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At least 685 records · Page 38

Doping Effects on the Ductility of a Lightweight Refractory High-Entropy Alloy: Grain Boundary and Bulk Lattice Aspects

Doping elements in small amounts often segregate to grain boundaries (GBs) in alloys and can significantly impact mechanical properties and performance. Refractory high-entropy alloys (RHEAs) are known for their poor ductility, especially at low temperatures. Promoting GB cohesion through segregation can be an effective approach to mitigate embrittlement. Here, in this study, first-principles density functional theory (DFT) calculations were performed to examine the effects of important interstitial dopants (O, B, C, and N) and substitutional dopants (Cr, Y, La, and Ce) on the Σ5(310) [001] tilt GB of a lightweight RHEA Nb 32.5 Ti 27.5 Mo 22.5 Ta 12.5 Hf 2.5 Zr 2.5 . The DFT calculations reveal that certain dopants, such as B, C, Cr, N, and Y, exhibit favorable GB strengthening effects by improving bonding interactions with the bulk alloy. The impact of doping on the ductility parameter of the bulk lattice, defined as the ratio of surface energy to unstable stacking fault energy for the {110} <111> slip system, was also studied; and the results show that doping reduces the intrinsic ductility of the alloy, decreasing the D-parameter from 2.90 to 2.55, depending on the specific dopant. The present findings provide a foundational understanding at atomic level of the effect of representative dopants on mechanical properties of RHEAs and can be used to guide future alloy design for improved mechanical properties.

deformation charge density↗

Multi-objective materials bayesian optimization with active learning of design constraints: Design of ductile refractory multi-principal-element alloys

We report Bayesian Optimization (BO) has emerged as a powerful framework to efficiently explore and exploit materials design spaces. To date, most BO approaches to materials design have focused on the materials discovery problem as if it were a single expensive-to-query ‘black box’ in which the target is to optimize a single objective (i.e., material property or performance metric). Also, such approaches tend to be constraint agnostic. Here, we present a novel multi-information BO framework capable of actively learning materials design as a multiple objectives and constraints problem. We demonstrate this framework by optimally exploring a Refractory Multi-Principal-Element Alloy (MPEA) space, here specifically, the system Mo-Nb-Ti-V-W. The MPEAs are explored to optimize two density-functional theory (DFT) derived ductility indicators (Pugh’s Ratio and Cauchy pressure) while learning design constraints relevant to the manufacturing of high-temperature gas-turbine components. Alloys in the BO Pareto-front are analyzed using DFT to gain an insight into fundamental atomic and electronic underpinning for their superior performance, as evaluated within this framework.

36 MATERIALS SCIENCE↗

Theory-guided design of duplex-phase multi-principal-element alloys

Density-functional theory (DFT) is used to identify phase-equilibria in multi-principal-element and high-entropy alloys (MPEAs/HEAs), including duplex-phase and eutectic microstructures. Here, a combination of composition-dependent formation energy and electronic-structure-based ordering parameters were used to identify a transition from FCC to BCC favoring mixtures, and these predictions experimentally validated in the Al-Co-Cr-Cu-Fe-Ni system. A sharp crossover in lattice structure and dual-phase stability as a function of composition were predicted via DFT and validated experimentally. The impact of solidification kinetics and thermodynamic stability was explored experimentally using a range of techniques, from slow (castings) to rapid (laser remelting), which showed a decoupling of phase fraction from thermal history, i.e., phase fraction was found to be solidification rate-independent, enabling tuning of a multi-modal cell and grain size ranging from nanoscale through macroscale. Strength and ductility tradeoffs for select processing parameters were investigated via uniaxial tension and small-punch testing on specimens manufactured via powder-based additive manufacturing (directed-energy deposition). This work establishes a pathway for design and optimization of next-generation multiphase superalloys via tailoring of structural and chemical ordering in concentrated solid solutions.

