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At least 1,333 records · Page 74
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Interplay of charge density wave states and strain at the surface of CeTe 2

in this work we use scanning tunneling microscopy (STM) to study charge density wave (CDW) states in the rare-earth ditelluride, CeTe 2 . Our STM measurements surprisingly detect a unidirectional CDW with q ~ 0.28 a * , which differs from previous experimental and first-principles studies of the rare-earth ditellurides, and which is very close to what is found in experimental measurements of the related rare-earth tritellurides. Furthermore, in the vicinity of an extended subsurface defect, we find spatially-separated as well as spatially-coexisting unidirectional CDWs at the surface of CeTe 2 . We quantify the nanoscale strain and its variations induced by this defect, and establish a correlation between local lattice strain and the locally-established CDW states; this suggests that lattice strain plays an important role in determining the specific characteristics of the established CDW state. Our measurements probe the fundamental properties of a weakly-bound two-dimensional Te sheet, which experimental and theoretical work has previously established as the fundamental component driving much of the essential physics in both the rare-earth di- and tritelluride compounds.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Active Learning Surrogates for Integrating Electron Microscopy and Computational Insights from Simulations in Autonomous Experiments

Artificial Intelligence (AI) combined with simulations and experiments has great potential to accelerate scientific discovery across technology and pharmaceuticals. However, the gap between simulations and experiments is challenging due to disparities in time and scale, making it difficult to estimate properties like energy and electronic states from experiments, and to provide feedback based on theoretical insights.Our research addresses the challenge by developing unique deep kernel based surrogate models that learns from microscopic images, mapping structural features to energy differences from defect formation. We start with full-training using simulated images to determine optimal settings, establishing a baseline for active learning. Using these settings from the baseline, active learning is trained, and predicts structures along simulation trajectories based on uncertainty and energetic stability, thus reducing data requirements, simulation time and computational costs. The results demonstrate that the model achieves a low average error margin of approximately 0.03 meV, indicating good performance. To enhance feature extraction and reconstruction capabilities, we developed an autoencoder-decoder as additional surrogate to create latent space to capture essential features, enabling precise comparisons between simulations and experiments. The results from this model achieved a reconstruction loss of around 0.2 and accurately reconstructed molecular structures.Overall, this work advances the steering of experiments through computational simulations by employing a surrogate models that actively predicts the trajectories of structural evolution, achieving time-to-solution comparable to experimental measurements.

Saranathan, Gayathri [Hewlett-Packard]↗
DOE OSTI2024

Boron carbide films with reduced nodular defect density deposited by full-face erosion radio-frequency magnetron sputtering

Boron carbide coatings deposited by sputtering with conventional planar magnetrons exhibit nodular growth defects. Here, we demonstrate that the density of nodular defects in B 4 C films can be greatly reduced by using a full-face-erosion magnetron source that achieves a more uniform target erosion by sweeping the confining magnetic field over the target surface. Here, we systematically study properties of B 4 C films deposited on substrates with different tilt angles and demonstrate deposition of ultrathick films with compressive residual stress below 200MPa.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Degradation and Self-Healing in Perovskite Solar Cells

Organic–inorganic halide perovskites are well-known for their unique self-healing ability. In the presence of strong external stimuli, such as light, temperature, and moisture, high-energy defects are created which can be healed by removing the perovskite from the degradation source. Furthermore, this self-healing ability has been showcased in devices with recoverable performance and day-and-night cycling operation to dramatically extend the device lifetime and even mechanical durability. However, to date, the mechanistic details and theory around this captivating trait are sparse and convoluted by the complex nature of perovskites. With a clear understanding of the intrinsic self-healing property, perovskite solar cells with extended lifetimes and durability can be designed to realize the large-scale commercialization of perovskite solar cells. Here, we spotlight the relevant degradation and self-healing literature and then propose design strategies to help conceptualize future research.

