APPENDIX.—FACE-CENTERED CUBE MODELING PROCEDURE

The three-variable face-centered cube experiment de-
sign in matrix form is shown below in normalized units.
Independent variables: x & %

1-4 +1
1 1-4
16164
1 1-4
1-161
1161
1611
1 $11
100 «0
1 0 0
0-1 «0
01 0
0 0 -1
001
0 0 0
00 0
0 0 0

Geometrically, the points correspond to the corners, faces,
and center of a cube. The matrix is designed so that
independent estimates of the variable coefficients can be
obtained using multiple regression analysis. The general
form of the model utilized in this analysis is as follows:

Y = (constant) + (linear effects) + (interaction effects)

+ nate oe)

- > bade, iat > bx
isl i=l
where = predicted value,

Db = coefficients of model,

x = normalized level of variable,

The face-centered cube design allows for the estimation of
linear, interaction, and curvature effects. For the esti-
mates to be independent estimates of the effects, however,
the regression analysis must be conducted using normal-
ized units. If normalized units are not used, the inter-
action and curvature variables are highly correlated with
their respective linear variables, which does not meet the
regression analysis assumption that the independent
variables are independent of one another. When normal-
ized units are used, correlations between the linear,
interaction, and curvature variables are minimized. The
normalization equation is

= (ariable level - middle level) _
normalized level (high level - low level)/2*

‘Using temperature as an example, the range of 25°, 50°,
and 75° C would correspond to -1, 0, and 1 in normalized
units, A temperature of 40° C would correspond to -0.4 in
normalized units.

The face-centered cube design used in this report was
modified slightly in that 1.00 g of Cu per liter (normalized
unit = -0.33) was the middle value of Cu concentration
tested in the experimentation (see table 4) rather than
1.25 g of Cu per liter. However, 1.25 g of Cu per liter
must still be used as the middle value in the normalization
equation (see below).

The regression equations in this report were developed
using a stepwise regression procedure with a t-test signif-
icance of 0.10 or less required to enter a variable into the
equation. The equations were developed using normalized
units and variable ranges of temperature from 25° to
75° C, final pH from 1.00 to 3.00, and final Cu concen-
tration from 0.5 to 2.0 g/L according to the matrix design
shown above.

‘When using the models to calculate Cu loss predictions,
it becomes somewhat repetitive to normalize the independ-
ent variable levels for each calculation. One way to avoid
this repetition is to substitute the normalization equations
into the normalized regression equations and then simplify
the result. For the Ca montmorillonite model, the trans-

and Pp = number of independent variables. formation would be as follows:
¥=520-10 7-50), 199 _(@H-20) | 43. (Cu-129) , 4, _(T-50)_ _(pH-20)
(5 =25)/2 G0-10)/2 "a0 O52 (I5=25)/2 (0-10)
9 (PH-20) (Cu-125) _54 (pH-20) (pH-20) 47 (Cu-125) (Cu-125)

° Go- 10/3 10)/2 (2.0-0.5)/2

G.0-10)/2 G.0-1.0)/2

1 OO7 03)/2 (20-05)/2"


g/L

UNIT OF MEASURE ABBREVIATIONS USED IN THIS REPORT

degree Celsius meq __ milliequivalent
gram mL milliliter
gram per liter pet percent

