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Related papers: Data Mining for Terahertz Generation Crystals

200 papers

The study of granular crystals, metamaterials that consist of closely packed arrays of particles that interact elastically, is a vibrant area of research that combines ideas from disciplines such as materials science, nonlinear dynamics,…

Pattern Formation and Solitons · Physics 2017-10-11 C. Chong , Mason A. Porter , P. G. Kevrekidis , C. Daraio

Machine learning (ML) models utilizing structure-based features provide an efficient means for accurate property predictions across diverse chemical spaces. However, obtaining equilibrium crystal structures typically requires expensive…

Materials Science · Physics 2021-04-22 Yunxing Zuo , Mingde Qin , Chi Chen , Weike Ye , Xiangguo Li , Jian Luo , Shyue Ping Ong

Spintronic terahertz (THz) emitter provides the advantages such as apparently broader spectrum, significantly lower cost, and more flexibility in compared with the commercial THz emitters, and thus attracts great interests recently. In past…

Mesoscale and Nanoscale Physics · Physics 2018-11-13 Zheng Feng , Rui Yu , Yu Zhou , Hai Lu , Wei Tan , Hu Deng , Quancheng Liu , Zhaohui Zhai , Liguo Zhu , Jianwang Cai , Bingfeng Miao , Haifeng Ding

The constant demand for new functional materials calls for efficient strategies to accelerate the materials design and discovery. In addressing this challenge, machine learning generative models can offer promising opportunities since they…

Materials Science · Physics 2020-06-24 Sungwon Kim , Juhwan Noh , Geun Ho Gu , Alán Aspuru-Guzik , Yousung Jung

The traditional techniques for extracting polycrystalline grain structures from microscopy images, such as transmission electron microscopy (TEM) and scanning electron microscopy (SEM), are labour-intensive, subjective, and time-consuming,…

Machine Learning · Computer Science 2025-04-22 Ahmed Sobhi Saleh , Kristof Croes , Hajdin Ceric , Ingrid De Wolf , Houman Zahedmanesh

Crystal structure prediction (CSP), which aims to predict the three-dimensional atomic arrangement of a crystal from its composition, is central to materials discovery and mechanistic understanding. However, given the composition in a unit…

Materials Science · Physics 2026-03-10 Shi Yin , Jinming Mu , Xudong Zhu , Linxin He

De novo crystal generation, a central task in materials discovery, aims to generate crystals that are simultaneously valid, stable, unique, and novel. Existing methods mainly rely on black-box stochastic sampling, providing limited control…

We propose two novel samplers to generate high-quality samples from a given (un-normalized) probability density. Motivated by the success of generative adversarial networks, we construct our samplers using deep neural networks that…

Machine Learning · Statistics 2021-02-10 Tianyang Hu , Zixiang Chen , Hanxi Sun , Jincheng Bai , Mao Ye , Guang Cheng

We present an application of a high-throughput search of new rare-earth free permanent magnets focusing on 3d-5d transition metal compounds. The search involved a part of the ICSD database (international crystallographic structural…

Terahertz waves hold immense potential across diverse fields, including healthcare monitoring, biomedical imaging, precision navigation, high-speed communication, security screening, industrial quality control, and space exploration.…

Optics · Physics 2026-04-13 Yifan Zhao , Shahed-E- Zumrat , Szu-An Tsao , Mona Jarrahi

Intense, single-cycle terahertz (THz) pulses offer a promising approach for understanding and controlling the properties of a material on an ultrafast time scale. In particular, resonantly exciting phonons leads to a better understanding of…

Strongly Correlated Electrons · Physics 2016-10-05 P. Bowlan , J. Bowlan , S. A. Trugman , R. Valdes Aguilar , J. Qi , X. Liu , J. Furdyna , M. Dobrowolska , A. J. Taylor , D. A. Yarotski , R. P. Prasankumar

When searching for novel inorganic materials, limiting the combination of constituent elements can greatly improve the search efficiency. In this study, we used machine learning to predict elemental combinations with high reactivity for…

Materials Science · Physics 2025-04-30 Yuki Inada , Masaya Fujioka , Haruhiko Morito , Tohru Sugahara , Hisanori Yamane , Yukari Katsura

Liquid crystal polymers with exceptional optical properties are highly promising for next-generation virtual, augmented, and mixed reality (VR/AR/MR) technologies, serving as high-performance, compact, lightweight, and cost-effective…

We analytically show how a superposition of beamlets produces terahertz radiation with greater spatial homogeneity and efficiency compared to tilted-pulse-fronts generated by diffraction gratings. The advantages are particularly notable for…

It is found that nonlinear interaction of plasma wakefields driven by counterpropagating laser or particle beams can efficiently generate high-power electromagnetic radiation at the second harmonic of the plasma frequency. Using a simple…

Plasma Physics · Physics 2017-10-11 I. V. Timofeev , V. V. Annenkov , E. P. Volchok

We present a genetic algorithm (GA) for structural search that combines the speed of structure exploration by classical potentials with the accuracy of density functional theory (DFT) calculations in an adaptive and iterative way. This…

Materials Science · Physics 2015-11-06 S. Q. Wu , M. Ji , C. Z. Wang , M. C. Nguyen , X. Zhao , K. Umemoto , R. M. Wentzcovitch , K. M. Ho

Magnetic materials are crucial components of many technologies that could drive the ecological transition, including electric motors, wind turbine generators and magnetic refrigeration systems. Discovering materials with large magnetic…

Recent advances in the synthesis of polar molecular materials have produced practical alternatives to ferroelectric ceramics, opening up exciting new avenues for their incorporation into modern electronic devices. However, in order to…

We report the coherent generation and detection of terahertz (THz) pulses covering the bandwidth of 0.1-9 THz in a high repetition rate, low pulse energy laser system. In this work we demonstrate the application and evaluation of…

Discovering new solid-state materials requires rapidly exploring the vast space of crystal structures and locating stable regions. Generating stable materials with desired properties and compositions is extremely difficult as we search for…

Machine Learning · Computer Science 2024-11-08 Tri Minh Nguyen , Sherif Abdulkader Tawfik , Truyen Tran , Sunil Gupta , Santu Rana , Svetha Venkatesh