Zobrazeno 1 - 10
of 1 861
pro vyhledávání: '"HU Jianjun"'
Searching for technologically promising crystalline materials with desired thermal transport properties requires an electronic level comprehension of interatomic interactions and chemical intuition to uncover the hidden structure-property relationshi
Externí odkaz:
http://arxiv.org/abs/2410.16066
The accurate prediction of material properties is crucial in a wide range of scientific and engineering disciplines. Machine learning (ML) has advanced the state of the art in this field, enabling scientists to discover novel materials and design mat
Externí odkaz:
http://arxiv.org/abs/2408.09297
Deep learning (DL) models have been widely used in materials property prediction with great success, especially for properties with large datasets. However, the out-of-distribution (OOD) performances of such models are questionable, especially when t
Externí odkaz:
http://arxiv.org/abs/2407.15214
Autor:
Wei, Lai, Omee, Sadman Sadeed, Dong, Rongzhi, Fu, Nihang, Song, Yuqi, Siriwardane, Edirisuriya M. D., Xu, Meiling, Wolverton, Chris, Hu, Jianjun
Crystal structure prediction (CSP) is now increasingly used in discovering novel materials with applications in diverse industries. However, despite decades of developments and significant progress in this area, there lacks a set of well-defined benc
Externí odkaz:
http://arxiv.org/abs/2407.00733
Computational prediction of stable crystal structures has a profound impact on the large-scale discovery of novel functional materials. However, predicting the crystal structure solely from a material's composition or formula is a promising yet chall
Externí odkaz:
http://arxiv.org/abs/2404.04810
Deep learning (DL) models have now been widely used for high-performance material property prediction for properties such as formation energy and band gap. However, training such DL models usually requires a large amount of labeled data, which is usu
Externí odkaz:
http://arxiv.org/abs/2401.05223
Photon counting radiation detectors have become an integral part of medical imaging modalities such as Positron Emission Tomography or Computed Tomography. One of the most promising detectors is the wide bandgap room temperature semiconductor detecto
Externí odkaz:
http://arxiv.org/abs/2311.00682
Due to the vast chemical space, discovering materials with a specific function is challenging. Chemical formulas are obligated to conform to a set of exacting criteria such as charge neutrality, balanced electronegativity, synthesizability, and mecha
Externí odkaz:
http://arxiv.org/abs/2310.00475
Crystal structure prediction using neural network potential and age-fitness Pareto genetic algorithm
While crystal structure prediction (CSP) remains a longstanding challenge, we introduce ParetoCSP, a novel algorithm for CSP, which combines a multi-objective genetic algorithm (MOGA) with a neural network inter-atomic potential (IAP) model to find e
Externí odkaz:
http://arxiv.org/abs/2309.06710
Crystal structure prediction (CSP) is now increasingly used in the discovery of novel materials with applications in diverse industries. However, despite decades of developments, the problem is far from being solved. With the progress of deep learnin
Externí odkaz:
http://arxiv.org/abs/2307.05886