hour



‘Table 7.-CuEC’s for Na montmorillonite

Table 9.—CuEC’s for illite

Initial Final CUEC, meq
Temp, Cu Cu per 100 g clay
c pH cone, = pH_— conc, «Op. Cae
g/t g/L served! cu
lated”
25... 094 062 098 O52 130 125
98 221 1.04 1,98 285 8 20.5
175 1.838 2.00 1.04 37.0 35.0
2080-730 206849 306 = 314
208 «237 «293° 2.06 390 407
50... 100 116 106 99 214 0 218
W730 71 197A 252 © 26.9
1771.27) 198 98 349 35.0
181 231 2031.98 5 402
204 1.30 3.05 1.00 382 38.0
75... 94 62 100 52 130 125
98 221 1.05 1.98 290 29.8
175 1.332.068 1.05 35.3 35.0
208 73 2067 32700 312
208 233° 299 2.00 414 40.7
CuEC Cu exchange capacity.
‘Calculated as average of triplicate runs.
?Calculated based on design values given In Table 4.
Table 8.—CuEC’s for attapulgite
Initial Final CUE, meq
Temp, Cu Cu per 100g clay
c pH cone, PH cone, ‘Ob- Cal-
oft g/L served’ =—cu-
lated?
25... 092 085 097 O51 2734
97 210 © 1.09 2,00 66 = 6.05
1581.16 1.96 1.05 67 59
184 061 3.0952. 5756
195 221 307 203 Wt 11.6
50... 82 107 1.05 1.00 44 5.0
158 601.993 46 5.95
158 1.16 2.04 1.08 80 74
200 214 2.00 2.00 90 10.3
189° 1.45 3.08 1.00 92 98
7%... $2 85 101 47 50 49
87 212 «832.01 67 78
188 1.16 2021.00 103 89
186 002« «6029748, 94 © 10.1
200 224 2.90 1.99 159 16.1

CuEC Cu exchange capacity.
‘Calculated as average of triplicate runs.
*Calculated based on design values given in Table 4.

initial Final CuEC, meq
Temp, ~ Cu Gu _—_—~per 100g clay
c PH = cone, = pH_— cone, «Ob ale
oft g/L served’ cu
lated?

25... 080 061 102 085 0901.4
178 216 «1.09 2.02 220 24

120 108 203 96 1916

128 623.0883 13° 18

196 228 «3.08 1.99 45° 83

50... 74 107 8898 140 18
140 561.9750 88 (95

112° 1.10 © 202 1.00 16-18
115-218 1.99 2.02 25 35
131121 3071.02 30 33

75... 78 581.082 od
76 217 1.04 = 201 25 24

121 118 © 2041.06 220 24

137° 683.0853 23 (26

147 243 3.09 2.02 65 63

CuEC Cu exchange capacity.
‘Calculated as average of triplicate runs.
2Calculated based on design values given in Table 4.

‘Table 10.—CuEC’s for kaolinite

Tnitial Final _GUEC, meq
Temp, Cu Cu Per 1009 clay
c pH = cone, pH_— conc, «OB. ale
oft g/L served’ — cu
lated?
2. 054 1.03 0.49 038 0.2
208 1.04 2.00 60 66
110 200 1.05 Ay 59
56 294 48 oO 5
215 297 202 1.06 1.18
50. 1.08 971.04 2 2h
56 204 St 3688
111 2.04 1.05 4847
209 206 200 wm 72
111 297 1.02 ma 7
78. 530 0852 08 05
205 1.00 2.03 1406
1.02 200 95. a
59 290 50 v2 87
215 205 202 1.03 98
CuEC hange capacity.

Calculated as average of triplicate runs.
?€alculated based on design values given in Table 4.


INTRODUCTION

In situ leaching is an alternative mining technique used
to extract metals from ore deposits that preclude conven-
tional methods of mining because of economic, environ-
mental, or other factors. Leaching solutions are applied to
the deposit through a grid of injection wells, and the solu-
tions travel through flow channels within the ore body to
adjacent solution recovery wells. Metals are dissolved as
the leach solution contacts the metal-bearing minerals in
the deposit. The metal-containing pregnant solution is
pumped to the surface to a metal removal and production
facility. The depleted solution is replenished with neces-
sary chemicals for leaching and reinjected into the deposit
for further in situ leaching.

There are a number of potential problems associated
with in situ leaching of oxidized ores. One of these is the
loss of metal from the leaching solution due to cation
exchange with clays that are present in the ores. This
exchange ability is called the cation exchange capacity
(CEC) of the clay and is commonly measured in terms of
milliequivalents of ion removed from solution per 100 g of
clay. CEC’s measured to date have most often been
determined at neutral pH and varying ion concentrations.
Table 1 gives a range of published CEC’s for several clay
groups (1) Unfortunately, these values are unsuitable
for predicting the effects of clays under acidic in situ
leaching conditions since they were determined at pH 7.
The CEC values should be lower in an acidic environment
because of the severe competition between H* ions and
the metal cations in solution for the exchange sites in the
clay lattice.

