TL;DR:
- London-based startup Orbital Materials is leveraging generative AI to accelerate the development of clean energy technologies.
- The goal is to create computer models that can identify the best formulas for sustainable products like jet fuel and rare-earth mineral-free batteries.
- Orbital Materials aims to make AI as accessible and effective for chemical engineering as it is for other design disciplines.
- The current technology for decarbonizing the planet lacks the speed required, but AI researchers believe they can help bridge the gap.
- The startup plans to train AI models using extensive data on molecular structures to generate proposed molecular formulas for desired properties.
- Tech investors are interested in companies improving greener material production, particularly in sectors like renewable energy, transportation, and agriculture.
- Challenges lie in scaling the production of advanced materials and navigating complex supply chains.
- Despite the risks, the potential trillion-dollar markets in batteries and carbon capture make these investments attractive.
Main AI News:
Artificial intelligence (AI) has been making waves across various industries, promising to simplify and enhance our lives. From virtual assistants to tutors, lawyers, and doctors, companies have been touting the capabilities of AI. But what about a superhuman chemical engineer? London-based startup Orbital Materials aims to create just that by harnessing the power of generative AI, specifically to accelerate the development of clean energy technologies. The company envisions computer models that are as accessible and effective as the software engineers currently use to design products like airplane wings and household furniture.
Jonathan Godwin, a co-founder of Orbital Materials, has a vision of an AI system that can predict the behavior of new molecules not just in a lab but in the real world. While AI has been deployed to search for greener materials, the technology has yet to catch up for many of the materials required to decarbonize the planet. The process of bringing advanced materials from discovery to the market can take decades, posing a significant challenge for businesses and nations aiming to rapidly reduce emissions and achieve net-zero targets. Material science startup VSParticle’s co-founder, Aaike van Vugt, stresses the need for accelerated progress within the next 10 years.
AI researchers, however, believe they can help overcome these hurdles. Godwin, who previously researched advanced material discovery at DeepMind, is inspired by the breakthroughs in AI, such as AlphaFold’s ability to predict protein structures, which speeds up the search for new drugs and vaccines. Godwin compares Orbital Materials’ approach to AI image generators like Dall-E and Stable Diffusion, which create photorealistic images based on text prompts. Orbital Materials plans to train models using vast amounts of data on the molecular structure of materials. By inputting desired properties and material specifications, such as an alloy capable of withstanding high heat, the model would generate proposed molecular formulas.
Tech investors are actively seeking companies that can improve the production of greener materials, particularly in Europe, where regulations are compelling manufacturers to reduce carbon emissions or face penalties. Advanced materials markets in sectors like renewable energy, transportation, and agriculture are expected to grow significantly in the coming years. Some researchers have even established “self-driving labs” that combine AI systems with robots to accelerate the search for new materials.
Orbital Materials, having secured $4.8 million in undisclosed initial funding, plans to initially focus on carbon capture. The startup aims to develop an algorithmic model for designing molecular sieves, which can efficiently extract CO2 and other harmful chemicals from emissions. Carbon capture technology has not yet achieved scalability, but the increasing government incentives, particularly in the US, are driving interest in its deployment. Eventually, Orbital Materials intends to expand its scope to areas like fuel and batteries, following the business model of synthetic biology and drug discovery companies.
However, the path to success involves more than just perfecting AI capabilities. The production of advanced materials, particularly in sectors like battery and fuel production, requires collaboration with established enterprises and intricate supply chains. MIT’s Gomez-Bombarelli argues that this can be even more challenging and costly than developing new drugs. Despite the risks, tech investors like Flying Fish Partners recognize the immense potential in markets such as batteries and carbon capture, which are estimated to reach a value of $1 trillion.
Gomez-Bombarelli understands the challenges firsthand, having been involved in a similar venture called Calculario in 2015. Despite using AI and quantum chemistry to expedite the discovery process for new materials, the company struggled to gain traction and had to refocus on the OLED industry. However, with advancements in computing power and greater awareness of AI’s potential, the market landscape may be more favorable now.
Conclusion:
The application of AI in green material development, as demonstrated by Orbital Materials, represents a significant opportunity in the market. By leveraging AI’s predictive capabilities, businesses can accelerate the discovery and development of sustainable materials. However, challenges related to scaling production and supply chain complexities need to be addressed for widespread adoption. Nonetheless, the potential for growth in markets such as batteries and carbon capture makes investing in this field a promising prospect for tech investors.
