📄 chemistry

Framework Zn Modulation of Confined CuxOy Species for Photothermal Methane to Methanol

This study demonstrates that incorporating redox-inactive zinc into the framework of SSZ-13 zeolites stabilizes specific Cu₃O₃ clusters and modulates their electronic structure via interfacial charge transfer, thereby enabling a highly efficient and stable photothermal strategy for converting methane to methanol with significantly improved yield and selectivity compared to conventional thermal catalysis.

Wenting Wu, Jinchen han, Haonan Zhang, Yan Sun, Yue Zhao, Chunlei Sun, Lei Liu, Qiwen Sun, Zhijun Zuo2026-07-15
📄 chemistry

Phase-controlled Tribocorrosion Mechanisms in Heat-treated Electrodeposited Ni–mo–b Coatings

This study demonstrates that heat-treating electrodeposited Ni–Mo–B coatings to form Mo₂NiB₂ boride-rich microstructures significantly enhances hardness and stabilizes tribocorrosion performance in saline environments by shifting the wear mechanism from unstable oxidative–adhesive to stable oxidation-controlled regimes.

Svitlana Halaichak, Sergiy Korniy, Vadim Zakiev, Vasyl Vynar, Maksym Danylchuk, Marian Chuchman, Roman Mardarevych, Yuri (…)2026-07-15
📄 chemistry

Green Electropolishing of Nickel and Cobalt in a Choline Chloride–Lactic Acid Deep Eutectic Solvent: Electrochemical Behavior and Nanoscale Surface Smoothing

This study demonstrates that a choline chloride–lactic acid deep eutectic solvent serves as an effective, environmentally friendly medium for the electropolishing of nickel and cobalt, achieving significant nanoscale surface smoothing and mirror-like finishes under optimized potentiostatic conditions.

Wrya O. Karim, Harez R. Ahmed, Kawan F. Kayani, Srood O. Rashid, Sewara J. Mohammad, Aso. Q. Hassan, Rebaz F. Hamarawf (…)2026-07-14
📄 chemistry

Integrated classical/quantum-classical neural networks, DFT, and experiments for predicting bandgap and color of CrxSbxTi1−2xO2 yellow-orange pigments

This study presents an integrated framework combining experimental synthesis, density functional theory calculations, and classical/hybrid quantum-classical neural networks to accurately predict the bandgap and color of Cr/Sb co-doped TiO₂ ceramic pigments, demonstrating the potential of quantum machine learning for materials design.

Seyed Yousof Vaselnia, Mohsen Khajeh Aminian, Reza Dehghan banadaki2026-07-14