Search

The electrochemical effects of anisotropic lattice deformation during La0.6Sr0.4FeO3−δ growth by pulsed laser deposition are investigated by in situ impedance spectroscopy.

This study represents the first quantitative assessment of Paracrinoidea using comparative phylogenetics as well as phylomorphospace to understand intraclade relationships.&nbsp

Li0.29La0.57TiO3 (LLTO) is a promising solid electrolyte material with a high Li-ion conductivity. However, its experimental electrochemical stability window is not precisely known, and thus the compatibility with potential electrode materials is partly unclear. In this contribution, we present results from electrochemical and analytical experiments to elucidate the stability of LLTO when being polarized with Li-ion-blocking Pt electrodes. Above 2.5 V, a darkened color front starts moving from the cathode to the anode, leading to electrolyte degradation. While first-principles calculation predict appearance of new phases as decomposition products, we find zones with modified defect chemical properties originating from the anode and cathode. The darkened zone forming at the cathode contains Ti3+ polarons with high mobility, which leads to a mixed ion-electron conductivity, already for a very small Li excess concentration. Next to the anode a spatially very confined, weakly conductive Li depletion zone forms. The spatially confined but substantial Li depletion near the anode could be quantified by analytical laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS). In contrast to first-principles calculations no new phases were found near the anode, according to synchrotron-based grazing incidence XRD measurements.

Alzheimer disease (AD) is an emerging medical problem worldwide without any cure yet. By 2050, more than 152 million people will be affected. AD is characterized by mitochondrial dys-function (MD) and increased amyloid beta (Aβ) levels. Coffee is one of the most commonly consumed beverages. It has many bioactive and neuroprotective ingredients of which caffeine (Cof), kahweohl (KW) and cafestol (CF) shows a variety of pharmacological properties such as anti-inflammatory and neuroprotective effects. Effects of Cof, KW, and CF were tested in a cel-lular model of AD on MD and Aβ. SH-SY5Y-APP695 cells were incubated with 50µM Cof, 1µM CF and 1µM KW for 24h. The energetic metabolite ATP was determined using a luciferase-catalyzed bioluminescence assay. The activity of mitochondrial respiration chain complexes was assessed by high-resolution respirometry using a Clarke electrode. Expression levels genes were deter-mined using quantitative real-time polymerase chain reaction (qRT-PCR). The levels of amyloid β-protein (Aβ1-40) were measured using homogeneous time-resolved fluorescence (HTRF). ROS levels, cAMP levels, and peroxidase activity were determined using a fluorescence assay. The combination of Cof, KW and CF significantly increased ATP levels. The combination had neither a significant effect on MMP, on activity of respiration chain complexes, nor on Aβ1-40levels. cAMP levels were slightly increased after incubation with the combination, but not the peroxi-dase activity. Pyruvate levels and the lactate-pyruvate-ration but not lactate levels were signifi- cantly enhanced. No effect was seen on the expression level of lactate dehydrogenase and py-ruvate dehydrogenase kinase. In some experiments we have tested the single substances. They showed significant results especially in ATP, lactate and pyruvate values compared to the con-trol. The combinations have a lesser effect on mitochondrial dysfunction in cells and none on Aβ production. Whereas ATP levels and pyruvate levels were significantly increased. This suggests a change in glycolysis in neuronal cells harbouring human genes relevant for AD.

Interdiffusion of transition metals across the cathode-electrolyte interface is identified as a key challenge for the practical realization of solid-state batteries. This is related to the formation of highly resistive interphases impeding the charge transport across the materials thus limiting the battery performance. Herein, we investigate the hypothesis that formation of interphases is associated with the incorporation of Co into the LLZO lattice representing the starting point of a cascade of degradation processes. It is shown that Co incorporates into the garnet structure preferably four-fold coordinated as Co2+ or Co3+ depending on oxygen fugacity. The solubility limit of Co is determined to be around 0.16 pfu, whereby concentrations beyond this limit causes a cubic-to-tetragonal phase transition. Moreover, the temperature-dependent Co diffusion coefficient is determined, e.g., D700 °C = 9.46 × 10-14 cm2/s and an activation energy Ea = 1.65 eV, suggesting that detrimental cross diffusion will take place at any relevant process condition. Additionally, the optimal protective Al2O3 coating thickness for relevant temperatures is studied, which allows to create a process diagram to mitigate any degradation with a minimum compromise on electrochemical performance. This study provides a tool to optimize processing conditions toward developing high energy density solid-state batteries.

