experimental planning & data analysis

P A G E 0 P A G E 0

O U T L I N E

• Experimental tips and tricks

• Experimental planning

• Cleaning of surfaces

• Samples

• Instrument

• Data analysis

• Modelling fundamentals

• Advanced modelling

EXPERIMENTAL PLANNING

& DATA ANALYSIS

P A G E 1 P A G E 1

EXPERIMENTAL TIPS AND

TRICKS

GENERATING QUALITY DATA

P A G E 2 P A G E 2

QCM-D Experiment Planning

Surface

What type of surface?

How will I clean/prepare the surface?

What buffer (solvent)?

Which concentration(s)?

What Temperature?

Do I need to degas my samples?

Samples

How do I clean/prepare the instrument?

What liquid path am I going to use?

What about solvent compatibility?

Flow rate/Batch mode?

Instrument 1

2

3

4

parallel

P A G E 3 P A G E 3

Methods & Protocols

Collection of preparation and cleaning

methods for surfaces and instrument

Cleaning Au Cleaning SiO2 Instrument cleaning

P A G E 4 P A G E 4

Surfaces in Gas & Liquid Environment Deposits in ambient air:

• hydrocarbons

• dust

• oxidation

• water

Deposits in liquid environment:

• solvent residues (organic, salt)

• detergents

• dissolution of surface components and deposits

Consequences of deposits:

• changes in chemical composition

• change in wetability

• decrease in reproducibility

P A G E 5 P A G E 5

Contamination - 3D vs. 2D

small effect in 3D large effect in 2D

P A G E 6 P A G E 6

Cleaning Q-Sense sensors

• Q-Sense sensors have been exposed to

ambient air for a considerable amount of

time (weeks) when they reach the

customer.

What are the practical implications of contamination?

• For most applications relevant cleaning is

necessary before use in order to get

reproducible results!

P A G E 7 P A G E 7

Reusing Surfaces

sensors are disposable, but can

in some cases be reused

materials:

• quartz

• gold

• chromium

resistance to:

• many organic solvents, acids, bases

• temperatures up to 100ºC (and more)

reusing application-dependent

active side

contact side

Sensor

active

electrode

counter

electrode

quartz disc

P A G E 8 P A G E 8

Clean Sensor (and tweezers)

+

Gold

Ammonia, Peroxide Mix (TL1) UV/Ozone

SiO2

SDS Thick films/

Heavy contaminated + UV/Ozone

P A G E 9 P A G E 9

Equipment

Cleaning Holder

• holds up to 5 sensors

• made of Teflon

• prevents wear of sensors

• with removable grip for easy transfer

P A G E 10 P A G E 10

Chemical Treatment, TL1

• Surface: Gold

• Removes: Lipids, thiols, proteins in

molecular layers

W. Kern et al., RCA Review 31 (1970) 187

Method:

• UVO-treatment (10 min)

• Heat 5:1:1-mixture of MQ-water,

ammonia (25%) and hydrogen peroxide

(30%) to 75C

• Immerse the sensors in the solution

using a cleaning holder (5 min)

• Clean tweezer

• Rinse in MQ-water, dry with N2

• UVO-treatment (10 min)

P A G E 11 P A G E 11

Surfactant treatment

• Surface: Any metal and oxide surface (standard for SiO2)

• Much milder than TL1

• Removes: most biologic substances, like proteins and lipids

Method:

• UVO-treatment (10 min) (Not for Ag!)

• Prepare a solution of 2% Sodium

Dodecyl Sulfate (SDS) in milliQ water.

• Immerse the sensors in the solution in

room temperature for 30 min

• Rinse in mQ-water, dry with N2

• UVO-treatment (10 min) (Not for Ag!)

K. Harewood et al, Anal. Biochem. 55 (1973) 573

J. Penfold et al, Langmuir 18 (2002)

P A G E 12 P A G E 12

Cleaning Surfaces–UVO-Treatment

sensor surface

• effective in air

• exposure time: 5-10 min

P A G E 13 P A G E 13

does:

• volatilize thin films of organic contaminants

• oxidize the surface

does not:

• remove thick films of contaminants (risk of incrustation)

• remove inorganic contaminants (dust, salt)

Plasma cleaning – an alternative ?

• common cleaning method

• UVO-treatment cheaper

• risk of contamination in contaminated chamber

Cleaning Surfaces – UVO-Treatment

references:

J.R. Vig, J. Vac. Sci. Technol. A 3 (1985) 1027

Krozer et al, J. Vac. Sci. Technol. A 15 (1997) 1704

P A G E 14 P A G E 14

Be careful with polymer surfaces!

