arXiv subjects

Elif Ertekin

Publications and source records attributed to Elif Ertekin.

At least 37 records · Page 2Linked to original sources

arXiv2024

First-principles and cluster expansion study of the effect of magnetism on short-range order in Fe-Ni-Cr austenitic stainless steels

Short-range order (SRO) alters the mechanical properties of technologically relevant structural materials such as medium/high entropy alloys and austenitic stainless steels. In this study, we present a generalized spin cluster expansion (CE) model and show that magnetism is a primary factor influencing the level of SRO present in austenitic Fe-Ni-Cr alloys. The spin CE consists of a chemical cluster expansion combined with an Ising model for Fe-Ni-Cr alloys. It explicitly accounts for local magnetic exchange interactions, thereby capturing the effects of finite temperature magnetism on SRO. Model parameters are obtained by fitting to a first-principles data set comprising both chemically and magnetically diverse FCC configurations. The magnitude of the magnetic exchange interactions are found to be comparable to the chemical interactions. Compared to a conventional implicit magnetism CE built from only magnetic ground state configurations, the spin CE shows improved performance on several experimental benchmarks over a broad spectrum of compositions, particularly at higher temperatures due to the explicit treatment of magnetic disorder. We find that SRO is strongly influenced by alloy Cr content, since Cr atoms prefer to align antiferromagnetically with nearest neighbors but become magnetically frustrated with increasing Cr concentration. We predict that increasing the Cr concentration in typical austenitic stainless steels promotes the formation of SRO and increases order-disorder transition temperatures. This study underscores the significance of considering magnetic interactions explicitly when exploring the thermodynamic properties of complex transition metal alloys. It also highlights guidelines for customizing SRO through adjustments of alloy composition.

cond-mat.mtrl-sci↗

arXiv2024

JARVIS-Leaderboard: A Large Scale Benchmark of Materials Design Methods

Lack of rigorous reproducibility and validation are major hurdles for scientific development across many fields. Materials science in particular encompasses a variety of experimental and theoretical approaches that require careful benchmarking. Leaderboard efforts have been developed previously to mitigate these issues. However, a comprehensive comparison and benchmarking on an integrated platform with multiple data modalities with both perfect and defect materials data is still lacking. This work introduces JARVIS-Leaderboard, an open-source and community-driven platform that facilitates benchmarking and enhances reproducibility. The platform allows users to set up benchmarks with custom tasks and enables contributions in the form of dataset, code, and meta-data submissions. We cover the following materials design categories: Artificial Intelligence (AI), Electronic Structure (ES), Force-fields (FF), Quantum Computation (QC) and Experiments (EXP). For AI, we cover several types of input data, including atomic structures, atomistic images, spectra, and text. For ES, we consider multiple ES approaches, software packages, pseudopotentials, materials, and properties, comparing results to experiment. For FF, we compare multiple approaches for material property predictions. For QC, we benchmark Hamiltonian simulations using various quantum algorithms and circuits. Finally, for experiments, we use the inter-laboratory approach to establish benchmarks. There are 1281 contributions to 274 benchmarks using 152 methods with more than 8 million data-points, and the leaderboard is continuously expanding. The JARVIS-Leaderboard is available at the website: https://pages.nist.gov/jarvis_leaderboard

cond-mat.mtrl-sci↗

arXiv2024

Investigation of Ga interstitial and vacancy diffusion in $β$-Ga$_2$O$_3$ via split defects: a direct approach via master diffusion equations

