Impedance-based Solid Oxide Fuel Cell testing as scalable and reliable Quality Control tool for cell and batch manufacturing: first findings

Testing is a necessary step in the manufacturing process of Solid Oxide Fuel Cells (SOFC) to assess the performance of the produced cells before on-field deployment. In this work, the implementation of Electrochemical Impedance Spectroscopy (EIS) and subsequent data elaboration via Equivalent Circuit Modelling (ECM) is evaluated as a viable experimental framework for characterization and Quality Control (QC) of cells or cell batches, complemented to standard polarization-based methods. By performing a statistical analysis of the ECM parameters (representative of each physico-chemical process) the cell and batch operational parameters can be determined and compared. The validity of the proposed methodology is assessed using a wide experimental dataset of a significant number of SOFC samples (20 cells from 3 batches – two of which identical and the third with an intentional modification in the manufacturing process in order to validate the proposed methodology) tested in identical conditions. Results show that the impedance-based method provide detailed information in terms of impedance breakdown (anode gas diffusion process resulting the main criticality), as well as confirming the preliminary results obtained from the polarization approach (Batch#2 showing the lowest total performance and highest uniformity). Highly reproducible intra-batch distributions of the ECM parameters encourage the applicability of such methodology for QC purposes, even with few data collected only in Open Circuit Voltage (OCV) conditions. A relevant deviation of charge transfer and diffusion resistances in Batch#3 respect to other batches is observed (not visible from the polarization curves), which is reconducted to the modified anode functional layer, opening potential applications of the proposed methodology to assess the impact of targeted modifications of manufacturing methods on specific cell electrochemical performances.

LC-MS Identification and Quantification of Phenolic Compounds in Solid Residues from the Essential Oil Industry

Plant solid residues obtained from the essential oil industry represent a rich source of phenolic compounds with bioactive properties to be used in the food and pharmaceutical industries. A selective and sensitive liquid chromatography-mass spectrometry (LC-MS) method was developed for the simultaneous determination of phenolic compounds in solid residues of the Lamiaceae family plants. A total of 48 compounds can be separated within 35 min by using the Poroshell-120 EC-C18 column, and a gradient mobile phase of 0.1% formic acid and acetonitrile with flow rate of 0.5 mL/min; salicylic acid was used as internal standard. The calibration curves showed good linearity in the tested concentration range for each analyte (R2 > 0.9921), while recoveries ranged from 70.1% to 115.0% with an intra-day and inter-day precision of less than 6.63% and 15.00%, respectively. Based on the retention behavior, as well as absorption and mass spectra, 17 phenolic acids, 19 flavonoids and 2 phenolic diterpenes were identified and quantified in the solid residues obtained by distillation of six aromatic plants: oregano, rosemary, sage, satureja, lemon balm, and spearmint. The method constitutes an accurate analytical and quality control tool for the simultaneous quantitation of phenolics present in solid waste residues from the essential oil industry.

Stability Indicating HPLC Method for Estimation of Thymoquinone in Nasal Simulated Fluid: Method Development and Validation

Introduction: A simple rapid and precise HPLC method was developed for estimation of TH in nasal simulated fluid and stability was assessed in various stressed conditions. Methods: Chromatographic separation of TH in nasal simulated fluid was done using HPLC AS-4050 coupled with Jasco UV 2075 Plus detector, Jasco LC-Net 11/ADC valve, Jasco PU-2080 pump and hypersil gold C18 (250x6x5 µm) column, ChromNAV 2.0 Chromatography Data System software with mobile phase as acetonitrile: water (65:35) and acetonitrile: NSF (60:40) at a flow rate of 1ml/min and having run time of 10 min with loop volume of 20 µl and detection wavelength of 252 nm. The method was validated for accuracy, precision, linearity, specificity, and sensitivity in accordance with ICH (Q2B) guidelines. Results: The results of all the validation parameters were found to be within the acceptable limits. The calibration plots were linear over the concentration ranges from 2 to 14µg/ml. The accuracy and precision were found to be between 97.04±0.112 to101.081±0.0191and ≤2% for three drugs. Developed method was successfully applied for the determination TH in nasal simulated fluid and recovery was found to be >98% for three drugs. The degradation products produced as a result of stress studies did not interfere with drug peak. Conclusion: The developed method was found to be simple, specific, economic, reliable, accurate, precise, and reproducible used as a quality control tool for analysis of pure thymoquinone in nasal simulated fluid.

Stimulated Raman histology in the neurosurgical workflow of a major European neurosurgical center — part A

Histopathological diagnosis is the current standard for the classification of brain and spine tumors. Raman spectroscopy has been reported to allow fast and easy intraoperative tissue analysis. Here, we report data on the intraoperative implementation of a stimulated Raman histology (SRH) as an innovative strategy offering intraoperative near real-time histopathological analysis. A total of 429 SRH images from 108 patients were generated and analyzed by using a Raman imaging system (Invenio Imaging Inc.). We aimed at establishing a dedicated workflow for SRH serving as an intraoperative diagnostic, research, and quality control tool in the neurosurgical operating room (OR). First experiences with this novel imaging modality were reported and analyzed suggesting process optimization regarding tissue collection, preparation, and imaging. The Raman imaging system was rapidly integrated into the surgical workflow of a large neurosurgical center. Within a few minutes of connecting the device, the first high-quality images could be acquired in a “plug-and-play” manner. We did not encounter relevant obstacles and the learning curve was steep. However, certain prerequisites regarding quality and acquisition of tissue samples, data processing and interpretation, and high throughput adaptions must be considered. Intraoperative SRH can easily be integrated into the workflow of neurosurgical tumor resection. Considering few process optimizations that can be implemented rapidly, high-quality images can be obtained near real time. Hence, we propose SRH as a complementary tool for the diagnosis of tumor entity, analysis of tumor infiltration zones, online quality and safety control and as a research tool in the neurosurgical OR.

