Results 111 to 120 of about 25,724 (259)

A Family of Sodium Solid‐State Electrolytes Based on the NaGaxAl1‐xCl4 Solid Solution

Advanced Materials Interfaces, EarlyView.
ABSTRACT Sodium‐based metal chloride solid electrolytes are promising for sodium solid‐state batteries due to their excellent oxidation stability, which, as shown for Li halides, can coexist with high ionic conductivity. To explore cationic substitution effects, we synthesized NaGaxAl1‐xCl4 (0 ≤ x ≤ 1) via ball milling and investigated structural and ...
Hao Guo, Matteo Bianchini
wiley   +1 more source

Anomalous diffusion and asymmetric tempering memory in neutrophil chemotaxis. [PDF]

PLoS Comput Biol, 2022
Dieterich P, Lindemann O, Moskopp ML, Tauzin S, Huttenlocher A, Klages R, Chechkin A, Schwab A.   +7 more
europepmc   +1 more source

Nonwoven‐Based Textile Architectures for Energy Storage Applications: Materials, Preparation, Characterization, and Prospects

Advanced Materials Interfaces, EarlyView.
Nonwoven textile architectures are emerging as versatile platforms for next‐generation energy storage, demonstrating how tailored materials and fabrication strategies enhance ion transport, conductivity, flexibility, and scalability for high‐performance sustainable devices.
Tarikul Islam, Md. Hanif Munshi, Rijon Saha, Shaikh Almoon Hussain, Aqib Adnan Shafin, Shumsul Arefin, Md. Kamruzzaman   +6 more
wiley   +1 more source

Objective comparison of methods to decode anomalous diffusion. [PDF]

Nat Commun, 2021
Muñoz-Gil G, Volpe G, Garcia-March MA, Aghion E, Argun A, Hong CB, Bland T, Bo S, Conejero JA, Firbas N, Garibo I Orts Ò, Gentili A, Huang Z, Jeon JH, Kabbech H, Kim Y, Kowalek P, Krapf D, Loch-Olszewska H, Lomholt MA, Masson JB, Meyer PG, Park S, Requena B, Smal I, Song T, Szwabiński J, Thapa S, Verdier H, Volpe G, Widera A, Lewenstein M, Metzler R, Manzo C.   +33 more
europepmc   +1 more source

From the Discovery of the Giant Magnetocaloric Effect to the Development of High‐Power‐Density Systems

Advanced Materials Technologies, EarlyView.
The article overviews past and current efforts on caloric materials and systems, highlighting the contributions of Ames National Laboratory to the field. Solid‐state caloric heat pumping is an innovative method that can be implemented in a wide range of cooling and heating applications.
Agata Czernuszewicz, Yaroslav Mudryk, Jun Cui, Lucas Griffith, Duane D. Johnson, Julie Slaughter   +5 more
wiley   +1 more source

Comparison of Heuristic Algorithms in Identification of Parameters of Anomalous Diffusion Model Based on Measurements from Sensors. [PDF]

Sensors (Basel), 2023
Brociek R, Wajda A, Słota D.
europepmc   +1 more source

Anomalous Diffusion by Fractal Homogenization

Annals of PDE
For every $α< \frac13$, we construct an explicit divergence-free vector field $\mathbf{b}(t,x)$ which is periodic in space and time and belongs to $C^0_t C^α_x \cap C^α_t C^0_x$ such that the corresponding scalar advection-diffusion equation $$\partial_t θ^κ+ \mathbf{b} \cdot \nabla θ^κ- κΔθ^κ= 0$$ exhibits anomalous dissipation of scalar variance ...
Armstrong, Scott, Vicol, Vlad
openaire   +4 more sources

Sustainable Materials Design With Multi‐Modal Artificial Intelligence

Advanced Science, EarlyView.
Critical mineral scarcity, high embodied carbon, and persistent pollution from materials processing intensify the need for sustainable materials design. This review frames the problem as multi‐objective optimization under heterogeneous, high‐dimensional evidence and highlights multi‐modal AI as an enabling pathway.
Tianyi Xu, Tianshuo Wei, Yan Ge, Bo Peng, Yue Li, Maolin Wang, Peng Wen, Chao Yang, Ye Wei   +8 more
wiley   +1 more source

Brain serotonergic fibers suggest anomalous diffusion-based dropout in artificial neural networks. [PDF]

Front Neurosci, 2022
Lee C, Zhang Z, Janušonis S.
europepmc   +1 more source

Unifying Composition and Process Design: A Heterogeneous Graph Neural Network for Discovering High‐Performance Cu Alloys

Advanced Science, EarlyView.
By overcoming the fixed‐path limitations of conventional machine learning, a heterogeneous graph neural network fundamentally reconstructs material data representation. Integrating variable processing sequences with intrinsic elemental features, this framework enables exploratory optimization across high‐dimensional spaces.
Jie Yin, Qian Lei, Wei Yan, Yue Li, Tong Xie, Shuang Zhou, Chong Wang, Bram Hoex, Qiang Long, Caoyang Jiang, Min Song, Zhou Li, Zhangwei Wang   +12 more
wiley   +1 more source