Results 191 to 200 of about 665 (240)

Design and operational challenges of renewable-powered isolated microgrids: a zero-carbon approach. [PDF]

Sci Rep
Figueredo WM, Saavedra OR, Leite Neto PB, Oliveira DQ.   +3 more
europepmc   +1 more source

Copper Contact for Perovskite Solar Cells: Properties, Interfaces, and Scalable Integration

Advanced Energy and Sustainability Research, EarlyView.
Copper electrodes, as low‐cost, scalable contacts for perovskite solar cells, offer several advantages over precious metals such as Au and Ag, including performance, cost, deposition methods, and interfacial engineering. Copper (Cu) electrodes are increasingly considered practical, sustainable alternatives to noble‐metal contacts in perovskite solar ...
Shuwei Cao, Jianyong Han, Xiaohu Zhao, Yaming Yu, Peng Gao   +4 more
wiley   +1 more source

Adaptive virtual impedance control strategy based on IWOA-fuzzy PID and its application to reactive power sharing in islanded microgrids. [PDF]

Sci Rep
Hou Y.
europepmc   +1 more source

Unveiling Localized Heat in Lithium‐Ion Cells for Intelligent Temperature Sensing

Advanced Energy and Sustainability Research, EarlyView.
Heat generation, thermal responses, and intelligent management in batteries. Lithium‐ion batteries (LIBs) power electric vehicles, portable electronics, and grid‐scale storage, yet their safety, performance, and lifetime are constrained by thermal effects.
Yunke Wang, Yuzhu Yuan, Javed Alam, Guangpeng Zhang, José V. Anguita, Zijian Wang, Kai Yang   +6 more
wiley   +1 more source

Intrinsically flexible multimode reconfigurable transistors for polymorphic circuits and neuromorphic devices. [PDF]

Nat Commun
Wang W, Qiu R, Zhu J, Zhu T, Wang J, Liu D, Liang J, Wang C, Zhang S, Wang Z, Huang Q, Wang X, Zhang M.   +12 more
europepmc   +1 more source

What to Make and How to Make It: Combining Machine Learning and Statistical Learning to Design New Materials

Advanced Intelligent Discovery, EarlyView.
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley   +1 more source

Environmental impacts of a stand-alone photovoltaic system in sub-saharan Africa: A case study in Burkina Faso. [PDF]

Heliyon
Badza K, Sawadogo M, Soro YM.
europepmc   +1 more source

Deep Learning Prediction of Surface Roughness in Multi‐Stage Microneedle Fabrication: A Long Short‐Term Memory‐Recurrent Neural Network Approach

Advanced Intelligent Discovery, EarlyView.
A sequential deep learning framework is developed to model surface roughness progression in multi‐stage microneedle fabrication. Using real‐world experimental data from 3D printing, molding, and casting stages, an long short‐term memory‐based recurrent neural network captures the cumulative influence of geometric parameters and intermediate outputs ...
Abdollah Ahmadpour, Sara Soltanabadi Farshi, Tuanna Ozcan, Amir Mohammad Ketabchi, Alper Kiraz, Savas Tasoglu   +5 more
wiley   +1 more source

A Joint Active Damping Strategy Based on LCL-Type Grid-Connected Inverters for Grid Current Feedback and PCC Voltage Unit Feedforward. [PDF]

Sensors (Basel)
Ke S, Liang B.
europepmc   +1 more source

Gaussian Process Regression–Neural Network Hybrid with Optimized Redundant Coordinates: A New Simple Yet Potent Tool for Scientist's Machine Learning Toolbox

Advanced Intelligent Discovery, EarlyView.
A machine learning method, opt‐GPRNN, is presented that combines the advantages of neural networks and kernel regressions. It is based on additive GPR in optimized redundant coordinates and allows building a representation of the target with a small number of terms while avoiding overfitting when the number of terms is larger than optimal.
Sergei Manzhos, Manabu Ihara
wiley   +1 more source