2
3
This habilitation thesis is a commented selection of my 16 peer-review papers that are
focused on the distribution of elements by laser ablation-based methods. The ability of laser
ablation with mass spectrometry of inductively coupled plasma (LA-ICP-MS) for elemental
distribution is shown on metallic, geological, and biological materials. In the first part, the
development of LA-ICP-MS for identification and description of corrosion processes on Nibased
alloys caused by LiF-NaF mixture is described. For geology, the evolution of the lateral
distribution is monitored from the single spot analysis in specific zones in individual grains to
the imaging of entire grains. The final part is focused on the distribution in biological tissues.
As the distribution of elements by LA-ICP-MS has become a routine analysis, our efforts
have forwarded to the imaging of specific biomolecules. For these purposes, we developed
two ways for molecular imaging – labelling of antibodies by Au nanoparticles and utilisation
of molecularly imprinted polymers (MIPs).
4
First, I would like to express my gratitude to my wife Markéta for her help and support,
without which, none of this would be possible.
During my development from student to scientist, I was lucky enough to have the
opportunity to cooperate with many brilliant scientists and co-workers. Above all I else
would like to name prof. Viktor Kanický, and prof. Vítězslav Otruba.
Thanks also go to my great colleagues, former and current students. Namely, Markéta
Holá, Karel Novotný, Aleš Hrdlička, Míša Tvrdoňová, Lucka Šimoníková and Verča
Dillingerová.
Last but not least, my thanks go to my family and friends.
5
Ab Antibody
CE-LIF Capillary Electrophoresis Laser-Induced Fluorescence
DCC 2,3-dicarboxycellulose
EPMA Electron Probe Micro Analysis
ETV Electro-Thermal Vaporizer
ICP-OES Inductively Coupled Plasma Optical Emission Spectrometry
IR InfraRed
IS Internal Standard
LA-ICP-MS Laser Ablation with Inductively Coupled Plasma Mass Spectrometry
LASER Light Amplification by Stimulated Emission of Radiation
LIP Laser-Induced Plasma
LOD Limit Of Detection
MALDI-MS Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry
MASER Microwave Amplification by Stimulated Emission of Radiation
MeCAT Metal-Coded Affinity Tagging
MeLiM Melanoma-bearing-Libechov-Minipig
MFS Molten Fluoride Salts
MIP Molecularly Imprinted Polymer
MT Metallothionein
Nd:YAG Neodymium-doped Yttrium-Aluminum-Garnet
NIP Non-Imprinted Polymer
NP NanoParticle
PSD Particle Size Distribution
OES Optical Emission Spectrometry
QD Quantum Dots
REE Rare Earth Elements
SSIM Structural Similarity Index Metric
TIMS Thermal-Ionoization Mass Spectrometry
UV UltraViolet
XRF X-Ray Fluorescence
6
1 Introduction ................................................................................................................................ 7
1.1 Structure of the thesis.......................................................................................................... 7
1.2 My contribution to the study of elemental distribution ....................................................... 8
2 Laser ablation ........................................................................................................................... 10
2.1 From bulk to the distribution............................................................................................. 10
2.1.1 Development of lasers................................................................................................... 11
2.2 Suppression of influence of different ablation rate ........................................................... 14
2.2.1 Internal standardisation ................................................................................................. 15
2.2.2 Normalisation on the total sum of oxides...................................................................... 16
2.2.3 Normalisation on the sum of ion intensities .................................................................. 17
2.2.4 Total mass removal........................................................................................................ 17
3 LA-ICP-MS for lateral distribution .................................................................................... 18
3.1 Imaging of corrosion of metallic samples ......................................................................... 20
3.2 Elemental imaging in geology........................................................................................... 21
3.3 Lateral distribution for bio-applications............................................................................ 23
3.3.1 Elemental imaging......................................................................................................... 23
3.3.2 Molecular imaging......................................................................................................... 27
4 Conclusion and Outlook......................................................................................................... 30
5 Literature................................................................................................................................... 32
6 Articles........................................................................................................................................ 36
6.1 Article 1............................................................................................................................. 37
6.2 Article 2............................................................................................................................. 48
6.3 Article 3............................................................................................................................. 55
6.4 Article 4............................................................................................................................. 62
6.5 Article 5............................................................................................................................. 68
6.6 Article 6............................................................................................................................. 81
6.7 Article 7............................................................................................................................. 99
6.8 Article 8........................................................................................................................... 115
6.9 Article 9........................................................................................................................... 124
6.10 Article 10......................................................................................................................... 149
6.11 Article 11......................................................................................................................... 157
6.12 Article 12......................................................................................................................... 171
6.13 Article 13......................................................................................................................... 178
6.14 Article 14......................................................................................................................... 191
6.15 Article 15......................................................................................................................... 198
6.16 Article 16......................................................................................................................... 208
7
The pioneering works devoted to the connection of laser ablation to ICP date back to
the 80s of the 20th
century. The first connection of laser sampling with ICP published by
Thompson et al. in 1981(*)
was carried out with optical detection (ICP-OES). The published
results were very promising with both the absolute limit of detection and the precision
comparable to solution analysis. When Gray first published the connection of laser sampling
with ICP-MS(†)
several problems were found; Gray himself pointed to an inappropriate ICPMS
construction for linking with laser ablation (LA) and the amount of ablated material was so
high that it caused its deposition in a sampler cone. On the other hand, the limit of detection
lower than 1 mg/kg demonstrated the potential of this technique in the future. At that time, ruby
lasers were used for ablation, creating large craters with a diameter of hundreds of μm and
producing a huge amount of ablated material (200 μg/pulse). The LA-ICP was introduced as a
possible quantitative method for analysis of solid samples without dissolution. As the
development of lasers continued, ablation craters became smaller and detection limits at OES
became inadequate. Hence, ICPs with mass detection were able to respond to a decreasing
amount of ablated material. As the information about total content of elements in the sample
may be insufficient for some applications, lateral distribution of elements in the sample is of
interest. Therefore, since the beginning of the 21st
century, the investigation of the spatial
distribution of elements in all possible types of samples has been the focus of LA-ICP-MS.
This work aims to show my contribution to the study of elemental distribution by LAICP-MS
in various types of materials from metallic samples through geological to biological.
This thesis presents collection of 16 peer-reviewed papers published between 2007 and
2020, related to the determination of elemental distribution. As the elemental distribution is
analysed in metallic materials1-4, geological materials5-9, and bio-applications10-16 in the form
of lateral scans or elemental maps, there are two ways to sort the publications: either by type of
distribution – from lateral scans to the elemental mapping, or by type of material. Finally, I
decided to sort them by type of analysed material. For better orientation within the cited papers,
these works are listed as the first 16 papers and are highlighted bold in the text.
*
Thompson, M.; Goulter, J. E.; Sieper, F. Analyst 1981, 106, 32-39.
†
Gray, A. L. Analyst 1985, 110, 551-556.
8
Currently, I have published 74 papers, including 60 journal articles and 14 conference
proceedings. I have chosen 16 research articles related to elemental distribution as a part of my
thesis. My contribution to these articles is summarised in the following tables with special
attention to the experimental work, supervision of students, manuscript preparation and
research direction.
1) Novotny, K.; Vaculovic, T.; Galiova, M.; Otruba, V.; Kanicky, V.; Kaiser, J.; Liska, M.; Samek, O.;
Malina, R.; Palenikova, K. Applied Surface Science 2007, 253, 3834-3842 (IF=5.155)
Experimental work (%) Supervision (%) Manuscript (%) Research direction (%)
20 30 20 10
2) Vaculovic, T.; Sulovsky, P.; Machat, J.; Otruba, V.; Matal, O.; Simo, T.; Latkoczy, C.; Gunther, D.;
Kanicky, V. Journal of Analytical Atomic Spectrometry 2009, 24, 649-654 (IF=3.646)
Experimental work (%) Supervision (%) Manuscript (%) Research direction (%)
20 - 80 -
3) Vaculovic, T.; Warchilova, T.; Simo, T.; Matal, O.; Otruba, V.; Mikuska, P.; Kanicky, V. Journal of
Analytical Atomic Spectrometry 2012, 27, 1321-1326 (IF=3.646)
Experimental work (%) Supervision (%) Manuscript (%) Research direction (%)
30 50 70 30
4) Warchilova, T.; Dillingerova, V.; Skoda, R.; Simo, T.; Matal, O.; Vaculovic, T.; Kanicky, V.
