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Its properties make copper one of the world’s most important functional metals. Numerous megatrends are increasing the demand for copper. This requires the prospection and exploration of new deposits, as well as the monitoring of copper quality in the various production steps. A promising technique to perform these tasks is Laser Induced Breakdown Spectroscopy (LIBS). Its unique feature, among others, is the ability to measure on site without sample collection and preparation. In this work, copper-bearing minerals from two different deposits are studied. The first set of field samples come from a volcanogenic massive sulfide (VMS) deposit, the second part from a stratiform sedimentary copper (SSC) deposit. Different approaches are used to analyze the data. First, univariate regression (UVR) is used. However, due to the strong influence of matrix effects, this is not suitable for the quantitative analysis of copper grades. Second, the multivariate method of partial least squares regression (PLSR) is used, which is more suitable for quantification. In addition, the effects of the surrounding matrices on the LIBS data are characterized by principal component analysis (PCA), alternative regression methods to PLSR are tested and the PLSR calibration is validated using field samples.
Its properties make copper one of the world’s most important functional metals. Numerous megatrends are increasing the demand for copper. This requires the prospection and exploration of new deposits, as well as the monitoring of copper quality in the various production steps. A promising technique to perform these tasks is Laser Induced Breakdown Spectroscopy (LIBS). Its unique feature, among others, is the ability to measure on site without sample collection and preparation. In this work, copper-bearing minerals from two different deposits are studied. The first set of field samples come from a volcanogenic massive sulfide (VMS) deposit, the second part from a stratiform sedimentary copper (SSC) deposit. Different approaches are used to analyze the data. First, univariate regression (UVR) is used. However, due to the strong influence of matrix effects, this is not suitable for the quantitative analysis of copper grades. Second, the multivariate method of partial least squares regression (PLSR) is used, which is more suitable for quantification. In addition, the effects of the surrounding matrices on the LIBS data are characterized by principal component analysis (PCA), alternative regression methods to PLSR are tested and the PLSR calibration is validated using field samples.
Infrared matrix-assisted desorption and ionization (IR-MALDI) enables the transfer of sub-micron particles (sMP) directly from suspensions into the gas phase and their characterization with differential mobility (DM) analysis. A nanosecond laser pulse at 2940 nm induces a phase explosion of the aqueous phase, dispersing the sample into nano- and microdroplets. The particles are ejected from the aqueous phase and become charged. Using IR-MALDI on sMP of up to 500 nm in diameter made it possible to surpass the 100 nm size barrier often encountered when using nano-electrospray for ionizing supramolecular structures. Thus, the charge distribution produced by IR-MALDI could be characterized systematically in the 50-500 nm size range. Well-resolved signals for up to octuply charged particles were obtained in both polarities for different particle sizes, materials, and surface modifications spanning over four orders of magnitude in concentrations. The physicochemical characterization of the IR-MALDI process was done via a detailed analysis of the charge distribution of the emerging particles, qualitatively as well as quantitatively. The Wiedensohler charge distribution, which describes the evolution of particle charging events in the gas phase, and a Poisson-derived charge distribution, which describes the evolution of charging events in the liquid phase, were compared with one another with respect to how well they describe the experimental data. Although deviations were found in both models, the IR-MALDI charging process seems to resemble a Poisson-like charge distribution mechanism, rather than a bipolar gas phase charging one.
