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SCEJ 91st Annual Meeting
Mar. 17 (Tue) - 19 (Thu), 2026
Yoshida Campus, Kyoto University
Japanese page
$B:G=*99?7F|;~!'(B2026-10-03 18:44:01
 Popular Keywords inthis topics | Keywords | Count | |
|---|---|---|---|
| Machine Learning | 3 |  | |
| neural network | 2 | | |
| High entropy alloys | 1 | | |
| Acknowledgement number | Title/Authors | Keywords | Style |
|---|---|---|---|
| 29 | Extending Flory-Huggins Model for the dispersion of surface modified CeO2 nanoparticle via data-driven modeling of solvent activity coefficient | data-driven modeling Flory-Huggins model nanoparticle dispersion | P |
| 137 | Automated classification of organic reaction mechanisms in heterogeneous real-world data via transformers and domain generalization | Machine learning Neural Network Encoder | O |
| 161 | Optimization of temperature ramp profiles in ceramic firing process: GNN vs. PINN | surrogate model neural network optimization | O |
| 183 | Machine Learning Interatomic Potentials Reveal Surface Proton Diffusion on Perovskite Oxide | Machine Learning Interatomic Potential Proton Diffusion Surface Conduction | P |
| 200 | In-line spectroscopic monitoring of phase structure for polymer processing using a light scattering model | In-line analysis polymer blends phase structure | O |
| 349 | Topological Phase Transitions in Non-Centrosymmetric LiBaBi under Strain | DFT Topological insulator Strain-induced band inversion | P |
| 352 | Improving Reaction Prediction Accuracy Using Machine Learning and Reaction Networks | machine learning chemical reaction network reaction pathway prediction | P |
| 355 | Atomistic Studies of$B!R(B110$B!S(B Symmetric Tilt Grain Boundaries in Al0.5CoCr0.5FeNi High-Entropy Alloys | Molecular dynamics High entropy alloys Grain boundaries | P |
| 506 | Analysis of Structural and Electronic Factors Influencing the Activity and Electrical Conductivity of Non-Precious Metal Oxide Catalysts for Water Electrolysis | Anion Exchange Membrane Water Electrolysis Electrochemical Catalyst Materials Informatics | P |
| 627 | Development of a Machine Learning Model for Species-Specific MIC Prediction of Antimicrobial Peptides | Machine Learning Antimicrobial Peptides Minimum Inhibitory Concentration (MIC) | P |
Organizing Committee of SCEJ 91st Annual Meeting (2026)
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