The materials development landscape has been waiting for innovation for a long time. The amount of steps needed to go from the development of materials to manufacturing, to the supply chain, and then to sales is a multidimensional complexity.
But ever since the rise of AI and ML in common organizational practices, laboratories across the world have been able to siphon those steps into something far more manageable and streamlined, further helping to accelerate the process and make the development of materials – from beginning to end – far more cost-efficient.
The Impact Of Materials Informatics
The most impactful tool in this area is undoubtedly materials informatics, which is used to enhance the efficiency of materials development using information science and other methods, including statistical analysis.
It does this by using material databases, AI and ML to calculate properties with high precision on supercomputers, helping to eliminate the cost and time consumption of trial-and-error and further supporting researchers’ knowledge and insights into all of the data available.
Materials Informatics In Management and Experimentation
In terms of data, materials informatics helps to eradicate some of the most notorious challenges, including a lack of knowledge about the necessary data that can take researchers from targeting material to actually obtaining selected candidates. It also rids the problem of wasted data, the lack of predictability and the knowledge loss that comes with unnecessary repetition.
When it comes to experimentation, materials informatics can reduce the number of experiments and iterations needed to obtain material performance – which results in reduced R&D costs and helps to accelerate the steps between development and the supply chain. With easily applied AI and ML visualisations, researchers can achieve insights before unnecessary experimentation takes place, helping them to focus on the more urgent variables.
Materials Informatics In Development
In this way, materials informatics also aids the development process itself, as it helps researchers to pinpoint material candidates – with no loss of knowledge and no time spent on experimenting with different potentials.
In short, it has eradicated the methodology of trial-and-error and replaced it with a clear, data-driven approach. With data visualisation and predictive analysis, it can not only increase the chance of meeting a target but drastically cut down on the time it takes to get there.
Materials Informatics In Supply
When it comes to the supply chain, manufacturing and selling, materials informatics can also learn about an organisation and understand how to complete the process as a whole – meaning it will take into account pricing, geographical location, logistical considerations and more.
For instance, many products do not reach the market on time because their specific ingredients need to be revised – perhaps due to the increased emphasis on carbon footprint recognition, an existing ingredient is unreliable, or the characteristics of the product need to be changed.
With materials informatics, however, every aspect of the process is considered, which will lead to a drastically efficient workplace and far more room for innovative, straight-to-market products. Of course, it’s still early days, and not every lab has integrated software like this into their setup yet. But over the next few years, it is very likely that the effects of materials informatics will be felt not only in the world of science but the modern world in general.
