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Produced by the NASA Center for Aerospace Information (CASI)
(11151-C&-175625) STUEY Os THI IFFSCT'S CF N85-226E1

IMINTITICY ON :EE HIGd Fe- Ni-Cr 1NJ

Vi-Cr-11 ALLOYS Final Report )Georgia Inst.

of Tech.; 3b p HC 103/11F !01 CSCL 11F unclas

G3/26 14745

FINAL REPORT

STUDY OF THE EFFECTS OF IMPLANTATION ON THE HIGH TEMPERATURE

CORROSION AND HYDROGEN PERMEABILITY OF Fe-Ni-Cr AND Ni-Cr-A1 ALLOYS

Under Grant No. NAG3-255

M.W. Ribarsky

Principal Investigator

School of Physics

Georgia Institute of Technology

April 12, 1985

I ^

^C^bl LL ^`,^`4

i
TABLE OF CONTENTS

Abst ract ........................................ii

Introduction .....................................1

Interactions, Talks and Papers ...................3

Models of Segregation in Binary

and Ternary Alloys ..............4

Surface Layering Effect and Long- and

Short-Range Ordering ........... 11

Calculations of Surface and Grain

Boundary Composition ........... 15

Diffusion of Implant Profiles ...................19

Size and Heat of Formation Data .................21 

Implantation Studies on Ni Alloys ...............23

Cluster Calculations of Grain

Boundary Structure .............28

Accomplishments.... .............................30

Reference .......................................31

Appendix ........................................32

i
Abatract

A theoretical study of the effects of implantation on the corrosion resistance

of Fe-Ni-Cr and Ni-Cr-A1 alloys was undertaken. The purpose was to elucidate the

process by which corrosion scales form on alloy surfaces. Since the corrosion

process is complicated with different mechanisms of scale formations for different

materials and with different implants producing varying effects, the theoretical

work was carried out in conjunction with experimental analysis. The experiments

dealt with Ni implanted with Al, exposed to S at high temperatures, and then

analyzed using scanning electron microscopy, scanning Auger spectroscopy and X-ray

flourescence spectroscopy. A variety of theoretical approaches were used. Pair

bonding and tight-binding models were developed to study the compositions of the

alloys, and as a result, a new surface ordering effect was found which may exist in

certain real alloys. With these models, the behavior of alloy constituents in the

presence of surface concentrations of 0 or S was als^ studied. Improvements of the

models to take into account the important effects of long- and short-range ordering

were considered. The diffusion kinetics of implant profiles at various temperatures

w:re investigated, and it was found that significant non-equilibrium charges in the

profiles can take place which may affect the implants' performance in the presence 

of surface contaminants. Finally, another approach was considered in which molecular

cluster calculations would be used to simulate the effect of impurity atoms on

the electronic structure at grain boundaries.

ii
I. Introduction

The problem of corrosion of iron and nickel based alloys has been studied

extensively. The most successful studies are those which have used a combination

of techniques such as scanning electron microscopy, Auger analysis, x-ray diffraction

and emission, sputter profiling, marker experiments and other techniques to provide

information about the structure, composition and morphology of the scales formed,

and about the diffusion rates and paths of the constituents. Only with combinations

of techniques such as these can one reach d.-finite conclusions about the complicated

corrosion processes which occur especially in alloys with more than two cos;ponents

or with impurities. Unfortunately, there has not been much basic theoretical

analysis in conjunction with most of these experimental results. Such an analysis is

necessary if one is to understand the basis of the competing corrosion mechanisms

and the process by which the ions arrive to form the scale, and especially if one

is to predict the effect of various additions to the alloy. The purpose of this

work was to provide some of this theorecical analysis.

Resistance to metallic corrosion can also be improved by ion implantation.

Among the qualities of ion implantation is that relatively small amounts of scarce

or expensive elements can be implanted and can provide materials behavior quite

similar to that of bulk alloys. The elements can be implanted in controlled amounts 

and distributions and at non-equilibrium concentrations far greater than in the

alloying process so that new materials may be formed. However, due to the nature of

the implantation process, one must be aware of possible differences in diffusion

rates or structure caused by radiation damage or non-equilibr-Lun; concentrations. For

example, Fe-Ni-Cr-Al alloys have been formed by implanting Ni, Cr and Al in Fe ar.d

these provide corrosion resistance similar to the bulk alloys. However, sputter

profiling with proton-induced x-rays showed a diffusion rate of Al in Fe at 3000C

which was 9 orders of magnitude greater thin the volume diffusion rate! The difference

may have been due to radiation-enhanced 'iffusion, but tt,cre was not much difference

-1-
between the bulk and implanted diffusion rates in the Cr and Ni implanted alloys.

The nature of the oxide or other scale formed on the implanted material can also

be significantly different than on the unimplanted material and quite dependent on

the implanted species. All this makes a careful analysis of the corrosion process

for each implanted material highly useful, especially since th(.re have been few

such studies.

