Nanoengineers Develop Predictive Database for Materials

November 29, 2022

Nov. 29, 2022 — Nanoengineers at the University of California San Diego’s Jacobs School of Engineering have developed an AI algorithm that predicts the structure and dynamic properties of any material—whether existing or new—almost instantaneously. Known as M3GNet, the algorithm was used to develop matterverse.ai, a database of more than 31 million yet-to-be-synthesized materials with properties predicted by machine learning algorithms. Matterverse.ai facilitates the discovery of new technological materials with exceptional properties.

Schematic courtesy of Shyue Ping Ong, Jacobs School of Engineering, University of California San Diego.

The team behind M3GNet, led by UC San Diego nanoengineering professor Shyue Ping Ong, uses matterverse.ai and the new capabilities of M3GNet in their search for safer and more energy-dense electrodes and electrolytes for rechargeable lithium-ion batteries. The project is explored in the November issue of Nature Computational Science.

The properties of a material are determined by the arrangement of its atoms. However, existing approaches to obtain that arrangement are either prohibitively expensive or ineffective for many elements.

“Similar to proteins, we need to know the structure of a material to predict its properties.” said Ong, the associate director of the Sustainable Power and Energy Center at the Jacobs School of Engineering. “What we need is an AlphaFold for materials.”

AlphaFold is an AI algorithm developed by Google DeepMind to predict protein structure. To build the equivalent for materials, Ong and his team combined graph neural networks with many-body interactions to build a deep learning architecture that works universally, with high accuracy, across all the elements of the periodic table.

“Mathematical graphs are really natural representations of a collection of atoms,” said Chi Chen, a former senior project scientist in Ong’s lab and first author of the work, who is now a senior quantum architect at Microsoft Quantum. “Using graphs, we can represent the full complexity of materials without being subject to the combinatorial explosion of terms in traditional formalisms.”

To train their model, the team used the huge database of materials energies, forces and stresses collected in the Materials Project over the past decade. The result is the M3GNet interatomic potential (IAP), which can predict the energies and forces in any collection of atoms. Matterverse.ai was generated through combinatorial elemental substitutions on more than 5,000 structural prototypes in the Inorganic Crystal Structure Database (ICSD). The M3GNet IAP was then used to obtain the equilibrium crystal structure—a process called “relaxation”—for property prediction.

Of the 31 million materials in matterverse.ai today, more than a million are predicted to be potentially stable. Ong and his team intend to greatly expand not just the number of materials, but also the number of ML-predicted properties, including high-value properties with small data sizes using a multi-fidelity approach they developed earlier.

Beyond structural relaxations, the M3GNet IAP also has broad applications in dynamic simulations of materials and property predictions as well.

“For instance, we are often interested in how fast lithium ions diffuse in a lithium-ion battery electrode or electrolyte. The faster the diffusion, the more quickly you can charge or discharge a battery,” Ong said. “We have shown that the M3GNet IAP can be used to predict the lithium conductivity of a material with good accuracy. We truly believe that the M3GNet architecture is a transformative tool that can greatly expand our ability to explore new material chemistries and structures.”

To promote the use of M3GNet, the team has released the framework as an open-source Python code on Github. Since posting the preprint on Arxiv in Feb 2022, the team has received interest from academic researchers and those in the industry. There are plans to integrate the M3GNet IAP as a tool in commercial materials simulation packages.

This work was authored by Chi Chen and Shyue Ping Ong at UC San Diego. The research was primarily funded by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences, Materials Sciences and Engineering Division under the Materials Project program. Part of the work was funded by LG Energy Solution through the Frontier Research Laboratory Program. This work used the Extreme Science and Engineering Discovery Environment (XSEDE).


Source: Emerson Dameron, UCSD

Subscribe to HPCwire's Weekly Update!

Be the most informed person in the room! Stay ahead of the tech trends with industy updates delivered to you every week!

Nvidia Touts Strong Results on Financial Services Inference Benchmark

February 3, 2023

The next-gen Hopper family may be on its way, but that isn’t stopping Nvidia’s popular A100 GPU from leading another benchmark on its way out. This time, it’s the STAC-ML inference benchmark, produced by the Securi Read more…

Quantum Computing Firm Rigetti Faces Delisting

February 3, 2023

Quantum computing companies are seeing their market caps crumble as investors patiently await out the winner-take-all approach to technology development. Quantum computing firms such as Rigetti Computing, IonQ and D-Wave went public through mergers with blank-check companies in the last two years, with valuations at the time of well over $1 billion. Now the market capitalization of these companies are less than half... Read more…

