Why using molecular modeling?

• Prediction the existence of molecules and their properties prior to their synthesis in test tube

• Considering intermediates and transition states and other elusive molecular species

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Molecular modeling

• Object of study (system): A single molecule (atom) or a limited number of molecules

• Subsystems: They could

be electrons and nuclei, atoms and ions, even molecules

• Interactions: electric and magnetic forces

• Outcome: Predicting all static or dynamic properties of a molecule or a cluster of molecules prior to its synthesis

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Modeling a single molecule: Possible subsystems

• Composed on electrons and nuclei

• Composed of atoms

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Quantum Mechanical (QM) modeling: Electrons and nuclei as subsystems

• Electrons and nuclei interact by electric forces

• They behavior is dictated by Schrödinger’s equation

• The final picture is the electron cloud and point charge nuclei

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Molecular mechanics (MM) modeling: Atoms as subsystems

• Atoms are balls attached by “elastic” springs • Their behavior is dictated by the total energy of balls and

springs system (force field) • The final picture of a molecule is the atoms joint by

springs as bonds

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Why using different molecular modeling techniques?

• QM: high quality results and low speed

• MM: lower quality results but much higher speed

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What molecular modeling predicts about a single molecule?

• Molecular structure (conformation)

• Spectra of a molecule

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Modeling a cluster of molecules by MM method

• Subsystems could be atoms or even a molecule

• Understanding solvation at microscopic level

• Protein dynamics

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The role of computers in the modern molecular modeling

• Why we need to computers?

The need for doing large scale computations

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Modeling packages

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Let’s start the first appreciation of molecular modeling in next session!

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