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Researchers relied on support from ORNL’s Quantum Computing User Program to simulate a key quantum state at one of the largest scales reported. The findings could mark a step toward improving quantum simulations. Credit: Getty Images
Steering toward quantum simulation at scale
PowerGrid Auburn University
Auburn, ORNL to partner on grid security
Three ORNL researchers receive Outstanding Young Manufacturing Engineer Award
Researchers receive SME awards

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ORNL, VA and Harvard researchers developed a sparse matrix full of anonymized information on what is thought to be the largest cohort of healthcare data used for this type of research in the U.S. The matrix can be probed with different methods, such as KESER, to gain new insights into human health. Credit: Nathan Armistead/ORNL, U.S. Dept. of Energy

VA, ORNL and Harvard develop novel method to identify complex medical relationships

A team of researchers has developed a novel, machine learning–based  technique to explore and identify relationships among medical concepts using electronic health record data across multiple healthcare providers.

QLAN submit - A team from the U.S. Department of Energy’s Oak Ridge National Laboratory, Stanford University and Purdue University developed and demonstrated a novel, fully functional quantum local area network, or QLAN, to enable real-time adjustments to information shared with geographically isolated systems at ORNL using entangled photons passing through optical fiber. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

QIS investments position ORNL to lead the quantum revolution

A rapidly emerging consensus in the scientific community predicts the future will be defined by humanity’s ability to exploit the laws of quantum mechanics.

This protein drives key processes for sulfide use in many microorganisms that produce methane, including Thermosipho melanesiensis. Researchers used supercomputing and deep learning tools to predict its structure, which has eluded experimental methods such as crystallography. Credit: Ada Sedova/ORNL, U.S. Dept. of Energy

Scientists use Summit supercomputer, deep learning to predict protein functions at genome scale

A team of scientists led by the Department of Energy’s Oak Ridge National Laboratory and the Georgia Institute of Technology is using supercomputing and revolutionary deep learning tools to predict the structures and roles of thousands of proteins with unknown functions.

A material’s spins, depicted as red spheres, are probed by scattered neutrons. Applying an entanglement witness, such as the QFI calculation pictured, causes the neutrons to form a kind of quantum gauge. This gauge allows the researchers to distinguish between classical and quantum spin fluctuations. Credit: Nathan Armistead/ORNL, U.S. Dept. of Energy

Key witness helps scientists detect ‘spooky’ quantum entanglement in solid materials

A team led by the U.S. Department of Energy’s Oak Ridge National Laboratory demonstrated the viability of a “quantum entanglement witness” capable of proving the presence of entanglement between magnetic particles, or spins, in a quantum material.

ORNL researchers demonstrated a 3D printed power pole made of bioderived and recycled materials could be easily manufactured, transported and assembled, enabling the quick restoration of power after natural disasters. Credit: ORNL, U.S. Dept. of Energy

Manufacturing – Powered by nature

A team of researchers at Oak Ridge National Laboratory demonstrated the ability to additively manufacture power poles from bioderived and recycled materials, which could more quickly restore electricity after natural disasters.

ORNL researchers installed and demonstrated their wireless charging technology for the first time on an autonomous vehicle – the Local Motors Olli shuttle bus. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

Wireless charging – Get on the bus

Oak Ridge National Laboratory researchers demonstrated their wireless charging technology on an autonomous electric vehicle for the first time in a project with Local Motors.

ORNL researchers are developing a method to print low-cost, high-fidelity, customizable sensors for monitoring power grid equipment. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

Sensors – Printing on the fly

A method developed at Oak Ridge National Laboratory to print high-fidelity, passive sensors for energy applications can reduce the cost of monitoring critical power grid assets.

ORNL has modeled the spike protein that binds the novel coronavirus to a human cell for better understanding of the dynamics of COVID-19. Credit: Stephan Irle/ORNL, U.S. Dept. of Energy

Computing – Modeling COVID dynamics

To better understand the spread of SARS-CoV-2, the virus that causes COVID-19, Oak Ridge National Laboratory researchers have harnessed the power of supercomputers to accurately model the spike protein that binds the novel coronavirus to a human cell receptor.

Pella Marion

Hydropower – More than megawatts

A new Department of Energy report produced by Oak Ridge National Laboratory details national and international trends in hydropower, including the role waterpower plays in enhancing the flexibility and resilience of the power grid.

Suman Debnath is using simulation algorithms to accelerate understanding of the modern power grid and enhance its reliability and resilience. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

Suman Debnath: Applied math, modeling for the grid of the future

Planning for a digitized, sustainable smart power grid is a challenge to which Suman Debnath is using not only his own applied mathematics expertise, but also the wider communal knowledge made possible by his revival of a local chapter of the IEEE professional society.