Development of anticorrosive pigments by EIS and ACET. A ... of...CONCLUSIONS 1. A new methodology...
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J. Suay*, M.J. Gimeno, J. Gracenea, S. Chamorro, R.March, Esther Oro, Patricia Pérez Development of anticorrosive pigments by EIS and ACET. A general correlation model with NSS results. Protective Coatings, 12-13 Dusseldorf
Transcript of Development of anticorrosive pigments by EIS and ACET. A ... of...CONCLUSIONS 1. A new methodology...
J. Suay*, M.J. Gimeno, J. Gracenea, S. Chamorro, R.March, Esther Oro, Patricia Pérez
Development of anticorrosive pigments by EIS and ACET.
A general correlation model with NSS results.
Protective Coatings, 12-13 Dusseldorf
INTRODUCTION
THE EXPERIMENT
RESULTS
CONCLUSIONS
INTRODUCTION
THE EXPERIMENT
RESULTS
CONCLUSIONS
Pigment (Evolution) Hazard Anticorrosive Properties
2PbO·PbHPO3· 1/2H2O 3ZnCrO4·K2CrO4·Zn(OH)2·2H2O
*****
Zn3(PO4)2·4H2O
***
xZn3(PO4)2·yZnMoO4·zH2O
****
aM*. bP2O5 . cSiO2 . xH2O
****
CONVENTIONAL ACCELERATED TESTS
ASTM G154 ISO 4892-3
STATIC
ISO 20340 NORSOK 501
DYNAMIC
IMITATING THE NATURE
MIMETIZAR Imitar o reproducir la Naturaleza.
SEPARATING FACTORS
MIMETIZAR Imitar o reproducir la Naturaleza. INTENSIFICATING FACTORS
PREDICTING FAILURE
To correlate the data of ACET
with the salt fog spray data
To predict the anticorrosive behaviour
in 24h for developing
anticorrosive pigments much faster
INTRODUCTION
THE EXPERIMENT
RESULTS
CONCLUSIONS
16 FORMULATIONS
CPV: 3 , 4.5, 6 and 8% (acrylic matrix)
Thickness: 100 μm
Pigments N2, N106 and N302
PRODUCT FUNCTION SUPPLIER Weight range (%)
Water Solvent 9,71-9,33 Byk 154 Dispersing agent BYK-Chemie 0,5-0,56 Surfynol 104 E Wetting agent Air Products 0,15-0,16 Tioxide TR92 Titanium Dioxide Huntsman 7,50-7,63 ZnPh, N302, N106 Anticorrosive Pigment Nubiola Pigments 2,84-8,57 Plastorit Micro Mica/quartz/chlorite filler Rio Tinto Miin. 14,22 Byk 024 Antifoamer BYK-Chemie 0,07 Nubirox FR-10 Flash-rust inhibitor Nubiola Pigments 0,15-0,16 Letdown
Encor 2401 Styrene-acrylic dispersion Arkema 58,89-62,57 Texanol Coalescing agent Eastman 3,41-3,64 Acrysol RM2020 PU-thickener Dow Chemical 0,12-0,13 Byk 024 Antifoamer BYK-Chemie 0,32-0,34 Ammonia Neutralizing agent 0,12-0,13 TOTAL 100,00
5% NaCl pH= 7 Air pressure: 1.5Kg Temperature: 40ºC
SALT FOG SPRAY
CROSS CUT ADHESION (ASTM B3359)
ADHESION AT THE SCRIBE (ASTM D1654)
RUST AT THE SCRIBE (ASTM D1654)
RUST ON THE PANEL (ASTM B610)
(IV) EIS test (A.C.)
(III)
Relaxation time
AC
(IV)
DC
AC
(I)
(II) Polarization
0 40 80 120 160 240 200
Time (min)
Pot
entia
l (V
)
A sequence Stress/impedance is repeated several times.
(I) EIS test (A.C.)
(II) Stress: cathodic polarization
(III) Ionic relaxation
ACCELERATED CYCLIC ELECTROCHEMICAL TECH. (ACET)
Evolution of IMPEDANCE with ACET cycles
Evolution of RELAXATION POTENTIAL with ACET cycles
10-3 10-1 101 103 105102
104
106
108
1010
0
20
40
60
80
100
ciclo 0 ciclo 1 ciclo 2 ciclo 3 ciclo 4 ciclo 5 ciclo 6
|Z| Ω
Frequency (Hz)
Bode graphic
Pha
se θ
(•)
-2000 0 2000 4000 6000 8000 1000012000-4
-3
-2
-1
0
ciclo 1 ciclo 2 ciclo 3 ciclo 4 ciclo 5 ciclo 6
Relax graphic
ER
elax
atio
n(V
vs
Ag/
AgC
l)
Time (s)
ACCELERATED CYCLIC ELECTROCHEMICAL TECH. (ACET)
3 mm; t= 1400h
Frequency (Hz)
Bode graphic
10-2 10-1 100 101 102 103 104 105 103
104
105
106
107
108
|Z|
(Ω)
100
80
60
40
20
0
|Pha
se (º
)
Parameters Values
|Z|max(&) 5,22E+08
|Z|min(&) 8,74E+07
• Z* 11,44
Emax (V) -0,05
Emin (V) -0,23
• E (V) 0,17
ACCELERATED CYCLIC ELECTROCHEMICAL TECH. (ACET)
Bode graphic
10-2 10-1 100 101 102 103 104 105
Frequency (Hz)
103
104
105
106
107
108
|Z|
()Ω
102
101
100
80
60
40
20
0
|Pha
se (º
)
16 mm; t= 454h