The oxygen exchange reaction mechanism on truly pristine surfaces of SOFC cathode materials (La0.6Sr0.4CoO3-δ, La0.6Sr0.4FeO3-δ, (La0.6Sr0.4)0.98Pt0.02FeO3-δ, SrTi0.3Fe0.7O3-δ, Pr0.1Ce0.9O2-δ and La0.8Sr0.2MnO3±δ) was investigated employing in-situ impedance spectroscopy during pulsed laser deposition (i-PLD) over a wide temperature and p(O2) range. Besides demonstrating the often astonishing catalytic capabilities of the materials, it is possible to discuss the oxygen exchange reaction mechanism based on experiments on clean surfaces unaltered by external degradation processes. All investigated materials with at least moderate ionic conductivity (i.e. all except LSM) exhibit polarization resistances with very similar p(O2)- and T-dependences, mostly differing only in absolute value. In combination with non-equilibrium measurements under polarization and defect chemical model calculations, these results elucidate several aspects of the oxygen exchange reaction mechanism and refine the understanding of the role oxygen vacancies and electronic charge carriers play in the oxygen exchange reaction. It was found that a major part of the effective activation energy of the surface exchange reaction, which is observed during equilibrium measurements, originates from thermally activated charge carrier concentrations. Electrode polarization was therefore used to control defect concentrations and to extract concentration amended activation energies, which prove to be drastically different for oxygen ncorporation and evolution (0.26 vs. 2.05 eV for LSF).

Background and Purpose: Pleural mesothelioma (PM) is a highly aggressive thoracic tumor with poor prognosis. Although reduced tissue drug accumulation is one of the key features of platinum (Pt) resistance, little is known about Pt distribution in human PM. Experimental Approach: We assessed Pt levels of blood samples and surgically resected specimens from 25 PM patients who had received neoadjuvant Pt-based chemotherapy (CHT). Pt levels and tissue distributions were measured by laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS) and correlated with clinicopathological features. Key Results: In surgically resected PM specimens, mean Pt levels were significantly higher in the non-tumorous (fibrotic) areas (vs. tumorous regions, p

Deep learning models have seen significant successes in numerous applications, but their inner workings remain elusive. The purpose of this work is to quantify the learning process of deep neural networks through the lens of a novel topological invariant called magnitude. Magnitude is an isometry invariant; its properties are an active area of research as it encodes many known invariants of a metric space. We use magnitude to study the internal representations of neural networks and propose a new method for determining their generalisation capabilities. Moreover, we theoretically connect magnitude dimension and the generalisation error, and demonstrate experimentally that the proposed framework can be a good indicator of the latter.

Echinoderms have evolved diverse and disparate morphologies throughout the Phanerozoic. Among them, blastozoans, an extinct group of echinoderms that were an important component of Paleozoic marine ecosystems, are primarily subdivided into groups based on the morphology of respiratory structures. However, systematic and phylogenetic research from the past few decades have shown that respiratory structures in blastozoans are not group-defining and they have re-evolved throughout echinoderm evolution. This Element provides a review of the research involving blastozoan respiratory structures, along with research concerning the morphology, paleoecology, and ontogeny of each of the major groupings of blastozoans as it relates to their corresponding respiratory structures. Areas of future research in these groups are also highlighted.

Nanoindentation, laser ablation inductively coupled plasma mass spectroscopy and weighing ion-spiked organic matrix standards revealed structure-property relations in the microscopic jaw structures of a cosmopolitan bristle worm, Platynereis dumerilii. Hardness and elasticity values in the jaws’ tip region, exceeding those in the center region, can be traced back to more metal and halogen ions built into the structural protein matrix. Still, structure size appears as an even more relevant factor governing the hardness values measured on bristle worm jaws across the genera Platynereis, Glycera and Nereis. The square of the hardness scales with the inverse of the indentation depth, indicating a Nix-Gao size effect as known for crystalline metals. The limit hardness for the indentation depth going to infinity, amounting to 0.53 GPa, appears to be an invariant material property of the ion-spiked structural proteins likely used by all types of bristle worms. Such a metal-like biogenic material is a major source of bio-inspiration.

