Random Alloy Research Articles

Electrical and Magnetic Properties of Rough Alloyed Interface of Fe/Co.

We investigated the electronic structure of rough interfaces in random Co/Fe  alloys, where cobalt (Co) was deposited on an iron (Fe) substrate with varying composition ratios. To model the rough surface, we utilized a coupled continuum equation as described by Huda. The electronic properties, specifically the density of states of these random alloys, were calculated using the augmented space recursion method in conjunction with the Linear Muffin-tin Orbital (LMTO) Method. Furthermore, we analyzed the magnetic and electronic properties derived from the calculated density of states.

Random alloy growth of AlAs0.08Sb0.92 on GaSb under high Group-V flux condition

The growth of AlAsxSb1-x epilayers with x < 0.1 is crucial for various optoelectronic device applications. However, achieving the desired alloy composition and lattice-matched condition remains challenging. In this study, the epitaxial growth of the random alloy AlAsSb on GaSb was investigated using molecular beam epitaxy. The objective was to determine the optimal growth condition to obtain AlAs0.08Sb0.92 on GaSb (lattice-matched to GaSb) with a high growth rate and under a high group-V/III beam equivalent pressure (BEP) ratio. The growth parameters, including the group-V/III BEP ratio, growth rate, and temperature, were studied to monitor the change in the structural properties of the AlAsSb epilayer. It was shown that the As incorporation in AlAsSb was higher than expected at high growth rate and under high Sb BEP condition. The results demonstrated that increasing the growth temperature while decreasing the As BEP did not significantly improve the crystal quality where the optimization of group-V/III BEP ratio and As BEP is effective to obtain AlAs0.08Sb0.92 on GaSb and enhance the crystal quality. The findings provide valuable insights into the growth dynamics of AlAsSb to achieve high quality and lattice-matched epilayers grown on GaSb which is well-suited for a range of optoelectronic applications.

(GaAs/InAs)–GaAsSb digital alloy type-II superlattice for extended short-wavelength infrared detection

GaInAs–GaAsSb type-II superlattices (T2SLs) on an InP substrate are promising candidates for an optical absorption layer in the extended short-wavelength region (2–3 μm), offering more flexibility in designing a cutoff wavelength compared to strained GaInAs bulk material. However, T2SL-based photodetectors inherently suffer from lower quantum efficiency (QE) due to the reduced overlap of the wavefunctions of the conduction and valence bands in the optical matrix element of the T2SL. To improve QE, a (GaAs/InAs)–GaAsSb digital alloy T2SL, which replaces the GaInAs random alloy layer in the GaInAs–GaAsSb T2SL with a GaAs/InAs digital alloy, has been proposed recently by an empirical tight-binding calculation. This paper presents a demonstration of a fabricated photodetector using the (GaAs/InAs)–GaAsSb digital alloy grown on an InP substrate by molecular beam epitaxy and shows that the average QE in the wavelength region of 2.3–2.6 μm is approximately 1.6 times higher than that of a conventional GaInAs–GaAsSb T2SL photodetector. Furthermore, the dark-current density of the digital alloy photodetector is lower than that of the GaInAs–GaAsSb T2SL photodetector despite having a longer cutoff wavelength.

Molecular beam epitaxial growth and physical properties of AlN/GaN superlattices with an average 50% Al composition

Abstract We report molecular beam epitaxial growth and electrical and ultraviolet light emitting properties of (AlN)m/(GaN)n superlattices (SLs), where m and n represent the numbers of monolayers. Clear satellite peaks observed in XRD 2θ-ω scans and TEM images evidence the formation of clear periodicity and atomically sharp interfaces. For (AlN)m/(GaN)n SLs with an average Al composition of 50%, we have obtained an electron density up to 4.48×1019 cm-3 and a resistivity of 0.002 Ω·cm, and a hole density of 1.83×1018 cm-3 with a resistivity of 3.722 Ω·cm, both at room temperature. Furthermore, the (AlN)m/(GaN)n SLs exhibit a blue shift for their photoluminescence peaks, from 403 nm to 318 nm as GaN reduced from n=11 to n=4 MLs, reaching the challenging UVB wavelength range. The results demonstrate that the (AlN)m/(GaN)n SLs have the potential to enhance the conductivity and avoid the usual random alloy scattering of the high-Al-composition ternary AlGaN, making them promising functional components in both UVB emitter and AlGaN channel high electron mobility transistor applications.