Table 1.—CEC’s of clay minerals

Clay meq per
100 g clay
Montmorillonite .. 80-150
Attapulgite 0- 30
Mite. . 10- 50
Kaolinite . 3- 15
Chiorite 10- 40
CEC (change capacity.

Oxidized Cu deposits are potential candidates for in situ
leaching because Cu is easily leached with dilute sulfuric
acid solutions and because methods are available commer-
cially to recover the Cu from the solution as salable metal.
Consequently, research to determine relevant CEC’s of Cu
for six common clays under simulated in situ conditions
was conducted by the U.S. Bureau of Mines, as part of the
Bureau's mission to increase the efficiency and economy
of extracting metals from domestic ores.

italic numbers in parentheses refer to items in the list of references
preceding the appendix at the end of this report.

Clays are composed of a negatively charged repetitive
framework of alumina and silica and adsorbed singly or
doubly charged cations. Depending on the particular clay,
the majority of adsorbed cations are located either in the
interlayer positions between the alumina-silica sheet, as in
montmorillonite, or on the particle surface, as in kaolinite.
When clay particles are placed in an aqueous environment,
a fraction of the interlayer or surface cations is quickly
replaced by solution cations without appreciable structural
damage to the clay material. An example would be the
exchange of Cu** and H* ions in Cu leach solutions for
the exchangeable Na* ions of Na montmorillonite. In this
case the two competing exchange reactions are

Na/X + H* + H/X + Nat (A)
and 2 (Na/X) + Cu?+ + Cu/2X + 2Na*, @)
where X = an alumina-silica unit cell.

Assuming chemical equilibrium, then

*anat
K,= 4H/x* aNa ;
8Na/x* apt

@

and . sovyax’ at)
@nayx)”* acy
K = equilibrium constant,

®

where
and a = activity.
Multiplying the two equilibrium equations,
KiK)« 8H /x* Na+" Aqy/2x" (Anat)? .
Ana /x* n+ (@Na/x)”* acu
Taking the log of both sides, then

Q)

log KyKy = log ayy + Slog aygt + log agyox
~ Blog anax - log agy* - log ag,?*, (4)
Substituting
K = log KyK, - log ayyx - Slog aygt + 310g anarx (5)
into equation 4 gives

K = log Acu/2x ~ log ayt - log acy, ©


COPPER EXCHANGE CAPACITY OF CLAYS AND THEIR POTENTIAL EFFECT
ON IN SITU COPPER LEACHING

By J. S. Gomer,’ S. W. Yopps,’ S. P. Sandoval,? and A. E. Clark*

ABSTRACT

The U.S. Bureau of Mines conducted Cu exchange tests for six common clays under simulated in situ
leaching conditions. Regression equations were obtained from the data expressing the Cu exchange
capacity as a function of Cu concentration, pH, and temperature. Using these equations, an analysis
was made of the impact each clay could have on overall Cu recovery. The results suggest that Ca and
Na montmorillonite clays could have a major impact on Cu recovery and that attapulgite and illite clays
could have a smaller, but still significant, impact. Kaolinite and ripidolite clays pose little threat to loss
of Cu from in situ leaching solutions.

1Metallurgical engineer (now with Nalco Chemical Co, Naperville, IL).
2Mill metallurgist (now with Bond Gold Bullfrog, Inc., Beatty, NV).
Metallurgical engineer.

‘Supervisory chemical engineer.

Reno Research Center, U.S. Bureau of Mines, Reno, NV.


baths and agitated at the appropriate temperature. The
slurries were vacuum filtered after 1h of shaking, and
equilibrium pH and Cu concentrations of the filtrates were
measured to determine the exact experimental conditions,
If the pH of a test solution was not within 0.1 or the Cu
concentration was not within 0.06 g/L of the desired test
parameters, the experiment was repeated utilizing different
initial acid and/or Cu concentrations until the design
criteria were met.

