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DOE OSTI2020

Noncollinear magnetic structure and magnetoelectric coupling in buckled honeycomb Co 4 Nb 2 O 9 : A single-crystal neutron diffraction study

Through an analysis of single-crystal neutron diffraction data, we present the magnetic structure and magnetoelectric properties of Co 4 Nb 2 O 9 under various magnetic fields. In zero field, neutron diffraction experiments below T N =27K reveal that the Co 2+ moments order in the (ab) plane without any spin canting along the c axis, manifested by the magnetic symmetry C2/c'. Along each Co chain parallel to the c axis, the moments of nearest-neighbor Co atoms order ferromagnetically with a small cant away from the next-nearest-neighbor Co moments. Under the applied magnetic field H ∥ a, three magnetic domains were aligned with their major magnetic moments perpendicular to the magnetic field with no other observable magnetic transitions. The influences of magnetic fields on the magnetic structures associated with the observed magnetoelectric coupling are discussed.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2021

Improvement of Front-Junction GaInP by Point-Defect Injection and Annealing

Traditional front junction GaInP solar cells are radiation tolerant and can have good diffusion length, but have limited voltage and thus efficiency. Here, we investigate the impact of annealing on GaInP device performance. First, Zn-doped GaInP/AlGaInP double heterojunction structures are studied in order to investigate the impact of annealing in a simple structure. While standard anneals lower diffusion length and lifetime, annealing after injecting point-defects improves material quality, presumably by eliminating sources of non-radiative recombination. Atomic ordering is reduced by the anneal, which raises the device bandgap and requires consideration. These results can be used to improve front junction device performance while controlling the bandgap. Then, GaInP front-junction devices are created using anneals with and without point-defect injection. Voc and EQE trends follow the diffusion length and lifetime trends from the DH structures. Baseline devices have Woc of 0.484 V, raising to 0.504 V after a high temperature anneal. However, injecting point defects prior to the anneal results in a front junction device with Woc of 0.405 V and a diffusion length greater than 8 micrometers. Optimized front-junction GaInP devices with an ARC have ~20% efficiency without a rear reflector.

anneal↗

DOE OSTI2021

Improvement of Front-Junction GaInP by Point-Defect Injection and Annealing: Preprint

anneal↗

DOE OSTI2026

Lattice vacancy migration barriers in Fe-Ni alloys, and an indication as to why Ni atoms diffuse slowly: A first-principles study

Lattice vacancy migration barriers in ferromagnetic Fe 𝑥 ⁢Ni 1−𝑥 alloys (0.4 ≤ 𝑥 ≤ 0.6) are accurately quantified within the framework of ab initio electronic structure calculations using the nudged elastic band (NEB) method. Both the atomically disordered (A1) fcc phase, as well as the atomically ordered, tetragonal L⁢1 0 phase—which is under consideration as a material for a rare-earth-free gap magnet for advanced engineering applications—are investigated. Across an ensemble of NEB calculations performed on supercell configurations spanning a range of compositions and containing disordered, partially ordered, and fully ordered structures, we find that Ni-vacancy interchanges encounter significantly higher energetic barriers than do Fe-vacancy interchanges. We contend that this aspect is a key factor in determining the differences in mobility between Fe and Ni atoms in this ferromagnetic alloy. Moreover, we are able to interpret these findings in terms of the ferromagnetic alloy's underlying spin-polarized electronic structure. Specifically, we report a coupling between the size of local lattice distortions and the magnitude of the local electronic spin polarization around vacancies. This causes Fe atoms to relax into lattice vacancies, while Ni atoms remain rigidly fixed to their original lattice positions. These results give atomic-scale insight into the longstanding experimental observation that Ni exhibits remarkably slow atomic diffusion in Fe-Ni alloys.