The numerous applications of rare earth elements (REE) has lead to a growing global demand and to the search for new REE deposits. One promising technique for exploration of these deposits is laser-induced breakdown spectroscopy (LIBS). Among a number of advantages of the technique is the possibility to perform on-site measurements without sample preparation. Since the exploration of a deposit is based on the analysis of various geological compartments of the surrounding area, REE-bearing rock and soil samples were analyzed in this work. The field samples are from three European REE deposits in Sweden and Norway. The focus is on the REE cerium, lanthanum, neodymium and yttrium. Two different approaches of data analysis were used for the evaluation. The first approach is univariate regression (UVR). While this approach was successful for the analysis of synthetic REE samples, the quantitative analysis of field samples from different sites was influenced by matrix effects. Principal component analysis (PCA) can be used to determine the origin of the samples from the three deposits. The second approach is based on multivariate regression methods, in particular interval PLS (iPLS) regression. In comparison to UVR, this method is better suited for the determination of REE contents in heterogeneous field samples. View Full-Text
The numerous applications of rare earth elements (REE) has lead to a growing global demand and to the search for new REE deposits. One promising technique for exploration of these deposits is laser-induced breakdown spectroscopy (LIBS). Among a number of advantages of the technique is the possibility to perform on-site measurements without sample preparation. Since the exploration of a deposit is based on the analysis of various geological compartments of the surrounding area, REE-bearing rock and soil samples were analyzed in this work. The field samples are from three European REE deposits in Sweden and Norway. The focus is on the REE cerium, lanthanum, neodymium and yttrium. Two different approaches of data analysis were used for the evaluation. The first approach is univariate regression (UVR). While this approach was successful for the analysis of synthetic REE samples, the quantitative analysis of field samples from different sites was influenced by matrix effects. Principal component analysis (PCA) can be used to determine the origin of the samples from the three deposits. The second approach is based on multivariate regression methods, in particular interval PLS (iPLS) regression. In comparison to UVR, this method is better suited for the determination of REE contents in heterogeneous field samples. View Full-Text
The increasing development of antibiotic resistance in bacteria has been a major problem for years, both in human and veterinary medicine. Prophylactic measures, such as the use of vaccines, are of great importance in reducing the use of antibiotics in livestock. These vaccines are mainly produced based on formaldehyde inactivation. However, the latter damages the recognition elements of the bacterial proteins and thus could reduce the immune response in the animal. An alternative inactivation method developed in this work is based on gentle photodynamic inactivation using carbon nanodots (CNDs) at excitation wavelengths λex > 290 nm. The photodynamic inactivation was characterized on the nonvirulent laboratory strain Escherichia coli K12 using synthesized CNDs. For a gentle inactivation, the CNDs must be absorbed into the cytoplasm of the E. coli cell. Thus, the inactivation through photoinduced formation of reactive oxygen species only takes place inside the bacterium, which means that the outer membrane is neither damaged nor altered. The loading of the CNDs into E. coli was examined using fluorescence microscopy. Complete loading of the bacterial cells could be achieved in less than 10 min. These studies revealed a reversible uptake process allowing the recovery and reuse of the CNDs after irradiation and before the administration of the vaccine. The success of photodynamic inactivation was verified by viability assays on agar. In a homemade flow photoreactor, the fastest successful irradiation of the bacteria could be carried out in 34 s. Therefore, the photodynamic inactivation based on CNDs is very effective. The membrane integrity of the bacteria after irradiation was verified by slide agglutination and atomic force microscopy. The method developed for the laboratory strain E. coli K12 could then be successfully applied to the important avian pathogens Bordetella avium and Ornithobacterium rhinotracheale to aid the development of novel vaccines.
The increasing development of antibiotic resistance in bacteria has been a major problem for years, both in human and veterinary medicine. Prophylactic measures, such as the use of vaccines, are of great importance in reducing the use of antibiotics in livestock. These vaccines are mainly produced based on formaldehyde inactivation. However, the latter damages the recognition elements of the bacterial proteins and thus could reduce the immune response in the animal. An alternative inactivation method developed in this work is based on gentle photodynamic inactivation using carbon nanodots (CNDs) at excitation wavelengths λex > 290 nm. The photodynamic inactivation was characterized on the nonvirulent laboratory strain Escherichia coli K12 using synthesized CNDs. For a gentle inactivation, the CNDs must be absorbed into the cytoplasm of the E. coli cell. Thus, the inactivation through photoinduced formation of reactive oxygen species only takes place inside the bacterium, which means that the outer membrane is neither damaged nor altered. The loading of the CNDs into E. coli was examined using fluorescence microscopy. Complete loading of the bacterial cells could be achieved in less than 10 min. These studies revealed a reversible uptake process allowing the recovery and reuse of the CNDs after irradiation and before the administration of the vaccine. The success of photodynamic inactivation was verified by viability assays on agar. In a homemade flow photoreactor, the fastest successful irradiation of the bacteria could be carried out in 34 s. Therefore, the photodynamic inactivation based on CNDs is very effective. The membrane integrity of the bacteria after irradiation was verified by slide agglutination and atomic force microscopy. The method developed for the laboratory strain E. coli K12 could then be successfully applied to the important avian pathogens Bordetella avium and Ornithobacterium rhinotracheale to aid the development of novel vaccines.
