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Search Publications by: Carelyn E. Campbell (Fed)

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Displaying 1 - 25 of 62

Structure-Aware GNN-Based Deep Transfer Learning Framework For Enhanced Predictive Analytics On Small Materials Data

January 2, 2024
Vishu Gupta, Kamal Choudhary, Brian DeCost, Francesca Tavazza, Carelyn E. Campbell, Wei-keng Liao, Alok Choudhary, Ankit Agrawal
Modern data mining methods have been demonstrated to be effective tools to comprehend and predict materials properties. An essential component in the process of materials discovery is to know which material(s) (represented by their composition and crystal

Applying the Effective Bond Energy Formalism (EBEF) to Describe the Sigma (s) Phase in the Co-Cr-Ni-Re System

December 30, 2023
Julio Cesar Pereira Dos Santos, Sean Griesemer, Nathalie Dupin, Ursula R. Kattner, Chuan Liu, Daniela Ivanova, Thomas Hammerschmidt, Suzana Fries, Chris Wolverton, Carelyn E. Campbell
Proper descriptions of Topologically Closed-Packed (TCP) phases in thermodynamic databases are essential to adequately design new alloys. Thus, the recently introduced Effective Bond Energy Formalism (EBEF) is used in this work to describe the sigma (σ)

MPpredictor: An Artificial Intelligence-Driven Web Tool for Composition-Based Material Property Prediction

March 27, 2023
Kamal Choudhary, Francesca Tavazza, Carelyn E. Campbell, Vishu Gupta, Yuwei Mao, Kewei Wang, Wei-keng Liao, Alok Choudhary, Ankit Agrawal
The applications of artificial intelligence, machine learning, and deep learning techniques in the field of materials science are becoming increasingly common due to their promising abilities to extract and utilize data-driven information from available

Developing an Appropriate Heat Treatment Protocol for Additively Manufactured Alloy 718 for Oil and Gas Applications

March 23, 2023
Mark R. Stoudt, James Zuback, Carelyn E. Campbell, Maureen E. Williams, Kil-Won Moon, Carlos R. Beauchamp, Mark Yunovich
The combination of strength, corrosion resistance, and excellent weldability makes Alloy 718 an attractive alloy for additive manufacturing (AM) applications, but the AM build process generates considerable residual stresses, and large compositional and

Development of a Diffusion Mobility Database for Co-based Superalloys

November 27, 2022
Greta Lindwall, Kil-Won Moon, Carelyn E. Campbell, Maureen E. Williams, Whitney Tso
To facilitate the development of high-temperature Co-based - superalloys, a Co-Ni based diffusion mobility database is developed for the eight component FCC (Face Centered Cubic) system of Co-Al-W-Ni-Cr-Ti-Ta-Re. A CALPHAD approach is used to represent

The effects of diffusional couplings on compositional trajectories and interfacial free energies during phase separation in a quaternary Ni-Al-Cr-Re model superalloy

August 1, 2022
Carelyn E. Campbell, Sung-Il Baik, Zugang Mao, Qingqiang Ren, Chuan Zhang, BiCheng Zhou, Ronald D. Noebe, David N. Seidman, Fei Xue
The temporal evolution of ordered γ′(L12)-precipitates and the compositional trajectories during phase-separation of the γ(face-centered-cubic (f.c.c.))- and γ′(L12)-phases are studied in a Ni–0.10Al-0.085Cr-0.02Re (mole-fraction) superalloy, utilizing

Co-Based Superalloy Morphology Evolution: A Phase Field Study Based on Experimental Thermodynamic and Kinetic Data

July 1, 2022
Carelyn E. Campbell, Ursula R. Kattner, Jonathan E. Guyer, James A. Warren, Wenkun Wu, Peter Voorhees, Olle Heinonen
Cobalt-based superalloys with gamma/gamma prime microstructures off er great promise as candidates for next-generation high-temperature alloys for applications, such as turbine blades. It is essential to understand the thermodynamic and kinetic factors

A Roadmap for LIMS at NIST Material Measurement Laboratory

April 11, 2022
Gretchen Greene, Jared Ragland, Zachary Trautt, June W. Lau, Raymond Plante, Joshua Taillon, Adam Abel Creuziger, Chandler A. Becker, Joe Bennett, Niksa Blonder, Lisa Borsuk, Carelyn E. Campbell, Adam Friss, Lucas Hale, Michael Halter, Robert Hanisch, Gary R. Hardin, Lyle E. Levine, Samantha Maragh, Sierra Miller, Chris Muzny, Marcus William Newrock, John Perkins, Anne L. Plant, Bruce D. Ravel, David J. Ross, John Henry J. Scott, Christopher Szakal, Alessandro Tona, Peter Vallone
Instrumentation generates data faster and in higher quantity than ever before, and interlaboratory research is in historic demand domestically and internationally to stimulate economic innovation. Strategic mission needs of the NIST Material Measurement

How Austenitic is a Martensitic Steel Produced by Laser Powder Bed Fusion? A Cautionary Tale

