Machine learning for flow batteries: opportunities and challenges
With increased computational ability of modern computers, the rapid development of
mathematical algorithms and the continuous establishment of material databases, artificial …
mathematical algorithms and the continuous establishment of material databases, artificial …
Unlocking the potential: Predicting redox behavior of organic molecules, from linear fits to neural networks
R Fedorov, G Gryn'ova - Journal of Chemical Theory and …, 2023 - ACS Publications
Redox-active organic molecules, ie, molecules that can relatively easily accept and/or
donate electrons, are ubiquitous in biology, chemical synthesis, and electronic and …
donate electrons, are ubiquitous in biology, chemical synthesis, and electronic and …
Quinones for Aqueous Organic Redox Flow Battery: A Prospective on Redox Potential, Solubility, and Stability
In recent years, there has been considerable interest in the potential of quinones as a
promising category of electroactive species for use in aqueous organic redox flow batteries …
promising category of electroactive species for use in aqueous organic redox flow batteries …
Static theoretical investigations of organic redox active materials for redox flow batteries
A Zaichenko, AJ Achazi, S Kunz, HA Wegner… - Progress in …, 2023 - iopscience.iop.org
New efficient redox flow batteries (RFBs) are currently of great interest for large-scale
storage of renewable energy. Further development requires the improvement of the redox …
storage of renewable energy. Further development requires the improvement of the redox …
Choice of the Right Supporting Electrolyte in Electrochemical Reductions: A Principal Component Analysis
F Mast, MM Hielscher, T Wirtanen… - Journal of the …, 2024 - ACS Publications
We present an analysis of a set of molecular, electrical, and electronic properties for a large
number of the cations of quaternary ammonium salts usually employed as supporting …
number of the cations of quaternary ammonium salts usually employed as supporting …
Autonomous data extraction from peer reviewed literature for training machine learning models of oxidation potentials
We present an automated data-collection pipeline involving a convolutional neural network
and a large language model to extract user-specified tabular data from peer-reviewed …
and a large language model to extract user-specified tabular data from peer-reviewed …
[HTML][HTML] DFT calculation, a practical tool to predict the electrochemical behaviour of organic electrolytes in aqueous redox flow batteries
J Asenjo-Pascual, I Salmeron-Sanchez… - Journal of Power …, 2023 - Elsevier
Herein, a computational predictive tool for redox flow batteries based on NBO and ADCH
charge distribution studies is presented and supported by experimental evidence. Using …
charge distribution studies is presented and supported by experimental evidence. Using …
N‐Alkylated Pyridoxal Derivatives as Negative Electrolyte Materials for Aqueous Organic Flow Batteries: Computational Screening
A Hamza, FB Németh, Á Madarász… - … A European Journal, 2023 - Wiley Online Library
N‐functionalized pyridinium frameworks derived from the three major vitamers of vitamin B6,
pyridoxal, pyridoxamine and pyridoxine, have been screened computationally for …
pyridoxal, pyridoxamine and pyridoxine, have been screened computationally for …
Predicting redox potentials by graph‐based machine learning methods
The evaluation of oxidation and reduction potentials is a pivotal task in various chemical
fields. However, their accurate prediction by theoretical computations, which is a …
fields. However, their accurate prediction by theoretical computations, which is a …
AI for organic and polymer synthesis
Recent years have witnessed the transformative impact from the integration of artificial
intelligence with organic and polymer synthesis. This synergy offers innovative and …
intelligence with organic and polymer synthesis. This synergy offers innovative and …