tag: materials

When Semiconductor Materials Misbehave
By Gregory Haley - 27 Apr, 2026 - Comments: 0

Key Takeaways Material behavior in production depends on the process context that no development environment can fully replicate. In advanced packaging, the interactions that cross domain boundaries are increasingly where failures originate. The most accurate materials data is also the most commercially sensitive, leaving simulation models calibrated against generic inputs rather tha... » read more

Batteries Charge To The Edge
By Ed Sperling - 20 Apr, 2026 - Comments: 1

Long-awaited advances in battery chemistry and materials science are beginning to roll out, opening the door for higher capacity, faster charging, and much lower likelihood of thermal runaway. This is a high-stakes race, fueled by an insatiable demand for power everywhere from handheld devices to data centers. When Finland's Donut Lab claimed earlier this year that it had developed a solid-s... » read more

Research Bits: Apr. 6
By Jesse Allen - 06 Apr, 2026 - Comments: 0

Reservoir computing Researchers from Loughborough University designed a memristor reservoir computing chip that can process data that changes over time directly in hardware. “Inspired by the way the human brain forms very numerous and seemingly random neuronal connections between all its neurons, we created complex, random, physical connections in an artificial neural network by designing... » read more

Reliability Risks Shift To The Materials Stack
By Gregory Haley - 18 Dec, 2025 - Comments: 0

The semiconductor industry’s push into 3D integration and large-format substrates has fundamentally changed the role of materials in packaging. What were once structural supports and electrical insulators have become critical performance limiters. Modern packages contain far more polymers, adhesives, advanced dielectrics, thermal materials, and composite laminates than previous generations... » read more

Benefits And Limits Of Using ML For Materials Discovery
By Katherine Derbyshire - 18 Dec, 2025 - Comments: 0

Machine learning tools can accelerate all stages of materials discovery, from initial screening to process development. Whether the goal is to identify new applications for known materials or to design new molecules for a particular task, these tools help materials scientists find correlations in large data libraries. Still, machine learning tools are not magic. “Software tools are only as... » read more

Thermal Management In 3D-IC: Modeling Hotspots, Materials, & Cooling Strategies
By Reela Samuel - 11 Dec, 2025 - Comments: 1

As three-dimensional integrated circuit (3D-IC) technology becomes the architectural backbone of AI, high-performance computing (HPC), and advanced edge systems, thermal management has shifted from a downstream constraint to a fundamental design driver. The dense vertical integration that enables unprecedented performance also concentrates heat at levels that traditional two-dimensional design ... » read more

Machine Learning Tools Accelerate Materials Discovery
By Katherine Derbyshire - 20 Nov, 2025 - Comments: 0

Literature searches, simulations, and practical experiments have been part of the materials science toolkit for decades, but the last few years have seen an explosion of machine learning-driven software tools that promise to accelerate all three. Many of the challenges facing the semiconductor manufacturing industry are fundamentally materials science problems. What metal has the lowest resi... » read more

Scaling Memory With Molybdenum
By Katherine Derbyshire - 18 Sep, 2025 - Comments: 2

Molybdenum is looking increasingly promising as a replacement for a variety of metals commonly used in semiconductor manufacturing today, especially at leading-edge nodes. One by one, chipmakers are crossing metals off the list at advanced nodes. While ruthenium liners are nearly ready for production, the metal is not ready to replace copper in highly scaled interconnects. Ruthenium is very ... » read more

Materials Modeling Of Superconducting Qubits In Quantum Computers
By Anders Blom - 21 Aug, 2025 - Comments: 0

While the concept of quantum computing has been discussed for more than 40 years, only recently have experiments indicated that a practical quantum computer may be possible. Recent developments in this area have captured headlines with dramatic claims—and equally dramatic rebuttals. Google’s Willow chip demonstrated error-corrected operations in late 2024, while D-Wave’s assertion of quan... » read more

Research Bits: August 19
By Jesse Allen - 19 Aug, 2025 - Comments: 0

Co-packaged optics Researchers from the Massachusetts Institute of Technology (MIT) and Bridgewater State University developed a new way to co-package photonic and electronic chips that uses existing automated pick-and-place assembly equipment in traditional fabs along with a less-expensive passive alignment process. “We’ve developed a packaging design [for integrating photonics with el... » read more

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