density functional theory↗

DOE OSTI2023

Surface structure studies in 2D and 3D Nb resonators using GI-XRD

Superconductor radio frequency (SRF) Nb-resonators are a key element in the development of new generations of particle accelerators as well as in the fabrication of 3D circuit QED architecture for quantum computing. Nevertheless, Niobium is extremally reactive to light elements such as C, N, O and H, and therefore to the impurities ordering under special conditions, e.g., cryogenic temperatures. Since these resonators are put through a series of metallurgical and chemical processes, the number of impurities in the solid increases in tens of ppm. Upon operational conditions ~1.6 K, Nb become vulnerable to H atoms ordering, which leads to the nucleation of secondary phases such as Nb-hydrides. Thereupon to the energy dissipation and eventually to the superconductivity breakdown known as Q-disease and potentially High-Field Q-slope. In this contribution, we present a detailed structural analysis by high-energy grazing-incidence X-ray diffraction of specimens extracted from 3D Nb resonators to shed light on the kinetic formation of the resulting secondary phases and their crystal phase identification upon cooling and heating cycles. To our knowledge, this is the first study carried out in resonators samples using a light source, shallow angles and temperatures near ~4 K. Consequently, this work opens new routes to understand the chemical and phase composition, crystal and electronic structure of the Nb surface at temperatures near the operating conditions as a strategy to improve the physical and functional properties of Nb superconducting resonators.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2025

Scanning tunneling microscope tip-induced formation of Bi bilayers on Bi 2 Te 3

We report the formation of Bi(111) bilayer islands and crater structures on Bi 2 Te 3 (111) surfaces induced by voltage pulses from a scanning tunneling microscope tip. Pulses above a threshold voltage (+3 V) produce craters ∼0.5μm in diameter, similar to the size of the tip. Redeposited material self-assembles into a network of atomically ordered islands with a lattice constant identical to the underlying Bi2Te3 surface. The island size monotonically decreases over several micrometers from the pulse site, until the pristine Bi 2 Te 3 surface is recovered. We assign these islands to Bi bilayer based on atomic resolution images, analysis of step heights, and tunneling spectroscopy. Here, the dependence of bilayer formation on bias polarity and the evidence for defect diffusion together suggest a mechanism driven by the interplay of field evaporation and tunneling-current-induced Joule heating.

Bi bilayer↗

DOE OSTI2024

Superstructures and magnetic order in heavily Cu-substituted ( Fe 1 – x Cu x ) 1 + y Te

Most iron-based superconductors exhibit stripe-type magnetism, characterized by the ordering vector Q = ($\frac{1}{2},\frac{1}{2}$). In contrast, Fe 1+y Te, the parent compound of the Fe 1+y Te 1–x Se x superconductors, exhibits double-stripe magnetic order associated with the ordering vector Q = ($\frac{1}{2},0$). Here, we use elastic neutron scattering to investigate heavily Cu-substituted (Fe 1–x Cu x ) 1+y Te compounds and reveal that (1) for x ≳ 0.4, short-range magnetic order emerges around the stripe-type vector at Q = ($\frac{1}{2}$ ± δ, $\frac{1}{2}$ ± δ, $\frac{1}{2}$) with δ ≈ 0.05; (2) the short-range magnetic order is associated with a superstructure modulation at Q = ($\frac{1}{3},\frac{1}{3},\frac{1}{2}$), with the magnetic correlation length shorter than that for the superstructure; and (3) for x ≳ 0.55, we observe an additional intergrown phase with higher Cu content, characterized by a superstructure modulation vector Q = ($\frac{1}{3},\frac{1}{3},0$) and magnetic peaks at Q = ($\frac{2}{3},\frac{1}{3},\frac{1}{2}$)/($\frac{1}{3},\frac{2}{3},\frac{1}{2}$). The positions of superstructure peaks suggest that relative to the tetragonal unit cell of Fe 1+y Te, heavy Cu substitution leads to Fe-Cu orderings that expand the unit cell by $\sqrt{2}$ × 3$\sqrt{2}$ times in the ab plane, corroborated by first-principles calculations that suggest the formation of spin chains and spin ladders. Finally, our findings show that stripe-type magnetism is common in magnetically diluted iron pnictides and chalcogenides, despite the varying associated atomic orderings

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2022

Scalable Synthesis of Monolayer Hexagonal Boron Nitride on Graphene with Giant Bandgap Renormalization

