Conductivity Detection Research Articles

Non-contact dynamic detection of apple juice conductivity based on magnetic induction spectroscopy

Non-contact dynamic detection of apple juice conductivity based on magnetic induction spectroscopy

A micro thermal conductivity detector with diffusion channels suppressing the effect of forced convection

A micro thermal conductivity detector with diffusion channels suppressing the effect of forced convection

Simultaneous determination of inorganic ions in saline water from the Mekong Delta using ion chromatography

ABSTRACT The economy of Vietnam is significantly influenced by agriculture, forestry, and fisheries; thus, developing analytical methods to assess water quality is crucial. Salinization is an escalating concern in the Mekong Delta, particularly in Ben Tre province, where it adversely affects the livelihoods and local economy. In saline water, besides NaCl, which is the predominant component, other ions such as K+, Ca2+, Mg2+, and SO4 2− are vital for crop development. This study introduces an ion chromatography technique with conductivity detection capable of simultaneously analyzing six ions in saline water samples with high precision. The standard curves demonstrated excellent linearity with a correlation coefficient (R2 >0.995) and commendable repeatability (%RSD <5%) for concentration ranges of 1–10 mg L−1 for cations, 0–10 mg L−1 for SO4 2−, and 10–50 mg L−1 for Cl−. The outcomes will be compared with those of reference methods, including Flame Atomic Absorption Spectrometry, Mohr Titration, and Turbidimetric Methods, revealing no significant differences in ion concentration determinations across six saline water backgrounds in Ben Tre province.

Early Technology Readiness Level (TRL) Development of the Microfluidic Inorganic Conductivity Detector for Europa and the Solenoid-Based Actuator Assembly for Impact Penetrators.

This study introduces an innovative in situ lander/impact-penetrator design tailored for Discovery-class missions to Europa, specifically focused on conducting astrobiological analyses. The platform integrates a microfluidic capacitively coupled contactless conductivity detector (C4D), optimized for the detection of low-concentration salts potentially indicative of biological activity. Our microfluidic system allows for automated sample routing and precise conductivity-based detection, making it suitable for the harsh environmental and logistical demands of Europa's icy surface. This technology provides a robust toolset for exploring extraterrestrial habitability by enabling in situ chemical analyses with minimal operational intervention, paving the way for advanced astrobiological investigations on Europa.

A Spectroscopy Solution for Contactless Conductivity Detection in Capillary Electrophoresis.

This paper introduces a novel contactless single-chip detector that utilizes impedance-to-digital conversion technology to measure impedance in the microfluidic channel or capillary format analytical device. The detector is designed to operate similarly to capacitively coupled contactless conductivity detectors for capillary electrophoresis or chromatography but with the added capability of performing frequency sweeps up to 200 kHz. At each recorded data point, impedance and phase-shift data can be extracted, which can be used to generate impedance versus frequency plots, or phase-shift versus frequency plots. Real and imaginary parts can also be calculated from the data, allowing for the generation of Nyquist diagrams. This detector represents the first of its kind in the contactless conductivity class to provide spectrum-type data, as demonstrated in capillary electrophoresis experiments.

Contactless Conductivity Detection for Capillary Electrophoresis-Developments From 2020 to 2024.

The review covering the development of capillary electrophoresis with capacitively coupled contactless conductivity detection from 2020 to 2024 is the latest in a series going back to 2004. The article considers applications employing conventional capillaries and planar lab-on-chip devices as well as fundamental and technical developments of the detector and complete electrophoresis instrumentation.

Green Microfluidic Method for Sustainable and High-Speed Analysis of Basic Amino Acids in Nutritional Supplements.