The tensile behaviour of non-equi-atomic configurations of multiple elemental alloys: molecular dynamics based study

This article aims to study the effect of lattice distortion on the mechanical behavior of equi-atomic and non-equi-atomic configurations of high entropy alloys. Molecular dynamics-based simulations were performed with an embedded atomic method force field. Random alloy configuration of multiple elemental alloys (MEAs) was developed along with average atom (A-atom) configurations by modifying the embedded atom potential. The non-equi-atomic configuration of MEAs was generated by varying the contribution of Cr, Co, Fe, Cu, Ni, and Cr in pairs and all together. It was predicted from the simulations that the deformation governing mechanism, as well as the tensile strength of high entropy alloys, can be tailored by switching from equi-atomic to non-equi-atomic configurations of high entropy alloys. Increasing the composition of Cr, Fe, and Ni helps enhance the tensile strength and Young's modulus of the high entropy alloy, which is even higher than equi-atomic configurations. Partial Shockley dislocations, in conjunction with the phase change from fcc to hcp, primarily govern the deformation in the non-equi-atomic composition of MEAs. The tensile behaviour of MEAs was directly associated with the distortion present in the lattice, which was quantified with the help of the radial distribution function. It was revealed from the simulations that lattice distortion present in the random alloy configuration helps in improving the ductility of material by early onset of dislocation emission. A higher value of lattice distortion also increases the gap between the peak stress values in A-atom and random alloy configurations. The article will help develop high-entropy alloys for broader space, nuclear, defense, and energy generation applications.

Machine learning-based prediction of FeNi nanoparticle magnetization

This work proposes a computationally efficient approach for estimating the magnetization of Fe0.7Ni0.3 body-centered cubic (bcc) nanoparticles (NPs) at room temperature using machine-learning algorithms, in terms of the average magnetic moment per atom, ⟨μ⟩. The magnetization data of isolated NPs were generated using atomistic spin dynamics (ASD) simulations for various nanoparticle shapes (cubes, spheres, octahedra, cones, cylinders, ellipsoids, flakes, and pyramids, with or without nanovoids) and FeNi distributions (random, core-shell, onion, sandwich, and Janus with different boundary planes). More than 1600 NPs were created and split into training and testing sets (70%-30% split), with features including the number of Ni/Fe surface and core atoms, potential energy distributions, pair correlation functions, and coordination distributions. Several machine-learning algorithms, including Random Forest (RF), Elastic Net, Support Vector Regression (SVR), and Gradient Boosting Regression (CatBoost), were applied to predict the average magnetic moment per atom of these NPs. The best-performing models, CatBoost and RF, achieved R2 scores of up to 0.86, demonstrating their accuracy in predicting NP magnetization. Feature analysis highlighted the significance of the interface between Fe and Ni clusters, Fe-Fe interactions, and the presence of Fe on the surface as critical contributors to overall magnetization. Random alloy spherical NPs without porosity exhibited the highest ⟨μ⟩ ∼ 1.6μB due to reduced Ni-Ni interactions. Applying machine-learning methods significantly reduces computational time and memory requirements compared to traditional ASD simulations. This allows for rapid prediction of NPs with desired magnetic properties, making them suitable for various technological applications.

Monolayer-scale AlN/GaN digital alloys grown by plasma-assisted molecular beam epitaxy

The efficiency of usual AlGaN based deep ultraviolet light-emitting devices is still quite low. The difficulties are basically originated from the fundamental material properties of AlGaN. This work has adopted monolayer-scale (AlN)m/(GaN)n ordered digital alloys (DAs) as alternatives to AlGaN random alloys, m and n are the numbers of monolayers. X-ray diffraction scans have demonstrated clear satellite peaks, verifying good periodicity of AlN/GaN DAs grown by molecular beam epitaxy (MBE), and transmission electron microscopy results have revealed atomically sharp and smooth interfaces and quite precise m:n values agreeing well with designs. The electron densities of Si-doped (AlN)m/(GaN)n DAs with high equivalent Al compositions are significantly higher than those of conventional AlGaN:Si random alloys grown in the same MBE system. Si dopant ionization energies in DAs are only 2–5 meV, much lower than that for usual random alloys. The red shift of the light emission for DAs with thinner AlN barriers has suggested strong coupling between the GaN wells and thus formation of a miniband in a vertical direction. The results have demonstrated the potential of the (AlN)m/(GaN)n DAs as electronically functional alternatives for various device applications.