US and India Strengthen HPC, Quantum Ties Amid Tech Tension with China

February 2, 2023

Last May, the United States and India announced the “Initiative on Critical and Emerging Technology” (iCET), aimed at expanding the countries’ partnerships in strategic technologies and defense industries across th Read more…

Pittsburgh Supercomputing Enables Transparent Medicare Outcome AI

February 2, 2023

Medical applications of AI are replete with promise, but stymied by opacity: with lives on the line, concerns over AI models’ often-inscrutable reasoning – and as a result, possible biases embedded in those models Read more…

Europe’s LUMI Supercomputer Has Officially Been Accepted

February 1, 2023

“LUMI is officially here!” proclaimed the headline of a blog post written by Pekka Manninen, director of science and technology for CSC, Finland’s state-owned IT center. The EuroHPC-organized supercomputer’s most Read more…

AWS Solution Channel

Shutterstock 2069893598

Cost-effective and accurate genomics analysis with Sentieon on AWS

This blog post was contributed by Don Freed, Senior Bioinformatics Scientist, and Brendan Gallagher, Head of Business Development at Sentieon; and Olivia Choudhury, PhD, Senior Partner Solutions Architect, Sujaya Srinivasan, Genomics Solutions Architect, and Aniket Deshpande, Senior Specialist, HPC HCLS at AWS. Read more…

Microsoft/NVIDIA Solution Channel

Shutterstock 1453953692

Microsoft and NVIDIA Experts Talk AI Infrastructure

As AI emerges as a crucial tool in so many sectors, it’s clear that the need for optimized AI infrastructure is growing. Going beyond just GPU-based clusters, cloud infrastructure that provides low-latency, high-bandwidth interconnects and high-performance storage can help organizations handle AI workloads more efficiently and produce faster results. Read more…

Intel’s Gaudi3 AI Chip Survives Axe, Successor May Combine with GPUs

February 1, 2023

Intel's paring projects and products amid financial struggles, but AI products are taking on a major role as the company tweaks its chip roadmap to account for more computing specifically targeted at artificial intellige Read more…

Quantum Computing Firm Rigetti Faces Delisting

February 3, 2023

Quantum computing companies are seeing their market caps crumble as investors patiently await out the winner-take-all approach to technology development. Quantum computing firms such as Rigetti Computing, IonQ and D-Wave went public through mergers with blank-check companies in the last two years, with valuations at the time of well over $1 billion. Now the market capitalization of these companies are less than half... Read more…

US and India Strengthen HPC, Quantum Ties Amid Tech Tension with China

February 2, 2023

Last May, the United States and India announced the “Initiative on Critical and Emerging Technology” (iCET), aimed at expanding the countries’ partnership Read more…

Intel’s Gaudi3 AI Chip Survives Axe, Successor May Combine with GPUs

February 1, 2023

Intel's paring projects and products amid financial struggles, but AI products are taking on a major role as the company tweaks its chip roadmap to account for Read more…

Roadmap for Building a US National AI Research Resource Released

January 31, 2023

Last week the National AI Research Resource (NAIRR) Task Force released its final report and roadmap for building a national AI infrastructure to include comput Read more…

PFAS Regulations, 3M Exit to Impact Two-Phase Cooling in HPC

January 27, 2023

Per- and polyfluoroalkyl substances (PFAS), known as “forever chemicals,” pose a number of health risks to humans, with more suspected but not yet confirmed Read more…

Multiverse, Pasqal, and Crédit Agricole Tout Progress Using Quantum Computing in FS

January 26, 2023

Europe-based quantum computing pioneers Multiverse Computing and Pasqal, and global bank Crédit Agricole CIB today announced successful conclusion of a 1.5-yea Read more…

Critics Don’t Want Politicians Deciding the Future of Semiconductors

January 26, 2023

The future of the semiconductor industry was partially being decided last week by a mix of politicians, policy hawks and chip industry executives jockeying for Read more…

Riken Plans ‘Virtual Fugaku’ on AWS

January 26, 2023

The development of a national flagship supercomputer aimed at exascale computing continues to be a heated competition, especially in the United States, the Euro Read more…

Leading Solution Providers

Contributors

SC22 Booth Videos

AMD @ SC22
Altair @ SC22
AWS @ SC22
Ayar Labs @ SC22
CoolIT @ SC22
Cornelis Networks @ SC22
DDN @ SC22
Dell Technologies @ SC22
HPE @ SC22
Intel @ SC22
Intelligent Light @ SC22
Lancium @ SC22
Lenovo @ SC22
Microsoft and NVIDIA @ SC22
One Stop Systems @ SC22
Penguin Solutions @ SC22
QCT @ SC22
Supermicro @ SC22
Tuxera @ SC22
Tyan Computer @ SC22
  • arrow
  • Click Here for More Headlines
  • arrow
HPCwire