Spectrochimica Acta Part B-Atomic Spectroscopy 2018, 148, 113-117 (IF=3.101)
Experimental work (%) Supervision (%) Manuscript (%) Research direction (%)
10 100 30 80
5) Novak, M.; Gadas, P.; Filip, J.; Vaculovic, T.; Prikryl, J.; Fojt, B. Mineralogy and Petrology 2011,
102, 3-14 (IF=1.573)
Experimental work (%) Supervision (%) Manuscript (%) Research direction (%)
30 - 20 -
6) Bacik, P.; Uher, P.; Ertl, A.; Jonsson, E.; Nysten, P.; Kanicky, V.; Vaculovic, T. Canadian
Mineralogist 2012, 50, 825-841 (IF=1.398)
Experimental work (%) Supervision (%) Manuscript (%) Research direction (%)
30 - 20 -
7) Breiter, K.; Gardenova, N.; Vaculovic, T.; Kanicky, V. Mineralogical Magazine 2013, 77, 403-417
(IF=2.21)
Experimental work (%) Supervision (%) Manuscript (%) Research direction (%)
30 50 20 30
9
8) Vaculovic, T.; Breiter, K.; Korbelova, Z.; Venclova, N.; Tomkova, K.; Jonasova, S.; Kanicky, V.
Microchemical Journal 2017, 133, 200-207 (IF=3.206)
Experimental work (%) Supervision (%) Manuscript (%) Research direction (%)
60 - 90 90
9) Petrík, I.; Janák, M.; Klonowska, I.; Majka, J.; Froitzheim, N.; Yoshida, K.; Sasinková, V.;
Konečný, P.; Vaculovič, T. Journal of Petrology 2020 (IF=3.38)
Experimental work (%) Supervision (%) Manuscript (%) Research direction (%)
30 - 20 10
10) Vaculovic, T.; Warchilova, T.; Cadkova, Z.; Szakova, J.; Tlustos, P.; Otruba, V.; Kanicky, V.
Applied Surface Science 2015, 351, 296-302 (IF=5.155)
Experimental work (%) Supervision (%) Manuscript (%) Research direction (%)
20 60 80 40
11) Anyz, J.; Vyslouzilova, L.; Vaculovic, T.; Tvrdonova, M.; Kanicky, V.; Haase, H.; Horak, V.;
Stepankova, O.; Heger, Z.; Adam, V. Scientific Reports 2017, 7 (IF=4.011)
Experimental work (%) Supervision (%) Manuscript (%) Research direction (%)
15 40 30 30
12) Tvrdonova, M.; Vlcnovska, M.; Vanickova, L. P.; Kanicky, V.; Adam, V.; Ascher, L.;
Jakubowski, N.; Vaculovicova, M.; Vaculovic, T. Analytical and Bioanalytical Chemistry 2019, 411,
559-564 (IF=3.286)
Experimental work (%) Supervision (%) Manuscript (%) Research direction (%)
10 30 50 50
13) Munster, L.; Fojtu, M.; Capakova, Z.; Vaculovic, T.; Tvrdonova, M.; Kuritka, I.; Masarik, M.;
Vicha, J. Biomacromolecules 2019, 20, 1623-1634 (IF=5.667)
Experimental work (%) Supervision (%) Manuscript (%) Research direction (%)
20 40 20 15
14) Vaneckova, T.; Vanickova, L.; Tvrdonova, M.; Pomorski, A.; Krezel, A.; Vaculovic, T.; Kanicky,
V.; Vaculovicova, M.; Adam, V. Talanta 2019, 198, 224-229 (IF=4.916)
Experimental work (%) Supervision (%) Manuscript (%) Research direction (%)
20 40 25 30
15) Vaneckova, T.; Bezdekova, J.; Tvrdonova, M.; Vlcnovska, M.; Novotna, V.; Neuman, J.;
Stossova, A.; Kanicky, V.; Adam, V.; Vaculovicova, M.; Vaculovic, T. Scientific Reports 2019, 9
(IF=4.011)
Experimental work (%) Supervision (%) Manuscript (%) Research direction (%)
15 40 15 30
16) Dumkova, J.; Smutna, T.; Vrlikova, L.; Kotasova, H.; Docekal, B.; Capka, L.; Tvrdonova, M.;
Jakesova, V.; Pelkova, V.; Krumal, K.; Coufalik, P.; Mikuska, P.; Vecera, Z.; Vaculovic, T.;
Husakova, Z.; Kanicky, V.; Hampl, A.; Buchtova, M. ACS nano 2020, 14, 3096-3120. (IF=13.903)
Experimental work (%) Supervision (%) Manuscript (%) Research direction (%)
10 25 10 25
10
The term laser ablation includes a set of events that occur when a laser beam interacts
with the surface of a sample. In time sequence, it is the absorption of laser radiation, the
transmission of the radiant energy of laser radiation, the removal of atoms, ions and molecular
fragments from the surface of the sample and their immediate conversion into a form of dry
aerosol. At the same time, the pressure and temperature increases in the surrounding area of the
interaction site. This interaction results in a shock wave and a microplasma formation. The
carrier of analytical information is thus not only a laser-generated aerosol but also laser-induced
plasma (LIP). There are two ways to remove material from the sample surface - thermal
(selective evaporation) and non-thermal (ablation). Selective evaporation occurs when the
power density is less than 106
W.cm-2
, or when the laser pulse width is higher than
microseconds. Ablation is observed when the power density is larger than 109
W.cm-2
and the
laser pulse width is in the order of ns and less. Selective evaporation is manifested by
enrichment of the vapour phase with slightly volatile elements from the surface of the sample.
Thus the composition of the aerosol is different from the solid phase composition, causing
a systematic error in the result. In the case of ablation, the heating of the solid material is so
intense that the evaporation phase is suppressed and the composition of the ablated material is
ideally the same as of the solid phase.
Under optimal conditions, laser ablation can be used not only for quantitative analysis
but also for the investigation of the lateral distribution of elements - imaging as well as
investigation of depth distribution - depth profiling.
The ablated material generated by the explosive interaction of focused laser radiation
with the surface of a specimen is carried by the carrier gas (most commonly helium) into the
plasma torch of the ICP spectrometer where the atomisation of material occurs. The resulting
atoms are excited and ionised. They then enter the evacuated part of the ICP-MS where they
are separated in the analyser by their mass/charge ratio (m/z).
LA-ICP-MS is currently a well-established method whose first use dates back to 1985
when Gray17
introduced a combination of laser ablation with ICP-MS for rock samples that
were compressed into tablets. For this purpose, a ruby laser emitting radiation with
11
a wavelength of 694 nm was used. Since then, the use of LA-ICP has been expanded, and
currently, 7107 original works with the topic “LA-ICP” (excluding reviews, conference
abstracts, etc.) are available on the Web of Science.
The first publications dealing with the use of laser ablation as a method of sampling
for ICP-MS were performed using metallic materials18,19
and geological samples that were
analysed in the form of compressed tablets17,20,21
. The first attempts at semiquantitative analysis
were based on the determination of the relative response of the individual isotopes19,20
, which
were determined experimentally. The relative response depends on the relative representation
of the observed isotope in nature, the volatility of the element and its ionisation energy.
However, for quantification, this method was insufficient and in 1991 Vanheuzen devised
a matrix-matched quantification (matrix-matched standards). This method was based on an
approach where the analysed material was mixed with a binder (graphite and cellulose) and
pressed into a tablet22
or blended with flux and melted in the form of glass beads23
. Utilisation
of both matrix matching methods was affected by considerable problems with memory effects
that complicated quantification: even in the case of tablets, quantification was not possible at
all. Polyatomic interference was the second major problem complicating the quantification that
was revealed in those works22,23
. Despite these problems, the use of matrix-matched calibration
standards has proved successful and has been used to date with various modifications correcting
for systematic errors of determination (e.g. different ablation rates).