Data independent acquisition enables deep and fast label-free dynamic organellar mapping

The membrane compartments of eukaryotic cells organize the proteome into dynamic reaction spaces that control protein activity. This 'spatial proteome' and its changes can be captured systematically by our previously established Dynamic Organellar Maps (DOMs) approach, which combines cell fractionation and shotgun-proteomics into a profiling analysis of subcellular localization. Our original method relied on data dependent acquisition (DDA), which is inherently stochastic, and thus offers limited depth of analysis across replicates. Here we adapt DOMs to data independent acquisition (DIA), in a label-free format, and establish an automated data quality control tool to benchmark performance. Matched for mass spectrometry (MS) runtime, DIA-DOMs provide double the depth relative to DDA-DOMs, with substantially improved precision and localization prediction performance. Matched for depth, DIA-DOMs provide organellar maps in a third of the runtime. To test the DIA-DOMs performance for comparative applications, we mapped subcellular localization changes in response to starvation/disruption of lysosomal pH in HeLa cells, revealing a subset of Golgi proteins that cycle through endosomes. DIA-DOMs offer a superior workflow for label-free spatial proteomics, with a broad application spectrum in cell and biomedical research.

Assessment of external defects at mechanical engineering enterprises

The methodology for calculating the constituent elements that form external defects in the manufacture of engineering products is considered. A classic quality control tool, a Pareto chart, is proposed to analyze the causes of defects and their cost. When testing the methodology on the example of the production of gearboxes, it was revealed that the number of defects has a different ranking order relative to the assessment of external losses. For the formation of corrective and preventive actions, it is recommended to use two diagrams at the same time. Keywords: external defect, losses, quality control tools, Pareto chart. [email protected]

No-Reference Image Quality Assessment Of Large FLAIR MRI Datasets

<div>The study of neurodegenerative diseases have found promise through white matter lesions best visualized in FLAIR MRI; however, algorithms experience difficulty in generalizing to large multicenter datasets due to the variance of image quality and characteristics. This thesis presents a quality control tool that combines image quality assessment with outlier rejection algorithms; this tool is unique as it is specifically designed for large multicenter FLAIR MRI datasets. An image processing approach evaluates each volume by: intensity-based features, sharpness/blur-based features, signal- and contrast-to-noise ratios, noise field characteristics, motion artifact prevalence</div><div>and a total IQ score. The performance of this tool was evaluated on labelled ADNI and CCNA data reporting F1 scores of 0.82, and 0.85, respectively. Applications for this tool include potential rescan or longitudinal scanner study alongside the immediate application of outlier removal for</div><div>large FLAIR datasets.</div>

No-Reference Image Quality Assessment Of Large FLAIR MRI Datasets

<div>The study of neurodegenerative diseases have found promise through white matter lesions best visualized in FLAIR MRI; however, algorithms experience difficulty in generalizing to large multicenter datasets due to the variance of image quality and characteristics. This thesis presents a quality control tool that combines image quality assessment with outlier rejection algorithms; this tool is unique as it is specifically designed for large multicenter FLAIR MRI datasets. An image processing approach evaluates each volume by: intensity-based features, sharpness/blur-based features, signal- and contrast-to-noise ratios, noise field characteristics, motion artifact prevalence</div><div>and a total IQ score. The performance of this tool was evaluated on labelled ADNI and CCNA data reporting F1 scores of 0.82, and 0.85, respectively. Applications for this tool include potential rescan or longitudinal scanner study alongside the immediate application of outlier removal for</div><div>large FLAIR datasets.</div>

Optimized Umkehr profile algorithm for ozone trend analyses

The long-term record of Umkehr measurements from four NOAA Dobson spectrophotometers was reprocessed after updates to the instrument calibration procedures. In addition, a new data quality-control tool was developed for the Dobson automation software (WinDobson). This paper presents a comparison of Dobson Umkehr ozone profiles from NOAA ozone network stations (Boulder, OHP, MLO, Lauder) against several satellite records, including Aura Microwave Limb Sounder (MLS; ver. 4.2), and combined SBUV and OMPS records (NASA AGG and NOAA COH). A subset of satellite data is selected to match Dobson Umkehr observations at each station spatially (distance less than 200 km) and temporally (within 24 hours). Umkehr Averaging Kernels (AKs) are applied to vertically smooth all overpass satellite profiles prior to comparisons. The station Umkehr record consists of several instrumental records, which have different optical characterizations, and thus instrument-specific stray light contributes to the data processing errors and creates step changes in the record. This work evaluates the overall quality of Umkehr long-term measurements at NOAA ground-based stations and assesses the impact of the instrumental changes on the stability of the Umkehr ozone profile record. This paper describes a method designed to correct biases and discontinuities in the retrieved Umkehr profile that originate from the Dobson calibration process, repair, or optical realignment of the instrument. The M2GMI and GMI CTM ozone profile model output matched to station location and date of observation is used to evaluate instrumental step changes in the Umkehr record. Homogenization of the Umkehr record and discussion of the apparent stray light error in retrieved ozone profiles are the focus of this paper. Homogenization of ground-based records is of great importance for studies of long-term ozone trends and climate change.