The visible-light photocatalyticE/Zisomerization of olefins can be mediated by a wide spectrum of triplet sensitizers (photocatalysts). However, the search for the most efficient photocatalysts through screenings in photo batch reactors is material and time consuming. Capillary and microchip flow reactors can accelerate this screening process. Combined with a fast analytical technique for isomer differentiation, these reactors can enable high-throughput analyses. Ion mobility (IM) spectrometry is a cost-effective technique that allows simple isomer separation and detection on the millisecond timescale. This work introduces a hyphenation method consisting of a microchip reactor and an infrared matrix-assisted laser desorption ionization (IR-MALDI) ion mobility spectrometer that has the potential for high-throughput analysis. The photocatalyzedE/Zisomerization of ethyl-3-(pyridine-3-yl)but-2-enoate (E-1) as a model substrate was chosen to demonstrate the capability of this device. Classic organic triplet sensitizers as well as Ru-, Ir-, and Cu-based complexes were tested as catalysts. The ionization efficiency of theZ-isomer is much higher at atmospheric pressure which is due to a higher proton affinity. In order to suppress proton transfer reactions by limiting the number of collisions, an IM spectrometer working at reduced pressure (max. 100 mbar) was employed. This design reduced charge transfer reactions and allowed the quantitative determination of the reaction yield in real time. Among 14 catalysts tested, four catalysts could be determined as efficient sensitizers for theE/Zisomerization of ethyl cinnamate derivativeE-1. Conversion rates of up to 80% were achieved in irradiation time sequences of 10 up to 180 s. With respect to current studies found in the literature, this reduces the acquisition times from several hours to only a few minutes per scan.
A new ion mobility (IM) spectrometer, enabling mobility measurements in the pressure range between 5 and 500 mbar and in the reduced field strength range E/N of 5-90 Td, was developed and characterized. Reduced mobility (K-0) values were studied under low E/N (constant value) as well as high E/N (deviation from low field K-0) for a series of molecular ions in nitrogen. Infrared matrix-assisted laser desorption ionization (IR-MALDI) was used in two configurations: a source working at atmospheric pressure (AP) and, for the first time, an IR-MALDI source working with a liquid (aqueous) matrix at sub-ambient/reduced pressure (RP). The influence of RP on IR-MALDI was examined and new insights into the dispersion process were gained. This enabled the optimization of the IM spectrometer for best analytical performance. While ion desolvation is less efficient at RP, the transport of ions is more efficient, leading to intensity enhancement and an increased number of oligomer ions. When deciding between AP and RP IR-MALDI, a trade-off between intensity and resolving power has to be considered. Here, the low field mobility of peptide ions was first measured and compared with reference values from ESI-IM spectrometry (at AP) as well as collision cross sections obtained from molecular dynamics simulations. The second application was the determination of the reduced mobility of various substituted ammonium ions as a function of E/N in nitrogen. The mobility is constant up to a threshold at high E/N. Beyond this threshold, mobility increases were observed. This behavior can be explained by the loss of hydrated water molecules.
The contamination of barley by molds on the field or in storage leads to the spoilage of grain and the production of mycotoxins, which causes major economic losses in malting facilities and breweries. Therefore, on-site detection of hidden fungus contaminations in grain storages based on the detection of volatile marker compounds is of high interest. In this work, the volatile metabolites of 10 different fungus species are identified by gas chromatography (GC) combined with two complementary mass spectrometric methods, namely, electron impact (EI) and chemical ionization at atmospheric pressure (APCI)-mass spectrometry (MS). The APCI source utilizes soft X-radiation, which enables the selective protonation of the volatile metabolites largely without side reactions. Nearly 80 volatile or semivolatile compounds from different substance classes, namely, alcohols, aldehydes, ketones, carboxylic acids, esters, substituted aromatic compounds, alkenes, terpenes, oxidized terpenes, sesquiterpenes, and oxidized sesquiterpenes, could be identified. The profiles of volatile and semivolatile metabolites of the different fungus species are characteristic of them and allow their safe differentiation. The application of the same GC parameters and APCI source allows a simple method transfer from MS to ion mobility spectrometry (IMS), which permits on-site analyses of grain stores. Characterization of IMS yields limits of detection very similar to those of APCI-MS. Accordingly, more than 90% of the volatile metabolites found by APCI-MS were also detected in IMS. In addition to different fungus genera, different species of one fungus genus could also be differentiated by GC-IMS.