The advances in laser ablation as a sampling technique for ICP-MS are closely
connected with the progress of the construction of lasers. The theoretical basis of the laser was
laid in 1917 when Einstein postulated the term stimulated emission in his publication "Zur
Quantentheorie der Strahlung(‡)
." The first device using stimulated emissions was described in
1952 by Basow and Prokhorov, and built by Townes in the same year. It was a predecessor to
the laser - the MASER - Microwave Amplification by Stimulated Emission of Radiation24
. The
first LASER (Light Amplification by Stimulated Emission of Radiation)25
was constructed in
1960 by T.H. Maiman. It was a ruby laser, whose active environment is corundum with the
addition of Cr3+
. This laser belongs to a group of three-level lasers where the efficiency of
radiation generation is low and considerable energy is needed for excitation. For laser ablation,
‡
Einstein A., Phys.Z., 1917, 121-128
12
the ruby laser was used mainly in pioneering work dealing with the combination of laser
ablation with ICP spectrometers, both emission26-28
and mass17,20
. Due to the lower excitation
powers for the generation of laser radiation, Nd:YAG (neodymium-doped yttrium-aluminiumgarnet)
lasers gradually began to emerge. The vast majority of commercial ablation systems are
currently working with Nd:YAG lasers, although their development has been delayed by a few
years compared to the ruby laser. The first Nd:YAG laser was built in 196429
and the first use
for laser ablation in combination with ICP was published in 198530
. Another reason for
replacing ruby lasers was the need for shorter laser radiation wavelengths. Indeed, the effect of
fractionation in laser ablation decreases with shorter wavelength (see Fractionation).
Consequently, excimer lasers are currently used which, depending on the charge, can emit laser
radiation shorter than 200 nm (Table 1). The first excimer laser coupled to the ICP spectrometer
was a XeCl laser31
.
At present, in ablation systems, we can encounter Nd: YAG lasers emitting radiation
at the wavelength of 266, 213, and 193 nm with excimer lasers of different fill types;
ArF (193 nm), XeCl (308 nm), KrF (248 nm) and F2 (157 nm). Jeffries et al. observed that by
using shorter laser radiation (UV) wavelengths when interacting with glass material (NIST610)
fractionation decreases significantly compared to IR laser radiation32,33
. This smaller
fractionation observed at UV ablation was the reason that excimer lasers (XeCl33
, ArF25 34
,
KrF35
, and F2
36
) became increasingly popular. The indisputable advantage of excimer lasers is
the beam profile. In this case, it is "flat-top," which means that the laser radiation energy is the
same at every point of the beam profile. The use of a flat-top profile results in the formation of
a crater, which has not only a flat bottom but also vertical walls. This shape differs significantly
from craters created by solid-state lasers (e.g. Nd:YAG), which have a Gaussian profile - the
energy of the laser radiation is highest in the centre of the beam and decreases towards its edges.
Thus the obtained crater has oblique walls and the diameter of the crater bottom is smaller than
the diameter at the sample surface. Mank et al. described the effect of the aspect ratio - the ratio
of crater depth to crater diameter - on the fractionation and found that if this ratio is greater than
6, the signal is reduced by up to 50%37
. This implies that if a significant decrease in the signal
intensity is observed during a single point ablation, the laser beam diameter has to be reduced.
In addition to adjusting the wavelength of laser radiation, the duration of the laser pulse
is also optimised. In the first works on LA-ICP-MS, lasers with pulse lengths in nanoseconds
(ns-lasers) were used26
. Although the development of lasers moves towards shorter pulse
lengths (picosecond- 38
and femtosecond lasers39
), ns-lasers are still commonly used. If the
energy of the laser pulse is emitted within a shorter time (fs), the selective evaporation of the
13
elements is suppressed. When higher laser pulse energies are used, selective evaporation is
suppressed in both ps and ns lasers40
. Similar conclusions came from Russo et al. even when
comparing ns and fs lasers; they found that lasers working in the UV region reduce fractionation
in the same way as lasers working in the IR region39
. Currently, the development of fs lasers is
moving towards the UV region of radiation because this type of laser (fs-UV - 266 nm) provides
the lowest fractionation phenomena along with more accurate results compared to fs-IR or
ns-UV lasers41
.
Conditions during laser ablation significantly affect the particle size distribution (PSD)
generated by ablation. Ideally, particles generated during laser ablation should be as small as
possible (in tens of nm). Larger particles entering the ICP source are not entirely vaporised and
cannot be completely ionized42
which results in a change in the response of the individual
analytes being measured43
. The changing PSD of the aerosol affects the intensity of the ICPMS
signal, which was demonstrated by inserting an electrothermal vaporiser (ETV) between
the ablation system and the ICP source44
.
The conditions influencing the course of laser ablation include the choice of gas in
which the ablation occurs. This effect on the ICP-MS signal was confirmed by Horn et al.45
,
when comparing the effects of noble gases (Ar, He, Ne) used in LA. It was found that ambient
gas affects PSD45
, the amount of material deposited at the edges of the ablation crater1,45
and
the efficiency of particle transport to ICP. The fact that the choice of ambient gas affects the
ablation processes was also determined by the work of Novotny when the influence of air, He
and Ar was studied. It was found that there is also a significant influence on the course of
emission of microplasma radiation resulting from ablation in dependence on the gas used1.
The crucial problem of LA-ICP-MS, including imaging, is a different ablation rate, but there
are some possibilities on how to correct it (see chapter Suppression of influence of different
ablation rate).
14
When laser radiation interacts with different sample matrices, unequal amounts of
material are released even with the same laser ablation parameters (radiation wavelength,
radiation frequency, beam diameter, radiant energy density, etc.). The different ablation rate is
caused mainly due to the different absorption of laser radiation of a given wavelength by
a different matrix (see Table 1).
material
absorption of radiation of various wavelength (%)
200 nm 500 nm 1000 nm
Fused quartza
8 5 5
MgF2
a
12 4 4
Sapphirea
35 18 18
CaF2
b
10 8 8
Sic
15 8 55
ZnSed
89 95 80
Bor-silicate
glassa
100 8 7
Table 1: Overview of radiation absorption of different wavelengths by different materials
a
C. Fridriech, Precision Micromanufacturing Processes Applied to Miniaturization Technologies, Michigan Technology
University, 1998.
b
http://www.thorlabs.com/NewGroupPage9.cfm?ObjectGroup_ID=3978
c
http://www.thorlabs.com/NewGroupPage9.cfm?ObjectGroup_ID=3979
d
http://www.thorlabs.com/newgrouppage9.cfm?objectgroup_id=3981
This effect is the more significant the longer the wavelength of the laser radiation used,
and as such, the use of shorter laser radiation wavelengths (213, 193 nm) is more appropriate.
Fluctuations in the energy density of the laser radiation contribute to the amount of released
material. Both of these phenomena result in a systematic error of the result. Therefore, certain
ways are available to suppress it. These corrections may be as follows:
a) internal standardisation46
b) normalisation on the total sum of oxides2,47
c) normalisation on the sum of ion intensities48
d) total mass removal11
Each of the listed procedures has its pros and cons, which will be discussed in the
following text.
15
The most common method for compensation of different ablation rates is the utilisation
of internal standard (IS) and it is necessary to know the content of the internal standard in the
sample to be analysed:
𝑤 (𝑋) 𝑐𝑜𝑟𝑟
𝑖
(%) = 𝑤(𝑋)𝑖
×
𝑤 𝐼𝑆
𝑤 𝐸𝑃𝑀𝐴
𝐼𝑆
Where, 𝑤 (𝑋) 𝑐𝑜𝑟𝑟
𝑖
is the content of i-element after compensation of ablation rate, 𝑤(𝑋)𝑖
is the
content of i-element obtained by LA-ICP-MS, 𝑤 𝐼𝑆
is the content of internal standard obtained
by LA-ICP-MS, and 𝑤 𝐸𝑃𝑀𝐴
𝐼𝑆
is the content of the internal standard obtained by an independent
method.
Most commonly, the content of IS is detected by an independent method (e.g. EPMA
- Electron Probe Micro Analysis, XRF - X-Ray Fluorescence, etc.). There are several rules for
choosing a suitable IS that should be followed: 1) An element of a high content (one of the
matrix elements) should be chosen as the IS to minimise the relative error of determination due
to the inaccuracy of the independent method. 2) This element must be detectable by ICP-MS.
Therefore, for example, the use of oxygen as an IS element for the analysis of silicates or
fluorine in the analysis of fluorites is eliminated, even though its content in the samples is the
highest. 3) The distribution of the IS in the sample should be homogeneous to suppress possible
errors caused by different contents of the IS at different locations of the sample. When
a heterogeneous sample is analysed, it is possible to circumvent this condition by performing
the LA-ICP-MS analysis at the same site of the sample as the independent method. This
normalisation method was first used in the determination of impurities REE in geological
material fused to a glass bead, with the IS being strontium23
. Its use leads to a significant
improvement in the precision of the assay. The disadvantage of this method of normalisation is
the necessity to use another, very often expensive method, such as EPMA. Nevertheless, this
method of normalisation is currently one of the most widely used and has many applications,
especially in the analysis of geological samples.
