nanopatterns – understanding emergence of properties at scale

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Nanopatterns – Understanding Emergence of Properties at Scale Robert D. Cormia & Jill N. Johnsen Foothill College

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novel pedogogy for understanding the emergence of properties at the nanoscale

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Page 1: Nanopatterns – understanding emergence of properties at scale

Nanopatterns – Understanding Emergence of Properties at

Scale

Robert D. Cormia & Jill N. Johnsen

Foothill College

Page 2: Nanopatterns – understanding emergence of properties at scale

Overview

• Nanoscience => the big ideas

• Emergence => the missing idea

• Nanopatterns => a new rubric

• Examples => nanopatterns in use

• Future directions and practice

Page 3: Nanopatterns – understanding emergence of properties at scale

Nanoscience – Big Ideas

• 2006 workshops

• NCLT and SRI

• University of Michigan and Northwestern University

• Eight big ideas

• A textbook guide

Page 4: Nanopatterns – understanding emergence of properties at scale

The Big Ideas

• Size and scale

• Matter

• Dominant Forces

• Properties are size dependent

• Models

• Tools

• Technology and society

• Self assembly

The Big Ideas in Nanoscale Science and Engineering Stevens, Sutherland, Schank, & Krajcik, (2007). Collaboration of NCLT, Northwestern University and SRI, in a series of workshops, (culminating in August 2006 in San Luis Obispo)

Page 5: Nanopatterns – understanding emergence of properties at scale

The Missing Idea

• Emergence of properties at scale

• We talk about it all the time

• But no one ever explains it

• Because……

Emergence is a very difficult topic to talk about!

Page 6: Nanopatterns – understanding emergence of properties at scale

Emergence Model

Archetype

Properties

Process

System

Process evolutionArc

hety

pe B

ehav

iors

System processSystem Archetype

System Constituents Actor Interactions

Class

prop

ertie

s

Archetype process

Syst

em P

rope

rties

Syst

em b

ehav

iors

Primitive interactions

Emergent Properties

Page 7: Nanopatterns – understanding emergence of properties at scale

Size Dependent Properties“Molecular Dynamics (MD) simulations of heat transfer based on classical statistical mechanics allow the atom to have thermal heat capacity through kT energy. Here k is Boltzmann’s constant and T absolute temperature. The above picture shows melting temperatures applied on the left with the right maintained at freezing. The simulation is discreted and submicron. But lacking periodicity, MD solutions of discrete nanostructures are invalid by QM. Here QM stands for quantum mechanics. Unlike statistical mechanics, QM forbids atoms in discrete submicron nanostructures to have heat capacity, and therefore the nanostructure cannot conserve EM energy by an increase in temperature. Without temperature changes, thermal conduction is precluded at the nanoscale.”

Melting point is an emergent property

Validity of Heat Transfer by Molecular Dynamics - http://www.nanoqed.org/

Page 8: Nanopatterns – understanding emergence of properties at scale

Size Dependent Properties:Ni nanoparticles => Nanomagnetism

http://www.grin.com/en/doc/231229/size-dependent-magnetic-properties-

http://www.flickr.com/photos/brookhavenlab/3191719900/in/photostream

Page 9: Nanopatterns – understanding emergence of properties at scale

Phonon Network

http://en.wikipedia.org/wiki/Phonon Images Wikipedia commons

Page 10: Nanopatterns – understanding emergence of properties at scale

Nanopatterns

• Network archetypes• Memorizing patterns, vs. structures• Patterns of atoms in structural networks• Atoms as nodes, each with atomic orbitals

=> focus on bonding networks• Network archetypes => nanosystems

– Smaller motifs, that expand into systems

Page 11: Nanopatterns – understanding emergence of properties at scale

Nanopatterns Rubric

• Networks of atoms• Systems of physics• Emergence of

properties at scale

• Draw network of atoms for a structural system

• Sketch out the chemical bonding / orbital network

• Look at the extended structure as a system

http://en.wikipedia.org/wiki/Pi_bond

Page 12: Nanopatterns – understanding emergence of properties at scale

Graphene Nanostructure

Extended sp2 hybridized carbon and p-p* network

Page 13: Nanopatterns – understanding emergence of properties at scale

Graphene as a System

Page 14: Nanopatterns – understanding emergence of properties at scale

Nanostructures and Nanosystems from carbon nano-motifs

nanostructure Nano-motif (or structural unit) Nanopattern Nanosystem

Graphene/graphite sp2 moiety bracket graphene hexagon Extended plane

Fullerene sp2 moiety cap hexagon/pentagon Enclosed sphere

Nanotube sp2 moiety mesh zigzag/armchair mesh Enclosed tube

Nanoonion sp2 moiety (ring?) zigzag/armchair swirl? Nanospheres?