Each test was run in triplicate and the average CuEC’s,
pH’s, and Cu concentrations at a given temperature were
analyzed using multiple regression analysis, With the ex-
ception of the clay-to-solution ratio, each clay was sub-
jected to the same experimental procedure, The clay-to-
solution ratios were chosen for each clay to allow a
detectable change in the concentration of Cu in solution
after ion exchange, These ratios are detailed in table 5,

Table 5.—Clay-to-solution ratios
Clay Clay-to-solution,

g:ml.
Ca montmorillonite. . 2.5:100
Na montmorillonite . . 2.5:100
Attapulgie ........ 5.0:100
Ite... 5.0: 25
Kaolinite 10.0; 25
Ripidolite .. 10.0: 25

The Cu ion concentrations of the initial and equili-
brated solutions were determined by atomic absorption
spectroscopy. The difference between the two values was

the Cu exchanged.

RESULTS

The CuEC’s and the equilibrium conditions for each
test are presented in tables 6 through 11, The results
show that Ca montmorillonite exhibits the greatest ex-
change, ranging from 19 to 70 meq per 100 g of clay.
Sodium montmorillonite removed from 13 to 42 meq of
Cu* ions from solution per 100 g of clay, Attapulgite
ranged from 3 to 16 meq per 100 g of clay, illite from 1 to
6 meq, kaolinite from 0.1 to 1.1 meq, and ripidolite from
0.01 to 1.3 meq. Only five tests were reported from the
tipidolite series, since no Cu exchange occurred at pH 1 or
2. Under these test conditions, the CuEC of this series of
clays varied in the following manner: Ca montmorillonite
> Na montmorillonite > attapulgite > illite > kaolinite >
tipidolite, Based on these results, Ca and Na montmoril-
lonite have the greatest potential to exchange Cu and,
therefore, pose the greatest threat in affecting Cu recovery
during in situ leaching. Kaolin and ripidolite clays pose
little threat to Cu recovery.

Table 6-CuEC’s for Ca montmorillonite
Initial . Final CuEC, meq
a

Temp, Gu Cu’ per 100.9 olay
c pH cone, += pH_— cone, Ob- Cale
g/t g/L served! = cue
lated?
SB... 099° 06310304898
9 241 95 200 520 526
186194 (199974700483
245 83300 BAT AG
253° 253° «292 «197 = 705698
5... 98 1.21015 BR
188 772084085783
188 192-206 94474478
188 249-203-197 5135
252 140 300 «94 087.9559
7... 98 239 97 201 479 496
9% 6 10 48 189 208
1861.34 2036470073.
24 83 2008S ASG
261 257 209 «202 688708

CuEC Cu exchange capacity,
{Calculated as average of triplicate runs,
Calculated based on design values given in Table 4,


RI | 9396 | REPORT OF INVESTIGATIONS/1992

Copper Exchange Capacity of Clays and Their
Potential Effect on In Situ Copper Leaching

By J. S. Gomer, S. W. Yopps, S. P. Sandoval, and A. E. Clark

UNITED STATES DEPARTMENT OF THE INTERIOR

BUREAU OF MINES


degrees Celsius, final pH, and final Cu concentration in
grams per liter. Details of the conversion from normalized
to natural units are given in the appendix. The trans-
formed equations are as follows:

Ca montmorillonite:
CuEC = -8.1 - 0.1T + 21.4pH + 32.7Cu
+ 0.04(T)(pH) ~ 1.3(pH)(Cu) - 2.8(pH)?
~ 48(Cu)?
Na montmorillonite:
CuEC = -264 + 31.0pH + 32.1Cu - 2.5(pH)(Cu)
- 5.(pH)? - 73(Cu*
Attapulgite:
CuEC = 1.9 - 0.2pH + 0.7Cu + 0.03(T)(pH)

+11 (pH)(Cu)

(10)

(11)

(12)
Illite:
CuEC = 2.8 - 0.01T - 2.8pH + 0.1Cu
+ 0.01(T)(pH) + 0.8(pH)(Cu) + 0.6(pH)? (13)
Kaolin:
CuEC = 0.4 - 0.01T - 0.04pH + 0.2Cu
+ 0,004(T)(pH) - 0.003(T)(Cu)

+0.1(pH)(Cu) (14)

The predicted CuEC’s of each clay based on the trans-
formed equations are compared with the observed CuEC’s
in tables 6 through 10.

