53 citations · 56 across the 9 of their papers we have counts for
9 papers
Accelerating Atom Simulations with Variable-Block Sparse Matrix Library
Zhanghao Zhouyin, Hong Guo
Modern atomistic simulations increasingly employ localized orbitals to represent quantum operators, yielding sparse block matrices whose block shapes vary with chemical species and…
Moiré Phonon Condensation in Magic-Angle Twisted Bilayer Graphene
Zhanghao Zhouyin, Jyun-jie Jiang, Xianghua Kong +1
Twisted bilayer graphene reconstructs from weak breathing corrugation to large common bending near the magic angle, but the origin of this collective crossover has remained unclear…
Deep Learning-Based Quantum Transport Simulations in Two-Dimensional Materials
Jijie Zou, Zhanghao Zhouyin, Qiangqiang Gu +1
Two-dimensional (2D) materials exhibit a wide range of electronic properties that make them promising candidates for next-generation nanoelectronic devices. Accurate prediction of…
Deep Neural Network for Phonon-Assisted Optical Spectra in Semiconductors
Qiangqiang Gu, Shishir Kumar Pandey, Zhanghao Zhouyin
Ab initio based accurate simulation of phonon-assisted optical spectra of semiconductors at finite temperatures remains a formidable challenge, as it requires large supercells for…
Deep Learning Accelerated Quantum Transport Simulations in Nanoelectronics: From Break Junctions to Field-Effect Transistors
Jijie Zou, Zhanghao Zhouyin, Dongying Lin +4
Quantum transport simulations are essential for understanding and designing nanoelectronic devices, yet the long-standing trade-off between accuracy and computational efficiency ha…
Learning local equivariant representations for quantum operators
Zhanghao Zhouyin, Zixi Gan, MingKang Liu +3
Predicting quantum operator matrices such as Hamiltonian, overlap, and density matrices in the density functional theory (DFT) framework is crucial for material science. Current me…
Pitfalls of Exchange-Correlation Functionals in Descriptions of Magnetism: Cautionary Tale of the FeRh Alloy
Shishir Kumar Pandey, Saikat Debnath, Zhanghao Zhouyina +1
The magnetic ground state of FeRh is highly sensitive towards the lattice constant. This, in addition to partially filled d-shells of Fe and Rh, posed a significant challenge for D…
Deep learning tight-binding approach for large-scale electronic simulations at finite temperatures with accuracy
Qiangqiang Gu, Zhanghao Zhouyin, Shishir Kumar Pandey +3
Simulating electronic behavior in materials and devices with realistic large system sizes remains a formidable task within the framework due to its computational inte…
Understanding Neural Networks with Logarithm Determinant Entropy Estimator
Zhanghao Zhouyin, Ding Liu
Understanding the informative behaviour of deep neural networks is challenged by misused estimators and the complexity of network structure, which leads to inconsistent observation…