SPOOC (Sensor for Periodic Observation of Choline): An Integrated Lab-on-a-Spoon Platform for At-Home Quantification of Choline in Infant Formula.

Choline is an essential micronutrient for infants' brain development and health. To ensure that infants receive the needed daily dose of choline, the U.S. Food and Drug Administration (FDA) has set requirements for choline levels in commercialized infant formulas. Unfortunately, not all families can access well-regulated formulas, leading to potential inadequacies in choline intake. Economic constraints or difficulties in obtaining formulas, exacerbated by situations like COVID-19, prompt families to stretch formulas. Accurate measurement of choline in infant formulas becomes imperative to guarantee that infants receive the necessary nutritional support. Yet, accessible tools for this purpose are lacking. An innovative integrated sensor for the periodic observation of choline (SPOOC) designed for at-home quantification of choline in infants' formulas and milk powders is reported. This system is composed of a choline potentiometric sensor and ionic-liquid reference electrode developed on laser-induced graphene (LIG) and integrated into a spoon-like device. SPOOC includes a micro-potentiometer that conducts the measurements and transmits results wirelessly to parents' mobile devices. SPOOC demonstrated rapid and accurate assessment of choline levels directly in pre-consuming infant formulas without any sample treatment. This work empowers parents with a user-friendly tool for choline monitoring promoting informed nutritional decision-making in the care of infants.

Ion Selective Electrode (ISE) Method for Determination of Total Fluorine and Total Organic Fluorine in Packaging Substrates.

Various testing methods and techniques have been used to identify and quantify per- and polyfluoroalkyl substances (PFAS) in food packaging. A common indirect measurement of PFAS is total fluorine (TF) and total organic fluorine (TOF). These methods are critical in rapidly screening food packaging materials for the >9000 PFAS and are often globally used for regulatory limits. However, this destructive approach requires careful sample preparation, combustion, and the analysis of the solution by a fluoride-specific electrode. The method described herein is a cost-effective, rapid, quantitative, and externally validated initial screening of packaging materials for fluoro-chemistry. This study presents validated protocols for measuring TF and TOF in packaging substrates using oxygen combustion sample preparation coupled with fluoride ion-selective electrode (F-ISE); the materials and required equipment are provided, and the step-by-step procedure from sample preparation to the analysis are described, including critical steps to minimize contamination and interferences during sample preparation.

A case of pseudohyperchloraemia caused by sodium nitrate ingestion.

Emergency department presentations of sodium nitrate poisoning are increasing in frequency. Point-of-care blood gas analysis is useful for identifying methaemoglobinaemia and other abnormalities in such patients. Topically applied nitrate is known to positively interfere with chloride measurement in both point-of-care instruments and automated analysers of the clinical chemistry laboratory. In this article, the authors describe a case of pseudohyperchloraemia caused by sodium nitrate, which was consumed orally for the purpose of suicide. Consistent with the established pattern of interference, the ABL800 (Radiometer Medical, Brønshøj Copenhagen) blood gas analyser produced spuriously high chloride results, whilst the Alinity (Abbott Diagnostics, Abbot Park, Illinois) automated analyser resulted in chloride measurements comparable to those of inductively coupled mass spectrometry (ICP-MS). Both instruments, measure chloride with ion-selective electrodes (ISEs). The ABL800 (Radiometer) uses a membrane electrode, which is vulnerable to permeation by lipophilic nitrate ions, whereas the Alinity (Abbott) employs a silver chloride redox electrode system that is resistant to precipitation of silver nitrate due to its relatively high solubility. These mechanistic differences likely explain why nitrate interferes with some point-of-care devices but does not appear to affect the results of automated analysers.

An ISE-based On-Site Soil Nitrate Nitrogen Detection System.