The low symmetry of monoclinic $β$-Ga$_2$O$_3$ leads to elaborate intrinsic defects, such as Ga vacancies split amongst multiple lattice sites. These defects contribute to fast, anisotropic Ga diffusion, yet their complexity makes it challenging to understand dominant diffusion mechanisms. Here, we predict the 3D diffusivity tensors for Ga interstitials (Ga${_i^{3+}}$) and vacancies (V${_{Ga}^{3-}}$) via first principles and direct solution of the master diffusion equations. We first explore the maximum extent of configurationally complex ''$N$-split'' Ga interstitials and vacancies. With dominant low-energy defects identified, we enumerate all possible elementary hops connecting defect configurations to each other, including interstitialcy hops. Hopping barriers are obtained from nudged elastic band simulations. Finally, the comprehensive sets of (i) defect configurations and their energies and (ii) the hopping barriers that connect them are used to construct the master diffusion equations for both Ga${_i^{3+}}$ and V${_{Ga}^{3-}}$. The solution to these equations yields the Onsager transport coefficients, i.e. the components of the 3D diffusivity tensors $D_{{Ga}_i}$ and $D_{V_{Ga}}$ for Ga${_i^{3+}}$ and V${_{Ga}^{3-}}$, respectively. It further reveals the active diffusion paths along all crystallographic directions. We find that both Ga${_i^{3+}}$ and V${_{Ga}^{3-}}$ diffusion are fastest along the $c$-axis, due to 3-split defects that bridge neighboring unit cells along the $c$-axis and divert diffusing species around high-energy bottlenecks. Although isolated Ga${_i^{3+}}$ diffuse faster than isolated V${_{Ga}^{3-}}$, self-diffusion of Ga is predominantly mediated by V$_{Ga}^{3-}$ due to the higher V$_{Ga}^{3-}$ defect concentration under most thermodynamic environments.

cond-mat.mtrl-sci↗

arXiv2023

Registry-dependent potential energy and lattice corrugation of twisted bilayer graphene from quantum Monte Carlo

An uncertainty in studying twisted bilayer graphene (TBG) is the minimum energy geometry, which strongly affects the electronic structure. The minimum energy geometry is determined by the potential energy surface, which is dominated by van der Waals (vdW) interactions. In this work, large-scale diffusion quantum Monte Carlo (QMC) simulations are performed to evaluate the energy of bilayer graphene at various interlayer distances for four stacking registries. An accurate registry-dependent potential is fit to the QMC data and is used to describe interlayer interactions in the geometry of near-magic-angle TBG. The band structure for the optimized geometry is evaluated using the accurate local-environment tight-binding model. We find that compared to QMC, DFT-based vdW interactions can result in errors in the corrugation magnitude by a factor of 2 or more near the magic angle. The error in corrugation then propagates to the flat bands in twisted bilayer graphene, where the error in corrugation can affect the bandwidth by about 30\% and can change the nature and degeneracy of the flat bands.

cond-mat.mes-hall↗

arXiv2023

Leveraging Language Representation for Material Recommendation, Ranking, and Exploration

Data-driven approaches for material discovery and design have been accelerated by emerging efforts in machine learning. However, general representations of crystals to explore the vast material search space remain limited. We introduce a material discovery framework that uses natural language embeddings derived from language models as representations of compositional and structural features. The discovery framework consists of a joint scheme that first recalls relevant candidates, and next ranks the candidates based on multiple target properties. The contextual knowledge encoded in language representations conveys information about material properties and structures, enabling both representational similarity analysis for recall, and multi-task learning to share information across related properties. By applying the framework to thermoelectrics, we demonstrate diversified recommendations of prototype structures and identify under-studied high-performance material spaces. The recommended materials are corroborated by first-principles calculations and experiments, revealing novel materials with potential high performance. Our framework provides a task-agnostic means for effective material recommendation and can be applied to various material systems.

cond-mat.mtrl-sci↗

arXiv2023

The nature of dynamic local order in CH$_3$NH$_3$PbI$_3$ and CH$_3$NH$_3$PbBr$_3$

