The application of physics-informed neural networks to hydrodynamic voltammetry
Electrochemical problems are widely studied in flowing systems since the latter offer improved sensitivity notably for electro-analysis and the possibility of steady-state measurements for fundamental studies even with macro-electrodes. We report the exploratory use of Physics-Informed Neural Networ...
Asıl Yazarlar: | Chen, H, Kätelhön, E, Compton, RG |
---|---|
Materyal Türü: | Journal article |
Dil: | English |
Baskı/Yayın Bilgisi: |
Royal Society of Chemistry
2022
|
Benzer Materyaller
-
Predicting voltammetry using physics-informed neural networks
Yazar:: Chen, H, ve diğerleri
Baskı/Yayın Bilgisi: (2022) -
A critical evaluation of using physics-informed neural networks for simulating voltammetry: strengths, weaknesses and best practices
Yazar:: Chen, H, ve diğerleri
Baskı/Yayın Bilgisi: (2022) -
Reversible voltammetry at cylindrical electrodes: Validity of a one-dimensional model
Yazar:: Le, H, ve diğerleri
Baskı/Yayın Bilgisi: (2020) -
Voltammetry at electrodes decorated with an insulating porous film: Understanding the effects of adsorption
Yazar:: Chan, HTH, ve diğerleri
Baskı/Yayın Bilgisi: (2017) -
Hydrodynamic microelectrode voltammetry
Yazar:: Rees, N, ve diğerleri
Baskı/Yayın Bilgisi: (2008)