It is well known that alloys of iron or nickel with 20 wt% or more chromium

form continuous Cr 20 3 scales when oxidized. In Ni-Cror Fe-Ni-Cr alloys, the Cr203

scales pr,)vide good resistance to further high temperature oxidation when they

are adherent, but they are permeable to sulfur and sulfur-bearing species Ghich lead

to base metal corrosion. :additions of certain elements, sometimes in small amounts,

can greatly improve the resistance of the oxide to corrosion or sulfidation or can

increase the adherence and stability of the scale. Ion implantation can be of great

use in.adding these elements to the surface region without changing the bu3k

properties.

The addition of several percent Al to the Fe-Cr and Ni-Cr alloys forms a

surface oxide mainly consisting of Al 2 0 3' The Al 2 0 3 scale provides greater protection

than the Cr 2 0 3 scale but spalls at high temperatures. Relatively minor additions

of rare earths such as Ce or transition metals such as Y or Sc greatly improve the

oxidation resistance of the Al-doped alloys. Voids form in the undoped Fe alloys

which are connected with the Al 20 3 scale which grows at the grain boundaries.

Additions of Ce migrate to the grain boundaries and prevent void formation by capturing

vacancies. 2 The result is a significant improvement in oxide adherence. The

mechanism of void formation is similar for Ni-Cr-A1 alloys.3

-2-
II. Interactions, Talks and Papers

During the course of this research, there have been several interactions and

communications with researchers and also talks given and papers presented.

Abstracts for the main papers are in the Appendix.

The main interactions have been with:

- Dr. Keith Legg of the School of Physics at Georgia Tech concerning the

implanting and analysis of Ni alloys,

- Dr. Susan Schuon at NASA-Lewis concerning the results of the calculations

and analyses,

- Dr. Susan Benford of NASA-Lewis concerning the nature and scope of this

research program.

Talks presented on this work include the following colloquia:

- "Effects of Implantation on the Corrosion Properties of Iron and Nickel

Alloys," presented at NASA-Lewis in August, 1982;

- "Surface and Grain Boundary Segregation in Alloys," presented at the School

of Physics, Georgia Tech in November, 1982.

The following papers have been produced on this work:

- "Surface Segregation in Ternary Alloys," 42nd Physical Electronics Conference,

Atlanta, Georgia (1982);

- "The Diffusion of Implanted Ions Near Surface and Grain Boundaries," Bull.

Amer. Phys. Soc. 29, 389 (1983).

The following article is in preparation:

- "Effects of Temperature and Surface Contamination on the Diffusion of

Implanted Ions."

-3-
III. Models of Segregation in Binary and Ternary Alloys

We have made considerable progress in extending segregation models to

ternary systems. The e_.tension involves minimizing the ' free energy.

F(4, Xi, ... X2, X2....) with respect to concentrations of each species in

the first, second, etc... crystal layers parallel to the surface. Under the

constraint that the total number of atoms of each species remains fixed, the

minimization condition is

aF s aF i - 1, 2, 3. ... (1)

axia aXBa

a - A, B, C, ...

where Xi is the concentration of species a in the i'th layer and X aa is the bulk

concentration.

We are using two models in evaluating Eq. (1); a tight-binding method and a

pair-bonding method. 

4,5 

In the latter method, one assumes that only the nearest

neighbor interactions contribute and derives bond enthalpies H

1.. 

for identical

P

atoms from the heats of vaporization of the pure elements. One then uses heat of

mixing data or interaction calculations to derive the bond enthalpy HAB between

different atoms. For a random binary system the resulting interna l energy

contribution from atoms in the first layer is

Ull -ZR [ 2 Xi H^ X

1 

(1-X

1

11 + 2 (1-X1 ) 2 HBB ]

AB (2)

where Z is the number of nearest neighbors for that layer. Similar equations

held for 

U12' U

22' U23 and so on and for the general case of multicomponint

systems.

A. Surface Segregation in the Pair-Bonding model

We have studied the general behavior of the pair-bonding; model as the

-4-
model parameters are varied and have added effects such as short-range order

and elastic mismatch energies for the case when different size components are

present. In most cases we find that short-range order effects are fairly

small and that the major contribution due to size mismatch is already contained

in the heat of mixing term. We also find that, in general,raising the temperature lowers segregation and that cne should use surface energies of the components rather than heats of vaporization to calculate the internal energy of

the surface layer. Lastly we find a striking dependence on the size and sign

of the heat of mixing which we will discuss below.

Our pair-bonding calculations for the (111) surface layer concentration

of Cu-Ni are shown in Fig. 1. We chose Cu-Ni as a test system because it has

been extensively studied experimentally and theoretically. As can be seen, the

calculations are in good agreement with the experimental data ? and show the

correct temperature dependence.

