Co-precipitation approach to measure amount of $^{238}$U in copper to sub-ppt level using ICP-MS
Ya-Yun Ding Meng-Chao Liu Jie Zhao Wen-Qi Yan Liang-Hong Wei Zhi-Yong Zhang Liang-Jian Wen
physics.ins-det






Co-precipitation approach to measure amount of in copper to sub-ppt level using ICP-MS








Ya-Yun Ding ^a, [E-mail: dingyy@ihep.ac.cn]
  Meng-Chao Liu ^a,
  Jie Zhao ^a,b,
  Wen-Qi Yan ^a,
  Liang-Hong Wei ^a,
  Zhi-Yong Zhang ^a,
  Liang-Jian Wen ^a,b, [E-mail: wenlj@ihep.ac.cn]


^aInstitute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China

^bState Key Laboratory of Particle Detection and Electronics, Institute of High Energy Physics, CAS, Beijing 100049, China







Inductively coupled plasma mass (ICP-MS) spectroscopy is widely
used for screening materials of low background detectors in dark
matter and double beta decay searches due to its high sensitivity to
trace and .
This work describes a novel co-precipitation approach to
measure the amount of in high-purity copper to sub-ppt level.
Such an approach allows the pre-concentration of U and removal of
the matrix, by selecting a proper precipitator to co-precipitate with
and using excess ammonia water to separate the uranium hydroxide
from copper by forming water-soluble tetra-amminecopper (II).
The isotope dilution method and standard addition method were both
used to mitigate the matrix effect and cross-check each other.
The latter was also used to measure the recovery efficiency of by using as the tracer.
The method detection limit (MDL) reached ∼0.1 pg /g Cu
for both methods while the recovery efficiency of uranium robustly
remains 65%–85%.
Various sources of interference in the ICP-MS analysis were thoroughly evaluated,
and the contamination from reagents were found to be the dominant factor
that affected the MDL. Further purification will allow
significant improvements in the MDL.
This co-precipitate approach can be easily extended to measure by using as the tracer.




 Keywords: ultra-low radioactivity, ICP-MS, co-precipitation, uranium



footnote







§ INTRODUCTION



Experiments searching for neutrino-less double beta decay (NDBD)
have a stringent requirement on the natural radioactivity in the
detector materials, particularly and .
The capability to detect ultra-trace amounts of and
allows careful assessment of the backgrounds,
and thus is important to the planned NDBD
experiments <cit.>.
In addition to NDBD experiments, many neutrino experiments
or dark matter experiments also require ultra-low-radioactivity
materials for the detector construction.
The highly sensitive methodologies known to date include
neutron activation analysis and inductively coupled plasma
mass spectroscopy (ICP-MS) <cit.>.
ICP-MS analysis is relatively quick and typically has an intrinsic
detection limit better than parts-per-trillion (ppt or pg/g) for
a large number of elements, particularly uranium and thorium.

ICP-MS analysis is optimized for aqueous samples, e.g., it is
commonly used to measure uranium and thorium in water samples
 <cit.>.
However, the drawback of using this technique to detect ultra-trace
elements is the need for arduous pre-treatment of the samples.
Acid digestion is typically used to deal with the
solid materials, and the tolerable total
dissolved salts (TDSs) in the matrix for ICP-MS analysis is <0.1%.
The pre-treatment inevitably needs additional reagents
and chemical separation processing to reduce TDSs or concentrated
U and Th. It may consequently introduce contamination and
result in worse detection
limits <cit.>.
Thus the pre-treatment approach must be scrupulously
designed and carried out.

Electrochemical techniques, precipitation, and ion exchange are
widely used methods used to separate the matrix and analyte <cit.>.
Recently, an anion exchange method was reported
in <cit.> that achieved detection limits of
10^-2 pg/g level for both and in copper samples.
With anion exchange, this method effectively
concentrated analytes and simultaneously removed an unwanted sample matrix.
The radio-assay to ultra-trace U and Th is extremely challenging.
Development of other convenient methods with different pre-treatments
is highly desired and would benefit future experiments.
It is well known that Cu has the complex ability to form water-soluble
compounds in excess ammonia water, whereas U will precipitate.
However, ultra-trace U or Th in solutions are too diluted to be
separated by conventional methods. The co-precipitation approach is
feasible in this case. Furthermore, to achieve a sub-ppt-level
detection limit, it is critical to scrupulously perform sample
preparation, and qualify the cleanness of labware and the purity of reagents.
Calibration of the recovery efficiencies of U or Th during the pre-treatment
is also essential, and the typical way is to use or as a tracer. We have obtained and standard solutions, but only the former is qualified to have sufficiently
low contamination with respect to the target element.
Hence, in this work, we present the measurement to demonstrate
this approach, but it should be pointed out that the method is also applicable
to the measurement.