14 SOLAR ENERGY↗
DOE OSTI2026

Influence of thermal treatment on structure and catalytic performance of ceria-zirconia supported copper oxide (CuO x /Ce y Zr 1-y O 2 ) catalysts for CO oxidation

Copper oxide (CuO x ) supported on ceria-zirconia (Ce y Zr 1-y O 2 , y = 1.0, 0.5, 0.0) catalysts were investigated to elucidate the effects of thermal treatment on their physicochemical properties and catalytic performance in carbon monoxide (CO) oxidation. Here, the catalysts were synthesized via a one-pot chemical vapor deposition (OP-CVD) method at 700˚C and 900˚C with controlled Cu loading. Characterization techniques, including synchrotron X-ray diffraction (S-XRD), Raman spectroscopy, X-ray photoelectron spectroscopy (XPS), inductively coupled plasma spectroscopy (ICP), and N 2 adsorption-desorption, were implemented to probe the crystalline structure, molecular and electronic structure, oxygen vacancies, specific surface area (SSA) and metal loading. CO oxidation was chosen as a model reaction to explore the structure-catalytic performance relationship. A ∼100% CO conversion was achieved at < 150˚C, particularly with the CuO x /CeO 2 catalyst calcined at 700˚C. In contrast, calcination at 900˚C caused a ∼90% decrease in SSA and a ∼24% increase in T 50 . Activity tests revealed that increasing ZrO 2 content lowered CO oxidation activity despite generating more defect sites. In-situ measurement of the 700 °C calcined samples revealed the presence of stable and unstable defects in CuO x /Ce 0.5 Zr 0.5 O 2 and CeO 2 respectively, which play a key role in the activity of the catalysts. The results highlight that catalytic performance is closely related to the SSA. Furthermore, an optimum calcination temperature favor significant oxygen vacancy formation with required CuO x -support interactions, enhancing redox properties and catalytic performance.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Low temperature recovery of OFF-state stress induced degradation of AlGaN/GaN high electron mobility transistors

Thermal annealing is a widely used strategy to enhance semiconductor device performance. However, the process is complex for multi-material multi-layered semiconductor devices, where thermoelastic stresses from lattice constant and thermal expansion coefficient mismatch may create more defects than those annealed. We propose an alternate low temperature annealing technique, which utilizes the electron wind force (EWF) induced by small duty cycle high density pulsed current. To demonstrate its effectiveness, we intentionally degrade AlGaN/GaN high electron mobility transistors (HEMTs) with accelerated OFF-state stressing to increase ON-resistance ∼182.08% and reduce drain saturation current ∼85.82% of pristine condition at a gate voltage of 0 V. We then performed the EWF annealing to recover the corresponding values back to ∼122.21% and ∼93.10%, respectively. The peak transconductance, degraded to ∼76.58% of pristine at the drain voltage of 3 V, was also recovered back to ∼92.38%. This recovery of previously degraded transport properties is attributed to approximately 80% recovery of carrier mobility, which occurs during EWF annealing. We performed synchrotron differential aperture x-ray microscopy measurements to correlate these annealing effects with the lattice structural changes. We found a reduction of lattice plane spacing of (001) planes and stress within the GaN layer under the gate region after EWF annealing, suggesting a corresponding decrease in defect density. Application of this low-temperature annealing technique for in-operando recovery of degraded electronic devices is discussed.

Physics↗
DOE OSTI2020

Synthesis of luminescent core/shell α-Zn 3 P 2 /ZnS quantum dots

Metal chalcogenide nanoparticles offer vast control over their optoelectronic properties via size, shape, composition, and morphology which has led to their use across fields including optoelectronics, energy storage, and catalysis. While cadmium and lead-based nanocrystals are prevalent in applications, concerns over their toxicity have motivated researchers to explore alternate classes of nanomaterials based on environmentally benign metals such as zinc and tin. The goal of this research is to identify material systems that offer comparable performance to existing metal chalcogenide systems from abundant, recyclable, and environmentally benign materials. With band gaps that span the visible through the infrared, II–V direct band gap semiconductors such as tetragonal zinc phosphide (α-Zn 3 P 2 ) are promising candidates for optoelectronics. To date, syntheses of α-Zn 3 P 2 nanoparticles have been hindered because of the toxicity of zinc and phosphorus precursors, surface oxidation, and defect states leading to carrier trapping and low photoluminescence quantum yield. Here, we report a colloidal synthesis of quantum confined α-Zn 3 P 2 nanoparticles from common phosphorus precursor tris(trimethylsilyl)phosphine and environmentally benign zinc carboxylates. Shelling of the nanoparticles with zinc sulfide is shown as a method of preventing oxidation and improving the optical properties of the nanoparticles. These results show a route to stabilizing α-Zn 3 P 2 nanoparticles for optoelectronic device applications.