B. Segregation and electronic structure in the tight-binding model

In contrast to the pair-bonding model, the tight-binding model provides a

description of the electronic structure at the surface in terms of microscopic

quantities such as the band centers and band widths of the pure metals and the

interactions between sites as the alloy is formed. The equations are more 

complicated than in the pair-bonding model and more time-consuming to evaluate

because one must calculate densities of states at a range of energies for each

set of layer configurations and then numerically integrate over energy to

obtain the total free energy. This process must be followed to find each layer

concentration by solving Eq. (1), and then ti-:e whole procedure must be repeated

until the zoncentrations do not change from one iteration to the next. In spite

of the effort necessary, the method yields microscopic information which can be

quite valuable in evaluating the chemistry of a surface or grain boundary and in

-5-
i i ri.r. t A 

0.5 1 1 .

0.0 0.2 0.4 0.6 0.8

XB (CU)

Fig. 1 Comparison of the calculated Cu-Ni concentration , at the (III) surface

with Low Energy Ion Scattering results (Ref. 4).

-6-

1.0

1.0

0.9

08

0.7

0.6

^I
Ihe

studying the effects of impurities or defects.

Our results for the the Cu-Ni binary system are shown in Fig. 2. These

results are at 6000 K so that the surface segregation of Cu should be somewhat

less than the experimental results in Fig. 1. However, the experiments ? show

no tendency to cross over the zero segregation line between 60 and 70 at y Cu

j as the results in Fig. 2 do. Recent calculations $ indicate t1::t the additional

r

constraint

aF aF

a<ni > 8<n b> (3)

when required with Eq. (1) brings the Cu-Ni tight-binding results into excellent

agreement with experiment. Here <ni > is the average electron number on an atom 

in she i'th laver so that Eq. (3) is the requirement that the number cf electrons

remains fixed.

There has been a good deal of work 

9-11 

in recent years directed toward

understanding the roles of d, s and p valence electrons in the bonding of

transition metal alloys and in contributing to the allay cohesive energies and

heats of formation.. Relativel y simple models have been consr.ructed 10-11

 wh±.ch

show that accurate heats of formation can be obtained using rectangular d-sand

densities of states having the band positions and widths appropriate to the

pure metals except for some straightforward modifications due to alloying. Calculations with these models show that the d-bands make the most significant contribution to the heats of formation for transition metals. Since the heats of

formation are directly related to the pair bonds in the pair bonding model, this

method provides a direct way of evaluating the contributions of electronic structure to the pair bonds. Also the simple modelling of the d-bandG in terms of

position and width is just the information needed to define the parameters in the

tight-binding model. We thus have a method to directly connect the results of

the tight-binding and pair-bonding models.

-7-
0.8 i

U)

x

0.6

0.4

1.0

0.2

0.0 x-- I T

0.0 0.2 0.4 0.6 0.8 1.0

XD (CUB

Fig.2 Tight-binding calculation of Cu-Ni surface concentration At T-6000K.

-8-
C. Grain boundary segregation

The composition and strucrure of grain boundaries greatly affect the

strength, oxidation rates and adherence of oxides ir. polycrystalline materials.

In alloys the addition of small amounts of certain metals to the base metal

can greatly affect the segregation of trace impurities to the grain boundary

and thus change significantly the properties of t':e system. For example, when

Ni is a6,:ad to Fe, the grain boundary segregation of impurities such as Sn or

Sb can be increased by a factor of 15 or 20. The resulting alloy undergoes

tem,, er erbrittlement and all fractures occur along the grain boundary.

The pair-bonding model is quite s,iccessful in explaining this enhancing

t1 effect. If one defines the parameter a' as follows,

a. 'MhI - 'M-Fe - 'I-Fe (4)

where aM- I is the interaction strength of the added metal and the trace impurity, then for a'>0 the pair-bonding model predicts that the boundary segregation of I w-11 be enhanced by the presence of M 12 . We have found the inter-

' actions a

M-I, 

a 

M-Fe I-Fe

and a using experimental heat of solution data, and our

results are shown in Table I for the effect of Cr, Ni, V, Mn and Co on Sn and Sb.

In every case the predicted

.

 enhancement is seen experimentally. When a'<0 the

model shows depletion of I at the boundary, so that we can also predict which 

elements will have the opposite effect.

-9-
a` VALUES FOR Fe-M-I SYSTEMS

-10-

1 r•-

J i •..ice }

M

I

M Sn Sb

Ni 4.6 (+) 3.i (+)

Cr .35+) 1.3 (+)

Mn 6.1 (+) 7.5 (+)

V 4.0 (+j 6.3 '^)

Co I 3.3 (+)

Table I Comparison of a' values with experimental determinations of grain

bounda.y enhancement. The (+) indicates that the M component

enhances the segregation of the I component.
IV. Surface Layering Effect and Long- and Short-Range Ordering

Usually the solutions to Eq. (1) return to the bulk concentrations by the

fourth or fifth layer. However, in certain cases a remarkable surface layering

effect shows up. For example, the layer concentrations for the first 8 layers of

Fe (61 at 7.) - Ni (19 at %) - Y are shown in Fig. 3. The Y does not segregate

to the surface layer but segregates strongly to the second layer. However, the

first, third, fifth layers and so on are almost entirely Ni while the alternate

layers are almost entirely Y. This effect persists much deeper into the bulk

than is usually the case. Evidently, the layering effect is related to the large

attraction between Y and Ni reflected ir. their large hea,. of mixing. The energy

is favorable for Ni segregation in the surface layer, but the large attractive

interaction causes Y to segregate in the second layer and so on.

