Scanning Probe Microscopy - A plethora of possibilities

Transkript

1 Scanning Probe Microscopy - A plethora of possibilities

2 Topics The basic idea The scanning part Scanning Tunneling Microscopy (STM) Theoretical backround Applications Various other modes of interest Atomic Force Microscopy (AFM) Lateral (sometimes called Friction) Force Microscopy (LFM) Magnetic Force Microscopy (MFM) Others Scanning Nanoindentation Quantitative mechanical/tribological properties on the nanoscale

3 Brief historic overview Topografiner: by Russel D. Young (piezo-translators) at NBS STM: 1982 by Heinrich Rohrer (1933-) and Gerd Karl Binning (1947-) at IBM Zürich Nobel prize 1986 AFM: 1986 by Gerd Karl Binning, Christoph Gerber and Calvin Quate at IBM Zürich & Stanford University Heinrich Rohrer (l) and Gerd Karl Binning (r)

4 Basic idea

5 The SPM family

6 The scanning part of SPMs Based on the piezoelectric effect: Piezo Tri-Pods Piezo-Tube-Scanners Problems of these scanners are: Hysteresis, creep Aging Cross-correlations between the individual axis These are addressed by extensive calibrationfunctions or closed-loopsystems utilizing laserinterferrometry Piezo-tube scanner and sketch of a piezo tripod

7 Scanning Tunneling Microscopy (STM) First success by Binning and Rohrer (IBM) in 1982 Atomic resolution is achieved due to the high sensitivity of the tunneling current with respect to the tip-sample distance s I ψ 1,2 2 2k 1 ψ2 2e s

8 Operation modes of STM Constant current A feeback-loop tries to keep the current between tip and sample constant while scanning z-piezo movement = constant density of states ( topography) Constant height Is an alternative approach: here the height is kept constant while the current is measured during scanning Scanning tunneling spectroscopy STS Probes the density of states at a given surface position by ramping the voltage while measuring the tunneling current

9 Applications of STM Examples Binning and Rohrer original scan of the 7 7 reconstruction of the Si(111) surface 20 years later: IBM work shows the density of states (DOS) of 48 iron atoms on a Cu (111) surface

10 Applications of STS Principles: By ramping of V T the density of states is probed Detailed information about the electronic configuration of the sample is available PbS quantum boxes electric states:

11 AFM - interaction Lennard-Jones potential is often cited Consisting of a vander-waals and a Pauli-part Distance-dependence of interaction is changed in case of nanoscale objects Basic behavior, however, is comparable

12 Various AFM modi

13 Contact mode pro High resolution is possible even though rather the exception Often one deals with a kind of Moirée-effect and is not able to identify individual defects (better resolution is reached by noncontact AFM under UHV conditions) Easy & artifacts are usually easy to handle cons Capillary forces can cause large forces between tip and surface Moving of objects on the surface Indentation effects / scratching of soft surfaces Friction based artifacts depending on scan direction Adhesive samples cause troubles

14 Non-contact mode Idea here is to sense the sample without touching it essential in the context of most polymer and biological samples Cantilever is operated close to its resonance frequency via a piezo actuator

15 Non-contact AFM Equation of motion free cantilever

16 Non-contact AFM What happens if we add a sample?

17 Lateral/Friction Force Microscopy (LFM)/(FFM) Set up: Cantilever based quadrant photo detector Comments: Challenging to calibrate Friction-loop is necessary to remove topography-effect Geometry of the tip Single or multiple asperity contact Stability of the tip

18 F-d measurements While moving the stage, the deflection of the cantilever is monitored Factors that have an influence on the experimental outcome: Adhesion Elasticity Visco-elastic behavior Plastic yield

19 Other techniques

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21 Beschreibung der Topographie Die Oberfläche eines ebenen Halbraumes sei durch z (x, y) gegeben. Statistisch lässt sich nun die Oberfläche durch die Funktion φ (z), die die Wahrscheinlichkeit angibt, dass ein Punkt der Oberfläche eine Höhe zwischen z und z + dz besitzt, beschreiben. Folgende Kennwerte findet man bei der Beschreibung der Rauheit einer Oberfläche: kumulative Höhenverteilung, Φ (z): Φ z ( z) φ ( z ) dz Mittelwert der Oberfläche, <z>: z L x 1 L y L x y z 0 L 0 dx dy RMS (root-mean-squared), s(rq): s L x 1 L y L x y 0 L 0 [ z z] 2 dx dy

22 Beschreibung der Topographie Weitere Parameter: Die mittlere lokale Steigung s' sowie die mittlere lokale Krümmung s'' der Oberfläche. Die folgenden zwei Gleichungen geben die Definition dieser Größen für den eindimensionalen Fall wieder: s x 1 L x L x 0 z x 2 dx s x 1 L x Viele reale Oberflächen weisen eine Normalverteilung (Gaussverteilung) der Höhen auf. Für abweichende Fälle werden in der Literatur zwei weitere Parameter eingeführt. Hierbei wird mittels der Größen Schräge der Verteilung (skewness) Sk sowie Schärfe der Verteilung (kurtosis) K die Form der Wahrscheinlichkeitsverteilung φ (z) charakterisiert. L x 0 2 z 2 x 2 dx Sk 1 s 1 s 3 4 z φ ( z) dz K z φ ( z) 3 4 dz Bei einer Oberfläche, deren Wahrscheinlichkeitsverteilung φ (z) der Gaussverteilung entspricht, erhält man eine Schräge Sk = 0 und eine Schärfe K = 3

23 Challenges in the context of SPMs Scanners: Hysteresis Creep Non-Linearity's Aging Tip artifacts Convolution Change over time Porous Aluminum Tip radis 1nm Uncertainties about the mechanism of interaction Tip radis 10nm

24 Tip convolution Sampling rate can also have an effect on the results