Chemical short-range order increases the phonon heat conductivity in a refractory high-entropy alloy

We study the effects of the chemical short-range order (SRO) on the thermal conductivity of the refractory high-entropy alloy HfNbTaTiZr using atomistic simulation. Samples with different degrees of chemical SRO are prepared by a Monte Carlo scheme. With increasing SRO, a tendency of forming HfTi and TiZr clusters is found. The phonon density of states is determined from the velocity auto-correlation function and chemical SRO modifies the high-frequency part of the phonon density of states. Lattice heat conductivity is calculated by non-equilibrium molecular dynamics simulations. The heat conductivity of the random alloy is lower than that of the segregated binary alloys. Phonon scattering by SRO precipitates might be expected to reduce scattering times and, therefore, decrease thermal conductivity. We find that, in contrast, due to the increase of the conductivity alongside SRO cluster percolation pathways, SRO increases the lattice heat conductivity by around 12 %. This is expected to be a general result, extending to other HEAs.

Basics of the reaction kinetics on metallic alloys.

Kinetics of heterogeneous catalytic reactions are often complicated by various factors, and from the perspective of statistical physics the development of the corresponding models is frequently challenging especially in the case of practically important alloy catalysts. To extend the basics in this area, I use a generic kinetic model of N_{2} formation inthe NO reaction with such species as CO or H_{2}. The focus is onthe reaction on the surface of a bimetallic alloy with low integral fraction of one of the metals so that the alloy is formed only at the surface. The main goal is to illustrate the specifics of the reaction kinetics and to clarify the accuracy of various approximations which are often inevitable for the analysis of such systems. The key results are as follows. (i) In the baseline one-metal case with the Langmuir-type equations, the model predicts the existence of the optimal adsorbate binding energy corresponding to the maximal reaction rate. (ii) With suitable substitution of the symbols, the equations employed for a uniform surface [item (i)] can be used for the mean-field description of reaction on the surface of a random alloy. In particular, the maximum in the dependence of the reaction rate on the binding energy is converted to the maximum with respect to the alloy composition. (iii) The reaction kinetics on the random-alloy surface have been described exactly. The corresponding maximum in the reaction rate is lower and somewhat smeared compared to that predicted in the mean-field approximation for an alloy or for the optimal monometallic catalyst. (iv) The reaction kinetics have been scrutinized also in the case of two-dimensional (2D) segregation of metal atoms at the surface in the limits of slow and rapid adsorbate diffusion between the spots. The kinetics are shown to be qualitatively different in these limits and also compared to the random-alloy case. (v) The thermodynamic criteria for 2D segregation of metal atoms at the surface have been derived as well.

Bimetallic Catalysts in Acetylene Semi‐Hydrogenation: Conceptual Advances and Challenges

The hydrogenation of acetylene to ethylene is of great industrial interest. Achieving both high selectivity and conversion of ethylene from acetylene via semi‐hydrogenation is quite challenging. Bimetallic catalysts offer opportunities to selectively control reaction pathways by altering the electronic and geometric properties of active sites on the catalyst surface. Recent advancements in the synthesis of bimetallic catalysts enabled the creation of random alloys, intermetallics, segregated structures, or single‐site alloys with precision. These catalysts could be tailored for semi‐hydrogenation of acetylene by tuning the features including adsorption energy, active site isolation, and the d‐band center. Modern machine learning tools are also helpful for catalyst design. In this article, an overview of the design aspects of bimetallic catalysts, advances and challenges involved in acetylene semi‐hydrogenation, has been presented.

