Currently, both the rate and output of traditional materials synthesis and discovery are too slow and too small to efficiently provide needed advances. This project will establish an autonomous chemistry lab (ACL) that can operate 24/7 with high precision to greatly accelerate materials discovery and innovation.
There is a critical need for efficient scale-up of atom precise synthesis products to quantities that enable full characterization of the structure-composition-property relationships and for scalable deployment of important material for key applications.
Over the last two decades, aberration-corrected scanning transmission electron microscopy (STEM) has become the mainstay of condensed matter physics, materials science, chemistry, catalysis, and nanotechnology.
Automation and autonomy can enable revolutionary scientific advances by coordinating a diverse array of experimental and computational capabilities more efficiently and more effectively than current hands-on approaches. We propose an INTERSECT Self-Driven Processes, Experiments, Laboratories (SPEL) project to create an autonomous system to plan and adaptively control additive manufacturing (AM) build processes.
The proposed project will research upon the challenge of emulating and automating the emulation of the real-world energy system and power grid at the Grid Research Integration and Deployment Center (GRID-C) laboratories.
We will provide an INTERSECT quantum edge node (IQEN) to provide the other INTERSECT edge nodes and HPC resources access to a quantum computer/simulator/accelerator for natively quantum tasks including those from the Spallation Neutron Source (SNS) and materials sciences and technology edge node(s).
This project creates an open federated hardware/software architecture for the laboratory of the future using a novel system-of-systems (SoS) and microservice architecture approach, connecting scientific instruments, robot-controlled laboratories and edge/center computing/data resources to enable autonomous experiments, “self-driving” laboratories, smart manufacturing, and AI-driven design, discovery and evaluation.
This project addresses the frameworks and platforms to support the designs and operations of domain science projects by integrating the technologies, both existing and under development, into current working ecosystems systems.