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Nodal semimetals, materials systems with nodal-point or -line Fermi surfaces, are much sought after for their novel transport and topological properties. Identification of experimental materials candidates, however, has mainly relied on…

Materials Science · Physics 2017-11-06 Ru Chen , Hoi Chun Po , Jeffrey B. Neaton , Ashvin Vishwanath

Recent observations have revealed an unexpectedly high binary fraction among the Trans-Neptunian Objects (TNOs) that populate the Kuiper-belt. The discovered binaries have four characteristics they comprise a few percent of the TNOs, the…

Astrophysics · Physics 2015-06-24 Yoko Funato , Junichiro Makino , Piet Hut , Eiichiro Kokubo , Daisuke Kinoshita

Amorphous materials are solids that lack long-range atomic order but possess complex short- and medium-range order. Unlike crystalline materials that can be described by unit cells containing few up to hundreds of atoms, amorphous materials…

Machine Learning · Computer Science 2026-04-01 Yan Lin , Jonas A. Finkler , Tao Du , Jilin Hu , Morten M. Smedskjaer

Amorphous solids lack long-range order. Therefore identifying structural defects -- akin to dislocations in crystalline solids -- that carry plastic flow in these systems remains a daunting challenge. By comparing many different structural…

Generating high magnetic fields requires materials with not only high electric conductivity, but also good strength properties in order to withstand the necessarily strong Lorentz forces. A number of bi-metal composites, most notably Cu/Nb,…

Materials Science · Physics 2024-10-21 Daniel N. Blaschke , John S. Carpenter , Abigail Hunter

The topological properties of materials are, until now, associated with the features of their crystalline structure, although translational symmetry is not an explicit requirement of the topological phases. Recent studies of hopping models…

Metamaterials are artificially engineered structures that manipulate electromagnetic waves, having optical properties absent in natural materials. Recently, machine learning for the inverse design of metamaterials has drawn attention.…

The mechanical properties of metallic nanostructures are governed not only by topology but also by crystal symmetry and face-specific surface physics, which are typically absent from continuum topology optimization. We develop an…

Applied Physics · Physics 2026-04-07 Chun-Teh Chen , Denvid Lau

There are still debates regarding the mechanisms that lead to hot cracking in parts build by additive manufacturing (AM) of non-weldable Ni-based superalloys. This lack of in-depth understanding of the root causes of hot cracking is an…

Progress in the application of machine learning (ML) methods to materials design is hindered by the lack of understanding of the reliability of ML predictions, in particular for the application of ML to small data sets often found in…

Materials Science · Physics 2023-04-06 Evan M. Askanazi , Emanuel A. Lazar , Ilya Grinberg

The vastness of the space of possible multicomponent metal alloys is hoped to provide improved structural materials but also challenges traditional, low-throughput materials design efforts. Computational screening could narrow this search…

The large-scale search for high-performing candidate 2D materials is limited to calculating a few simple descriptors, usually with first-principles density functional theory calculations. In this work, we alleviate this issue by extending…

Materials Science · Physics 2020-07-07 Victor Venturi , Holden Parks , Zeeshan Ahmad , Venkatasubramanian Viswanathan

A coarsened model for a binary system with limited miscibility of components is proposed; the system is described in terms of structural states in small parts of the material. The material is assumed to have two alternative types of…

Statistical Mechanics · Physics 2007-05-23 Leonid D. Son , German M. Rusakov , Alexander Z. Patashinski , Mark A. Ratner

High entropy materials, which include high entropy alloys, carbides, and borides, are a topic of substantial research interest due to the possibility of a large number of new material compositions that could fill gaps in application needs.…

Materials Science · Physics 2020-07-16 Lavina Backman , Joshua Gild , Jian Luo , Elizabeth J. Opila

Multicomponent nanoparticles can be synthesized with either homogeneous or phase-segregated architectures depending on the synthesis conditions and elements incorporated. To understand the parameters that determine their structural fate,…

Amorphous metallic foams are prospective materials due to unique combination of their mechanical and energy-absorption properties. In the present work, atomistic dynamics simulations are performed under isobaric conditions with the pressure…

Materials Science · Physics 2020-05-22 Bulat N. Galimzyanov , Anatolii V. Mokshin

The formation of bulk metallic glass requires the constituent elements to have a negative heat of mixing but has no restrictions on its magnitude. An understanding of this issue is lacking due to the absence of a valid method for describing…

Materials Science · Physics 2023-05-10 Song Ling Liu , Xin Yu Luo , Jing Shan Cao , Zhao Yuan Liu , Bei Bei Xu , Yong Hao Sun , Weihua Wang

Linear complexions are stable defect states that form along dislocations and recent experiments have demonstrated strengthening effects exceeding classical precipitation hardening predictions, motivating a detailed study of nanoscale…

Materials Science · Physics 2026-04-15 Zhengyu Zhang , Daniel S. Gianola , Timothy J. Rupert

Antiferromagnetic spintronic devices have the potential to outperform conventional ferromagnetic devices due to their ultrafast dynamics and high data density. A challenge in designing these devices is the control and detection of the…

Materials Science · Physics 2021-01-20 Sarah Jenkins , Roy W. Chantrell , Richard F. L. Evans

Amorphous solids form an enormous and underutilized class of materials. In order to drive the discovery of new useful amorphous materials further we need to achieve a closer convergence between computational and experimental methods. In…

Disordered Systems and Neural Networks · Physics 2024-11-19 Ata Madanchi , Emna Azek , Karim Zongo , Laurent K. Béland , Normand Mousseau , Lena Simine
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