The chemical capacitance of La

Li

The determination of mineral dust and elemental carbon in snow samples is of great interest, as both compounds are known as light absorbing snow impurities. Different analytical methods have to be used to quantify both compounds. Still, the occurrence of mineral dust, which contains hematite, leads to a bias in the quantification of elemental carbon via thermal-optical analysis. Here we present an approach which utilizes this interference to determine the concentration of hematite via thermal-optical analysis using a Lab OC/EC Aerosol Analyzer (Sunset Laboratory Inc.) and the EUSAAR2 protocol. Therefore, the temperature dependency of the transmittance signal determined during the calibration phase, i.e. when all carbonaceous compounds are already removed, is evaluated. Converting the transmittance signal into an attenuation, a linear relationship between this attenuation and the hematite loading is obtained for loadings ranging from 10 to 100 µgFe cm-2. Furthermore, the approach allows to identify samples which need to be re-evaluated, as the analysis of elemental carbon is biased by mineral dust. We discuss the successful application of the method, designed for snow samples, to ambient air samples containing mineral dust, and the limitations of the method when other iron compounds besides hematite are present.

The Groningen gas field in the Netherlands is experiencing induced seismicity as a result of ongoing depletion. The physical mechanisms that control seismicity have been studied through rock mechanical experiments and combined physical-statistical models to support development of a framework to forecast induced-seismicity risks. To investigate whether machine learning techniques such as Random Forests and Support Vector Machines bring new insights into forecasts of induced seismicity rates in space and time, a pipeline is designed that extends time-series analysis methods to a spatiotemporal framework with a factorial setup, which allows probing a large parameter space of plausible modelling assumptions, followed by a statistical meta-analysis to account for the intrinsic uncertainties in subsurface data and to ensure statistical significance and robustness of results. The pipeline includes model validation using e.g. likelihood ratio tests against average depletion thickness and strain thickness baselines to establish whether the models have statistically significant forecasting power. The methodology is applied to forecast seismicity for two distinctly different gas production scenarios. Results show that seismicity forecasts generated using Support Vector Machines significantly outperform beforementioned baselines. Forecasts from the method hint at decreasing seismicity rates within the next 5 years, in a conservative production scenario, and no such decrease in a higher depletion scenario, although due to the small effective sample size no statistically solid statement of this kind can be made. The presented approach can be used to make forecasts beyond the investigated 5-years period, although this requires addition of limited physics-based constraints to avoid unphysical forecasts.

We present a novel approach for the separation and recovery of Pt and Pd leached from a spent automotive catalyst relying on conventional and polymerized supported ionic liquid phases (SILPs and polySILPs, respectively). A variety of parameters with possible effects on the separation behavior, namely, acidity and concentration of the platinum group metal (PGM) containing solution, as well as different SILP and polySILP loadings, were evaluated for the separation of PGMs in the presence of high concentrations of Al, Fe, Zn, and Ce. The polySILP material demonstrated the ability to separate the PGMs from major accompanying interferences in a single separation step, while problems arising from ionic liquid leaching in the case of SILPs could be avoided. Moreover, the use of supported ionic liquid phases allowed the drastic reduction of the amount of required ionic liquid compared to conventional liquid–liquid separation, while avoiding problems arising from emulsion formation. Subsequent stripping experiments lead to further purification of the PGMs and finally desorption from the solid material into a pure solution. Eventually, the concept of chemisorbed polySILPs provides a new and convenient approach for the recycling of platinum group metals., Supported ionic liquid technology presents an environmentally benign alternative for fast and simple recovery and separation of platinum group metals from end-of-life car catalysts, thereby, contributing to a sustainable future.

Both cerium oxide (CeOx) nanoparticles and mefenamic acid (MFA) are known anti-inflammatory agents with hepatoprotective properties and are therefore prescribed for one of the major diseases in the world, nonalcoholic fatty liver disease (NAFLD). To study the potential cytotoxicity and anti-inflammatory effects as well as drug retention of a potential therapeutic CeOx/MFA supramolecular complex, a well-standardized hepatic (HepG2) spheroid model was used. Results showed that the highest cytotoxicity for the CeOx/MFA supramolecular complex was found at 50 μg/mL, while effective doses of 0.1 and 1 μg/mL yielded a significant decrease of TNF-α and IL-8 secretion. Time-resolved analysis of HepG2 spheroids revealed a spatiotemporal distribution of the supramolecular complex and limited clearance from the internal microtissue over a period of 8 days in cultivation. In summary, our results point at rapid uptake, distribution, and biostability of the supramolecular complex within the HepG2 liver spheroid model as well as a significant anti-inflammatory response at noncytotoxic levels.