36 MATERIALS SCIENCE↗

Mechanisms and site requirements for NO and NH 3 oxidation on Cu/SSZ-13

Two series of Cu/SSZ-13 catalysts were synthesized via aqueous solution and solid-state ion exchange using SSZ-13 supports of varying Si/Al ratios. The isolated and multinuclear Cu content of these catalysts were determined by H 2 temperature programmed reduction (H 2 -TPR). Multinuclear Cu in these catalysts, including in situ Cu- dimers formed from ZCu II OH coupling and permanent CuO clusters, are active species for dry NO oxidation. NH 3 oxidation on these catalysts follows an internal SCR (i-SCR) mechanism, i.e., a portion of NH 3 is first oxidized to NO, then NO is selectively reduced by the remaining NH 3 to N 2 . NH 3 oxidation displays distinct kinetic behavior below ~300 °C and above ~400 °C. At low temperature the results indicate that NH 3 -solvated mobile Cu-ions are the active centers. CuO clusters, when present, also contribute to the low temperature activity by catalyzing NH 3 oxidation to NO. At high temperature, in situ Cu-dimers and CuO clusters catalyze NH 3 oxidation to NO, and isolated Cu-ions catalyze SCR to realize the cascade turnovers. For both NO and NH 3 oxidation, Cu-dimers balanced by framework charges of close proximity appear to be more active than Cu-dimers balanced by distant framework charges. However, the former Cu-dimers are less stable than the latter and tend to split into monomers in the presence of vicinal Brønsted acid sites. Via density functional theory (DFT) calculations, the i-SCR mechanism for low temperature NH 3 oxidation, i.e., the energetic favorability for the involvement of the NO intermediate, is justified. Furthermore, the DFT results also agree with experimental data that the formation of Cu-dimers from ZCu II OH dimerization is essential for NH 3 oxidation at high temperature.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Improving stability of ALD ZrN thin film coatings over U-Mo dispersion fuel

Atomic layer deposition (ALD) of ZrN is a candidate technology for coating U-Mo dispersion fuel as a diffusion barrier coating. During the early development stages of the coating the ZrN deposition showed to be mechanically unstable and ultimately resulted in spalling. Based on experimental outcomes it was found that instabillity can be eliminated through the introduction of a thin amorphous (a) Al 2 O 3 interlayer coating deposited in between the ~1-μm thick ZrN and the U-Mo. substrate. To elucidate these findings simulations were performed with density functional theory (DFT) to measure work of adhesions at different interfaces while finite element modeling (FEM) was performed to measure the residual stress distribution. DFT indicated that the ZrN coating deposited over (a)-Al 2 O 3 is ~2.5 times stronger when compared to direct deposition over U or UO 2 substrate. While calculations from FEM recognized; (1) large stress concentrations can originate from the irregularly distributed native surface oxides (UO 2 ) over U-Mo and (2) stress concentrations can be reduced if those surface UO 2 can be modified to a uniform layer (achieved after application of a 8 nm (a)-Al 2 O 3 interlayer). These results provided explanations and confirmed the role played by interlayer in eliminating the original mechanical instability of the ZrN.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Computational synthesis of 2D materials: A high-throughput approach to materials design

2D materials find promising applications in next-generation devices, however, large-scale, low-defect, and reproducible synthesis of 2D materials remains a challenging task. Here, to assist in the selection of suitable substrates for the synthesis of as-yet hypothetical 2D materials, we have developed an open-source high-throughput workflow package, Hetero2d, that searches for low-lattice mismatched substrate surfaces for any 2D material and determines the stability of these 2D-substrate heterostructures using density functional theory (DFT) simulations. Hetero2d automates the generation of 2D-substrate heterostructures, the creation of DFT input files, the submission and monitoring of computational jobs on supercomputing facilities, and the storage of relevant parameters alongside the post-processed results in a MongoDB database. We demonstrate the capability of Hetero2d in identifying stable 2D-substrate heterostructures for four 2D materials, namely 2H-MoS 2 , 1T- and 2H-NbO 2 , and hexagonal-ZnTe, considering 50 cubic elemental substrates. We find Cu, Hf, Mn, Nd, Ni, Pd, Re, Rh, Sc, Ta, Ti, V, W, Y, and Zr substrates sufficiently stabilize the formation energies of these 2D materials, with binding energies in the range of ~0.1–0.6 eV/atom. Upon examining the z-separation, the charge transfer, and the electronic density of states at the 2D-substrate interface, we find a covalent type bonding at the interface which suggests that these substrates can be used as contact materials for the 2D materials. Hetero2d is available on GitHub as an open-source package under the GNU license.