A comprehensive investigation of alloying elements on site preferences, elastic properties and electronic structure of Mg17Al12 by first-principles calculations

The effect of elemental doping on the site preference, elastic properties and electronic structure of Mg17Al12 has been systematically investigated by first-principles calculations. And twenty-seven elements (Li, Na, K, Ca, Sc, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, Ga, Ge, Sr, Y, Zr, Ag, Cd, In, Sn, Sb, Pb, Bi and La) are considered in this study. The calculations of substitution formation energies indicate that the alkali metal (Li), alkaline earth (Ca, Sr) and rare earth (Sc, Y, La) group elements and Ti, Zr favor to occupy Mg sites, and transition group (Fe, Co, Ni, Cu, Ag, Zn, Cd) elements and Ga, Ge, Sn, Sb prefer to occupy Al site, while Na, K, V, Cr, Mn, In, Pb and Bi are unstable in Mg17Al12 phase. Meanwhile, the results of phonon dispersion curves for the preferentially doped systems show that all doped structures are dynamically stable except for Sr, La and Sn doped systems. The elastic constants indicate that all preferential doping models are mechanically stable, and solute atoms with high bulk modulus lead to an increase in the bulk modulus of Mg17Al12 phase. Simultaneously, the calculated shear modulus/bulk modulus ratio (G/B), Poisson's ratio (v) and Cauchy's pressure (C‾12‐C‾44) indicate that the ductility of doped systems is better than Mg17Al12 alloy. All structures are elastic anisotropic, while the doping of Fe, Co and Ni reduces the degree of anisotropy of Mg17Al12 phase. Furthermore, the electronic structures show a strong hybridization between the p-orbitals of Mg and Al and the d-orbitals of alkaline earth, rare earth and Zr elements, resulting in higher structural stability. Finally, the adsorption behavior of O atom on Mg17Al12(110) surface and the structural stability, lattice constants, and elastic modulus of Mg34Al24-xZnx random solid solution alloys are investigated.

Carrier Recombination in Nitride-Based Light-Emitting Devices: Multiphonon Processes, Excited Defects, and Disordered Heterointerfaces.

We study recombination processes in nitride LEDs emitting from 270 to 540 nm with EQE ranging from 4% to 70%. We found a significant correlation between the LEDs' electro-optical properties and the degree of nanomaterial disorder (DND) in quantum wells (QWs) and heterointerfaces. DND depends on the nanoarrangement of domain structure, random alloy fluctuations, and the presence of local regions with disrupted alloy stoichiometry. The decrease in EQE values is attributed to increased DND and excited defect (ED) concentrations, which can exceed those of Shockley-Read-Hall defects. We identify two mechanisms of interaction between EDs and charge carriers that lead to a narrowing or broadening of electroluminescence spectra and increase or decrease EQE, respectively. Both mechanisms involve multiphonon carrier capture and ionization, impacting EQE reduction and efficiency droop. The losses caused by these mechanisms directly affect EQE dependencies on current density and the maximum EQE values for LEDs, regardless of the emission wavelength. Another manifestation of these mechanisms is the reversibility of LED degradation. Recombination processes vary depending on whether QWs are within or outside the space charge region of the p-n junction.

Machine learned environment-dependent corrections for a spds∗ empirical tight-binding basis

Abstract Empirical tight-binding (ETB) methods have become a common choice to simulate electronic and transport properties for systems composed of thousands of atoms. However, their performance is profoundly dependent on the way the empirical parameters were fitted, and the found parametrizations often exhibit poor transferability. In order to mitigate some of the the criticalities of this method, we introduce a novel Δ-learning scheme, called MLΔTB. After being trained on a custom data set composed of ab-initio band structures, the framework is able to correlate the local atomistic environment to a correction on the on-site ETB parameters, for each atom in the system. The converged algorithm is applied to simulate the electronic properties of random GaAsSb alloys, and displays remarkable agreement both with experimental and ab-initio test data. Some noteworthy characteristics of MLΔTB include the ability to be trained on few instances, to be applied on 3D supercells of arbitrary size, to be rotationally invariant, and to predict physical properties that are not exhibited by the training set.