• Surfactants like SDS and Hellmanex may increase

the surface roughness of the polymer coating, or

remove parts of it

• SDS particles may also get stuck in the polymer

• UVO-treatment may destroy a polymer surface

P A G E 15 P A G E 15

Sensors Dry and Dust Free

Rinse washing solution off Dry with a clean gas

N2

Ar2

CO2

Never use compressed air!

Keep tweezer below sensor

P A G E 16 P A G E 16

Surfaces – Spin-Coating

• Thickness of the deposited film can be roughly determined with

QCM-D by measuring f and D before and after coating

• Excess polymer solution can travel over sensor edge and cover

backside electrodes – clean with solvent on cotton stick

References on spin-coating:

• Meyerhofer et al., J. Appl. Phys. 49 (1978) 3993

• Bornside et al., J. Imaging Technology 13 (1987) 122

sensor

cotton stick

P A G E 17 P A G E 17


Surface


How will I clean it?

P A G E 18 P A G E 18

Pure samples

Water:

18,3 MΩ MilliQ

Buffers:

Prepare your own

buffers, do not trust

the ”kitchen”!

Water

PBS

HEPES

MES

ACETAT

.....

sterile≠clean

P A G E 19 P A G E 19

Concentrations

low high

No/slow response

Diffusion / Depletion

Bulk effect, aggregation

Too rapid kinetics

Costly

Typical Concentrations

Protein 0.1-100 μg/ml

Antibody 0.01-10 μg/ml

Cells 104 - 106 CFU/ml

DNA pmol-nmol

0.1-100 µg/ml

Optimal concentration region

P A G E 20 P A G E 20

-10

-5

0

5

10

-3

-2

-1

0

1

2

0 5 10 15 20

f3 (Hz)f5 (Hz)f7 (Hz)

D3 (1E-6)D5 (1E-6)D7 (1E-6)

f (H

z)

D

(10

-6)

time (min)

Bulk effects – “Buffer step”

Effect:

offset in baseline of f and D

when changing solution

Cause:

bulk properties

- density & viscosity -

influence f and D

D

off

f o

ff

buffer 1 buffer 2

P A G E 21 P A G E 21

Avoid Temperature changes

Sun light

Draught

Air condition

Fume Hood

General recommendation

• Constant ambient

temperature

• Ensure good heat transport

from chamber base

P A G E 22 P A G E 22

Degas samples

Origin: Buffer

Hydrophobic

surfaces more

problematic!

Degassing samples

• Sonicator + vacuum

• Heat (Tsample>Tinstrument)

P A G E 23 P A G E 23


Surface





Temperature?

Degassing

Samples

P A G E 24 P A G E 24

Instrument cleaning

Cleaning solutions:

Hellmanex 2% in mQ (ca 10 ml)

SDS 2% in mQ (ca 10 ml)

Always end with a water

rinse and store chamber

dry!

Replace rubber parts when

worn out or every year.

P A G E 25 P A G E 25

Handling of the system

Flow modules can be disassembled and cleaned

Tubing and other consumables need exchanging

High chemical compatibility (Teflon, titanium, o-

ring and gasket polymer material)

Cleaning protocols, chemical compatibility charts

and consumable guides available

P A G E 26 P A G E 26

Solvent compatibility

E4/E1 systems

Liquid interfacing materials

(standard configuration)

• Module: Titanium, grade 2

• Inlet/outlet tubing: Teflon

• O-rings and gaskets: Viton

• Pump tubing: Viton

Check Chemical Compatibility Chart!

Highly resistant tubings and O-rings/sealings (Kalrez)

available

P A G E 27 P A G E 27

Summary

Surface





Temperature?

Degassing

Samples

Cleaning

Liquid path

Solvent compatibility

Flow rate

Instrument 1

2

3

4

parallel

P A G E 28 P A G E 28

Tech tips

• Ensure to have a clean surface

• Always start in reference solvent (buffer, water etc)

• Avoid difference in bulk properties

• Bubble = trouble

• Do your own sample preparation!

