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Unexpectedly large energy variations from dopant interactions in ferroelectric HfO_(2) from high-throughput ab initio calculations

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npj Computational Materials 2018年第1期4卷 45-53页

作者： max falkowski Christopher Künneth Robin Materlik Alfred Kersch Munich University of Applied Sciences Lothstr.3480335 MunichGermany

Insight into the origin of process-related properties like small-scale inhomogeneities is key for material ***,we analyze DFT calculations of randomly doped HfO_(2) structures with Si,La,and VO and relate them to the kind of production *** energies of the relevant ferroelectric Pbc2_(1) phase are compared with the competing crystallographic phases under the influence of the arising local inhomogeneities in a coarse-grained *** interaction among dopants adds to the statistical effect from the random positioning of the *** anneals after atomic layer or chemical solution deposition processes,which are short compared to ceramic process tempering,the large energy variations remain because the dopants do not *** the energy difference is the criterion for the phase stability,the large variation suggests the possibility of nanoregions and diffuse phase transitions because these local doping effects may move the system over the paraelectric-ferroelectric phase boundary.

关键词： ferroelectric dopant grain

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High-throughput reaction engineering to assess the oxidation stability of max phases

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npj Computational Materials 2021年第1期7卷 20-32页

作者： D.Sauceda P.Singh A.R.falkowski Y.Chen T.Doung G.Vazquez M.Radovic R.Arroyave Department of Materials Science & Engineering Texas A&M UniversityCollege StationTX 77843USA Department of Mechanical Engineering Texas A&M UniversityCollege StationTX 77843USA Ames Laboratory US Department of EnergyIowa State UniversityAmesIA50011USA

The resistance to oxidizing environments exhibited by some Mn+1AXn(max)phases stems from the formation of stable and protective oxide layers at high operating *** max phases are hexagonally arranged layered nitrides or carbides with general formula M_(n+1)AX_(n),n=1,2,3,where M is early transition elements,A is A block elements,and X is C/*** attempts to model and assess oxide phase stability in these systems has been limited in scope due to higher computational *** address the issue,we developed a machine-learning driven high-throughput framework for the fast assessment of phase stability and oxygen reactivity of 211 chemistry max phase M_(2)*** proposed scheme combines a sure independence screening sparsifying operator-based machine-learning model in combination with grand-canonical linear programming to assess temperaturedependent Gibbs free energies,reaction products,and elemental chemical activity during the oxidation of max *** thermodynamic stability,and chemical activity of constituent elements of Ti_(2)AlC with respect to oxygen were fully assessed to understand the high-temperature oxidation *** predictions are in good agreement with oxidation experiments performed on Ti_(2)*** were also able to explain the metastability of Ti_(2)SiC,which could not be synthesized experimentally due to higher stability of competing *** generality of the proposed approach,we discuss the oxidation mechanism of Cr_(2)*** insights of oxidation behavior will enable more efficient design and accelerated discovery of max phases with maintained performance in oxidizing environments at high temperatures。

关键词： stability max maintained

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