This community holds the data associated with articles published in Integrating Materials and Manufacturing Innovation (IMMI) https://hdl.handle.net/11256/416 2026-04-08T00:33:36Z 2026-04-08T00:33:36Z Lass, Erc Stoudt, Mark Campbell, Carelyn https://hdl.handle.net/11256/961 2018-04-16T13:23:11Z 2015-11-06T00:00:00Z

Systems Design Approach to Low-Cost Coinage Materials Lass, Erc; Stoudt, Mark; Campbell, Carelyn 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 current coinage materials required matching the currently used alloy properties of yield strength, work-hardening behavior, electrical conductivity, color, corrosion resistance and wear resistance. In addition, the design alloys were required to use current production processes. CALPHAD-based models for electrical conductivity and color were developed to integrate into the system design approach. Three prototype alloys were designed, produced and characterized. The design process highlighted the trade-off between minimizing the raw material costs and achieving the desired color properties. Characterization of the three prototype alloys showed good agreement with the design goals.

2015-11-06T00:00:00Z Shah, Sapan Vora, Dhwani Reddy, Sreedhar Gautham, BP https://hdl.handle.net/11256/950 2023-03-07T23:36:46Z

Dictionaries for Material Properties, Compositions and Processing conditions used for Intelligent Search on Steel Related Publications Shah, Sapan; Vora, Dhwani; Reddy, Sreedhar; Gautham, BP Knowledge of material properties, micro-structures, underlying material composition and manufacturing process parameters that the material has undergone is of significant interest to materials scientists and engineers. A large amount of information of this nature is available in publications in the form of experimental measurements, simulation results, etc. However, getting to right information of this kind that is relevant for a given problem on hand is a non-trivial task. First an engineer has to go through a large collection of documents to select the right ones. Then the engineer has to scan through these selected documents to extract relevant pieces of information. Our goal is to help automate some of these steps. Traditional search engines are not of much help here, as they are keyword centric and weak on relation processing. To address this problem, we have developed a domain specific search engine, that processes relations to significantly improve search accuracy. This engine uses dictionary matching based algorithm to extract instances of various domain entities such as material property, elemental composition, manufacturing process and their parameters. The dictionaries used by the algorithm are submitted as part of this data submission.

Li, Shengyen Kattner, Ursula Campbell, Carelyn https://hdl.handle.net/11256/946 2017-12-01T02:34:01Z 2017-08-18T00:00:00Z

A computational framework for material design Li, Shengyen; Kattner, Ursula; Campbell, Carelyn A computational framework is proposed that enables the integration of experimental and computational data, a variety of user-selected models, and a computer algorithm to direct a design optimization. To demonstrate this framework a sample design of a ternary Ni-Al-Cr alloy with a high work-to-necking ratio is presented. This design example illustrates how CALPHAD phase-based, composition and temperature dependent phase equilibria calculations and precipitation models are coupled with models for elastic and plastic deformation to calculate the stress-strain curves. A genetic algorithm then directs the search within a specific set of composition and processing constrains for the ideal composition and processing profile to optimize the mechanical properties. The initial demonstration of the framework provides a potential solution to initiate the material design process in a large space of composition and processing conditions. This framework can also be used in similar material systems or adapted for other material classes.

2017-08-18T00:00:00Z Hecht, Matthew D. DeCost, Brian L. Francis, Toby Holm, Elizabeth A. Picard, Yoosuf N. Webler, Bryan A. https://hdl.handle.net/11256/940 2017-08-30T21:05:38Z

Ultrahigh Carbon Steel Micrographs Hecht, Matthew D.; DeCost, Brian L.; Francis, Toby; Holm, Elizabeth A.; Picard, Yoosuf N.; Webler, Bryan A. We present a new microstructure informatics dataset consisting of ultrahigh carbon steel (UHCS) micrographs taken over a range of length scales under systematically varied heat treatments. Using the UHCS dataset as a case study, we develop a set of visualization tools for interacting with and exploring large microstructure and metadata datasets. Based on generic microstructure representations adapted from the field of computer vision, these tools enable image-based microstructure retrieval, as well as spatial maps of both microstructure and related metadata, such as processing conditions or properties measurements. We provide the microstructure image data, processing metadata, and source code for these microstructure exploration tools. The UHCS dataset is intended as a community resource for development and evaluation of microstructure informatics techniques, and for creation of microstructure informatics teaching modules.