Results 101 to 110 of about 1,466,211 (327)

First‐Principles Modeling of Solid Solution Softening and Hardening Effects in Al–Mg–Zr–Si Aluminum Alloys

Advanced Engineering Materials, EarlyView.
The role of various alloying elements in face‐centered cubic aluminum on the barrier of a Shockley partial dislocation during its motion is presented. The study aims to understand how alloying atoms such as Mg, Si, and Zr affect the energy landscape for dislocation motion, thus influencing the solid solution hardening and softening in aluminum, which ...
Inna Plyushchay, Zhengqing Wei, Nebahat Bulut, Sibylle Gemming   +3 more
wiley   +1 more source

Learning Sets with Separating Kernels

, 2014
We consider the problem of learning a set from random samples. We show how relevant geometric and topological properties of a set can be studied analytically using concepts from the theory of reproducing kernel Hilbert spaces.
De Vito, Ernesto, Rosasco, Lorenzo, Toigo, Alessandro   +2 more
core   +1 more source

Wafer Bonding Technologies for Microelectromechanical Systems and 3D ICs: Advances, Challenges, and Trends

Advanced Engineering Materials, EarlyView.
This review explores wafer bonding technologies, covering wafer preparation, activation methods, and bonding mechanisms. It compares direct and indirect bonding, highlights recent advancements and future trends, and examines applications in 3D integration and packaging.
Abdul Ahad Khan, Tuan‐Khoa Nguyen, Quang Thang Trinh, Nam‐Trung Nguyen, Dzung Viet Dao, Yong Zhu   +5 more
wiley   +1 more source

Comparisons of different deep learning-based methods on fault diagnosis for geared system

International Journal of Distributed Sensor Networks, 2019
The running state of a geared transmission system affects the stability and reliability of the whole mechanical system. It will greatly reduce the maintenance cost of a mechanical system to identify the faulty state of the geared transmission system ...
Bing Han, Xiaohui Yang, Yafeng Ren, Wanggui Lan   +3 more
doaj   +1 more source

Introduction: Investigating Written Dyadic Interaction through a Complex Dynamic Systems Theory Perspective

Studies in Applied Linguistics & TESOL, 2017
Since its inception in the late 1960’s, the field of Second Language Acquisition (SLA) has undergone many transformations. As pre-existing theories have been expanded upon and new theories introduced, researchers and practitioners have come to a deeper ...
Shafinaz Ahmed, Anna Ciriani Dean
doaj   +1 more source

Adversarial scheduling analysis of Game-Theoretic Models of Norm Diffusion. [PDF]

In (Istrate et al. SODA 2001) we advocated the investigation of robustness of results in the theory of learning in games under adversarial scheduling models.
Istrate, Gabriel, Marathe, Madhav V., Ravi, S.S.   +2 more
core   +1 more source

5,11‐Di(thiophen‐2‐yl)Tetracene: A Novel Tetracene Derivative for Efficient Singlet Fission with Enhanced Physical and Chemical Stability in Thin Films

Advanced Functional Materials, EarlyView.
In this work, a new tetracene derivative, 5,11‐di(thiophen‐2‐yl)tetracene (2T‐Tc) is introduced, exhibiting enhanced physical and chemical stability, and retaining favorable singlet fission kinetics with near unity triplet pair yield in thin films.
Jieun Lee, Jeoungin Yi, Hyerim Hong, Yu Jin Lee, Feifei Fang, Sangjun Lee, Won Bo Lee, Sungyoung Yun, Kyung‐Bae Park, Jeong‐Il Park, Dongho Kim, Woojae Kim   +11 more
wiley   +1 more source

Active delta-learning for fast construction of interatomic potentials and stable molecular dynamics simulations

Machine Learning: Science and Technology
Active learning (AL) requires massive time for comprehensive sampling of complex potential energy surfaces to achieve desirable accuracy and stability of machine learning (ML) potentials.
Yaohuang Huang, Yi-Fan Hou, Pavlo O Dral
doaj   +1 more source

Method of Motion Planning for Digital Twin Navigation and Cutting of Shearer

Sensors
To further enhance the intelligence level of coal mining faces and achieve the autonomous derivation, learning, and optimization of shearer navigation cutting, this paper proposes the methods of shearer digital twin navigation cutting motion planning ...
Bing Miao, Shirong Ge, Yunwang Li, Yinan Guo   +3 more
doaj   +1 more source

Understanding Stability Mechanisms in Single-Atom Alloys with Theory-infused Deep Learning

We present an interpretable deep learning model that enhances the prediction of cohesive energy in transition metal alloys (TMAs) by incorporating cohesion theory into a graph neural network (GNN) framework. The model not only predicts the total cohesive energy-an indicator of crystal stability-but also disentangles its various contributing factors and
Huang, Yang, Wang, Shih-Han, Cao, Shuyi, Achenie, Luke E. K., Xin, Hongliang   +4 more
openaire   +2 more sources