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Thermodynamic and electronic properties of ReN2 polymorphs at high pressure
Linköpings universitet, Institutionen för fysik, kemi och biologi, Teoretisk Fysik. Linköpings universitet, Tekniska fakulteten.ORCID-id: 0000-0001-6373-5109
Linköpings universitet, Institutionen för fysik, kemi och biologi, Teoretisk Fysik. Linköpings universitet, Tekniska fakulteten.
NUST MISIS, Russia.
Univ Bayreuth, Germany.
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2021 (Engelska)Ingår i: Physical Review B, ISSN 2469-9950, E-ISSN 2469-9969, Vol. 104, nr 17, artikel-id 184103Artikel i tidskrift (Refereegranskat) Published
Abstract [en]

The high-pressure synthesis of rhenium nitride pernitride with a crystal structure that is unusual for transition metal dinitrides and high values of hardness and bulk modulus attracted significant attention to this system. We investigate the thermodynamic and electronic properties of the P2(1)/c phase of ReN2 and compare them with two other polytypes, the C2/m and P4/mbm phases, suggested in the literature. Our calculations of the formation enthalpy at zero temperature show that the former phase is the most stable of the three up to a pressure p = 170 GPa, followed by the stabilization of the P4/mbm phase at higher pressure. The theoretical prediction is confirmed by diamond anvil cell synthesis of the P4/mbm ReN2 at approximate to 175 GPa. Considering the effects of finite temperature in the quasiharmonic approximation at p = 100 GPa we demonstrate that the P2(1)/c phase has the lowest free energy of formation at least up to 1000 K. Our analysis of the pressure dependence of the electronic structure of rhenium nitride pernitride shows the presence of two electronic topological transitions around 18 GPa, when the Fermi surface changes its topology due to the appearance of an electron pocket at the high-symmetry Y-2 point of the Brillouin zone while the disruption of the neck takes place slightly off from the Gamma-A line.

Ort, förlag, år, upplaga, sidor
American Physical Society, 2021. Vol. 104, nr 17, artikel-id 184103
Nationell ämneskategori
Den kondenserade materiens fysik
Identifikatorer
URN: urn:nbn:se:liu:diva-181785DOI: 10.1103/PhysRevB.104.184103ISI: 000718103900015OAI: oai:DiVA.org:liu-181785DiVA, id: diva2:1619960
Anmärkning

Funding Agencies|Knut and Alice Wallenberg Foundation (Wallenberg Scholar Grant) [KAW-2018.0194]; Swedish Government Strategic Research Areas in Materials Science on Functional Materials at Linkoping University (Faculty Grant SFO-Mat-LiU) [2009 00971]; SeRC, the Swedish Research Council (VR) [2019-05600]; VINN Excellence Center Functional Nanoscale Materials (FunMat-2) [201605156]; Russian Science FoundationRussian Science Foundation (RSF) [18-12-00492]; Swedish Research CouncilSwedish Research CouncilEuropean Commission [2016-07213]

Tillgänglig från: 2021-12-14 Skapad: 2021-12-14 Senast uppdaterad: 2024-04-02
Ingår i avhandling
1. Combining ab‐initio and machine learning techniques for theoretical simulations of hard nitrides at extreme conditions
Öppna denna publikation i ny flik eller fönster >>Combining ab‐initio and machine learning techniques for theoretical simulations of hard nitrides at extreme conditions
2024 (Engelska)Doktorsavhandling, sammanläggning (Övrigt vetenskapligt)
Abstract [en]

In this thesis I focus on combining the high accuracy of first-principles calculations with modern machine learning methods to make large scale investigations of industrially relevant nitride systems reliable and computationally viable. I study the electronic, thermodynamic and mechanical properties of two families of compounds: Ti1−xAlxN alloys at the operational conditions of industrial cutting tools and ReNx systems at crushing pres-sures comparable to inner earth core conditions. Standard first-principles simulations of materials are usually carried out at zero temperature and pressure, and while many state-of-the-art approaches can take these effects into account, they are usually accompanied by a substantial increase in computational demand. In this thesis I therefore explore the possiblities of studying materials at extreme conditions using machine learning methods with extraordinary efficiency without loss of calculational accuracy. 

Ti1−xAlxN alloy coatings exhibit exceptional properties due to their inherent ability to spinodally decompose at elevated temperature, leading to age-hardening. Since the cubic B1 phase of Ti1−xAlxN is well-studied, available high-accuracy first-principles data served as both a benchmark and data set on which to train a machine learning interatomic potential. Using the reliable moment tensor potentials, an investigation of the accuracy and efficiency of this approach was carried out in a machine learning study. Building upon the success of this technique, implementation of a learning-on-the-fly (active learning) methodology into a workflow to determine accurate material properties with minimal prior knowledge showed great promise, while maintaining a computational demand up to two orders of magnitude lower than comparable first-principles approaches. Investigations of properties of industrially lesser desired, but sometimes present hexagonal alloy phases of Ti1−xAlxN are also included in this thesis, since knowledge and understanding of all competing phases can help guide development toward improving cutting tool lifetime and performance. Furthermore, while w-Ti1−xAlxN may not be able to compete with its cubic counterpart in terms of hardness, it shows promise for other applications due to its electronic and elastic properties. 

Metastable ReNx phases are high energy materials due to their covalent N-N and Re-N bonds, leading to exceptional mechanical and electronic properties. Just like diamond, the hardest and arguably most famous metastable mate-rial naturally occurring on earth, they are stabilized by extreme pressures and high temperatures, but can be quenched to ambient conditions. Understanding the formation and existence of these non-equilibrium compounds may hold the key to unlocking a new generation of hard materials. In this thesis, all currently known phases of ReNx compounds have been investigated, encompassing both experimentally observed and theoretically suggested structures. Investigations of the convex hulls across a broad pressure range were carried out, coupled with calculations of phonons in the proposed crystals to determine both energetic and dynamical stability. Overall, the studies included in this thesis focused mainly on investigation of the ground state of ReN2 at higher pressure, where experimental results were deviating from earlier theoretical predictions. Additional research focused on specifically exploring properties and stability of novel ReN6 at synthesis conditions using the active learning workflow to train an interatomic potential. 

Ort, förlag, år, upplaga, sidor
Linköping: Linköping University Electronic Press, 2024. s. 87
Serie
Linköping Studies in Science and Technology. Dissertations, ISSN 0345-7524 ; 2375
Nationell ämneskategori
Den kondenserade materiens fysik
Identifikatorer
urn:nbn:se:liu:diva-201992 (URN)10.3384/9789180755320 (DOI)9789180755313 (ISBN)9789180755320 (ISBN)
Disputation
2024-04-19, Planck, F-building, Campus Valla, Linköping, 10:15 (Engelska)
Opponent
Handledare
Tillgänglig från: 2024-04-02 Skapad: 2024-04-02 Senast uppdaterad: 2024-04-02Bibliografiskt granskad

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