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Laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) has been revealed as a convenient technique for trace elemental imaging in tissue sections, providing elemental 2D distribution at a quantitative level. For quantification purposes, in the last years several approaches have been proposed in the literature such as the use of CRMs or matrix matched standards. The use of Isotope Dilution (ID) for quantification by LA-ICP-MS has been also described, being mainly useful for bulk analysis but not feasible for spatial measurements so far. In this work, a quantification method based on ID analysis was developed by printing isotope-enriched inks onto kidney slices from rats treated with antitumoral Pt-based drugs using a commercial ink-jet device, in order to perform an elemental quantification in different areas from bio-images. For the ID experiments ¹⁹⁴Pt enriched platinum was used. The methodology was validated by deposition of natural Pt standard droplets with a known amount of Pt onto the surface of a control tissue, where could be quantified even 50 pg of Pt, with recoveries higher than 90%. The amount of Pt present in the whole kidney slices was quantified for cisplatin, carboplatin and oxaliplatin-treated rats. The results obtained were in accordance with those previously reported. The amount of Pt distributed between the medullar and cortical areas was also quantified, observing different behavior for the three drugs.
The goal of this work is to identify the optimal operating input for a lithiation reaction that is performed in a highly innovative pilot scale continuous flow chemical plant in an industrial environment, taking into account the process and safety constraints. The main challenge is to identify the optimum operation in the absence of information about the reaction mechanism and the reaction kinetics. We employ an iterative real-time optimization scheme called modifier adaptation with quadratic approximation (MAWQA) to identify the plant optimum in the presence of plant-model mismatch and measurement noise. A novel NMR PAT-sensor is used to measure the concentration of the reactants and of the product at the reactor outlet. The experiment results demonstrate the capabilities of the iterative optimization using the MAWQA algorithm in driving a complex real plant to an economically optimal operating point in the presence of plant-model mismatch and of process and measurement uncertainties.
This is the first time that PE frits were used to quantify sulfur in copper and its alloys by isotope dilution combined with LA-ICP-MS: an alternative approach for sample preparation. The following properties of the PE frit meet the requirements for isotope dilution LA-ICPMS: porous material, thermo plastic (melting point >100°C), chemical resistance (nitric acid >70%) and high adsorption efficiency. The breakthrough, however, as a support material, especially when comparing the PE frit with other materials such gelatin or sodium silicate is the low blank, which is only two times of the gas flow blank (2.3-4.0 x 10⁴ cps). Additionally, the porosity of the frit was considered, as it directly affects the adsorption efficiency for the sample solution, which is present in the cavities of the frit.
Adsorption efficiency was studied by depositing sulfur standards with varying sulfur amounts (0, 2, 5, 10, 20, 40 and 80 µg S) on the frits. The remaining sulfur which was not absorbed by the frit was rinsed off and was measured by ICP-MS. This indirect method shows that more than 99.5 % of the loaded sulfur was absorbed by the frit. Such high absorption efficiency is completely sufficient for a support material to be used in LA-ICP-IDMS. The so prepared frits with increasing sulfur amount were measured by LA-ICP-MS showing a good linearity between 0 µg S and 40 µg S with a correlation coefficient r2 of 0.9987 and sensitivity of 3.4x10⁴ cps µgˉ¹ for 32S.
Three copper reference materials produced by BAM were selected to develop and validate the LA-ICP-IDMS procedure. The IDMS technique was applied to these samples as follows: the samples were spiked, dissolved, digested and then the digest was adsorbed on the frits.
This is the first time that PE frits were used to quantify sulfur in copper and its alloys by isotope dilution combined with LA-ICP-MS: an alternative approach for sample preparation. The following properties of the PE frit meet the requirements for isotope dilution LA-ICPMS:: porous material, thermo plastic (melting point >100oC), chemical resistance (nitric acid >70%) and high adsorption efficiency. The breakthrough, however, as a support material, especially when comparing the PE frit with other materials such gelatin or sodium silicate is the low blank, which is only two times of the gas flow blank (2.3-4.0 x 104 cps). Additionally, the porosity of the frit was considered, as it directly affects the adsorption efficiency for the sample solution, which is present in the cavities of the frit.
Adsorption efficiency was studied by depositing sulfur standards with varying sulfur amounts (0, 2, 5, 10, 20, 40 and 80 µg S) on the frits. The remaining sulfur which was not absorbed by the frit was rinsed off and was measured by ICP-MS. This indirect method shows that more than 99.5 % of the loaded sulfur was absorbed by the frit. Such high absorption efficiency is completely sufficient for a support material to be used in LA-ICP-IDMS. The so prepared frits whith increasing sulfur amount were measured by LA-ICP-MS showing a good linearity between 0 µg S and 40 µg S whit a correlation coefficient r2 of 0.9987 and sensitivy of 3.4x104 cpsµg-1 for 32S.
Three copper reference materials produced by BAM were selected to develop and validate the LA-ICP-IDMS procedure. The IDMS technique was applied to these samples as follows: the samples were spiked, dissolved, digested and then the digest was adsorbed on the frits.