Other effects may impair this surface layering effect. In the Fe-Ni-Y system,

Y has a much larger volume than Fe or Ni. Thus Y would want to segregate to

the surfa--e to reduce lattice strain and therefore the surface layering effect would

be diminished. In principle one could diminish this effect by choosing elements

which strongly attract but are of similar sizes. However, there are also other

ordering effects which could significantly alter the segregation pattern, and we

will discuss these next.

The surface layering effect is a type of ordering phenomenon. To get a complete

picture, one must also add the effects of bulk and surface short- and long-range

ordering. For systems with large heats of mixing between two components, such as

is the case for the surface layering effect, some type of long- or short-range

ordering becomes more likely. We can introduce ordering by considering a lattice

with a and $ sublattices. For a BCC crystal, the a sublattice might be the corners

and the 6 sublattice the body-centered sites. For an FCC crystal, the a sublattice

might `F. the face centered sites and 6 sublattice might be the corners. These types

-11-

r 
Y

NI

I.0 2.0 3.0 4.0 5.0 6.0 7.0

LAYER

1.0

0.8

CO. 6

z

0

U

0.2

0.0

V-V

Fig. 3 Concentration of Y and Ni in the first eight layers at T=298 

0 

K.

-12-

zx,
of ordering have been seen for several AB-type alloy:, in the BCC case and A3B-type

alloys in the FCC case.

We may consider a simple nearest-neighbor-only pair-wise interaction model for

our alloy. For a binary system in the bulk, the short- and long-range order

parameters are defined in terms of the pair probability PIB which is the probability

of finding an IJ bond with the I atom in the a sublattice and the J atom in the s

sublattice. the pair probabilities are normalized by

PAA + PAB + PBA + PBB = 1 ( 3)

The long-range order (LRO) parameter is

ns as

_ P

AB - P BA (4)

so that if A is completely ordered on sublattice a and B on sublattice s or vice-versa,

then n = ±1. On the other hand, if A and B are random, then PAB = PBB and n = 0. We

define the short-range order (SRO) parameter as

a = 1 - [(PC' + PBA) /2x(1 - x) ] . (5)

Since for a random system PAB = x(1 - x), a = 0. Now the SRO would be in the

form of clustering. In the most ordered state all nearest-neighbors would be alike

except at the boundaries PAB = PBA = 0 so that a = 1.

The main difference due to ordering in the expression for the free energy

introduced in Eq. 1 is in the entropy term. In the pair approximation, 13 the entropy

is

S = KN(1/2(Z - 1) I F v PI n PI - 1/2 Z E PIS In PIS (6)

IJ

where PI is the site probability that atom I is in the v sublattice. Here N is the

total number of sites in the c--vstal and Z is the number of nearest-neighburb. Vlp

-13-

J
equilibrium values n and a , for a given concentration x, are obtained by minimizing

the free energy F

D

0 2n o (7)

With Eq. (3-7) one can find a and n in terms of x. Similar equations exist for the

surface exce p t that n and a will depend on she surface layer. Also, we can generalize

to ternary ABC systems by defining n and a for AB, AC and BC pairings. Calculations

show that LRO effects due to large heats of mixing diminish surface segregation effects. l4

Thus the surface layering effect would be diminished. On the other hand, strong

surface segregation also diminishes LRO. Further calculations are necessary to

see whether LRO or surface layering wins out.

-14-
V. Calculations of Surface and Grain Boundary Composition

The surface or grain boundary is often where the action is in corrosion and

embrittling processes. Impurity ions may diffuse mainly along the surface or

grain boundary o ► may segregate significantly to these boundaries. Certain

impurities, such as S or P, may segregate strongly to t'ae grain boundary under

certain conditions and cause intergranular failure. Other impurities, such as

Ce or Y, enhance scale adhesion after segregating to grain boundaries. Of

course the scale formations process itself begins in the boundary region and

the kinetics of ion diffusion across the boundary determine the structure of the

scale as, for example, when inner and outer oxides form due to different diffusion

rates of alloy constituents.

In this section we will show that the basic theory can give quite useful

qualitative and even quantitative results for the compositions of alloy surfaces

and grain boundaries. Thus one can obtain a lot of information about alloy

behavior just by comparing the appropriate parameters for different constituents.

