Results 81 to 90 of about 496 (221)

Single‐Atom‐Enhanced Fully Inkjet‐Printed Electrochemical Sensor for Dopamine Detection

Advanced Science, EarlyView.
Fully inkjet‐printed paper‐based dopamine sensors are fabricated using nitrogen‐doped graphene acid functionalized with copper single atoms. The copper sites uniquely enhance dopamine oxidation through strong molecular adsorption, as verified by electrochemical measurements and DFT calculations. The approach highlights the potential of single‐atom inks
Martin‐Alex Nalepa, David Panáček, Vítězslav Hrubý, Matěj Jendrišák, Rostislav Langer, Michal Langer, Petr Jakubec, Ivan Dědek, Vojtěch Kupka, Michal Mazur, Radek Zbořil, Michal Otyepka   +11 more
wiley   +1 more source

Liquid Metals in Radio Frequency Applications: A Review of Physics, Manufacturing, and Emerging Technologies

Advanced Electronic Materials, EarlyView.
This paper reviews the physics of liquid metals in RF devices, including the influence of mechanical strain on resonance as well as fabrication methods and strategies for designing tunable and strain‐tolerant inductors, capacitors, and antennas.
Md Saifur Rahman, William J. Scheideler
wiley   +1 more source

On extensions of theorems in the geometry of polynomials [PDF]

, 2020
The geometry of polynomials started with the famous Gauss-Lucas theorem at the beginning of the 19th century. Many giants in mathematics such as Laguerre, Legendre, Chebyshev, Polya and Szego also contributed to theories that have become fundamental ...
譚國宗, Tam, Kwok Chung
core  

Low‐Power Control Of Resistance Switching Transitions in First‐Order Memristors

Advanced Electronic Materials, EarlyView.
Joule losses are a serious concern in modern integrated circuit design. In this regard, minimizing the energy necessary for programming memristors should be handled with care. This manuscript presents an optimal control framework, allowing to derive energy‐efficient programming voltage protocols for resistance switching devices. Following this approach,
Valeriy A. Slipko, Alon Ascoli, Fernando Corinto, Yuriy V. Pershin   +3 more
wiley   +1 more source

Exceptional Antimodes in Multi‐Drive Cavity Magnonics

Advanced Electronic Materials, EarlyView.
Driven‐dissipative cavity‐magnonics provides a flexible platform for engineering non‐Hermitian physics such as exceptional points. Here, using a four‐port, three‐mode system with controllable microwave interference, antimodes and coherent perfect extinction (CPE) are realized, enabling active tuning to antimode exceptional points.
Mawgan A. Smith, Ryan D. McKenzie, Alban Joseph, Robert L. Stamps, Rair Macêdo   +4 more
wiley   +1 more source

Enhanced High Dimensionality and the Information Processing Capacity in Interfered Spin Wave‐Based Reservoir Computing, Achieved With Eight Detectors

Advanced Electronic Materials, EarlyView.
Physical reservoir computing (PRC) based on spin wave interference has demonstrated high computational performance, yet room for improvement remains. In this study, we fabricated this concept PRC with eight detectors and evaluated the impact of the number of detectors using a chaotic time series prediction task.
Sota Hikasa, Wataru Namiki, Daiki Nishioka, Maki Nishimura, Ryo Iguchi, Kazuya Terabe, Takashi Tsuchiya   +6 more
wiley   +1 more source

Scan‐Path‐ and Initial‐State‐Dependent Superdomain Switching in (111)‐Oriented PZT

Advanced Electronic Materials, EarlyView.
Scan trajectory and initial superdomain topology govern polarization switching in (111)‐oriented PZT. Automated AFM writing, pulsing experiments, and interferometric 3D‐PFM show that raster scans reproducibly stabilize ordered Type‐I stripe superdomains with constrained variant selection, whereas spiral trajectories generate frustrated mixed‐variant ...
Rama Vasudevan, Laveeza Ahmad, Bharat Pant, Ralph Bulanadi, Asraful Haque, Puneet Kaur, Sabine Neumayer, Jan‐Chi Yang, Yongtao Liu, Ye Cao, Stephen Jesse, Marti Checa   +11 more
wiley   +1 more source

Smart Exploration of Perovskite Photovoltaics: From AI Driven Discovery to Autonomous Laboratories

Advanced Energy Materials, EarlyView.
In this review, we summarize the fundamentals of AI in automated materials science, and review AI applications in perovskite solar cells. Then, we sum up recent progress in AI‐guided manufacturing optimization, and highlight AI‐driven high‐throughput and autonomous laboratories.
Wenning Chen, Zheyu Zhang, Kelvian T. Mularso, Bonghyun Jo, Hyun Suk Jung   +4 more
wiley   +1 more source

Zero location and asymptotic behavior of orthogonal polynomials of Jacobi-Sobolev [PDF]

, 2001
16 pages, no figures.-- MSC2000 codes: Primary 41A10, 42C05; Secondary 33C45, 46E35, 46G10.MR#: MR2003640 (2004k:33019)[EN] In this article we consider the Sobolev orthogonal polynomials associated to the Jacobi's measure on [-1,1] .
Urbina, Wilfredo, Pijeira, Héctor, Pijeira Cabrera, Héctor Esteban, Quintana, Yamilet   +3 more
core   +1 more source

Machine Learning Interatomic Potentials for Energy Materials: Architectures, Training Strategies, and Applications

Advanced Energy Materials, EarlyView.
Machine learning interatomic potentials bridge quantum accuracy and computational efficiency for materials discovery. Architectures from Gaussian process regression to equivariant graph neural networks, training strategies including active learning and foundation models, and applications in solid‐state electrolytes, batteries, electrocatalysts ...
In Kee Park, Saeed Pourasad, Jinhong Mun, Arunkumar Chitteth Rajan, Tae Hyeon Park, Anand Rohit, Mohammad Zafari, Tan‐Lien Pham, Eunjae Jung, Bonseung Koo, Miran Ha, Gi Beom Sim, Hyun Gyu Park, Won Woong Choi, Kwanghyeon Jo, Soohaeng Yoo Willow, David ChangMo Yang, Chang Woo Myung, Geunsik Lee, Kwang S. Kim   +19 more
wiley   +1 more source