Results 151 to 160 of about 1,130,914 (300)

Quantum Emitters in Hexagonal Boron Nitride: Principles, Engineering and Applications

Advanced Functional Materials, EarlyView.
Quantum emitters in hexagonal boron nitride have emerged as a promising candidate for quantum information science. This review examines the fundamentals of these quantum emitters, including their level structures, defect engineering, and their possible chemical structures.
Thi Ngoc Anh Mai, Md Shakhawath Hossain, Nhat Minh Nguyen, Yongliang Chen, Chaohao Chen, Xiaoxue Xu, Quang Thang Trinh, Toan Dinh, Toan Trong Tran   +8 more
wiley   +1 more source

Integration of Perovskite/Low‐Dimensional Material Heterostructures for Optoelectronics and Artificial Visual Systems

Advanced Functional Materials, EarlyView.
Heterojunctions combining halide perovskites with low‐dimensional materials enhance optoelectronic devices by enabling precise charge control and improving efficiency, stability, and speed. These synergies advance flexible electronics, wearable sensors, and neuromorphic computing, mimicking biological vision for real‐time image analysis and intelligent
Yu‐Jin Du, Junjie Yang, Ziyu Lv, Yongbiao Zhai, Zezhuang Yi, Yuhui Xie, Ming‐Lin Zheng, Xiangyu Ma, Guodong Gong, Yan Wang, Ye Zhou, Su‐Ting Han   +11 more
wiley   +1 more source

Educating Future Computer Science Teachers to use the DQN Machine Learning Algorithm with ROS

, 2023

openalex   +1 more source

Flow‐Induced Vascular Remodeling on‐Chip: Implications for Anti‐VEGF Therapy

Advanced Functional Materials, EarlyView.
Flow‐induced vascular remodeling plays a critical role in network stabilization and function. Using a vasculature‐on‐chip system, this study reveals how physiological VEGF levels and flow affect vascular remodeling and provides insights into tumor vessel normalization.
Fatemeh Mirzapour‐Shafiyi, Elias Huber, Leonie Karr, Johnny Tong, Andreas Richard Bausch, Friedrich Christian Simmel, Karen Alim   +6 more
wiley   +1 more source

Predicting Aggregation Behavior of Nanoparticles in Liquid Crystals via Automated Data‐Driven Workflows

Advanced Functional Materials, EarlyView.
Herein, a comprehensive framework that enabled the optimization of colloidal solubility within a high‐dimensional parameter space and study of reversible assembly processes is developed. This data‐driven workflow integrated innovations including the robotic platform for automated AuNPs functionalization, machine learning for predicting and revealing ...
Yueyang Gao, Niamh Mac Fhionnlaoich, Max Besenhard, Arun Pankajakshan, Federico Galvanin, Stefan Guldin   +5 more
wiley   +1 more source

High‐Performance Millimeter Scale Electromagnetic Generator

Advanced Functional Materials, EarlyView.
A high‐performance millimeter‐scale electromagnetic generator (mmEMG) is developed using magnetic flux concentrator (MFC) films on both coil ends to enhance magnetic flux. Through simulations and experiments, structural and magnetic properties are optimized, achieving a 5.6‐fold electrical output improvement.
Jin Pyo Lee, Xinran Zhou, Yangyang Xin, Dace Gao, Peiwen Huang, Pooi See Lee   +5 more
wiley   +1 more source

Machine Learning‐Enabled Polymer Discovery for Enhanced Pulmonary siRNA Delivery

Advanced Functional Materials, EarlyView.
This study provides an efficient approach to train a machine learning model by merging heterogeneous literature data to predict suitable polymers for siRNA delivery. Without the need for extensive laboratory synthesis, the machine learning enabled a virtual screening and successfully predicted a polymer that is validated for effective gene silencing in
Felix Sieber‐Schäfer, Min Jiang, Adrian Kromer, Anny Nguyen, Müge Molbay, Simone Pinto Carneiro, David Jürgens, Gerald Burgstaller, Bastian Popper, Benjamin Winkeljann, Olivia Monika Merkel   +10 more
wiley   +1 more source

Biases and Ethical Considerations for Machine Learning Pipelines in the Computational Social Sciences

, 2023
De, S, Jangra, S, Agarwal, V, Johnson, J, Sastry, N   +4 more
openaire   +2 more sources

Prediction of the Computer Science Department's Educational Performance Through Machine Learning Model by Analyzing Students' Academic Statements

, 2023
Md. Alamgir Hossain, Ishtiaq Ahammad, Md. Kawsar Ahmed, Md Imtiaz Ahmed   +3 more
openalex   +2 more sources

AI and Machine Learning in Engineering: Transformative Applications and Case Studies in Computational Science

This paper explores the transformative impact of Artificial Intelligence (AI) and Machine Learning (ML) in engineering, emphasizing their integration with computational science to address complex challenges and optimize infrastructure. By leveraging advanced neural network architectures, such as Physics-Informed Neural Networks (PINNs) and deep ...
openaire   +2 more sources