AIMC Topic: Colorimetry

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Explainable Deep Learning-Assisted Self-Calibrating Colorimetric Patches for In Situ Sweat Analysis.

Analytical chemistry
Sweat has emerged as a compelling analyte for noninvasive biosensing technology because it contains a wealth of important biomarkers in hormones, organic biomacromolecules, and various ionic mixtures. These components offer valuable insights and can ...

Visible detection of chilled beef freshness using a paper-based colourimetric sensor array combining with deep learning algorithms.

Food chemistry
This study developed an innovative approach that combines a colourimetric sensor array (CSA) composed of twelve pH-response dyes with advanced algorithms, aiming to detect amine gases and assess the freshness of chilled beef. With the assistance of m...

Combination of headspace single-drop microextraction (HS-SDME) with a nickel-embedded paper-based analytical device for cyanide quantification.

Analytica chimica acta
BACKGROUND: Cyanide anion can be found in foodstuffs, tobacco smoke and a variety of types of waters, mainly originating from anthropogenic activities. Due to its highly toxic nature, several agencies have established limits for cyanide levels in wat...

A deep learning-enabled smartphone platform for rapid and sensitive colorimetric detection of dimethoate pesticide.

Analytical and bioanalytical chemistry
A novel deep learning-enabled smartphone platform is developed to assist a colorimetric aptamer biosensor for fast and highly sensitive detection of dimethoate. The colorimetric determination of dimethoate is based on the specific binding of dimethoa...

CoO/CoFeO Hollow Nanocube Multifunctional Nanozyme with Oxygen Vacancies for Deep-Learning-Assisted Smartphone Biosensing and Organic Pollutant Degradation.

ACS applied materials & interfaces
Although the application of nanozymes has been widely studied, it is still a huge challenge to develop highly active and multifunctional nanozyme catalysts with a wider application prospect. CoO/CoFeO hollow nanocubes (HNCs) with oxygen vacancies wer...

Deep learning-assisted ultra-accurate smartphone testing of paper-based colorimetric ELISA assays.

Analytica chimica acta
Smartphone has long been considered as one excellent platform for disease screening and diagnosis, especially when combined with microfluidic paper-based analytical devices (μPADs) that feature low cost, ease of use, and pump-free operations. In this...

A regression-based machine learning approach for pH and glucose detection with redox-sensitive colorimetric paper sensors.

Analytical methods : advancing methods and applications
Colorimetric paper sensors are used in various fields due to their convenience and intuitive manner. However, these sensors present low accuracy in practical use because it is difficult to distinguish color changes for a minute amount of analyte with...

Explainable Deep-Learning-Assisted Sweat Assessment via a Programmable Colorimetric Chip.

Analytical chemistry
Multianalytes and individual differences of biofluids (such as blood, urine, or sweat) pose enormous complexity and challenges to rapid, facile, high-throughput, and accurate clinical analysis or health assessment. Deep-learning (DL)-assisted image a...

Photodegradation Kinetics and Deep Learning-Based Intelligent Colorimetric Method for Bioavailability-Based Dissolved Iron Speciation.

Analytical chemistry
Via the photodegradation of dissolved iron (dFe) complexes in the euphotic zone, released free Fe(III) is the most important source of bioavailable iron for eukaryotic phytoplankton. There is an urgent need to establish bioavailability-based dissolve...

Development of a paper-based analytical device for the colourimetric detection of alanine transaminase and the application of deep learning for image analysis.

Analytica chimica acta
A paper-based colourimetric assay for the detection of alanine transaminase has been developed. In the presence of alanine transaminase, 2,4-dinitrophenyl hydrazine changes to pyruvate hydrazone leading to a colour change from pale yellow to dark yel...