Penn Engineers have developed a new way to use AI to solve inverse partial differential equations (PDEs), a particularly challenging class of mathematical problems with broad implications for understanding the natural world. The advance, which the researchers call “Mollifier Layers,” could benefit fields as varied as genetics and weather forecasting, because inverse PDEs help scientists work backward from observable patterns to infer the hidden dynamics that produced them.

Optimization isn’t always about maximization: researchers at Tohoku University found a subtle rule where a bit of restraint actually speeds up chemical reactions in nanoreactors.

Researchers from The University of Osaka, Kyushu University, and the University of Victoria have developed MV-SZZ, a new method that accurately identifies defect-inducing software commits. By combining detailed code tracking with a majority voting system, the approach reduces false positives and outperforms existing techniques. This improvement could help developers debug software more efficiently and build more reliable systems.

A bimetallic NiFe catalyst was successfully constructed to overcome the activity–selectivity trade‑off in furfural hydrogenation. The introduction of Fe dilutes continuous Ni sites, modulates the electronic structure, and creates synergistic active sites: Ni for H₂ dissociation and Fe for carbonyl activation. This design boosts the selectivity toward furfuryl alcohol from 38% to >90% at nearly full conversion, while maintaining high activity and recycle stability.

Rice researchers have developed extremely stable perovskite crystalline films for long-lasting, high-efficiency solar cells.