Abstract Monolayer hexagonal boron nitride (hBN) has been widely considered a fundamental building block for 2D heterostructures and devices. However, the controlled and scalable synthesis of hBN and its 2D heterostructures has remained a daunting challenge. Here, an hBN/graphene (hBN/G) interface‐mediated growth process for the controlled synthesis of high‐quality monolayer hBN is proposed and further demonstrated. It is discovered that the in‐plane hBN/G interface can be precisely controlled, enabling the scalable epitaxy of unidirectional monolayer hBN on graphene, which exhibits a uniform moiré superlattice consistent with single‐domain hBN, aligned to the underlying graphene lattice. Furthermore, it is identified that the deep‐ultraviolet emission at 6.12 eV stems from the 1s‐exciton state of monolayer hBN with a giant renormalized direct bandgap on graphene. This work provides a viable path for the controlled synthesis of ultraclean, wafer‐scale, atomically ordered 2D quantum materials, as well as the fabrication of 2D quantum electronic and optoelectronic devices.

2D heterostructures↗

DOE OSTI2023

Non-Linear Optics at Twist Interfaces in h-BN/SiC Heterostructures

Understanding the emergent electronic structure in twisted atomically thin layers has led to the exciting field of twistronics. However, practical applications of such systems are challenging since the specific angular correlations between the layers must be precisely controlled and the layers have to be single crystalline with uniform atomic ordering. Here, in this work, an alternative, simple, and scalable approach is suggested, where nanocrystalline two-dimensional (2D) film on 3D substrates yields twisted-interface-dependent properties. Ultrawide-bandgap hexagonal boron nitride (h-BN) thin films are directly grown on high in-plane lattice mismatched wide-bandgap silicon carbide (4H-SiC) substrates to explore the twist-dependent structure-property correlations. Concurrently, nanocrystalline h-BN thin film shows strong non-linear second-harmonic generation and ultra-low cross-plane thermal conductivity at room temperature, which are attributed to the twisted domain edges between van der Waals stacked nanocrystals with random in-plane orientations. First-principles calculations based on time-dependent density functional theory manifest strong even-order optical nonlinearity in twisted h-BN layers. This work unveils that directly deposited 2D nanocrystalline thin film on 3D substrates could provide easily accessible twist-interfaces, therefore enabling a simple and scalable approach to utilize the 2D-twistronics integrated in 3D material devices for next-generation nanotechnology.

36 MATERIALS SCIENCE↗

DOE OSTI2021

High-Resolution In-Situ Synchrotron X-Ray Studies of Inorganic Perovskite CsPbBr[subscript 3]: New S

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Liu, Sizhan↗

DOE OSTI2020

Propane Dehydrogenation on Single-Site [PtZn4] Intermetallic Catalysts

Propane dehydrogenation (PDH) is a commercial propylene production technology that has received much attention, but high reaction temperature results in decrease of propylene selectivity and catalyst stability. This paper describes a single-site [PtZn 4 ] catalyst by assembling atomically ordered intermetallic alloy (IMA) as a selective and ultrastable PDH catalyst. The catalyst enables more than 95% propylene selectivity from 520 to 620 oC. No obvious deactivation is observed within 160-hours test, superior to PtSn/Al 2 O 3 and state-of-the-art Pt-based catalysts. Additionally, based on in situ X-ray absorption fine-structure, X-ray photoelectron spectroscopy measurements and density functional theory calculations, we reveal that the surface [PtZn 4 ] ensembles in PtZn IMAs serve as the key active site structures, wherein the geometry-isolated and electron-rich Pt1 site in [PtZn 4 ] ensembles readily promotes the first and second C–H cleavage of propane, but inhibits further dehydrogenation of surface-bounded propylene. This significantly improves the selectivity and stability by prohibiting coke side reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Graphite crystals in catalytically-graphitized glass-like carbon

