AI-Driven Simulation of Stochastic Electrochemiluminescence DOI Creative Commons
Klaus Mathwig

ACS electrochemistry., Год журнала: 2024, Номер unknown

Опубликована: Дек. 17, 2024

Electrochemiluminescence (ECL) is a vital analytical technique widely used in immunosensing and emerging applications biological imaging. Traditional ECL simulations rely on finite element methods, which provide valuable insights into reaction dynamics spatial distribution of species. However, such methods are limited mesoscopic environments where stochastic effects become significant. Here, I present novel approach using ChatGPT o1 to generate Python-based simulation for reactions nanofluidic channel, incorporating diffusion, electrochemical chemical reactions, photon emission. The successfully replicates results from models while offering additional time-dependent behaviors enabling noise analysis simulated luminescence traces. iterative development this was rapid, requiring minimal coding expertise leveraging the model's "reasoning" capabilities implement physical principles, verify calculations, optimize performance. This work demonstrates that large language (LLMs) can serve as effective co-intelligence tools, facilitating complex electrochemistry. AI-driven tools/LLMs have promising role advancing electrochemistry research, though careful validation remains essential ensure scientific accuracy.

Язык: Английский

Nanochannel-Confined Ni(OH)2-CeO2 Composite Nanozyme Boosts Electrochemiluminescence of Luminol-Dissolved Oxygen for Immunosensing DOI
Fan Xue, Lujie Wang, Hongxin Wang

и другие.

Biosensors and Bioelectronics, Год журнала: 2025, Номер unknown, С. 117451 - 117451

Опубликована: Апрель 1, 2025

Язык: Английский

Процитировано

1
Overcoming Kinetic Barriers of Remote Electrochemiluminescence on Boron-Doped Diamond via Catalytic Coreactant Oxidation DOI Creative Commons
Alessandro Fracassa, Chiara Mariani, Andrea Fiorani

и другие.

Chemical Communications, Год журнала: 2025, Номер unknown

Опубликована: Янв. 1, 2025

Using an Ir( iii )-based redox mediator ([Ir(sppy) 3 ] 3- ) overcomes the traditional kinetic barrier of tri- n -propylamine oxidation on BDD, enhancing ECL from Ru( ii )-labeled beads by up to 46-fold.

Язык: Английский

Процитировано

0
The development of electrochemiluminescent probes: Mechanism and application DOI

Tongtong Li,

Yingying Su, Lichun Zhang

и другие.

Microchemical Journal, Год журнала: 2025, Номер unknown, С. 113216 - 113216

Опубликована: Март 1, 2025

Язык: Английский

Процитировано

0
AI-driven simulation of stochastic electrochemiluminescence DOI Creative Commons
Klaus Mathwig

Опубликована: Ноя. 14, 2024

Electrochemiluminescence (ECL) is a vital analytical technique widely used in immunosensing and emerging applica-tions biological imaging. Traditional ECL simulations rely on finite element methods, which provide valuable insights into reaction dynamics spatial distribution of species. However, such methods are limited mesoscopic environ-ments where stochastic effects become significant. Here, I present novel approach using ChatGPTo1 to generate Py-thon-based simulation for reactions nanofluidic channel, incorporating diffusion, electrochemical chemical reactions, photon emission. The successfully replicates results from models while offering additional time-dependent behaviors enabling noise analysis simulated luminescence traces. iterative development this ChatGPT was rapid, requiring minimal coding expertise leveraging the model’s "reasoning" capabilities implement physical principles, verify calculations, optimize per-formance. This work demonstrates that large language (LLMs) can serve as effective co-intelligence tools, facili-tating complex electrochemistry. AI-driven tools/LLMs have promising role ad-vancing electrochemistry research, though careful validation remains essential ensure scientific accuracy.

Язык: Английский

Процитировано

1
Nb2CTx-supported bimetallic NPs@ZIF-8 nanohybrid as ECL signal amplifier and peroxidase mimics for chromogranin a immunosensing in human serum and saliva DOI
Faheem Kareem, Yuan‐Fong Chou Chau, Minhaz Uddin Ahmed

и другие.

International Journal of Biological Macromolecules, Год журнала: 2024, Номер 287, С. 138476 - 138476

Опубликована: Дек. 9, 2024

Язык: Английский

Процитировано

0
AI-Driven Simulation of Stochastic Electrochemiluminescence DOI Creative Commons
Klaus Mathwig

ACS electrochemistry., Год журнала: 2024, Номер unknown

Опубликована: Дек. 17, 2024

Electrochemiluminescence (ECL) is a vital analytical technique widely used in immunosensing and emerging applications biological imaging. Traditional ECL simulations rely on finite element methods, which provide valuable insights into reaction dynamics spatial distribution of species. However, such methods are limited mesoscopic environments where stochastic effects become significant. Here, I present novel approach using ChatGPT o1 to generate Python-based simulation for reactions nanofluidic channel, incorporating diffusion, electrochemical chemical reactions, photon emission. The successfully replicates results from models while offering additional time-dependent behaviors enabling noise analysis simulated luminescence traces. iterative development this was rapid, requiring minimal coding expertise leveraging the model's "reasoning" capabilities implement physical principles, verify calculations, optimize performance. This work demonstrates that large language (LLMs) can serve as effective co-intelligence tools, facilitating complex electrochemistry. AI-driven tools/LLMs have promising role advancing electrochemistry research, though careful validation remains essential ensure scientific accuracy.

Язык: Английский

Процитировано

0