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