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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

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

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Refined Composite Multiscale Permutation Entropy to Overcome Multiscale Permutation Entropy Length Dependence

IEEE Signal Processing Letters, 2015
Multiscale permutation entropy (MPE) has recently been proposed to evaluate complexity of time series. MPE has numerous advantages over other multiscale complexity measures, such as its simplicity, robustness to noise and its low computational cost.
Anne Humeau-Heurtier, Chiu-Wen Wu, Shuen-De Wu   +2 more
exaly   +3 more sources

Multivariate Multiscale Dispersion Entropy of Biomedical Times Series [PDF]

Entropy, 2019
Due to the non-linearity of numerous physiological recordings, non-linear analysis of multi-channel signals has been extensively used in biomedical engineering and neuroscience. Multivariate multiscale sample entropy (MSE - mvMSE) is a popular non-linear
Hamed Azami, Alberto Fernández, Javier Escudero   +2 more
exaly   +2 more sources

MULTISCALE COMPLEXITY/ENTROPY [PDF]

Advances in Complex Systems, 2004
We discuss the role of scale dependence of entropy/complexity and its relationship to component interdependence. The complexity as a function of scale of observation is expressed in terms of subsystem entropies for a system having a description in terms of variables that have the same a priori scale.
openaire   +2 more sources

Topological entropy bounds multiscale entropy

Topology and its Applications, 2023
In this paper, the concept of topological entropy is defined for a discrete dynamical system over a compact metric space \(X\). Section 1 is introductory. Section 2 is devoted to the concept of topological entropy with respect to an observable function: \[ h(f,\varphi)=\sup\{h(f,\varphi,\mathcal{A}); \mathcal{A}\in \mathcal{R}\}, \] where \(f:X\to X ...
openaire   +2 more sources

Multiscale Entropy for Physical Activity Recognition

Proceedings of the 2020 2nd Asia Pacific Information Technology Conference, 2020
This paper presents the evaluation of multiscale entropy (MSE) as a feature in physical activity recognition compared to the mostly used traditional features. Walking, jogging, and running were chosen as the physical activities for the comparison considering their similarities.
Nurul Retno Nurwulan, Bernard C. Jiang
openaire   +1 more source