Using peat bogs as palaeoenvironmental archives is a well-established practice for reconstructing changing climate and anthropogenic activity in the past. In this paper, we present multi-proxy analyses (element geochemistry, pollen, non-pollen palynomorphs, stable Pb isotopes, humification, ash content) of a 500 cm long, 14C-dated peat core covering the past ∼5000 years from the ombrotrophic Pürgschachen Moor in the Styrian Enns valley (Austrian Alps). Early indications of low settlement and agricultural activity date to ∼2900 cal BCE. An early enrichment of Cu was found in peat layers corresponding to the late Copper Age (∼2500 cal BCE). These enrichments are attributed to Cu mining activities in the Eisenerz Alps. More pronounced increases in cultural indicators (cultivated plants, shrubs, herbs, charcoal) in the pollen record and enrichments of trace metals suggest significant human impact in the vicinity of Pürgschachen Moor in the middle Bronze Age (∼1450–1250 cal BCE), in the late Bronze Age (∼1050–800 cal BCE) and in the period of the late La Tène culture (∼300 cal BCE–1 cal CE). The greater part of the Iron Age and the Roman imperial period are each characterized by a general decline in anthropogenic indicators compared to previous periods. Distinct enrichments of Pb and Sb in the sample that corresponds to ∼900 cal CE are attributed to medieval siderite mining activity in the immediate vicinity of Pürgschachen Moor. The results of this interdisciplinary study provide evidence that strong, climate-controlled interrelations exist between the pollen record, the humification degree and the ash content in an ombrotrophic environment. Human activity, in contrast, is mainly reflected in the pollen record and by enrichments of heavy metals. The study indicates a dry period in the region of the bog around ∼1950 cal BCE.

The ever-increasing speed of exchange of ideas, information, and culture allows contemporary art to be in constant growth, especially concerning the choice of artistic materials. Their characterization is not only crucial for the study of artistic techniques but also for research into the stability of the material and, consequently, the best preservation practices. For this aim, an analytical method should have the advantages of not requiring sample preparation, performing superficial micro-analysis, and obtaining detailed spectral information. For this study, laser-induced breakdown spectroscopy (LIBS) was employed. It was used for the identification of modern paints composed of inorganic pigments and organic binders, such as acrylics, alkyds, and styrene-acrylics. Principal component analysis (PCA) was used to classify the different pure materials, above all, the polymeric binders. To distinguish the paint mixtures, whose LIBS spectral results were more complex due to the pigment/binder interaction, a statistical method recently employed in the cultural heritage field was chosen, namely, random decision forest (RDF). This methodology allows a reduction of the variance of the data, testing of different training data sets by cross-validation, an increase of the predictive power. Furthermore, for the first time, the distribution of different inorganic pigments and organic binder materials in an unknown sample was mapped and correctly classified using the developed RDF. This study represents the first approach for the classification of modern and contemporary materials using LIBS combined with two different multivariate analyses. Subsequent optimization of measurement parameters and data processing will be considered in order to extend its employment to other artistic materials and conservation treatments.

Hydraulic fracturing is a key driver of well productivity and field development planning, in addition to being the most significant portion of capex in shales. Recent breakthroughs in connectivity and digital technologies have enabled the monitoring and analyses of frac operations in real-time. However, most of the digitalization effort to date has been focused on increasing operational efficiency to reduce cost. Without an equal consideration for creating effective fracture geometries, this may lead to poor resource recovery and leave significant value behind. In this paper, we - 1) demonstrate the need to balance between optimizing fracture efficiency and effectiveness; 2) present an integrated system for frac optimization using real-time, historical data along with organizational knowledge; and 3) discuss the challenges of setting up such a system and key considerations, along with examples of large, untapped potential that can be unlocked with data science to deliver real value. Currently, several service providers exist to stream frac data with interactive analytics dashboards. While they offer some customizability, most do not provide a true frac optimization platform that goes beyond frac monitoring and analytics geared towards efficiency and cost indicators. We are still dependent on an individual operator's experience and rules of thumb to make job decisions during a frac stage. In this paper, a real-time optimization workflow is presented that uses advanced data science and statistical techniques to interpret and predict time-series treatment data, integrate historical and contextual information, and honor basin-specific knowledge that has been gathered and tested over the years. Examples are presented from diagnostic pads that highlight the need for balancing stimulation effectiveness with efficiency. We demonstrate a platform to host and execute an ensemble of models and visualizations that communicate actionable insights to an operator within minutes of identifying an event, gather feedback, and learn. Results from field testing show that our system accelerates the learning curve, enables consistent decision making by operators, and can generate significant cost savings. Finally, we share learnings from our digitalization journey. Completion and stimulation expenses account for approximately half of an unconventional well cost. Automated decision making for real-time fracture treatment is the holy grail of digital completions in shales. However, a blind pursuit of efficiency may lead to sub-par fracture treatments and significant value erosion for shale assets. We present an integrated framework that connects real-time data and organizational knowledge to guide an operator to pump the best frac stage while reacting to formation response within a set of constraints. To the best of our knowledge, this is the first paper to describe the general architecture and demonstrate the viability of such a system that relies only on standard wellhead measurements during fracturing.

