Results 51 to 60 of about 1,862 (208)

Polarization Dynamics in Ferroelectrics: Insights Enabled by Machine Learning Molecular Dynamics

Advanced Science, EarlyView.
Machine learning molecular dynamics is presented as a route to capture polarization switching, domain wall kinetics, topological polar textures, and polar mechanical coupling beyond the limits of conventional atomistic methods. This Perspective surveys recent progress and identifies key methodological directions, including long‐range electrostatics ...
Dongyu Bai, Ri He, Junxian Liu, Liangzhi Kou   +3 more
wiley   +1 more source

Machine‐Learning Framework for Designing Stable Interfaces in All‐Solid‐State Lithium‐Ion Batteries

Advanced Science, EarlyView.
A data‐driven strategy is developed to discover coating materials for all‐solid‐state lithium batteries. Using calculations of interfacial reactivity, unsupervised pattern recognition, and machine‐learning prediction, the study identifies low‐reactivity compositional patterns and screens new lithium‐based oxide and polyanion candidates, extending ...
Sehyeok Park, Myeongcho Jang, Hun‐Gi Jung, Kyung Yoon Chung, Seungho Yu   +4 more
wiley   +1 more source

Variational Wavelet Ensemble Empirical (VWEE) Denoising Method for Electromagnetic Ultrasonic Signal in High-Temperature Environment with Low-Voltage Excitation

Chinese Journal of Mechanical Engineering, 2022
Low excitation voltage for an electromagnetic acoustic transducer (EMAT) is necessary for the petrochemical equipment and facilities inspection, which work at high-temperatures, to avoid potential explosion.
Jinjie Zhou, Shuaijie Zhao, Yang Zheng, Xingquan Shen, Jitang Zhang   +4 more
doaj   +1 more source

StackingNet: Collective Inference Across Independent AI Foundation Models

Advanced Science, EarlyView.
ABSTRACT Artificial intelligence (AI) built on large foundation models has transformed language understanding, computer vision, and reasoning, yet these systems remain isolated and cannot readily share their capabilities. Coordinating the complementary strengths of independently developed, black‐box foundation models is essential for trustworthy ...
Siyang Li, Chenhao Liu, Dongrui Wu, Zhigang Zeng, Lieyun Ding   +4 more
wiley   +1 more source

Gap‐Free Information Transfer in 4D‐STEM via Fusion of Complementary Scattering Channels

Advanced Science, EarlyView.
Fused Full‐Field STEM (FF‐STEM) is introduced as a 4D‐STEM imaging modality that combines direct ptychography with tilt‐corrected dark‐field reconstruction in a single acquisition. Fourier‐space fusion using Wiener‐type spectral weighting closes the low‐frequency contrast gap inherent to bright‐field methods, delivering gap‐free, dose‐efficient, near ...
Shengbo You, Georgios Varnavides, Sagar Khavnekar, Nikita Palatkin, Sihan Shao, Mingjian Wu, Daniel Stroppa, Darya Chernikova, Baixu Zhu, Ricardo Egoavil, Stefano Vespucci, Dileep Krishnan, Xingchen Ye, Florian K. M. Schur, Erdmann Spiecker, Philipp Pelz   +15 more
wiley   +1 more source

Application of Ensemble Empirical Mode Decomposition based Support Vector Regression Model for Wind Power Prediction

Jurnal Teknik Industri, 2020
Improving accuracy of wind power prediction is important to maintain power system stability. However, wind power prediction is difficult due to randomness and high volatility characteristics.
Irene Karijadi, Ig. Jaka Mulyana
doaj   +1 more source

Analysis of Rainfall and Temperature Data Using Ensemble Empirical Mode Decomposition

Data Science Journal, 2019
Climatic variables such as rainfall and temperature have nonlinear and non-stationary characteristics such that analysing them using linear methods inconclusive results are found. Ensemble empirical mode decomposition (EEMD) is a data-adaptive method that is best suitable for data with nonlinear and non-stationary characteristics.
Willard Zvarevashe, Syamala Krishnannair, Venkataraman Sivakumar   +2 more
openaire   +4 more sources

A Global Methane Observation System to Reduce Uncertainty for Anthropogenic and Natural Sources and Sinks for Detecting and Attributing Climate Feedbacks

Advanced Science, EarlyView.
Conceptual illustration of a Global Ecosystem Methane Observing System (GEM‐OS) integrating satellites, aircraft, atmospheric networks, and ecosystem measurements to quantify methane emissions from anthropogenic and natural sources. The multi‐scale observing framework improves source attribution, reduces uncertainty in regional methane budgets, and ...
P. Ciais, S. Peng, J. Chang, F. Li, Q. Zhu, K. Yuan, G. Hugelius, H. Li, Y. Cai, F. Chevallier, K. Tibrewal, E. A. Kort, K. Arndt, J. Watts, B. Buma, N. Besic, P. I. Palmer, H. Cadillo‐Quiroz, E. Euskirchen, M. J. Gondwe, A. Hoyt, R. Jackson, S. Malone, D. Monteverde, S. Natali, M. Ramonet, C. Rey‐Sanchez, L. B. Sagang, E. A. G. Schuur, R. Vargas, R. Varner, Z. Zhang, B. Poulter   +32 more
wiley   +1 more source

Reimagining Lignin Valorization: Synthetic Biology–Enabled Sustainable Aromatic Carbon Biomanufacturing

Advanced Science, EarlyView.
The diagram illustrates a sustainable model of lignin valorization and carbon cycling based on microbial cell factories. Using lignin as the feedstock, synthetic biology technologies, including depolymerization, cell factory construction, pathway gene module integration, and metabolic network regulation, are applied to convert lignin into bulk ...
Na Li, Jun‐Jie Zhangyang, Bing‐Zhi Li, Zhi‐Hua Liu, Ying‐Jin Yuan   +4 more
wiley   +1 more source

Probing Electrocatalyst Design for Product Selectivity in CO2 Reduction

Advanced Science, EarlyView.
Selective CO2 electroreduction is controlled by catalyst structure, dynamic surface reconstruction, adsorbate interactions, and reaction microenvironment. This review summarizes Cu‐ and non‐Cu‐based catalysts, single‐atom and molecular systems, degradation pathways, and operando/computational strategies for steering CO2RR toward hydrocarbons ...
Suvodeep Sen, Bapan Biswas, Apinya Ngoipala, Julia Wiktor, Ujjwal Pal, Shalini Singh   +5 more
wiley   +1 more source