IMPACT OF CATION EXCHANGE

The developed CuEC relationships, equations 10 to 14,
can be used to predict the impact of cation exchange on
Cu recoveries from an in situ leaching operation. Copper
losses can be calculated given an ore body grade, type and
percentage of clay in the deposit, solution composition,
and pH. An example is given in table 14, The calcula-
tions are based on the assumption that all of the Cu in the
ore body is extracted into solution and that the solution
contacts all of the clay in the ore body. Results presented
in table 14 suggest that clays can have a large effect on Cu
recovery. Even minimal amounts of Ca or Na montmoril-
lonite could potentially decrease the viability of the opera-
tion, Minor amounts of attapulgite in the ore body would
decrease the Cu recovery slightly, but larger amounts of
attapulgite could increase the Cu loss measurably. Losses
associated with illite would only be noticeable in bodies
containing high illite and low Cu grades.

Operating conditions vary from site to site. If the pH
and/or Cu concentration of the pregnant solution are
greater than those of the test matrix of this report, the Cu
losses would increase. Conversely, lower pH and/or Cu
concentration would reduce the loss. Changes in temper-
ature would affect Cu recovery slightly.

As mentioned previously, the effect of competing metal
ions, such as Al and Mg, that would be present in an
actual in situ leaching solution will be examined in a future
study. Competing metal ions may exchange in preference
to Cu, thereby reducing Cu exchange losses.

CONCLUSIONS

This investigation demonstrated that the ability of clays
to exchange their adsorbed cations for the valuable Cu
ions is potentially detrimental to the success of an acidic
in situ leaching operation.

The Cu ion exchange capacity of each clay varied from
high to low as follows: Ca montmorillonite > Na mont-
morillonite > attapulgite > illite > kaolinite > ripidolite.
The montmorillonite clays, because of their relatively high
CuEC’s, have the potential to exchange a major portion of
the dissolved Cu and could render an in situ leaching
operation unprofitable, Depending on attapulgite and illite
concentrations in an ore body, measurable losses of Cu
ions could occur as a result of these clays. Based on
CEC’s, the presence of kaolinite and ripidolite in Cu ore

deposits would pose little threat to the recovery of sol-
ubilized Cu.

Operating at the highest possible acid concentration
and minimizing the recirculation of Cu ions to maintain
the lowest possible Cu concentration within the ore body
minimizes the exchange of Cu ions into clay matrices,
Changes in temperature affect the Cu exchange with the
clays slightly.

It should be noted that this research was conducted in
the absence of competing metal ions, which would be pres-
ent in actual in situ leaching solutions. Competing metal
ions may exchange in preference to Cu, thereby reducing
Cu exchange losses, The effect of competing metal ions
will be addressed in a future study.


Table 11.—CuEC’s for ripidolite!

Initial Final Observed?
Temp, Cu Cu ‘CuEC,
c pH cone, pH conc, meq per
g/t g/t 100 g clay
2... 1.18 0.55 3.03 0.54 0.11
1.21 2.04 3.01 2.01 26
50... 1.15 1.05 3.06 1.01 we
75... 1.20 56 2.93 5 c J
1.21 2.07 2.95 1.91 1.3
CuEC Cu exchange capacity.

Only five tests reported, because no Cu exchange occurred at
PH to 2.
2Calculated as average of triplicate runs.

REGRESSIONS

An objective of the present work was to develop
empirical equations to predict the magnitude of soluble Cu
losses during in situ leaching of oxidized deposits. The
equations were developed using a stepwise regression
procedure with a t-test significance of 0.10 or less required
to enter a variable into the equation (10). The details of
the modeling procedure are presented in the appendix.
The general form of the model is

ya bg + Bye + bax + byxs + Bygxp + bygxy%
+ bagtans + byxy? + bygKy? + bygxy’,

where y = CuEC in milliequivalents per 100 g of
clay,
X, = temperature from 25° to 75° C,
X, = final pH from 1.00 to 3.00,
= final Cu concentration from 0.5 to 2.0
and b= coefficients of variables.

