Shyue Ping Ong

Identifiers

• name variant Shyue Ping Ong 0.60 · backfill

Papers (35)

1. Robust Training of Machine Learning Interatomic Potentials with Dimensionality Reduction and Stratified Sampling cond-mat.mtrl-sci · 2023 · author #5
2. Machine Learning Moment Tensor Potential for Modelling Dislocation and Fracture in L1$_0$-TiAl and D0$_{19}$-Ti$_3$Al Alloys cond-mat.mtrl-sci · 2023 · author #10
3. Compositionally Complex Perovskite Oxides as a New Class of Li-Ion Solid Electrolytes cond-mat.mtrl-sci · 2022 · author #11
4. The Intercalation Chemistry of the Disordered RockSalt Li3V2O5 Anode from Cluster Expansions and Machine Learning Interatomic Potentials cond-mat.mtrl-sci · 2022 · author #3
5. Synthetic control of structure and conduction properties in Na-Y-Zr-Cl solid electrolytes cond-mat.mtrl-sci · 2022 · author #11
6. Quantum materials for energy-efficient neuromorphic computing cs.ET · 2022 · author #14
7. Atomic-scale origin of the low grain-boundary resistance in perovskite solid electrolytes cond-mat.mtrl-sci · 2022 · author #13
8. Multi-scale Investigation of Chemical Short-Range Order and Dislocation Glide in the MoNbTi and TaNbTi Refractory Multi-Principal Element Alloys cond-mat.mtrl-sci · 2022 · author #9
9. A Universal Graph Deep Learning Interatomic Potential for the Periodic Table cond-mat.mtrl-sci · 2022 · author #2
10. A Universal Machine Learning Model for Elemental Grain Boundary Energies cond-mat.mtrl-sci · 2022 · author #4
11. Recent Advances and Applications of Deep Learning Methods in Materials Science cond-mat.mtrl-sci · 2021 · author #12
12. Proton distribution visualization in perovskite nickelate devices utilizing nanofocused X-rays cond-mat.mtrl-sci · 2021 · author #17
13. Emergence of near-boundary segregation zones in face-centered cubic multi-principal element alloys cond-mat.mtrl-sci · 2021 · author #7
14. Accelerating Materials Discovery with Bayesian Optimization and Graph Deep Learning cond-mat.mtrl-sci · 2021 · author #7
15. Bridging the Gap Between Simulated and Experimental Ionic Conductivities in Lithium Superionic Conductors cond-mat.mtrl-sci · 2021 · author #8
16. AtomSets -- A Hierarchical Transfer Learning Framework for Small and Large Materials Datasets cond-mat.mtrl-sci · 2021 · author #2
17. Learning Properties of Ordered and Disordered Materials from Multi-fidelity Data cond-mat.mtrl-sci · 2020 · author #5
18. Genetic Algorithm-Guided Deep Learning of Grain Boundary Diagrams: Addressing the Challenge of Five Degrees of Freedom cond-mat.mtrl-sci · 2020 · author #4
19. Complex Strengthening Mechanisms in the NbMoTaW Multi-Principal Element Alloy cond-mat.mtrl-sci · 2019 · author #5
20. Random Forest Models for Accurate Identification of Coordination Environments from X-ray Absorption Near-Edge Structure cond-mat.mtrl-sci · 2019 · author #4
21. Unified Theory of Thermal Quenching in Inorganic Phosphors cond-mat.mtrl-sci · 2019 · author #7
22. Oxygen deficiency and migration mediated electric polarization in Fe,Co-substituted SrTiO$_{3-\delta}$ cond-mat.mtrl-sci · 2019 · author #2
23. Grain Boundary Properties of Elemental Metals cond-mat.mtrl-sci · 2019 · author #8
24. Oxygen-vacancy tuning of magnetism in SrTi$_{0.75}$Fe$_{0.125}$Co$_{0.125}$O$_{3-\delta}$ perovskite cond-mat.mtrl-sci · 2019 · author #2
25. A Performance and Cost Assessment of Machine Learning Interatomic Potentials physics.comp-ph · 2019 · author #11
26. Anisotropic work function of elemental crystals cond-mat.mtrl-sci · 2019 · author #6
27. 2DMatPedia: An open computational database of two-dimensional materials from top-down and bottom-up approaches cond-mat.mtrl-sci · 2019 · author #5
28. An Electrostatic Spectral Neighbor Analysis Potential (eSNAP) for Lithium Nitride cond-mat.mtrl-sci · 2019 · author #4
29. Graph Networks as a Universal Machine Learning Framework for Molecules and Crystals cond-mat.mtrl-sci · 2018 · author #5
30. Quantum-Accurate Spectral Neighbor Analysis Potential Models for Ni-Mo Binary Alloys and FCC Metals cond-mat.mtrl-sci · 2018 · author #6
31. Deep Neural Networks for Accurate Predictions of Garnet Stability cond-mat.mtrl-sci · 2017 · author #5
32. Predicting the Volumes of Crystals cond-mat.mtrl-sci · 2017 · author #5
33. Automated Generation and Ensemble-Learned Matching of X-ray Absorption Spectra cond-mat.mtrl-sci · 2017 · author #12
34. Accurate Force Field for Molybdenum by Machine Learning Large Materials Data physics.comp-ph · 2017 · author #6
35. Electronic Structure Descriptor for Discovery of Narrow-Band Red-Emitting Phosphors cond-mat.mtrl-sci · 2016 · author #4

