Researchers at Lehigh University are developing a faster, more accurate way to predict how metals solidify during 3D printing and other additive manufacturing processes. Supported by a three-year, $350,000 grant from the National Science Foundation, assistant professor Parisa Khodabakhshi is creating a physics-based, data-driven model that connects manufacturing process parameters with the resulting material microstructure. The approach aims to replace costly trial-and-error methods with efficient simulation tools that can guide the design of high-performance metal components. The project’s outcomes could accelerate innovation across industries that rely on advanced manufacturing—such as aerospace, automotive, and healthcare—while helping train the next generation of engineers and scientists.

In JASA Express Letters, researchers evaluate the relationships between sound quality, speech recognition, and quality-of-life outcomes for cochlear implant (CI) users. They found CI sound quality leads to a 32% variance in users’ quality of life — in contrast, speech recognition has virtually no predictive power over quality of life. In their study, speech recognition only correlated with sound quality under noisy conditions, suggesting it is particularly relevant in situations with background noise and different sound sources — in other words, the real world.

Auburn University scientists have designed a new family of materials where the interaction between electrons residing periphery of molecules unlocks properties nature never intended. By anchoring special molecules onto stable surfaces like diamond, the team created electride arrangements that can be tuned to act as building blocks for quantum computers or as powerful catalysts for advanced chemistry. This discovery paves the way for technologies that promise faster, more efficient computing and entirely new ways to manufacture materials and medicines.