Search Results - "Iwasaki, Yuma"

Autonomous search for materials with high Curie temperature using ab initio calculations and machine learning by Iwasaki, Yuma

“…Efficient exploration of vast material spaces is a challenging task in materials science. Autonomous material search methods utilizing machine learning and ab…”
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Machine-learning guided discovery of a new thermoelectric material by Iwasaki, Yuma, Takeuchi, Ichiro, Stanev, Valentin, Kusne, Aaron Gilad, Ishida, Masahiko, Kirihara, Akihiro, Ihara, Kazuki, Sawada, Ryohto, Terashima, Koichi, Someya, Hiroko, Uchida, Ken-ichi, Saitoh, Eiji, Yorozu, Shinichi

“…Thermoelectric technologies are becoming indispensable in the quest for a sustainable future. Recently, an emerging phenomenon, the spin-driven thermoelectric…”
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Improving efficiency of autonomous material search via transfer learning from nontarget properties by Hwang, Jaekyun, Iwasaki, Yuma

“…Recently, autonomous material search methods combining machine learning and experiments/simulations have become indispensable for exploring the extremely vast…”
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Comparison of dissimilarity measures for cluster analysis of X-ray diffraction data from combinatorial libraries by Iwasaki, Yuma, Kusne, A. Gilad, Takeuchi, Ichiro

“…Machine learning techniques have proven invaluable to manage the ever growing volume of materials research data produced as developments continue in…”
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Machine learning autonomous identification of magnetic alloys beyond the Slater-Pauling limit by Iwasaki, Yuma, Sawada, Ryohto, Saitoh, Eiji, Ishida, Masahiko

“…Discovery of new magnets with high magnetization has always been important in human history because it has given birth to powerful motors and memory devices…”
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Predicting material properties by integrating high-throughput experiments, high-throughput ab-initio calculations, and machine learning by Iwasaki, Yuma, Ishida, Masahiko, Shirane, Masayuki

“…High-throughput experiments (HTEs) have been powerful tools to obtain many materials data. However, HTEs often require expensive equipment. Although…”
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Model-Free Cluster Analysis of Physical Property Data using Information Maximizing Self-Argument Training by Sawada, Ryohto, Iwasaki, Yuma, Ishida, Masahiko

“…We present semi-supervised information maximizing self-argument training (IMSAT), a neural network-based classification method that works without the…”
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Early Clinical Outcomes of the First Commercialized Human Autologous Ex Vivo Cultivated Oral Mucosal Epithelial Cell Transplantation for Limbal Stem Cell Deficiency: Two Case Reports and Literature Review by Toshida, Hiroshi, Kasahara, Tomoto, Kiriyama, Masamichi, Iwasaki, Yuma, Sugita, Jobu, Ichikawa, Kohei, Ohta, Toshihiko, Miyahara, Katsumi

“…The first product in the world for ex vivo cultivated oral mucosal epithelial cell transplantation (COMET) to treat limbal stem cell deficiency (LSCD), named…”
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Flexible heat-flow sensing sheets based on the longitudinal spin Seebeck effect using one-dimensional spin-current conducting films by Kirihara, Akihiro, Kondo, Koichi, Ishida, Masahiko, Ihara, Kazuki, Iwasaki, Yuma, Someya, Hiroko, Matsuba, Asuka, Uchida, Ken-ichi, Saitoh, Eiji, Yamamoto, Naoharu, Kohmoto, Shigeru, Murakami, Tomoo

“…Heat-flow sensing is expected to be an important technological component of smart thermal management in the future. Conventionally, the thermoelectric (TE)…”
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Extraction of physicochemical laws by symbolic regression using a Bayesian information criterion by Yamane, Naoki, Hatakeyama-Sato, Kan, Iwasaki, Yuma, Igarashi, Yasuhiko

“…In the search for new high-performance materials in materials science, especially in polynomial science, it is important to use physicochemical laws linking…”
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Autonomous synthesis system integrating theoretical, informatics, and experimental approaches for large-magnetic-anisotropy materials by Furuya, Daigo, Miyashita, Takuya, Miura, Yoshio, Iwasaki, Yuma, Kotsugi, Masato

