BEAVERTON, OR– Datavault AI Inc. (Nasdaq: DVLT) announced it will develop an AI-driven multi-modal machine learning system to support biofuel crop optimization.
The initiative focuses on increasing fatty acid metabolism efficiency in Brassica napus (canola) using high-performance computational modeling, supporting the EPA’s goal to replace up to 140,000 barrels of crude oil per day with biofuels. Aspects of this work will be facilitated with Datavault AI’s research partners from the Computing and Data Sciences Directorate at the U.S. Department of Energy’s Brookhaven National Laboratory.
The project will combine expertise in comparative genomics, multi-omics data processing and evolutionary biology to refine metabolic pathways in Brassica napus. Datavault AI is providing project oversight and quality assurance, ensuring that computational models are structured, validated and scalable for biofuel producers.
“As investments in biofuels continue to scale, we are positioned to bridge the gap between research and market adoption, ensuring that biofuel innovations translate into real economic value. Additionally, digital twins and Web 3.0 enable new levels of collaboration, data indexing and perceptions, exponentially accelerating the pace of meaningful discovery,” said Nathaniel Bradley, CEO of Datavault AI. “By applying computational validation and high-performance computing, we are accelerating the timeline for biofuel crop optimization and ensuring these breakthroughs move beyond the lab and into commercial adoption. Our approach to data monetization offers a fresh perspective on scientific sustainability and empowers human-driven discovery in the pursuit of cleaner earth resources.”
With traditional biofuel crop optimization taking years, computational simulations provide a more efficient and precise approach to analyzing genetic modifications that enhance oil production. Datavault AI’s high-performance computing infrastructure and Digital Twin models will be applied to process metabolic datasets, reducing the time required to develop commercially viable biofuel crop enhancements.
“This collaboration is reinforcing Datavault AI’s role in structuring data for commercialization within the renewable energy sector,” stated Sonia Choi, Chief Marketing Officer at Datavault AI and Lead Principal Investigator for the project. “Brookhaven National Laboratory is providing a foundation for biofuel advancements, while our role is ensuring that these insights are structured for large-scale implementation.”
For Datavault AI, this project represents a strategic foothold in a market poised for exponential growth as federal investments in biofuel research expand. Global biofuel demand is projected to increase by 38 billion liters between 2023 and 2028, a nearly 30% surge driven by biofuel policies and rising transport fuel demand. Additionally, biofuel capacity investments reached a decade high in 2022, with major renewable diesel refineries securing funding commitments exceeding $1.9 billion in North America alone.1 By structuring data for commercialization, Datavault AI is positioned to play a critical role in the transition to high-performance computing-driven renewable energy solutions, unlocking potential revenue streams in both public and private sector energy markets.
