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Researchers used quantum Monte Carlo calculations to accurately render the structure and electronic properties of germanium selenide, a semiconducting nanomaterial. Credit: Paul Kent/ORNL, U.S. Dept. of Energy

A multi-lab research team led by ORNL's Paul Kent is developing a computer application called QMCPACK to enable precise and reliable predictions of the fundamental properties of materials critical in energy research.

Oak Ridge National Laboratory researchers developed a device called a piezoelectric-driven magnetic actuator, or PEDMA, that can be inserted into the header of a microchannel heat exchanger to keep refrigerants flowing evenly and the HVAC unit running efficiently. Credit: ORNL, U.S. Dept. of Energy

Oak Ridge National Laboratory researchers demonstrated that microchannel heat exchangers in heating, ventilation and air conditioning units can keep refrigerants evenly and continually distributed by inserting a device called a piezoelectric-driven

Caption: ORNL researchers demonstrated a system that can detect propane leaks within seconds and notify emergency services immediately, well before flames ignite. Credit: ORNL, U.S. Dept. of Energy

Oak Ridge National Laboratory researchers demonstrated that an electrochemical sensor paired with a transmitter not only detects propane leaks within seconds, but it can also send a signal to alert emergency services.

Oak Ridge National Laboratory researchers used an invertible neural network, a type of artificial intelligence that mimics the human brain, to select the most suitable materials for desired properties, such as flexibility or heat resistance, with high chemical accuracy. The study could lead to more customizable materials design for industry.

A study led by researchers at ORNL could help make materials design as customizable as point-and-click.

This image illustrates lattice distortion, strain, and ion distribution in metal halide perovskites, which can be induced by external stimuli such as light and heat. Image credit: Stephen Jesse/ORNL

A study by researchers at the ORNL takes a fresh look at what could become the first step toward a new generation of solar batteries.

A zoomed in view of downtown Chattanooga’s sensors, which allowed the researchers to create building occupancy schedules that could enable improved energy efficiency and faster emergency responses. Credit: Andy Berres/ORNL, U.S. Dept. of Energy

Every day, hundreds of thousands of commuters across the country travel from houses, apartments and other residential spaces to commercial buildings — from offices and schools to gyms and grocery stores.

The Energy Exascale Earth System Model project reliably simulates aspects of earth system variability and projects decadal changes that will critically impact the U.S. energy sector in the future. A new version of the model delivers twice the performance of its predecessor. Credit: E3SM, Dept. of Energy

A new version of the Energy Exascale Earth System Model, or E3SM, is two times faster than an earlier version released in 2018.

Using quantum Monte Carlo methods, the researchers simulated bulk VO2. Yellow and turquoise represent changes in electron density between the excited and ground states of a compound composed of oxygen, in red, and vanadium, in blue, which allowed them to evaluate how an oxygen vacancy, in white, can alter the compound’s properties. Credit: Panchapakesan Ganesh/ORNL, U.S. Dept. of Energy

Neuromorphic devices — which emulate the decision-making processes of the human brain — show great promise for solving pressing scientific problems, but building physical systems to realize this potential presents researchers with a significant