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Related papers: Data Mining for Terahertz Generation Crystals

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Transmission electron diffraction is a powerful and versatile structural probe for the characterization of a broad range of materials, from nanocrystalline thin films to single crystals. With recent developments in fast electron detectors…

Materials Science · Physics 2021-10-06 Jian-Min Zuo , Renliang Yuan , Yu-Tsun Shao , Haw-Wen Hsiao , Saran Pidaparthy , Yang Hu , Qun Yang , Jiong Zhang

Data mining techniques, including clustering and classification tasks, for the automatic information extraction from large datasets are increasingly demanded in several scientific fields. In particular, in the astrophysical field, large…

Astrophysics · Physics 2015-06-24 M. Frailis , A. De Angelis , V. Roberto

Predicting and characterizing the crystal structure of materials is a key problem in materials research and development. It is typically addressed with highly accurate quantum mechanical computations on a small set of candidate structures,…

Materials Science · Physics 2009-11-10 Stefano Curtarolo , Dane Morgan , Kristin Persson , John Rodgers , Gerbrand Ceder

The design of molecules and materials with tailored properties is challenging, as candidate molecules must satisfy multiple competing requirements that are often difficult to measure or compute. While molecular structures, produced through…

Chemical Physics · Physics 2023-02-07 Julia Westermayr , Joe Gilkes , Rhyan Barrett , Reinhard J. Maurer

Noncentrosymmetric materials play a critical role in many important applications such as laser technology, communication systems,quantum computing, cybersecurity, and etc. However, the experimental discovery of new noncentrosymmetric…

Computational Physics · Physics 2020-06-30 Yuqi Song , Joseph Lindsay , Yong Zhao , Alireza Nasiri , Steph-Yves Louis , Jie Ling , Ming Hu , Jianjun Hu

We are reporting on terahertz generation from organic crystal BNA using a 1.15 to 1.55 um near infrared pump. We observed a very large emission spectrum extending up to 7 THz, compared to 2.5 THz from Ti:Sa pump in previous reports. The…

Materials Science · Physics 2019-07-24 Hang Zhao , Yong Tan , Tong Wu , Gunther Steinfeld , Yan Zhang , Cunlin Zhang , Liangliang Zhang , Mostafa Shalaby

The discovery of novel solid-state materials, such as electrocatalysts, super-ionic conductors, or photovoltaic materials, plays a critical role in addressing various global challenges. It has, for instance, the potential to significantly…

Data-driven methods, in particular machine learning, can help to speed up the discovery of new materials by finding hidden patterns in existing data and using them to identify promising candidate materials. In the case of superconductors,…

Superconductivity · Physics 2022-12-15 Timo Sommer , Roland Willa , Jörg Schmalian , Pascal Friederich

Generative models trained on internet-scale data are capable of generating novel and realistic texts, images, and videos. A natural next question is whether these models can advance science, for example by generating novel stable materials.…

Machine Learning · Computer Science 2024-06-05 Sherry Yang , KwangHwan Cho , Amil Merchant , Pieter Abbeel , Dale Schuurmans , Igor Mordatch , Ekin Dogus Cubuk

High-order harmonic generation (HHG) is a powerful tool for probing electronic structure and ultrafast dynamics in matter. Traditionally studied in atomic and molecular gases, HHG has recently been extended to condensed matter, enabling…

Frequency multiplication of terahertz signals on a solid state platform is highly sought-after for the next generation of high-speed electronics and the creation of frequency combs. Solutions to efficiently generate extreme harmonics (up to…

Optics · Physics 2021-02-25 J. Lim , Y. S. Ang , F. J. G. de Abajó , I. Kaminer , L. K. Ang , L. J. Wong

Machine learning (ML) is becoming increasingly popular for predicting material properties to accelerate materials discovery. Because material properties are strongly affected by its crystal structure, a key issue is converting the crystal…

Materials Science · Physics 2023-10-12 Hirofumi Tsuruta , Yukari Katsura , Masaya Kumagai

Understanding structure-property relationships in materials is fundamental in condensed matter physics and materials science. Over the past few years, machine learning (ML) has emerged as a powerful tool for advancing this understanding and…

We introduce the Computational 2D Materials Database (C2DB), which organises a variety of structural, thermodynamic, elastic, electronic, magnetic, and optical properties of around 1500 two-dimensional materials distributed over more than…

Autonomous materials discovery with desired properties is one of the ultimate goals for materials science, and the current studies have been focusing mostly on high-throughput screening based on density functional theory calculations and…

A thorough in situ characterization of materials at extreme conditions is challenging, and computational tools such as crystal structural search methods in combination with ab initio calculations are widely used to guide experiments by…

Materials Science · Physics 2018-11-14 Maximilian Amsler , Vinay I. Hegde , Steven D. Jacobsen , Chris Wolverton

Crystal structure design is important for the discovery of new highly functional materials because crystal structure strongly influences material properties. Crystal structures are composed of space-filling polyhedra, which affect material…

Materials Science · Physics 2024-02-06 Tomoyasu Yokoyama , Kazuhide Ichikawa , Hisashi Naito

Developing new metal hydrides is a critical step toward efficient hydrogen storage in carbon-neutral energy systems. However, existing materials databases, such as the Materials Project, contain a limited number of well-characterized…

Machine Learning · Computer Science 2026-01-30 Xiyuan Liu , Christian Hacker , Shengnian Wang , Yuhua Duan

We present a universal and rigorous approach to study difference frequency generation in the terahertz domain, keeping the number of degrees of freedom to a minimum, through the definition of a suitable figure of merit. The proposed method…

This paper describes the open Novamag database that has been developed for the design of novel Rare-Earth free/lean permanent magnets. The database software technologies, its friendly graphical user interface, advanced search tools and…