Soil nitrate-nitrogen (NO3--N) is one of the primary factors used to control nitrogen topdressing application during the crop growth period. The ion-selective electrode (ISE) is a promising method for rapid lower-cost in-field detection. Due to the simplification of sample preparation, the accuracy and stability of ISE-based in-field detection is doubted. In this paper, a self-designed prototype system for on-site soil NO3--N detection was developed. The procedure of spinning centrifugation was used to avoid interference from soil slurry suspension. A modified Nernstian prediction model was quantitatively characterized with outputs from both the ISE and the soil moisture sensor. The measurement accuracy of the sensor fusion model was comparable with the laboratory ISE detections with standard sample pretreatment. Compared with the standard spectrometric method, the average absolute error (AE) and root-mean-square error (RMSE) were found to be less than 4.7 and 6.1 mg/L, respectively. The on-site soil testing efficiency was 4-5 min/sample, which reduced the operation time by 60% compared with manual sample preparation. The on-site soil NO3--N status was dynamically monitored for 42 consecutive days. The declining peak of NO3--N was observed. In all, the designed ISE-based detection system demonstrated a promising capability for the dynamic on-site monitoring of soil macronutrients.

Flexible Laser-Induced Graphene for Nitrogen Sensing in Soil.

Flexible graphene electronics are rapidly gaining interest, but their widespread implementation has been impeded by challenges with ink preparation, ink printing, and postprint annealing processes. Laser-induced graphene (LIG) promises a facile alternative by creating flexible graphene electronics on polyimide substrates through the one-step laser writing fabrication method. Herein, we demonstrate the use of LIG, created with a low-cost UV laser, for electrochemical ion-selective sensing of plant-available nitrogen (i.e., both ammonium and nitrate ions: NH4+ and NO3-) in soil samples. The laser used to create the LIG was operated at distinct pulse widths (10, 20, 30, 40, and 50 ms) to maximize the LIG electrochemical reactivity. Results illustrated that a laser pulse width of 20 ms led to a high percentage of sp2 carbon (77%) and optimal peak oxidation current of 120 µA during cyclic voltammetry of ferro/ferricyanide. Therefore, LIG electrodes created with a 20 ms pulse width were consequently functionalized with distinct ionophores specific to NH4+ (nonactin) or NO3- (tridodecylmethylammonium nitrate) within poly(vinyl chloride)-based membranes to create distinct solid contact ion-selective electrodes (SC-ISEs) for NH4+ and NO3- ion sensing, respectively. The LIG SC-ISEs displayed near Nernstian sensitivities of 51.7 ± 7.8 mV/dec (NH4+) and -54.8 ± 2.5 mV/dec (NO3-), detection limits of 28.2 ± 25.0 µM (NH4+) and 20.6 ± 14.8 µM (NO3-), low long-term drift of 0.93 mV/h (NH4+ sensors) and -5.3 µV/h (NO3- sensors), and linear sensing ranges of 10-5-10-1 M for both sensors. Moreover, soil slurry sensing was performed, and recovery percentages of 96% and 95% were obtained for added NH4+ and NO3-, respectively. These results, combined with a facile fabrication that does not require metallic nanoparticle decoration, make these LIG electrochemical sensors appealing for a wide range of in-field or point-of-service applications for soil health management.

Effect of humic substances aggregation on the determination of fluoride in water using an ion selective electrode.

The control of drinking water quality is critical in preventing fluorosis. In this study humic substances (HS) are considered as representative of natural organic matter (NOM) in water. We show that when HS aggregate the response of fluoride ion selective electrodes (ISE) may be perturbed. Dynamic light scattering (DLS) results of both synthetic solutions and natural water sample suggest that low pH and high ionic strength induce HS aggregation. In the presence of HS aggregates, fluoride concentration measured by ISE has a reduction up to 19%. A new "open cage" concept has been developed to explain this reversible phenomenon. The interference of HS aggregation on fluoride measurement can be effectively removed by centrifugation pretreatment.

Application of neural networks with novel independent component analysis methodologies to a Prussian blue modified glassy carbon electrode array.

