Zobrazeno 1 - 10
of 54
pro vyhledávání: '"Dmitry S. Bulgarevich"'
Publikováno v:
Science and Technology of Advanced Materials: Methods, Vol 4, Iss 1 (2024)
Two protocols for multistep grain segmentation and analysis workflow in optical microscopy images of cubic boron nitride materials were developed and compared. One is based on statistical region merging and second one on morphological segmentation of
Externí odkaz:
https://doaj.org/article/4025122c8ec84936bd6d9f1121f7b121
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-15 (2023)
Abstract Additive manufacturing of as-build metal materials with laser powder bed fusion typically leads to the formations of various chemical phases and their corresponding microstructure types. Such microstructures have very complex shape and size
Externí odkaz:
https://doaj.org/article/cfe59be6e40c4f23a329764b5b3a9fac
Autor:
Vickey Nandal, Sae Dieb, Dmitry S. Bulgarevich, Toshio Osada, Toshiyuki Koyama, Satoshi Minamoto, Masahiko Demura
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-13 (2023)
Abstract In this paper, a state-of-the-art Artificial Intelligence (AI) technique is used for a precipitation hardening of Ni-based alloy to predict more flexible non-isothermal aging (NIA) and to examine the possible routes for the enhancement in st
Externí odkaz:
https://doaj.org/article/d00fbb4ec9374ad88ae87ec4445bf984
Autor:
Toshio Osada, Toshiyuki Koyama, Dmitry S. Bulgarevich, Satoshi Minamoto, Makoto Osawa, Makoto Watanabe, Kyoko Kawagishi, Masahiko Demura
Publikováno v:
Materials & Design, Vol 226, Iss , Pp 111631- (2023)
Aiming to designing the aging heat treatment conditions to maximize the 0.2 % proof stress of γ-γ′ two-phase Ni-based superalloys, we develop the automated computational workflow for γ-γ′ two-phase Ni-Al binary alloy that serves at the system
Externí odkaz:
https://doaj.org/article/1e30e6a6291241f6ad5fd90e6e21ee8e
Publikováno v:
Scientific Reports, Vol 11, Iss 1, Pp 1-8 (2021)
Abstract Several machine learning (ML) techniques were tested for the feasibility of performing automated pattern and waveform recognitions of terahertz time-domain spectroscopy datasets. Out of all the ML techniques under test, it was observed that
Externí odkaz:
https://doaj.org/article/20abf015762a401f86ff26e42bd44bed
Publikováno v:
Science and Technology of Advanced Materials, Vol 20, Iss 1, Pp 532-542 (2019)
It is demonstrated that optical microscopy images of steel materials could be effectively categorized into classes on preset ferrite/pearlite-, ferrite/pearlite/bainite-, and bainite/martensite-type microstructures with image pre-processing and stati
Externí odkaz:
https://doaj.org/article/ee0b300f22364790ad39868794259846
Autor:
Vickey Nandal, Sae Dieb, Dmitry S. Bulgarevich, Toshio Osada, Toshiyuki Koyama, Satoshi Minamoto, Masahiko Demura
In this paper, a state-of-the-art Artificial Intelligence (AI) technique is used for a precipitation hardenable Ni-based alloy to predict more flexible non-isothermal heat treatment and to examine the possible heat treatment routes for the enhancemen
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6460a55a860045cf28670213f2a57543
https://doi.org/10.21203/rs.3.rs-2593940/v1
https://doi.org/10.21203/rs.3.rs-2593940/v1
Autor:
Toshio Osada, Toshiyuki Koyama, Dmitry S. Bulgarevich, Satoshi Minamoto, Makoto Osawa, Makoto Watanabe, Kyoko Kawagishi, Masahiko Demura
Publikováno v:
SSRN Electronic Journal.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ab766075bd3b69eef5b39011625420a4
https://doi.org/10.2139/ssrn.4290793
https://doi.org/10.2139/ssrn.4290793
Autor:
Miezel Talara, Dmitry S. Bulgarevich, Kana Kobayashi, Hideaki Kitahara, Takashi Furuya, Mary Clare Escaño, Makoto Watanabe, Masahiko Tani
Publikováno v:
Applied Physics Express. 15:122002
We compare THz emission properties of rectangular, circular, and diabolo spintronic antennas composed of 2 nm Fe and 3 nm Pt layers on MgO substrates. Although the rectangular antenna generated the highest amplitude (∼1.8× improvement), the radiat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d717ee580769c9be9172378046f9f235
https://doi.org/10.35848/1882-0786/ac99b5
https://doi.org/10.35848/1882-0786/ac99b5
Publikováno v:
Science and Technology of Advanced Materials
Science and Technology of Advanced Materials, Vol 20, Iss 1, Pp 532-542 (2019)
Science and Technology of Advanced Materials, Vol 20, Iss 1, Pp 532-542 (2019)
It is demonstrated that optical microscopy images of steel materials could be effectively categorized into classes on preset ferrite/pearlite-, ferrite/pearlite/bainite-, and bainite/martensite-type microstructures with image pre-processing and stati
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9bc9f03cfa3ddfd87ea7c3c746911b38
http://europepmc.org/articles/PMC6567074
http://europepmc.org/articles/PMC6567074