From the view of elemental imaging, this procedure is suitable for imaging of minerals or
metallic materials without corrosion.
16
This normalisation finds application, especially in the analysis of geological samples.
The main reasons for applying normalisation to the sum of contents are two: eliminating the
need to use a complementary method (EPMA, XRF, etc.) or the inability to use IS. As in the
case of internal standardisation, the first step is to use calibration standards, followed by the
recalculation of content into the form of oxides. Then the contents are summed and the
individual contents are multiplied by factor “100/sum of oxide content”:
𝑤(𝑋𝑂) 𝑐𝑜𝑟𝑟
𝑖
(%) = 𝑤(𝑋𝑂)𝑖
×
100
∑ 𝑤(𝑋𝑂)𝑖
Where 𝑤(𝑋𝑂) 𝑐𝑜𝑟𝑟
𝑖
is the content of i-element in the form of oxide after compensation of
ablation rate, 𝑤(𝑋𝑂)𝑖
is the content of i-element in the form of oxide obtained by LA-ICP-MS,
100 means 100 %, and ∑ 𝑤(𝑋𝑂)𝑖
is the sum of all elements in the form of oxide,
Three requirements should be met for the appropriate application of this method;
a) to have information about the matrix composition of the sample, b) ensure the matrix does
not contain elements that are not determinable by ICP-MS and can replace each other
additionally (typically hydroxy- groups replacing phosphate groups in hydroxyapatites). If
these two requirements are met, then the third requirement is the measurement of all matrix and
minor elements contained in the sample. Otherwise, there is a systematic error, and the detected
contents of the measured elements are higher than the actual. If these requirements are met,
then the results obtained by this normalisation are the same as those obtained using the IS8.
It should be noted that the requirement regarding non-determinable elements can be
circumvented, as in the case of elemental imaging in a mica sample8, as follow:
𝑤(𝑋𝑂) 𝑐𝑜𝑟𝑟 = 𝑤(𝑋𝑂) ×
(100 − 𝑌)
∑ 𝑤(𝑋𝑂)
Where Y is the total content of non-determinable elements by LA-ICP-MS (e.g. OH,
F-
)
obtained by EPMA.
Both the above-mentioned methods for suppression of different ablation rates are used
mainly in combination with external calibration.
17
This approach for the compensation of different ablation rates is suitable for a simple
matrix with a well-defined composition as are e.g. alloys49
, and metallic samples2-4 (corroded
and intact surface). It is based on the measurement of isotopes of all major and minor
elements and recalculation of their measured intensities according to their isotope abundance:
𝐼𝑒𝑙𝑒𝑚𝑒𝑛𝑡1 =
𝐼𝑖𝑠𝑜𝑡𝑜𝑝𝑒1
𝑎𝑖𝑠𝑜𝑡𝑜𝑝𝑒1
𝑤 𝑒𝑙𝑒𝑚𝑒𝑛𝑡1(%) =
𝐼𝑒𝑙𝑒𝑚𝑒𝑛𝑡1
∑ 𝐼𝑒𝑙𝑒𝑚𝑒𝑛𝑡
× 100
Where 𝐼𝑖𝑠𝑜𝑡𝑜𝑝𝑒1 is the measured intensity of isotope, 𝑎𝑖𝑠𝑜𝑡𝑜𝑝𝑒1 is the abundance of the isotope,
𝐼𝑒𝑙𝑒𝑚𝑒𝑛𝑡1 is elemental intensity, and 𝑤 𝑒𝑙𝑒𝑚𝑒𝑛𝑡1 is the content of the element.
The advantage is that it is not necessary to use external calibration. On the other
hand, this approach works well when the degree of ionisation is close to 100 %. This means
that the ionisation energy of the element should be lower than 8 eV – at this ionisation energy,
the ionisation efficiency is about 95 %50
.
The final method for compensating for the different ablation rate is completely
different from the previous ones. This way is based on the sample preparation and it is mainly
suitable for biosamples11,13. Soft tissue sections are cut with a thickness that allows laser
radiation to penetrate the whole thickness of the cut and to reach the substrate (e.g. glass slide).
If the substrate is reached in every spot of the tissue section, it means that the sample has been
removed completely and the influence of the different ablation rate was suppressed
successfully. To verify the total mass removal was reached, it is useful to monitor some isotope
released from the substrate (mostly Si from glass substrate11).
18
As mentioned above, the development of lasers was directed towards shorter
wavelength (from 1064 to 193 nm for Nd:YAG and ArF laser, respectively) and the related
creation of smaller craters. The reduction of the crater size offered the possibility of a new type
of laser ablation-based analysis. These can be divided into two groups depending on the amount
of ablated material (spot size): a) bulk analysis; and b) spatially resolved analysis. The second
one is a very attractive method that allows the gathering of information on the content of the
element as well as its distribution within the analysed sample. The distribution information can
be beneficial in detecting changes in the development of rocks and crystals, the study of
corrosion changes in metallic materials and, last but not least, in studying changes in different
biological materials, as shown below. The beginnings of LA-ICP-MS were mainly concerned
with geological samples. Therefore, it is not surprising that the first study on the lateral
distribution of the elements was carried out on a geological sample. In 1992, Imai showed the
possibility of determination of distribution on the sample of stalactite where they reported
concentration changes of 25 elements (from Mg to U)51
. Shortly after that, Chenery and Cook
performed a lateral scan over the monazite grain and compared the LA-ICP-MS results from
the individual zones to the EPMA results52
. Lateral scanning was performed as a profile of
individual points whose distance was significantly larger than their diameter.
However, in the case of really heterogeneous materials, the use of a single profile is
insufficient. There is a plenty of missing information about the elemental content in the rest of
the sample. The need to know the information about the content of the elements in the whole
sample surface increased and thus a study in which the ablation spots covered a larger portion
of the sample surface was of interest. Pioneering work devoted to elemental imaging was done
on leaves53
. The leaf surface was divided into 70 fields. Each of them was analysed by four
ablation spots and the signals from these spots were averaged. However, this procedure is not
typical for the elemental imaging as we know it now. Today, a line by line or spot by spot
approach is used to cover the whole sample surface. From this point of view, the first elemental
imaging work was done on sheep liver by Kindness in 200354
. Over the next 16 years, LA-ICPMS
imaging has undergone dramatic developments in map quality (resolution improvement
and display), acceleration of imaging, 3D mapping and the ability to map not only elements but
also molecules (Fig. 1).
19
Fig.1: Development of LA-ICP-MS imaging from pioneering work54
(a) to 3D model55
(b), sub-micron
resolution56
(c) and imaging of proteins57
(d).
1a 1b
1c
1d
20
Determination of lateral distribution in our laboratory started with analysis of metallic
samples. This was in relation to the cooperation with the company Energovýzkum Ltd., whose
focus was on the development of new materials for a new type of nuclear reactor – Generation
IV. As one of them uses molten fluoride salts (MFS) for cooling, the aim of the study was to
monitor the progress of corrosion in the presence of MFS.
The MFS represents media of an extremely corrosive and invasive nature, which
highly affects the properties of the reactor vessel. The tested candidate materials were treated
to 680 °C for up to 1000 h in presence of MFS and the surface was subsequently analysed in
order to investigate the corrosion process.
Our first publication was devoted to the corrosion caused by MFS treatment and LAICP-MS
was used for the determination of the thickness of the corrosion layer2. For this
purpose, a single line scan across the corrosion layer into the intact material was made and the
thickness of the corroded layer was measured according to Na and Li presence in the sample.
Inconel A686 and stainless steel 1.4571 were exposed to a LiF-NaF mixture at 680 °C for 380
and 1000 h. In comparison to EPMA, LA-ICP-MS showed a better ability to determine the
thickness of the corroded layer, which relates to the inability of EPMA to measure Li and
significantly worse LOD for Na. On the other hand, a significantly worse lateral resolution was
achieved. Hence, the laser beam diameter was reduced in the following research to improve the
lateral resolution.
As the LA-ICP-MS has proved to be suitable for the determination of the thickness of
the corroded layer, the method was developed to identify the corrosion damage and elemental
changes in structural materials. For this purpose, three candidates of structural materials were
tested (nickel, Ni-based alloy, and nickel-coated iron). Both LA-ICP-MS (the thickness of the
corroded layer) and ICP-OES (the content of the corrosion products) identified nickel as the
most resistant material3. When the more detailed view on the content of the corrosion products
was applied, the conspicuous enrichment of Fe was found for nickel-coated iron. This was
caused by preferential corrosion of the steel substrate that occurred by MFS penetration through
the nickel coating to the iron substrate as seen in Fig. 2.