Sodium potassium absorption ratio (SPAR) is an important measure of agricultural water quality, wherein four exchangeable cations (K(+), Na(+), Ca(2+) and Mg(2+)) should be simultaneously determined. An ISE-array is suitable for this application because its simplicity, rapid response characteristics and lower cost. However, cross-interferences caused by the poor selectivity of ISEs need to be overcome using multivariate chemometric methods. In this paper, a solid contact ISE array, based on a Prussian blue modified glassy carbon electrode (PB-GCE), was applied with a novel chemometric strategy. One of the most popular independent component analysis (ICA) methods, the fast fixed-point algorithm for ICA (fastICA), was implemented by the genetic algorithm (geneticICA) to avoid the local maxima problem commonly observed with fastICA. This geneticICA can be implemented as a data preprocessing method to improve the prediction accuracy of the Back-propagation neural network (BPNN). The ISE array system was validated using 20 real irrigation water samples from South Australia, and acceptable prediction accuracies were obtained.

Evaluation of the plasticization of ion-selective electrode membranes by pulsed NMR analyses.

The potentiometric polymeric membranes for ion-selective electrodes were evaluated by analyses of the proton spin-spin relaxation times T2 with pulsed NMR. The T2 measurements were performed using the Hahn-Echo, Solid-Echo and CPMG pulse sequences. The T2 values and fractions F of each component were obtained by analyses of the FID signals measured with the Hahn-Echo pulse sequence. The softer potentiometric polymeric membrane possessed the main fraction F(L), providing a relatively longer T(2L) value. A linear relationship existed between the weight ratio of the membrane solvent and ln T(2L) (or ln total T2×F). This analysis method could quantify the degree of hardness or softness of the potentiometric polymeric membranes with the differences in the membrane solvent weight. The normalized derivative spectra were acquired from the transverse magnetization M(t) data measured by using the Solid-Echo and CPMG pulse sequences. In the normalized derivative spectra of the potentiometric polymeric membranes, most PVC peaks in the short time region shifted to a larger area of long time regions by plasticization, and the softer potentiometric polymeric membrane incorporating more membrane solvent exhibited a relaxation peak in the relatively longer time region. Thus, the normalized derivative spectra were effective in elucidating the compatibility of the PVC with the membrane solvent.

Extended artificial neural networks: incorporation of a priori chemical knowledge enables use of ion selective electrodes for in-situ measurement of ions at environmentally relevant levels.

A novel artificial neural network (ANN) architecture is proposed which explicitly incorporates a priori system knowledge, i.e., relationships between output signals, while preserving the unconstrained non-linear function estimator characteristics of the traditional ANN. A method is provided for architecture layout, disabling training on a subset of neurons, and encoding system knowledge into the neuron structure. The novel architecture is applied to raw readings from a chemical sensor multi-probe (electric tongue), comprised of off-the-shelf ion selective electrodes (ISEs), to estimate individual ion concentrations in solutions at environmentally relevant concentrations and containing environmentally representative ion mixtures. Conductivity measurements and the concept of charge balance are incorporated into the ANN structure, resulting in (1) removal of estimation bias typically seen with use of ISEs in mixtures of unknown composition and (2) improvement of signal estimation by an order of magnitude or more for both major and minor constituents relative to use of ISEs as stand-alone sensors and error reduction by 30-50% relative to use of standard ANN models. This method is suggested as an alternative to parameterization of traditional models (e.g., Nikolsky-Eisenman), for which parameters are strongly dependent on both analyte concentration and temperature, and to standard ANN models which have no mechanism for incorporation of system knowledge. Network architecture and weighting are presented for the base case where the dot product can be used to relate ion concentrations to both conductivity and charge balance as well as for an extension to log-normalized data where the model can no longer be represented in this manner. While parameterization in this case study is analyte-dependent, the architecture is generalizable, allowing application of this method to other environmental problems for which mathematical constraints can be explicitly stated.