Hybrid lead halide perovskites (LHPs) are a class of semiconductor with novel properties that are distinctively governed by structural fluctuations. Diffraction experiments sensitive to average, long-range order reveal a cubic structure in the device-relevant, high-temperature phase. Local probes find additional short-range order with lower symmetry that may govern the structure-function relationships of LHPs. However, the dimensionality, participating atoms, and dynamics of this short-range order are unresolved, impeding our understanding of technologically relevant properties including long carrier lifetimes and facile halide migration. Here, we determine the true structure of two prototypical hybrid LHPs, CH$_3$NH$_3$PbI$_3$ and CH$_3$NH$_3$PbBr$_3$, using a combination of single-crystal X-ray and neutron diffuse scattering, neutron inelastic spectroscopy, and molecular dynamics simulations. The remarkable collective dynamics we found are not suggested by previous studies and consist of a network of local two-dimensional, circular pancake-like regions of dynamically tilting lead halide octahedra (lower symmetry) that induce longer range intermolecular correlations within the CH$_3$NH$_3^+$ sublattice. The dynamic local structure can introduce transient ferroelectric or antiferroelectric domains that increase charge carrier lifetimes, and strongly affect the halide migration, a poorly understood degradation mechanism. Our approach of co-analyzing single-crystal X-ray and neutron diffuse scattering data with MD simulations will provide unparalleled insights into the structure of hybrid materials and materials with engineered disorder.

cond-mat.mtrl-sci↗

arXiv2023

Origin of ultra-low thermal conductivity in unconventional clathrates: Strong scattering from extremely low-frequency rattling modes

Recent discoveries of materials with ultra-low thermal conductivity open a pathway to significant developments in the field of thermoelectricity. Here, we conduct a comparative study of three chemically similar antimonides to establish the root causes of their extraordinarily low thermal conductivity ($0.4-0.6$ Wm$^{-1}$K$^{-1}$ at 525 K). The materials of interest are: the unconventional type-XI clathrate K$_{58}$Zn$_{122}$Sb$_{207}$, the tunnel compound K$_{6.9}$Zn$_{21}$Sb$_{16}$, and the type-I clathrate K$_8$Zn$_{15.5}$Cu$_{2.5}$Sb$_{28}$ discovered herein. Calculations of the phonon dispersions show that the type-XI compound exhibits localized (i.e., rattling) phonon modes with unusually low frequencies that span the entire acoustic regime. In contrast, rattling in the type-I clathrate is observed only at higher frequencies, and no rattling modes are present in the tunnel structure. Modeling reveals that low-frequency rattling modes profoundly limit the acoustic scattering time; the scattering time of the type-XI clathrate is half that of the type-I clathrate and a quarter of the tunnel compound. For all three materials, the thermal conductivities are additionally suppressed by soft framework bonding that lowers the acoustic group velocities, and structural complexity that leads to diffusonic character of the optical modes. Understanding details of thermal transport in structurally complex materials will be crucial for developing the next generation of thermoelectrics.

cond-mat.mtrl-sci↗

arXiv2022

Towards overcoming data scarcity in materials science: unifying models and datasets with a mixture of experts framework

While machine learning has emerged in recent years as a useful tool for rapid prediction of materials properties, generating sufficient data to reliably train models without overfitting is still impractical for many applications. Towards overcoming this limitation, we present a general framework for leveraging complementary information across different models and datasets for accurate prediction of data scarce materials properties. Our approach, based on a machine learning paradigm called mixture of experts, outperforms pairwise transfer learning on 16 of 19 materials property regression tasks, performing comparably on the remaining three. Unlike pairwise transfer learning, our framework automatically learns to combine information from multiple source tasks in a single training run, alleviating the need for brute-force experiments to determine which source task to transfer from. The approach also provides an interpretable, model-agnostic, and scalable mechanism to transfer information from an arbitrary number of models and datasets to any downstream property prediction task. We anticipate the performance of our framework will further improve as better model architectures, new pre-training tasks, and larger materials datasets are developed by the community.

cond-mat.mtrl-sci↗

arXiv2021

An accurate tight binding model for twisted bilayer graphene describes topological flat bands without geometric relaxation