We will use the basic pair-bonding theory as outlined briefly in Sec. II, but we

will ignore the effects of long- and short-range order. The structure of the pairbonding equations for the grain boundary is nearly the same as for the surface,

although grain boundary energies must replace surface energies, and site

competition may not be as important at the grain boundary due to lattice

distortion.

The effect of oxygen at an alloy surface can be significant. As shown in

Figs. 4 a and 4b for Ni-Cr-A1 alloys of varying compositions, Ni segregates

strongly to Elie clean surface. However when an oxygen mono-layer is added, the

Cr is pulled to this surface. The result that the surface concentration of Cr

in Fig. 4b is 50% at about 20 at % bulk Cr is in agreement with experiments

-15-

r_ V
-16-

0.8

7

O

E,

Q

0.6

W

Uz0U

U 0.4

Q

0.0

0.1

0.2

1.0

Fig. 4a

0.2 0.3 0.4 0.5 0.6 0.7 0.3 

BULK CONCENTRATION (NI) 

Ni and Cr surface concentrations for clean Ni-Cr-Fe. The

Ni strongly segregates.

1.0

0.2

0.8

z0

Ea

a

F- 0.6 Z

W

U

z

O

U

U 0.4

a

o:

0.0 -- ---L-- -i

0.05 0.10 0.15 0.20 0 25 030

BULK CONCENTRATION (CR)

Fig. 4b The dependence of Cr surface concentration on bulk

concentration when an oxygen monolayer is added. Note

that the surface concentration is 50% at about 20% bulk Cr.
which sh^w a Cr-rich oxide appearing at about 20 at % bulk Cr. If we have an

Ni-Cr-A1 alloy plus oxygen, on the other hand, the situation is quite different

and Al segregates strongly as shown in Fig. 5. This result is in agreement

with experiments which show that surface oxides on Fe-Cr-A1 alloys with more

than 4 at % Al are mostly alumina. The qualitative behavior of segregation with

oxygen adsorption is predicted using oxide heat of formation data to estimate

the oxygen-metal bond strength. Thus Al is attracted to 0 more strongly than

either Cr or Ni, and the rare earths are attracted even more strongly still.

This last result is consistent with the observation of Ce and 0 at grain boundaries

during the initial stages of oxidation in Fe-Cr-A1 alloys. 15

We

W ;

-17-
1.0

0.8

z

0

Hd

Q^

Z 0.6

WUz

o.U

0.4

d

04

NI(.7)-CR-AL

T=298 K

(100)

0.2

0.01

0.0 0.3

' BULK CONCENTRATION (AL)

Fig. S Al concentration in a Ni(.7)-Cr-Al alloy with a half monolayer i

1 of 0 on the surface. The slope discontinuities are due to a sparse

1 number of points.

-18-

U
VI. Diffusion of Implant Profiles

The time-dependence of the concentration for a binary system in the

diffusion approximation can be found by considering the equation 16

aCt ^ a 2 C b

at ax 

(8)

subject to the boundary conditions

dc 1

s = D ac - ES Cs - D 

/2 

e b C(x = 0) b (9)

dt

a 

x=0

and

1/2

Cs = Da

Cb(x = 0) (10)

i

where Cs (t) is the surface concentration of the solute per unit depth, Cb(x,t)

is the bulk concentration, D(T) is the temperature-dependent bulk diffusion

coefficient, and E s and 

6 

are evaporation rates from surface and adjacent bulk

layers respectively. The coefficient a is the surface depletion factor -.,ld is

i

proportional to exp(-H

seg seg

) where H is the heat of segregation. Thus

adsorbed species which increase H seg will result in higher surface concentra

tions of the solute, that is, greater diffusion to the surface.

The diffusion approximation in Eq. (8-10) has been applied with success to

systems where the bulk concentration was assumed fixed initially at a constant

value. 

16 

We have now generalized the model to an implant profile which would have

a depth dependent initial distribution. 17 Our results show that the implant tends

to accumulate at the surface if the diffusion coefficient is large enough. This

happens regardless of the size of a . For larger a , the implant leaves the surface

more quickly, but the largest surface concentration is nearly the samE. ?hus implants

-19-
-20-

close enough to the surface or in materials with large enough diffusion co•::icients

will have significant surface concentrations before equilibrium is reached, even

if there is no segregation of the implant at equilibrium.
VII. Size and Heat of Formation Data

Since we have seen that size and heat of formation data are quite useful in

determining the constitution and corrosion properties of alloys, we have compiled

some of these date for rare earths in Table II. We calculated surface energies from

cohesive energy -ata since there are few measurements in the literature, and we

calculated heats of formation for Al and Ni compounds using the Miedema model.

We see that there is quite a difference in surface energies so that one would expect

Yb, for example, to segregate to surfaces or grain boundaries much more strongly

than Ce. However, the much larger volumes of all rare earths with respect to, say,

the molar volume of Ni at 6.5cm3. tends to drive all rare earth impurities to the

surface in this solvent. This effect would again be stronger in Yb than in Ce. The

heats of formation of Dy, Ho and Er with Ni indicate compounds are probably formed

whereas Eu does not form Ni compounds. Also, the rare earths in general tend to order

and form compounds more strongly with Al than with Ni.

