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The race to evolve and enhance battery technology is on. Batteries are crucial to a greener way of life, but how do we overcome supply chain challenges and shortages of key materials? The answer could lie in artificial intelligence ploughing through generations of research and data…
By Richard Kidd, Head of Chemistry Data at the Royal Society of Chemistry
Several large companies are predicting that larger batteries will follow the success of smaller, solid-state batteries and we could see some come to market as early as this year. As a result, we’re likely to see adjustment of materials and design strategies which contribute to the development of this new battery technology.
To extract the information needed to push battery capabilities forward, database technologies – such as Text and Data Mining (TDM) – can provide a crucial head start. By having artificial intelligence target specific questions, researchers, academics and scientists are able to set off in the right direction.
TDM allows technology to summarise past research, freeing up researchers for the more analytical work. This allows teams to innovate at pace to beat competition, stay ahead of market trends, and unearth new discoveries. Through facilitating the gathering of existing knowledge from integrated and enhanced data resources, applying modern search technology to large sets of text, imagery, tablets, charts and database resources can be crucial to make vital advances for the next breakthrough in battery technology research and recovery.
The data and information generated every day has significant economic and societal value, however, is often not used to full advantage. Scientific research papers and findings span decades, and we think 80% of data in the world resides in an unstructured format. Traditional information retrieval techniques are no longer adequate for interpreting the increasing volume of data. So, applying advanced AI-powered analysis tools to amplify discovery by smartly shifting through millions of documents can help to uncover hidden relationships within unstructured data.
Batteries play a crucial role in integrating renewables into the electricity grid and are aiding nations worldwide in working towards net zero targets. This sustainable future relies on cooperation between industry and the government, aided by interdisciplinary knowledge sharing, with more standardisation in data to open collections and research. Without this, data is inconsistent and unable to function properly. Standardisation in data can define how the data should be formatted, eliminate any unnecessary data and identify incorrect data points, improving the accuracy and analysis to help solve future issues and reduce uncertainty.
When considering a data mining project, sourcing a high-quality and reliable data set is the most important place to start. Any AI driven research tool can only be as good as the data it mines, so it is of utmost importance to use the best quality resources available. That’s where the Royal Society of Chemistry’s (RSC) journals archive comes in. The RSC’s collection includes high-quality, peer-reviewed research in digital form, spanning 180 years and several eras of scientific discovery. This high-quality resource allows researchers and academics to plug and play with other digital collections, allowing connections to be made across disciplines.
Knowing what you’re looking for is essential, as well as ruling out false leads. This is crucial on the path to discovery and could be the difference between project success or failure. Harnessing the speed and power of digital technology will provide research teams a crucial head-start on their project. Harnessing TDM technology to identify key pointers can set research on the right path from the very beginning. As more and more resources such as our own become available, the functionality – and impact – of these processes can only grow.
More information on Text and Data Mining can be found at: rsc.li/tdm
