Results 101 to 110 of about 21,657 (263)

Characterization of an energy efficient pulsed current TIG welding process on AISI 316 and 304 stainless steels. [PDF]

Heliyon, 2023
Casanueva R, Brañas C, Diaz FJ, Azcondo FJ, Ferreño D, Setien J.   +5 more
europepmc   +1 more source

Atomic‐Layer‐Deposited ZnF2 on Aluminum Enabling In Situ NaF/Na–Zn Interphase for Robust Anode‐Free Sodium Batteries

Advanced Energy Materials, EarlyView.
“Sodiation of an ultrathin ALD‐ZnF2 layer on an Al current collector generates a sodiophilic Na–Zn alloy and a NaF‐rich SEI, enabling uniform Na deposition and highly reversible anode‐free sodium batteries.” ABSTRACT Achieving high‐energy‐density “anode‐free” sodium batteries remains a daunting challenge due to rapid capacity decay caused by poor ...
Viet Phuong Nguyen, Angelina Sarapulova, Michael Günthel, Markus Knäbbeler‐Buß, Changin Kim, Young‐Woon Byeon, Moonwon Lee, Kanghoon Yim, Eric Tröster, Sonia Dsoke, Seung‐Mo Lee   +10 more
wiley   +1 more source

Numerical Analysis of Molten Pool Dynamic Behaviors during High-Speed Oscillation Laser Welding with Aluminum Alloy

Metals
Increased welding speeds are often used to achieve high welding efficiency. However, welding defects, including pores and humps, can easily be formed under high-speed welding conditions.
Yuewei Ai, Yachao Yan, Shibo Han
doaj   +1 more source

Microscopic and Mechanical Characterization of Co-Cr Dental Alloys Joined by the TIG Welding Process. [PDF]

Materials (Basel), 2023
Carek A, Slokar Benić L, Bubalo V, Kosović N.   +3 more
europepmc   +1 more source

Toward Knowledge‐Guided AI for Inverse Design in Manufacturing: A Perspective on Domain, Physics, and Human–AI Synergy

Advanced Intelligent Discovery, EarlyView.
This perspective highlights how knowledge‐guided artificial intelligence can address key challenges in manufacturing inverse design, including high‐dimensional search spaces, limited data, and process constraints. It focused on three complementary pillars—expert‐guided problem definition, physics‐informed machine learning, and large language model ...
Hugon Lee, Hyeonbin Moon, Junhyeong Lee, Seunghwa Ryu   +3 more
wiley   +1 more source

Effect of Welding Process Parameters on the Strength of Dissimilar Joints of S355 and Strenx 700 Steels Used in the Manufacture of Agricultural Machinery. [PDF]

Materials (Basel), 2023
Szusta J, Derpeński Ł, Karakaş Ö, Tüzün N, Dobrzański S.   +4 more
europepmc   +1 more source

Resource‐Aware Contrastive Scattering Meta‐Learning for Efficient Few‐Shot Acoustic Anomaly Detection

Advanced Intelligent Systems, EarlyView.
This paper introduces a resource‐aware Contrastive Scattering Meta‐Learning (CSML) framework for acoustic anomaly detection. By leveraging training‐free wavelet scattering and metric‐based meta‐learning, the model achieves competitive performance with only 50 K learnable parameters—a 98% reduction compared to state‐of‐the‐art frameworks—enabling ...
Rami Zewail, Bassem Mokhtar
wiley   +1 more source

Optimization of Friction Stir Spot Welding Process Using Bonding Criterion and Artificial Neural Network. [PDF]

Materials (Basel), 2023
Jo DS, Kahhal P, Kim JH.
europepmc   +1 more source

Pre‐Curved Everting Robots With Embedded Steering Intelligence Fabricated by CO2 Laser Welding

Advanced Intelligent Systems, EarlyView.
Design and experimental demonstration of a laser welded growing robot for anatomically guided navigation. The robot follows an aortic arch phantom entering the branchiocephalic branch through steering by design. The figure shows the physical phantom setup, CAD defined weld geometry and full robot eversion.
Brandon Saldarriaga, Panagiotis Kalozoumis, Panagiotis Vartholomeos, Carlo Seneci, Kawal Rhode, Christos Bergeles   +5 more
wiley   +1 more source

Advanced Analytical Methods of the Analysis of Friction Stir Welding Process (FSW) of Aluminum Sheets Used in the Automotive Industry. [PDF]

Materials (Basel), 2023
Chyła K, Gaska K, Gronba-Chyła A, Generowicz A, Grąz K, Ciuła J.   +5 more
europepmc   +1 more source