Role of tin clustering in band structure and thermodynamic stability of GeSn by atomistic modeling

Synthesis of device-quality GeSn materials with higher Sn compositions is hindered by various factors, such as Sn segregation, clustering, and short-range ordering effects. In the present work, the impact of the clustering of Sn atoms in a GeSn semiconductor alloy was studied by density functional theory using SG15 pseudopotentials in a Synopsys QuantumATK tool, where the thermodynamic stability, effective band structure, indirect and direct bandgaps, and density of states (DOS) were computed to highlight the difference between a cluster-free random GeSn alloy and a GeSn alloy with Sn–Sn clusters. A 54-atom bulk Ge1–xSnx (x = 3.71%–27.77%) supercell was constructed with cluster-free and a first nearest neighbor Sn–Sn clustered GeSn alloy at each composition for this work. Computation using the generalized gradient approximation exchange-correlation functional showed that the thermodynamic stability of GeSn was reduced due to the clustering of Sn, which increased the formation energy of the GeSn alloys by increasing the Hartree potential energy and exchange-correlation energy. Moreover, with the effective band structure of the GeSn material at a Sn composition of ∼22%, both direct (Eg,Γ) and indirect (Eg,L) bandgaps decreased by a large margin of 40.76 and 120.17 meV, respectively, due to Sn–Sn clustering. On the other hand, Eg,Γ and Eg,L decrease is limited to 0.5 and 12.8 meV, respectively, for Sn composition of ∼5.6%. Similar impacts were observed on DOS, in an independent computation without deducing from the electronic band structure, where the width of the forbidden band reduces due to the clustering of Sn atoms in GeSn. Moreover, using the energy bandgaps of GeSn computed with the assumption of it being a random alloy having well-dispersed Sn atoms needs revision by incorporating clustering to align with the experimentally determined bandgap. This necessitates incorporating the effect of Sn atoms clustered together at varying distributions based on experimental characterization techniques such as atom probe tomography or extended x-ray absorption fine structure to substantiate the energy bandgap of the GeSn alloy at a particular composition with precision. Hence, considering the effect of Sn clusters during material characterization, beginning with the accurate energy bandgap characterization of GeSn would help in mitigating the effect of process variations on the performance characteristics of GeSn-based group IV electronic and photonic devices such as varying leakage currents in transistors and photodiodes as well as the deviation from the targeted wavelength of operation in lasers and photodetectors.

Group IV topological quantum alloy and the role of short-range order: the case of Ge-rich Ge1–xPbx

Despite the explosion of interest in topological materials over the last decades, their applications remain limited due to challenges in growth and incorporation with today’s microelectronics. As a potential bridge to close this gap, we investigate the group-IV alloy Ge1–xPbx, in the Ge-rich condition using density functional theory and show that relatively low concentrations of Pb (~9.4%) can lead to a topological phase transition. Furthermore, the calculation of the Z2 invariant for both the random alloy and the alloy with short-range order (SRO) indicate that the topological phase of the material can be directly modified by the degree of SRO. These findings are understood in terms of local structural relaxation, which decreases the bandgap in the random alloy. However, in the SRO case, the mutual avoidance of Pb leads to minimal structural relaxation, alleviating strain. Our findings not only highlight the emerging importance of SRO in alloy properties but also indicate the possibility of constructing topological interfaces between materials of identical composition (and nominally identical structure). Moreover, they uncover a viable avenue toward the monolithic integration of quantum materials with today’s semiconductor industry.

Nanoindentation into a bcc high-entropy HfNbTaTiZr alloy-an atomistic study of the effect of short-range order.

The plastic response of the Senkov HfNbTaTiZr high-entropy alloy is explored by means of simulated nanoindentation tests. Both a random alloy and an alloy with chemical short-range order are investigated and compared to the well understood case of an elementary Ta crystal. Strong differences in the dislocation plasticity between the alloys and the elementary Ta crystal are found. The high-entropy alloys show only little relaxation of the indentation dislocation network after indenter retraction and only negligible dislocation emission into the sample interior. Short-range order-besides making the alloy both stiffer and harder-further increases the size of the plastic zone and the dislocation density there. These features are explained by the slow dislocation migration in these alloys. Also, the short-range-ordered alloy features no twinning plasticity in contrast to the random alloy, while elemental Ta exhibits twinning under high stress but detwins considerably under stress relief. The results are in good qualitative agreement with our current knowledge of plasticity in high-entropy alloys.