36 MATERIALS SCIENCE↗

Development of an interatomic potential for the W–Ta system

A physics-inspired, data-driven interatomic potential framework for multi-element system is presented. This potential is based on the generalization of the embedded atom method potential and systematically incorporates two-, three- and many-body effects. Different atomic environments are described by atom-centered Gaussian basis sets which provides sufficient flexibility to capture diverse atomic environments and allows for easy optimization of the free parameters. An interatomic potential model for the tungsten–tantalum (W–Ta) system is developed using this framework by training on data from ab initio density functional theory (DFT) calculations. The potential is thoroughly tested at various compositions by comparing bulk and defect properties from experimental and DFT data. It is shown that the potential predicts the elastic constants, defect properties, such as vacancy and interstitial formation energies, core structures of dislocations, and melting points for both pure and tantalum and tungsten with an accuracy comparable to other single element machine learning based potentials. In conclusion, the potential model is used to investigate the formation energies of ordered alloys and vacancy formation energies for chemically random W–Ta alloys.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Revisiting point defect thermodynamics in group IVB and VB transition metal carbides

We present a comprehensive re-examination of point defect thermodynamics in group IVB and VB transition metal carbides (TMCs) with the rocksalt structure using a combination of density functional theory (DFT) calculations and a statistical mechanical Wagner-Schottky model within the canonical ensemble. The most stable configurations of point defects were discovered using basin-hopping global optimization, driven by either a machine learning interatomic potential (MLIP) or DFT. A key finding is the identification of previously unreported dicarbon antisites—a C–C dimer occupying a metal site—as the structural (constitutional) defects on the carbon-rich side of stoichiometry in all group IVB and VB TMCs except TaC. Furthermore, dicarbon antisite-containing thermal defect complexes, such as quadruple and interbranch defects, can dominate in TMCs under specific stoichiometric and temperature conditions. In conclusion, by incorporating dicarbon antisites into the defect landscape, this work provides a revised understanding of the thermodynamics of point defects in TMCs.

Carbides↗

MechElastic: A Python library for analysis of mechanical and elastic properties of bulk and 2D materials

We report the MechElastic Python package evaluates the mechanical and elastic properties of bulk and 2D materials using the elastic coefficient matrix ( C ij ) obtained from any ab-initio density-functional theory (DFT) code. The current version of this package reads the output of VASP, ABINIT, and Quantum Espresso codes (but it can be easily generalized to any other DFT code) and performs the appropriate post-processing of elastic constants as per the requirement of the user. This program can also detect the input structure's crystal symmetry and test the mechanical stability of all crystal classes using the Born-Huang criteria. Various useful material-specific properties such as elastic moduli, longitudinal and transverse elastic wave velocities, Debye temperature, elastic anisotropy, 2D layer modulus, hardness, Pugh's ratio, Cauchy's pressure, Kleinman's parameter, and Lame's coefficients, can be estimated using this program. Another existing feature of this program is to employ the ELATE package (2016) [29] and plot the spatial variation of several elastic properties such as Poisson's ratio, linear compressibility, shear modulus, and Young's modulus in three dimensions. Further, the MechElastic package can plot the equation of state (EOS) curves for energy and pressure for a variety of EOS models such as Murnaghan, Birch, Birch-Murnaghan, and Vinet, by reading the inputted energy/pressure versus volume data obtained via numerical calculations or experiments. This package is particularly useful for the high-throughput analysis of elastic and mechanical properties of materials.

