Pairwise interactions for potential energy surfaces and atomic forces using deep neural networks von Nguyen, Van-Quyen, Nguyen, Viet-Cuong, Nguyen, Tien-Cuong, Nguyen, Nguyen-Xuan-Vu, Pham, Tien-Lam

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Application of materials informatics on crystalline materials for two-body terms approximation von Nguyen, Van-Doan, Pham, Tien-Lam, Dam, Hieu-Chi

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Machine learning reveals orbital interaction in materials von Lam Pham, Tien, Kino, Hiori, Terakura, Kiyoyuki, Miyake, Takashi, Tsuda, Koji, Takigawa, Ichigaku, Chi Dam, Hieu

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Transition of electron transport process in Be-doped low-temperature-grown GaAs layer von Mohamed, Mohd Ambri, Tien Lam, Pham, Otsuka, N.

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Cooperative transition of electronic states of antisite As defects in Be-doped low-temperature-grown GaAs layers von Ambri Mohamed, Mohd, Tien Lam, Pham, Bae, K. W., Otsuka, N.

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Corrigendum: Ensemble learning reveals dissimilarity between rare-earth transition metal binary alloys with respect to the Curie temperature (2019 J. Phys. Mater. 2 034009) von Nguyen, Duong-Nguyen, Pham, Tien-Lam, Nguyen, Viet-Cuong, Kino, Hiori, Miyake, Takashi, Dam, Hieu-Chi

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Learning structure-property relationship in crystalline materials: A study of lanthanide–transition metal alloys von Pham, Tien-Lam, Nguyen, Nguyen-Duong, Nguyen, Van-Doan, Kino, Hiori, Miyake, Takashi, Dam, Hieu-Chi

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First principles study of the physisorption of hydrogen molecule on graphene and carbon nanotube surfaces adhered by Pt atom von Pham, Tien Lam, Dung, Phan Viet, Sugiyama, Ayumu, Duc, Nguyen Dinh, Shimoda, Tatsuya, Fujiwara, Akihiko, Chi, Dam Hieu

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A regression-based model evaluation of the Curie temperature of transition-metal rare-earth compounds von Nguyen, Duong-Nguyen, Pham, Tien-Lam, Nguyen, Viet-Cuong, Nguyen, Anh-Tuan, Kino, Hiori, Miyake, Takashi, Dam, Hieu-Chi

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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 von Pham, Tien-Lam, Nguyen, Duong-Nguyen, Ha, Minh-Quyet, Kino, Hiori, Miyake, Takashi, Dam, Hieu-Chi

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Non-equilibrium critical point in Be-doped low-temperature-grown GaAs von Ambri Mohamed, Mohd, Tien Lam, Pham, Otsuka, N.

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Learning Materials Properties from Orbital Interactions von Pham, Tien-Lam, Dang, Tran-Thai, Nguyen, Van-Doan, Kino, Hiori, Miyake, Takashi, Dam, Hieu-Chi

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Committee machine that votes for similarity between materials von Nguyen, Duong-Nguyen, Pham, Tien-Lam, Nguyen, Viet-Cuong, Ho, Tuan-Dung, Tran, Truyen, Takahashi, Keisuke, Dam, Hieu-Chi

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Ensemble learning reveals dissimilarity between rare-earth transition-metal binary alloys with respect to the Curie temperature von Nguyen, Duong-Nguyen, Pham, Tien-Lam, Nguyen, Viet-Cuong, Kino, Hiori, Miyake, Takashi, Dam, Hieu-Chi

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Data mining for materials design: a computational study of single molecule magnet von Dam, Hieu Chi, Pham, Tien Lam, Ho, Tu Bao, Nguyen, Anh Tuan, Nguyen, Viet Cuong

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A study on carbon nanotube titanium dioxide hybrids: experiment and calculation von Nguyen, Minh Thuy, Nguyen, Cao Khang, Phuong Vu, Thi Mai, Duong, Quoc Van, Pham, Tien Lam, Nguyen, Tien Cuong

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Important Descriptors and Descriptor Groups of Curie Temperatures of Rare-earth Transition-metal Binary Alloys von Dam, Hieu Chi, Nguyen, Viet Cuong, Pham, Tien Lam, Nguyen, Anh Tuan, Terakura, Kiyoyuki, Miyake, Takashi, Kino, Hiori

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Transformer vibration and noise monitoring system using internet of things von Thinh, Tran Ngoc Huy, Lam, Pham Duc, Tran, Huy Q., Tien, Lam Hoang Cat, Thai, Pham Huu

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Novel mixture model for the representation of potential energy surfaces von Pham, Tien Lam, Kino, Hiori, Terakura, Kiyoyuki, Miyake, Takashi, Dam, Hieu Chi

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Learning hidden chemistry with deep neural networks von Nguyen, Tien-Cuong, Nguyen, Van-Quyen, Ngo, Van-Linh, Than, Quang-Khoat, Pham, Tien-Lam

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