AI and robots are the new battery development dream team

Why battery development is difficult

Battery development is a complex field with several challenges to overcome. At present, the main issues tend to include, but are not limited to:

• Energy density: Batteries must store more energy in a smaller volume to cater to the needs of different applications, particularly in electric cars and portable gadgets. Attaining higher energy densities while ensuring safety and longevity is a significant obstacle.
• Lifespan and cycle stability: Batteries gradually lose their ability to hold a charge over time. The number of full charge-discharge cycles a battery can go through before it reaches a certain degree of degradation (usually 80% of original capacity) is an important aspect of battery performance. Improving the longevity and cycle stability of batteries is crucial.
• Charging speed: Faster charging is a key demand for batteries, especially for electric vehicles, where prolonged charging times can deter potential users. Balancing faster charging times while preventing overheating or degradation of the battery is a complex challenge.
• Cost: Many advanced batteries that offer better performance are also more expensive to produce. Reducing the cost of these batteries is essential for them to become more widespread.
• Safety: Higher energy densities and faster charging times can increase the risk of battery failures and fires. Ensuring safety is always a paramount concern in battery development.

• Sustainability and recycling: Many batteries, particularly lithium-ion batteries, use relatively rare and expensive materials whose mining and use has a significant environmental impact. There are also some very important ethical and geopolitical issues around child labor and poor working conditions where most materials are commonly sourced. Creating more sustainable batteries and improving battery recycling processes are important goals.
• Material scarcity: Many batteries rely on materials like lithium and cobalt, which are limited in supply. There's also a geopolitical risk as these resources are concentrated in specific regions.
• The scale of production: With the growing demand for batteries, particularly for electric vehicles and renewable energy storage, the ability to scale up production while maintaining quality and cost-effectiveness is a significant challenge.

Innovations in materials science, engineering, and manufacturing are continually being pursued to address these issues. To this end, it is hoped that robotics and AI can significantly aid in accelerating these efforts and overcoming the challenges faced in battery development.

Robotics and AI

To get an appreciation of the potential impact AI and robotics could have on the battery industry, we already have a test case from Carnegie Mellon University. In September of 2022, a team of researchers combined cutting-edge AI and robotics technologies to drastically speed up the research process for creating new forms of better batteries.

Since efficient ion conductivity is crucial for designing lithium-ion batteries, researchers are constantly searching for ways to optimize it. The Carnegie Mellon team may have found a novel way to speed this up dramatically.

In their paper, published in Nature Communications, the researchers highlighted successfully pairing a specific type of robot with an AI learning system to develop advanced, non-aqueous liquid electrolytes.

To expedite this process, the researchers created a robot named "Clio" that utilized the necessary ingredients to craft electrolyte samples based on instructions.

A computer with a deep learning AI program named "Dragonfly" was incorporated into the system alongside "Clio" and electrolyte sensors.

"Dragonfly" analyzed the data and proposed suggestions for improvement. "Clio" then implemented these suggestions to create a new sample. The process was repeated over two days until the electrolyte quality improved. The mechanical duo was halted once the researchers deemed the products were ready for testing.

During the experiment, the scientists observed that their paired AI system functioned as intended, gradually enhancing the electrolyte samples.

The most exceptional outcome yielded an improvement of 13% compared to the current top-performing batteries on the market. The researchers now intend to enhance further their system's capabilities to assess various objectives and increase speed.

This research and development area has already expanded outside of academia, with companies like Chemix using a similar approach to develop advanced batteries for the EV market. Whether through university research or commercial development, it is hoped that the discovery of new and innovative materials can be accelerated through automation and machine learning. This could lead to improved batteries, more efficient photovoltaic systems, and other advancements.

And that is your lot for today.

While new battery development is complex and intensive, robotics and artificial intelligence might expedite this process to produce safe and reliable future batteries. The work of researchers at Carnegie Mellon, among others, has already shown some interesting results, and it will be exciting to see what this embryonic field will come up with in the future.