A major hurdle in understanding the phase diagram of twisted bilayer graphene (TBLG) are the roles of lattice relaxation and electronic structure on isolated band flattening near magic twist angles. In this work, the authors develop an accurate local environment tight binding model (LETB) fit to tight binding parameters computed from $ab\ initio$ density functional theory (DFT) calculations across many atomic configurations. With the accurate parameterization, it is found that the magic angle shifts to slightly lower angles than often quoted, from around 1.05$^\circ$ to around 0.99$^\circ$, and that isolated flat bands appear for rigidly rotated graphene layers, with enhancement of the flat bands when the layers are allowed to distort. Study of the orbital localization supports the emergence of fragile topology in the isolated flat bands without the need for lattice relaxation.

cond-mat.mes-hall↗

arXiv2020

Understanding Cu Incorporation in the $\mathrm{Cu_{2x}Hg_{2-x}GeTe_4}$ Structure using Resonant X-ray Diffraction

The ability to control carrier concentration based on the extent of Cu solubility in the $\mathrm{Cu_{2x}Hg_{2-x}GeTe_4}$ alloy compound (where 0 $\leq$ x $\leq$ 1) makes $\mathrm{Cu_{2x}Hg_{2-x}GeTe_4}$ an interesting case study in the field of thermoelectrics. While Cu clearly plays a role in this process, it is unknown exactly how Cu incorporates into the $\mathrm{Cu_{2x}Hg_{2-x}GeTe_4}$ crystal structure and how this affects the carrier concentration. In this work, we use a combination of resonant energy X-ray diffraction (REXD) experiments and density functional theory (DFT) calculations to elucidate the nature of Cu incorporation into the $\mathrm{Cu_{2x}Hg_{2-x}GeTe_4}$ structure. REXD across the $\mathrm{Cu_k}$ edge facilitates the characterization of Cu incorporation in the $\mathrm{Cu_{2x}Hg_{2-x}GeTe_4}$ alloy and enables direct quantification of anti-site defects. We find that Cu substitutes for Hg at a 2:1 ratio, wherein Cu annihilates a vacancy and swaps with a Hg atom. DFT calculations confirm this result and further reveal that the incorporation of Cu occurs preferentially on one of the z = 1/4 or z = 3/4 planes before filling the other plane. Furthermore, the amount of $\mathrm{Cu_{Hg}}$ anti-site defects quantified by REXD was found to be directly proportional to the experimentally measured hole concentration, indicating that the $\mathrm{Cu_{Hg}}$ defects are the driving force for tuning carrier concentration in the $\mathrm{Cu_{2x}Hg_{2-x}GeTe_4}$ alloy. The link uncovered here between crystal structure, or more specifically anti-site defects, and carrier concentration can be extended to similar cation-disordered material systems and will aid the development of improved thermoelectric and other functional materials through defect engineering.

cond-mat.mtrl-sci↗

arXiv2020

A topologically-derived dislocation theory for twist and stretch moiré superlattices in bilayer graphene

We develop a continuum dislocation description of twist and stretch moire superlattices in 2D material bilayers. The continuum formulation is based on the topological constraints introduced by the periodic dislocation network associated with the moire structure. The approach is based on solving analytically for the structural distortion and displacement fields that satisfy the topological constraints, and which minimize the total energy. The total energy is described by both the strain energy of each individual distorted layer, and a Peierls-Nabarro like interfacial contribution arising from stacking disregistry. The dislocation core emerges naturally within the formalism as a result of the competition between the two contributions. The approach presented here captures the structure and energetics of twist and stretch moire superlattices of dislocations with arbitrary direction and character, without assuming an analytical solution a priori, with no adjustable parameters, while accounting naturally for dislocation-dislocation image interactions. In comparisons to atomistic simulations using classical potentials, the maximum structure deviation is 6%, while the maximum line energy deviation is 0.019 eV/Angstrom. Several applications of our model are shown, including predicting the variation of structure with twist angle, and describing dislocation line tension and junction energies.