-21-
Table II. Thermodynamic data for rare earth metals. The surface energies are at

00 K and the heats of formation at room temperature. All energies are in kcal/mole.

M Molar Volume (cm 3 ) Surface Energy Heats of Formation

RNi RA1

Ce 21. 27.5 -7.4 -20.

aPr 21. 22.3 -7.4 -20.

Nd 21.4 19.3 -8.5 -20.

Pm 20.1 -9.3 -21.

Sm 20.1 12.2 -9.3 -21.

Eu 28.8 10.4 +8. -12.

Gd 19.7 23.9 -10. -21.

Tb 19.3 23.5 -10. -21.

Dy 18.9 17.8 -11. -21.

Ho 18.9 17.5 -11. -21.

Er 18.5 19.3 -11. -21.

Tm 18.1 14.8 -11. -21. 

aYb 24.8 9.0 -.3 -16.

Lu 17.7 27.7 -11. -21. 

-22-

9 0 ' ►.+^
VII. Implantation Studies on Ni Alloys

We have initiated a series of implantation studes on Ni.-based alloys. The

implantations and Auger Analysis were performed by Dr. Keith Legg in the Sch^o1 of

Physics. Our first studies were to investigate the effect of implanted Al on the

high temperature sulfidation of Ni. The polycrystalline Ni samples were annealed

at 750°C for an hour to obtain equi-axed grains and to get rid of dislocations and then

were polished down to 1 micron. The implant beam had a primary energy of 100 Kev

O

which created an Al distribution that ranged from the surface to about 1000 A with a

0 0

peak at 600 A and a full width at half maximum of 500 A. The implant dosage was

2.3 10 17 atoms/cm2 which amounts to an Al concentration of about 40 :.t% in the

implant region. Two samples, one unimplanted (sample A) and one implanted (sample B),

were heated in a S ambient at a pressure of about 1 atmosphere at 850°C for 1 hour.

The samples were analysed with scanning electron microscopy (SEM) and x-ray

flourescence spectroscopy (EDAX). The SEM photographs are shown in Figs. 6-7. We

see that both samples have grains of similar size. The appearance of the surfaces,

however, is quite different. Sample A in Fig.6 is flat while sample B in Fig.7 is

rumpled as if the grains had grown out. Surprisingly, EDAX shows little difference

between the two samples and finds no Al in either case. Analysis of the EDAX spectrum

for sample A gives a S concentration of 14 at% at the grain boundary while sample B

has 13 atl at the boundary. Since the EDAX signals for S on the grain surface are a

good deal smaller, most of the S resides in the grain boundaries with a slightly

smaller concentration in sample B.

We next analyzed the samples with a surface sensitive technique, scanning Auger

Electron Spectroscopy (SAES). Since EDAX has a range of a few microns, it may not see

an Al profile of a few percent concentration in the surface region. However, SAES

sees no Al either on the grains or at the beundar •:es in sample B, even though calculations

indicate Al should segregate to the surface. The resolution of the spectra indicates

-23-
b. High mag. showing grain

boundary features in arrowed

region of a.

ORIGWAL P^.ice.

OF POOR QUAUT%

Fi3. 6 Unimplanted Ni after

su. 'ding.

a. Low m •-'lowing general

grain structure.

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"It:21 f^

^•^.v^Ef

Fig. 7 A1-implanted Ni after

sulfiding.

b. Nigh mag. showing grain

boundary features in arrowed

region of a.

P

•`

, 1

-25-

ORIGMiAL P,^ GE ,

OF POOR QUALITY

Z-14 It

a. Low mag. showing general

grain structure.
an Al surface concentration of <5% of a monolayer. In agreement with EDAX, the

SAES shows a smaller S concentration on the surface and a larger concentration at

Cie grain boun "'cries. To examine the S depth profile and to see if Al resided

O

under the surface, we next sputtered away about 200 A of sample B with an Ar beam.

Again the SAES showed <5% monolayer of Al, but it also showed removal of S from

the grains. A SAES micrograph set for the S peak at 150 eV is shown in Fig.8 . One

can clearly see grains of about 60 microi:s across which are outlined by thick S

regions up to 30 microns. However, the SAES shows thicker boundary regions

than SEM which indicates that the S profile along the grain boundary must thin

out deeper into the sample.

Evidently the Al implant diffuses into the solid at higher temperatures. The

addition of 0 at the surface, to which Al bonds strongly, before raising the

temperature may hold the Al in the surface region. The S reduction in sample B

indicates that if the Al remains in the surface region, the sulfidation resistance

may be improved.

