. 24/7 Space News .
AI spurs scientists to advance materials research
by Staff Writers
Tempe Az (SPX) Sep 01, 2022

New machine learning model can compute melting points for any compound.

If you apply enough heat to a material, at some point, most things melt, just like ice cream on a hot summer day.

Engineers rely on this knowledge daily. Knowing the exact melting temperatures is a critical parameter for building any high-performance materials. From the building and safety of bridges to gas turbines and jet engines to heat shields on aircraft, all are dependent on knowing the performance limits of materials. Materials are often synthesized or processed employing the molten or liquid state, so knowing melting is critical to making new materials.

Shift to the field of Earth and planetary science, and the melting points are used to reveal clues into Earth's past and the characteristics of planets in our solar system and far-out orbiting exoplanets.

But measuring the melting temperature of a compound or material is an arduous task. That's why, of the estimated 200,000-plus inorganic compounds, less than 10% of their melting temperatures are known.

Melting temperatures are often measured after carefully calibrating crystal structures or plotting the thermodynamic free energy curves when a material melts, creating a phase change from a solid to a liquid. This is analogous to the melting of solid ice to form liquid water. But when high-temperature materials exceed 2,000 or 3,000 degrees, finding an experimental chamber to do the measurements can be a challenge. And sometimes, rocks have complex mixtures of minerals not much larger than a grain of sand - so getting enough sample of a single mineral can also present a challenge. Materials synthesized under extreme conditions of high pressure and temperature are also often available in only very small amounts.

Now, Arizona State University researchers Qi-Jun Hong, Alexandra Navrotsky, and Sergey Ushakov, together with Axel van de Walle at Brown University have harnessed the power of artificial intelligence (AI), or machine learning (ML), to demonstrate an easier way to predict melting temperatures for potentially any compound or chemical formula.

"We employ machine learning methods to fill this gap by building a rapid and accurate mapping from chemical formula to melting temperature," said Hong, assistant professor in the School for Engineering of Matter, Transport and Energy, within the Ira A. Fulton Schools of Engineering.

"The model we have developed will facilitate large-scale data analysis involving melting temperature in a wide range of areas. These include the discovery of new high-temperature materials, the design of novel extractive metallurgy processes, the modeling of mineral formation, the evolution of Earth over geological time, and the prediction of exoplanet structure."

Hong's approach allows melting temperatures to be computed in milliseconds for any compound or chemical formula input. To do so, the research team built a model from an architecture of neural networks, and trained their machine learning program on a custom-curated database encompassing 9375 materials, out of which 982 compounds have melting temperatures higher than a scorching 3100 degrees Fahrenheit (or 2000 degrees Kelvin). Materials at this temperature glow white-hot.

Hong used this methodology to explore two lines of research: 1) predicting the melting temperatures of nearly 5,000 minerals and 2) finding new materials that have extremely high melting temperatures above 3000 Kelvin (or 5000 degrees Fahrenheit).

For the minerals project, Hong's team was able to predict melting temperatures and correlate these with the known major geological epochs of Earth's history. These AI-garnered melting temperatures were applied to minerals made since the formation of Earth about 4.5 billion years ago. The oldest minerals originate directly from stars or interstellar and solar nebula condensates predating Earth's formation 4.5 billion years ago. These are the most refractory, with melting temperatures around 2600 F.

For the most part, there was a gradual decrease in the calculated melting temperatures of minerals identified on Earth with more recent time, with 2 major exceptions.

"The gradual overall decrease in the melting temperature of minerals formed during Earth history is interrupted with two anomalies, which are distinctly pronounced in average and medium melting temperatures using 250 or 500 million years ago binning," said Navrotsky, an ASU Professor with joint faculty appointments in the School of Molecular Sciences and School for Engineering of Matter, Transport and Energy and Director of MOTU, the Navrotsky Eyring Center for Materials of the Universe.

The first anomaly in Earth's early history came from a dramatic temperature spike caused by a scary and dynamic time of major meteor strikes, including the possible formation of the Moon.

"The spike at 3.750 billion years ago correlates to the proposed timing of late-heavy bombardment, hypothesized exclusively from dating of lunar samples and currently debated," said Navrotsky.

The team also noticed a large temperature dip in the melting temperatures of minerals around 1.75 billion years ago.

"The dip at 1.750 billion years ago is related to the first known occurrences of a large number of hydrous (water-containing) minerals and correlates with the Huronian glaciation, the longest ice age thought to be the first time Earth was completely covered in ice."

With their machine learning program trained to successfully replicate mineral melting in Earth's early history, next, the team turned their attention to finding new materials that have extremely high melting temperatures. Dozens of new materials are identified and computationally predicted to have extremely high melting temperatures above 5,000 degrees Fahrenheit (3000 Kelvin), more than half the temperature of the Sun's surface.

The team made their model simple and reliable enough so that any user can obtain the melting temperature within seconds for any compound based only on its chemical formula.

