Although the sensitivity of THz spectra to the crystal form of the sample being analysed makes it an ideal tool for differentiating polymorphic forms of crystalline materials, the lack of adequate knowledge about the THz response to various materials often results in misinterpretations. The inclusion of structural information in THz spectral databases of crystalline substances is therefore suggested.
In this concept paper, the development of strategies for the integration of first-principles methods with crystallographic database mining for the discovery and design of novel ferroelectric materials is discussed, drawing on the results and experience derived from exploratory investigations on three different systems: (1) the double perovskite Sr(Sb$_{1/2}$Mn$_{1/2}$)O$_3$ as a candidate semiconducting ferroelectric; (2) polar derivatives of schafarzikite $M$Sb$_2$O$_4$; and (3) ferroelectric semiconductors with formula $M_2$P$_2$(S,Se)$_6$. A variety of avenues for further research and inves…
We show clear experimental evidence of co-operative terahertz (THz) dynamics observed below 3 THz (~100 cm-1), for a low-symmetry Zr-based metal-organic framework (MOF) structure, termed MIL-140A [ZrO(O2C-C6H4-CO2)]. Utilizing a combination of high-resolution inelastic neutron scattering and synchrotron radiation far-infrared spectroscopy, we measured low-energy vibrations originating from the hindered rotations of organic linkers, whose energy barriers and detailed dynamics have been elucidated via ab initio density functional theory (DFT) calculations. For completeness, we obtained Raman spe…
Hexaferrite materials are highly demanded to develop and manufacture electronic devices operating at radio- and microwave frequencies. In the light of the prospects for their use in the forthcoming terahertz electronics, here, we present our results on the terahertz and infrared dielectric response of a typical representative of hexaferrites family, lead-substituted M-type barium hexaferrite doped with aluminum, Ba0.2Pb0.8AlxFe12-xO19, x(Al)=0.0, 3.0, and 3.3. We studied uniquely large and high-quality single crystals of the. Systematic and detailed investigations of the dependences of teraher…
An easily available resource of common crystal structures is essential for researchers, teachers, and students. For many years this was provided by the U.S. Naval Research Laboratory's $Crystal\ Lattice\ Structures$ web page, which contained nearly 300 crystal structures, including a majority of those which were given $Strukturbericht$ designations. This article presents the updated version of the database, now including 288 standardized structures in 92 space groups. Similar to what was available on the web page before, we present a complete description of each structure, including the formul…
A simplified polycrystalline model (the so-called RL model) is proposed to simulate the anisotropic viscoplastic behavior of metallic materials. A generic method is presented that makes it possible to build a simplified anisotropic material texture, based on the principal features of the pole figures. The method is applied to a recrystallized zirconium alloy, used as clad material in the fuel rods of nuclear power plants. An important database consisting in mechanical tests performed on Zircaloy tubes is collected. Only a small number of tests (pure tension, pure shear) are used to identify th…
We demonstrate a data mining approach to discover and develop new organic nonlinear optical crystals that produce intense pulses of terahertz radiation. We mine the Cambridge Structural Database for non-centrosymmetric materials and use this structural data in tandem with density functional theory calculations to predict new materials that efficiently generate terahertz radiation. This enables us to (in a relatively short time) discover, synthesize, and grow large, high-quality crystals of four promising materials and characterize them for intense terahertz generation. In a direct comparison t…
Crystal structure prototype data have become a useful source of information for materials discovery in the fields of crystallography, chemistry, physics, and materials science. This work reports the development of a robust and efficient method for assessing the similarity of structures on the basis of their interatomic distances. Using this method, we proposed a simple and unambiguous definition of crystal structure prototype based on hierarchical clustering theory, and constructed the Crystal Structure Prototype Database (CSPD) by filtering the known crystallographic structures in a database.…
Recognition of structure prototypes from tremendous known inorganic crystal structures has been an important subject beneficial for material science research and new materials design. The existing databases of inorganic crystal structure prototypes were mostly constructed by classifying materials in terms of the crystallographic space group information. Herein, we employed a distinct strategy to construct the inorganic crystal structure prototype database, relying on the classification of materials in terms of local atomic environments (LAE) accompanied by unsupervised machine learning method.…