2D materials↗

Antimony stable isotope fractionation during adsorption onto birnessite: A molecular perspective from X-ray absorption spectroscopy and density functional theory

Sorption of antimony (Sb) onto birnessite significantly influences the fate of Sb in oceanic and terrestrial environments and fractionates Sb isotopes. Nevertheless, little is known about Sb isotopic fractionation during its adsorption on birnessite. Here, in this study, we show the value of Δ 123 Sb adsorbed-aqueous increases from −0.398 to −0.332 ‰ in 1 h and then decreases and stabilizes at −0.384 ‰ in 72 h. The enrichment of the light Sb isotope is predominantly due to the distortion of the octahedral symmetry. X-ray absorption spectroscopy results indicate Sb first forms a double-corner-sharing complex on birnessite and then transforms to a double-edge-sharing complex during adsorption. The optimized bond distances for double-corner-sharing (3.37 Å) and double-edge-sharing (2.90 Å) complexes calculated using density functional theory (DFT) fits well with the structure (3.41 and 3.00 Å) revealed by X-ray absorption spectroscopy, respectively. The fractionation derived from reduced partition function ratios calculated using DFT aligns well with the experimental results. Therefore, the variation in Sb isotopic fractionation during adsorption is attributed to the evolving structure of Sb complexes on birnessite. Our results demonstrate the isotopic fractionation of Sb during adsorption on birnessite and provide a molecular-scale understanding of Sb behavior, contributing to the correct reconstruction of the Sb isotope composition of ancient seawater using ferromanganese crusts and nodules, and efforts to trace Sb migration in epigenetic mining environments.

Adsorption↗

The u 3 si 2 -H system

U 3 Si 2 is of interest to the nuclear industry as a candidate fuel material due to its high uranium density and high thermal conductivity. However, it has been observed to react with hydrogen, resulting in material decrepitation. As a result, it is important to understand the thermodynamics of the U 3 Si 2 -H system. In this study, the thermodynamics of the hydrogen absorption reaction of USi were determined experimentally using Sievert’s gas absorption and related to crystallographic evolution with hydrogen content using X-ray diffraction. Experimentally-determined thermodynamic parameters were compared with results from density functional theory modeling. Results from this study were also compared with those determined in previous work. Sievert’s gas absorption results were used to develop the pressure-composition-temperature (PCT) curves of the U 3 Si 2 -H system. It was found that the hydride phase exhibited a maximum stoichiometry between U 3 Si 2 H 1.8 and U 3 Si 2 H 2 . The two-phase region for hydride formation from U 3 Si 2 exhibited a miscibility gap with a critical temperature between 623 and 673 K, as calculated from the PCT curves. Analysis of the PCT curves also showed that both the enthalpy and entropy of the hydrogen absorption reaction increased with hydrogen content but were lower than the values for uranium trihydride formation from uranium metal. The enthalpy of reaction for hydrogen absorption was calculated to range between -86.9 and -94.8 kJ mol -1 , while the entropy of reaction was calculated to range between 101.9 and 138.8 J mol -1 K -1 . Furthermore, DFT modeling of the thermoydnamic stability of the USi hydride phases yielded a decomposition temperature of U 3 Si 2 H 2 of approximately 600 K, which was consistent with the experimental results. Similarly, the DFT-calculated enthalpy and entropy of reaction to form USiH were determined to be -106.5kJ mol and 121.8J mol -1 K -1 , respectively, which were both in close agreement with the experimentally-determined values.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Accurate prediction of short-range order and its effect on thermodynamic, structural, and electronic properties of disordered alloys: exemplified in archetypical Cu 3 Au

Electronic-structure methods based on density-functional theory (DFT) were used to quantify the effect of chemical short-range order (SRO) on thermodynamic, structural, and electronic properties of archetypal face-centered-cubic (fcc) Cu3Au alloy. We showed that SRO can be tuned to alter bonding and lattice dynamics (i.e., phonons) and detail how these properties are changed with SRO. Thermodynamically favorable SRO significantly improved the phase stability of fcc Cu3Au from -0.0343 eV-atom -1 to –0.0682 eV-atom -1 . We used our DFT-based linear-response theory to predict SRO and its electronic origin, and accurately estimate the observed transition temperature, ordering instability (L1 2 ), and Warren-Cowley SRO parameters, in agreement with experiments. The accurate prediction of real-space SRO gives an edge over computationally and resource intensive approaches such as monte-carlo methods or experiments, which will enable large scale molecular dynamic simulations by providing supercells with optimized SRO. Here we also analyzed phonon dispersion and estimated the vibrational entropy change (from 9kB at 300 K to 6kB at 100 K) in fcc Cu3Au. We established from SRO analysis that exclusion of chemical interactions may lead to a skewed view of true properties in chemically complex alloys. The first-principles methods described in this work are generally applicable to any arbitrary solid-solution alloys, including multi-principal-element alloys, therefore, holds promise for designing technologically useful materials.