Precision agriculture (PA) strongly relies on spatially differentiated sensor information. Handheld instruments based on laser-induced breakdown spectroscopy (LIBS) are a promising sensor technique for the in-field determination of various soil parameters. In this work, the potential of handheld LIBS for the determination of the total mass fractions of the major nutrients Ca, K, Mg, N, P and the trace nutrients Mn, Fe was evaluated. Additionally, other soil parameters, such as humus content, soil pH value and plant available P content, were determined. Since the quantification of nutrients by LIBS depends strongly on the soil matrix, various multivariate regression methods were used for calibration and prediction. These include partial least squares regression (PLSR), least absolute shrinkage and selection operator regression (Lasso), and Gaussian process regression (GPR). The best prediction results were obtained for Ca, K, Mg and Fe. The coefficients of determination obtained for other nutrients were smaller. This is due to much lower concentrations in the case of Mn, while the low number of lines and very weak intensities are the reason for the deviation of N and P. Soil parameters that are not directly related to one element, such as pH, could also be predicted. Lasso and GPR yielded slightly better results than PLSR. Additionally, several methods of data pretreatment were investigated.
Electrospray ionization-ion mobility spectrometry was employed for the determination of collision cross sections (CCS) of 25 synthetically produced peptides in the mass range between 540-3310 Da. The experimental measurement of the CCS is complemented by their calculation applying two different methods. One prediction method is the intrinsic size parameter (ISP) method developed by the Clemmer group. The second new method is based on the evaluation of molecular dynamics (MD) simulation trajectories as a whole, resulting in a single, averaged collision cross-section value for a given peptide in the gas phase. A high temperature MD simulation is run in order to scan through the whole conformational space. The lower temperature conformational distribution is obtained through thermodynamic reweighting. In the first part, various correlations, e.g. CCS vs. mass and inverse mobility vs. m/z correlations, are presented. Differences in CCS between peptides are also discussed in terms of their respective mass and m/z differences, as well as their respective structures. In the second part, measured and calculated CCS are compared. The agreement between the prediction results and the experimental values is in the same range for both calculation methods. While the calculation effort of the ISP method is much lower, the MD method comprises several tools providing deeper insights into the conformations of peptides. Advantages and limitations of both methods are discussed. Based on the separation of two pairs of linear and cyclic peptides of virtually the same mass, the influence of the structure on the cross sections is discussed. The shift in cross section differences and peak shape after transition from the linear to the cyclic peptide can be well understood by applying different MD tools, e.g. the root-mean-square deviation (RMSD) and the root mean square fluctuation (RMSF). (C) 2018 Elsevier B.V. All rights reserved.
The lack of soil data, which are relevant, reliable, affordable, immediately available, and sufficiently detailed, is still a significant challenge in precision agriculture. A promising technology for the spatial assessment of the distribution of chemical elements within fields, without sample preparation is laser-induced breakdown spectroscopy (LIBS). Its advantages are contrasted by a strong matrix dependence of the LIBS signal which necessitates careful data evaluation. In this work, different calibration approaches for soil LIBS data are presented. The data were obtained from 139 soil samples collected on two neighboring agricultural fields in a quaternary landscape of northeast Germany with very variable soils. Reference analysis was carried out by inductively coupled plasma optical emission spectroscopy after wet digestion. The major nutrients Ca and Mg and the minor nutrient Fe were investigated. Three calibration strategies were compared. The first method was based on univariate calibration by standard addition using just one soil sample and applying the derived calibration model to the LIBS data of both fields. The second univariate model derived the calibration from the reference analytics of all samples from one field. The prediction is validated by LIBS data of the second field. The third method is a multivariate calibration approach based on partial least squares regression (PLSR). The LIBS spectra of the first field are used for training. Validation was carried out by 20-fold cross-validation using the LIBS data of the first field and independently on the second field data. The second univariate method yielded better calibration and prediction results compared to the first method, since matrix effects were better accounted for. PLSR did not strongly improve the prediction in comparison to the second univariate method.