Amino acids (AAs) have broad nutritional, therapeutic, and medical significance and thus are one of the most common active ingredients of nutritional supplements. Analytical strategies for determining AAs are high-priced and often limited to methods that require modification of AA polarity or incorporation of an aromatic moiety. The aim of this work was to develop a new method for the determination of L-arginine, L-ornithine, and L-lysine on low-cost microchip electrophoresis instrumentation conjugated with capacitively coupled contactless conductivity detection. A solution consisting of 0.3 M acetic acid and 1 × 10-5 M iminodiacetic acid has been identified as the optimal background electrolyte, ensuring the shortest possible analysis time. The short migration times of amino acids (t ≤ 64 s) and method simplicity resulted in high analysis throughput with high precision and linearity (R2≥ 0.9971). The limit of detection values ranged from 0.15 to 0.19 × 10-6 M. The accuracy of the proposed method was confirmed by recovery measurements. The results were compared with CE-UV-VIS and HPLC-DAD methods and showed good agreement. This work represents the first successful demonstration of the ME-C4D analysis of L-arginine, L-ornithine, and L-lysine in real samples.

Operando Measurements of Copper Catalyst Morphology in Gas Diffusion Electrodes during Electrochemical CO2 Reduction for the Formation of C2+ Compounds

Carbon capture and conversion technologies have been widely studied as promising approaches to solving the global warming problem. The conversion of CO2 to carbon-based chemicals and fuels by electrochemical CO2 reduction (CO2RR) using renewable electricity is one of the attractive strategies to achieve carbon neutrality. Among the various products of CO2RR, multi-carbon products (C2+) such as ethylene and ethanol are essential chemicals with high energy density and value-added. Various metals, alloys, and metal oxides have been widely studied as electrocatalysts for CO2RR, but copper (Cu) and its derivatives are the only electrocatalysts with selectivity for the formation of C2+ compounds [1]. Current electrocatalysts for CO2RR have limitations concerning current density enhancement, faradaic efficiency (FE) of the desired product, and catalyst durability. The use of gas diffusion electrodes (GDEs), which allow CO2RR to occur at the solid catalyst/liquid electrolyte/gaseous CO2 interface, can effectively accelerate CO2RR and solve the problem of limited mass transport due to the inherently low diffusivity and solubility of CO2 in water. Recently, high C2+ product selectivity was achieved at current densities above 100 mA/cm2 using GDEs with Cu-based catalysts [2,3]. However, the influence of the catalytic morphology of GDEs on reactivity and product selectivity is not fully understood yet because of the complex CO2RR mechanism and catalyst structure in GDEs. In this study, in situ and ex situ synchrotron radiation spectroscopy and imaging techniques were used to investigate the dynamic behavior of the catalyst morphology and electrolyte permeability changes inside Cu-GDEs during CO2RR.Cu(x)-GDEs were prepared by magnetron sputtering of Cu on a commercial carbon-based gas diffusion layer (GDL) with a microporous layer (MPL). Cu thicknesses of x = 70, 300, and 1000 nm were used. CO2RR experiments were performed in a homemade three-compartment flow cell using a neutral electrolyte (e.g. KCl aq, KHCO3 aq) with Cu-GDE as the working electrode, Pt mesh as the counter electrode, and Ag/AgCl as the reference electrode. The FEs of each product were obtained by the constant current CO2 electrolysis (chronopotentiometry, CP). The gas products were quantified using gas chromatography with a thermal conductivity detector. As for the liquid products, alcohols were evaluated using gas chromatography with a flame ionization detector, and organic acids were detected by high-performance liquid chromatography with a conductivity detector, respectively. The in situ and ex situ evaluation of Cu-GDE before, during, and after CO2RR was performed by scanning X-ray fluorescence microscopy (SXFM), X-ray computed tomography (CT), and X-ray absorption spectroscopy (XAS). Synchrotron radiation experiments were carried out at SPring-8 BL16XU/B2, PF BL14B, and saga-LS BL07, respectively.Figure (a) shows the FEs of CO2RR products as a function of total current density (Jtotal) with the Cu(300)-GDE. FEs for C2+ products (FEC2+), including C2H4, C2H5OH, CH3COOH, C3H7OH, reached up to 82% at Jtotal = 400 mA/cm2. When the total current density increased above 1000 mA/cm2, FEC2+ decreased and FEH2 increased. This suggests that the state of the triple-phase boundary changes with current density during electrolysis. To elucidate the following questions: i) what morphology of Cu catalyst leads to high C2+ selectivity, and ii) why FEH2 increases at high current densities, the internal structure of the Cu-GDE after electrolysis was observed using X-ray CT. Figures (b), and (c) show ex situ CT slice images of Cu(70)-GDE before and after CO2 electrolysis at CP 400 mA/cm2. In the CT images contrasting the absorption coefficients corresponding to the electron density, the denser Cu and K are observed brighter than carbon (MPL/GDL). Before CO2 electrolysis, Cu was deposited on the MPL surface with a uniform thickness (Fig. (b)), but after CP 400 mA/cm2, Cu on the MPL surface decreased and bright spots were dispersed within the MPL region (Fig. (c)). Elemental discrimination imaging using spectral CT and SXFM confirmed that Cu and K were dispersed within the MPL region after CO2 electrolysis, while only K and no Cu were observed within the MPL region after electrolysis with Ar gas supply. These results suggest that the morphology of the Cu catalyst within the GDEs changes from its initial state during CO2RR. In the presentation, we also report on the operando SXFM and XAS during CO2 and Ar electrolysis and discuss the effect of changes in the morphology and oxidation state of Cu catalyst on C2+ selectivity in Cu-GDE during CO2 electrolysis.[1] S. Nitopi, et al., Chem. Rev., 119, 7610 (2019).[2] G. Zhang, et al., Nat. Commun., 12, 5745 (2021).[3] A. Inoue, et al., EES Catal., 1, 9 (2023). Figure 1

