-
- News
- Books
Featured Books
- smt007 Magazine
Latest Issues
Current IssueCounterfeit Concerns
The distribution of counterfeit parts has become much more sophisticated in the past decade, and there's no reason to believe that trend is going to be stopping any time soon. What might crop up in the near future?
Solder Printing
In this issue, we turn a discerning eye to solder paste printing. As apertures shrink, and the requirement for multiple thicknesses of paste on the same board becomes more commonplace, consistently and accurately applying paste becomes ever more challenging.
A Culture of Thriving
One cannot simply command thriving; it must be nurtured, developed, and encouraged. In this issue, we explore strategies to improve your working relationship model—both internally and externally. In this culture of thriving, your business will grow in the process.
- Articles
- Columns
Search Console
- Links
- Events
||| MENU - smt007 Magazine
Machine Learning Techniques Improve X-ray Materials Analysis
November 21, 2023 | ACN NewswireEstimated reading time: 2 minutes
Researchers of RIKEN at Japan’s state-of-the-art synchrotron radiation facility, SPring-8, and their collaborators, have developed a faster and simpler way to carry out segmentation analysis, a vital process in materials science. The new method was published in the journal Science and Technology of Advanced Materials: Methods.
Segmentation analysis is used to understand the fine-scale composition of a material. It identifies distinct regions (or ‘segments’) with specific compositions, structural characteristics, or properties. This helps evaluate the suitability of a material for specific functions, as well as its possible limitations. It can also be used for quality control in material fabrication and for identifying points of weakness when analyzing materials that have failed.
Segmentation analysis is very important for synchrotron radiation X-ray computed tomography (SR-CT), which is similar to conventional medical CT scanning but uses intense focused X-rays produced by electrons circulating in a storage ring at nearly the speed of light. The team have demonstrated that machine learning is capable in conducting the segmentation analysis for the refraction contrast CT, which is especially useful for visualizing the three-dimensional structure in samples with small density differences between regions of interest, such as epoxy resins.
“Until now, no general segmentation analysis method for synchrotron radiation refraction contrast CT has been reported,” says first author Satoru Hamamoto. “Researchers have generally had to do segmentation analysis by trial and error, which has made it difficult for those who are not experts.”
The team’s solution was to use machine learning methods established in biomedical fields in combination with a transfer learning technique to finely adjust to the segmentation analysis of SR-CTs. Building on the existing machine learning model greatly reduced the amount of training data needed to get results.
“We’ve demonstrated that fast and accurate segmentation analysis is possible using machine learning methods, at a reasonable computational cost, and in a way that should allow non-experts to achieve levels of accuracy similar to experts,” says Takaki Hatsui, who led the research group.
The researchers carried out a proof-of-concept analysis in which they successfully detected regions created by water within an epoxy resin. Their success suggests that the technique will be useful for analyzing a wide range of materials.
To make this analysis method available as widely and quickly as possible, the team plans to establish segmentation analysis as a service offered to external researchers by the SPring-8 data center, which has recently started its operation.
Suggested Items
TSMC Expands Collaboration with Ansys by Integrating AI Technology to Accelerate 3D-IC Design
09/27/2024 | ANSYSAnsys and TSMC have expanded their collaboration to leverage AI for advancing 3D-IC design and develop next generation multiphysics solutions for a wider array of advanced semiconductor technologies.
CACI Awarded $314 Million Task Order to Provide Engineering Services to U.S. Navy Naval Undersea Warfare Center (NUWC)
09/25/2024 | CACI International Inc.CACI International Inc announced that it has been awarded a five-year task order valued at up to $314 million to provide engineering services and technology to the U.S. Navy Naval Undersea Warfare Center (NUWC) under the Department of Defense Information Analysis Center’s (DoD IAC) multiple-award contract (MAC) vehicle.
CACI Awarded $273 Million Task Order to Continue Providing Intelligence Expertise to the USCENTCOM
09/23/2024 | CACI International Inc.CACI International Inc announced that it has won a five-year task order valued at up to $273 million to continue providing intelligence expertise to the United States Central Command (USCENTCOM).
CentraTEQ Appointed as UK Distributor for MB Dynamics' Squeak & Rattle Test Systems
09/11/2024 | CentraTEQCentraTEQ, a leading UK supplier of Vibration Test Systems, proudly announces its new partnership as the exclusive UK distributor for German company MB Dynamics, renowned for their advanced buzz, squeak, and rattle (BSR) test systems.
SEMI Energy Collaborative Releases Recommendations for Growing the Supply of Low Carbon Energy in Japan
09/03/2024 | SEMISeeking to bolster global semiconductor value chain efforts to lower greenhouse gas (GHG) emissions, the industry association SEMI released today an analysis by its Energy Collaborative (EC) of current and forecasted low-carbon energy (LCE) markets for Japan, the second in a series of market-specific reports.