A team of researchers at PNNL is developing a new approach to explore the higher-dimensional shape of cyber systems to identify signatures of adversarial attacks.
New funding spurs a new approach to researching the effective retrieval and processing of legacy radioactive waste. Four-year focus of the IDREAM EFRC will link attosecond timescales to decades-long chemical processes.
The use of disciplines in pure mathematics can increase the reliability and explainability of machine learning models that “transcend human intuition,” according to PNNL scientists.
To overcome high-performance computing bottlenecks, a research team at PNNL proposed using graph theory, a mathematical field that explores relationships and connections between a number, or cluster, of points in a space.
Scientists are pioneering approaches in the branch of artificial intelligence known as machine learning to design and train computer software programs that guide the development of new manufacturing processes.
Morris Bullock has led PNNL's pursuit of the efficient conversion of electrical energy and chemical bonds through control of electron and proton transfers.
In adjoining Energy Sciences Center laboratories, researchers develop better energy storage devices by understanding the fundamental reactions that form interfaces.
