Hydrodynamically limited precision of gradient techniques in flow injection analysis

Phosphorescence in liquid solutions: a promising detection principle in liquid chromatography and flow injection analysis

Sandwich techniques in flow-injection analysis : Part 2. Simultaneous Determination of Iron(II) and Total Iron

This paper explores a new source of graphite for working electrodes, which presents advantages such as low electrical resistance, good flexibility, favorable mechanical performance, versatility to design electrodes in almost any size and very low cost. The new electrodes were investigated in batch electrochemical cells as associated with flow injection analysis systems. Cyclic voltammetry, stripping voltammetry, and amperometry associated with flow injection analysis techniques were applied for the determination of ascorbic acid, zinc and paracetamol in pharmaceutical formulations, respectively. Well‐established analytical methods were applied for comparison purposes. The results herein demonstrate the potential of graphite foils as working electrodes in different electroanalytical methods, offering the possibility of producing disposable sensors for routine applications.

On-line monitoring and control of fermentation processes by flow-injection analysis

Bilirubin is a metabolic breakdown product of blood haem, of great biological and diagnostic importance. A new chemiluminescence (CL) method has been developed for the quantification of bilirubin. The method is combined with the flow injection analysis (FIA) technique and based on the inhibition effect of bilirubin on the CL from the lucigenin-hydrogen peroxide system in an alkaline medium. Under the optimum conditions, the decreased CL intensity was proportional to the concentration of bilirubin, in the range 0.0585-58.47 microg/mL. The detection limit estimated from the calibration graph was about 7.8826 ng/mL. The relative standard deviation (RSD) of 10 parallel measurements (1 x 10(-4) mol/L bilirubin) was 2.5%. Recoveries of bilirubin were found to fall in the range 94-97.5% using control sera. The method is interference-free, fast and easy to carry out.

One of the problems in testing the performance of (fiber) optical chemical sensors is to establish a reliable and reproducible test protocol in order to determine response time, reversibility, sensor stability, and longevity. A versatile arrangement for testing a variety of sensors is presented. It is based on the flow injection analysis (FIA) technique and was used to characterize new optical sensors for pH, potassium ion, and nitrate with respect to sensitivity, dynamic range, response time, specificity, and reversibility.© (1992) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Response to the comments by K. Grudpan on “Flow injection analysis and radiochemical techniques”

Organic pollutants in biological waste water treatment. Results of mass and tandem mass spectrometry of the flow injection mode compared with liquid chromatographic examinations: Polar compounds under positive ionization

A convenient screening method for tracing the amount of anionic surfactants (AS) in environmental water was developed by applying flow injection analysis (FIA) technique, a simple technique for the automation of wet chemical analyses, to the new solvent extraction spectrophotometry of AS (Motomizu, S., et al., Anal. Chem., 54, 392 (1982)). AS in more than 140 points of river and creek waters were determined by employing the screening method to assess the AS pollution of Saga city. The AS pollution was devided into four stages: scarecely or slightly polluted water; 0-0.1ppm (as sodium dodecyl sulphate), polluted water; 0.1-0.5ppm, highly polluted water; 0.5-1.0ppm, and extremely polluted water; 1.0ppm<. About 70% of all samples contained more than 0.1ppm of AS. The main contaminator was assumed to be the AS in waste water from houses. The AS concentration in all streams in the city tended to increase from upstream to downstream. The dynamics of AS were also investigated by monitoring the fluctuation of AS concentration for 24 hours and for 10 days.

Abstract The steam distillation technique for the quantification of soil mineral nitrogen is not well adapted to estimate very low levels of NH4 + and NO3 −such as those found in tropical pastures. In this paper we describe a flow injection analysis (FIA) technique for the direct estimation of soil ammonium in potassium chloride extracts. The technique is based on the salicylate/hypochlorite colorimetric reaction with the resulting colouration read at 647 nm. The speed of the reaction was increased by immersing the reaction coils in a water bath maintained at 70°C. The technique was capable of accurately quantifying ammonium to concentrations as low as 0.05 mg NH4+‐N/L (equivalent to 0.25 mg NH4 +‐N/g dry soil) and sample thoughputs of at least 60 samples per hour could be achieved. It was found that amino acids would also give a positive colorimetric reaction but that in the ten tropical soils examined this was not a significant source of error.

Flow-injection chemiluminescence determination of aminomethylbenzoic acid and aminophylline based on N-bromosuccinimide–luminol reaction

A comprehensive, critical and updated review for the applications of flow-injection analysis (FIA) techniques for the analysis of organic pollutants in several types of water samples, except marine waters, is presented. The methods of indirect determination of organic pollutants in water by using flow injection coupled with atomic absorption spectroscopy are also discussed.

Chapter 1 - Flow Injection Analysis: Its Origins and Progress

Describes the setting up of a moiré topographic system to measure three‐dimensional convex and concave surfaces of moulded brassière cups. The essential features of the system consisted of a photographic instrument which precisely controlled the position of the light source, the camera, the grid and the cup sample. As the uniformity of the grid was most crucial to produce a high contrast moiré picture, a photochemical‐machined grid plate was developed, and a pneumatic grid translation device was incorporated into the system to produce a clear image. The tolerance of the instrumental error was derived by the law of error propagation and the confidence with the moiré set‐up was assured.

The error propagation among estimated parameters reflects the correlation among the parameters. We study the capability of machine learning of “learning” the correlation of estimated parameters. We show that machine learning can recover the relation between the uncertainties of different parameters, especially, as predicted by the error propagation formula. Gravitational lensing can be used to probe both astrophysics and cosmology. As a practical application, we show that the machine learning is able to intelligently find the error propagation among the gravitational lens parameters (effective lens mass M L and Einstein radius θ E ) in accordance with the theoretical formula for the singular isothermal ellipse (SIE) lens model. The relation of errors of lens mass and Einstein radius, (e.g., the ratio of standard deviations =σMLˆ/σθEˆ ) predicted by the deep convolution neural network are consistent with the error propagation formula of the SIE lens model. As a proof-of-principle test, a toy model of linear relation with Gaussian noise is presented. We found that the predictions obtained by machine learning indeed indicate the information about the law of error propagation and the distribution of noise. Error propagation plays a crucial role in identifying the physical relation among parameters, rather than a coincidence relation, therefore we anticipate our case study on the error propagation of machine learning predictions could extend to other physical systems on searching the correlation among parameters.