25 ENERGY STORAGE↗
DOE OSTI2023

Semihard magnetic properties of TiFe 2.5 iron-rich Laves phase and the effect of 4d- and 5d-element-substitutions for Ti

Rare-earth-free compounds exhibiting modest intrinsic hard magnetic properties may still yield viable permanent magnets if their constituent elements are abundant and inexpensive, and the properties are at least comparable to those of the hard ferrites. In this study, one such compound, the off-stoichiometric TiFe 2.5 Laves phase with the hexagonal C14 crystal structure, was found to exhibit – in addition to the already known room-temperature ferromagnetism – a uniaxial, albeit weak, magnetic anisotropy. With a Curie temperature of 422 K, saturation magnetization of 55.3 Am 2 /kg and magnetic hardness parameter of 0.97 this semihard compound is just below the threshold for being of interest for the development into permanent magnets. Replacing a small fraction of Ti with the 4d Nb and Mo or with the 5d Ta or W increases the anisotropy field, but only below room temperature. Replacing Ti with Zr or Hf increases the Curie temperature and leads to a spin reorientation below 200 K. All these substitutions, as well as combined (Zr,W) and (Nb,W) substitutions, fail to improve the room-temperature intrinsic hard magnetic properties of the Fe-rich Laves phase. Furthermore, an attempt to develop a room-temperature coercivity through high-energy ball-milling yielded a value of 0.026 T, an unusually small 2.9% fraction of the anisotropy field. Here, defects inherent in the C14 crystal lattice may be responsible for the underperformance.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Learning to Predict Crystal Plasticity at the Nanoscale: Deep Residual Networks and Size Effects in Uniaxial Compression Discrete Dislocation Simulations

The density and configurational changes of crystal dislocations during plastic deformation influence the mechanical properties of materials. These influences have become clearest in nanoscale experiments, in terms of strength, hardness and work hardening size effects in small volumes. The mechanical characterization of a model crystal may be cast as an inverse problem of deducing the defect population characteristics (density, correlations) in small volumes from the mechanical behavior. In this work, we demonstrate how a deep residual network can be used to deduce the dislocation characteristics of a sample of interest using only its surface strain profiles at small deformations, and then statistically predict the mechanical response of size-affected samples at larger deformations. As a testbed of our approach, we utilize high-throughput discrete dislocation simulations for systems of widths that range from nano- to micro- meters. We show that the proposed deep learning model significantly outperforms a traditional machine learning model, as well as accurately produces statistical predictions of the size effects in samples of various widths. By visualizing the filters in convolutional layers and saliency maps, we find that the proposed model is able to learn the significant features of sample strain profiles.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Evidence for current suppression in superconductor–superconductor bilayers

Superconducting radio frequency (SRF) cavities, which are critical components in many particle accelerators, need to be operated in the Meissner state to avoid strong dissipation from magnetic vortices. For a defect-free superconductor, the maximum attainable magnetic field for operation is set by the superheating field, B sh , which directly depends on the surface current. In heterostructures composed of different superconductors, the current in each layer depends not only on the properties of the individual material, but also on the electromagnetic response of the adjacent layers through boundary conditions at the interfaces. Three prototypical bilayers [Nb 1–x Ti x N (50 nm)/Nb, Nb 1–x Ti x N (80 nm)/Nb, and, Nb 1–x Ti x N (160 nm)/Nb] are investigated here by depth-resolved measurements of their Meissner screening profiles using low energy muon spin rotation (LE-µSR). From fits to a model based on London theory (with appropriate boundary and continuity conditions), a magnetic penetration depth for the thin Nb 1–x Ti x N layers of λ Nb 1–x Ti x N = 182.5(31) nm is found, in good agreement with literature values for the bulk alloy. Using the measured λ Nb 1–x Ti x N , the maximum vortex-free field, B max , of the superconductor-superconductor (SS) bilayer structure was estimated to be 610(40) mT. The strong suppression of the surface current in the Nb 1–x Ti x N layer suggests an optimal thickness of ~ 1.4λ Nb 1–x Ti x N = 261(14) nm.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Assessment of thermally driven local structural phase changes in 1⁢𝑇′−MoTe 2

