via Ames Laboratory
Computational materials science experts at the U.S. Department of Energy’s Ames Laboratory enhanced an algorithm that borrows its approach from the nesting habits of cuckoo birds, reducing the search time for new high-tech alloys from weeks to mere seconds.
The scientists are investigating a type of alloys called high-entropy alloys, a novel class of materials that are highly sought after for a host of unusual and potentially beneficial properties. They are lightweight in relation to their strength, fracture-resistant, highly corrosion and oxidation resistant, and stand up well in high-temperature and high-pressure environments — making them attractive materials for aerospace industry, space exploration, nuclear energy, and defense applications.
While the promise of these materials is great, they present major difficulties to scientists attempting to search for and customize them for use in technologies. Because these alloys are constructed of five or more different elements, they are expensive and difficult to develop and search experimentally, making an Edison-like approach a nonstarter. With so many ingredients, and so many different ways to construct them, there are nearly endless permutations of recipes for their design. Among literally billions of options, how do researchers narrow their search to a few excellent potential candidates for an application?
The answer in this case is an evolutionary algorithm, using a hybrid version of a computer program developed ten years ago, called Cuckoo Search (CS). Cuckoo birds are brood parasites, laying their eggs in the nest of a host bird such that they end up rearing the bigger, stronger cuckoo chick as one of its own.
“This ‘survival of the fittest’ strategy from the behavior of birds is the idea behind Cuckoo Search,” said Duane Johnson, a computational materials scientist at Ames Laboratory. Each egg represents a possible solution, competing to be the best solution in any given nest in a fixed number of possible nests. The best solution of each nest competes against other nests, until the best solution is found.
The Ames Laboratory team put a twist on the Cuckoo Search, which greatly speeded up the process of locating ideal alloys or the best “egg” within a huge number of possibilities. The original CS takes advantage of a mathematical concept called Lévy flight, which computational theorists use to their advantage in searching extremely large data sets. But, while this method works for large data sets, the Ames Lab team found that pairing another mathematical concept, a Monte Carlo algorithm, with Lévy flight, greatly reduced the time to achieving optimal candidates for high-entropy alloys, providing optimal models almost on the fly.
“With the model-building bottleneck eliminated, computational design can be performed that is currently impractical, said Johnson, “As our hybrid CS is problem-agnostic, it offers application in optimization in many diverse fields.”
The Latest Updates from Bing News & Google News
Go deeper with Bing News on:
New materials discovery
- Agencies respond to possible explosive devices, materials in New Iberia
The 800 block of Fontelieu Drive in New Iberia is now clear following a discovery of a potential explosive device and materials that can be used to make an explosive.
- New innovation may help EV batteries last significantly longer
An unexpected EV innovation could completely change how we make EV batteries, allowing them to last longer and charge faster.
- This discovery could lead to creation of credit card-sized smartphones
While the world is already amazed at smartphones that shrink in size, a discovery has the potential to disrupt the wireless communication space further. It will help build smartphones that can be as ...
- Batteries News
New Materials Discovered for Safe, High-Performance Solid-State Lithium-Ion Batteries Apr. 2, 2024 — All-solid-state lithium-ion batteries offer enhanced safety and energy density compared to ...
- Children’s Discovery Museum to Open ‘Storytime Inventing’ Exhibit Supporting Early Literacy
The San Diego Children’s Discovery Museum announced Storytime Inventing, a new interactive and educational exhibit for young children and their caregivers supported by Kid Spark Education.
Go deeper with Google Headlines on:
New materials discovery
[google_news title=”” keyword=”new materials discovery” num_posts=”5″ blurb_length=”0″ show_thumb=”left”]
Go deeper with Bing News on:
Evolutionary algorithm
- Using Artificial Intelligence for Celebrity News: A Modern Approach to Entertainment Journalism
In the fast-paced world of celebrity and star news, artificial intelligence (AI) is revolutionizing the way information is identified, communicated, and disseminated. AI tools not only improve the ...
- A new approach to using neural networks for low-power digital pre-distortion in mmWave systems
In a study published in the journal IEICE Electronics Express, researchers present a neural network digital pre-distortion (DPD) for mmWave RF-PAs.
- Evolutionary algorithm generates tailored 'molecular fingerprints'
A team led by Prof Frank Glorius from the Institute of Organic Chemistry at the University of Münster has developed an evolutionary algorithm that identifies the structures in a molecule that are ...
- Google DeepMind’s New AlphaFold AI Maps Life’s Molecular Dance in Minutes
AlphaFold 3 models all life's molecules—proteins, DNA, RNA, and small molecules—and their interactions. The work could speed up science and drug discovery.
- 9 steps to reimagine, reboot, and bring the “rhythm to your algorithm”
Reaching new heights and retrenching requires revolution and evolution, especially when you are in a rut. The key is finding the reboots that work for you to reignite growth and drive passion into ...
Go deeper with Google Headlines on:
Evolutionary algorithm
[google_news title=”” keyword=”evolutionary algorithm” num_posts=”5″ blurb_length=”0″ show_thumb=”left”]