{"id":8042,"date":"2025-08-14T23:45:08","date_gmt":"2025-08-15T03:45:08","guid":{"rendered":"https:\/\/staging.asminternational.org\/fas\/new-computational-model-by-northeastern-scientists-revolutionizing-alloy-design\/"},"modified":"2025-08-15T03:54:42","modified_gmt":"2025-08-15T03:54:42","slug":"new-computational-model-by-northeastern-scientists-revolutionizing-alloy-design","status":"publish","type":"post","link":"https:\/\/www.asminternational.org\/fas\/new-computational-model-by-northeastern-scientists-revolutionizing-alloy-design\/","title":{"rendered":"New computational model by Northeastern scientists revolutionizing alloy design"},"content":{"rendered":"

Scientists at Northeastern University, Boston, Mass., introduce a new cost- and energy-efficient computational model for designing alloys that factors in material defects.<\/p>\n

New research published in the Journal of Applied Physics<\/em> by Moneesh Upmanyu, Northeastern professor of mechanical and industrial engineering, introduces a new computational model that offers strategies for alloy design of real materials in seconds. Compared to traditional lab experiments and AI-based approaches, the model offers greater speed, cost efficiency and accuracy.<\/p>\n

Previous computational tools \u2014 including those based on machine learning and artificial intelligence \u2014 often failed to account for a critical factor, Upmanyu says: real-life crystalline materials, such as metals and ceramics, contain defects.<\/p>\n

In materials science, defects are irregularities or imperfections in a crystal\u2019s atomic structure. While they may sound like flaws, defects are often intentionally introduced to enhance properties such as strength, conductivity and corrosion resistance.<\/p>\n

The new model takes into account an important class of material defects (grain boundaries) and the tendency of the mixed solutes to gather \u2014 or segregate \u2014 around the structural imperfections during alloy formation.<\/p>\n

\u201cYou are dealing with these defective materials by default, and all these alloy design techniques ignore this,\u201d Upmanyu says. \u201cThey just can\u2019t factor that in because it\u2019s a very complex system with all these defects in place.\u201d<\/p>\n

One well-known example of such material defect that has been studied extensively over the past century is a dislocation. It occurs when an entire atomic plane is missing from a crystal\u2019s structure. Despite this imperfection, dislocations allow for plastic deformation of a material without breaking by letting the defect move through the crystal lattice.<\/p>\n

When alloys are formed by mixing with solutes, or dissolved substances, the dislocations act as preferred locations for the solutes. The solutes attach to dislocation threads like a swarm of bees, making it harder for dislocations to move. By engineering these defects and behaviors of solutes in alloys, Upmanyu says, humans can make stronger, cost-effective materials.<\/p>\n

His research focuses on another key defect: grain boundaries. These occur in polycrystalline materials \u2014 such as copper \u2014 at the interfaces where differently oriented crystal grains meet. Unlike dislocations, these defects run along surfaces within the material.<\/p>\n

\u201cFor a crystal small enough to hold between your fingers, conventional alloys with micron-sized grains have a grain boundary area as large as a basketball court,\u201d Upmanyu says.<\/p>\n

That is a vast area for solutes to attach to, he says, which affects the entire mixing strategy when alloys are being made as well as their mechanical, electrical and magnetic properties.<\/p>\n

Material engineers often manipulate these boundaries to control, for example, the direction of electricity conduction, by orienting the grains in the crystals along one direction.<\/p>\n

\u201cThe motion of grain boundaries with the solutes is completely ignored in current general alloying theory,\u201d Upmanyu says. His model examines how solutes affect that motion.<\/p>\n

\u201cIf I look under a microscope at finite temperature (non-zero absolute temperature that affects the energy state of a system), these grain boundaries and these defects are not static, they are dancing around, they are moving,\u201d Upmanyu says. \u201cAnd we exploit these fluctuations of the grain boundaries with solute segregated to them.\u201d<\/p>\n

The model tracks how much and when solute segregates, and how it impacts the motion of grain boundaries. \u201cWhich is a first step toward understanding how the properties of the material are modified by these solutes at the grain boundaries,\u201d he says.<\/p>\n

The paper focuses on steel, an alloy of iron and carbon. However, Upmanyu notes the model applies broadly \u2014 not just to metals but also to ceramics like metal oxides. \u201cWe feel it\u2019s general enough because it\u2019s based on fluctuations of interfaces and grain boundaries. All these interfaces fluctuate at finite temperature,\u201d he says. \u201cThere is always segregation of solutes. It\u2019s universal.\u201d<\/p>\n

To reflect this broader scope, the researchers use the term \u201cinterface\u201d rather than \u201cgrain boundary\u201d to include non-crystalline materials.<\/p>\n

The model realistically simulates how solutes interact with both defects and each other. \u201cIf I take a snapshot of what we actually have simulated and use it as an input to actually extract the alloy properties, it\u2019s identical to what you see in an experiment,\u201d Upmanyu says.<\/p>\n

The model works with two or more base materials and can be extended to predict thermal, electrical and magnetic properties of resulting alloys.<\/p>\n

Another advantage: it delivers accurate predictions using very short simulation times. \u201cWe\u2019re looking at a computational investigation of this fluctuation over nanoseconds,\u201d Upmanyu says. \u201cYou\u2019re taking a very brief snapshot of how this thing fluctuates, and coming up with the modified behavior based on that.\u201d<\/p>\n

 <\/p>\n

For more information:<\/p>\n

Northeastern University
\nhttps:\/\/www.northeastern.edu\/<\/a><\/p>\n

 <\/p>\n","protected":false},"excerpt":{"rendered":"

Scientists at Northeastern University, Boston, Mass., introduce a new cost- and energy-efficient computational model for designing alloys that factors in material defects.<\/p>\n","protected":false},"author":63245,"featured_media":8053,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[675,676,677,555,503],"tags":[],"class_list":["post-8042","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ceramics","category-computational-materials-engineering","category-copper-alloys","category-materials","category-research-and-development"],"yoast_head":"\nNew computational model by Northeastern scientists revolutionizing alloy design - Failure Analysis Society<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.asminternational.org\/fas\/new-computational-model-by-northeastern-scientists-revolutionizing-alloy-design\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"New computational model by Northeastern scientists revolutionizing alloy design - 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