Results 201 to 210 of about 176,057 (286)

Toward Reliable Metal Halide Perovskite FETs: From Electronic Structure and Device Physics to Stability and Performance Engineering

Advanced Electronic Materials, EarlyView.
Metal halide perovskite field‐effect transistors (PeFETs) offer great promise for flexible, low‐cost, and high‐performance due to their excellent charge carrier properties. However, challenges like ion migration, hysteresis, and instability limit their performance.
Georgios Chatzigiannakis, Anastasia Soultati, Leonidas C. Palilis, Ermioni Polydorou, Konstantinos Davazoglou, Petros‐Panagis Filippatos, Goutham Raj Perumallapelli, Ravindra Naik Bukke, Abd. Rashid bin Mohd Yusoff, Ilhwan Ryu, Peng Gao, Alexander Chroneos, Mohammad Khaja Nazeeruddin, Maria Vasilopoulou   +13 more
wiley   +1 more source

Comparative Role of rGO, AgNWs, and rGO-AgNWs Hybrid Structure in the EMI Shielding Performance of Polyaniline/PCL-Based Flexible Films. [PDF]

Molecules
Gajić B, Radoičić M, Yasir M, Saeed W, Bolka S, Nardin B, Potočnik J, Ćirić-Marjanović G, Šaponjić Z, Jovanović S.   +9 more
europepmc   +1 more source

Aqueous Zinc‐Based Batteries: Active Materials, Device Design, and Future Perspectives

Advanced Energy Materials, EarlyView.
This review conducts a comprehensive analysis of aqueous zinc‐based batteries (AZBs) based on their intrinsic mechanisms, including redox reactions, ion intercalation reactions, alloying reactions, electrochemical double‐layer reactions, and mixed mechanisms, systematically discussing recent advancements in each type of AZBs.
Yan Ran, Fang Dong, Shuhui Sun, Yong Lei
wiley   +1 more source

Can We Predict Posterior Cruciate Ligament Degeneration with Functional Tests? [PDF]

Maedica (Bucur)
Aydin ME, Atik A, Turan G.
europepmc   +1 more source

Artificial Intelligence‐Driven Insights into Electrospinning: Machine Learning Models to Predict Cotton‐Wool‐Like Structure of Electrospun Fibers

Advanced Intelligent Discovery, EarlyView.
Electrospinning allows the fabrication of fibrous 3D cotton‐wool‐like scaffolds for tissue engineering. Optimizing this process traditionally relies on trial‐and‐error approaches, and artificial intelligence (AI)‐based tools can support it, with the prediction of fiber properties. This work uses machine learning to classify and predict the structure of
Paolo D’Elia, Giovanna Pappalardo, Aldo R. Boccaccini, Liliana Liverani   +3 more
wiley   +1 more source

The Influence of Miscibility of Some PLA-Based Bio-Hybrids Designed for 3D Printing and Medium-Life Applications on Their Physical Aging and Thermodynamic Stability. [PDF]

Polymers (Basel)
Dimonie D, Mathe S, Trușcă RD, Damian CM, Râpă M, Dima ȘO, Dumitru Ș, Oancea F.   +7 more
europepmc   +1 more source

Roadmap on Artificial Intelligence‐Augmented Additive Manufacturing

Advanced Intelligent Systems, EarlyView.
This Roadmap outlines the transformative role of artificial intelligence‐augmented additive manufacturing, highlighting advances in design, monitoring, and product development. By integrating tools such as generative design, computer vision, digital twins, and closed‐loop control, it presents pathways toward smart, scalable, and autonomous additive ...
Ali Zolfagharian, Liuchao Jin, Qi Ge, Wei‐Hsin Liao, Andrés Díaz Lantada, Francisco Franco Martínez, Tianyu Zhang, Tao Liu, Charlie C. L. Wang, Mohammad Hossein Mosallanejad, Reza Ghanavati, Abdollah Saboori, Alejandro De Blas De Miguel, William Solórzano‐Requejo, Yi Cai, Xiangyang Dong, Huangyi Qu, Najmeh Samadiani, Guangyan Huang, Austin Downey, Yanzhou Fu, Lang Yuan, Tsz‐Kwan (Glory) Lee, Arbind Agrahari Baniya, Eisha Waseem, Abdul Rahman Sani, Abbas Z. Kouzani, Yijia Wu, Markus P. Nemitz, Masoud Shirzad, Dageon Oh, Seung Yun Nam, Amedeo Franco Bonatti, Irene Chiesa, Gabriele Maria Fortunato, Giovanni Vozzi, Carmelo De Maria, Mahdi Bodaghi   +37 more
wiley   +1 more source

Apolipoprotein E knockout attenuates vascular graft fibrosis by reducing profibrotic macrophage formation through low-density lipoprotein receptor related protein 1. [PDF]

Bioact Mater
Fu J, Zhao M, Zhao J, Wu S, Wu J, Hong X, Huang H, Fu G, Xu S.   +8 more
europepmc   +1 more source