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New Material for Lower Cost Nuclear Fuel Recycling

Computer-inspired materials discovery has led to the discovery of a new material that might help in nuclear fuel recycling and waste reduction by capturing certain gases released during reprocessing. ...

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Symmetry Breaking with Euclidean Neural Networks

Curie's principle states that "when effects show certain asymmetry, this asymmetry must be found in the causes that gave rise to them". In this paper, we demonstrate that symmetry equivariant neural n...

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Electronic Properties of Materials at 100 PFLOP/s

Mauro Del Ben (CCMC) and Charlene Yang (NERSC) lead the optimization of the BerkeleyGW software package on leadership class HPC systems. By exploiting GPU acceleration they demonstrate for the first t...

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AI for More Efficient Flying Qbits

A cross-Divisional collaboration is working on an AI approach to developing more efficient quantum transducers.

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Materials Simulations on Quantum Computers 101

The emergence of quantum computers provides a promising path forward for testing and analyzing the remarkable, and often counter-intuitive, behavior of quantum materials. In our recently released top...

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Ultracompact Hamiltonian Eigenstates

We have developed and analyzed an optimal version of a highly efficient quantum algorithm, variational quantum phase estimation (VQPE), for ground and excited state calculations of general many-body s...

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NWChem’s Planewave “Purrs” on Intel’s KNL Nodes

A team of researchers at the Berkeley Lab, PNNL and Intel are working hard to make sure that computational chemists are prepared to compute efficiently on next-generation exascale machines. Recently, ...

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Researchers Catch Extreme Waves with High-Resolution Modeling

Using decades of high-resolution global climate data, researchers were able to capture the formation of tropical cyclones and the extreme waves that they generate.

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Quantum Chemistry with Quantum Computers

Berkeley Lab is preparing for quantum computing future and Luis Alvarez Fellow in Computing Science Jarrod McClean is hard at work to find ways to exploit this new computing paradigm to simulate and p...

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Materials discoveries: don't dump the past

Materials discoveries are typically driven by their potential for industrial and commercial applications. In a new Perspective article, Nils Zimmermann and Maciej Haranczyk unravel trends in zeolite ...


High Resolution Climate Simulations

Not long ago, it would have taken several years to run a high-resolution simulation on a global climate model. But using supercomputing resources at NERSC, climate scientist Michael Wehner of Berkeley...

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Major Speedups Through Intel Parallel Computing Center

Quicker time to discovery. That’s what scientists focused on quantum chemistry are looking for. To achieve this, changes must be made in the HPC software used in quantum chemistry research to take adv...

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Assessing the Impact of Human-Induced Climate Change

The past century has seen a 0.8°C (1.4°F) increase in average global temperature. What remains unclear is precisely what fraction of the observed changes in these climate-sensitive systems can confid...

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Simulations Confirm Observations on 2015 India/Pakistan Heat Waves

Three researchers from Berkeley Lab are co-authors on the paper, "The Deadly Combination of Heat and Humidity in India and Pakistan in Summer 2015," which examined observational and simulated temperat...

The Computational Chemistry, Materials & Climate Group is focused on enabling scientific discovery through the development of advanced software applications, tools, and libraries in key research areas in chemistry, materials science and climate research, as well as the development of scientific computing applications and capabilities for the integration and analysis of complex data from simulation and experiment. Members of the group have expertise in domain science areas, applied mathematics, and computer science. The group develops

  • Scientific applications in areas such as atmospheric modeling and materials & chemical sciences

  • Methodologies and strategies for computational science, designing and implementing highly efficient computational kernels

Group Leader: Bert de Jong

Administrative Assistant: Rachel Lance