Electrodeposition of Cu with Amino Acids Toward Electrocatalytic Enhancement of CO₂ Reduction Reactions

The electrochemical reduction of carbon dioxide (CO2) is attracting technology because it can convert CO2 into a useful resource with zero emissions by using surplus electricity and renewable energy. For achieving efficient electrolysis of CO2, the development of a high performance electrocatalysts is required. Copper (Cu) is the only metal that is capable of electrochemically converting CO2 to hydrocarbons, but the high overpotential of hydrocarbon formation and the low selectivity of the reduction products have been problems. One of the solutions to these problems is the hybridization of metal and organic materials, in which the metal serves as the CO2 reduction reaction sites and the organic material stabilizes the intermediates [1]. In this study, we have electrodeposited Cu with five different types of amino acids which is expecting stabilization of CO2 reductive intermediates and evaluated its catalytic activity of electrochemical reduction of CO2.The electrodeposited Cu with amino acids was obtained by a constant current electrolysis at -2.0 mA cm-2 for 1.0 C cm-2 from the aqueous solutions containing 10 mmol dm-3 CuSO4･5H2O, 0.1 mol dm-3 Na2SO4, and 1.0 mmol dm-3 amino acids in a three-electrode cell with carbon paper (CP) as the working electrode, platinum wire as the counter electrode, and Ag/AgCl as the reference electrode. The pH of electrolytic bath was fixed at 1.10 by adding H2SO4. The obtained electrodeposited Cu samples were characterized by Raman measurement, high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM), energy dispersive X-ray spectroscopy (EDS) measurement, scanning electron microscopy (SEM) and X-ray diffraction (XRD). The electrochemical reduction of CO2 has been conducted by a constant potential electrolysis at -1.27 V vs. RHE of 0.5 mol dm-3 KHCO3 aqueous solutions saturated with CO2. The amount of reductive gas products was quantified by gas chromatograph- mass spectrometer (GC-MS) and gas chromatograph thermal conductivity detector (GC-TCD).The chronopotentiograms obtained during the electrodeposition of Cu, both in the presence and absence of 1.0 mmol dm−3 of the various amino acids showed different potential required to reach a current of −4.0 mA depending on the amino acids. However, considering the result of the open-circuit-potential measurement, the amino acids do not form complexes with Cu2+, suggesting that the electrolysis species remain consistent regardless of the amino acid present in the Cu electrodeposition bath. Therefore, the differences observed in the chronopotentiograms during Cu electrodeposition are attributed to the adsorption of amino acids on the electrodeposited Cu. The adsorption of amino acids on electrodeposited Cu was confirmed by Raman spectra and EDS spectra obtained from cross-sectional HAADF-STEM images. The peak of Raman spectra originating from amino acids was observed from electrodeposited Cu when Cu electrodeposition was conducted with amino acids, confirming the higher ratio of N and Cu on the surface compared to within the particle in the EDS spectra. Surface morphologies were observed by using SEM. CP has fiber-like structure but electrodeposited Cu without and with amino acids were deposited such coating CP fiber. The particle size of electrodeposited Cu with amino acids was more homogeneous, and the particles were more densely packed together than pure electrodeposited Cu. However, changing diffraction patterns and peak broadening due to loading amino acids in XRD were not observed.The electrochemical reduction of CO2 on electrodeposited Cu samples was performed and the faradic efficiency (FE) of the CO2 reduction gas products were calculated. All electrodeposited Cu with and without amino acids showed a higher FE for the electrochemical reduction of CO2 to CH4 compared to Cu foil (24.2%) and different values depending on amino acids. In particular, electrodeposited with L-histidine containing imidazole groups showed a high FE of 67.6%, effectively suppressing the hydrogen evolution reaction. This finding highlights the important role of functional groups in amino acids, especially imidazole, in facilitating the electrochemical conversion of CO2 to CH4. This study shows that certain functional groups in amino acids have a crucial influence on the catalytic efficiency of electrodeposited Cu in CO2 reduction reaction applications.[1] S. Jia et al., Angew. Chem. Int. Ed. 2021, 60, 10977–10982.

