A study by researchers at PNNL assessed the feasibility of using strontium isotope ratios and an existing machine learning–based model to predict and verify a product’s source—in this case, honey.
The Center for Continuum Computing at PNNL aims to integrate cloud platforms, high-performance computing, and edge devices into a seamless ecosystem that accelerates scientific discovery.
In a recent publication in Nature Communications, a team of researchers presents a mathematical theory to address the challenge of barren plateaus in quantum machine learning.
In the latest issue of the Domestic Preparedness Journal, Ashley Bradley and Kristin Omberg share how new research is shedding light on the scientific and technological challenges with detecting fentanyl.
Recycling polyolefin materials is challenging. One waste management strategy is plastic upcycling. New work demonstrates a single-step upcycling route coupling cracking and alkylation, recycling carbon and keeping valuable resources active.
Research at PNNL and the University of Texas at El Paso are addressing computational challenges of thinking beyond the list and developing bioagent-agnostic signatures to assess threats.