Multivariate Gaussian process surrogates for predicting basic structural parameters of refractory non-dilute random alloys

Refractory non-dilute random alloys consist of two or more principal refractory metals with complex interactions that modify their basic structural properties such as lattice parameters and elastic constants. Atomistic simulations (ASs) are an effective method to compute such basic structural parameters. However, accurate predictions from ASs are computationally expensive due to the size and number of atomistic structures required. To reduce the computational burden, multivariate Gaussian process regression (MVGPR) is proposed as a surrogate model that only requires computing a small number of configurations for training. The elemental atom percentage in the hyper-spherical coordinates is demonstrated to be an effective feature for surrogate modeling. An additive approximation of the full MVGPR model is also proposed to further reduce computations. To improve surrogate accuracy, active learning is used to select a small number of alloys to simulate. Numerical studies based on AS data show the accuracy of the surrogate methodology and the additive approximation, as well as the effectiveness and robustness of the active learning for selecting new alloy designs to simulate.

Digital Alloy-Grown InAs/GaAs Short-Period Superlattices with Tunable Band Gaps for Short-Wavelength Infrared Photodetection.

The InGaAs lattice-matched to InP has been widely deployed as the absorption material in short-wavelength infrared photodetection applications such as imaging and optical communications. Here, a series of digital alloy (DA)-grown InAs/GaAs short-period superlattices were investigated to extend the absorption spectral range. The scanning transmission electron microscopy, high-resolution X-ray diffraction, and atomic force microscopy measurements exhibit good material quality, while the photoluminescence (PL) spectra demonstrate a wide band gap tunability for the InGaAs obtained via the DA growth technique. The photoluminescence peak can be effectively shifted from 1690 nm (0.734 eV) for conventional random alloy (RA) InGaAs to 1950 nm (0.636 eV) for 8 monolayer (ML) DA InGaAs at room temperature. The complete set of optical constants of DA InGaAs has been extracted via the ellipsometry technique, showing the absorption coefficients of 398, 831, and 1230 cm-1 at 2 μm for 6, 8, and 10 ML DA InGaAs, respectively. As the period thickness increases for DA InGaAs, a red shift at the absorption edge can be observed. Furthermore, the simulated band structures of DA InGaAs via an environment-dependent tight binding model agree well with the measured photoluminescence peaks, which is advantageous for a physical understanding of band structure engineering via the DA growth technique. These investigations and results pave the way for the future utilization of the DA-grown InAs/GaAs short-period superlattices as a promising absorption material choice to extend the photodetector response beyond the cutoff wavelength of random alloy InGaAs.

The effects of Escaig stress and solution concentration on the interaction between screw dislocation and coherent twin boundary in random alloys

The effect of Escaig stress as well as the solution concentration on the interaction between screw dislocation and coherent twin boundary (CTB) in random Ni–Co alloys is investigated using molecular dynamics (MD) simulations. Our results show that Co concentration would promote the screw dislocation-CTB reaction from absorption to transmission. And Escaig stress can influence the critical interaction shear stress (CISS) depending on its magnitude and direction, even changing the mode from transmission to absorption, which is not recognized before. Such phenomenon is well interpreted by modifying the traditional criterion through considering the differences between the average stacking fault energy (SFE) and elastic repulsion within the dislocation, which suggests that the repulsion under specific Escaig stress can better assess the reaction mechanism. Our results provide new insights in understanding the high-strength properties of nanotwinned face-centered cubic (FCC) metals or alloys.

Screw dislocation core interaction with C or Nb in [formula omitted]-TiAl: A multiscale study

The solute strengthening caused by the interaction between dislocations and solutes in random solid solution alloys has already been investigated widely provided that the solutes outside the dislocation core interact through nominally elastic interactions. However, the topological variation of dislocation core due to the solute segregation can influence the strengthening of system. We investigate the dislocation core reconstruction with solute C and Nb and their effects on dislocation glide in γ-TiAl by multiscale QM/MM scheme due to the long-range elastic field of a dislocation. The solutes doping in dislocation core region can influence the core energy and eventually cause a violation of Frank’s rule. The contribution analysis of lattice distortion and chemical effect between dislocations and solutes is further investigated. The energy barriers of constriction and transition state in pure γ-TiAl and under solutes environment in the process of external stress reveal electronically the effects of alloying elements and heterogeneous mechanisms on cross-slip process. The carbon diffusion along and across dislocation core by the CI-NEB method are also investigated.