21
Part of the sponge-like corroded area shown in Fig. 2 was subjected to quantitative
elemental mapping to demonstrate the penetration of MFS into the exposed specimen and to
show relative depletion or enrichment of constituents in the structural material by EPMA and
LA-ICP-MS4. Full-reference objective image quality metrics were performed for the
quantitative comparison of EPMA and LA-ICP-MS elemental maps. These methods compare
the original image with distorted images using the structural similarity index metric (SSIM).
According to this SSIM, the EPMA and LA-ICP-MS maps are similar (not yet published
results).
Our studied system is very specific; however the developed imaging method could be
successfully used in other studies, e.g. development of alloys for implants. Most often implants
based on Ti-, Ti-Ni- or Zr-alloys and are placed into bones and teeth. Hence, the release of the
elements from the developed implants into the tissues could be determined.
The beginning of LA-ICP-MS analysis in geological samples in our laboratory was
concerned with single spot analysis without any relation to the distribution. However, since
2011, there have been demands for analysis of specific zones in individual grains (e.g. zoned
beryl 5, or tourmaline crystals6) and various minerals (quartz, feldspar, zinnwaldite, topaz)7.
These requests led to the development of imaging methods for geological samples. As a crucial
problem, the quantification of the elemental maps of heterogeneous samples (e.g. zoned
muscovite) was identified8. When the mineral grain is imaged, the internal standardisation can
be successfully used, if the content of the internal standard is uniform. However, our muscovite
samples (from Argemela) contained two different zones (Fig. 3a) with non-uniform content of
any elements. Hence, the normalisation using IS (chapter 2.2.1) is not applicable in this case.
Moreover, the zones differ in the content of species non-determinable by ICP-MS (F, OH, etc.).
Fig. 2: Similarlity of LA-ICP-MS and EPMA elemental maps
22
For this purpose, the modified normalisation on the total sum of oxides had to be developed.
The LA-ICP-MS imaging found the enrichment of Li, Rb, and Mn in the rim, whereas the core
is enriched by Fe and Al (Fig. 3). The trueness of LA-ICP-MS results was confirmed by EPMA
analysis.
Fig. 3: Cathodo-Luminiscence (CL) (a) and Back Scattered Electron (BSE) (b) images of muscovite
grain. The circle and ellipse mark the core and rim, respectively. LA-ICP-MS elemental maps of Li2O
(0-4 %m/m), Rb2O (0-0.8 %m/m), Fe2O3 (0-3 %m/m), and Al2O3 (20-50 %m/m)
A combination of lateral profiling and imaging was used for the analysis of garnet and
monazite grains from Seve Nappe (Sweden)9. As the content of SiO2 is homogeneous across
whole grains, the Si could be used as the internal standard. LA-ICP-MS investigation was
focused on the REE profile in various parts of the samples. As follows from the obtained results,
Li2O
Al2O3
Rb2O
Fe2O3
23
the REE profiles vary very strongly depending not only on the minerals (monazite, apatite or
garnet) but across the garnet as well.
The advantages of LA-ICP-MS imaging are very similar as at comparison of EPMA and
LA-ICP-MS individual spot analysis: speed, very low LODs, and an ability to determine light
elements as e.g. Li, and B. This means the determination of the lateral distribution of elements
from Li to U in levels of hundreds µg/g. As the ICP-MS measures isotopes, the main advantage
of LA-ICP-MS imaging lies in the possibility to determine the lateral distribution of isotopic
ratios. The most often used isotopic ratios relate to geochronology U-Th-Pb58
. It is true that
Thermal-Ionisation Mass Spectrometry (TIMS) provides much more accurate determination of
the age, however there is no possibility of lateral resolution. And this is the gap that can be
filled by LA-ICP-MS imaging – dating of highly zoned minerals e.g. zircons.
In recent years, the interest in the determination of elements in biological samples by
LA-ICP-MS has increased significantly. It relates to the fact that many processes in biology are
driven by the exchange of elements, which results in a change of their content and lateral
distribution. As the content of these elements is, in some cases, very low (at the level of mg/kg)
and the changes in distribution are in the level of tens of μm, the LA-ICP-MS is one of the few
methods that can be used for this purpose.
As the lateral resolution and limit of detection are two crucial parameters in imaging,
the influence of the laser ablation parameters such as laser beam diameter, scan speed, and
repetition rate were studied10. Laser repetition rate and laser fluence were investigated in the
tapeworm thin-section to attain optimum ablation rate, yielding an appropriately low detection
limit which complies with elemental contents in the tissue. The effect of combinations of laser
spot size and scan speed on relative broadening (Δwrel) of the image of the ablated pattern (line)
was investigated with the aim to quantify the trueness of imaging. The Δwrel is strongly reduced
(down to 2%) at low scan speed (10 μm s−1
) and a laser spot diameter of 10 μm but results in
an unacceptably long time of mapping (up to 3000 min).
24
Next, the potential of the LA-ICP-MS imaging was demonstrated in the study that
determined Zn and Cu levels in the development of spontaneous regression in melanoma tissue
in MeLiM (Melanoma-bearing-Libechov-Minipig) model (Fig. 4A)11. Two cryosections were
sliced from tissue (Fig. 4B). A thin slice (8 µm) was used for histological analysis to find
uniform spots - red - normally growing melanoma tissue, violet - early spontaneous regression,
yellow - late spontaneous regression and green - fibrous tissue. The thicker slice (30 µm) was
photographed (Fig. 4C) and analysed by LA-ICP-MS (Fig. 4D). The slices were registered in
two steps. Firstly, the elemental maps were registered with slice photography and secondly; the
result of the first step was registered with the histological scan. The registration is based on
silhouette registration. The output of the process is a layered representation of the tissue
consisting of the histological layer with selected spots and metal layers. The layered
representation of all tissues was statistically evaluated. Our data confirm the hypothesis that the
content of zinc in the zone of growing melanoma tissue is significantly higher than in all
remaining zones.
Fig. 4: A schematic description of the transformation process from cryosections to matched layers
interpretation11
25
In addition to the distribution of bio-elements in tissues, we can also determine the
distribution of xenobiotics as Pt-based cytostatics13 or Pb-based nanoparticles16. LA-ICP-MS
imaging was successfully used in the study where the influence of selectively oxidised cellulose
(2,3-dicarboxycellulose – DCC) as a carrier of cisplatin cytostatics (cis-Pt) was compared to
bare cis-Pt treatment13. It was found that utilisation of DCC- cis-Pt affects the distribution of Pt
in tumour tissue. When the mice were treated by cis-Pt, the Pt was localized in the whole tumour
(Fig. 5a) and the content of Pt in the majority of the tumour was between 2.5 and 7.5 mg/kg. In
contrast, the utilisation of DCC-cis-Pt led to the accumulation of Pt in the centre of the tumour
(Fig. 5b) with the content of Pt about 20 mg/kg.
Fig. 5: Distribution of Pt in tumour tissue after treatment by cis-Pt (a) and DCC-cis-Pt (b). The red
dashed line represents the boundary of the tumour tissue13
In the last research, LA-ICP-MS was used for determination of the distribution of Pb
and Pb nanoparticles in mice tissues exposed to treatment by PbO nanoparticles16. A new
method for the imaging of the nanoparticles had to be developed in this study. Moreover, using
this method, we were able to distinguish between Pb in ionic or nanoparticle form. The main
focus of this study was to identify differences in the ability to clear the inhaled PbO NPs from
secondary target organs (clearance). Hence the lateral distribution was determined in lung, liver
and kidney tissues after PbO treatment and clearance. The clearance of ionic lead and PbO NPs
(Pb/PbO NPs) from the lungs and liver was very effective, with the lead being almost eliminated
from the lungs and the physiological state of the lung tissue conspicuously restored. Kidneys
exposed to nanoparticles did not exhibit serious signs of damage; however, LA-ICP-MS
uncovered a certain amount of lead located preferentially in the kidney cortex even after
a clearance period (Fig. 6).