Quantifying H2 Crossover in PEM Water Electrolyzers Operating at High Differential Pressure

Large-scale deployment of proton exchange membrane water electrolyzers (PEMWEs) is crucial for producing clean and economically viable hydrogen to create hydrogen-based energy ecosystems that can replace existing carbon-intensive processes. Efficient operation of PEMWEs requires the use of thinner membranes to reduce ohmic losses as well as the differential pressure operation to increase the overall system efficiency. The high differential pressure operation of PEMWEs with thin membranes results in significant hydrogen crossover from cathode to anode. This crossover-H2 has considerable implications on PEMWE performance, durability, as well as operational safety.In this work, we develop a method to accurately quantify hydrogen crossover rates in PEMWEs operating at high differential pressure. Our analysis shows that crossover-H2 is oxidized at the anode catalyst layer resulting in measurable hydrogen oxidation reaction (HOR) currents. We combine this HOR current measurement with online gas chromatography with thermal conductivity detector to determine H2 concentration in the anode outlet and also calculate H2 crossover rates at various operating current and differential pressures (up to 30 bar). Further, we use this methodology to evaluate the effect of porous transport layer (PTL) coatings (Pt, Ir, and Au) on the HOR current as well as the hydrogen crossover rate in PEMWEs.Acknowledgment: This research is supported by the U.S. Department of Energy (DOE) Hydrogen and Fuel Cell Technologies Office (HFTO) through the Hydrogen from Next-generation Electrolyzers of Water (H2NEW) consortium.

Fast simple determination of nitrogen in reduced graphene oxide by pulse furnace heating combined with thermal conductivity detection technique

The fast accurately determining the contents of various elements in reduced graphene oxide (rGO) has long been the most important research topic in the field of analytical chemistry for a long time. In this study, a new method was developed for fast and simple determination of total nitrogen content in rGO via pulse furnace heating combined with a thermal conductivity detection technique. Two key parameters, extraction power and sample weight were optimized experimentally. A nitrogen release curve was obtained through pulse furnace heating combined with thermal conductivity detection. The quantification limit of nitrogen element was calculated based on the results of the multiple blank experiments, and the accuracy and precision of the new method were verified by measuring nitrogen contents in rGO samples. The accuracy of this method was verified through X-ray photoelectron spectroscopy and a CHNOS analyzer comparisons. This is the first study, in which pulse furnace heating combined with thermal conductivity detection was used to determine the total nitrogen content in rGO.