cond-mat.mtrl-sci↗

arXiv2018

Structural Disorder and Electronic Structure in Alloyed SrTiO3/SrFeO2.5 Compounds: A Theoretical Study

Many mixed ionic/electronic conductors (MIECs) applied in fuel cell electrodes can be considered as alloys between perovskite oxides and ordered oxygen vacancy compounds. For example, in the model MIEC (STF), low oxygen diffusion barrier exist in SrTiO3 lattice, when it has been mixed with SrFeO2.5 with intrinsic oxygen deficiency, the ionic conductivity can be greatly improved. Meanwhile, the electronic conductivity can be optimized by controlling the defect chemistry of the alloy. However, the configurational space is too large in such alloys so that it is difficult for direct atomic modeling, which hinders in-depth understanding and predictive modeling. In this work, we present a cluster expansion model to describe the energetics of the disordered SrTiO3/SrFeO2.5 alloy within the full solid solution composition space Sr(Ti1-x,Fex)O3-0.5x (0<x<1). Cluster expansion Monte Carlo simulations have been performed to search the lowest energy atomic configurations and investigate the origin of lattice disorder. With representations of realistic configurations, the electronic structures of such alloys at different stoichiometry have also been examined. We find that the band gap evolution with composition calculated using our atomic model is consistent with experiment measurement. Meanwhile, the band edge analysis elucidate that electronic conductivity within such alloy can be facilitated by the Fe/Ti cation disorder. Taking SrTiO3/SrFeO2.5 alloy as an example, the generalized computational framework applied here can be extended to other relevant MIEC material systems.

cond-mat.mtrl-sci↗

arXiv2017

Thermoelectric phonon glass electron crystal via ion beam patterning of silicon

Ion beam irradiation has recently emerged as a versatile approach to functional materials design. We show in this work that patterned defective regions generated by ion beam irradiation of silicon can create a phonon glass electron crystal (PGEC), a longstanding goal of thermoelectrics. By controlling the effective diameter of and spacing between the defective regions, molecular dynamics simulations suggest a reduction of the thermal conductivity by a factor of $\approx$20 is achievable. Boltzmann theory shows that the thermoelectric power factor remains largely intact in the damaged material. To facilitate the Boltzmann theory, we derive an analytical model for electron scattering with cylindrical defective regions based on partial wave analysis. Together we predict a figure of merit of ZT$\approx$0.5 or more at room temperature for optimally patterned geometries of these silicon metamaterials. These findings indicate that nanostructuring of patterned defective regions in crystalline materials is a viable approach to realize a PGEC, and ion beam irradiation could be a promising fabrication strategy.

cond-mat.mtrl-sci↗

arXiv2016

A generalized Debye-Peierls/Allen-Feldman model for the lattice thermal conductivity of low dimensional and disordered materials

We present a generalized model to describe the lattice thermal conductivity of low-dimensional (low-D) and disordered systems. The model is a straightforward generalization of the Debye-Peierls and Allen-Feldman schemes to arbitrary dimensions, accounting for low-D effects such as differences in dispersion, density of states, and scattering. Similar in spirit to the Allen-Feldman approach, heat carriers are categorized according to their transporting capacity as propagons, diffusons, and locons. The results of the generalized model are compared to experimental results when available, and equilibrium molecular dynamics simulations otherwise. The results are in very good agreement with our analysis of phonon localization in disordered low-D systems, such as amorphous graphene and glassy diamond nanothreads. Several unique aspects of thermal transport in low-D and disordered systems, such as milder suppression of thermal conductivity and negligble diffuson contributions, are captured by the approach.

cond-mat.mtrl-sci↗

arXiv2016

Screened-exchange density functional theory description of the electronic structure and phase stability of the chalcopyrite materials AgInSe$_2$ and AuInSe$_2$

