Results 81 to 90 of about 676,740 (244)

Organic Materials of Tomorrow: Horizons of Artificial Intelligence

Advanced Materials, EarlyView.
This review examines machine learning techniques accelerating the discovery of organic semiconductors by linking molecular structure to properties. Key methods include graph neural networks, generative models, and active learning. Applications to organic photovoltaics demonstrate practical impact.
Harold Mena, J. Terence Blaskovits, Kun‐Han Lin, Denis Andrienko   +3 more
wiley   +1 more source

Auxiliary variables for 3D multiscale simulations in heterogeneous porous media [PDF]

, 2013
The multiscale control-volume methods for solving problems involving flow in porous media have gained much interest during the last decade. Recasting these methods in an algebraic framework allows one to consider them as preconditioners for iterative ...
Sandvin, Andreas, Nordbotten, Jan Martin, Keilegavlen, Eirik   +2 more
core   +1 more source

Radiative Thermal Management for Extreme Environments: Mechanisms and Design Strategies

Advanced Materials, EarlyView.
In this review, we discuss the fundamental mechanisms of radiative cooling and solar heating, material and structural design strategies, hybrid approaches integrating additional heat transfer pathways, and durability‐oriented designs addressing environmental stresses.
Hyung Rae Kim, Haeseong Kim, Joo Hwan Ko, Gil Ju Lee, Dae‐Hyeong Kim, Young Min Song   +5 more
wiley   +1 more source

Fault Diagnosis of Hydraulic Pumps Using PSO-VMD and Refined Composite Multiscale Fluctuation Dispersion Entropy

Shock and Vibration, 2020
Multiscale fluctuation dispersion entropy (MFDE) has been proposed to measure the dynamic features of complex signals recently. Compared with multiscale sample entropy (MSE) and multiscale fuzzy entropy (MFE), MFDE has higher calculation efficiency and ...
Fuming Zhou, Xiaoqiang Yang, Jinxing Shen, Wuqiang Liu   +3 more
doaj   +1 more source

Multiscale Geometric Integration of Deterministic and Stochastic Systems [PDF]

, 2011
In order to accelerate computations and improve long time accuracy of numerical simulations, this thesis develops multiscale geometric integrators. For general multiscale stiff ODEs, SDEs, and PDEs, FLow AVeraging integratORs (FLAVORs) have been ...
Tao, Molei
core   +1 more source

Interface‐Mediated Catalysis for Improved Hydrogen Storage in Reactive Hydride Composites

Advanced Materials, EarlyView.
Catalyst–hydride interfaces are engineered in Co@C‐ and Ni@C‐modified 2LiH + MgB2 reactive hydride composites to accelerate hydrogen uptake and release. Multiscale scattering, in‐situ synchrotron radiation powder x‐ray diffraction and density functional theory calculations reveal the structural and electronic origin of the catalytic enhancement ...
Yuanyuan Shang, Pawan Kumar Soni, Han Ge, Weijie Yang, Fahim Karimi, Thi Thu Le, Tamás Simon, Michael Fröba, Jitendra Mata, Joshua King, Hai‐Wen Li, Thomas Klassen, Claudio Pistidda   +12 more
wiley   +1 more source

A novel pansharpening: when multiscale adaptive attention meets dual enhanced networks and low-rank tensor decomposition

International Journal of Digital Earth
Deep learning (DL) has achieved advanced results in pansharpening remote sensing images. However, existing DL-based methods still have several drawbacks, such as incomplete feature extraction and insufficient information fusion.
Hengyou Wang, Jie Zhang, Tingting Zhang, Zheng Zhang, Lianzhi Huo   +4 more
doaj   +1 more source

multiscale-spatial-image: A multiscale, chunked, multi-dimensional Xarray spatial image data structure, serializable to OME-NGFF and netCDF.

, 2022
What's Changed citation cff by @thewtex in https://github.com/spatial-image/multiscale-spatial-image/pull/43 ENH: Add DASK_GAUSSIAN scaling and fix ITK_GAUSSIAN by @tbirdso in https://github.com/spatial-image/multiscale-spatial-image/pull/40 Full ...
McCormick, Matthew, Birdsong, Thomas
core   +1 more source

Breaking Bottlenecks in Solid Electrolyte Discovery With Large Artificial Intelligence Models

Advanced Materials, EarlyView.
Large AI models are presented as a route to break key bottlenecks in solid electrolyte discovery by linking materials databases, machine‐learning interatomic potentials, large language models, and autonomous experiments. This perspective highlights how AI can accelerate the identification of solid electrolytes with fast ion transport, stable interfaces,
Eric Jianfeng Cheng, Min Hong, Zhiquan Zeng, Chuanyu Liu, Qian Wang, Melissa Jane Meadowcroft, Vlad Badilita, Carlos Miguel Costa, Senentxu Lanceros‐Méndez, Ying Li, Chenyao Ma, Weibo Gong, Surendra Kumar Martha, Aloysius Soon, Piao Ma, Di Zhang, Teguh Ariyanto, Sudaryanto, Hiroshi Kakinuma, Jie Zhao, Jiayu Peng, Pengfei Ou, Jun Lu, Shin‐ichi Orimo, Hao Li   +24 more
wiley   +1 more source

Biomass DNA: An Emerging Building Block for Advanced Materials

Advanced Materials, EarlyView.
Biomass DNA is rapidly emerging from its traditional role as a genetic blueprint to serve as a versatile abundant, highly programmable polymeric building block. This review highlights the transformation of macroscopic bulk biomass DNA into next generation of functional materials, spanning from dynamic hydrogels, sustainable bioplastics, and high ...
Yuwei Hu, Itamar Willner, Li Niu
wiley   +1 more source