This work presents a multisensor hyperspectral approach for the characterization of ultramarine blue, a valuable historical pigment, at the microscopic scale combining the information of four analytical techniques at the elemental and molecular levels. The hyperspectral images collected were combined in a single hypercube, where the pixels of the various spectral components are aligned on top of each other. Selected spectral descriptors have been defined to reduce data dimensionality before applying unsupervised chemometric data analysis approaches. Lazurite, responsible for the blue color of the pigment, was detected as the major mineral phase present in synthetic and good quality pigments. Impurities like pyrite were detected in lower quality samples, although the clear identification of other mineral phases with silicate basis was more difficult. There is no correlation between the spatial distribution of the bands arising in the Raman spectra of natural samples in the region 1200–1850 cm−1 and any of the transition metals or rare earth elements (REE). With this information, the previous hypothesis (based on bulk analysis) attributing these bands to luminescence emissions due to impurities of these elements must be revised. We propose the consideration of CO2 molecules trapped in the cages of the aluminosilicate structure of sodalite-type. Additionally, correlation between certain Raman features and the combined presence of Ca, P, and REE, in particular Nd, was detected for the lowest quality pigment. Our results highlight the usefulness of fusing chemical images obtained via different imaging techniques to obtain relevant information on chemical structure and properties.

Li7La3Zr2O12 (LLZO) garnets are highly attractive to be used as solid electrolyte in solid-state Li batteries. However, LLZO suffers from chemical interaction with air and humidity, causing Li+/H+ exchange with detrimental implication on its performance, processing and scalability. To better understand the kinetics of the detrimental Li+/H+ exchange and its dependence on microstructural features, accelerated Li+/H+ exchange experiments were performed on single crystalline and polycrystalline LLZO, exposed for 80 minutes to 80 °C hot water. The resulting chemical changes were quantified by analytical methods, i.e. inductively coupled plasma optical emission spectroscopy (ICP-OES) and laser induced breakdown spectroscopy (LIBS). From the time dependence of the Li+ enrichment in the water, measured by ICP-OES, a bulk interdiffusion coefficient of Li+/H+ could be determined (7 × 10−17 m2 s−1 at 80 °C). Depth dependent concentrations were obtained from the LIBS data for both ions after establishing a calibration method enabling not only Li+ but also H+ quantification in the solid electrolyte. Short interdiffusion lengths in the 1 μm range are found for the single crystalline Ga:LLZO, in accordance with the measured bulk diffusion coefficient. In polycrystalline Ta:LLZO, however, very long diffusion tails in the 20 μm range and ion exchange fractions up to about 70% are observed. Those are attributed to fast ion interdiffusion along grain boundaries. The severe compositional changes also strongly affect the electrical properties measured by impedance spectroscopy. This study highlights that microstructural effects may be decisive for the Li+/H+ ion exchange kinetics of LLZO.

The recovery of platinum group metals (PGMs) from secondary raw materials has become a topic of critical importance mainly due to the gradual depletion of their natural resources and their continuously increasing demand. However, the insufficient recovery of PGMs coupled with the negative environmental impact of the state-of-the-art recycling procedures mandate the investigation and development of alternative recovery processes that will assist in minimizing or even eliminating these drawbacks. Herein, we present a process for the extraction of platinum group metals from spent car catalysts relying on benign deep eutectic solvents (DESs). It is demonstrated that with addition of small amounts of an oxidizing agent, deep eutectic solvents can act as excellent leaching media for the quantitative extraction of platinum group metals. Despite its inertness towards acidic and oxidizing agents, Rh can be leached in a considerable amount which can be further increased by physical pre-treatment of the spent car catalyst material.