The coefficients of the equations developed for the clays
using normalized units are shown in table 12, An equation
for ripidolite was not generated because of the very low
Cu exchange at pH 1 and 2 noted earlier.

The coefficients of the equations provide useful infor-
mation about the CuEC’s of the clays. The coefficients re-
veal that final pH and final Cu concentration have the
greatest influence on Cu exchange, as was evidenced in
equation 8. Copper exchange increases with increasing pH
and increasing Cu concentration. The effect of pH is due
to the strong competition between H* ions and Cu**
ions for exchange sites. An increase in final H* ion

concentration decreased the total Cu exchanged, while an
increase in the final Cu** ion concentration increased the
exchange. This was expected because cation exchange is
a stoichiometric reaction and the laws of mass action
apply.

Table 12.—Coefficients of normalized clay regression
‘equations, milllequivalents per 100 g clay?

Costfi- Camont- Na mont- ‘Atta- —ilite Kaolin
cient __morillonite _morillonite__pulgite
by + 52.0 a7.6 7.9 24 06
by .. 1.0 ® 15 4 “A
b,.. 10.9 78 27 1.0
by .. 13,7 65 at 12
141 ie) 8 3
Q Q Q
-9 19 Fs 6 é
28 64 6 ¢
“27 4A @) O) o)

1Equation not generated for ripidolite because of very low ex-
change of Cu at pH 1 and 2,
2Not statistically significant.

The negative curvature terms of the Ca and Na mont-
morillonite models reveal that the effects of final pH and
final Cu concentration diminish as these variables are
increased for these two clays. Temperature and the inter-
action terms have small effects on the CuEC of the clays.

The accuracy of the equations is measured using two
statistics—the coefficient of multiple determination (R?),
which measures the accuracy of the equations in predicting
the values of the data set used to develop the equations,
and the adjusted coefficient of multiple determination
(adjusted R*), which estimates the accuracy of the equa-
tions in predicting future responses within the range of
applicability of the equations. These two statistics, which
range from 0 to 100 pct accurate, are shown in table 13 for
the clay equations. The statistics show that the models
capture to a satisfactory degree the phenomenon of Cu
exchange as a function of the three independent variables.

Table 13.—R? and adjusted R? for
clay models, percent!

Model Pe ‘Adjusted
RF
Ca montmorilionite . . 99 99
Na montmorilionite . . 99 98
Attapulgite . 95 92
: 96 93
94 91

ted for ripidolite be-
cause of very low exchange of Cu at pH 1 and
2.

The regression models were transformed into equations
that use the natural variable units of temperature in


The effect of the final concentration of the displaced
cation, Na* in the case of Na montmorillonite, was
assumed to be constant and was incorporated as the log
ay,+ term in the constant K. Since log acyax is a relative
measure of CEC, equation 6, relating CEC to the perti-
nent variables, becomes

CEC = K + Alog ay+ + Blog ag2+, (0)
where A and B are regression constants.

Since molar concentration, M, is related to activity by
a = AM, equation 7 becomes

CEC = K’ + Alog [H*] + Blog [Cu?*], (8)
where K’ = K + Alog \yt + Blog Ag, ()

and A = activity coefficient.
A more detailed explanation of these relationships can be
found in references 2 through 4.

The pertinent independent variables in equation 8 are
Cu concentration and pH. This research investigated the
effect of these variables on ion exchange. In addition, the
effect of temperature on the exchange capacity of the clays
was studied. Future research will report the effect of
competing ions in the general equation.

