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Tien-Lam Pham

Machine learning reveals orbital interaction in materials
2017 · Tien Lam Pham, Hiori Kino, et al. · Science and Technology of Advanced Materials · 129
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Learning structure-property relationship in crystalline materials: A study of lanthanide–transition metal alloys
2018 · Tien-Lam Pham, Nguyen-Duong Nguyen, et al. · The Journal of Chemical Physics · 39
Important Descriptors and Descriptor Groups of Curie Temperatures of Rare-earth Transition-metal Binary Alloys
2018 · Hieu Chi Dam, Viet Cuong Nguyen, et al. · Journal of the Physical Society of Japan · 34
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Novel mixture model for the representation of potential energy surfaces
2016 · Tien Lam Pham, Hiori Kino, et al. · The Journal of Chemical Physics · 24
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A study on carbon nanotube titanium dioxide hybrids: experiment and calculation
2014 · Minh Thuy Nguyen, Cao Khang Nguyen, et al. · Advances in Natural Sciences Nanoscience and Nanotechnology · 24
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First principles study of the physisorption of hydrogen molecule on graphene and carbon nanotube surfaces adhered by Pt atom
2010 · Tien Lam Pham, Phan Viet Dung, et al. · Computational Materials Science · 20
Data mining for materials design: A computational study of single molecule magnet
2014 · Hieu Chi Dam, Tien Lam Pham, et al. · The Journal of Chemical Physics · 17
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Explainable machine learning for materials discovery: predicting the potentially formable Nd–Fe–B crystal structures and extracting the structure–stability relationship
2020 · Tien-Lam Pham, Duong-Nguyen Nguyen, et al. · IUCrJ · 16
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A regression-based model evaluation of the Curie temperature of transition-metal rare-earth compounds
2019 · Duong-Nguyen Nguyen, Tien-Lam Pham, et al. · Journal of Physics Conference Series · 16
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Ensemble learning reveals dissimilarity between rare-earth transition-metal binary alloys with respect to the Curie temperature
2019 · Duong-Nguyen Nguyen, Tien-Lam Pham, et al. · Journal of Physics Materials · 13
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A regression-based feature selection study of the Curie temperature of transition-metal rare-earth compounds: prediction and understanding
2017 · Dam, Hieu Chi, Nguyen, Viet Cuong, et al. · arXiv (Cornell University) · 8
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Learnable features for predicting properties of metal-organic frameworks with deep neural networks
2024 · Van-Quyen Nguyen, Phuoc-Anh Le, et al. · Cell Reports Physical Science · 6
Committee machine that votes for similarity between materials
2018 · Duong-Nguyen Nguyen, Tien-Lam Pham, et al. · IUCrJ · 5
Computationally Predicted Electronic Properties and Energetics of Native Defects in Cubic Boron Nitride
2025 · Ngoc Linh Nguyen, Hung The Dang, et al. · Journal of Electronic Materials · 4
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Application of materials informatics on crystalline materials for two-body terms approximation
2019 · Van-Doan Nguyen, Tien-Lam Pham, et al. · Computational Materials Science · 4
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Learning hidden chemistry with deep neural networks
2021 · Tien-Cuong Nguyen, Van-Quyen Nguyen, et al. · Computational Materials Science · 2
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Node-aware convolution in Graph Neural Networks for Predicting molecular properties
2020 · Linh Le Pham Van, Quang Bach Tran, et al. · International Conference on Knowledge and Systems Engineering/Proceedings · 2
First-principles study of hydrogen-enhanced phosphorus diffusion in silicon
2016 · Le The Anh, Nguyen Tien Cuong, et al. · Journal of Applied Physics · 2
Prediction of thermodynamic properties oflanthanide/transition metal alloys by deep learning
2024 · Tien Lam Pham, Tien Cuong Nguyen, et al. · Ministry of Science and Technology Vietnam · 1
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Pairwise interactions for potential energy surfaces and atomic forces using deep neural networks
2022 · Van-Quyen Nguyen, Viet-Cuong Nguyen, et al. · Computational Materials Science · 1
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Learning Materials Properties from Orbital Interactions
2019 · Tien-Lam Pham, Tran-Thai Dang, et al. · Journal of Physics Conference Series · 1
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Measuring the Similarity between Materials with an Emphasis on the Materials Distinctiveness
2019 · Dang, Tran-Thai, Pham, Tien-Lam, et al. · arXiv (Cornell University) · 1
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Variational Quantum Circuit Parameterization of SchNet: A Simulator-Based Feasibility Study for Conservative Molecular Force Fields
2026 · Nguyen, Hoang - Anh, Dinh, Nhu - Duc, et al. · arXiv (Cornell University)
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Data-driven discovery and first-principles design of novel cathode materials for sodium-ion batteries
2026 · Huu Doanh Nguyen, Minh Do Dang, et al. · Energy and AI
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In Silico Engineering of Defect Spins in Silicon Carbide for Solid-State Hybrid Quantum Technologies
2026 · Dang Huy Ngo, Huyen-Trang T. Le, et al. · Journal of Physics Conference Series
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Works count: 30
Citation count: 369
H-index: 10
I10-index: 10
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