P A G E 29 P A G E 29

DATA ANALYSIS

h

r

h m

Δ

D

time

Δf Δf ΔD ΔD

P A G E 30 P A G E 30

O U T L I N E

• Different types of data evaluation

– Qualitative vs Quantitative analysis

• Quantitative analysis (modeling)

– Sauerbrey vs Viscoelastic modeling (Qtools)

1. What is the difference?

2. When to use what model

3. What happens if I use the wrong model?

• Viscoelastic modeling in Qtools

1. Procedure step by step

2. How do I know I have a good fit?

3. How do I improve the fit?

• Advanced modelling options

Δ

D

time

Δf Δf ΔD ΔD

P A G E 31 P A G E 31

Q U A L I T A T I V E

A N A L Y S I S

P A G E 32 P A G E 32

QCM-D data analysis

Qualitative :

– raw data plot

relative comparison of responses, shifts, rates, etc

– f –D plot reveals for example phase transitions

ΔD

time

Δf

Δf ΔD

ΔD

Frequency [Hz]

Phase 1

Phase 2

P A G E 33 P A G E 33

Q U A N T I T A T I V E

A N A L Y S I S

P A G E 34 P A G E 34

QCM-D data analysis

Quantitative (modeling): – rigid film: Sauerbrey m = -17.7 * f/n

– soft film: Viscoelastic modeling of f:s and D:s

Δ

D

time

Δf Δf ΔD

ΔD

•m (r, h)

•m

•h

?

h

r

h m

P A G E 35 P A G E 35

From raw data extract numbers that

describe our system in a quantitative way

1. RIGID FILM

2. SOFT FILM

Viscoelastic model

Output:

ρ: density (kg/m3)

η: viscosity (G’’/ω), (kg/ms)

μ: elasticity (G’), (Pa)

d: thickness (m)

Input:

∆f:s

∆D:s

Output:

m: mass (ng/cm2)

Input:

∆f Sauerbrey relation

Quantitative Analysis:

h

r

h m

P A G E 36 P A G E 36

The Sauerbrey equation

- input and Output

m = -17.7 * f/n

G. Sauerbrey in 1959

Sauerbrey

m = areal mass density (ng/cm2)

Thin and rigid homogeneous films Laterally heterogeneous films (“discrete particles”) with little energy dissipation

includes hydrodynamically coupled solvent

P A G E 37 P A G E 37

Mucin adsorption onto Au

Time (h:m:s)1:20:001:10:001:00:00

Th

ickn

ess (

nm

)

50

40

30

20

10

0


Time (h:m:s)1:20:001:10:001:00:00

Vis

co

sity (

Pa

s)

0.0015

0.001

0.0005

0

Viscoelastic Model (QTools)

- input and Output

D_1:3gfedcb

D_1:5gfedcb

D_1:7gfedcb

D_1:9gfedcb

D_1:11gfedcb

F_1:3gfedcb

F_1:5gfedcb

F_1:7gfedcb

F_1:9gfedcb

F_1:11gfedcb


Time (h:min:s)1:20:001:10:00

Fre

qu

en

cy s

hift

0

-10

-20

-30

-40

-50

-60

-70

-80

-90

Dis

sip

atio

n (E

-6)

15

14

13

12

11

10

9

8

7

6

5

4

3

2

1

0

-1

QTools

Input parameters

• Δf:s and ΔD:s

• Layer density

• Fluid density and viscosity


Time (h:m:s)1:20:001:10:001:00:00

Sh

ea

r m

od

ulu

s (

Pa

)

1.5E4

1E4

5000

0

thickness

viscosity

Shear modulus

P A G E 38 P A G E 38

Film is

• Rigidly attached

• Evenly distributed

• Homogeneous character ,

with certain properties

Thickness, h

Density, r

Viscosity,h

Elasticity, m

Our QCM-D response model

Assmptions:

homogeneous character, evenly distributed, rigidly attached

h

r

h m

P A G E 39 P A G E 39

MODEL INPUT Δf1 , ΔD1

+

Δf2, ΔD2

+

ρ (or h)

Domack et al., Physical Review E 56 (1997);

Voinova et al., Physica Scripta 59 (1999)

ρ: density, (kg/m3)

η: viscosity (kg/m·s)

μ: elasticity (kg/m·s2)

h: thickness, (m)

Crystal

Film

(ρ, h, m) h

Fluid

(ρl, hl)

n=1 n=3

MODEL OUTPUT η, μ, m (=h· ρ)

Viscoelastic modelling - What exactly is it that we do?

h

r

h m

P A G E 40 P A G E 40

Sauerbrey vs Viscoelastic modelling

When to use which model?

Sauerbrey Viscoelastic

• D = 0

• Responses overlapping

on all harmonics

• D > 0

• Responses NOT overlapping

on all harmonics

P A G E 41 P A G E 41

Sauerbrey vs Viscoelastic modelling

What happens if I use the wrong model?

Sauerbrey when it should be

Viscoelastic

Viscoelastic

when it should be

Sauerbey

2. Mass will be

underestimated

1. Mass depends

on harmonic

Can be difficult to model

– not enough input

P A G E 42 P A G E 42

Viscoelastic modelling in QTools

1. Procedure step by step

2. How do I know I have a good fit?

3. Improving the fit

P A G E 43 P A G E 43

Grid Fit

max

Viscosity

Thickness

Shear

modulus min

max

max

• Three parameters

• From ”initial guess values” of

the wanted parametrs, the

model calculates the f and

D shift.

