Methods in Material Science
Start Date
7-8-2026 11:15 AM
End Date
7-8-2026 11:30 AM
Location
ALT 205
Abstract
This study explored several areas of materials science, including crystal synthesis, applications of Atomic Force Microscopy (AFM), and the creation and analysis of iron-based alloys.
To investigate the potential role of artificial intelligence in scientific research, AI was evaluated as a research assistant during crystal synthesis projects. While AI proved effective at explaining scientific literature and generating ideas for potential crystal syntheses using limited starting materials, it often struggled to provide accurate experimental procedures and reliable citations. These findings suggest that current versions of AI can be a useful supplementary research tool but should not be relied upon without verification from primary scientific sources.
To better understand the research applications of Atomic Force Microscopy, Fourier transform analysis and surface roughness measurements were performed. Fourier transform techniques allowed scans of a computer chip to be reconstructed using selected spatial frequencies, enabling the identification of material impurities and the removal of imaging artifacts. Roughness measurements (Ra) were also used to characterize the surface of human hair, demonstrating AFM's usefulness in surface analysis and quality control applications.
In addition, two iron alloys, silicon iron and cast iron (carbon iron), were produced to investigate methods of modifying the properties of iron, including reducing its melting temperature. Magnetic Force Microscopy (MFM), a specialized AFM mode, was used to analyze the magnetic grain structure of the cast iron sample. MFM imaging revealed differences between carbon-rich and iron-rich regions that were not readily distinguishable in conventional height scans, demonstrating the value of magnetic imaging techniques for microstructural analysis.
Methods in Material Science
ALT 205
This study explored several areas of materials science, including crystal synthesis, applications of Atomic Force Microscopy (AFM), and the creation and analysis of iron-based alloys.
To investigate the potential role of artificial intelligence in scientific research, AI was evaluated as a research assistant during crystal synthesis projects. While AI proved effective at explaining scientific literature and generating ideas for potential crystal syntheses using limited starting materials, it often struggled to provide accurate experimental procedures and reliable citations. These findings suggest that current versions of AI can be a useful supplementary research tool but should not be relied upon without verification from primary scientific sources.
To better understand the research applications of Atomic Force Microscopy, Fourier transform analysis and surface roughness measurements were performed. Fourier transform techniques allowed scans of a computer chip to be reconstructed using selected spatial frequencies, enabling the identification of material impurities and the removal of imaging artifacts. Roughness measurements (Ra) were also used to characterize the surface of human hair, demonstrating AFM's usefulness in surface analysis and quality control applications.
In addition, two iron alloys, silicon iron and cast iron (carbon iron), were produced to investigate methods of modifying the properties of iron, including reducing its melting temperature. Magnetic Force Microscopy (MFM), a specialized AFM mode, was used to analyze the magnetic grain structure of the cast iron sample. MFM imaging revealed differences between carbon-rich and iron-rich regions that were not readily distinguishable in conventional height scans, demonstrating the value of magnetic imaging techniques for microstructural analysis.
