Results 81 to 90 of about 108,936 (256)

Defect Evolution and Mechanical Performance of Fused Filament Fabrication‐Manufactured 17‐4PH Stainless Steel Revealed by X‐Ray Computed Tomography

Advanced Engineering Materials, EarlyView.
X‐ray computed tomography reveals how process‐induced defects evolve from green to sintered states in Fused Filament Fabrication (FFF)‐manufactured 17‐4PH stainless steel. Internal porosity, weakest cross‐sections, and fracture locations show strong correlation with tensile performance, demonstrating the potential of computed tomography (CT)‐based ...
György Ledniczky, Márk Sárközi, Ibolya Zsoldos, Zoltán Weltsch   +3 more
wiley   +1 more source

Extraction of physicochemical laws by symbolic regression using a Bayesian information criterion

Science and Technology of Advanced Materials: Methods
In the search for new high-performance materials in materials science, especially in polynomial science, it is important to use physicochemical laws linking materials structure and physical properties, and predict the physical properties required for the
Naoki Yamane, Kan Hatakeyama-Sato, Yuma Iwasaki, Yasuhiko Igarashi   +3 more
doaj   +1 more source

Beyond Presumptions: Toward Mechanistic Clarity in Metal‐Free Carbon Catalysts for Electrochemical H2O2 Production via Data Science

Advanced Materials, EarlyView.
Metal‐free carbon catalysts enable the sustainable synthesis of hydrogen peroxide via two‐electron oxygen reduction; however, active site complexity continues to hinder reliable interpretation. This review critiques correlation‐based approaches and highlights the importance of orthogonal experimental designs, standardized catalyst passports ...
Dayu Zhu, Hsi‐wen Wu, Xiao Wang, Jie Zhang   +3 more
wiley   +1 more source

Defect Prediction Using Akaike and Bayesian Information Criterion [PDF]

Computer Systems Science and Engineering, 2022
Saleh Albahli, Ghulam Nabi Ahmad Hassan Yar   +1 more
openaire   +1 more source

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

Discussion of: "A Bayesian information criterion for singular models"

, 2016
Contributed discussion to the paper of Drton and Plummer (2017), presented before the Royal Statistical Society on 5th October 2016.
Friel, N., McKeone, J. P., Oates, C. J., Pettitt, A. N.   +3 more
openaire   +2 more sources

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

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

An Approach for Determining the Number of Clusters in a Model-Based Cluster Analysis

Entropy, 2017
To determine the number of clusters in the clustering analysis that has a broad range of applied sciences, such as physics, chemistry, biology, engineering, economics etc., many methods have been proposed in the literature.
Serkan Akogul, Murat Erisoglu
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