EXPERIMENTAL DESIGN AND PROCEDURES

The following clays, which were obtained from the
Source Clay Repository of the Clay Mineral Society, a
recognized source of homogeneous clay samples, were
used in the Cu exchange studies: Ca montmorillonite,
Apache County, AZ; Na montmorillonite, Crook County,
WY; attapulgite, Gadsden County, FL; illite, Silver Hill,
MT; kaolin, Washington County, GA; and ripidolite, a
chlorite clay, Flagstaff Hill, El Dorado County, CA. Each
clay was thoroughly blended to ensure homogeneity. The
ripidolite and illite clay pieces required crushing and
pulverizing prior to blending. Typical analyses of each clay
mineral are shown in table 2. The size distribution of each
clay sample as received is presented in table 3,

Table 2.—Typical analyses of clay minerals, weight percent

Ele- © Camont- Namont- Atta- illite  Kao- Ripi-
ment —_morillonite morillonite pulgite linite _dolite
A... 79 95 48 W7 204 10.6
Ca.. Ww 1.0 11 3 <3 046
Cu.. 012 009 008 013.008 016
Fe .. a7 27 22 5.1 AZ 175
Ka... 22 24 23 25 <1 <1
Mg... 33 15 53 15 04 11.5
Mn... 095 011 024 015 = 019 075
Na... A 84 063 085074 <.03
Pi. <a <i 38 WO <4 <1
Si... 26.5 0.0 27.9 26.1 226 13.1
Ti... pki 070 28 48 96 52
Zn.. 12 077 017 083.058 052

The effects of pH, Cu concentration, and temperature
on Cu exchange were determined utilizing a face-centered
cube response surface design (5). This approach allowed
the effects of experimental variables on the Cu exchange
capacity (CuEC) to be determined with a minimal number
of experimental tests. After a cursory review of the lit-
erature to determine the compositions of typical Cu leach
solutions (6-9), experimental ranges were chosen to
be 1to 3 for final pH, 0.5 to 2.0 g/L for final Cu

concentration, and 25° to 75° C for temperature. Test
order was randomized to reduce the effects of unknown
biases. The experimental parameters for each design are
shown in table 4,

Table 3.—Clay size distributions, weight percent

Particle size, mesh... +48 -48, 100, -200,  -400
+100 +200 +400
Camontmoriionite... 0 1 10 14 75
Na montmorillonite 0 0 0 0 100
Attapulgite o 5 6 2 §9
Mite. . 38 Ot 6 32
Kaolinite o 0 0 0 100
Ripidolite . 3510 8 1 3%

Table 4.—Experimental parameters for face-centered

cube test design

Temp, Cu |] Temp, Cu | temp, cu
ue} PH conc,|} *C pH cone,|} °C pH cone,
g/t g/t oft

2... 1 O85 50... 1 10 1175... 14 05
1 20 2 5 1 20

2 10 2 10 2 10

3. C+ 2 20 3 5

3. 20 310 3 2.0

Preliminary tests for each clay determined the rate and
amount of Cu exchanged and the acid consumed over a
given period at room temperature. These tests revealed
that the Cu exchange equilibrium was achieved within 1h
for each clay. Once the equilibrium time was established,
a face-centered cube experiment design was conducted for
each clay, Experiments were conducted by mixing un-
treated clay and copper sulfate-sulfuric acid solution in
screw top flasks. Initial Cu and acid concentrations varied
depending on acid consumption and Cu exchange for each
of the 15 test conditions. The flasks were placed in shaker


CONTENTS

Page

Abstract .......
Introduction .. .
Experimental design and procedures .......
Results ..........065.

Impact of cation exchange
Conclusions . .
References . seeeeee
Appendix.—Face-centered cube modeling procedure .

WOIId AaYNe

CEC’s of clay minerals ......... bees
Typical analyses of clay minerals
Clay size distributions ............... wees
Experimental parameters for face-centered cube test design.
Clay-to-solution ratios
CuEC’s for Ca montmorillonite
CuEC’s for Na montmorillonite .....
CuEC’s for attapulgite
CuEC’s for illite ...

CuEC’s for kaolinite ..........
CuEC’s for ripidolite ........ oa
Coefficients of normalized clay regression equations
13. R? and adjusted R? for clay models .....
14. Effect of clay ion exchange on Cu recovery

BES cer awayne

WAAAUUUNUNHRALWOUN



10

‘When simplified, this function equals equation 10 for the
Ca montmorillonite model. Predictions can be calculated
using this equation by entering the variable levels in their
natural units, Bach of the clay models was transformed
in this manner. In the transformation calculations, the

coefficients from the normalized regression equations were
carried out to the fourth decimal place and divisions and
miultiplications were not performed until the end of the
calculations to avoid rounding error.