26
As follows from the above-mentioned results, the information regarding elemental
distribution is very useful, especially in the case of monitoring xenobiotics (e.g. Pt and Pb). While
the origins and species of these xenobiotics can be well recognisable, in the case of natively
present elements, the situation is much more complicated. These elements are present in the
organism usually in the form of metalloproteins. For example, there are more than 3000 Znbinding
metalloproteins, each of which is related to a different process in the organism.
Furthermore, Zn is often bound to other biomolecules including nucleic acids. Hence, our other
work was focused on the development of a bio-recognition tool, allowing the determination of
the specific biomolecules by ICP-MS (i.e. molecular imaging).
Fig. 6: Lead distribution in lung, liver, and kidney at designated time points after PbONPs inhalation.
27
The real breakthrough of LA-ICP-MS in life sciences is the combination of molecularlyspecific
tools that allow the determination of biomolecules (e. g. proteins, nucleic acids, etc.).
Such tools applicable to biomolecular recognition include mainly antibodies (Ab), aptamers,
and/or molecularly imprinted polymers (MIPs). Utilisation of metal-containing labels for Ab
offered the possibility of the use of ICP-MS detection. The group of metal-containing tags
includes mostly metal-containing molecules59
, chelates60,61
, and nanoparticles62,63
.
A method for the determination of proteins by labelling the antibody with gold
nanoparticles (AuNPs) (10 and 60 nm) with detection by LA-ICP-MS12 was developed.
Additionally, the AuNPs labelling strategy (Fig. 7) was compared with commercially available
labelling reagents based on MeCAT (metal coded affinity tagging). Proof of principle
experiments based on dot blot experiments were performed using anti-IgG and IgG as the model
analyte. The two labelling probes (MeCAT and AuNPs) were compared by sensitivity and limit
of detection (LOD). The absolute LODs achieved were in the range of tens of picograms for
AuNP labelling compared to a few hundred picograms by the MeCAT labelling12.
Fig. 7: The workflow of a dot-blot immunoassay with the labelled Ab by Au-NPs and MeCAT.14
The second approach for the determination of specific biomolecules is the use of MIP
as the biorecognition tool. MIP was used as the selector for the determination of metallothionein
28
(MT) with mass spectrometric detection (matrix-assisted laser desorption/ionization mass
spectrometric detection - MALDI-MS and LA-ICP-MS)14. This method, for the first time,
integrated MIPs as a purification/pre-treatment step with MALDI-MS and LA-ICP-MS for
analysis of MTs (Fig. 8). The prepared MT-imprinted polydopamine layer showed high binding
capacity and specific recognition properties toward the template/analyte. This experimental
setup allowed detection µM concentrations of MT. Such concentrations are present in the blood
of cancer patients and therefore, this approach can be used for clinical studies recognising MT
as a marker of various diseases including tumours. Moreover, two protein isoforms (MT1 and
MT3) were successfully separated. The presented approach not only provides fast and selective
sample analysis but also avoids the limitations of methods based on antibodies (e.g. high price,
cross-reactivity, limited availability in some cases, etc.).
Fig. 8: Workflow of MIP formation, sampling and detection of MT.15
In this work, a MIP-based pseudo-immunoassay using NP-labelled antibody
recognition was introduced and coupled with the sensitive detection technique – LA-ICP-MS15.
Two approaches of specific recognition were tested. The first was based on the
immunolabelling of the analyte captured by the MIP layer. The second approach involved
immunolabelling of the analyte as a first step and the resulting QD-AB-AG complex was
captured by MIP and further analyzed. The double-selective approach comprising of the
glass
substrate
glass substrate
LA-ICP-MS analysis
29
specific immunolabelling reaction combined with isolation by MIP together with the LA-ICPMS
detection represents a viable approach of the IgG detection from a complex sample (LOD
4.2 μg and 1.6 μg, respectively) available for many exciting applications. Considering the
overall time of the LA-ICP-MS analysis not exceeding 23 s (scan speed of 2000 μm/s),
LA-ICP-MS is a promising technology to be used in future in conjunction with MIP technology.
Biorecognition elements (antibodies, aptamers, and MIPs) represent a unique possibility
to combine excellent sensitivity and multi-analyte detection of ICP-MS and the ability to
determine specific biomolecules. Fluorescence detection, a well-established method for
determination of biomolecules based on fluorescence probes offer excellent sensitivity,
however, multiplexing capability is limited due to the spectral overlap of the probes. Because
of minimal isobaric interference (equivalent to spectral overlap) in ICP-MS the multi-analyte
detection is limited only by the number of available labels (REEs, Au, Ag, etc.). Moreover, as
follows from our results, utilisation of NPs as the labels improve the sensitivity significantly.
As any target (ions, molecules, bacteria, nanoparticles) can be imprinted into an appropriate
polymer, the MIP technology can be successfully used for the determination of not only proteins
but also others analytes (e.g. metabolites, whole cells, etc.).
30
As shown above, LA-ICP-MS offers a great possibility to track elemental changes in
any type of material from corroded metals through geological samples to biomaterials. The
imaging of each of the studied materials has specific problems that have to be solved. The main
problem common to all is the different ablation rate. As we have successfully suppressed this
(using different normalisations or total mass removal), LA-ICP-MS elemental imaging is now
a routine matter in our laboratory.
In order not to rest on our laurels, our research is focused on the determination of
specific biomolecules by LA-ICP-MS. For this purpose, we use antibodies labelled by Au-NPs,
which improve the sensitivity significantly and MIPs. Our works with MIPs are the first
publications utilising the combination of MIPs with LA-ICP-MS detection.
The future of LA-ICP-MS imaging goes in two directions. The first is to improve the
lateral resolution and shorten the analysis time so that we get the multi-element maps of several
megapixels in the order of dozens minutes at the most. In this case, the solution is not only the
construction of ablation cells with a low dispersion but also the data and image processing. The
31
second direction is to use biorecognition tools not only for the determination of proteins but of
any type of molecule. As many labels (Au, Ag, REE, etc.) can be used for labelling, LA-ICPMS
offers the possibility of multi-molecule imaging. The combination of both directions will
lead to multi-target imaging with sub-micron resolution within several minutes, which will be
the last step to LA-ICP-MS becoming a molecular microscope. The ability to determine several
analytes and their lateral distribution during one analysis opens the door into clinical, diagnostic
and medicinal applications.
I believe that our contribution to elemental and molecular imaging will lead to this
future.
32
(1) Novotny, K.; Vaculovic, T.; Galiova, M.; Otruba, V.; Kanicky, V.; Kaiser, J.; Liska, M.;
Samek, O.; Malina, R.; Palenikova, K. Applied Surface Science 2007, 253, 3834-3842.
(2) Vaculovic, T.; Sulovsky, P.; Machat, J.; Otruba, V.; Matal, O.; Simo, T.; Latkoczy, C.;
Gunther, D.; Kanicky, V. Journal of Analytical Atomic Spectrometry 2009, 24, 649-654.
(3) Vaculovic, T.; Warchilova, T.; Simo, T.; Matal, O.; Otruba, V.; Mikuska, P.; Kanicky, V.
Journal of Analytical Atomic Spectrometry 2012, 27, 1321-1326.
(4) Warchilova, T.; Dillingerova, V.; Skoda, R.; Simo, T.; Matal, O.; Vaculovic, T.; Kanicky,
V. Spectrochimica Acta Part B-Atomic Spectroscopy 2018, 148, 113-117.
(5) Novak, M.; Gadas, P.; Filip, J.; Vaculovic, T.; Prikryl, J.; Fojt, B. Mineralogy and
Petrology 2011, 102, 3-14.
(6) Bacik, P.; Uher, P.; Ertl, A.; Jonsson, E.; Nysten, P.; Kanicky, V.; Vaculovic, T. Canadian
Mineralogist 2012, 50, 825-841.
(7) Breiter, K.; Gardenova, N.; Vaculovic, T.; Kanicky, V. Mineralogical Magazine 2013, 77,
403-417.
(8) Vaculovic, T.; Breiter, K.; Korbelova, Z.; Venclova, N.; Tomkova, K.; Jonasova, S.;
Kanicky, V. Microchemical Journal 2017, 133, 200-207.
(9) Petrík, I.; Janák, M.; Klonowska, I.; Majka, J.; Froitzheim, N.; Yoshida, K.; Sasinková,
V.; Konečný, P.; Vaculovič, T. Journal of Petrology 2020.
(10) Vaculovic, T.; Warchilova, T.; Cadkova, Z.; Szakova, J.; Tlustos, P.; Otruba, V.;
Kanicky, V. Applied Surface Science 2015, 351, 296-302.