=> These shifts are

compared to the ”true”

experimental values for f and

D

• Backwards calculation

P A G E 44 P A G E 44

The Viscoelastic Model- requirements

What needs to be fulfilled?

A laterally homogeneous and evenly distributed film

The bulk fluid is a Newtonian fluid

The adsorbed layer couples perfectly to the sensor (no slip) The observed signal is due only to the film

P A G E 45 P A G E 45

Getting started

• Open a QSoft file in QTools

• Go to Modeling/New Model/Viscoel....

P A G E 46 P A G E 46

Tab 1: ”Model Settings”

Choose the Voigt model

P A G E 47 P A G E 47

Each harmonc is unique

in a viscoelastic system

Δf=function1(n,ηf,ρf,μf,δf)

ΔD=function2(n,ηf,ρf,μf,δf)

Tab 1, Model Settings:

How many overtones do I need to include?

Include as many

harmonics

as possible!

P A G E 48 P A G E 48

Fixed parameters

Tab 2: ”Parameters”

Parameters to fit

P A G E 49 P A G E 49

”Estimate

all”

Tab 3: ”Measured data”

P A G E 50 P A G E 50

Tab 4: ”Fit settings”

Limit x

Fit

direction

P A G E 51 P A G E 51

Th

ickn

ess

Shear

modulus min

max

max

max

Grid

fit

Fitting routine SIMPLEX

Nelder, J. A., & Mead, R. 1965,Comp. J., 7, 308

Tab 4: ”Fit settings”

P A G E 52 P A G E 52

1. Do the fitted and measured curves overlap well (i.e. is the ChiSquare low)?

2. Do the output parameters vary smoothly with time?

3. Does the output make physical sense?

Do I have a good fit?

Tab 5: ”Fit analysis”

2 = Σi [(Ytheory,i - Ymeas,i)/σi]2

P A G E 53 P A G E 53

2 = Σi [(Ytheory,i - Ymeas,i)/σi]2

With a grid that is too rough, the deepest minimum might be overlooked Increase the number of steps or decrease the parameter range

How to improve the fit

(The best fit has the lowest chisquare 2)

10nm 100nm

e.g. thickness grid

2

P A G E 54 P A G E 54

Summary Sauerbrey:

• ΔD is small / overtones are overlapping

• Rigid and thin film

Viscoelastic modeling:

• ΔD > 0 and spreading of overtones

• Soft (and laterally homogeneous) film

How to validate the fit?

• The fit should match the experimental data.

• Alter input parameter matrix (min, max and/or number of steps), and

check if the solution is unique

• Do the output parameters make sense physically?

• In time-resolved fitting, the output parameters (viscoelastic properties,

mass/thickness) should vary smoothly with time.

P A G E 55 P A G E 55

ADVANCED MODELING OPTIONS

• Two layer modeling in QTools

• Frequency dependent viscoelasticity

(QTools Extended viscoelastic model)

P A G E 56 P A G E 56

MODELING A TWO-STEP

ADSORPTION PROCESS

USING QTOOLS

P A G E 57 P A G E 57

The experiment

Three approaches:

1. Model the layers one

by one (L1 + L2)

2. Model layer two as

L1(if first layer rigid)

3. Model L1 + L2

as one layer

P A G E 58 P A G E 58

Approach 1: Model the two layers one by one

Step 1: Model Layer A as Layer 1 [L1]

– Parameters to fit: viscosity, shear modulus and thickness

– Limit x-values

P A G E 59 P A G E 59

• Find the best solution

• Results in the parameters for L1, Layer A

Approach 1: Results step 1

Parameter Modeled data

L1 Viscosity 0,003 kg/ms

L1 Shear 22031 Pa

L1 Thickness 25 nm

P A G E 60 P A G E 60

Approach 1

Step 2: Model Layer B as Layer 2 [L2]