"To use the model, a user needs to visit the webpage and input the chemical compositions of the material of interest," said Hong. "The model will respond with a predicted melting temperature in seconds, as well as the actual melting temperatures of the nearest neighbors (i.e., the most similar materials) in the database. Thus, this model serves as not only a predictive model, but a handbook of melting temperature as well."

The model, hosted by ASU's Research Computing Facilities, is now publicly available at the ASU webpage here.

Research Report:Melting temperature prediction using a graph neural network model: From ancient minerals to new materials

Related Links
Arizona State University
Space Technology News - Applications and Research

Thanks for being there;
We need your help. The SpaceDaily news network continues to grow but revenues have never been harder to maintain.

With the rise of Ad Blockers, and Facebook - our traditional revenue sources via quality network advertising continues to decline. And unlike so many other news sites, we don't have a paywall - with those annoying usernames and passwords.

Our news coverage takes time and effort to publish 365 days a year.

If you find our news sites informative and useful then please consider becoming a regular supporter or for now make a one off contribution.
SpaceDaily Monthly Supporter
$5+ Billed Monthly

paypal only
SpaceDaily Contributor
$5 Billed Once

credit card or paypal

Digging through patents to make mining greener
Fukuoka, Japan (SPX) Sep 01, 2022
As the world confronts the ongoing climate crisis, moving to greener technology has become a requirement in every facet of our lives. Naturally, industries critical to our daily lives are also moving to integrate such technology into their operations. All of these depend in some way on the industry that extracts and processes the raw materials used to make most green technologies: the mining industry. But the economic and policy factors that drive the mining sector to become more sustainable remai ... read more

Comment using your Disqus, Facebook, Google or Twitter login.

Share this article via these popular social media networks
del.icio.usdel.icio.us DiggDigg RedditReddit GoogleGoogle

NASA awards contract to demonstrate trash compacting system for ISS

Boeing eyes February for space capsule's first crewed flight

Voyager logs 45 years in space as NASA's longest mission to date

45 years after launch, NASA's Voyager probes still blazing trails billions of miles away

NASA Moon rocket ready for second attempt at liftoff

NASA says weather, SLS rocket look good for Artemis I launch on Saturday

NASA scrubs launch of giant Moon rocket, may try again Friday

Saturn V was loud but didn't melt concrete

MIT's MOXIE experiment reliably produces oxygen on Mars

An Unexpected Stop during Sols 3580-3581

MAVEN and EMM make first observations of patchy proton aurora at Mars

Sols 3568-3570: That Was Close

Energy particle detector helps Shenzhou-14 crew conduct EVAs

China conducts spaceplane flight test

103rd successful rocket launch breaks record

Chinese space-tracking ship docks at Sri Lanka's Hambantota port

Space tech: In Jilin, they build satellites

SpaceX and T-Mobile unveil satellite plan to end cellphone 'dead zones'

Introducing Huginn

T-Mobile Takes Coverage Above and Beyond With SpaceX

AI spurs scientists to advance materials research

Google's immersive Street View could be glimpse of metaverse

Space Station experiment to probe origins of elements

Selfridges targets 'circular' sales for almost half its goods

JWST makes first unequivocal detection of carbon dioxide in an exoplanet atmosphere

An extrasolar world covered in water

Webb detects carbon dioxide in exoplanet atmosphere

Webb telescope finds CO2 for first time in exoplanet atmosphere

The PI's Perspective: Extending Exploration and Making Distant Discoveries

Uranus to begin reversing path across the night sky on Wednesday

Underwater snow gives clues about Europa's icy shell

Why Jupiter doesn't have rings like Saturn

The content herein, unless otherwise known to be public domain, are Copyright 1995-2024 - Space Media Network. All websites are published in Australia and are solely subject to Australian law and governed by Fair Use principals for news reporting and research purposes. AFP, UPI and IANS news wire stories are copyright Agence France-Presse, United Press International and Indo-Asia News Service. ESA news reports are copyright European Space Agency. All NASA sourced material is public domain. Additional copyrights may apply in whole or part to other bona fide parties. All articles labeled "by Staff Writers" include reports supplied to Space Media Network by industry news wires, PR agencies, corporate press officers and the like. Such articles are individually curated and edited by Space Media Network staff on the basis of the report's information value to our industry and professional readership. Advertising does not imply endorsement, agreement or approval of any opinions, statements or information provided by Space Media Network on any Web page published or hosted by Space Media Network. General Data Protection Regulation (GDPR) Statement Our advertisers use various cookies and the like to deliver the best ad banner available at one time. All network advertising suppliers have GDPR policies (Legitimate Interest) that conform with EU regulations for data collection. By using our websites you consent to cookie based advertising. If you do not agree with this then you must stop using the websites from May 25, 2018. Privacy Statement. Additional information can be found here at About Us.