Results 181 to 190 of about 11,571 (267)

Measuring the Hall Effect in Hysteretic Materials

Advanced Materials, EarlyView.
The authors highlight common pitfalls in measuring the Hall effect: in hysteretic magnets, improper data processing can create signals that look exotic but are not real. This Perspective explains the origin of these artifacts and presents practical measurement strategies that help researchers identify reliable Hall responses in complex magnetic ...
Jaime M. Moya, Anthony Voyemant, Sudipta Chatterjee, Scott B. Lee, Grigorii Skorupskii, Connor J. Pollak, Leslie M. Schoop   +6 more
wiley   +1 more source

Self-Oscillatory Neuron-like Devices for Unconventional Computing Applications. [PDF]

Chem Rev
Rivera-Sierra G, Bisquert J, Fenollosa R.   +2 more
europepmc   +1 more source

High‐Performance Transparent, Deformable, and Recoverable Biomimetic Stevia–PVA Hydrogel Triboelectric Nanogenerator with Machine Learning‐Assisted Motion Recognition

Advanced Materials, EarlyView.
A transparent, deformable stevia–PVA hydrogel triboelectric nanogenerator delivers significantly enhanced mechanical strength and electrical output through biomimetic hydrogen‐bonded networks. Coupled with machine learning–assisted signal recognition, the self‐powered hydrogel enables accurate human‐motion sensing for intelligent wearable and IoT ...
Thien Trung Luu, Bui Minh Quang, Toan Minh Pham, Jinsoo Kim, Kyungwho Choi, Dukhyun Choi   +5 more
wiley   +1 more source

Relationships Among Auditory Discrimination, Adaptive Vocal Learning, and Perilaryngeal Muscle Activation in People With and Without Hyperfunctional Voice Disorders. [PDF]

J Speech Lang Hear Res
Kapsner-Smith MR, Cádiz MD, Knutson M, Eadie TL, Stepp CE.   +4 more
europepmc   +1 more source

Phase Engineering of Nanomaterials (PEN): Evolution, Current Challenges, and Future Opportunities

Advanced Materials, EarlyView.
This review summarizes the synthesis, phase transition, advanced characterization spanning ex situ to in situ and operando techniques, and diverse applications of phase engineering of nanomaterials (PEN). It further outlines key challenges and future opportunities, such as phase stability, architecture control, and artificial intelligence (AI)‐driven ...
Ye Chen, Zhanxi Fan, Jingjie Ge, Qiyuan He, Zhuangchai Lai, Jiawei Liu, Chaoliang Tan, Hua Zhang   +7 more
wiley   +1 more source

Enhanced smart commuting with artificial intelligence for intelligent health and safety monitoring in school buses. [PDF]

Sci Rep
Hossam H, Tamer R, Mohsen M, Ahmed O, Alaa M, Mourad J, Adel R, Hatem A, Sherif S.   +8 more
europepmc   +1 more source

Advancing Lithium–Oxygen Batteries: Pioneering Cathode Catalyst Innovation and Artificial Intelligence‐Driven Design Paradigms

Advanced Materials, EarlyView.
This review summarizes the principles and challenges of nonaqueous lithium‐oxygen batteries and recent advances in cathode catalysts, including carbon‐based materials, metals, oxides, sulfides, nitrides, carbides, and redox mediators. It highlights emerging design strategies and artificial intelligence‐driven approaches, emphasizing data‐assisted ...
Yuqing Yao, Chongyang Hao, Karol Viviana Mejia‐Centeno, Malik Dilshad Khan, Shang Wang, Longqiu Li, Yanhong Tian, Andreu Cabot, Qing Sun   +8 more
wiley   +1 more source

Electromechanical Impedance Sensing Under Humid Conditions: Experimental Insights and Compensation Using Machine Learning. [PDF]

Sensors (Basel)
Dahl MK, Hire JH, Zamani M, Luca A, Moradi F.   +4 more
europepmc   +1 more source

Advances in Magnesium‐Based Thermoelectrics: A Critical Review

Advanced Materials, EarlyView.
Magnesium‐based thermoelectric materials have emerged as promising candidates for low‐to‐mid‐temperature energy conversion due to their abundance, low cost, and competitive performance. This review summarizes recent advances in Mg3X2, MgAgSb, and Mg2X systems, covering transport mechanisms, fabrication strategies, stability challenges, and device ...
Li‐Min Zhang, Li Zhang, Nan‐Hai Li, Yan‐Ling Yang, Xiao‐Lei Shi, Zhi‐Gang Chen   +5 more
wiley   +1 more source

Accurate estimation of lesion metrics in radiofrequency ablation using machine learning model. [PDF]

Eur Heart J Open
Takigawa M, Tsunoda S, Shigeta T, Yamaguchi J, Negishi M, Honda M, Tateishi R, Kawamura I, Yamamoto T, Goto K, Nishimura T, Yamao K, Tao S, Miyazaki S, Fujiwawra K, Sasano T.   +15 more
europepmc   +1 more source