The rest of this paper is organized as follows:
In Sec. <ref>, the experimental details to detect the
ultra-trace amount of in copper is introduced, highlighting the
pre-treatment process with a co-precipitator and tracer. The various
sources of interference in the ICP-MS analysis are discussed in Sec. <ref>.
Two separate analyses with the standard addition method and the isotope
dilution method are presented in Sec. <ref>,
and they give a consistent detection limit.
Finally, we summarize this work and discuss its prospects
in Sec. <ref>.



§ EXPERIMENTAL SECTION





 §.§ Instruments, reagents, and labware


All chemical operations and measurements were done in a class 10,000
clean room to suppress environmental contamination, since the
concentration of and in dust is typically
around the ppm level. The analyses were performed using a ThermoFisher
iCAP-Qc Quadrupole ICP-MS instrument with a PFA concentric nebulizer.
A collision cell was equipped but not used in this work.
The spectrometer was tuned every few months.
For 1 pg or per gram solution, the typical
counts per second with the ICP-MS device is approximately 700–900.
Before measuring the samples, a standard solution with
a ppt-level concentration should be tested for at least 30
min to ensure that the instrument is stable. Between every two samples,
ultra-pure solution was measured to ensure that the entire
system was clean.

The reagents used in this work are listed in Table <ref>.
The water for cleaning and dilution was unexceptionally ultra-pure water.
The ammonia water was further purified before use.
The and , both of 99.99% purity,
were dissolved in ultra-pure water.
The standard solution contains
2.3539(42)×10^-6 g ()/g (solution).
The standard solution was diluted with 5% .



The filter units were Millex-LG^ sterilizing filter
units (Millipore Ireland BV, Carrigtwohill, Co. Cork),
which were tested to be compatible with 6 .
The 20-mL polypropylene syringes were produced in JiangSu, China.
All vials, containers, pipette tips, stirring bars, filter units,
and syringes were cleaned with Alconox^ detergent and
rinsed with ultra-pure water at least three times, followed by at
least two overnight leaches in 6 electronic grade ,
followed by rinsing with water. All labware was filled with or immersed
in hot 6 OPTIMA for 20 min prior to use,
followed by at least three rinses with water.



 §.§ Pre-treatment process



The pre-treatment flow is shown in Fig. <ref>.
The key idea is to form water-soluble Cu ammonia complex with
excess , which allows the separation between the bulky Cu
and the and elements that precipitate in such
circumstances. The major steps include dissolution, co-precipitation,
and filtration. During pre-treatment, the calibration of recovery
efficiency is critical and also implemented.





  §.§.§ Dissolution


The copper samples were first soaked in the detergent
(Alconox^) aqueous solution for 15 min under
ultrasonic conditions, then rinsed and soaked in fresh water for
5 min three times under ultrasonic conditions. Finally
they were dried with high-purity nitrogen.
To remove the surface contaminants, the cleaned copper was etched in
fresh 6 twice until its total weight lost was
∼3% by mass. The remaining copper was rinsed
with water, dried with nitrogen gas,
and completely dissolved by using 8 .
A reddish-brown smoke was visible in the beginning of dissolution,
which indicates the formation of NO_2:

    Cu + 4 HNO_3 = Cu(NO_3)_2 + 2 NO_2↑ + 2 H_2O.

As the acid is consumed over time, the reaction equation becomes:

    3 Cu + 8 HNO_3 = 3 Cu(NO_3)_2 + 2 NO↑ + 4 H_2O.

The molar ration of Cu to was chosen to be 1:4 for complete
dissolution, and the excess helped to maintain the stability
of the copper solution.



  §.§.§ Recovery efficiency calibration



Recovery efficiency is an important indicator used to evaluate the
effectiveness of pre-treatment and must be obtained.
To evaluate the recovery efficiency during
the pre-treatment process, can be used as a tracer.
Because does not naturally exist, its recovery efficiency
can be determined easily. As an isotope of uranium, has
the most similar chemical properties as .
If the content is at the same level as in the solution, their recovery efficiencies are expected to be
the same. In addition, it is possible to use the isotope dilution
method with .

