Lecture 7: Coarse Grain simulations Flashcards

1
Q

What do reduced units allow for?

A

Time, mass etc to be expressed in unitless quantities

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2
Q

What is the law of corresponding states?

A

There are infinitely many combinations that all correspond to the same reduced units

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3
Q

Why are reduced units useful?

A

Avoids errors from working with very small numbers from SI units

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4
Q

How can reduced units be thought of?

A

Rescaling so that corresponding states collapse onto one line

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5
Q

Where do reduced length units come from?

A

From the LJ potential
Length unit σ
Mass unit energy unit ε

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6
Q

What is reduced length equation? If σ =length of argon atom

A

r*=r/σ

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7
Q

Where do reduced units of time come from?

A

From the LJ potential

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8
Q

How do we find reduced units of time?

A

Find a combination of length, mass and energy units that give a unit of time
Use units from LJ potential
Take a product of arbitrary powers of these contacts and equate for s^1

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9
Q

Why is using reduced units good for larger systems?

A

More Computationally efficient

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10
Q

What is coarse groaning?

A

Representing more than one atom as a single bead by grouping them together

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11
Q

What is least coarse graining?

A

United atom that represents -CH2 as one bead with no explicit hydrogens

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12
Q

What are some advantages of coarse graining?

A

-allows larger system sizes
-allows longer timescales

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13
Q

What are some disadvantages of coarse graining?

A

-lose finer detail such as hydrogen bonding
-don’t always know what is a reasonable assumption/CG scheme to capture all the underlying physics/chemistry and won’t know until comparison with experimental data

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14
Q

What is a bottom up approach?

A

Match model to quantum mechanical or atomistic simulations
-first step to decide on mapping scheme- what atoms in what beads

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15
Q

What is the iterative Boltzmann inversion?

A

-generates non-analytical potential U(r)
-iterative so repeats until threshold tolerance value met
-generally done to compare from atomistic simulations based on CG scheme

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16
Q

What are the strengths of iterative Boltzmann inversion

A

-works for non-bonded and bonded interactions
-successful for a wide range of systems

17
Q

What are some weaknesses of iterative Boltzmann inversion

A

-non-transferable: highly dependent on state point of system used for parameterisation
-May not be representative of “true” underlying potential due to artefacts or properties not considered in procedure