Panelists discuss cutting-edge advances in monitoring ultra-pure water (UPW) purity, from ICP-MS to online pre-concentration, and the growing push for sub-ppt-level contaminant detection.

The panelists discuss the vital role of ultra-pure water (UPW) and recycled water strategies to support yield, safety, and environmental compliance.

The panel discusses how silicon (Si), silicon carbide (SiC), and gallium nitride (GaN) materials influence semiconductor design choices, yield challenges, and supply chain risks.

This episode takes a look at the evolving regulatory environment in semiconductor manufacturing, including stricter contamination standards and the challenges of global compliance.

The panelists consider non-destructive wafer analysis using TXRF and complementary methods, and how combining techniques enables advanced defect and contamination mapping.

In this episode, the panel focuses on automation in semiconductor analysis, including sample prep innovations and the unique capabilities of next-generation ICP-MS systems.

The panel compares traditional ATD-GC-MS methods to emerging TOF-MS approaches for impurity and defect analysis, emphasizing speed and sensitivity advancements.

The panelists discuss the different techniques used for testing semiconductor materials—such as ICP-MS, VPD, GDI, and GED-ICP-MS—including which approaches the industry will adopt more moving forward.

Ruth Merrifield, PhD, discusses how continuous manufacturing can help control contamination as humans don’t have to touch the materials as often, or even at all. Katsu Kawabata also mentions how automation that supports continuous manufacturing can help reduce human exposure to chemicals that would otherwise be manually handled.

Panelists discuss primary bottlenecks in semiconductor manufacturing, from geopolitical supply chain issues to purity and talent gaps, and explore strategies to maintain innovation under pressure.

Researchers in Scotland have developed a drone-mounted infrared imaging system that can detect and map methane gas leaks in real time from up to 13.6 meters away. The innovative approach combines laser spectroscopy with infrared imaging, offering a safer and more efficient tool for monitoring pipeline leaks and greenhouse gas emissions.

Researchers from institutions in Brazil harness near-infrared spectroscopy and machine learning to determine cocoa content with precision.

Researchers from Jiangsu University and Jimei University developed an advanced FT-NIR-based method for food safety monitoring, achieving over 97% accuracy in identifying multiple oil-based contaminants in peanut oil.

In the first part of a three-part interview, Robert Ewing discusses the core technology behind the VaporID system, explains how the system differs from current IMS systems, and describes the challenges the team faced in miniaturizing the VaporID device into a portable, microwave-sized system.

The U.S. Department of Energy’s Pacific Northwest National Laboratory’s (PNNL) VaporID, which is a newly developed portable air sampling system incorporating a miniaturized mass spectrometer (MS), can detect trace levels of fentanyl, methamphetamine, cocaine, and even explosives like TNT with great accuracy.