Background signals from in situ-formed amorphous carbon, despite not being fully understood, are known to be a common issue in few-molecule surface-enhanced Raman scattering (SERS). Here, discrete gold and silver nanoparticle aggregates assembled by DNA origami were used to study the conditions for the formation of amorphous carbon during SERS measurements. Gold and silver dimers were exposed to laser light of varied power densities and wavelengths. Amorphous carbon prevalently formed on silver aggregates and at high power densities. Time-resolved measurements enabled us to follow the formation of amorphous carbon. Silver nanolenses consisting of three differently-sized silver nanoparticles were used to follow the generation of amorphous carbon at the single-nanostructure level. This allowed observation of the many sharp peaks that constitute the broad amorphous carbon signal found in ensemble measurements. In conclusion, we highlight strategies to prevent amorphous carbon formation, especially for DNA-assembled SERS substrates.
The departure from the current automation landscape to next generation automation concepts for the process industry has already begun. Smart functions of sensors simplify their use and enable plug-and-play integration, even though they may appear to be more complex at first sight. Monitoring specific information (i.e., “chemical” such as physico-chemical properties, chemical reactions, etc.) is the key to “chemical” process control. Here we introduce our smart online NMR sensor module provided in an explosion proof housing as example.
Due to NMR spectroscopy as an “absolute analytical comparison method”, independent of the matrix, it runs with extremely short set-up times in combination with “modular” spectral models. Such models can simply be built upon pure component NMR spectra within a few hours (i.e., assignment of the NMR signals to the components) instead of tedious calibrations runs. We present a range of approaches for the automated spectra analysis moving from statistical approach, (i.e., Partial Least Squares Regression) to physically motivated spectral models (i.e., Indirect Hard Modelling and Quantum Mechanical calculations).
Based on concentration measurements of reagents and products by the NMR analyzer a continuous production and direct loop process control were successfully realized for several validation runs in a modular industrial pilot plant and compared to conventional analytical methods (HPLC, near infrared spectroscopy). The NMR analyser was developed for an intensified industrial process funded by the EU’s Horizon 2020 research and innovation programme (“Integrated CONtrol and SENsing”, www.consens-spire.eu).
The departure from the current automation landscape to next generation automation concepts for the process industry has already begun. Smart functions of sensors simplify their use and enable plug-and-play integration, even though they may appear to be more complex at first sight. Monitoring specific information (i.e., “chemical” such as physico-chemical properties, chemical reactions, etc.) is the key to “chemical” process control.
The talk introduces a smart online NMR sensor module provided in an explosion proof housing as example. This sensor was developed for an intensified industrial process (pharmaceutical lithiation reaction step) funded by the EU’s Horizon 2020 research and innovation programme (www.consens-spire.eu). Due to NMR spectroscopy as an “absolute analytical comparison method”, independent of the matrix, it runs with extremely short set-up times in combination with “modular” spectral models. Such models can simply be built upon pure component NMR spectra within a few hours (i.e., assignment of the NMR signals to the components) instead of tedious calibrations runs.
Industry 4.0, IIoT, or Lab 4.0 will enable us to handle more complex processes in shorter time. Intensified production concepts require for adaptive analytical instruments and control technology to realize short set-up times, modular control strategies. They are based on a digitized Laboratory 4.0.
The transition from the current automation landscape to next generation automation concepts for the process industry has already begun. Smart functions of sensors simplify their use and enable plug-and-play integration, even though they may appear to be more complex at first sight. Monitoring specific information (i.e., “chemical” such as physico-chemical properties, chemical reactions, etc.) is the key to “chemical” process control. Here we introduce our smart online NMR sensor module provided in an explosion proof housing as example.
Due to NMR spectroscopy as an “absolute comparison method”, independent of the matrix, it runs with very short set-up times in combination with “modular” spectral models. These are based on pure component NMR spectra without the need for tedious calibrations runs. We present approaches from statistical, (i.e., Partial Least Squares Regression) to physically motivated models (i.e., Indirect Hard Modelling).
Based on concentration measurements of reagents and products by the NMR analyser a continuous production and direct loop process control were successfully realized for several validation runs in a modular industrial pilot plant and compared to conventional analytical methods (HPLC, near infrared spectroscopy). The NMR analyser was developed for an intensified industrial process funded by the EU’s Horizon 2020 research and innovation programme (“Integrated CONtrol and SENsing”, www.consens-spire.eu).
The CLEAN ENERGY Flagship is an initiative designed to utilize recent game changing developments in digital, materials and manufacturing technologies to catalyze a radical paradigm shift towards clean, reliable, efficient and cost-optimal energy.
Unifying and drastically accelerating radically new energy material design, processing and integration across the entire value chain addressing energy production, conversion, storage and systems.
CLEAN ENERGY participants are all distinguished research organisations that each benefit from their own industry networks and contacts with regions and state-level activities and have a long history of collaborating with each other (for 10 years now under the umbrella of EERA) within a European collaborative framework.
Through EERA, CLEAN ENERGY aims to become a crucial partner in the SET-Plan, supporting long-lasting approaches through its established networks and internal collaborations.