The wide application range and ascending demand for platinum group metals combined with the progressive depletion of their natural resources renders their efficient recycling a very important and pressing matter. Primarily environmental considerations associated with state-of-the-art recovery processes have shifted the focus of the scientific community toward the investigation of alternative recycling approaches. Within this context, ionic liquids have gained considerable attention in the last two decades chiefly sparked by properties such as tunabilty, low-volatility, and relatively easy recyclability. In this review an understanding of the state-of-the-art processes, including their drawbacks and limitations, is provided. The core of the discussion is focused on platinum group metal recovery with ionic liquid-based systems. A brief insight in some environmental considerations related to ionic liquids is also provided while some discussion on research gaps, common misconceptions related to ionic liquids and outlook on unresolved issues could not be absent from this review.

Accelerating the oxygen reduction kinetics of solid oxide fuel cell (SOFC) cathodes is crucial to improve their efficiency and thus to provide the basis for an economically feasible application of intermediate temperature SOFCs. In this work, minor amounts of Pt were doped into lanthanum strontium ferrite (LSF) thin film electrodes to modulate the material's oxygen exchange performance. Surprisingly, Pt was found to be incorporated on the B-site of the perovskite electrode as non metallic Pt

We developed a top-irradiated, liquid-phase attenuated total reflectance Fourier transform infrared (ATR-FTIR) setup that allows time-resolved investigations of both Pt particle growth during in si...

Cubic Li7La3Zr2O12 (LLZO) garnets are among the most promising solid-state electrolytes for next-generation Li batteries. However, despite intensive research in recent years, little effort is spent on proper chemical analysis of the material. For reliable LLZO investigation, knowledge about the exact chemical composition, especially the Li content, is of uttermost importance. Herein, we present a method for the laterally resolved stoichiometry determination of Al stabilized LLZO (Li7−3xAlxLa3Zr2O12) using LA-ICP-OES. To ensure reliable signal quantification, matrix-matched standards are prepared and carefully characterized using sample digestion and liquid ICP-OES measurement. An internal standard-independent calibration strategy based on 100 m% normalization is applied, enabling the quantification of all cations within the material. By comparing the obtained high-precision LA-ICP-OES calibrations with analog LA-ICP-MS measurements, it is shown that ICP-OES is the superior choice for the analysis of Li. The developed method is applied to record quantitative distribution images of an Al stabilized LLZO pellet, revealing macroscopic stoichiometry variations within the sample. To verify the analysis, the average stoichiometry obtained by the LA measurements is compared with the bulk composition determined via liquid ICP-OES analysis after sample fusion. The obtained values show excellent agreement, confirming the accuracy of the developed method.

Summary In this paper, we propose a machine–learning methodology using domain–knowledge constraints for well–data integration, prior/expert–knowledge incorporation, and sweet–spot identification. Such methodology enables the analysis of the effects of the main variables involved in production prediction and the evaluation of what–if scenarios of production prediction within geological zones. This methodology will allow streamlining the process of data integration, analytics and machine learning for better decisions, saving time, and helping geologists and reservoir and completion engineers in the task of sweet–spot identification and completion design. We tested the proposed methodology with production, completions, and petrophysical data from a field within a geological target zone. For instance, using local Kriging, we estimated gamma ray features from gamma ray measurements from vertical and horizontal wells, and we integrated those features into the production– and completion–well data, generating an integrated data set for machine–learning modeling. Besides the usual black–box machine–learning models, we used generalized additive models (GAMs) and shape–constraint additive models (SCAMs) for predictive modeling. Those models permit the incorporation of prior/expert knowledge in terms of interaction terms and mathematical constraints on the shape of the effect of the covariates, such as petrophysical and completion parameters, resulting in greater accuracy and interpretability of the predicted production vs. classical black–box machine–learning modeling. We also defined hypothetical what–if scenarios of oil production, such as by estimating the empirical distributions of production estimates using hypothetical settings for completions within the region of interest.