Acoustically levitated droplets have been suggested as compartmentalized, yet wall-less microreactors for high-throughput reaction optimization purposes. The absence of walls is envisioned to simplify up-scaling of the optimized reaction conditions found in the microliter volumes. A consequent pursuance of high-throughput chemistry calls for a fast, robust and sensitive analysis suited for online interrogation. For reaction optimization, targeted analysis with relatively low sensitivity suffices, while a fast, robust and automated sampling is paramount. To follow this approach, in this contribution, a direct coupling of levitated droplets to a homebuilt ion mobility spectrometer (IMS) is presented. The sampling, transfer to the gas phase, as well as the ionization are all performed by a single exposure of the sampling volume to the resonant output of a mid-IR laser. Once formed, the nascent spatially and temporally evolving analyte ion cloud needs to be guided out of the acoustically confined trap into the inlet of the ion mobility spectrometer. Since the IMS is operated at ambient pressure, no fluid dynamic along a pressure gradient can be employed. Instead, the transfer is achieved by the electrostatic potential gradient inside a dual ring electrode ion optics, guiding the analyte ion cloud into the first stage of the IMS linear drift tube accelerator. The design of the appropriate atmospheric pressure ion optics is based on the original vacuum ion optics design of Wiley and McLaren. The obtained experimental results nicely coincide with ion trajectory calculations based on a collisional model.
The lack of soil data, which are relevant, reliable, affordable, immediately available, and sufficiently detailed, is still a significant challenge in precision agriculture. A promising technology for the spatial assessment of the distribution of chemical elements within fields, without sample preparation is laser-induced breakdown spectroscopy (LIBS). Its advantages are contrasted by a strong matrix dependence of the LIBS signal which necessitates careful data evaluation. In this work, different calibration approaches for soil LIBS data are presented. The data were obtained from 139 soil samples collected on two neighboring agricultural fields in a quaternary landscape of northeast Germany with very variable soils. Reference analysis was carried out by inductively coupled plasma optical emission spectroscopy after wet digestion. The major nutrients Ca and Mg and the minor nutrient Fe were investigated. Three calibration strategies were compared. The first method was based on univariate calibration by standard addition using just one soil sample and applying the derived calibration model to the LIBS data of both fields. The second univariate model derived the calibration from the reference analytics of all samples from one field. The prediction is validated by LIBS data of the second field. The third method is a multivariate calibration approach based on partial least squares regression (PLSR). The LIBS spectra of the first field are used for training. Validation was carried out by 20-fold cross-validation using the LIBS data of the first field and independently on the second field data. The second univariate method yielded better calibration and prediction results compared to the first method, since matrix effects were better accounted for. PLSR did not strongly improve the prediction in comparison to the second univariate method.
Precision agriculture (PA) strongly relies on spatially differentiated sensor information. Handheld instruments based on laser-induced breakdown spectroscopy (LIBS) are a promising sensor technique for the in-field determination of various soil parameters. In this work, the potential of handheld LIBS for the determination of the total mass fractions of the major nutrients Ca, K, Mg, N, P and the trace nutrients Mn, Fe was evaluated. Additionally, other soil parameters, such as humus content, soil pH value and plant available P content, were determined. Since the quantification of nutrients by LIBS depends strongly on the soil matrix, various multivariate regression methods were used for calibration and prediction. These include partial least squares regression (PLSR), least absolute shrinkage and selection operator regression (Lasso), and Gaussian process regression (GPR). The best prediction results were obtained for Ca, K, Mg and Fe. The coefficients of determination obtained for other nutrients were smaller. This is due to much lower concentrations in the case of Mn, while the low number of lines and very weak intensities are the reason for the deviation of N and P. Soil parameters that are not directly related to one element, such as pH, could also be predicted. Lasso and GPR yielded slightly better results than PLSR. Additionally, several methods of data pretreatment were investigated.
The applications of quantum dots (QDs) in two-photon (2P) excitation applications demand reliable data about their 2P absorption (2PA) cross sections (sigma(2PA)). In the present study, sigma(2PA) values have been determined for a series of commercial colloidal CdSe/ZnS QDs and CdSeTe/ZnS QDs in aqueous media. For the first time for these QDs, the sigma(2PA) values have been determined over a wide spectral range, that is, between 720 and 900 nm, and are compared to the extinction coefficient (epsilon) values obtained under one-photon (1P) excitation. Furthermore, we present a QD in combination with an organic dye in a biotin-streptavidin Forster resonance energy transfer bioassay under 1P and 2P excitation. The results for the bioassay under 2P excitation are compared to those obtained under 1P excitation. The results demonstrate that in the case of the 2P excitation, higher sensitivity can be achieved because of an improved signal-to-noise ratio.