Other implants which would tend to migrate to the surface rather than into the

bulk at high temperatures might affect the sulfidation rate. Among the possibilities

are Y, Dy or Ce. These are mLzh larger atoms than the Ni substraLe and thus would

find it energetically favorable to reside at the surface where they could release

some of their strain energy. They also bond more strongly to S or 0 than does Ni so

that they would change the chemical nature of the scale. Small amounts of Ce have

been shown to increase the adherence of high temperature oxides in Fe-Cr-Al alloys, 15

In fact, a study of the annealing behavior of Ni implanted with Dy ions at a dose of

10 16 /cm 2 shows that with heating up to 800°C the implant has migrated to the surface

19

to form a Dy 2 0 3 layer.

-26-

7
M.

ORIGWAL PAt3e

Oh POOR QUA-ITY

Fig.8 Scanning Auger micrograph of sulfur-rich regions at grain

boundaries of A1-implanted Ni. Magnification is 160x.

-27-

f

I

t

1
IX. Clust:tr Calculations of Grain Boundary Structure

' Even if we can successfully predict the grain boundary concentration, this

knowledge tells us little about the effect of an impurity on the boundary strength

and adhesion. To address this question we undertook a series of calculations of

the microscopic structure :,f S at Fe grain boundaries. We chose S because of the

importance in this work of understanding the effect of S on boundary strength

and the adhesion of oxides. We used a molecular cluster model based on the X-alpha

approximation to the exchange interaction 20.

To describe the arrangement of atoms at the boundary, we chose a model in

which the packing of atoms in metals can be described as the close packing of hard

epheres. This is a good approximation for metals. It can be shown 

21 

that all

spacings at the grain boun dart' in this model for an f.c.c. solid can be built up

from combinations of only eight polyhedra called Bernal polyhedra. We chose the

1

8 vertex polyhedron because it has atoms from both the first and second layers in

I the boundary region. The structure of the 8 vertex polyhedron is shown in Fig. 9.

The atoms at 1,2,3 and ^i are equivalent and describe the two boundary surfaces

I

(atoms 1 and 4 are in one surface, and 2 and 3 are in the other). The atoms 5,6 or

and 8 are in the second laver. The procedure entails calculating the self-consistent

electronic structure for Fe and Fe 8 S and then comparing the results. The S is the

center of the polyhedron in the second calculation. Similar calculations have been

reported for Ni 8 and Ni 8 S `2 . In that case the S was shown to take bonding electrons

away from the Ni-Ni bond's resulting in the decrease of bond strength between the first

and second layer Ni.

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I 9

9 3

S F,

2

3

FRONT VI EIV SIDE VI PV

1 `

TURAGONAI. DUDI:C:AHEMON D2d Sl'( mil-'ri-ky

Fig.9 Eight vertex Bernal polyhedron for representing an FCC grain boundary.

-29-
X. Accomplishments

In the course of this research project, we have established several methods

to analyze and predict the composition and behavior of alloys in corrosive environments.

We have begun investigations of particular implanted alloys exposed to sulfur at

high temperatures and are developing novel methods to look at the alloy behavior.

Among our accomplishments are:

- Applicatiou of useful models, such as the pair-bonding model, to alloys of

interest, such as Ni-Cr-Al.

- Investigation of new effects, such as the surface ordering effect, W'J ch

may greatly affect the properties of certain materials.

- Cotrelation of empirical parameters, such as surface energies, heats of

solution or volume differences, with the expected behavior of alloy

constituents either with or without the presence of 0 or S. With our

models we can use these parameters to get quantitative results for alloy

constitutions.

- Improvements of the models to take into account the important effects of

long- and short-range ordering and. of the kinetics of implant profile

changes. This latter effect has not been handled before in a way which

takes into account both surface segregation and bulk diffusion effects.

- Investigations of Ni implanted with Al and then exposed to S at high temperature.

This work showed what could be obtained wish SEMS, EDAX, SAES and other

analysis techniques, and the results indicated likely future directions.

-30-
1. B.D. Sartwebl, A.B. Campbell III, B.S. Covino, Jr. and T.J. Driscoll, IEEE

Trans. NS-26, 1670 (1979).

2. T. Amano, S. Yajima and Y. Saito, Trans. JIM 20, 431 (1979).

3. A. Kumar, M. Naszallah and D.L. Douglass, Oxid. Met. 8, 227 (1974).

r^ 4. G. Kerker, J.L. Moran-Lopez, and K.H. Benneman, Phys. Rev. B 15, 638 (1977).

EI 5. V. Kumar, Phys. Rev. B 23, 3756 (1981).

6. R.E. Watson and L.H. Bennet, CALPHAD 5, 25 (1981).

7. H.H. Brongersma, M.J. Spornaay, and T.M. Buck, Surf. Sci. 71, 657 (1978).

8. S. Mukherjee, J.L. Moran-Lopez, V. Kumar, and K.H. Benneman, Phys. Rev. B 25,

730 (1982).

