Interatomic Interactions in the Structures of Intermetallic Compounds. (binary compounds)

2021 ◽  
Author(s):  
Grigory Seguru ◽  
Valery Fertiko
1990 ◽  
Vol 213 ◽  
Author(s):  
R.L. Fleischer ◽  
C.L. Briant ◽  
R.D. Field

ABSTRACTA four-year survey of high-temperature intermetallic compounds has been aimed at identifying potentially useful structural materials for aerospace and aircraft engine applications. Since the good properties of high strength and stiffness at high temperatures are typically negated by brittleness at ambient temperature, new materials must have roomtemperature toughness or ductility. Screening has been done of 90 binary compounds with 20 different crystal structures, and 130 ternary or higher-order alloys. Testing typically included hardness vs. temperature, elastic modulus determination, and toughness evaluation via a room-temperature chisel test. Four alloy systems, including only two types that are of the simplest structures, showed substantial room-temperature toughness: Al-Ru, Ru-Sc, Ir-Nb, and Ru-Ta. Of these the last and the first are the most promising. Special features of the Ru- Ta (L1o) alloys are their room-temperature impact resistance and high-temperature strength. AIRu (B2) alloys can be tougher than the L1o structures and most are also ductile in compression at room temperature. Alloying experiments with B, Cr, and Sc show beneficial effects on ductility, oxidation resistance, and high-temperature strength.


1990 ◽  
Vol 213 ◽  
Author(s):  
Douglas W. Mckee ◽  
Robert L. Fleischer

ABSTRACTThe oxidation behavior of a number of ordered high melting point intermetallic materials has been studied in flowing air in the temperature range 1000 to 1500°C. The alloys were selected for acceptable toughness and ductility at temperatures above 1000°C. Included were ruthenium aluminides, chromium silicide and compounds of iridium and ruthenium with elements such as titanium, tantalum, nickel, iron, cobalt, silicon, vanadium and rhenium. In general, alloys containing the metals iron, cobalt and nickel, and also titanium and tantalum, oxidized rapidly at 1000°C and above. Oxidation-resistant materials were those capable of forming scales of chromia/silica or alumina. Intermetallic compounds of chromium and ruthenium formed volatile oxides above 1200°C, but binary compounds of these elements with silicon and aluminum were highly oxidation resistant at lower temperatures.


1987 ◽  
Vol 48 (C3) ◽  
pp. C3-497-C3-504 ◽  
Author(s):  
B. DUBOST ◽  
M. AUDIER ◽  
P. JEANMART ◽  
J.-M. LANG ◽  
P. SAINFORT

1988 ◽  
Vol 49 (C8) ◽  
pp. C8-375-C8-376
Author(s):  
C. D. Wentworth ◽  
A. f. Deutz ◽  
H. B. Brom

1988 ◽  
Vol 49 (C8) ◽  
pp. C8-393-C8-394 ◽  
Author(s):  
S. Miura ◽  
T. Kaneko ◽  
S. Abe ◽  
G. Kido ◽  
H. Yoshida ◽  
...  

2020 ◽  
Author(s):  
Cameron Hargreaves ◽  
Matthew Dyer ◽  
Michael Gaultois ◽  
Vitaliy Kurlin ◽  
Matthew J Rosseinsky

It is a core problem in any field to reliably tell how close two objects are to being the same, and once this relation has been established we can use this information to precisely quantify potential relationships, both analytically and with machine learning (ML). For inorganic solids, the chemical composition is a fundamental descriptor, which can be represented by assigning the ratio of each element in the material to a vector. These vectors are a convenient mathematical data structure for measuring similarity, but unfortunately, the standard metric (the Euclidean distance) gives little to no variance in the resultant distances between chemically dissimilar compositions. We present the Earth Mover’s Distance (EMD) for inorganic compositions, a well-defined metric which enables the measure of chemical similarity in an explainable fashion. We compute the EMD between two compositions from the ratio of each of the elements and the absolute distance between the elements on the modified Pettifor scale. This simple metric shows clear strength at distinguishing compounds and is efficient to compute in practice. The resultant distances have greater alignment with chemical understanding than the Euclidean distance, which is demonstrated on the binary compositions of the Inorganic Crystal Structure Database (ICSD). The EMD is a reliable numeric measure of chemical similarity that can be incorporated into automated workflows for a range of ML techniques. We have found that with no supervision the use of this metric gives a distinct partitioning of binary compounds into clear trends and families of chemical property, with future applications for nearest neighbor search queries in chemical database retrieval systems and supervised ML techniques.


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