Topic: Advanced manufacturing | SLAC National Accelerator Laboratory

Illustration

Scientists have developed an AI-based method that helps gather data more efficiently in the search for new materials, allowing researchers...

News Feature

The method could lead to the development of new materials with tailored properties, with potential applications in fields such as climate change, quantum computing...

news collection

Two of the most urgent challenges of our time – clean energy and sustainability – require investigation at the atomic level.

Aerial image of workers installing solar panels on a home.

Illustration

With help from two small businesses, SLAC’s vintage ACE3P software is spreading its wings to make supercomputing easier and faster.

A large, complex shape is seen against a blue background crisscrossed with white lines. The shape is dark blue and resembles a brick partially topped with a thick shark’s fin. Three areas of bright red, orange and green, are on the shape’s bottom edge.

Press Release

SLAC and its collaborators are transforming the way new materials are discovered. In a new report, they combine artificial intelligence and accelerated experiments to...

SLAC postdoctoral scholar Fang Ren at an SSRL beamline

News Feature

The goal of these X-ray studies is to find ways to improve manufacturing of specialized metal parts for the aerospace, aircraft, automotive and healthcare...

Scientists have developed an AI-based method that helps gather data more efficiently in the search for new materials, allowing researchers to navigate complex design challenges with greater precision and speed.

The method could lead to the development of new materials with tailored properties, with potential applications in fields such as climate change, quantum computing and drug design.

Two of the most urgent challenges of our time – clean energy and sustainability – require investigation at the atomic level.

With help from two small businesses, SLAC’s vintage ACE3P software is spreading its wings to make supercomputing easier and faster.

SLAC and its collaborators are transforming the way new materials are discovered. In a new report, they combine artificial intelligence and accelerated experiments to discover potential alternatives to steel in a fraction of the time.

The goal of these X-ray studies is to find ways to improve manufacturing of specialized metal parts for the aerospace, aircraft, automotive and healthcare industries.

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Scientists Use Machine Learning to Speed Discovery of Metallic Glass

SLAC Scientists Investigate How Metal 3D Printing Can Avoid Producing Flawed Parts