The role of layer disorder is important in establishing the topological phases of MoTe 2 . A rich tapestry of atomic ordering influences the structural phase transitions (SPTs), but there is little understanding of the mechanistic details of the phase transition. An atomistic level study was conducted to investigate the local structure of the 1⁢𝑇′ and 𝑇 𝑑 phases of MoTe 2 by using the pair distribution function (PDF) technique. While the average structure exhibits an SPT and coexistence of phases as a function of temperature, the local structure showed the suppression of SPT. The sample retained its monoclinic structure at all temperatures in short-range order. A sharp PDF peak observed at short distances indicated a strong atom-atom correlation between the Mo and Te atoms within the Mo octahedra. In addition, a large-box modeling of the PDF data indicated a preferential motion of Te atoms towards 𝑐 axis at all temperatures. Structural defects, such as stacking faults, likely result in the coexistence of phases in the average structure and suppress the local SPT of MoTe 2 . These results are stepping stones to understand the long-debated origins of structural, vibrational, and electronic properties of MoTe 2 and similar transition metal dichalcogenides.

2-dimensional systems↗
DOE OSTI2025

Self-Learning Kinetic Monte Carlo Simulations of Radiation Damage in Nuclear Fuels

Understanding how irradiation affects the thermo-physical and mechanical properties of nuclear materials, such as thermal conductivity degradation in fuels and embrittlement of structural components, is critical to the safety and efficiency of nuclear reactors. These effects are largely governed by the formation and evolution of atomic-scale point defects and defect clusters. Due to their small sizes, however, these defects are invisible under high-resolution scanning transmission electron microscopy. This project aims to fill this experimental knowledge gap by integrating density functional theory (DFT), machine learning interatomic potential (MLIP), and kinetic Monte Carlo (KMC) techniques to predict longtime evolution of irradiation-induced defects in nuclear fuels.

36 - MATERIALS SCIENCE↗
DOE OSTI2024

Effect of fabrication processes on BaTiO 3 capacitor properties

There is an increasing desire to utilize complex functional electronic materials such as ferroelectrics in next-generation microelectronics. As new materials are considered or introduced in this capacity, an understanding of how we can process these materials into those devices must be developed. Here, the effect of different fabrication processes on the ferroelectric and related properties of prototypical metal oxide (SrRuO 3 )/ferroelectric (BaTiO 3 )/metal oxide (SrRuO 3 ) heterostructures is explored. Two different types of etching processes are studied, namely, wet etching of the top SrRuO 3 using a NaIO 4 solution and dry etching using an Ar + -ion beam (i.e., ion milling). Polarization-electric-field hysteresis loops for capacitors produced using both methods are compared. For the ion-milling process, it is found that the Ar + beam can introduce defects into the SrRuO 3 /BaTiO 3 /SrRuO 3 devices and that the milling depth strongly influences the defect level and can induce a voltage imprint on the function. Realizing that such processing approaches may be necessary, work is performed to ameliorate the imprint of the hysteresis loops via ex situ “healing” of the process-induced defects by annealing the ferroelectric material in a barium-and-oxygen-rich environment via a chemical-vapor-deposition-style process. This work provides a pathway for the nanoscale fabrication of these candidate materials for next-generation memory and logic applications.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Halide Perovskites Breathe Too: The Iodide–Iodine Equilibrium and Self-Doping in Cs 2 SnI 6

The response of an oxide crystal to the atmosphere can be personified as breathing-a dynamic equilibrium between O 2 gas and O 2– anions in the solid. We characterize the analogous defect reaction in an iodide double-perovskite semiconductor, Cs 2 SnI 6 . Here, I 2 gas is released from the crystal at room temperature, forming iodine vacancies. The iodine vacancy defect is a shallow electron donor and is therefore ionized at room temperature; thus, the loss of I2 is accompanied by spontaneous n-type self-doping. Conversely, at high I 2 pressures, I 2 gas is resorbed by the perovskite, consuming excess electrons as I 2 is converted to 2I – . Halide mobility and irreversible halide loss or exchange reactions have been studied extensively in halide perovskites. However, the reversible exchange equilibrium between iodide and iodine [2I – (s) ↔ I 2(g) + 2e – ] described here has often been overlooked in prior studies, though it is likely general to halide perovskites and operative near room temperature, even in the dark. An analysis of the 2I – (s) /I 2(g) equilibrium thermodynamics and related transport kinetics in single crystals of Cs 2 SnI 6 therefore provides insight toward achieving stable composition and electronic properties in the large family of iodide perovskite semiconductors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

