news, journals and articles from all over the world.
A recent collaboration among researchers from HUN-REN Wigner Research Centre for Physics in Hungary and the Department of Energy’s Pacific Northwest National Laboratory, along with industry collaborators SandboxAQ and NVIDIA, has achieved unprecedented speed and performance in efforts to model complex metal-containing molecules.
The speed and agility of cloud computing opens doors to completing advanced computational chemistry workflows in days instead of months.
Researchers will explore climate, pathogens and energy-efficient microelectronics using 3 million node hours on the nation’s supercomputers.
New research employs shutter speed analogies to validate 55-year-old theory about chemical reaction rates.
As new paradigms in advanced computing take shape, computational chemistry researchers are finding new ways to solve challenging chemistry problems.
Machine learning interatomic potentials (MLIP)s have become an efficient and less expensive alternative to traditional quantum chemical simulations.
The three-year grant is earmarked for the purchase of an additional high-performance computer cluster to join existing MERCURY resources hosted offsite. The grant will enable 13 more undergraduate-focused research groups to benefit, growing the consortium to 47 computational scientists at 41 institutions nationwide.
PNNL is collaborating with Microsoft, Micron and other partners to make computational chemistry broadly available.
A new online platform to explore computationally calculated chemical reaction pathways has been released, allowing for in-depth understanding and design of chemical reactions.
Computational chemists reduce or eliminate hazardous materials by running simulations to develop fast, accurate models. MIT researchers use SDSC’s supercomputer to explore the luminescent properties of iridium-centered phosphors.
Scientists at Argonne National Laboratory have recently demonstrated an automated process for identifying and exploring promising new materials by combining machine learning (ML) and high performance computing.
The U.S. Department of Energy (DOE) has awarded DOE’s Argonne National Laboratory with $600,000 in federal funding to work on two new projects that will advance cutting edge manufacturing and clean energy technologies.
Scientists at Argonne have used machine learning algorithms to predict how long a lithium-ion battery will last.
Wet electrolyte could be a key to inexpensive energy storage.
Large ion clusters known as aggregates are an important emerging topic for research on electrolytes in batteries. The research indicates that aggregates can affect electrolyte properties, including stability and ion transport.
Physical chemist Marcel Baer brings meticulous care to understanding how energy moves through molecules.
Stepping into their superhero gear, Argonne scientists are using science and the world’s best technology to combat some of Earth’s toughest foes, from pollution to climate change.
In a collaborative effort to “recover, recycle and reuse,” Argonne strengthens research that addresses pollution, greenhouse gases and climate change and aligns with new policies for carbon emission reduction.
A growing global population will need energy from a range of sources. Scientists at Argonne National Laboratory have been pioneering solutions for 75 years.
A recent special issue in The Journal of Chemical Physics highlights PNNL’s contributions to developing two prominent open-source software packages for computational chemistry used by scientists around the world.
UB’s Eva Zurek, a theoretical chemist, is an expert on high-pressure chemistry and the search for superconductors BUFFALO, N.Y. — After decades of hunting, scientists recently announced the discovery of a room-temperature superconductor — an elusive material that conveys electricity with…
Anyone with a smartphone can download the app ViDok, which lets users pick from a library of molecules that might bind to key proteins on the SARS-CoV-2 virus, which causes COVID-19, and then can tweak the molecules to try to find a better fit.
In a new study from the U.S. Department of Energy’s Argonne National Laboratory, researchers are accelerating the hunt for the best possible battery components by employing artificial intelligence.
University reports a new electrocatalyst that converts carbon dioxide and water into ethanol with very high energy efficiency, high selectivity for the desired final product and low cost.
In a recent study, led by UC San Diego’s Rommie Amaro, researchers broke new ground with their molecular simulations in terms of size, complexity and methodological analyses of the viral envelope.
As a staff member in the Theory and Computation Group at Brookhaven Lab’s Center for Functional Nanomaterials, Qu applies various approaches in artificial intelligence to analyze experimental and computational nanoscience data.
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