Quality control of fish sauce by simultaneous determination of histamine and tyramine with capillary electrophoresis and contactless conductivity detection

In this study, we report the development of a simple and cost-effective approach for fish sauce quality control. This is based on simultaneous determination of histamine and tyrosine in fish sauce using capillary electrophoresis (CE) coupled with contactless conductivity detection (C4D). Considerations for the use of purpose-made CE-C4D for food quality control in Vietnam are provided. The best detection limit (LOD) achieved was 5 mg/kg for histamine and 6 mg/kg for tyramine using the optimized background electrolyte (BGE) composed of 20 mM (N-(2-Hydroxyethyl)piperazine-N’-(2-ethane-sulfonic acid]) (HEPES) / 10 mM L-Histidine (His), 5 % methanol (MeOH) at pH 6.6. Excellent agreement between the results from CE-C4D and those from the confirmation method (HPLC-PDA for histamine and HPLC-FLD for tyramine) was achieved for different fish sauce samples, with their result deviations less than 10 % for all tested compounds.

Development of an online cloud fog monitor: Design, laboratory, and field deployment at an unoccupied coastal site in Eastern China

Online detection of cloud water chemistry is a pressing issue in atmospheric outfield observation, with online detection modules representing a significant development direction for cloud water observation. Addressing the common problem of time-delayed errors in manual detection, particularly in the context of cloud water acidity, has remained challenging, with limited understanding and effective solutions available. We developed an Online Cloud Fog Monitor (OCFM) featuring automatic pH and electrical conductivity (EC) detection capabilities, and conducted comprehensive laboratory and field tests. The OCFM utilizes a peristaltic pump, water pipe, and diversion chamber to direct cloud samples to distinct detection chambers, enabling real-time analysis. The diversion chamber is equipped with dual liquid level sensors to segregate and preserve samples once the volume exceeds a predetermined threshold. Calibration results indicate that the instrument's background metal elements do not affect cloud water analysis, and detection occurs within the designed response time. Field tests demonstrate that the OCFM can collect over 50 ml of cloud water, with a response accuracy exceeding 63.6%, though influenced by meteorological conditions. The time-delay error for pH was notably larger than for EC. Comparative analysis with the Caltech Active Strand Cloudwater Collector (CASCC) revealed that the OCFM's sampling process does not introduce errors, and the online detection accuracy of pH and EC is comparable to manual methods. Additionally, water-soluble ions in samples collected by the OCFM showed no significant differences compared to those collected by CASCC. Overall, the OCFM effectively replaces manual testing, mitigating time-delay errors in chemical property testing. The introduction of this cloud water detector promises to significantly reduce labor costs and economic consumption associated with cloud water observation, thereby facilitating long-term, multi-site observation of cloud water chemistry.

Fatty Acid Analysis by Capillary Electrophoresis and Contactless Conductivity Detection for Future Life Detection Missions.

Future life-detection missions will likely search for biosignatures within a wide range of organic compounds, including fatty acids. In order to determine such biosignatures, it is necessary to identify and quantify individual fatty acids present within a sample. In this study, we present a method using capillary electrophoresis coupled to contactless conductivity detection (CE-C4D) for the separation and detection of both saturated and unsaturated fatty acids after derivatization with N,N-diethylethylenediamine, triethylamine, and 2-chloro-1-methylpyridinium iodide at 40°C for 10min. Operating conditions (background electrolyte, separation voltage, and temperature) were optimized to provide maximum separation of fatty acids, thereby allowing their identification and quantification. Using a background electrolyte of 2M acetic acid in 45% acetonitrile, an optimal separation was obtained with a separation voltage of 10kV and a capillary temperature of 15°C. The optimized CE-C4D method was used to analyze samples of the cyanobacterium Spirulina. Multiple fatty acids were detected in the samples, showing the potential of this method for detection of fatty acid biosignatures during future spaceflight missions.

Facile Preparation and Study of Self-Healing Water-Absorbing Expanding Elastomers.