36 MATERIALS SCIENCE↗

Electronic tuning of confined sub-nanometer cobalt oxide clusters boosting oxygen catalysis and rechargeable Zn–air batteries.

Reasonable design of robust bifunctional oxygen catalysts from an electronic structure perspective is intriguing and challenging for the development of high active rechargeable zinc-air batteries (ZABs). In this study, the favorable regulation of the electronic structure of the cobalt oxide nanoclusters was firstly predicted by density functional theory (DFT) simulation, and then experimentally verified by confining sub-nanometer CoOx clusters (0.86 nm) into the small pore of ZIF-8 derived N-doped nanomaterials (PNC) using a microporous MOFs confinement strategy. The confined effect of the MOF micropores not only enhanced the stability of the subnanometer cobalt oxide clusters, but also make it coupled with Co-Nx to further regulate the electronic structure of the former, synergistic resulting in enhanced ORR/OER actives. As a result, the optimized 0.05CoOx@PNC catalyst demonstrates outstanding bifunctional oxygen performance with a smaller potential gap of 0.67 V. Moreover, the rechargeable Zn-air batteries integrated 0.05CoOx@PNC air cathode displays encouraging performance with a peak power density of 157.1 mW cm(-2), a specific capacity of 887 mAh g(Zn)(-1)at 10 mA cm(-2) and long-term cyclability for over 200 h, significantly outperforming the benchmark electrode couple consisted of Pt/C/RuO2. DFT calculation further revealed that reducing particle size and coupling with Co-N could effectively regulate the charge distribution of CoOx nanoclusters and downshift the D-band center of Co adsorption sites in CoOx nanoclusters, which reduced the reaction barrier of intermediate O-2* and OH* and ORR/ OER over potential, thus accelerating the overall ORR/OER kinetic process. This work offers a novel reference for the construction of a robust sub-nanometer cluster catalysts in the field of ZABs.

Bifunctional oxygen electrocatalysts↗

Non-bonding interaction of dual atom catalysts for enhanced oxygen reduction reaction

Here, we demonstrate the design of graphene-supported dual atom catalysts (DACs) for the four-electron oxygen reduction reaction (ORR), by utilizing the non-bonding interaction of counterpart metals (M) that synergistically tune the electronic properties and catalytic activity of the Fe active site in FeMN 6 -DAC and FeMN 8 -DAC systems, where M stands for Fe, Co, Ni, Cu, and Zn. More specifically, for Fe-M distances below 15Å, the non-bonding interaction is significant, making the system act as the DAC. We predicted that FeNiN 6 -DAC and FeNiN 8 -DAC exhibit a low ORR overpotential (η ORR ) of 0.28 V and 0.47 V, respectively, which are at the summits of volcano plots. This low η ORR originates from the high Bader charge transfer coupled with high spin density at the Fe site in both the FeNiN 6 -DAC and FeNiN 8 -DAC systems, which weakens the adsorption of OH* intermediate while enhancing its desorption to H 2 O. Guided by these density functional theory (DFT) computational results, we synthesized FeCoN 8 -DAC and FeNiN 8 -DAC along with N-doped graphene and confirmed their structures with scanning transmission electron microscopy (STEM), X-ray photoelectron spectroscopy (XPS), X-ray absorption near-edge structure (XANES), extended X-ray absorption fine structure (EXAFS), and electron spin resonance (ESR). We verify experimentally the catalytic activities and find that FeNiN 8 -DAC has the low experimental overpotential of 0.39 V with a Tafel slope of 47 mVdec -1 . Based on these results, we propose a DFT-guided strategy to tune the charge transfer and spin population of the active site toward designing DACs for electrochemical ORR.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Accelerating the discovery of low-energy structure configurations: A computational approach that integrates first-principles calculations, Monte Carlo sampling, and Machine Learning

