A new wave of innovation is emerging in the field of chemicals and materials, driven by the power of AI-driven simulation. Companies like SandboxAQ are leveraging cloud hyperscalers and robust data strategies to accelerate the discovery of new materials and chemicals. This technology has far-reaching implications, from predicting battery cycle life to eliminating toxic PFAS chemicals from the environment. According to Jack D. Hidary, CEO of SandboxAQ, “Simulation will drive a new wave of GPU use, powering previously unattainable insights about our physical world.”
By combining simulation with advanced AI, companies can unlock solutions to some of the biggest addressable markets in the world. In collaboration with EY, SandboxAQ supports businesses in proprietary material discovery and streamlining general manufacturing processes. With its enterprise SaaS platform hosted on AWS, SandboxAQ has already achieved remarkable breakthroughs, including predicting optimal organometallic catalysts and discovering new cathodes for solid oxide fuel cells.
The traditional approach to assessing battery lifetime and performance can be time-consuming, but with SandboxAQ’s simulation software and NOVONIX’s proprietary battery data platform, research groups and companies can now access actionable information faster. This accelerated product development timeline is a game-changer for the industry.
SandboxAQ’s global foundational technology platform, which embeds EY.ai with leading-edge AI capabilities, robust data strategies, cloud hyperscalers, and efficient AI management, sets new industry benchmarks for responsible and ethical AI use.
The case studies presented are impressive, to say the least. From predicting optimal Ni/Fe Carboxylate organometallic catalysts in a library of millions of ligands to accelerating battery cycle life prediction using Graph Neural Networks (GNN), the applications of AI-driven simulation are vast and varied.
One standout example is the discovery of new cathodes for Solid Oxide Fuel Cells (SOFC). By developing a funnel-based searching process over tens of thousands of materials, SandboxAQ was able to identify promising perovskites with high potential for oxygen reduction reactions. The resulting material, BFCZ75, displays state-of-the-art cell performance, outperforming many existing materials.
Another notable example is the 1 Million+ core PFAS elimination simulation, which enabled a Fortune 500 company to reduce their waste PFAS output by 90%+. By accurately predicting the dissociation energy of alpha C-F bond of PFOA (perfluorooctanoic acid), SandboxAQ provided experimental chemists with new avenues to reduce the environmental impact and healthcare costs associated with PFAS exposure.
As CEO Jack D. Hidary notes, “Simulation will drive a new wave of GPU use, powering previously unattainable insights about our physical world that go beyond what extractive or generative AI are capable of unlocking.” The potential for AI-driven simulation to revolutionize the chemicals and materials space is vast, and companies that incorporate physics-based simulation and AI into their research programs will undoubtedly gain a competitive advantage.
In conclusion, the power of emerging technologies in AI-driven simulation is making breakthroughs in the chemicals and materials space more realizable and accessible. By collaborating with EY and SandboxAQ, businesses can position themselves at the forefront of innovation and reap the benefits of accelerated product development timelines and reduced environmental impact.
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