INT.BU.OF MINES,PGH.,PA 29483


Library of Congress Cataloging in Publication Data:

Copper exchange capacity of clays and their potential effect on in situ copper
leaching / by J.S. Gomer ... [et al.}.

P. _ cm. — (Report of investigations / United States Department of the
Interior, Bureau of Mines; 9396)

Includes bibliographical references (p. 8).
‘Supt. of Docs. no.: I 28.23:9396.
1. Copper—Metallurgy. 2. Metallurgy—on exchange process, 3. Clay—Testing.

4, Leaching. L. Gomer, J. S. (Jay S.) IL. Series: Report of investigations (United
States. Bureau of Mines); 9396,

TN23.U43 — [TN780] [622'.343—dc20} 91-25178 CIP



Report of Investigations 9396

Copper Exchange Capacity of Clays and Their
Potential Effect on In Situ Copper Leaching

By J. S. Gomer, S. W. Yopps, S. P. Sandoval, and A. E. Clark

UNITED STATES DEPARTMENT OF THE INTERIOR
Manuel Lujan, Jr., Secretary

BUREAU OF MINES
T S Ary, Director


Table 14.-Etfect of clay lon exchange on Cu recovery?

(Test matrix conditions: pH, 2.5; Cu cone, 1.8 g/L; temp, 65° C)

Clay CuEC, Cu loss per Cu loss,” pet
‘concentration, meq per 100g 100g ore, g at pot Cu levels® of~
Pet clay 0.2 0.4 0.6 08
Ca montmorillonite:
65 0.021 105 52 35 26
i} 103 51.5 25.7 7.2 129
65 207 100 51.7 MS 25.9
42 013 65 32 22 16
42 067 33.5 16.7 2 84
42 133 665 33.2 22.2 16.6
12 004 20 1.0 7 5
12 019 95 AT 32 24
12 038 19.0 95 63 47
4 001 5 2 2 A
4 006 3.0 15 10 7
4 013 65 32 22 16
08 0002 A 05 03 002
8 0013 6 3 2 2
& 0025 1.2 06 4 3
CuEC Cu exchange capacity,

{information for ripidolite not given because of very low exchange of Cu at pH 1 and 2,

26u loss to Clay lon exchange.
Assumes 100 pet of Cu is leached,

REFERENCES

1, Grim, RE. Applied Clay Mineralogy. McGraw-Hill, 1962,
422 pp.

2, Reichenberg, D. Ton Exchange Selectivity. Ch. in Ion Exchange,
ed, by J. A. Marinsky. Marcel Dekker, Inc,, v, 1, 1966, pp. 227-276.

3, Helffreich, F. Ton Exchange, McGraw-Hill, 1962, 624 pp.

4. Garrels, R. M,, and C. L. Christ. Solutions, Minerals and
Equilibria, Harper & Row, 1965, pp. 267-305,

5. Rautela, G, S., RD, Snee, and W. K. Miller, Response-Surface
Co-Optimization of Reaction Conditions in Clinical Chemical Methods.
Clin. Chem. (Winston-Salem, NC), v. 25, No. 11, 1979, pp. 1954-1964.

6, Ahlness, J. K, and M, G. Pojar. In Situ Copper Leaching in the
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37 pp.
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8. Longwell, R.L. In Place Leaching of a Mixed Copper Ore Body.
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Aplan, W. A. McKinney, and A. D. Pemichele. AIME, 1974,
pp. 233-242,

9. Bampton, K. F., F, Bologiannis, J. H, Canterford, and A. N. Smith.
Development of Experimental In-Situ Leaching at the Mutooroo Copper
Mine, South Australia, Paper in The Australian Institute of Mining and
Metallurgy Broken Hill Conference. Aust. Inst, Min. Metall., v. 12, 1983,
pp. 371-379.

10. Lewis-Beck, M.S. Applied Regression: An Introduction. Sage
University Paper Series on Quantitative Application in the Social Sci-
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