Results 81 to 90 of about 56,420 (266)

Self‐Assembled Monolayers in p–i–n Perovskite Solar Cells: Molecular Design, Interfacial Engineering, and Machine Learning–Accelerated Material Discovery

Advanced Materials, EarlyView.
This review highlights the role of self‐assembled monolayers (SAMs) in perovskite solar cells, covering molecular engineering, multifunctional interface regulation, machine learning (ML) accelerated discovery, advanced device architectures, and pathways toward scalable fabrication and commercialization for high‐efficiency and stable single‐junction and
Asmat Ullah, Ying Luo, Stefaan De Wolf
wiley   +1 more source

Bayesian Optimization for Categorical and Mixed Variables Using a Multinomial Logit Surrogate

Algorithms
Bayesian optimization (BO) is a widely used framework for optimizing expensive black-box functions. Most BO methods rely on Gaussian process (GP) surrogates, which perform well in continuous domains but encounter difficulties when decision variables ...
Muhammad Amir Saeed, Antonio Candelieri
doaj   +1 more source

Optimal Control Drives Ultrafast and Energy‐Efficient Magnetization Switching in Van der Waals Magnets

Advanced Materials, EarlyView.
ABSTRACT The accelerating expansion of data‐centric technologies is sharply increasing the energy burden of information storage, placing unprecedented pressure on the efficiency of magnetic switching. Conventional field‐driven reversal, once the foundation of magnetic memory, has become impractical in modern architectures due to its high energy cost ...
Mohammad H. Badarneh, PeiYu Cai, Elton J. G. Santos   +2 more
wiley   +1 more source

The Implementation of Bayesian Optimization for Automatic Parameter Selection in Convolutional Neural Network for Lung Nodule Classification

Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI)
Lung cancer's high mortality rate makes early detection crucial. Machine learning techniques, especially convolutional neural networks (CNN), play a very important role in lung nodule detection.
Kadek Eka Sapta Wijaya, Gede Angga Pradipta, Dadang Hermawan   +2 more
doaj   +1 more source

Neuromorphic Electronics for Intelligence Everywhere: Emerging Devices, Flexible Platforms, and Scalable System Architectures

Advanced Materials, EarlyView.
The perspective presents an integrated view of neuromorphic technologies, from device physics to real‐time applicability, while highlighting the necessity of full‐stack co‐optimization. By outlining practical hardware‐level strategies to exploit device behavior and mitigate non‐idealities, it shows pathways for building efficient, scalable, and ...
Kapil Bhardwaj, Roshni Satheesh Babu, Yuxin Xia, Eva Bestelink, Radu Sporea, Nikos Hastas, Ioannis Zeimpekis, Dimitra G. Georgiadou, Sayani Majumdar   +8 more
wiley   +1 more source

Laser material processing optimization using bayesian optimization: a generic tool

Light: Advanced Manufacturing
Optimizing laser processes is historically challenging, requiring extensive and costly experimentation. To solve this issue, we apply Bayesian optimization for process parameter optimization to laser cutting, welding, and polishing.
Tobias Menold, Volkher Onuseit, Matthias Buser, Michael Haas, Nico Bär, Andreas Michalowski   +5 more
doaj   +1 more source

Organic Materials of Tomorrow: Horizons of Artificial Intelligence

Advanced Materials, EarlyView.
This review examines machine learning techniques accelerating the discovery of organic semiconductors by linking molecular structure to properties. Key methods include graph neural networks, generative models, and active learning. Applications to organic photovoltaics demonstrate practical impact.
Harold Mena, J. Terence Blaskovits, Kun‐Han Lin, Denis Andrienko   +3 more
wiley   +1 more source

Mechanistically Interpretable Artificial Intelligence for Designing Oxygen Electrocatalysts

Advanced Materials, EarlyView.
Mechanistically interpretable artificial intelligence screens nearly seven million perovskite compositions and identifies key descriptors—d‐p hybridization and densification resistance—that govern oxygen electrocatalysis. The discovered BaCo0.8Nb0.1Zr0.1O3‐δ achieves a record 2.68 W cm−2 peak power density at 600°C with over 500 h of durable operation ...
Xueyu Hu, Yucun Zhou, Haoyu Li, Zheyu Luo, Nai Shi, Yong Ding, Weining Wang, Weilin Zhang, Doyeub Kim, Chanho Kim, Yoojin Ahn, Nikhil Govindarajan, Minda Zou, Zhijun Liu, Yuefeng Song, Meilin Liu   +15 more
wiley   +1 more source

Optimize Gate-All-Around Devices Using Wide Neural Network-Enhanced Bayesian Optimization

IEEE Journal of the Electron Devices Society
Device design processes based on manual design experience require numerous experiments and simulations. As transistors continue to shrink, complex physical effects, such as quantum effects intensify, making the design process increasingly costly, whether
Jiaye Shen, Zhiqiang Li, Zhenjie Yao
doaj   +1 more source

A Tutorial on Bayesian Optimization

CoRR, 2018
Bayesian optimization is an approach to optimizing objective functions that take a long time (minutes or hours) to evaluate. It is best-suited for optimization over continuous domains of less than 20 dimensions, and tolerates stochastic noise in function evaluations.
openaire   +2 more sources