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Traditionally, yield strength prediction relies on detailed and resource-intensive microstructural characterization combined with empirical equations. However, quantifying microstructural feature length scales for novel processes like…

Materials Science · Physics 2024-12-12 Abhinav Chandraker , Sampad Barik , Nichenametla Jai Sai , Ankur Chauhan

Accurate prediction of metal-oxide adhesion in high-entropy alloys (HEAs) is challenging because interfacial segregation, atomic environments, and macroscopic thermodynamic quantities are strongly correlated. Relying solely on…

Materials Science · Physics 2026-03-06 Dennis Boakye , Chuang Deng

Multi principal element alloys (MPEAs) comprise a unique class of metal alloys. MPEAs have been demonstrated to possess several exceptional properties, including, as most relevant to the present study, a high corrosion resistance. In the…

Significant improvements to the production rate of additive manufacturing (AM) technologies are essential to their cost-effectiveness and competitiveness with traditional processing routes. Moreover, much faster AM processes, in combination…

Applied Physics · Physics 2017-09-19 Jamison Go , A. John Hart

Decades accumulation of theory simulations lead to boom in material database, which combined with machine learning methods has been a valuable driver for the data-intensive material discovery, i.e., the fourth research paradigm. However,…

Materials Science · Physics 2025-02-10 Tiancheng Ma , Zihan Zhang , Shuting Wu , Defang Duan , Tian Cui

Machine learning (ML) has emerged as a powerful tool for accelerating the computational design and production of materials. In materials science, ML has primarily supported large-scale discovery of novel compounds using first-principles…

The increased energy and power density required in modern electronics poses a challenge for designing new dielectric polymer materials with high energy density while maintaining low loss at high applied electric fields. Recently, an…

Despite multiple successful applications of high-throughput computational materials design from first principles, there is a number of factors that inhibit its future adoption. Of particular importance are limited ability to provide high…

Materials Science · Physics 2018-07-17 Protik Das , Mohammad Mohammadi , Timur Bazhirov

In this degree work, a theoretical computational study on high entropy alloys (HEAs) was carried out. Two specific alloys were chosen for study, AlCoCrFeNi and TiVZrNbHf. The study was based on the parameters deduced from the Hume-Rothery…

Materials Science · Physics 2023-12-19 Jhonn Royero

Defects in laser powder bed fusion (L-PBF) parts often result from the meso-scale dynamics of the molten alloy near the laser, known as the melt pool. For instance, the melt pool can directly contribute to the formation of undesirable…

Additive-free electroformed copper has emerged as the material of choice in exceptionally radiopure detectors for rare-event searches, based on its radiopurity, physical properties, and affordability. However, copper is ductile and of…

Instrumentation and Detectors · Physics 2025-10-09 Dimitra Spathara , Patrick Knights , Konstantinos Nikolopoulos

Metal additive manufacturing (AM) by laser powder bed fusion (L-PBF) builds upon fundamentals established in the field of laser welding which include the influence of gas and plume dynamics on weld depth and quality. L-PBF demands a…

Additive manufacturing (AM; 3D printing) in aluminium using laser powder bed fusion provides a new design space for lightweight mirror production. Printing layer-by-layer enables the use of intricate lattices for mass reduction, as well as…

LPBF of Al alloys is associated with numerous challenges when compared to other commonly used alloys due to their higher reflectivity and thermal conductivity. In this work, processing diagrams, temperature prediction models, XCT, and…

Materials Science · Physics 2022-09-28 Sagar Patel , Haoxiu Chen , Mihaela Vlasea , Yu Zou

Hybrid manufacturing (HM) technologies combine additive and subtractive manufacturing (AM/SM) capabilities in multi-modal process plans that leverage the strengths of each. Despite the growing interest in HM technologies, software tools for…

Computational Geometry · Computer Science 2022-06-06 George P. Harabin , Morad Behandish

The paper presents an innovative methodology based on the use of a new predictive algorithm created by the researchers capable of obtaining the elastic modulus of a plastic material manufactured with MEX and its mechanical behaviour in the…

Computational Engineering, Finance, and Science · Computer Science 2025-08-20 J. M. Mercado Colmenero , C. Martin Donate

Printed electronics (PE) promises on-demand fabrication, low non-recurring engineering costs, and sub-cent fabrication costs. It also allows for high customization that would be infeasible in silicon, and bespoke architectures prevail to…

Machine Learning · Computer Science 2023-04-04 Giorgos Armeniakos , Georgios Zervakis , Dimitrios Soudris , Mehdi B. Tahoori , Jörg Henkel

The increased availability of computing time, in recent years, allows for systematic high-throughput studies of material classes with the purpose of both screening for materials with remarkable properties and understanding how structural…

Materials Science · Physics 2023-11-28 Robin Hilgers , Daniel Wortmann , Stefan Blügel

New refractory alloys are being continuously designed and characterised for applications requiring good high-temperature mechanical properties and stability. Computational design from atomistic simulations is limited by interatomic…

Materials Science · Physics 2026-03-05 Jesper Byggmästar , Tiago Lopes , Zheyong Fan , Tapio Ala-Nissila

The novel non-isothermal Hot Forming and cold die Quenching (HFQ) process can enable the cost-effective production of complex shaped, high strength aluminium alloy panel components. However, the unfamiliarity of designing for the new…

Computational Engineering, Finance, and Science · Computer Science 2021-04-28 Hamid Reza Attar , Haosu Zhou , Alistair Foster , Nan Li
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