Skala 1.1, the updated deep-learning exchange-correlation functional from Microsoft Research, provides greater accuracy, expanded accessibility across the computational chemistry ecosystem, and a living benchmark to track computational performance.

2.8 kcal/mol on GMTKN55 is a serious result but accessibility may matter even more. Skala 1.1 brings deep-learning DFT closer to everyday computational chemistry, with CP2K support available and broader integrations underway.

Can it predict good band gaps

Great advancement! 🧪 Skala 1.1 pushes computational chemistry forward.

Accessibility might end up mattering more than the accuracy gains. Getting these methods into the tools people already use (instead of staying stuck in research papers) is usually what determines whether something actually gets adopted. The living benchmark is a smart addition too.

Nghe hấp dẫn ghê, không biết bản này có chạy nhanh hơn bản cũ không nhỉ? 🧪

Living benchmarks matter when scientific models must improve beyond one static score.