The oxygen exchange reaction mechanism on truly pristine surfaces of SOFC cathode materials (La

This work deals with the effect of sulfur incorporation into model-type GDC thin films on their in-plane ionic conductivity. By means of impedance measurements, a strongly deteriorating effect on the grain boundary conductivity was confirmed, which additionally depends on the applied electrochemical polarisation. To quantify the total amount of sulfur incorporated into GDC thin films, online-laser ablation of solids in liquid (online-LASIL) was used as a novel solid sampling strategy. Online-LASIL combines several advantages of conventional sample introduction systems and enables the detection of S as a minor component in a very limited sample system (in the present case 35 μg total sample mass). To reach the requested sensitivity for S detection using an inductively coupled plasma-mass spectrometer (ICP-MS), the reaction cell of the quadrupole instrument was used and the parameters for the mass shift reaction with O

Objective: To compare outcomes among newborns of opioid-using and nonopioid drug-using mothers with those of control mothers who did not report substance use.Methods: Using the Rochester Epidemiology Project, newborns diagnosed with drug withdrawal syndrome (per ICD-9 or ICD-10 codes) from January 2010 through June 2017 were identified. For mothers, data collected included age, race, drug use, number of prenatal visits, and results of the urinary drug abuse survey, meconium test, and self-report survey. Demographic and perinatal data collected for newborns included birth date; sex; Apgar scores at 1, 5, and 10 minutes; neonatal intensive care stay; and vital status. Controls (n = 771) were similarly selected in regard to sex, birth date, and county.Results: Of 328 infants identified, 168 were born with opioid neonatal abstinence syndrome and 160 with a nonopioid withdrawal syndrome. Control mothers had more prenatal visits than mothers in the nonopioid and opioid groups. Newborns of control mothers had higher Apgar scores at 1 and 5 minutes than both substance-using groups. Opioid-using mothers were almost twice as likely to have newborns requiring intensive care and 3 times as likely to use benzodiazepines compared to the other substance-using mothers. Substance-using mothers had more premature babies than controls.Conclusions: Prenatal opioid use is a substantial risk factor for prematurity. Newborns diagnosed with neonatal abstinence syndrome are at risk of perinatal complications. Mothers using opioids during pregnancy also tend to use other substances. Longitudinal research should clarify how prenatal substance use interacts with other risk factors during a child's first years.

LixLaySrzMnO3 thin films of various compositions (x,y,z) have been grown using pulsed laser deposition. The compositions of the films have been studied as a function of deposition temperature, target-to-substrate distance and deposition pressure with respect to different cation ratios of the targets by inductively coupled plasma mass spectrometry. When growing multi-elemental oxide thin films containing lithium (with its large mass difference to other elements), lithium loss is most probably inevitable. But the desired thin film composition can be achieved by selecting specific growth conditions and different target compositions. The experiments also elucidate some of the mechanisms behind the incongruent lithium transfer from the targets to thin films.

The interplay of structure, composition and electrical conductivity was investigated for Fe-doped SrTiO3 thin films prepared by pulsed laser deposition. Structural information was obtained by reciprocal space mapping while solution-based inductively-coupled plasma optical emission spectroscopy and positron annihilation lifetime spectroscopy were employed to reveal the cation composition and the predominant point defects of the thin films, respectively. A severe cation non-stoichiometry with Sr vacancies was found in films deposited from stoichiometric targets. The across plane electrical conductivity of such epitaxial films was studied in the temperature range of 250–720 °C by impedance spectroscopy. This revealed a pseudo-intrinsic electronic conductivity despite the substantial Fe acceptor doping, i.e. conductivities being several orders of magnitude lower than expected. Variation of PLD deposition parameters causes some changes of the cation stoichiometry, but the films still have conductivities much lower than expected. Targets with significant Sr excess (in the range of several percent) were employed to improve the cation stoichiometry in the films. The use of 7% Sr-excess targets resulted in near-stoichiometric films with conductivities close to the stoichiometric bulk counterpart. The measurements show that a fine-tuning of the film stoichiometry is required in order to obtain acceptor doped SrTiO3 thin films with bulk-like properties. One can conclude that, although reciprocal space maps give a first hint whether or not cation non-stoichiometry is present, conductivity measurements are more appropriate for assessing SrTiO3 film quality in terms of cation stoichiometry., The interplay of structure, composition and electrical conductivity was investigated for Fe-doped SrTiO3 thin films prepared by pulsed laser deposition.