Our tests showed that when in aqueous solution is at
10^-9 g/g (ppb) level, the recovery efficiency can be
>90% by using the normal precipitation method with ammonia water.
However, if the content is at
10^-12 g/g (ppt) level or lower, the recovery
efficiency decreases to almost zero, and thus the co-precipitator
must be introduced.



  §.§.§ Co-precipitation


The co-precipitation approach is widely used in radiochemistry
to separate elements that are too diluted to be
separated by conventional methods.
All metal elements that do not precipitate in ammonia water,
such as Ag, Cu, Zn and Mg, cannot be chosen as co-precipitator.
Fe and Zr ions are found to be more suitable candidates.
The recovery efficiency for blanks (see Sec. <ref>)
was measured to be 71%±4% with as co-precipitator
and 48%±2% with as co-precipitator, respectively;
thus, was chosen for this assay.

As shown in Fig. <ref>, the quantitative standard solution and solution are first added into the
solution. Then, water is added in advance to dissolve
the copper ammonia complex formed later. Third, the ammonia water
is added slowly under stirring and the Cu^2+ ions start to precipitate:

    [Cu(H_2O)_6]^2+ + 2 OH^- → Cu(OH)_2↓+ 6 H_2O.

The ions of elemental Th, U, and Zr precipitate as well.
When adding excess ammonia water to the solution,
the Cu(OH)_2 precipitates start to disappear gradually:

    Cu(OH)_2 + 4 NH_3 + 2 H_2O → [Cu(NH_3)_4 (H_2O)_2]^2+ + 2 OH^-.

The solution turns dark blue due to the formation of
water-soluble tetra-amminecopper (II) in excess ammonia water,
whereas the precipitates due to Th, U, and Zr ions still exist.
In this process, one molar Cu needs four molar and six
molar . More ammonia water and may improve the
recovery of metal ions, but the impurities in these two reagents
will degrade the detection limits of ICP-MS analysis.
Thus, less ammonia water or is preferred.



  §.§.§ Filtration


The mixture after co-precipitation can be separated by filtration
with syringe-operated filter units.
The trace amount of the precipitates from U ions will be adsorbed
on the zirconium hydroxide and intercepted by the filter.
Then, the precipitates inside the filter unit are washed by warm
6 after rinsing with a small amount of diluted ammonia
water and pure water.
The eluent is collected and heated to remove excess acid until
the residual liquid is less than 0.4 g. The last step is to dilute
the residual liquid with 5% to a certain amount.
The final solution is ready for ICP-MS analysis, and called
Cu-sample in the following context.



  §.§.§ Blanks



Instrumental analysis is essential to determine the detection
limit when any pre-treatment is involved. The typical way is to
prepare the blank solution (called blank in the following context),
which should be prepared by following exactly the same procedure as
that for the sample, but without the sample.
For instance, the starter solution for the Cu-sample
is a certain amount of solution; thus, the starter
solution for the blank is the equivalent amount of nitric
acid to make that solution.
The contamination introduced from air, vessels,
water, and reagents can be estimated by blank measurements.



  §.§.§ Pre-treatment optimization


For blanks, an equivalent amount of for dissolving Cu is
used to replace the Cu-solution.
The main reaction occurring in the blanks is:

    HNO_3 + NH_3· H_2O → NH_4NO_3 + H_2O.

Different molar rations of nitric acid to ammonia water,
n_ HNO_3:n_ NH_3H_2O =4:5.8, 4:6, 4:6.4, 4:6.6, 4:11.5,
were tested while keeping the Zr concentration 3.5 ppm after
adding all chemicals. The Cu samples were tested under the same Zr
concentration, and the molar ratio of Cu to ammonia water was
chosen to be 1:5.8 and 1:6.4, respectively.
No obvious changes were observed in the recovery efficiencies
with different pH values.
Thus, the molar ration n_ Cu: n_ HNO_3: n_ NH_3H_2O =1:4:5.8
was chosen to dissolve Cu and form Cu ammine complex.
The pH value of the mixture after adding ammonia water and stirring
was monitored, and it was 8.2–9.0 for blanks and 8.5–8.9 for Cu-samples.

The concentration was optimized accordingly.
For blanks, when the Zr concentration during pre-treatment increased
from 1.7 ppm to 3.5 ppm, the recovery efficiencies were
measured to be 70%±3% and 65%±2%, respectively.
For Cu-samples, when Zr concentration was 1.7 ppm,
the recovery efficiency was measured to be 64 ±5%.
Finally, the Zr concentration for the pre-treatment was chosen to
be 1.7 ppm, resulting in 0.026% left in the blank or Cu-sample.

