Results 61 to 70 of about 477,351 (168)

The crystal structures of four dimethoxybenzaldehyde isomers

Acta Crystallographica Section E: Crystallographic Communications, 2019
The crystal structures of four dimethoxybenzaldehyde (C9H10O3) isomers, namely the 2,3-, 2,4-, 2,5- and 3,5- isomers, are reported and compared to the previously reported crystal structures of 3,4-dimethoxybenzaldehyde and 2,6-dimethoxybenzaldehyde.
Sander J. T. Brugman, Anthonius H. J. Engwerda, Emma Kalkman, Erik de Ronde, Paul Tinnemans, Elias Vlieg   +5 more
doaj   +1 more source

Machine learning assisted prediction of organic salt structure properties

npj Computational Materials
We demonstrate a machine learning-based approach which predicts the properties of crystal structures following relaxation based on the unrelaxed structure. Use of crystal graph singular values reduces the number of features required to describe a crystal
Ethan P. Shapera, Dejan-Krešimir Bučar, Rohit P. Prasankumar, Christoph Heil   +3 more
doaj   +1 more source

Temperature Tunability of Dielectric/ Liquid Crystal / Dielectric Photonic Crystal Structures [PDF]

Journal of Optoelectronical Nanostructures, 2017
Recently, photonic crystals doped with liquid crystal (LC) material havegained much research interest. In this article new ternary one-dimensional photoniccrystal introduced and studied.
Ali Vahedi, Tahere Froutan fard kobar olia   +1 more
doaj  

Diffusion probabilistic models enhance variational autoencoder for crystal structure generative modeling

Scientific Reports
The crystal diffusion variational autoencoder (CDVAE) is a machine learning model that leverages score matching to generate realistic crystal structures that preserve crystal symmetry.
Teerachote Pakornchote, Natthaphon Choomphon-anomakhun, Sorrjit Arrerut, Chayanon Atthapak, Sakarn Khamkaeo, Thiparat Chotibut, Thiti Bovornratanaraks   +6 more
doaj   +1 more source

Shotgun crystal structure prediction using machine-learned formation energies

npj Computational Materials
Stable or metastable crystal structures of assembled atoms can be predicted by finding the global or local minima of the energy surface within a broad space of atomic configurations. Generally, this requires repeated first-principles energy calculations,
Chang Liu, Hiromasa Tamaki, Tomoyasu Yokoyama, Kensuke Wakasugi, Satoshi Yotsuhashi, Minoru Kusaba, Artem R. Oganov, Ryo Yoshida   +7 more
doaj   +1 more source

Bridging text and crystal structures: literature-driven contrastive learning for materials science

Machine Learning: Science and Technology
Understanding structure–property relationships is an essential yet challenging aspect of materials discovery and development. To facilitate this process, recent studies in materials informatics have sought latent embedding spaces of crystal structures to
Yuta Suzuki, Tatsunori Taniai, Ryo Igarashi, Kotaro Saito, Naoya Chiba, Yoshitaka Ushiku, Kanta Ono   +6 more
doaj   +1 more source

Crystal structure generation with autoregressive large language modeling

Nature Communications
The generation of plausible crystal structures is often the first step in predicting the structure and properties of a material from its chemical composition.
Luis M. Antunes, Keith T. Butler, Ricardo Grau-Crespo   +2 more
doaj   +1 more source

Improved machine learning framework for prediction of phases and crystal structures of high entropy alloys

Journal of Alloys and Metallurgical Systems
High-entropy alloys (HEAs) are gaining popularity because of their remarkable properties controlled by phases and crystal structures. In addition to that, in the field of material informatics, machine learning (ML) techniques have gained considerable ...
Debsundar Dey, Suchandan Das, Anik Pal, Santanu Dey, Chandan Kumar Raul, Pritam Mandal, Arghya Chatterjee, Soumya Chatterjee, Manojit Ghosh   +8 more
doaj   +1 more source

Ferroelectricity-driven strain-mediated magnetoelectric coupling in two-dimensional multiferroic heterostructure

Nature Communications
In the post-Moore era, CMOS technology faces challenges in storage and power consumption. Two-dimensional van der Waals ferromagnets, with their atomically sharp interfaces, enable heterostructure with ferroelectric materials.
Chuanyang Cai, Yao Wen, Shiheng Liang, Lei Yin, Ruiqing Cheng, Hao Wang, Xiaoqiang Feng, Liang Liu, Jun He   +8 more
doaj   +1 more source

Crystal engineering: structure, property and beyond

IUCrJ, 2017
Gautam R. Desiraju
doaj   +1 more source