RedDB in global media
Our redox molecules database, RedDB, has been highlighted by several news outlets around the globe in the languages of English [Phys.org, Technology Networks, Innovation Origins, C2W International, ETN India], Dutch [Link Magazine, Innovation Origins, C2W Mens & Molecule, Solar Magazine], Spanish [World Energy Trade], and Italian [Energia Italia].
Publication in Scientific Data – Nature
At [AMD] we created the RedDB, a database of 31,618 molecules that could potentially be used in future redox-flow batteries. These batteries hold great promise for energy storage. Among other things, we used artificial intelligence and physics-based simulations on supercomputers to identify the molecules’ properties. Today, the results have been published in the Scientific Data journal. In addition, we shared the entire database and source code openly. Lastly, a public news item is available at the DIFFER website.
Publication in Journal of Materials Chemistry A
Using physics-based high-throughput screening that is coupled with machine learning and automated search of material purchasability, we discovered 516 new aza-aromatic compounds that can be used in redox flow batteries for efficient large-scale energy storage. Based on the new findings, we also proposed a molecular engineering strategy in a way to balance the inherent trade-offs among the redox, solubility and chemical stability features of the compounds, all together to improve the efficiency of energy storage. The study is published in Journal of Materials Chemistry A from The Royal Society of Chemistry.
Publication in Nature Catalysis
Together with our collaborators from Netherlands and Germany, we developed a catalyst from simple materials that generates ammonia from nitrogen and hydrogen at relatively low temperatures. Our group has contributed the publication though the use of predictive reaction simulations based on quantum chemical calculations. The work is published in Nature Catalysis and a news item is available on the DIFFER website.
Publication in Energy Storage Materials
The data-driven material design is a highly effective approach for the exploration of new compounds for electrochemical energy storage. In a recent study that is just published in Energy Storage Materials, together with our collaborators from GES, we first computationally predicted 100s of new compounds, next experimentally tested 10s of them, then identified the most promising candidates for energy storage in redox flow batteries. A public news item is available on the DIFFER website.
Publication in Batteries
Our publication entitled Evaluation of Computational Chemistry Methods for Predicting Redox Potentials of Quinone-Based Cathodes for Li-Ion Batteries has been accepted in Batteries, which is openly accessible. Congratulations to Xuan and Abhishek!
Publication in The Journal of Physical Chemistry Letters
It is a present-day challenge to design and develop electrocatalytic materials for clean energy applications. By using robust high-throughput computational screening methods, we accelerate the virtual exploration of all-inorganic perovskite materials for electrochemical conversion reactions. To learn more, you can find the paper here.
Publication in Applied Surface Science
Hydrogen is a promising energy carrier, but new technological solutions are required for its efficient storage. In a collaborative project with researchers from China and Australia, we explored the use of metal-doped carbonous materials for high-density hydrogen storage. The full paper is openly accessible here.
Publication in Journal of Energy Chemistry
Our work entitled Surface charging activated mechanism change: A computational study of O, CO, and CO2interactions on Ag electrodes has been published in Journal of Energy Chemistry. Electrocatalytic and plasma-activated processes receive increasing attention in catalysis. In this work, we used the neutral and progressively charged Ag(111) metal surfaces as a model electrode to study the interactions of O, CO, and CO2 under plasma-activated conditions.
Publication in Nature Scientific Data
Our paper that describes the curation of aqueous solubility database is published on Nature Scientific Data. AqSolDB is the largest open-access aqueous solubility database consists of 9,982 unique compounds curated from 9 publicly available datasets. With an openly accessible, machine-readable, and well-structured format, AqSolDB will serve a broad community as a reference aqueous solubility dataset for the bench-marking of new experimental, physics-based, and machine learning modeling. Browse AqSolDB!