A study of the Al–Co–Cr alloy system

Grushko, B.; Kowalski, W.; Mi, Shao‐Bo

doi:10.1016/j.jallcom.2017.12.226

Cited by 13 publications

(7 citation statements)

References 20 publications

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“…4) was constructed based on the experimental data on the melting temperatures of alloys and their phase composition at subsolidus temperatures (Table 2) considering lattice parameters of the phases according to the XRD measurements data (Table 3). The ternary monoclinic phase s 5 that was reported for the first time by Grushko et al [43] (there designated ø) was confirmed. According to the EPMA data of as-cast alloy #18, it had a composition Al 75.3 Cr 16.8 Co 7.9 (Table 4, Fig.…”

Section: Solidus Surfacesupporting

confidence: 59%

“…The formation of the ternary i phase with the icosahedral structure found [12] . Grushko et al [43] found no ternary phases at 1150-1100°C, and at lower temperatures (1000°C to 700°C) for the first time they found five ternary phases (labeled in our article as s 3 to s 7 ).…”

Section: Binary Systemsmentioning

confidence: 45%

“…Co 2 Al 5 ? s 5 (Table 5) was based on that 1000°C isothermal [43] because melting temperature of alloy #19 composition of which is placed inside of this three-phase region is phases indicated in the invariant four-phase equilibria with liquid.…”

Section: Solidus Surfacementioning

confidence: 99%

“…[42] . Recently, phase equilibria in the Al-Cr-Co system were experimentally investigated by Grushko et al [43] who presented partial isothermal sections at the temperatures of 1150, 1100, 1000, 900, 800 and 700°C. Five ternary phases were revealed for the first time.…”

Section: Introductionmentioning

confidence: 99%

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Phase Equilibria in the Al-Cr-Co System in the Range of Compositions 0-70 at.% Al

Korniyenko

Kriklya

Petyukh

et al. 2021

J. Phase Equilib. Diffus.

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Phase equilibria during solidification in the Al-Cr-Co system in the range of compositions 0-70 at.% Al were studied using optical microscopy, scanning electron microscopy, electron probe microanalysis, differential thermal analysis and x-ray diffraction. Solidus and liquidus surfaces, a melting diagram as their superposition, a Scheil diagram for solidification, as well as series of isopleths were constructed for the first time. Solid solutions based on Cr, aCo, Cr 5 Al 8 (c 3 and c 1 phases), CoAl, Co 2 Al 5 binary compounds and the ternary compound s 5 take part in phase equilibria. The monoclinic ternary compound s 5 forms by peritectic reaction L ? c 1 ? Co 2 Al 5 $ s 5 at 1065°C. Four invariant four-phase reactions and one invariant threephase reaction involving liquid take place at 1280, 1175, 1110, 1065 and about 1480°C, respectively. Isopleths 10, 20, 30 and 40 at.% Al as well as 40 at.% Cr demonstrate peculiarities of the phase diagram.

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Section: Solidus Surfacesupporting

confidence: 59%

Section: Binary Systemsmentioning

confidence: 45%

Section: Solidus Surfacementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Phase Equilibria in the Al-Cr-Co System in the Range of Compositions 0-70 at.% Al

Korniyenko

Kriklya

Petyukh

et al. 2021

J. Phase Equilib. Diffus.

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“…Yüzey dayanımını artırma yöntemlerinden olan borlama, malzemelerin yüzey direncini artırma konusunda en etkili yöntemlerden biridir [1][2][3]. Yüksek aşınma ve oksidasyon direnci diğer yöntemlere göre borlamada en büyük avantajlar arasındadır [4,5]. Borlama; bor atomlarının metal/alaşım yüzeyine difüzyonu yoluyla yüzeylerde bir borür tabakasının elde edilmesi şeklindedir.…”

Section: Introductionunclassified

%3 Mg içeren Borlanmış Co-Mg Alaşımının Yüzey Özelliklerinin İncelenmesi

Yildiz

Güneş

2019

El-Cezeri Fen Ve Mühendislik Dergisi

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Bu çalışmada, %97 Co ve %3 Mg içeren Co-Mg alaşımına borlama işlemi gerçekleştirilmiştir. Co-Mg alaşım malzemesini üretmek için toz metalurjisi (TM) yöntemi kullanılmıştır. Bu yöntemde, Co ve Mg metal tozları kapalı kaplar içerisinde homojen bir şekilde karıştırılarak şekillendirilmeleri için özel olarak tasarlanmış silindirik kalıplara dökülmüştür. Tek eksenli preste 300 bar basınç altında preslendikten sonra Argon gazı atmosferi ortamında 530 °C sıcaklıkta sinterlenmiştir. Sinterlenerek üretilen numunelere sırasıyla sertlik, yoğunluk ve yüzey pürüzlülüğü testleri uygulanmıştır. Sertlik testi sonrası 123 HV 0,05 değeri elde edilirken ölçülen yoğunluk değeri ise 4,95 gr/cm 3 olarak bulunmuştur. Bu işlemler sonrasında numuneler kapalı fırın ortamında 850 ve 900 °C sıcaklık ve 1.5-4.5 saat değişen sürelerde borlama işlemi gerçekleştirilmiştir. Bu işlem sonrasında SEM ve XRD analiz çalışmaları yapılmıştır. Analiz sonrasında borür tabakaları 850 °C sıcaklıkta 1,5 saat sürede 55 µm olarak bulunurken en yüksek 900 °C sıcaklık 4,5 saat sürede 140 µm olarak ölçülmüştür. Borlanmış Kobalt-Magnezyum alaşımlarına uygulanan XRD analizi sonucunda CoB, Co 2 B ve Co fazları elde edilmiştir. Mg elementinin hızlı bozulma özelliğinden dolayı yapılarda kısmende olsa boşluklar oluşmuştur.

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Machine Learning to Predict Quasicrystals from Chemical Compositions

et al. 2021

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Quasicrystals have emerged as the third class of solid‐state materials, distinguished from periodic crystals and amorphous solids, which have long‐range order without periodicity exhibiting rotational symmetries that are disallowed for periodic crystals in most cases. To date, more than one hundred stable quasicrystals have been reported, leading to the discovery of many new and exciting phenomena. However, the pace of the discovery of new quasicrystals has lowered in recent years, largely owing to the lack of clear guiding principles for the synthesis of new quasicrystals. Here, it is shown that the discovery of new quasicrystals can be accelerated with a simple machine‐learning workflow. With a list of the chemical compositions of known stable quasicrystals, approximant crystals, and ordinary crystals, a prediction model is trained to solve the three‐class classification task and its predictability compared to the observed phase diagrams of ternary aluminum systems is evaluated. The validation experiments strongly support the superior predictive power of machine learning, with the overall prediction accuracy of the phase prediction task reaching ≈0.728. Furthermore, analyzing the input–output relationships black‐boxed into the model, nontrivial empirical equations interpretable by humans that describe conditions necessary for stable quasicrystal formation are identified.

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A study of the Al–Co–Cr alloy system

Cited by 13 publications

References 20 publications

Phase Equilibria in the Al-Cr-Co System in the Range of Compositions 0-70 at.% Al

Phase Equilibria in the Al-Cr-Co System in the Range of Compositions 0-70 at.% Al

%3 Mg içeren Borlanmış Co-Mg Alaşımının Yüzey Özelliklerinin İncelenmesi

Machine Learning to Predict Quasicrystals from Chemical Compositions

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