– Fix the modeled parameters for layer 1

P A G E 61 P A G E 61

Approach 1: Results step 2

• Limit the x-values to Layer B



L2 Shear 55020 Pa

L2 Thickness 51 nm

Note: total thickness =

25 nm [L1] + 51 nm [L2] = 76 nm

P A G E 62 P A G E 62

Approach 2: If Layer A is a rigid film

• Mark a data point before Layer B is added

P A G E 63 P A G E 63

Approach 2

• Model Layer B as [L1] and limit x-values to this part

P A G E 64 P A G E 64

Approach 2: Results

• Assumption: Layer A is perfectly rigid

• Advantage if you have 3 different layers to quantify

• If Layer A is not perfectly rigid it will affect the results of

Layer B



L1 Shear 43421 Pa

L1 Thickness 59 nm



L2 Shear 55020 Pa

L2 Thickness 51 nm

Approach 1

Layer B

Approach 2

Layer B

P A G E 65 P A G E 65

Approach 3: Model all data as one layer



L1 Shear 82964 Pa

L1 Thickness 56 nm

• Average density for both

layers

• Thickness includes both

layers

• Bad fit as layers are

different

P A G E 66 P A G E 66

Conclusion

• L1: QTools treats the multilayer film as one homogenous

film to give an average value for the viscoelastic

parameters

• L1 and L2: QTools tries to find a solution with two

regions having different properties

• Recommended: model step-by-step according to

Approach 1

P A G E 67 P A G E 67

FREQUENCY DEPENDENT

VISCOELASTICITY

the Extended viscoelastic model

P A G E 68 P A G E 68

A Viscoelastic material can have different properties

depending on what frequency it is measured.

Example: Silly Putty

At short times, it bounces

like an elastic solid

t < 1ms

f >1kHz

At long times, it flows like

a viscous material

t > 1s

f <1Hz

Rheological properties depend on frequency

P A G E 69 P A G E 69

www.wikipedia.com

Silly putty is a melt of entangled polymers

disentanglement

processes

segmental

relaxations

slow fast

Rheological properties of entangled polymers

P A G E 70 P A G E 70

normalized frequency (Hz)

G’a

nd

G

’’ (P

a)

P. Oswald. 2009. Rheophysics

G* = G' + iG''

G* – complex shear modulus G’ – storage modulus G’’ – loss modulus

G’ >> G’’ – predominantly elastic G’ ≈ G’’ – viscoelastic G’ << G’’ – predominantly viscous

Rheological properties of polymers

P A G E 71 P A G E 71

00 ffGG

V2 hfG

20

Shear elastic modulus:

00 ffGG 11

1

00V,V

hh ff

Shear loss modulus:

normalized frequency (Hz)

G’a

nd

G

’’ (P

a)

G = G' + jG''

’ and ” have different values in

different time zones

Frequency dependence of parameters

P A G E 72 P A G E 72

www.wikipedia.com

• Viscoelastic properties can depend on the frequency

at which they are measured

• Viscoelastic properties of polymers are intimately

related to molecular-scale relaxation processes

• The viscoelastic parameters (G’ and G’’) of such

materials will vary as a function of frequency

Summary

P A G E 73 P A G E 73

EXTENDED VISCOELASTIC

MODEL IN QTOOLS

Frequency dependent model

P A G E 74 P A G E 74

Extended viscoelastic model in QTools

Same as the viscoelastic model in QTools but with

frequency dependence of storage modulus (shear)

and viscosity

P A G E 75 P A G E 75

When to use the extended viscoelastic model in QTools

General criteria

• A laterally homogeneous and

evenly distributed film

• The bulk fluid is a Newtonian

fluid

• The adsorbed layer couples

perfectly to the sensor (no slip)

• The film is soft/viscoelastic

Additional reasons

• For films known to be

frequency dependent

• Can always be used

• When not finding a stable and

reasonable fit in the standard

model

Thickness will not be correctly modeled using the standard viscoelastic

model if the viscoelastic properties of the film are frequency dependent!

P A G E 76 P A G E 76

Extended viscoelastic model

P A G E 77 P A G E 77

Model settings – extended viscoelastic model

Frequency dependence

• Use the Voigt representation

• Include 1 layer only, to keep

the number of fit parameters

small

• Choose power-law frequency

dependence of viscosity and

shear

P A G E 78 P A G E 78

h

hh 00 ffnn

hfG 2

00 ffGG nn

Storage modulus (shear):

00 ffGG nn

Loss modulus:

Parameters settings – extended equations

11

20

1 h

P A G E 79 P A G E 79

Results

00 ffGG nn

h

hh 00 ffnn

P A G E 80 P A G E 80

Summary – Extended viscoelastic model in QTools

• The extended viscoelastic model can be used if

the general criteria for modeling are fulfilled

• The extended viscoelastic model should be used

if viscoelastic properties of the film are frequency

dependent

• The model takes into account frequency

dependence of storage modulus (shear) and

viscosity

P A G E 81 P A G E 81

LEARN MORE AT Q-SENSE WEBSITE

[email protected]

mailto:[email protected]



THANKS!

Dr Malin Edvardsson

[email protected]

+46 (0)708-738269

experimental planning & data analysis

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