In computational material design, ionic radius is one of the most important physical parameters used to predict material properties. Motivated by the progress in computational materials science and material informatics, we extend the renowned Shannon's table from 475 ions to 987 ions. Accordingly, a rigorous Machine Learning (ML) approach is employed to extend the ionic radii table using all possible combinations of Oxidation States (OS) and Coordination Numbers (CN) available in crystallographic repositories. An ionic-radius regression model for Shannon's database is developed as a function o…
The influence of the microstructure of a polycrystalline material on its macroscopic deformation response is still one of the major problems in materials engineering. For materials characterized by elastic-plastic deformation responses, predictive computational models to characterize crystal-plasticity (CP) have been developed. However, due to their large demand of computational resources, CP simulations cannot be straightforwardly implemented in hierarchical computational models such as FE$^{2}$. This bottleneck intensifies the need for the development of macroscopic simulation tools that can…
Singapore-MIT Alliance for Research and Technology（新加坡-麻省理工学院研究与技术联盟）；National University of Singapore（新加坡国立大学）；Korea Advanced Institute of Science and Technology（韩国科学技术院）；Massachusetts Institute of Technology（麻省理工学院）；Okinawa Institute of Science and Technology Graduate University（冲绳科学技术大学院大学）；Agency for Science, Technology and Research（新加坡科技研究局）；Nanyang Technological University（南洋理工大学）；Shanghai University（上海大学）；Microsoft AI for Good（微软人工智能公益计划）；Toyota Research Institute（丰田研究院）；Tsinghua University（清华大学）
Realizing general inverse design could greatly accelerate the discovery of new materials with user-defined properties. However, state-of-the-art generative models tend to be limited to a specific composition or crystal structure. Herein, we present a framework capable of general inverse design (not limited to a given set of elements or crystal structures), featuring a generalized invertible representation that encodes crystals in both real and reciprocal space, and a property-structured latent space from a variational autoencoder (VAE). In three design cases, the framework generates 142 new cr…
A New Workflow for Materials Discovery Bridging the Gap Between Experimental Databases and Graph Neural Networks
Department of Physics, University at Buffalo, State University of New York, Buffalo, NY；Department of Computer Science \& Engineering, University at Buffalo, State University of New York, Buffalo, NY；Institute for Artificial Intelligence；Data Science, University at Buffalo, State University of New York, Buffalo, NY
Metal-insulator transition (MIT) compounds are materials that may exhibit insulating or metallic behavior, depending on the physical conditions, and are of immense fundamental interest owing to their potential applications in emerging microelectronics. There is a dearth of thermally-driven MIT materials, however, which makes delineating these compounds from those that are exclusively insulating or metallic challenging. Here we report a material database comprising temperature-controlled MITs (and metals and insulators with similar chemical composition and stoichiometries to the MIT compounds) …
The accelerated growth rate of repository entries in crystallographic databases makes it arduous to identify and classify their prototype structures. The open-source AFLOW-XtalFinder package was developed to solve this problem. It symbolically maps structures into standard designations following the AFLOW Prototype Encyclopedia and calculates the internal degrees of freedom consistent with the International Tables for Crystallography. To ensure uniqueness, structures are analyzed and compared via symmetry, local atomic geometries, and crystal mapping techniques, simultaneously grouping them by…
Determination of the symmetry profile of structures is a persistent challenge in materials science. Results often vary amongst standard packages, hindering autonomous materials development by requiring continuous user attention and educated guesses. Here, we present a robust procedure for evaluating the complete suite of symmetry properties, featuring various representations for the point-, factor-, space groups, site symmetries, and Wyckoff positions. The protocol determines a system-specific mapping tolerance that yields symmetry operations entirely commensurate with fundamental crystallogra…
SymmCD: Symmetry-Preserving Crystal Generation with Diffusion Models
McGill University（麦吉尔大学）；Mila；École Polytechnique Fédérale de Lausanne（洛桑联邦理工学院）；University of North Carolina at Charlotte（北卡罗来纳大学夏洛特分校）；Intel Labs（英特尔实验室）
Score-based diffusion models for accurate crystal-structure inpainting and reconstruction of hydrogen positions
Paul Scherrer Institute（保罗谢勒研究所）；Università di Parma（帕尔马大学）；INFN - Sezione di Milano-Bicocca（意大利国家核物理研究所米兰-比可卡分部）；Università degli Studi di Modena e Reggio Emilia（摩德纳和雷焦艾米利亚大学）；Institute Nanoscience - CNR-NANO, Center S3（纳米科学研究所-CNR-NANO，S3中心）
OBELiX: A Curated Dataset of Crystal Structures and Experimentally Measured Ionic Conductivities for Lithium Solid-State Electrolytes
Mila；McGill University（麦吉尔大学）；University of Ottawa（Ottawa大学）；Technical University of Kenya（肯尼亚技术大学）；National Research Council Canada（加拿大国家研究委员会）；Université de Montréal（蒙特利尔大学）