December 2, 2021
Fan Zhang, Mark R. Stoudt, Souzan Hammadi, Carelyn E. Campbell, Eric A. Lass, Maureen E. Williams
Accurate phase fraction analysis is an essential element of microstructural characterization of alloys and often serves as a basis to quantify effects such as heat treatment or mechanical deformation. Additive manufacturing (AM) of metals, due to the

Cross-property deep transfer learning framework for enhanced predictive analytics on small materials data

November 15, 2021
Vishu Gupta, Kamal Choudhary, Francesca Tavazza, Carelyn E. Campbell, Wei-Keng Liao, Alok Choudhary, Ankit Agrawal
Artificial Intelligence (AI) and Machine Learning (ML) has been increasingly used in materials science to build property prediction models and accelerate materials discovery. The availability of large materials databases for some properties like formation

Development of Computational Framework for Titanium Alloy Phase Transformation Prediction in Laser Powder-bed Direct Energy Additive Manufacturing

October 16, 2020
Zhi Liang, Ivan Zhirnov, Fan Zhang, Kevontrez K. Jones, David C. Deisenroth, Maureen E. Williams, Ursula R. Kattner, Kil-Won Moon, Wing-Kam Liu, Brandon M. Lane, Carelyn E. Campbell
In conjunction with bare metal single laser track validation experiments, a computational framework is proposed to accelerate the design and development of new additive manufacturing (AM) specific alloys. Specifically, Additive Manufacturing-Computational

Additive Manufacturing of Steels and Stainless Steels

August 1, 2020
Carelyn E. Campbell, Mark R. Stoudt, Fan Zhang
This work briefly reviews the classification of the different types of steels, the most common AM processes used for steel and the available powder feedstock. The characteristics of the as-built microstructure, including porosity, inclusions and residual

Learning to predict crystal plasticity at the nanoscale: Deep residual networks and size effects in uniaxial compression discrete dislocation simulations

May 19, 2020
Zijiang Yang, Stefanos Papanikolaou, Andrew C. Reid, Wei-keng Lao, Alok Choudhary, Carelyn E. Campbell, Ankit Agrawal
The increase of dislocation density in a metallic crystal undergoing plastic deformation influences the mechanical properties of the material. This effect can be used to examine the related inverse problem of deducing the prior deformation of a material

Outcomes and Conclusions from the 2018 AM-Bench Measurements, Challenge Problems, Modeling Submissions, and Conference

February 13, 2020
Lyle E. Levine, Brandon M. Lane, Jarred C. Heigel, Kalman D. Migler, Mark R. Stoudt, Thien Q. Phan, Richard E. Ricker, Maria Strantza, Michael R. Hill, Fan Zhang, Jonathan E. Seppala, Edward J. Garboczi, Erich D. Bain, Daniel Cole, Andrew J. Allen, Jason C. Fox, Carelyn E. Campbell
The Additive Manufacturing Benchmark Test Series (AM-Bench) was established to provide rigorous measurement test data for validating additive manufacturing (AM) simulations for a broad range of AM technologies and material systems. AM-Bench includes

Enhancing Materials Property Prediction by Leveraging Computational and Experimental Data using Deep Transfer Learning

November 22, 2019
Kamal Choudhary, Dipendra Jha, Ankit Agrawal, Alok Choudhary, Wei-keng Liao, Francesca M. Tavazza, Carelyn E. Campbell
The availability of huge collections of data from DFT-computations has spurred the interest of materials scientists in applying machine learning techniques to build models for fast prediction of materials properties. Such modeling practice has helped to

Simulation of TTT curves for additively manufactured Inconel 625

January 1, 2019
Carelyn E. Campbell, Greta Lindwall, Eric Lass, Fan Zhang, Mark R. Stoudt, Andrew J. Allen, Lyle E. Levine
The ability to use common computational thermodynamic and kinetic tools to study the microstructure evolution in Inconel 625 (IN625) manufactured using the additive manufacturing (AM) technique of laser powder-bed fusion is evaluated. Solidification

Generating Domain Terminologies using Root- and Rule-Based Terms

December 21, 2018
Talapady N. Bhat, John T. Elliott, Ursula R. Kattner, Carelyn E. Campbell, Eswaran Subrahmanian, Ram D. Sriram, Jacob Collard, Monarch Ira
Motivated by the need for exible, intuitive, reusable, and normalized ter- minology for the semantic web, we present a general approach for generat- ing sets of such terminologies from nat- ural language documents. The terms that this approach generates

Diffusion in the Ti-Al-V system

August 23, 2018
Greta Lindwall, Kil-Won Moon, Zhangqi Chen, Michael J. Mengason, Maureen E. Williams, Justin Gorham, Ji-Cheng Zhao, Carelyn E. Campbell
Diffusion in the Ti-Al-V system is studied and a CΑLPHAD diffusion mobility description is developed. Diffusion couple experiments are used to obtain information of Al and V diffusion in the α phase. This includes diffusion paths at the temperatures 923 K

Systems Design Approach to Low-Cost Coinage Materials

June 20, 2018
Eric Lass, Mark R. Stoudt, Carelyn E. Campbell
A system design approach using an Integrated Computational Materials Engineering (ICME) was used to design three new low-cost seamless replacement coinage alloys to reduce the raw material of the current US coinage alloys. Maintaining compatibility with