Catalytic graphitization of glass-like carbon leads to enhanced growth of micro-sized graphitic crystals with unusual shapes of wires, filaments, tubes, rods, whiskers, and spirals. Similar particles with axial symmetry are also found in pure glass-like carbon heat-treated at high temperatures. Nonetheless, the presence of a graphitization catalyst, Si in this case, in the heat-treatment process supports the transformation of porous, disordered carbon structure towards the graphitic atomic order and the formation of manifold peculiar polyhedral wires and particles of geometry distinct from the plate-like shape typical for conventional graphite. In contrast to conventional carbon nanotubes and fibers, the graphene layers are stacked perpendicular to the tube axis, while the size of the most common tube fibers can reach up to 10 μm in diameter and 100 μm in length. X-ray diffraction, Raman spectroscopy, scanning and transmission electron microscopy, small-angle X-ray scattering combined with complementary techniques have been used to characterize the structure of the glass-like carbon derived from furfuryl alcohol catalytically-graphitized using Si particles at 3000 °C. Finally, since control of graphite shape is vital to achieving the level of performance required in contemporary applications, the obtained results demonstrate that the catalytic graphitization method may be employed to produce filamentous graphite crystals.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Phase evolution of U-Zr system in a thermal cycling neutron diffraction experiment: as-cast U-35Zr and U-50Zr

Here, phase evolution of as-cast U-35 wt% Zr and U-50 wt% Zr alloys during thermal cycling (303–1073 K) was investigated using in-situ neutron diffraction. Analysis was performed using Rietveld crystal and microstructure refinements from time-of-flight neutron diffraction data, with a focus on evolution of lattice parameter, atom ordering, unit cell volume, and weight fractions during the thermal cycling. Disordered δ-UZr 2 and residual γ-(U,Zr) phase are retained in the field of δ of the U-Zr equilibrium phase diagram for the U-50Zr sample, and in the field between δ and α-U for the U-35Zr sample. The α phase that is present in the reported phase diagrams of U-Zr was not observed in the diffraction patterns. The evolutions of lattice parameter and unit cell volume of δ and γ are affected by both thermal expansion and chemistry.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2022

Predicting Oxygen Off-Stoichiometry and Hydrogen Incorporation in Complex Perovskite Oxides

Chemically and structurally complex solid compounds, including those with significant off-stoichiometry, are rapidly extending new material functionality across a variety of applications. Accelerated development of these compounds requires accurate predictions of material defect properties including effective defect formation energies and equilibrium defect concentrations. Traditional first-principles approaches typically examine dilute defect concentrations and relatively ordered atomic structures to identify the lowest energy defect sites. These approaches are rarely suitable for describing the disorder present in these systems and its influence on defect formation, which can lead to unphysically large predictions for defect concentrations. Here, we demonstrate a new method to accurately predict the temperature and pressure dependence of oxygen vacancy concentrations and proton interstitial concentrations in complex oxides. This method extends standard dilute defect calculations to incorporate atomic and magnetic disorder, employs the ensemble descriptions of defect sites resulting in improved predictions of defect formation energies, and accounts for effects beyond the dilute defect limit. To demonstrate our method, we show that the predicted defect concentrations in perovskites used as ceramic fuel cell cathodes, including Ba0.5Sr0.5Fe0.8Zn0.2O3-d, Ba0.5Sr0.5Co0.8Fe0.2O3-d, and BaCo1-x-y-zFexZryYzO3-d, are in good agreement with experimental values, thereby opening the door for predictive design of complex oxides by these applications.

DFT↗

DOE OSTI2023

Electrochemical Degradation of Pt 3 Co Nanoparticles Investigated by Off-Lattice Kinetic Monte Carlo Simulations with Machine-Learned Potentials