(11) Anyz, J.; Vyslouzilova, L.; Vaculovic, T.; Tvrdonova, M.; Kanicky, V.; Haase, H.;
Horak, V.; Stepankova, O.; Heger, Z.; Adam, V. Scientific Reports 2017, 7.
(12) Tvrdonova, M.; Vlcnovska, M.; Vanickova, L. P.; Kanicky, V.; Adam, V.; Ascher, L.;
Jakubowski, N.; Vaculovicova, M.; Vaculovic, T. Analytical and Bioanalytical Chemistry
2019, 411, 559-564.
(13) Muenster, L.; Fojtu, M.; Capakova, Z.; Vaculovic, T.; Tvrdonova, M.; Kuritka, I.;
Masarik, M.; Vicha, J. Biomacromolecules 2019, 20, 1623-1634.
(14) Vaneckova, T.; Vanickova, L.; Tvrdonova, M.; Pomorski, A.; Krezel, A.; Vaculovic, T.;
Kanicky, V.; Vaculovicova, M.; Adam, V. Talanta 2019, 198, 224-229.
(15) Vaneckova, T.; Bezdekova, J.; Tvrdonova, M.; Vlcnovska, M.; Novotna, V.; Neuman, J.;
Stossova, A.; Kanicky, V.; Adam, V.; Vaculovicova, M.; Vaculovic, T. Scientific Reports
2019, 9.
(16) Dumkova, J.; Smutna, T.; Vrlikova, L.; Kotasova, H.; Docekal, B.; Capka, L.;
Tvrdonova, M.; Jakesova, V.; Pelkova, V.; Krumal, K.; Coufalik, P.; Mikuska, P.; Vecera, Z.;
33
Vaculovic, T.; Husakova, Z.; Kanicky, V.; Hampl, A.; Buchtova, M. ACS nano 2020, 14,
3096-3120.
(17) Gray, A. L. Analyst 1985, 110, 551-556.
(18) Arrowsmith, P. Analytical Chemistry 1987, 59, 1437-1444.
(19) Hager, J. W. Analytical Chemistry 1989, 61, 1243-1248.
(20) Mochizuki, T.; Sakashita, A.; Iwata, H.; Kagaya, T.; Shimamura, T.; Blair, P. Analytical
Sciences 1988, 4, 403-409.
(21) Imai, N. Analytica Chimica Acta 1990, 235, 381-391.
(22) Vanheuzen, A. A.; Morsink, J. B. W. Spectrochimica Acta Part B-Atomic Spectroscopy
1991, 46, 1819-1828.
(23) Vanheuzen, A. A. Spectrochimica Acta Part B-Atomic Spectroscopy 1991, 46, 1803-
1817.
(24) Engst, P.; Horák, M. Aplikace laserů; SNTL: Praha, 1989.
(25) Maiman, T. H. Nature 1960, 187, 493-494.
(26) Thompson, M.; Goulter, J. E.; Sieper, F. Analyst 1981, 106, 32-39.
(27) Hale, M.; Thompson, M. Transactions of the Institution of Mining and Metallurgy
Section B-Applied Earth Science 1983, 92, B23-B27.
(28) Ishizuka, T.; Uwamino, Y. Spectrochimica Acta Part B-Atomic Spectroscopy 1983, 38,
519-527.
(29) Geusic, J. E.; Marcos, H. M.; Vanuitert, L. G. Applied Physics Letters 1964, 4, 182-&.
(30) Cremers, D. A.; Archuleta, F. L. Proceedings of the Society of Photo-Optical
Instrumentation Engineers 1985, 540, 542-546.
(31) Tremblay, M. E.; Smith, B. W.; Leong, M. B.; Winefordner, J. D. Spectroscopy Letters
1987, 20, 311-318.
(32) Jeffries, T. E.; Pearce, N. J. G.; Perkins, W. T.; Raith, A. Analytical Communications
1996, 33, 35-39.
(33) Bea, F.; Montero, P.; Stroh, A.; Baasner, J. Chemical Geology 1996, 133, 145-156.
(34) Gunther, D.; Frischknecht, R.; Heinrich, C. A.; Kahlert, H. J. Journal of Analytical
Atomic Spectrometry 1997, 12, 939-944.
(35) Borisov, O. V.; Mao, X. L.; Ciocan, A. C.; Russo, R. E. Applied Surface Science 1998,
127, 315-320.
(36) Russo, R. E.; Mao, X. L.; Borisov, O. V.; Liu, H. C. Journal of Analytical Atomic
Spectrometry 2000, 15, 1115-1120.
34
(37) Mank, A. J. G.; Mason, P. R. D. Journal of Analytical Atomic Spectrometry 1999, 14,
1143-1153.
(38) Chan, W. T.; Mao, X. L.; Russo, R. E. Applied Spectroscopy 1992, 46, 1025-1031.
(39) Russo, R. E.; Mao, X. L.; Gonzalez, J. J.; Mao, S. S. Journal of Analytical Atomic
Spectrometry 2002, 17, 1072-1075.
(40) Mao, X. L.; Ciocan, A. C.; Russo, R. E. Applied Spectroscopy 1998, 52, 913-918.
(41) Koch, J.; Gunther, D. Applied Spectroscopy 2011, 65, 155A-162A.
(42) Guillong, M.; Gunther, D. Journal of Analytical Atomic Spectrometry 2002, 17, 831-837.
(43) Figg, D. J.; Cross, J. B.; Brink, C. Applied Surface Science 1998, 127, 287-291.
(44) Vaculovic, T.; Guillong, M.; Binkert, J.; Kanicky, V.; Gunther, D. Canadian Journal of
Analytical Sciences and Spectroscopy 2004, 49, 353-361.
(45) Horn, I.; Gunther, D. Applied Surface Science 2003, 207, 144-157.
(46) Crain, J. S.; Gallimore, D. L. Journal of Analytical Atomic Spectrometry 1992, 7, 605-
610.
(47) Halicz, L.; Gunther, D. Journal of Analytical Atomic Spectrometry 2004, 19, 1539-1545.
(48) Leach, A. M.; Hieftje, G. M. Journal of Analytical Atomic Spectrometry 2000, 15, 1121-
1124.
(49) Latkoczy, C.; Muller, Y.; Schmutz, P.; Gunther, D. Applied Surface Science 2005, 252,
127-132.
(50) Houk, R. S. Analytical Chemistry 1986, 58, A97-&.
(51) Imai, N. Analytica Chimica Acta 1992, 269, 263-268.
(52) Chenery, S.; Cook, J. M. Journal of Analytical Atomic Spectrometry 1993, 8, 299-303.
(53) Hoffmann, E.; Ludke, C.; Skole, J.; Stephanowitz, H.; Ullrich, E.; Colditz, D. Fresenius
Journal of Analytical Chemistry 2000, 367, 579-585.
(54) Kindness, A.; Sekaran, C. N.; Feldmann, J. Clinical Chemistry 2003, 49, 1916-1923.
(55) Paul, B.; Hare, D. J.; Bishop, D. P.; Paton, C.; Van Tran, N.; Cole, N.; Niedwiecki, M.
M.; Andreozzi, E.; Vais, A.; Billings, J. L.; Bray, L.; Bush, A. I.; McColl, G.; Roberts, B. R.;
Adlard, P. A.; Finkelstein, D. I.; Hellstrom, J.; Hergt, J. M.; Woodhead, J. D.; Doble, P. A.
Chemical Science 2015, 6, 5383-5393.
(56) Van Acker, T.; Buckle, T.; Van Malderen, S. J. M.; van Willigen, D. M.; van Unen, V.;
van Leeuwen, F. W. B.; Vanhaecke, F. Analytica Chimica Acta 2019, 1074, 43-53.
(57) Aljakna, A.; Lauer, E.; Lenglet, S.; Grabherr, S.; Fracasso, T.; Augsburger, M.;
Sabatasso, S.; Thomas, A. International journal of legal medicine 2018.
35
(58) Schaltegger, U.; Schmitt, A. K.; Horstwood, M. S. A. Chemical Geology 2015, 402, 89-
110.
(59) Hutchinson, R. W.; Cox, A. G.; McLeod, C. W.; Marshall, P. S.; Harper, A.; Dawson, E.
L.; Howlett, D. R. Analytical Biochemistry 2005, 346, 225-233.
