Portable Mini-Electrochemical Cell: Integrating Microsampling and Micro-Electroanalysis for Multipurpose On-Site Nitrite Sensing DOI

Shohreh Madani,

Amir Hatamie

Langmuir, Год журнала: 2024, Номер unknown

Опубликована: Ноя. 20, 2024

In modern analytical chemistry, one of the primary goals is to develop miniaturized, easy-to-use sensing tools, particularly those with multitasking capabilities. this work, we designed a mini-voltammetric cell that integrates modified Au microelectrode (Au/Au NPs as working electrode) and an Ag/AgCl reference electrode installed within micropipette tip. This combined tool not only enables portable on-site microvolume sampling─requiring (around 20-40 μL) or single droplet─but also facilitates direct micro-electroanalysis in short time. To evaluate its capabilities, was optimized for trace analysis nitrite ions demonstrated linear responses ranges 20-150 150-1200 μM, acceptable limit detection (LOD) 18.40 meeting both WHO EPA standards levels. Furthermore, it exhibited high selectivity, stability (up 36 continuous measurements 3.24% signal drop), repeatability (RSD 2.98%,

Язык: Английский

Aspirin nanosensors DOI

Ghazal Koohkansaadi,

Mahsa Tabean,

Arash Mohagheghi

и другие.

Clinica Chimica Acta, Год журнала: 2025, Номер 571, С. 120222 - 120222

Опубликована: Март 7, 2025

Язык: Английский

Процитировано

1

A review on recent advances of AI-integrated microfluidics for analytical and bioanalytical applications DOI
Elham Asadian,

Farshad Bahramian,

Saeed Siavashy

и другие.

TrAC Trends in Analytical Chemistry, Год журнала: 2024, Номер 181, С. 118004 - 118004

Опубликована: Окт. 9, 2024

Язык: Английский

Процитировано

6

Machine Learning-Driven Innovations in Microfluidics DOI Creative Commons

JinSeok Park,

Y. Kim, Hee‐Jae Jeon

и другие.

Biosensors, Год журнала: 2024, Номер 14(12), С. 613 - 613

Опубликована: Дек. 13, 2024

Microfluidic devices have revolutionized biosensing by enabling precise manipulation of minute fluid volumes across diverse applications. This review investigates the incorporation machine learning (ML) into design, fabrication, and application microfluidic biosensors, emphasizing how ML algorithms enhance performance improving design accuracy, operational efficiency, management complex diagnostic datasets. Integrating microfluidics with has fostered intelligent systems capable automating experimental workflows, real-time data analysis, supporting informed decision-making. Recent advances in health diagnostics, environmental monitoring, synthetic biology driven are critically examined. highlights transformative potential ML-enhanced systems, offering insights future trajectory this rapidly evolving field.

Язык: Английский

Процитировано

4

Sample preparation for lab-on-a-chip/microfluidic sample preparation DOI
Matteo Ferroni, Ana Leonor Pardo Campos Godoy, Eduardo A. Takara

и другие.

Elsevier eBooks, Год журнала: 2025, Номер unknown

Опубликована: Янв. 1, 2025

Процитировано

0

An Integrated Microfluidic Microwave Array Sensor with Machine Learning for Enrichment and Detection of Mixed Biological Solution DOI Creative Commons
Sen Yang,

Yanxiong Wang,

Yanfeng Jiang

и другие.

Biosensors, Год журнала: 2025, Номер 15(1), С. 45 - 45

Опубликована: Янв. 13, 2025

In this work, an integrated microfluidic microwave array sensor is proposed for the enrichment and detection of mixed biological solution. individuals with urinary tract infections or intestinal health issues, levels white blood cells (WBCs) Escherichia coli (E. coli) in urine extracts can be significantly elevated compared to normal. The chip, characterized by its low cost, simplicity operation, fast response, high accuracy, designed detect a solution WBCs E. coli. results demonstrate that microfluidics could effectively enrich efficiency 88.3%. For WBC detection, resonance frequency sensing chip decreases increasing concentration, while capacitance value increases concentration. Furthermore, measurement data are processed using machine learning. Specifically, subjected further linear fitting. addition, prediction model employing four different algorithms, achieves maximum accuracy 95.24%. Consequently, employed clinical diagnosis coli, providing novel approach medical research involving bacteria.