We present a systematic assessment of the structural properties, the electronic density of states, the charge densities, and the phase stabilities of AgInSe$_2$ and AuInSe$_2$ using screened exchange hybrid density functional theory, and compare their properties to those of CuInSe$_2$. For AgInSe$_2$, hybrid density functional theory properly captures several experimentally measured properties, including the increase in the band gap and the change in the direction of the lattice distortion parameter $u$ in comparison to CuInSe$_2$. While the electronic properties of AuInSe$_2$ have not yet been experimentally characterized, we predict it to be a small gap ($\approx 0.15$ eV) semiconductor. We also present the phase stability of AgInSe$_2$ and AuInSe$_2$ according to screened-exchange density functional theory, and compare the results to predictions from conventional density functional theory, results tabulated from several online materials data repositories, and experiment (when available). In comparison to conventional density functional theory, the hybrid functional predicts phase stabilities of AgInSe$_2$ in better agreement with experiment: discrepancies in the calculated formation enthalpies are reduced by approximately a factor of three, from $\approx$ 0.20 eV/atom to $\approx$ 0.07 eV/atom, similar to the improvement observed for CuInSe$_2$. We further predict that AuInSe$_2$ is not a stable phase, and can only be present under non-equilibrium conditions.

cond-mat.mtrl-sci↗

arXiv2015

Towards a systematic assessment of errors in diffusion Monte Carlo calculations of semiconductors: case study of zinc selenide and zinc oxide

The fixed node diffusion Monte Carlo (DMC) method has attracted interest in recent years as a way to calculate properties of solid materials with high accuracy. However, the framework for the calculation of properties such as total energies, atomization energies, and excited state energies is not yet fully established. Several outstanding questions remain as to the effect of pseudopotentials, the magnitude of the fixed node error, and the size of supercell finite size effects. Here, we consider in detail the semiconductors ZnSe and ZnO and carry out systematic studies to assess the magnitude of the energy differences arising from controlled and uncontrolled approximations in DMC. The former include time step errors and supercell finite size effects for ground and optically excited states, and the latter include pseudopotentials, the pseudopotential localization approximation, and the fixed node approximation. We find that for these compounds, the errors can be controlled to good precision using modern computational resources, and that quantum Monte Carlo calculations using Dirac-Fock pseudopotentials can offer good estimates of both cohesive energy and the gap of these systems. We do however observe differences in calculated optical gaps that arise when different pseudopotentials are used.

cond-mat.mtrl-sci↗

arXiv2015

Phase Stability and Properties of Manganese Oxide Polymorphs: Assessment and Insights from Diffusion Monte Carlo

We present an analysis of the polymorphic energy ordering and properties of the rock salt and zincblende structures of manganese oxide using fixed node diffusion Monte Carlo (DMC). Manganese oxide is a correlated, antiferromagnetic material that has proven to be challenging to model from first principles across a variety of approaches. Unlike conventional density functional theory and some hybrid functionals, fixed node diffusion Monte Carlo finds the rock salt structure to be more stable than the zincblende structure, and thus recovers the correct energy ordering. Analysis of the site-resolved charge fluctuations of the wave functions according to DMC and other electronic structure descriptions give insights into elements that are missing in other theories. While the calculated band gaps within DMC are in agreement with predictions that the zincblende polymorph has a lower band gap, the gaps themselves overestimate reported experimental values.

cond-mat.mtrl-sci↗

arXiv2015

Lattice mismatch induced ripples and wrinkles in planar graphene/boron nitride superlattices

A continuum theory to describe periodic ripple formation in planar graphene/boron nitride superlattices is formulated. Due to the lattice mismatch between the two materials, it is shown that flat superlattices are unstable with respect to ripple formation of appropriate wavelengths. A competition between bending energy and transverse stretching energy gives rise to an optimal ripple wavelength that depends on the superlattice pitch. The optimal wavelengths predicted by the continuum theory are in good agreement with atomic scale total energy calculations previously reported in Nandwana and Ertekin, Nano Lett. 15 1468 (2015).

cond-mat.mtrl-sci↗