The reaction between metal ions and was quick.
After adding , the freshly formed Zr precipitate was left
in the solution under stirring to form larger particles,
which benefits the following filtration step.
Different stirring times from 1 to 3 h were tested, and
no difference was observed in the measured recovery
efficiencies.



§ INTERFERENCE ANALYSIS



After pre-treatment, the zirconium nitrate will remain in the solution
for both blanks and Cu-samples.
Part of the impurities from Cu or will also remain in the solution.
It is important to evaluate and eliminate the interference
to reduce the error. Typically the sources of interferences for
ICP-MS analysis include non-mass spectroscopic interferences,
spectral interferences, and contamination.



 §.§ Non-mass spectroscopic interference



Non-mass spectral interference is also called physical
interference, and the most critical one in this work is the matrix
effect. For blanks, the main dissolved salts in the solution are
and other metallic nitrates formed by impurities in .
For Cu-samples, the main dissolved salts are almost the same as
the blanks, except for extra metallic nitrates originating from
impurities in the copper.
The content was estimated to be 0.026% by mass.
The content of Cu^2+ ions in the Cu-sample was measured to be
approximately 5×10^-5 g/g, or equivalently 0.015%
by mass.
The maximum concentration of metal ions originating from Cu
impurities was estimated to be 3×10^-5 by mass
when the purity of Cu is 99.995%.
Other metal salts originating from in Cu-samples and blanks
were estimated to be 10^-6–10^-7 by mass.
Thus the TDSs in blanks or Cu-samples were
<0.1% by mass, which is close to the upper limit of
TDSs for ICP-MS measurement <cit.>.
This can be ignored for ordinary analysis, but must be taken
into account for the determination of ultra-trace
concentrations of analytes.

There are several ways to mitigate or eliminate the matrix effect,
such as the internal standard method, standard addition method,
argon gas dilution, and chemical separation method.
As one of the internal standard methods, the isotopic dilution
method allows a relative measurement by adding a known amount
of standard (isotopically enriched form of the analyte) to the
sample and measuring the ratio of analyte to standard.
This can significantly suppress the matrix effect since the
analyte and standard are in the same matrix.
However, the recovery efficiency after pre-treatment
cannot be obtained by using the isotopic dilution method.
To obtain the recovery efficiency and cross-check it,
the standard addition method can be used to simultaneously
determine the efficiencies for both and ,
because the matrix effect for both elements are perfectly matched.
The analysis details of these two methods are described
in Sec. <ref>.



 §.§ Spectral interference


Sources of spectral interference include polyatomic interference and
isobaric interference. Evaluation of the spectral interference
is necessary in this work due to the ultra-low concentration
of and the relatively high content of dissolved salts in blanks
and Cu-samples. For and measurements,
the isobaric interference can be ignored since there is
no isobar for these two isotopes. The polyatomic interference
is analyzed below.

A polyatomic ion can be formed in the plasma, and it can mimic
a monatomic ion with the same mass-to-charge ratio.
In the following, C_m/z are denoted as the measured
counts per second with ICP-MS at a particular
mass-to-charge value m/z.
The ubiquitous types of polyatomic ions,
such as MO^+, MOH^+, MO^2+, MO_2H^+, M^2+,
M_2O^+, and MAr^+, were taken into account,
and such a list could be not complete depending on the
possible presence of other elements.
The possible polyatomic ions that contribute C_233 are
^232ThH^+, ^201Hg^16O^2+,
^200Hg^16O_2H^+, and ^193Ir^40Ar^+.
The concentration of , ^200Hg, ^201Hg
and ^193Ir in Cu-samples was measured to be approximately
10^-12 g/g level or even lower; thus, the
probability of forming these polyatomic ions is quite low.
The Cu-samples and blanks without adding were tested
to check the interference, and the measured C_233 was
3.0±0.0, 2.1±0.9, and 0.2±0.2 for Cu-samples,
blanks, and 5% , respectively.

The polyatomic interference on C_238 cannot be measured
directly because is naturally existing and widely
distributed. Instead, we divided the possible interference into
three groups and theoretically calculated their contributions.
Dedicated tests were performed to verify the calculations;
the details appear below.



