”Automated Data Collection for Material Research using PHI nanoTOF3⁺.”,
Shin-ichi Iida

Abstract

In recent years, there has been a growing demand for the rapid development of advanced materials. In response, the utilization of digital technologies such as ML (machine learning) to predict optimal combination of materials and manufacturing processes from vast datasets has become increasingly popular. However, amidst this trend, the challenge of efficiently acquiring data from various analytical techniques has become significant. 
To address this challenge, ULVAC-PHI has endeavored to improve the efficiency of data collection by implementing common sample holders and standardizing software across our surface analysis instruments. Additionally, in PHI nanoTOF3⁺, the automation of measurements for all types of samples, including insulating materials, allows for automated unattended analysis facilitating the acquisition of large amounts of data. In this presentation, we will introduce the data collection scheme while ensuring that information on analysis point is maintained across different analytical techniques.