(60) Giesen, C.; Wang, H. A. O.; Schapiro, D.; Zivanovic, N.; Jacobs, A.; Hattendorf, B.;
Schuffler, P. J.; Grolimund, D.; Buhmann, J. M.; Brandt, S.; Varga, Z.; Wild, P. J.; Gunther,
D.; Bodenmillerthat, B. Nature Methods 2014, 11, 417-+.
(61) Giesen, C.; Mairinger, T.; Khoury, L.; Waentig, L.; Jakubowski, N.; Panne, U. Analytical
Chemistry 2011, 83, 8177-8183.
(62) Seuma, J.; Bunch, J.; Cox, A.; McLeod, C.; Bell, J.; Murray, C. Proteomics 2008, 8,
3775-3784.
(63) Baranov, V. I.; Quinn, Z.; Bandura, D. R.; Tanner, S. D. Analytical Chemistry 2002, 74,
1629-1636.
36
Article 1
37
Novotny, K.; Vaculovic, T.; Galiova, M.; Otruba, V.; Kanicky, V.; Kaiser, J.; Liska, M.;
Samek, O.; Malina, R.; Palenikova, K. Applied Surface Science 2007, 253, 3834-3842
(IF=5.155)
Article 1
38
Article 1
39
Article 1
40
Article 1
41
Article 1
42
Article 1
43
Article 1
44
Article 1
45
Article 1
46
Article 1
47
Article 2
48
Vaculovic, T.; Sulovsky, P.; Machat, J.; Otruba, V.; Matal, O.; Simo, T.; Latkoczy, C.;
Gunther, D.; Kanicky, V. Journal of Analytical Atomic Spectrometry 2009, 24, 649-654
(IF=3.646)
Article 2
49
Article 2
50
Article 2
51
Article 2
52
Article 2
53
Article 2
54
Article 3
55
Vaculovic, T.; Warchilova, T.; Simo, T.; Matal, O.; Otruba, V.; Mikuska, P.; Kanicky, V.
Journal of Analytical Atomic Spectrometry 2012, 27, 1321-1326 (IF=3.646)
Article 3
56
Article 3
57
Article 3
58
Article 3
59
Article 3
60
Article 3
61
Article 4
62
Warchilova, T.; Dillingerova, V.; Skoda, R.; Simo, T.; Matal, O.; Vaculovic, T.;
Kanicky, V. Spectrochimica Acta Part B-Atomic Spectroscopy 2018, 148, 113-117
(IF=3.101)
Article 4
63
Article 4
64
Article 4
65
Article 4
66
Article 4
67
Article 5
68
Novak, M.; Gadas, P.; Filip, J.; Vaculovic, T.; Prikryl, J.; Fojt, B. Mineralogy and
Petrology 2011, 102, 3-14 (IF=1.573)
Article 5
69
Article 5
70
Article 5
71
Article 5
72
Article 5
73
Article 5
74
Article 5
75
Article 5
76
Article 5
77
Article 5
78
Article 5
79
Article 5
80
Article 6
81
Bacik, P.; Uher, P.; Ertl, A.; Jonsson, E.; Nysten, P.; Kanicky, V.; Vaculovic, T.
Canadian Mineralogist 2012, 50, 825-841 (IF=1.398)
Article 6
82
Article 6
83
Article 6
84
Article 6
85
Article 6
86
Article 6
87
Article 6
88
Article 6
89
Article 6
90
Article 6
91
Article 6
92
Article 6
93
Article 6
94
Article 6
95
Article 6
96
Article 6
97
Article 6
98
Article 7
99
Breiter, K.; Gardenova, N.; Vaculovic, T.; Kanicky, V. Mineralogical Magazine 2013,
77, 403-417 (IF=2.21)
Article 7
100
Article 7
101
Article 7
102
Article 7
103
Article 7
104
Article 7
105
Article 7
106
Article 7
107
Article 7
108
Article 7
109
Article 7
110
Article 7
111
Article 7
112
Article 7
113
Article 7
114
Article 8
115
Vaculovic, T.; Breiter, K.; Korbelova, Z.; Venclova, N.; Tomkova, K.; Jonasova, S.;
Kanicky, V. Microchemical Journal 2017, 133, 200-207 (IF=3.206)
Article 8
116
Article 8
117
Article 8
118
Article 8
119
Article 8
120
Article 8
121
Article 8
122
Article 8
123
Article 9
124
Petrík, I.; Janák, M.; Klonowska, I.; Majka, J.; Froitzheim, N.; Yoshida, K.; Sasinková,
V.; Konečný, P.; Vaculovič, T. Journal of Petrology 2020 (IF=3.38)
Article 9
125
Article 9
126
Article 9
127
Article 9
128
Article 9
129
Article 9
130
Article 9
131
Article 9
132
Article 9
133
Article 9
134
Article 9
135
Article 9
136
Article 9
137
Article 9
138
Article 9
139
Article 9
140
Article 9
141
Article 9
142
Article 9
143
Article 9
144
Article 9
145
Article 9
146
Article 9
147
Article 9
148
Article 10
149
Vaculovic, T.; Warchilova, T.; Cadkova, Z.; Szakova, J.; Tlustos, P.; Otruba, V.;
Kanicky, V. Applied Surface Science 2015, 351, 296-302 (IF=5.155)
Article 10
150
Article 10
151
Article 10
152
Article 10
153
Article 10
154
Article 10
155
Article 10
156
Article 11
157
Anyz, J.; Vyslouzilova, L.; Vaculovic, T.; Tvrdonova, M.; Kanicky, V.; Haase, H.;
Horak, V.; Stepankova, O.; Heger, Z.; Adam, V. Scientific Reports 2017, 7 (IF=4.011)
Article 11
158
Article 11
159
Article 11
160
Article 11
161
Article 11
162
Article 11
163
Article 11
164
Article 11
165
Article 11
166
Article 11
167
Article 11
168
Article 11
169
Article 11
170
Article 12
171
Tvrdonova, M.; Vlcnovska, M.; Vanickova, L. P.; Kanicky, V.; Adam, V.; Ascher, L.;
Jakubowski, N.; Vaculovicova, M.; Vaculovic, T. Analytical and Bioanalytical
Chemistry 2019, 411, 559-564 (IF=3.286)
Article 12
172
Article 12
173
Article 12
174
Article 12
175
Article 12
176
Article 12
177
Article 13
178
Munster, L.; Fojtu, M.; Capakova, Z.; Vaculovic, T.; Tvrdonova, M.; Kuritka, I.;
Masarik, M.; Vicha, J. Biomacromolecules 2019, 20, 1623-1634 (IF=5.667)
Article 13
179
Article 13
180
Article 13
181
Article 13
182
Article 13
183
Article 13
184
Article 13
185
Article 13
186
Article 13
187
Article 13
188
Article 13
189
Article 13
190
Article 14
191
Vaneckova, T.; Vanickova, L.; Tvrdonova, M.; Pomorski, A.; Krezel, A.; Vaculovic, T.;
Kanicky, V.; Vaculovicova, M.; Adam, V. Talanta 2019, 198, 224-229 (IF=4.916)
Article 14
192
Article 14
193
Article 14
194
Article 14
195
Article 14
196
Article 14
197
Article 15
198
Vaneckova, T.; Bezdekova, J.; Tvrdonova, M.; Vlcnovska, M.; Novotna, V.; Neuman, J.;
Stossova, A.; Kanicky, V.; Adam, V.; Vaculovicova, M.; Vaculovic, T. Scientific
Reports 2019, 9 (IF=4.011)
Article 15
199
Article 15
200
Article 15
201
Article 15
202
Article 15
203
Article 15
204
Article 15
205
Article 15
206
Article 15
207
Article 16
208
Dumkova, J.; Smutna, T.; Vrlikova, L.; Kotasova, H.; Docekal, B.; Capka, L.;
Tvrdonova, M.; Jakesova, V.; Pelkova, V.; Krumal, K.; Coufalik, P.; Mikuska, P.;
Vecera, Z.; Vaculovic, T.; Husakova, Z.; Kanicky, V.; Hampl, A.; Buchtova, M. ACS
nano 2020, 14, 3096-3120. (IF=13.903)
Article 16
209
Article 16
210
Article 16
211
Article 16
212
Article 16
213
Article 16
214
Article 16
215
Article 16
216
Article 16
217
Article 16
218
Article 16
219
Article 16
220
Article 16
221
Article 16
222
Article 16
223
Article 16
224
Article 16
225
Article 16
226
Article 16
227
Article 16
228
Article 16
229
Article 16
230
Article 16
231
Article 16
232
Article 16
233