PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
May 10, 2026Nano Letters0 citations

Learning Piezoelectric Tensors through Strain-Conditioned Polarization Clusters

View Full Paper
CYChunlin YuCLChao LiangJLJunhao Liang

Key Points

  • This research aims to improve the learning of piezoelectric tensors and enhance materials discovery.
  • Developed a model based on strain-conditioned polarization clusters.
  • Compared performance against EATGNN and CGCNN.
  • Conducted large-scale screening of unlabeled materials.
  • The model outperformed EATGNN by 32.5% and CGCNN by 52.6%.
  • Successfully identified candidates with a strong piezoelectric response.

Abstract

, outperforming EATGNN and CGCNN by 32.5% and 52.6%, respectively. The model also supports large-scale screening of unlabeled materials and identifies candidates with strong piezoelectric response, providing a physically grounded route for tensor learning and materials discovery.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Yu et al. (2026) studied this question.

synapsesocial.com/papers/6a00210dc8f74e3340f9bd9ahttps://doi.org/10.1021/acs.nanolett.6c01295
Ask AI
Helpful
Bookmark
Share
View Full Paper