Resources

Author(s): Yu Xing, Ning Ding, Zhipeng Wang, Zhiwen Pan, Lei Guo, Guowei Du, Yangrui Liu, Xiaoxing Cao, Ran Su, Mengting Jiang, Xuezhi Ma, Xiyu Chen, Junchao Zhang, Xinyu Yang, Haoran Ye, Honghong Yao, Rui Feng, Dexiang Chen, Le-Ping Miao, Yumeng You, Zejun Li, Dongsheng Song, Linglong Li, and Shuai Dong Exotic noncollinear room-temperature ferroelectricity has now been experimentally realized in 2D WO2Cl2, establishing a polar counterpart to...

Author(s): C. M. Bowers, D. Palani, J. J. Barta, T. H. Guglielmo, S. B. Libby, D. Leibfried, and D. H. Slichter Adiabatic ramping of both state-dependent force amplitude and motional frequency delivers high-fidelity trapped-ion entanglement without ground-state cooling. [Phys. Rev. Lett. 137, 080602] Published Thu Aug 20, 2026

Author(s): Yanbo Lou, Jiabin Wang, Yuyan Zou, Lingyue Hou, Shengshuai Liu, and Jietai Jing Researchers have demonstrated the quantum teleportation of a 100-pixel image by a method that could help to scale up quantum networks. [Phys. Rev. Lett. 137, 080801] Published Thu Aug 20, 2026

Author(s): Minhyeok Kuk and Hyoungsoo Kim Experimental studies of multicomponent droplet evaporation reveal distinct stages, with internal flow shifting from multiple vortices within the droplet to a single toroidal vortex dominating the flow dynamic, departing from the classical single-component picture. [Phys. Rev. Lett. 137, 084002] Published Thu Aug 20, 2026

Author(s): Chao Deng, Motoharu Kitatani, Guiwen Jiang, Siqi Guo, Niklas Witt, Ao Zhang, Wenfeng Wu, Mi Jiang, Karsten Held, and Liang Si Intercalation-driven self-doping is a general mechanism for engineering high-temperature superconductivity and emergent quantum states in Ruddlesden–Popper phase correlated oxides. [Phys. Rev. Lett. 137, 086004] Published Thu Aug 20, 2026

Author(s): Seigo Ogawa, Tomoki Miyoshi, Saki Uchida, Kazuaki Matano, Shinji Kawasaki, Yoshihiko Inada, and Guo-qing Zheng Researchers have made the first definitive measurements of an elusive superconducting state. [Phys. Rev. Lett. 137, 086003] Published Wed Aug 19, 2026

Author(s): Lars Dingeldein, Aaron Lyons, Pilar Cossio, Michael T. Woodside, and Roberto Covino A simulation-based inference framework combines physics-based modeling with deep learning to recover the Bayesian posterior of a biomolecular folding model directly from single-molecule force spectroscopy data. [Phys. Rev. Lett. 137, 088402] Published Wed Aug 19, 2026