Mentions

• 2307.13710 #5 · arxiv_oai · confidence 0.70 Shyue Ping Ong
• 2203.03767 #9 · arxiv_oai · confidence 0.70 Shyue Ping Ong
• 2305.11825 #10 · arxiv_oai · confidence 0.70 Shyue Ping Ong
• 2204.00091 #13 · arxiv_oai · confidence 0.70 Shyue Ping Ong
• 2212.13451 #11 · arxiv_oai · confidence 0.70 Shyue Ping Ong
• 2202.02450 #2 · arxiv_oai · confidence 0.70 Shyue Ping Ong
• 1910.00176 #2 · arxiv_oai · confidence 0.70 Shyue Ping Ong
• 2208.14420 #3 · arxiv_oai · confidence 0.70 Shyue Ping Ong
• 2208.07823 #11 · arxiv_oai · confidence 0.70 Shyue Ping Ong
• 2204.01832 #14 · arxiv_oai · confidence 0.70 Shyue Ping Ong
• 2110.14820 #12 · arxiv_oai · confidence 0.70 Shyue Ping Ong
• 2201.11991 #4 · arxiv_oai · confidence 0.70 Shyue Ping Ong
• 2102.02401 #2 · arxiv_oai · confidence 0.70 Shyue Ping Ong
• 2106.09492 #7 · arxiv_oai · confidence 0.70 Shyue Ping Ong
• 2108.06439 #17 · arxiv_oai · confidence 0.70 Shyue Ping Ong
• 2102.08413 #8 · arxiv_oai · confidence 0.70 Shyue Ping Ong
• 2104.10242 #7 · arxiv_oai · confidence 0.70 Shyue Ping Ong
• 2005.04338 #5 · arxiv_oai · confidence 0.70 Shyue Ping Ong
• 1912.01789 #5 · arxiv_oai · confidence 0.70 Shyue Ping Ong
• 1910.12420 #7 · arxiv_oai · confidence 0.70 Shyue Ping Ong
• 2002.10632 #4 · arxiv_oai · confidence 0.70 Shyue Ping Ong
• 1906.08888 #11 · arxiv_oai · confidence 0.70 Shyue Ping Ong
• 1911.01358 #4 · arxiv_oai · confidence 0.70 Shyue Ping Ong
• 1907.05961 #2 · arxiv_oai · confidence 0.70 Shyue Ping Ong
• 1901.09487 #5 · arxiv_oai · confidence 0.70 Shyue Ping Ong
• 1907.08905 #8 · arxiv_oai · confidence 0.70 Shyue Ping Ong
• 1902.07811 #6 · arxiv_oai · confidence 0.70 Shyue Ping Ong
• 1901.08749 #4 · arxiv_oai · confidence 0.70 Shyue Ping Ong
• 1812.05055 #5 · arxiv_oai · confidence 0.70 Shyue Ping Ong
• 1712.01908 #5 · arxiv_oai · confidence 0.70 Shyue Ping Ong
• 1806.04777 #6 · arxiv_oai · confidence 0.70 Shyue Ping Ong
• 1712.01321 #5 · arxiv_oai · confidence 0.70 Shyue Ping Ong
• 1711.02227 #12 · arxiv_oai · confidence 0.70 Shyue Ping Ong
• 1706.09122 #6 · arxiv_oai · confidence 0.70 Shyue Ping Ong
• 1604.04581 #4 · arxiv_oai · confidence 0.70 Shyue Ping Ong

Frequent Coauthors

• Chi Chen 21 shared papers
• Yunxing Zuo 9 shared papers
• Jian Luo 6 shared papers
• Ji Qi 6 shared papers
• Xiang-Guo Li 6 shared papers
• Hui Zheng 5 shared papers
• Weike Ye 5 shared papers
• Iek-Heng Chu 4 shared papers
• Richard Tran 4 shared papers
• Xiangguo Li 4 shared papers
• Zhi Deng 4 shared papers
• Chen Zheng 3 shared papers
• Hanmei Tang 3 shared papers
• Xiaoqing Pan 3 shared papers
• Yiming Chen 3 shared papers
• Zhenbin Wang 3 shared papers
• Alex Frano 2 shared papers
• Anubhav Jain 2 shared papers
• C. A. Ross 2 shared papers
• Chongze Hu 2 shared papers