Язык: Английский

Процитировано

0

Advancing microfluidic design with machine learning: a Bayesian optimization approach DOI Creative Commons
Ivana Kundačina, Ognjen Kundačina, Dragiša Mišković

и другие.

Lab on a Chip, Год журнала: 2025, Номер unknown

Опубликована: Янв. 1, 2025

The proposed Bayesian optimization-based approach enhances micromixer performance by optimizing geometric parameters, significantly reducing required number of simulations, and accelerating the design process compared to conventional methods.

Язык: Английский

Процитировано

0

Biosensor Technologies for Water Quality: Detection of Emerging Contaminants and Pathogens DOI Creative Commons
Antía Fdez-Sanromán, Nuria Bernárdez-Rodas, Emílio Rosales

и другие.

Biosensors, Год журнала: 2025, Номер 15(3), С. 189 - 189

Опубликована: Март 15, 2025

This review explores the development, technological foundations, and applications of biosensor technologies across various fields, such as medicine for disease diagnosis monitoring, food industry. However, primary focus is on their use in detecting contaminants pathogens, well environmental monitoring water quality assessment. The classifies different types biosensors based bioreceptor transducer, highlighting how they are specifically designed detection emerging (ECs) pathogens water. Key innovations this technology critically examined, including advanced techniques systematic evolution ligands by exponential enrichment (SELEX), molecularly imprinted polymers (MIPs), self-assembled monolayers (SAMs), which enable fabrication sensors with improved sensitivity selectivity. Additionally, integration microfluidic systems into analyzed, demonstrating significant enhancements performance speed. Through these advancements, work emphasizes fundamental role key tools safeguarding public health preserving integrity.

Язык: Английский

Процитировано

0

Advancements of paper-based microfluidics and organ-on-a-chip models in cosmetics hazards DOI Creative Commons
Sanidhya Pai,

A Binu,

G. S. Lavanya

и другие.

RSC Advances, Год журнала: 2025, Номер 15(13), С. 10319 - 10335

Опубликована: Янв. 1, 2025

Different detection approaches for monitoring adulterants/hazards present in cosmetics using paper-based devices and organ-on-a-chip.

Язык: Английский

Процитировано

0

Emerging biomedical applications of surface-enhanced Raman spectroscopy integrated with artificial intelligence and microfluidic technologies DOI

Zehra Taş,

Fatih Çiftçi, Kutay İçöz

и другие.

Spectrochimica Acta Part A Molecular and Biomolecular Spectroscopy, Год журнала: 2025, Номер unknown, С. 126285 - 126285

Опубликована: Апрель 1, 2025

Язык: Английский

Процитировано

0

Conductive biological materials for in vitro models: properties and sustainability implications DOI Creative Commons
Aleksandra Serafin,

César R. Casanova,

Arvind K. Singh Chandel

и другие.

In vitro models, Год журнала: 2025, Номер unknown

Опубликована: Апрель 24, 2025

Abstract The integration of conductive biological materials into in vitro models represents a transformative approach to advancing biomedical research while addressing critical sustainability challenges. Traditional used tissue engineering and disease modeling are often environmentally detrimental, derived from non-renewable resources, limited their ability replicate the dynamic properties native tissues. Conductive bridge this gap by offering unique combination biodegradability, sustainability, functional properties, such as bioelectricity biocompatibility, that essential for mimicking physiological environments. Herein, development current applications biodegradable materials, including advanced polymers polyaniline polypyrrole, carbon-based nanocomposites, renewable biopolymers lignin cellulose, overviewed. These not only reduce ecological footprint but also enable precise simulation electrical signaling tissues, cardiac, neural, muscular systems, thereby enhancing relevance models. Their three-dimensional (3D) constructs, organ-on-chip platforms, bioprinting technologies facilitates patient-specific models, paving way personalized therapeutic diagnostic applications. In addition precision, these align with global efforts implement circular economy principles research, promoting resource efficiency waste reduction. By combining environmental responsibility state-of-the-art functionality, redefining future 3D accelerating innovation regenerative medicine, drug development, fostering sustainable framework scientific discovery.

Язык: Английский

Процитировано

0