“…We developed an autonomous and efficient system for synthesising ferromagnetic materials with large magnetocrystalline anisotropy by integrating theoretical,…”
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Combinatorial optimization for high spin polarization in Heusler alloy composition-spread thin films by anisotropic magnetoresistance effect by Toyama, Ryo, Kushwaha, Varun K., Sasaki, Taisuke T., Iwasaki, Yuma, Nakatani, Tomoya, Sakuraba, Yuya

“…Half-metallic Heusler alloys are promising candidates for spintronic applications due to their high spin polarization. However, the spin polarization strongly…”
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Identification of advanced spin-driven thermoelectric materials via interpretable machine learning by Iwasaki, Yuma, Sawada, Ryohto, Stanev, Valentin, Ishida, Masahiko, Kirihara, Akihiro, Omori, Yasutomo, Someya, Hiroko, Takeuchi, Ichiro, Saitoh, Eiji, Yorozu, Shinichi

“…Machine learning is becoming a valuable tool for scientific discovery. Particularly attractive is the application of machine learning methods to the field of…”
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Efficient autonomous material search method combining ab initio calculations, autoencoder, and multi-objective Bayesian optimization by Iwasaki, Yuma, Jaekyun, Hwang, Sakuraba, Yuya, Kotsugi, Masato, Igarashi, Yasuhiko

“…Autonomous material search systems that combine ab initio calculations and Bayesian optimization are very promising for exploring huge material spaces. Setting…”
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Skill-Agnostic analysis of reflection high-energy electron diffraction patterns for Si(111) surface superstructures using machine learning by Yoshinari, Asako, Iwasaki, Yuma, Kotsugi, Masato, Sato, Shunsuke, Nagamura, Naoka

“…Reflection high-energy electron diffraction (RHEED) data are important for the in-situ characterization of surface conditions during physical vapor deposition…”
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Autonomous search for half-metallic materials with B2 structure by Yuma Iwasaki, Ryo Toyama, Takahiro Yamazaki, Yasuhiko Igarashi, Masato Kotsugi, Yuya Sakuraba

“…Exploring vast material spaces efficiently is challenging in materials science. Autonomous methods for material search – integrating machine learning and ab…”
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Autonomous search for half-metallic materials with B 2 structure by Iwasaki, Yuma, Toyama, Ryo, Yamazaki, Takahiro, Igarashi, Yasuhiko, Kotsugi, Masato, Sakuraba, Yuya

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Individual multidisciplinary clinical phenotypes of nasal and ocular symptoms in hay fever: Crowdsourced cross-sectional study using AllerSearch by Inomata, Takenori, Sung, Jaemyoung, Fujio, Kenta, Nakamura, Masahiro, Akasaki, Yasutsugu, Nagino, Ken, Okumura, Yuichi, Iwagami, Masao, Fujimoto, Keiichi, Ebihara, Nobuyuki, Nakamura, Masahiro, Midorikawa-Inomata, Akie, Shokirova, Hurramhon, Huang, Tianxiang, Hirosawa, Kunihiko, Miura, Maria, Ohno, Mizu, Morooka, Yuki, Iwata, Nanami, Iwasaki, Yuma, Murakami, Akira

“…Multidisciplinary efforts to prospectively collect and analyze symptoms of hay fever are limited. We aimed to identify the characteristics of nasal and ocular…”
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Skeleton phylogeny reconstructed with transcriptomes for the tribe Drosophilini (Diptera: Drosophilidae) by Seto, Yosuke, Iwasaki, Yuma, Ogawa, Yoshitaka, Tamura, Koichiro, Toda, Masanori J

“…The family Drosophilidae is one of the most important model systems in evolutionary biology. Thanks to advances in high-throughput sequencing technology, a…”
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Materials Informatics for the Development and Discovery of Future Magnetic Materials by Okabe, Ryotaro, Li, Mingda, Iwasaki, Yuma, Regnault, Nicolas, Felser, Claudia, Shirai, Masafumi, Kovacs, Alexander, Schrefl, Thomas, Hirohata, Atsufumi

“…This letter summarizes the recent development of magnetic materials search using artificial intelligence (AI) and machine learning (ML) and briefly introduces…”
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