The absorbent expansion elastomer plays a crucial role in engineering sealing and holds a promising future in this field as infrastructure continues to develop. Traditional materials have their limitations, especially when used in large construction projects where the integrity and reliability of the material are of utmost importance. In this work, a self-healing water-absorbing expansion elastomer was developed for continuous production at a large scale to monitor the sealing conditions of massive infrastructure projects. At room temperature, the material exhibited a repairing efficiency of 57.77 % within 2 h, which increased to 84.02 % after 12 h. This extended reaction time allowed for effective repairs when defects were detected. The material's strength can attain 3 MPa, placing it at the upper echelon among common self-healing materials, thereby granting it a certain level of durability in its application environment. The material's volume expansion rate reached 200-400 % to achieve effective sealing, and the functional filling of the filler endowed the material itself with a favorable external force induction effect and prevented heat accumulation. The conductive detection performance of the absorbent expansion elastomer was improved by utilizing triple self-healing strategies, including dipole-dipole interaction, ion cross-linked network, and externally-aided restoration materials. These strategies were combined with a double packing strategy to enhance the material's properties. This innovative elastomer can be applied in various fields such as tunnel construction, infrastructure development, aerospace sealing, and railway transportation, showcasing significant potential for diverse engineering applications.

Rotary excitation of non-sinusoidal pulsed magnetic fields: Towards non-invasive direct detection of cardiac conduction.

There is a need for high resolution non-invasive imaging methods of physiologic magnetic fields. The purpose of this work is to develop a MRI detection approach for non-sinusoidal magnetic fields based on the rotary excitation (REX) mechanism which was previously successfully applied for the detection of oscillating magnetic fields in the sub-nT range. The new detection concept was examined by means of Bloch simulations, evaluating the interaction effect of spin-locked magnetization and low-frequency pulsed magnetic fields. The REX detection approach was validated under controlled conditions in phantom experiments at 3 T. Gaussian and sinc-shaped stimuli were investigated. In addition, the detection of artificial fields resembling a cardiac QRS complex, which is the most prominent peak visible on a magnetocardiogram, was tested. Bloch simulations demonstrated that the REX method has a high sensitivity to pulsed fields in the resonance case, which is met when the spin-lock frequency coincides with a non-zero Fourier component of the stimulus field. In the experiments, we found that magnetic stimuli of different durations and waveforms can be distinguished by their characteristic REX response spectrum. The detected REX amplitude was proportional to the stimulus peak amplitude (R2 > 0.98) and the lowest field detection was 1 nT. Furthermore, the detection of QRS-like fields with varying QRS durations yielded significant results in a phantom setup (p < 0.001). REX detection can be transferred to non-sinusoidal pulsed magnetic fields and could provide a non-invasive, quantitative tool for spatially resolved assessment of cardiac biomagnetism. Potential applications include the direct detection and characterization of cardiac conduction.

Study on hydrogen and helium chromatographic analysis system

Abstract Rare gas helium is widely used in industrial and high-tech areas, is the national important strategic resources, to lead the scientific and technological innovation has the increasingly important role, helium production capacity in China is relatively scarce, helium gas resources long-term dependence on imports. In order to strengthen the helium resource guarantee capacity of our country and ensure the advantageous position in the international development competition. In recent years, helium detection and analysis in real-time while drilling at wellsite has been gaining interest in the oil and gas industry, the detection of non-hydrocarbon gases such as helium has become the focus of current exploration. In order to meet the demand of hydrogen and helium exploration and development, a set of hydrogen-helium chromatography analyzers is developed. A separation method of helium and hydrogen combined with the pre-analysis column and the main analysis column is proposed to realize the efficient separation of hydrogen and helium, the wide spectrum TCD (Thermal Conductivity Detector) is used as the analyzer to achieve the high efficiency detection of hydrogen and helium. Field application shows that the system can detect hydrogen and helium efficiently within 30 seconds analysis cycle while drilling, which provides a technical means for the detection of hydrogen and helium in the exploration process. It provides a good technical reserve for the future large-scale development and utilization of natural hydrogen and helium.

Rapid Determination of Galantamine in Human Plasma by Microchip Electrophoresis With a Highly Integrated Contactless Conductivity Detector.

A novel and rapid method was developed for the determination of galantamine in human plasma by microchip electrophoresis with a highly integrated contactless conductivity detector (CCD). The instrumental parameters affecting the response of the detector, such as excitation frequency and excitation voltage, were examined and optimized. The electrophoresis conditions that influenced the separation and detection of galantamine, including the composition of buffer solution, buffer pH, buffer concentration, additives, injection time, and separation voltage were systematically investigated. Under the optimal conditions, the peak height had a good linear relationship with the concentration of galantamine in human plasma from 10 to 160 µg/L, and the correlation coefficient was 0.9992, the limit of detection reached 1.1 µg/L. The recoveries were between 98.6% and 102.1%. This sensitive, rapid, and convenient method is a good alternative to existing methods for galantamine determination. Also, this highly integrated CCD holds great promise in clinical biochemical analysis.