9. M. Cyrot and F. Cyrot-Lackman, J. Phys. F 6, 2257 (1976).

10. R.E. Watson and L.H. Bennett, Phys. Rev. Lett. 43, 1130 (1979).

11. D.G. Pettifor, Phys. Rev. Lett. 42, 846 (1979).

^. 12. M. Guttmann and D. McLean in Interfacial Segregation edited by W.C. Johnson

1

and J.M. Blakely (American Society for Metals, Metal Park, Ohio, 1977).

.

l-I

13. R. Kikuchi, Phys. Rev. 81, 988 (1951).

14. J.L. Moran-Lopez and L.M. Falicov, Phys. Rev. B 18, 2542 (1978).

15. T. Amano, S. Yajima and Y. Saito, Trans. JIM 20, 431 (1979).

( 16. G. Rowlands and D.P. Woodruff, Phil. Mag. A 40, 459 (1979).

I 17. M.W. Ribarsky, Bull. Am. Phys. Soc. 29, 389 (1983).

I 18. A.R. Miedema, J. Less-Common ?stet. 46, 67 (1976).

19. R. Andrews, Phil. Mag. 35, 1153 (1977).

20. B.I. Dunlap, J.W.D. Ccnnolly, and J.R. Sabin, J. Chem. Phys. 71, 3396 (1979).

21. M.F. Ashby, F. Spaepen, and S. Williams, Acta Metall. 26, 1647 (1978).

22. C.L. Briant and R.P. Messmer, Phil _ag. B 42, 569 (1980).

-31-
APPENDIX

Presented at the 42nd Physical Electronics Conference, Atlanta, Georgia (1982).

Surface Segregation in Ternary Alloy Systems,

M.W. Ribarsky, Georgia Institute of Technology.*

We extend to ternary systems the method of minimizing the total

free energy of a crystal with respect to component concentrations

in surface and bulk layers in order to calculate surface segregation. In this work we compare results between a pair bonding

approach with which one obtains surface free energies using bulk

thermochemical data and a continued fraction tight-binding technique suitable for transition metal alloys. With the continued

fraction technique, one calculates the electronic Green's function from which one derives the surface density of states. The

technique has been applied to random transition metal alloys,

and it yields reasonable values fc the surface d-band density

of states. For both the pair bonding and tight-binding methods,

the free energy minimization condition is a straightforward extension of the condition for binary alloys. l For multicomponent

systems, one has

aF aF

ax iA axiA

aF aF etc.....,

ax iB axiB

where F is the free energy, i refers to the surface layer, b refers to a bulk layer, and A,B,C,etc... are the atomic species

present. This approach opens the way to studying systems where

even trace amounts of a third element can change the surface

composition of a binary alloy. For example, small amounts of

Al in Ni-Cr alloys will cause the surface oxide to become aluminum oxide rather than chromium oxide. We will give results

for some interesting systems for the dependence of surface concentrations on the addition of the third element to binary solutions and also for the effect of chemisorbed species on the

surface concentration. We will also discuss the application of

this model to grain boundaries. Here one may visualize the

grain boundary as resulting from two half-crystals with stepped surfaces "glued" together. The procedure is then to consider separately the Green's function for each half crystal and

then consider the effect of interaction across the boundary.

Calculaticns on symmetrical tilt boundaries in s-like metals

yield densities of states with sharp structure due to localized boundary staes. The extension of this model to segregation

in ternary systems would be important. As an example, Ni, Cr, Mo

and Mn alloyed in steels enhance P segregation to dangerous

levels causing temper brittleness.

*Supported in part by a grant from NASA-Lewis Research Center.

1 G. Kerker, J.L. Moran-Lopez and K.H. Beaneman, Phys. Rev.B15,

638(1977).

-32-

J
Abstract Submitted

for the March Pieeting of 'the

American Physical Society

26-30 March, 1984

Physics and Astronomy Suggested title of session

Classification Scheme in which paper should be placed

Number 79 Ion Implantaicn

The Diffusion.of Implanted Tons Near

Surfaces and Grain Boundaries. M.W. RIBARShY,

Georgia Tech*--At higher temperatures an implant distribution can change greatly from its

original profile. We use a diffusion model to

investigate the kinetics of the implant 6istributiou in the presence of a surface or

grain boundary. The calculations show that

the movement and spreading of the implant profile is quite temperature-dependent. The model provides a method for relating the surface

and grain boundary enrichment factors to the

heats of segregation for these interfaces.

Our results show that chemisorbed layers of

certain elements or boundary segregation of

certain impurities can greatly affect the kinetics of the implant distribution. We also

discuss methods for developing a microscopic

framework for this model.

*Supported by NASA Grant No. NAGS-255

Please do not schedule on Friday, 30 March.

Please assign to regular program.

rna,^^-,^ ZO

Martin W. Ribarsky ^-

School of Physics 

Georgia Institute of Techna_ 3y

Atlanta, GA 30332

-33-

K%

r