In fuel cell applications, the durability of catalysts is critical for large-scale industrial implementation. However, limited synthesis controllability and spectroscopic resolution impede a comprehensive understanding of degradation mechanisms at the atomic level. In this study, we develop a machine-learned potential (MLP) to simulate the degradation processes for Pt3Co nanoparticles. The precision of MLP is determined to be comparable to that of density functional theory calculations. Using off-lattice kinetic Monte Carlo simulations with MLP, we successfully replicate established experimental trends and offer a logical resolution to ongoing debates regarding atomic orderings. Based on the simulation results, we suggest design principles for Pt3Co nanoparticles that combine high activity and durability. Finally, we validate the wide applicability of our method by successfully applying it to Pt3Ni and Pt3Co0.5Ni0.5 nanoparticles. The research serves as a guideline for developing MLPs for alloy electrochemical catalysts and lays the foundation for designing more durable and active fuel-cell catalysts.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Bulk Stoichiometry-Controlled Surface Reconstruction of Nanosized Ni−In Intermetallic Catalysts Steers Methanol Selectivity in CO2 Hydrogenation

Intermetallic compounds (IMCs) are attractive platforms for elucidating structure−catalysis relationships due to their ordered atomic structure and well-defined bulk composition. Yet, how their surfaces reconstruct under reaction conditions and how such reconstruction is governed by bulk stoichiometry remain poorly understood. Here, we show that SiO2-supported Ni−In IMCs undergo reaction-driven surface reconstruction during CO2 hydrogenation and that bulk stoichiometry can be used to steer this evolution toward methanol formation. Among the compositions examined (Ni2In1, Ni1In1, Ni2In3, and Ni1In2), Ni2In3/SiO2 exhibits the highest methanol selectivity (∼70%) and a methanol space-time yield of 652 mg·gmetal−1·h−1 at 250 °C and 30 bar. Combined structural, surface characterization, and kinetic analyses suggest that the intermetallic bulk remains largely preserved, whereas the surface departs from the stoichiometric bulk and evolves toward InOx-enriched surface domains coupled to an electron-rich Ni−In intermetallic phase. The extent of this evolution depends strongly on the bulk Ni:In stoichiometry and is most pronounced for Ni2In3/SiO2. These findings identify bulk stoichiometry as a handle for tuning the working-state surface of intermetallic catalysts and provide a basis for designing methanol synthesis catalysts through controlled surface reconstruction.

Wang, Caiqi [ORNL] (ORCID:0000000198849990)↗

DOE OSTI2025

Impact of Domain Knowledge on the Property Prediction of Specialized Machine Learning Models

Developing transferable machine learning models is trending in data-driven materials research. However, how to apply such models to a specific research domain remains unclear. Here, in this work, we choose high-entropy materials as a platform with a specialized data set containing 145,323 DFT-relaxed materials. This data set is used to explore the role of domain-specific knowledge in training effective models. Our tests with three representative graph neural network architectures indicate the model complexity has much smaller influence on performance than the data itself. Specifically, the consideration of low-energy atomic ordering, structures with diverse elemental coverage, and high-order interactions significantly influences the model performance. We also find that domain knowledge-driven sampling can greatly enhance unsupervised learning techniques. This research highlights that developing specialized data sets is more beneficial than further complicating deep learning architectures. Additionally, physics-inspired sampling algorithms are crucially needed for better machine learning models for a specific materials research domain.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Distilling nanoscale heterogeneity of amorphous silicon using tip-enhanced Raman spectroscopy (TERS) via multiresolution manifold learning

Abstract Accurately identifying the local structural heterogeneity of complex, disordered amorphous materials such as amorphous silicon is crucial for accelerating technology development. However, short-range atomic ordering quantification and nanoscale spatial resolution over a large area on a-Si have remained major challenges and practically unexplored. We resolve phonon vibrational modes of a-Si at a lateral resolution of <60 nm by tip-enhanced Raman spectroscopy. To project the high dimensional TERS imaging to a two-dimensional manifold space and categorize amorphous silicon structure, we developed a multiresolution manifold learning algorithm. It allows for quantifying average Si-Si distortion angle and the strain free energy at nanoscale without a human-specified physical threshold. The multiresolution feature of the multiresolution manifold learning allows for distilling local defects of ultra-low abundance (< 0.3%), presenting a new Raman mode at finer resolution grids. This work promises a general paradigm of resolving nanoscale structural heterogeneity and updating domain knowledge for highly disordered materials.

36 MATERIALS SCIENCE↗