Boron nitride nanomesh Trigonal BN BN hexagonal ring Planar honeycomb

Self Assembled Monolayers alkane (head and tail) 1-2 dimensional SAM 2 dimensional sheet

Liposomes phospholipid unit Phospholipid bilayer Spherical bilayers

Dendrimers g-0 functional branch Fractal branch (G-x)Spherical/functionalized macro-molecule

Page 15: Nanopatterns – understanding emergence of properties at scale

Allotropes of carbon

A - diamondB - graphiteC - lonsdaleiteD - C60 Buckminsterfullerene

E - Amorphous carbonF - C70

G - C540

H - single-walled carbon nanotube

http://en.wikipedia.org/wiki/Allotropes_of_carbon

Page 16: Nanopatterns – understanding emergence of properties at scale

Nano-OnionNano onion is a proposed structure for graphene which wraps itself into larger spheres and then into chains. The mechanism for forming the spheres is not known, but might be influenced by the chirality of the nanocarbon network, i.e., the armchair/zigzag m/n ratio. This factor can be measured in Raman G band (as G- and G+), and additionally in solid state 13C NMR. Nano-onion is an example of an extended nanostructure becoming a nanosystem, and having levels of unfolding complexity at scales of tens, hundreds, and thousands of Angstroms. The ability to ‘tune’ the chirality of the graphene networks, and alter the unfolding structure at the mesoscale, is one of the goals of combining the nanopatterns rubric with PNPA.

Page 17: Nanopatterns – understanding emergence of properties at scale
Page 18: Nanopatterns – understanding emergence of properties at scale

Borazine Nanomesh

• Borazine decomposition

• Forms ordered surface network

• One layer thick (like graphene)

• Extended structure• Emergent properties

http://en.wikipedia.org/wiki/Nanomesh

Page 19: Nanopatterns – understanding emergence of properties at scale

Borazine Nanomesh

Page 20: Nanopatterns – understanding emergence of properties at scale

Networks of atoms in novel nanoscale structures

“Dancing Triangles' are formed by sulfur atoms on a layer of copper, which in turn rests upon a base, or 'substrate' of ruthenium. Scientists at Brookhaven Lab will study this type of configuration to understand how metal behaves on top of another. Layered metals are often used as catalysts, such as those that clean pollutants from automobile exhaust in catalytic converters.”

Flickr Brookhaven Laboratory Stream http://www.flickr.com/photos/brookhavenlab/3191719710/in/photostream/

Page 21: Nanopatterns – understanding emergence of properties at scale

Nanostructures

• Small networks of atoms– Liposomes– Dendrimers– Carbon nanotubes– Self Assembled Monolayers– Unit cells of extended

nanostructured materials• Graphene• Nanomesh

Page 22: Nanopatterns – understanding emergence of properties at scale

Each phospholipid is a structural motif, a structure in itself, and a building block in a larger system

A system of phospholipids that is an emergent structure itself. Liposomes and cellular vessicles

http://en.wikipedia.org/wiki/Exosome_(vesicle)

http://en.wikipedia.org/wiki/Phospholipid

Page 23: Nanopatterns – understanding emergence of properties at scale

Nanosystems

Page 24: Nanopatterns – understanding emergence of properties at scale

Summary / References• Nanopatterns rubric

Networks of atomsSystems of physicsEmergence of properties at scale

• Nanostructures => nanosystems• The Big Ideas in Nanoscale Science and Engineering

Stevens, S. Y., Sutherland, L., Schank, P., & Krajcik, J. (2007).– http://www.mcrel.org/Nanoteach/pdfs/big_ideas.pdf