Finding Minimum Energy Configurations (MECs) is essential in fields such as physics, chemistry, and materials science, as they represent the most stable states of the systems. In particular, identifying such MECs in multi-component alloys considered candidate PFMs is key because it determines the most stable arrangement of atoms within the alloy, directly influencing its phase stability, structural integrity, and thermo-mechanical properties. However, since the search space grows exponentially with the number of atoms considered, obtaining such MECs using computationally expensive first-principles DFT calculations often results in a cumbersome task. To escape the above compromise between physical fidelity and computational efficiency, we have developed a novel physics-based data-driven approach that combines Monte Carlo sampling, first-principles DFT calculations, and Machine Learning to accelerate the discovery of MECs in multi-component alloys. More specifically, we have leveraged well-established Cluster Expansion (CE) techniques with Local Outlier Factor models to establish strategies that enhance the reliability of the CE method. In this work, we demonstrated the capabilities of the proposed approach for the particular case of a tungsten-based quaternary high-entropy alloy. However, the method is applicable to other types of alloys and enables a wide range of applications.

36 MATERIALS SCIENCE↗

Kβ X-ray Emission Spectroscopy as a Probe of Cu(I) Sites: Application to the Cu(I) Site in Preprocessed Galactose Oxidase

Cu(I) active sites in metalloproteins are involved in O 2 activation, but their O 2 reactivity is difficult to study due to the Cu(I) d 10 closed shell which precludes the use of conventional spectroscopic methods. Kβ X-ray emission spectroscopy (XES) is a promising technique for investigating Cu(I) sites as it detects photons emitted by electronic transitions from occupied orbitals. Here, we demonstrate the utility of Kβ XES in probing Cu(I) sites in model complexes and a metalloprotein. Using Cu(I)Cl, emission features from double-ionization (DI) states are identified using varying incident X-ray photon energies, and a reasonable method to correct the data to remove DI contributions is presented. Kβ XES spectra of Cu(I) model complexes, having biologically relevant N/S ligands and different coordination numbers, are compared and analyzed, with the aid of density functional theory (DFT) calculations, to evaluate the sensitivity of the spectral features to the ligand environment. While the low-energy Kβ 2,5 emission feature reflects the ionization energy of ligand np valence orbitals, the high-energy Kβ 2,5 emission feature corresponds to transitions from molecular orbitals (MOs) having mainly Cu 3d character with the intensities determined by ligand-mediated d–p mixing. A Kβ XES spectrum of the Cu(I) site in preprocessed galactose oxidase (GO pre ) supports the 1Tyr/2His structural model that was determined by our previous X-ray absorption spectroscopy and DFT study. Finally, the high-energy Kβ 2,5 emission feature in the Cu(I)-GO pre data has information about the MO containing mostly Cu 3d x 2 –y 2 character that is the frontier molecular orbital (FMO) for O 2 activation, which shows the potential of Kβ XES in probing the Cu(I) FMO associated with small-molecule activation in metalloproteins.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Effect of Linker Structure and Functionalization on Secondary Gas Formation in Metal–Organic Frameworks

Rare-earth terephthalic acid (BDC)-based metal–organic frameworks (MOFs) are promising candidate materials for acid gas separation and adsorption from flue gas streams. However, previous simulations have shown that acid gases (H 2 O, NO 2 , and SO 2 ) react with the hydroxyl on the BDC linkers to form protonated acid gases as a potential degradation mechanism. Herein, gas-phase computational approaches were used to identify the formation energies of these secondary protonated acid gases across multiple BDC linker molecules. Formation energies for secondary protonated acid gases were evaluated using both density functional theory (DFT) and correlated wave function methods for varying BDC–gas reaction mechanisms. Upon validation of DFT to reproduce wave function calculation results, rotated conformational linkers and chemically functionalized BDC linkers with -OH, -NH 2 , and -SH were investigated. Furthermore, the calculations show that the rotational conformation affects the molecule stability. Double-functionalized BDC linkers, where two functional groups are substituted onto BDC, showed varied reaction energies depending on whether the functional groups donate or withdraw electrons from the aromatic system. Based on these results, BDC linker design must balance adsorption performance with degradation via linker dehydrogenation for the design of stable MOFs for acid gas separations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