  * Group A: ^119Sn_2^+, ^198Hg^40Ar^+, ^111Cd_2^16O^+, ^206Pb^16O_2^+

If any of these polyatomic ions is generated, there will be also
contributions to C_240 if the heaviest atom is replaced
with its natural isotope, as shown in Table <ref>.
Because the element with m/z=240 does not naturally exist,
non-zero C_240 observed by ICP-MS should come from the
polyatomic interference. For each polyatomic ion in group A,
the ratio of C_240 to C_238 is calculated according
to the natural abundances.
Table <ref> shows the measured C_m/z with ICP-MS.
Taking the maximum C_240 and the minimum ratio in
Table <ref>, the interference on C_238 can be
conservatively estimated to be <0.01 ppt.


  * Group B: ^198Pt^40Ar^+

Similar estimation can be applied for ^198Pt^40Ar^+.
If PtAr^+ is generated, the ratios C_234(^194Pt^40Ar^+)/C_238(^198Pt^40Ar^+) and C_235(^195Pt^40Ar^+)/C_238(^198Pt^40Ar^+)
are calculated to be 4.6:1 and 4.7:1, respectively.
Using the measured C_234 and C_235 in Table <ref>,
the projected contribution of ^198Pt^40Ar^+ to C_238
would also be <0.01 ppt.


  * Group C: ^205Tl^16O_2H^+

^205Tl^16O_2H^+ is a polyatomic ion with four atoms.
The ^205Tl concentration in a blank or Cu-sample is low,
and thus the formation of TlO^+ is rare, as shown in the lower part
of Table <ref>, where the measured C_205,
C_219, and C_221 are corresponding to ^205Tl,
^203Tl^16O^+, and ^205Tl^16O^+, respectively.
The possibility of forming four-atomic ions such as
^205Tl^16O_2H^+ is much lower than that of forming TlO^+,
and thus it can be neglected in this assay.


In conclusion, the polyatomic interference on and
measurements for both blanks and Cu-samples are
less than 0.01 ppt. If the uranium in copper
is at the 0.1–1-ppt level, such sources of interference
can be ignored. Furthermore, they can be effectively
subtracted using the blank measurements.







 §.§ contaminations from reagents


Table <ref> summarizes the analysis of contamination from various sources,
and lists the required amount of reagents to deal with 3.2 g copper.
According to the used mass and the measured content
of each reagent, ammonia water contributed the largest contamination,
and the standard contributed the least.
had the worst purity, but its contribution
was not significant due to the tiny amount used.
Environmental contamination, due to dust in the air and
surface impurities from labware, was estimated by subtracting
the reagents' contribution from the total.
Although not listed in Table <ref>, the contamination of nitric acid, ammonia water, and were measured
to be <0.01, ∼0.02, and ∼150 ppt, respectively.
For future prospects, we expect to further purify the ammonia
water and and reduce the impurities by a factor of
10 and 100, respectively. Further distillation to nitric acid may
result in a factor-of-2 improvement.
The environmental contamination will be reduced by
at least an order of magnitude with a new class 100 clean laboratory
being built. The total contamination after these improvements is
projected to be within 0.06 ppt, which will significantly improve
the detection limits.





§ RESULTS AND DISCUSSION



The method detection limit (MDL) is defined as the minimum measured
concentration of a substance that can be reported with 99% confidence
so that the measured concentration is distinguishable from the method
blank results.
In this work, the MDL was obtained by following the U.S. Environmental Protection Agency (EPA) process <cit.>. The blanks with
a matrix similar to that of the Cu-samples were prepared by following
the procedures in Sec. <ref>, and then measured with
two independent methods as a cross-check, namely
the isotope dilution method (IDM) and standard addition method (SAM).
As discussed in Sec. <ref>, was used to calibrate the
recovery efficiency during pre-treatment, and the SAM and IDM shared the
same premise that the recovery of and are the same.



 §.§ Isotope dilution method


Isotope dilution analysis is known as an important analytical technique
for the quantification of mass-spectrometric data <cit.>.
It is a relative approach and only involves the measurement of isotopes
of the same element, thus eliminating differences in chemical behavior.
If the isotopes are mixed homogeneously, their ratio is expected not to
change during the entire analytical procedure,
including sample preparation, analyte separation, and enrichment.
In addition, the matrix effect and instability of ICP-MS have exactly
the same influence on each isotope; thus, they have negligible impact on
the result. In this work, a known quantity of Cu-solution
(for Cu-sample) or corresponding (for blank) was mixed
homogeneously with a known amount of standard,
and several parallel samples were prepared and measured.

