Zobrazeno 1 - 10
of 110
pro vyhledávání: '"Kei Terayama"'
Autor:
Ryo Tamura, Haruhiko Morito, Guillaume Deffrennes, Masanobu Naito, Yoshitaro Nose, Taichi Abe, Kei Terayama
Publikováno v:
Communications Materials, Vol 5, Iss 1, Pp 1-11 (2024)
Abstract Phase diagrams provide considerable information that is vital for materials exploration. However, the determination of multidimensional phase diagrams typically requires a significant investment of time, cost, and human resources owing to th
Externí odkaz:
https://doaj.org/article/b991e81cdccb4c4caf29c6b233f61afe
Publikováno v:
BMC Bioinformatics, Vol 25, Iss 1, Pp 1-14 (2024)
Abstract Background Liquid–liquid phase separation (LLPS) by biomolecules plays a central role in various biological phenomena and has garnered significant attention. The behavior of LLPS is strongly influenced by the characteristics of RNAs and en
Externí odkaz:
https://doaj.org/article/8dd62faed4844fe288b118ef60b843ca
Publikováno v:
Royal Society Open Science, Vol 11, Iss 6 (2024)
The seafloor is inhabited by a large number of benthic invertebrates, and their importance in mediating carbon mineralization and biogeochemical cycles is recognized. However, the majority of fauna live below the sediment surface, so most means of su
Externí odkaz:
https://doaj.org/article/5ad05f231c01473cba94d48c65e5087c
AI-driven molecular generation of not-patented pharmaceutical compounds using world open patent data
Autor:
Yugo Shimizu, Masateru Ohta, Shoichi Ishida, Kei Terayama, Masanori Osawa, Teruki Honma, Kazuyoshi Ikeda
Publikováno v:
Journal of Cheminformatics, Vol 15, Iss 1, Pp 1-11 (2023)
Abstract Developing compounds with novel structures is important for the production of new drugs. From an intellectual perspective, confirming the patent status of newly developed compounds is essential, particularly for pharmaceutical companies. The
Externí odkaz:
https://doaj.org/article/0b04847734da477a9d6dedc784708b85
Publikováno v:
Science and Technology of Advanced Materials: Methods, Vol 3, Iss 1 (2023)
Materials screening by high-throughput first-principles calculations is a powerful tool for exploring novel materials with preferable properties. Machine learning techniques are expected to accelerate materials screening by constructing surrogate mod
Externí odkaz:
https://doaj.org/article/659e031005da42baaba12a3bd91d9381
Publikováno v:
Materials & Design, Vol 232, Iss , Pp 112111- (2023)
Knowledge of the liquidus is important for the design and processing of many materials. For instance, deep eutectics are important for the design of metallic glasses, and recently multi-principal element alloys have been designed based on eutectic co
Externí odkaz:
https://doaj.org/article/daee33b243fc425aa2401f67d919e35d
Publikováno v:
Science and Technology of Advanced Materials: Methods, Vol 2, Iss 1, Pp 435-444 (2022)
Rietveld analysis necessitates the manual trial-and-error refinement of various parameters. To reduce human costs and resources, we have developed a robotic process automation (RPA) system for the Rietveld analysis program RIETAN-FP. By executing our
Externí odkaz:
https://doaj.org/article/51a0370c6789415196046c7ea8427cc0
Autor:
Ryo Tamura, Guillaume Deffrennes, Kwangsik Han, Taichi Abe, Haruhiko Morito, Yasuyuki Nakamura, Masanobu Naito, Ryoji Katsube, Yoshitaro Nose, Kei Terayama
Publikováno v:
Science and Technology of Advanced Materials: Methods, Vol 2, Iss 1, Pp 153-161 (2022)
To know phase diagrams is a time saving approach for developing novel materials. To efficiently construct phase diagrams, a machine learning technique was developed using uncertainty sampling, which is called as PDC (Phase Diagram Construction) packa
Externí odkaz:
https://doaj.org/article/915e39abaa58458c93354fcf5529759e
Autor:
Wei-Hsun Hu, Ta-Te Chen, Ryo Tamura, Kei Terayama, Siqian Wang, Ikumu Watanabe, Masanobu Naito
Publikováno v:
Science and Technology of Advanced Materials, Vol 23, Iss 1, Pp 66-75 (2022)
Stimuli-responsive polymers with complicated but controllable shape-morphing behaviors are critically desirable in several engineering fields. Among the various shape-morphing materials, cross-linked polymers with exchangeable bonds in dynamic networ
Externí odkaz:
https://doaj.org/article/a0fa1add16ae4436acd5d3ed839d7be7
Autor:
Takehiro Fujita, Kei Terayama, Masato Sumita, Ryo Tamura, Yasuyuki Nakamura, Masanobu Naito, Koji Tsuda
Publikováno v:
Science and Technology of Advanced Materials, Vol 23, Iss 1, Pp 352-360 (2022)
Recently, artificial intelligence (AI)-enabled de novo molecular generators (DNMGs) have automated molecular design based on data-driven or simulation-based property estimates. In some domains like the game of Go where AI surpassed human intelligence
Externí odkaz:
https://doaj.org/article/1e86faf762c24975ba05a028c83b7a19