Reduction of the environmental impact of the determination of l-carnitine and acetyl-l-carnitine in milk products by microchip electrophoresis

A novel miniaturized analytical method for the simultaneous determination of l-carnitine and its ester, acetyl-l-carnitine in fresh milk and milk products by microchip electrophoresis (MCE) with conductivity detection was developed. Under optimized separation conditions, separation voltage of 4 kV and 50 mmol L−1 acetic acid and 0.1 % methylhydroxyethylcellulose at pH 3.0 as background electrolyte, carnitines were sufficiently separated in less than 10 min. An elimination of adsorption of the cationically migrated analytes on a poly(methyl methacrylate) microchip was achieved by addition of 1 mmol L−1 triethylenetetramine to all analyzed samples. The detector response was linear in the range 0.2–1.5 µg mL−1 for l-carnitine and 0.4–2.0 µg mL−1 for acetyl-l-carnitine. The LOQ values were 0.1 µg mL−1 and 0.4 µg mL−1 for l-carnitine and acetyl-l-carnitine, respectively. Recoveries of the analytes in the analyzed samples were in the range 87.5–97.8 %. The developed MCE method has been successfully applied to the analysis of carnitines in eight milk products after a sample pretreatment which included precipitation, centrifugation, and filtration. The developed MCE method has a low hazardous impact on human health and the environment.

A multilabel deep learning model for the detection of conduction and rhythm disorders from PDF outputs of a widely available portable ECG Device

Abstract Background Wearable and portable devices with ECG capabilities can provide broad access to screening for cardiovascular disorders. However, most are approved for the detection of only atrial fibrillation. Most algorithms for detecting rhythm and conduction disorders are trained and tested on 12-lead ECGs or the lead I of clinical ECGs, with an unclear role for extending the diagnostic range of wearable and portable devices. Moreover, no current algorithms enable cardiovascular diagnosis on data available to end users, who largely have access to the PDF outputs of their data. Purpose To validate a novel artificial intelligence (AI) model trained to identify conduction disorders and arrhythmias on synthetic ECG outputs from lead I data of clinical ECGs, to detect the same disorders on cardiologist-annotated PDF outputs from the Alivecor KardiaMobile single-lead ECGs (Kardia ECGs). Methods We extracted lead I data from 3,076,352 clinical ECGs across 5 hospitals of a large U.S.-based hospital system from 2000-2024 and simulated wearable PDF outputs from commercial devices using a novel plotting approach that replicated the variations in plotted formats. Gold-standard cardiologist written diagnosis statements were processed to generate 8 clinical labels spanning conduction and rhythm disorders, and we developed a multilabel model to predict these labels using an EfficientNet-B3 convolutional neural network. We examined the performance of the model on 24,808 Kardia ECGs annotated by cardiologists. Results The model achieved a high performance on clinical ECGs in a held-out subset of the synthetic lead I ECG printouts resembling wearable outputs (AUC &amp;gt; 0.9 for all 8 labels). In the independent 24,808 Kardia ECGs, annotated by experts, the model achieved high performance across all labels. For the rhythm disorders atrial fibrillation or atrial flutter, premature atrial contraction, and premature ventricular contraction, the model had AUROCs of 0.99, 0.91, and 0.95, respectively. For the conduction disorders 1st-degree AV block and 2nd or 3rd-degree AV blocks, the model had AUROCs of 0.94 and 0.99, respectively. Finally, for supraventricular tachycardias, wide QRS, and paced ECGs, the model had AUROCs of 0.998, 0.98, and 0.98, respectively. Conclusions We demonstrate that a deep learning model trained to identify rhythm and conduction disorders based on synthetic ECGs where lead I data from clinical 12 lead ECGs are used to replicate real-world PDF outputs of wearable ECGs, generalizes to real-world wearable and handheld single-lead devices.