2D Vacancy Confinement in Anatase TiO 2 for Enhanced Photocatalytic Activities

Abstract Light‐driven energy conversion devices call for the atomic‐level manipulation of defects associated with electronic states in solids. However, previous approaches to produce oxygen vacancy (V O ) as a source of sub‐bandgap energy levels have hampered the precise control of the distribution and concentration ofV O . Here, a new strategy to spatially confineV O at the homo‐interfaces is demonstrated by exploiting the sequential growth of anatase TiO 2 under dissimilar thermodynamic conditions. Remarkably, metallic behavior with high carrier density and electron mobility is observed after sequential growth of the TiO 2 films under low pressure and temperature (L‐TiO 2 ) on top of high‐quality anatase TiO 2 epitaxial films (H‐TiO 2 ), despite the insulating properties of L‐TiO 2 and H‐TiO 2 single layers. Multiple characterizations elucidate that theV O layer is geometrically confined within 4 unit cells at the interface, along with low‐temperature crystallization of upper L‐TiO 2 films; this 2DV O layer is responsible for the formation of in‐gap states, promoting photocarrier lifetime (≈300%) and light absorption. These results suggest a synthetic strategy to locally confine functional defects and emphasize how sub‐bandgap energy levels in the confined imperfections influence the kinetics of light‐driven catalytic reactions.

Chemistry↗
DOE OSTI2020

Influence of hydrocracking and ionic liquid pretreatments on composition and properties of Arabidopsis thaliana wild type and CAD mutant lignins

Lignin is the primary contributor to the high cost of biofuel-production from lignocellulosic biomass. Here, in order to study lignin removal and the release of aromatic monomers, we applied hydrocracking and ionic liquid pretreatments on Arabidopsis thaliana biomass from both wild type (WT) and a mutant (CAD cxd) defective in two cinnamyl alcohol dehydrogenase genes involved in the lignin biosynthetic pathway. For Arabidopsis WT, our results highlight that pretreatments reduce average molecular weight of lignin by about 65% and decrease the content of β-O-4 linkages between lignin monomers. For Arabidopsis CAD mutant, an opposite effect is evidenced. Fewer differences were observed on depolymerization and molecular structure of lignin, which indicates that (8-O-4), (8-5), and (8-8) linkages observed in CAD mutant make lignin more resilient to pretreatment than wild-type lignin. Finally, our study shows the potential of hydrocracking pretreatment technology for extracting valuable aldehyde monomers such as vanillin and syringaldehyde from biomass.

09 BIOMASS FUELS↗
DOE OSTI2025

Benchmarking Density Functional Theory Methods for Efficient Calculations of a Strongly Correlated Li 1– x Ni 1– y O 2−δ System

Transition metal oxides (TMOs), such as LiNiO 2 , are promising candidates for energy storage and electronic devices due to their unique electronic properties, exceptional physical and chemical characteristics, and ability to adopt multiple oxidation states. However, accurately predicting their properties using mean-field density functional theory (DFT) is challenging due to the presence of strongly correlated d-electrons and the complex interplay between their structural, electronic, and magnetic responses. These challenges are further exacerbated by the need to model defects, surfaces, and interfaces, which require computationally efficient, large-scale simulations. To address these issues, we carry out a benchmark study on the Li 1–x NiO 2 system, evaluating the performance of several popular functionals. Our findings demonstrate that combining SCAN functional relaxation with single-step HSE calculations provides a practical and scalable computational strategy. This approach balances accuracy and efficiency, enabling high-throughput simulations of strongly correlated TMOs and improved predictive modeling capability of TMOs for practical applications.

25 ENERGY STORAGE↗
DOE OSTI2020

Surface Ligands for Methylammonium Lead Iodide Films: Surface Coverage, Energetics, and Photovoltaic Performance

Surface ligand treatment provides a promising approach for passivating defect states, improving material and device stability, manipulating interfacial energetics, and improving the performance of perovskite solar cells (PSCs). To facilitate targeted selection and design of surface ligands for PSCs, it is necessary to establish relationships between ligand structure and perovskite surface properties. In this work, surface ligands with different binding groups are investigated to determine their extent of surface coverage, whether they form a surface monolayer or penetrate the perovskite, how they influence material energetics and photoluminescence, and how this combination of factors affects PSC performance. Ultraviolet and inverse photoelectron spectroscopy measurements show that surface ligands can significantly shift the ionization energy and electron affinity. Lastly, these changes in surface energetics substantially impact PSC performance, with the performance decreasing for ligands that create less favorable energy landscapes for electron transfer from MAPbI 3 to the electron transport layer, C 60 .

14 SOLAR ENERGY↗