Materials Map

Discover the materials research landscape. Find experts, partners, networks.

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The Materials Map is an open tool for improving networking and interdisciplinary exchange within materials research. It enables cross-database search for cooperation and network partners and discovering of the research landscape.

The dashboard provides detailed information about the selected scientist, e.g. publications. The dashboard can be filtered and shows the relationship to co-authors in different diagrams. In addition, a link is provided to find contact information.

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The Materials Map is still under development. In its current state, it is only based on one single data source and, thus, incomplete and contains duplicates. We are working on incorporating new open data sources like ORCID to improve the quality and the timeliness of our data. We will update Materials Map as soon as possible and kindly ask for your patience.

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in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (3/3 displayed)

  • 2023Application of Machine Learning to Regression Analysis of a Large SMA Weld Metal Database4citations
  • 2022Metallurgical Design Rules for High-Strength Steel Weld Metals4citations
  • 2021Analysis of a High-Strength Steel SMAW Database6citations

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Chart of shared publication
Varadarajan, Rajan
1 / 1 shared
Society, American Welding
3 / 10 shared
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2023
2022
2021

Co-Authors (by relevance)

  • Varadarajan, Rajan
  • Society, American Welding
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article

Analysis of a High-Strength Steel SMAW Database

  • Sampath, Krishna
  • Society, American Welding
Abstract

<jats:p>Recently, Dr. Glyn M. Evans posted a large shielded metal arc (SMA) weld metal (WM) database on the ResearchGate website (researchgate.net). This database contains more than 950 WM compositions, along with their respective WM tensile and Charpy V-notch (CVN) impact properties. In particular, the CVN impact properties list the test temperatures that achieved 28 and 100 J impact energy for each WM composition. While the availability of this SMA WM database is a valuable and rare gift to the welding community, how could the welding community analyze this database to gain valuable insights? This paper utilizes a constraints-based model (CBM) as a simple and effective framework to organize and analyze this very large Fe-C-Mn SMA WM database. A CBM is built on the metallurgical principle that one needs to lower relevant solid-state phase transformation (i.e., austenite decomposition) temperatures to improve WM strength and fracture toughness while simultaneously reducing carbon content and Yurioka’s carbon equivalent number (CEN) to improve the weldability of high-strength steels. To this end, a CBM identifies and simultaneously solves several statistical (regression) equations that relate the chemical composition of high-strength steel WM with Yurioka’s CEN and selected solid-state phase transformation temperatures related to austenite decomposition. The results of the current effort demonstrate that the analysis of Evans’s shielded metal arc welding database using a CBM as a framework reaffirms that controlling carbon content, the value of the CEN, and calculated solid-state phase transformation temperatures, particularly the difference between the calculated Bs (bainite-start) and Ms (martensite-start) temperatures, is critical to developing and identifying high-performance, high-strength steel welding electrodes. A dual approach that manipulates the contents of principal alloy elements such as C, Mn, Ni, Cr, Mo, and Cu, and adds controlled amounts of Ti, B, Al, O, and N, appears to offer the best means to lower relevant solid-state phase transformation temperatures to produce high-strength and high-toughness WMs.</jats:p>

Topics
  • impedance spectroscopy
  • Carbon
  • phase
  • strength
  • steel
  • mass spectrometry
  • fracture toughness
  • decomposition
  • carbon content