The problem of atmospheric emission from OH molecules is a long standing problem for near-infrared astronomy. PRAXIS is a unique spectrograph which is fed by fibres that remove the OH background and is optimised specifically to benefit from OH-Suppression. The OH suppression is achieved with fibre Bragg gratings, which were tested successfully on the GNOSIS instrument. PRAXIS uses the same fibre Bragg gratings as GNOSIS in its first implementation, and will exploit new, cheaper and more efficient, multicore fibre Bragg gratings in the second implementation. The OH lines are suppressed by a factor of similar to 1000, and the expected increase in the signal-to-noise in the interline regions compared to GNOSIS is a factor of similar to 9 with the GNOSIS gratings and a factor of similar to 17 with the new gratings. PRAXIS will enable the full exploitation of OH suppression for the first time, which was not achieved by GNOSIS (a retrofit to an existing instrument that was not OH-Suppression optimised) due to high thermal emission, low spectrograph transmission and detector noise. PRAXIS has extremely low thermal emission, through the cooling of all significantly emitting parts, including the fore-optics, the fibre Bragg gratings, a long length of fibre, and the fibre slit, and an optical design that minimises leaks of thermal emission from outside the spectrograph. PRAXIS has low detector noise through the use of a Hawaii-2RG detector, and a high throughput through a efficient VPH based spectrograph. PRAXIS will determine the absolute level of the interline continuum and enable observations of individual objects via an IFU. In this paper we give a status update and report on acceptance tests.
Mold fungi on malting barley grains cause major economic loss in malting and brewery facilities. Possible proxies for their detection are volatile and semivolatile metabolites. Among those substances, characteristic marker compounds have to be identified for a confident detection of mold fungi in varying surroundings. The analytical determination is usually performed through passive sampling with solid phase microextraction, gas chromatographic separation, and detection by electron ionization mass spectrometry (EI-MS), which often does not allow a confident determination due to the absence of molecular ions. An alternative is GC-APCI-MS, generally, allowing the determination of protonated molecular ions. Commercial atmospheric pressure chemical ionization (APCI) sources are based on corona discharges, which are often unspecific due to the occurrence of several side reactions and produce complex product ion spectra. To overcome this issue, an APCI source based on soft X-radiation is used here. This source facilitates a more specific ionization by proton transfer reactions only. In the first part, the APCI source is characterized with representative volatile fungus metabolites. Depending on the proton affinity of the metabolites, the limits of detection are up to 2 orders of magnitude below those of EI-MS. In the second part, the volatile metabolites of the mold fungus species Aspergillus, Alternaria, Fusarium, and Penicillium are investigated. In total, 86 compounds were found with GC-EI/APCI-MS. The metabolites identified belong to the substance classes of alcohols, aldehydes, ketones, carboxylic acids, esters, substituted aromatic compounds, terpenes, and sesquiterpenes. In addition to substances unspecific for the individual fungus species, characteristic patterns of metabolites, allowing their confident discrimination, were found for each of the 4 fungus species. Sixty-seven of the 86 metabolites are detected by X-ray-based APCI-MS alone. The discrimination of the fungus species based on these metabolites alone was possible. Therefore, APCI-MS in combination with collision induced dissociation alone could be used as a supervision method for the detection of mold fungi.
In many laser based ionization techniques with a subsequent drift time separation, the laser pulse generating the ions is considered as the start time to. Therefore, an accurate temporal definition of this event is crucial for the resolution of the experiments. In this contribution, the laser induced plume dynamics of liquids evaporating into atmospheric pressure are visualized for two distinctively different laser pulse widths, Delta t = 6 nanoseconds and Delta tau = 280 microseconds. For ns-pulses the expansion of the generated vapour against atmospheric pressure is found to lead to turbulences inside the gas phase. This results in spatial and temporal broadening of the nascent clouds. A more equilibrated expansion, without artificial smearing of the temporal resolution can, in contrast, be observed to follow mu s-pulse excitation. This leads to the counterintuitive finding that longer laser pulses results in an increased temporal vapour formation definition. To examine if this fume expansion also eventually results in a better definition of ion formation, the nascent vapour plumes were expanded into a linear drift tube ion mobility spectrometer (IMS). This time resolved detection of ion formation corroborates the temporal broadening caused by collisional impeding of the supersonic expansion at atmospheric pressure and the overall better defined ion formation by evaporation with long laser pulses. A direct comparison of the observed results strongly suggests the coexistence of two individual ion formation mechanisms that can be specifically addressed by the use of appropriate laser sources.