Results 141 to 150 of about 12,597 (223)

Morphotropic Phase Boundary Engineering via Heterostructure for Low‐Voltage Ferroelectric Capacitors

Advanced Electronic Materials, EarlyView.
Morphotropic phase boundary engineering in HfxZr1‐xO2 heterostructures enables low‐voltage and fast ferroelectric switching. This layer promotes polarization switching near 0 V, resulting in ≈25% reduction in coercive voltage and enhanced capacitance. This heterostructure design provides a practical route for energy‐efficient ferroelectric capacitors ...
Changhyeon Han, Been Kwak, Ki‐Ryun Kwon, Jeong‐Han Kim, Jiyong Yim, Hyun‐Min Kim, Sangeun Kwak, Daewoong Kwon   +7 more
wiley   +1 more source

Machine Learning‐Assisted Design and Performance Prediction of a Compact Dual‐Band Polarization‐Insensitive THz Metamaterial Absorber for Skin‐Cancer‐Related Refractive‐Index Sensing

Advanced Electronic Materials, EarlyView.
A compact QASRR‐based THz metamaterial absorber enables polarization‐insensitive dual‐band absorption and skin‐cancer‐related refractive‐index sensing through measurable resonance shifts. Field, surface‐current, and circuit analyses clarify the dual‐resonance mechanism, while StackNet‐assisted prediction accurately estimates the simulated absorption ...
Md. Murad Kabir Nipun, S. M. Rifatur Rana, Md. Golam Morshed, Imrose Jahan, F. A. Sabbir Ahamed, Md. Jahedul Islam   +5 more
wiley   +1 more source

Deciphering histone mark-specific fine-scale chromatin organization at high resolution with Micro-C-ChIP. [PDF]

Nat Commun
Metelova M, Vigh ML, Krietenstein N.
europepmc   +1 more source

Emerging Materials and Future Strategies for Solid Oxide Electrochemical Cells

Advanced Energy Materials, EarlyView.
Solid oxide electrochemical cells operate under strongly coupled electrochemical and thermodynamic conditions, where performance is constrained by interactions among crystal structure, defect chemistry, and interfacial evolution. This review, based on a structure‐defect‐property‐durability framework, reveals the roles of lattice symmetry and defect ...
Qiuchun Lu, Yufei Zhang, Han Zhao, Pooi See Lee, Daniel H.C. Chua   +4 more
wiley   +1 more source

Constraint coordinate-momentum phase space formulations for finite-state quantum systems: The relation between commutator variables and complex Stiefel manifolds. [PDF]

Fundam Res
Shang Y, Cheng X, Liu J.
europepmc   +1 more source

Deciphering Intricacies in Directional CO2 Conversion From Electrolysis to CO2 Batteries

Advanced Energy Materials, EarlyView.
This review will delve into the inherent connections and distinctions of CO2‐directed conversion in ECO2RR and CO2 batteries, in terms of product types, catalyst selection, catalytic mechanisms, and electrochemical performances, while proposing a benchmarking framework for the evaluation of CO2 batteries and innovative CO2 battery configurations for ...
Changfan Xu, Huaping Zhao, Lizhuang Chen, Weidong Shi, Guosheng Shao, Yong Lei   +5 more
wiley   +1 more source

Visual cortex speckle imaging for shape recognition. [PDF]

Sci Rep
Kalyuzhner Z, Agdarov S, Beiderman Y, Beiderman Y, Zalevsky Z.   +4 more
europepmc   +1 more source

Asymmetric Multi‐Site Ion Exchange in Porous Carbon Electrodes

Advanced Energy Materials, EarlyView.
A lognormal‐distribution 2D EXSY NMR framework uncovers the full spectrum of ion dynamics in hierarchical porous carbons, bridging fast surface exchange and confined in‐pore transport—establishing structure–transport relationships for next‐generation energy storage, gas storage, and ion removal materials.
Henry R. N. B. Enninful, Marius Hermesdorf, Muhammad Abdullah Khan, Desirée Leistenschneider, Martin Oschatz, Rustem Valiullin   +5 more
wiley   +1 more source

Metabolomic biomarker differences of sarcopenia in older patients with sepsis. [PDF]

Front Med (Lausanne)
Liu Y, He T, Chen S, Li Z, Mei X, He X, Shang N.   +6 more
europepmc   +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