Parameters Values
|Z|max(&) 9,55E+07
|Z|min(&) 1,04E+04
• Z* 46,48
Emax (V) -0,05
Emin (V) -0,30
• E (V) 0,26
ACCELERATED CYCLIC ELECTROCHEMICAL TECH. (ACET)
INTRODUCTION
THE EXPERIMENT
RESULTS
CONCLUSIONS
Pigmento REF. N2 N2 N2 N2 N106 N106 N106 N106 N106 N302 N302 N302 N302
CPV (%) 0 3 4,5 6 8 3 4,5 6 6 8 3 4,5 6 8
Rust scribe (mm) 7,3 2,8 2,5 1,7 1,8 2,0 1,1 1,8 2,0 2,3 1,7 1,2 0,8 1,1 Rusted area (%) 100 5,3 5,3 2,3 4,0 0,2 0,0 0,1 0,0 0,0 0,2 0,0 0,1 0,0 Adhesion scribe 5 0,1 0,4 0,0 0,2 0,2 0,0 0,0 0,0 0,0 0,0 0,0 0,0 0,3
Cross cut Adh. (%) 55 5,3 0,0 0,0 1,7 0,0 0,0 0,0 0,0 0,0 0,0 0,0 0,0 0,0
Oxidation ranking 2 5 6 6 6 7 9 8 8 8 7 9 8 9 Global ranking 2 6 6 7 7 8 9 9 9 9 8 9 9 9
Oxidation ranking
Global ranking
N302 ≅ N106 > N2 >>> REF
N302 ≅ N106 > N2 >>> REF
SALT FOG SPRAY TEST RESULTS
Pigment REF. N2 N2 N2 N2 N106 N106 N106 N106 N106 N302 N302 N302 N302
CPV (%) 0 3 4,5 6 8 3 4,5 6 6 8 3 4,5 6 8 |Z|max(&) 1 E08 1E08 1E07 1E08 9E07 1E08 7E07 8E07 2E08 5E08 1E08 8E07 1E08 7E07 |Z|min(&) 1E04 3E04 5E03 2E04 1E04 9E04 4E05 2E06 2E06 5E07 9E07 2E07 3E07 6E07
Emax (V) 0,25 0,24 0,18 0,17 0,11 0,23 0,19 0,20 0,20 0,06 0,20 0,16 0,21 0,19
Emin (V) -0,16 0,03 -0,13 0,02 -0,02 0,12 -0,08 -0,02 0,18 -0,10 -0,33 -0,37 -0,35 -0,32
Rank: f[|Z|max(Ω), |Z|min(Ω), Emax (V), Emin (V)]
ACET RESULTS
ELECTROCHEMICAL MODELS????
USING THIS METHODOLOGY IN INDUSTRY
Nucleus
Cell body
Dentrites
Axon
Función de ponderación
ARTIFICIAL NEURAL NETWORKS (ANN)
ANN PARAMETERS
Net nature Multilayer (3): input, hidden and output layers Conections Feedforward
Activation function Función sigmoidal Learning Supervised
Input dimension 4 nodes Output signals log |Zmax; log |Zmin|; Emax; Emin
Parameters of the net 10 Neurones hidden layer 2
Experiments 6 Validation experiments 1
Output dimension 1 node Input signals Rust scribe (mm); rusted area (%); adhesion
scribe; cross cut adhesion (%); oxidation ranking; adhesion ranking; global ranking
ANN PARAMETERS
0
1
2
3
4
5
6
7
8
9
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
Rust
scrib
e (m
m)
Samples
SALT FOG SPRAY RNA VALIDATION
RUST SCRIBE (mm)
-20
0
20
40
60
80
100
120
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
Rust
ed a
rea
(%)
Samples
SALT FOG SPRAY RNA VALIDATION
RUSTED AREA (%)
-10
0
10
20
30
40
50
60
70
80
90
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
%af
fect
ed a
rea
CC
Samples
%superf.desadherida CC RNA (N.E)
Experimental RNA
Experimental RNA
ADHESION CROSS CUT (%)
SALT FOG SPRAY RNA VALIDATION
-1
0
1
2
3
4
5
6
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
Adhe
sion
scrib
e (%
)
Samples
ADHESION SCRIBE (%)
SALT FOG SPRAY RNA VALIDATION
0
1
2
3
4
5
6
7
8
9
10
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
Rust
ing
Rank
ing
Samples
SALT FOG SPRAY RNA VALIDATION
RUSTING RANKING (%)
0
1
2
3
4
5
6
7
8
9
10
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
Glo
bal R
anki
ng
Samples
SALT FOG SPRAY RNA VALIDATION
GLOBAL RANKING (%)
Pigment N106 6% NSS ACET
RUST IN THE SCRIBE
ASTM D 1654-91 (A)
mm rust at scribe 4 4
Classification 5 5
RUST ON THE PANEL
ASTM D 610-68
% rusting area 0 0
Classification 10 10
ADHESION SCRIBE
ASTM D 1654-91 (B)
% affected area 30 30
Classification 4 4
ADH. "CROSS CUT“
ASTM D 1654-91 (B)
ASTM B-3359 2B --- % affected area 5 15
Classification 7 5
INTRODUCTION
THE EXPERIMENT
RESULTS
CONCLUSIONS
CONCLUSIONS 1. A new methodology based on ACET and ANN has been proposed
to develop new pigments using coating as vehicles.
2. ACET is able to assess the anticorrosive properties of pigments.
3. This methodology is automated and needs short time and little effort to be applied.
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