For isotope dilution analysis, the measured signal ratio of to was used to calculate the introduced during
the pre-treatment of each gram of Cu:

    R = (n_238+n'_238 ) / n'_233,

where R is the measured ratio of to , n_238
is the total not originating from the tracer solution, and
n'_238 and n'_233 are the total and from
the tracer solution, respectively. Note that does not exist
naturally, so it does not appear in the denominator.
Given the measured R and the known n'_233 and n'_238,
n_238 can be easily calculated.
In this assay, for Cu-samples, n_238 was the total amount of originating from Cu and introduced during the pre-treatment,
while, for blanks, n_238 was only the amount of introduced
during the pre-treatment.

The isotope dilution method measures the ratio of to in blanks or Cu-samples, and thus it is necessary to quantify the
recovery efficiency of because it is an important indicator
used to evaluate the effectiveness of the pre-treatment method.
The standard addition method was chosen to quantify the recovery
efficiency, instead of the commonly used external standard method
due to the possible matrix effects mentioned in
Sec. <ref>.



 §.§ Standard addition method


As discussed in Sec. <ref>, the Cu-samples or blanks
in this assay contained certain impurities that may cause a matrix effect.
If using the external standard method, the calibration curve built with
pure standard solutions may result in incorrect data. Thus,
the standard addition method (also see <cit.>),
as one of the internal standard methods,
was applied to solve the matrix effect by adding the standard to
the samples to match the matrix.

A series of and standards with different
concentrations was prepared in advance. The blank or Cu-sample after
pre-treatment was equally divided into four or five sub-samples,
typically 1 g for each sub-sample.
Then, 0.2-g standard solutions with different concentrations of
and were added to the parallel sub-samples of
blanks or Cu-samples.
The final mixtures, namely the test samples, were injected into
the ICP-MS instrument for analysis.
Figure <ref> shows an example of the blank data.
A linear function was used to fit the measured
signals (in counts-per-second unit) versus different added
or contents in the test samples, respectively,
and the ratio of the intercept to the slope represented the
concentration of or in the first test sample
in which the concentration of added or was zero.
Therefore, the concentrations of and in the blanks
could be obtained.
The recovery efficiency of was determined and used to
extrapolate the overall contamination when dealing
each gram of raw Cu.






 §.§ MDL results


Eight re-duplicative blanks were processed and measured, and
Table <ref> shows that a method detection limit of ∼0.1 ppt
is consistently achievable for the two different quantitative methods.
The measured contents versus the recovery
efficiencies are shown in Fig. <ref>,
and no obvious dependency was observed, indicating the robustness of
the pre-treatment and analysis.







§ SUMMARY



A novel co-precipitation method was developed to determine the
trace or ultra-trace amount of in high-purity copper,
and the current MDL could achieve 0.1 ppt.
The matrix effect could be effectively suppressed by using the isotope
dilution method or standard addition method. The interference for
ICP-MS was evaluated to be lower than 0.01 ppt and thus could be
ignored for this assay.
The in copper could be determined by using exactly the
same method and ^229Th as the tracer. Preliminary tests
achieved a similar MDL and recovery efficiency for .

Several efforts are in progress to further improve the MDL.
The cleanness of the pre-treatment lab will be improved to class 100.
A more rigorous validation procedure is being developed to verify the
surface cleanness of the vessels and filter units.
Further purification of ammonia water has been undertaken and preliminary
tests have shown that the purity can be improved by an order of magnitude.
Further purification of should be able to realize at least
a 2-order-of-magnitude improvement by using an ion exchange resin
column or co-precipitation.
An alternative option is to find other co-precipitators that can have
higher purity or can be purified easily.
Nevertheless, along with the above improvements, the sources of
polyatomic interference will become a major factor that affects MDL.
The collision cell incorporated into the ICP-MS setup can be
used to suppress such effects.
Collision reaction cell technology is one of the major breakthroughs
to obviate the polyatomic or isobaric interference for ICP-MS measurement
based on ion-molecule chemistry. The ions entering the multipole
(quadrupole, hexapole or octupole) system will collide or react with
the collision gas, such as H_2 or He. Then, the polyatomic ions can be
changed into interference-free substances, or the elements to be
measured can be turned into other ions that will not cause interference.
Ultimately, the proposed method promises to improve the MDL of and in copper by an order of magnitude. Methods determining
the and in, e.g., other metals, quartz, and silicon,
will be developed in the future as well.



§ ACKNOWLEDGMENT

This work was supported by National Natural Science Foundation of China
(Grant No.11820101005), Strategic Priority Research Program of the Chinese
Academy of Sciences (Grant No. XDA10010500) and
Youth Innovation Promotion Association of CAS (2014008).


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