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At least 1,135 records · Page 63
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

ZIF-8 Vibrational Spectra: Peak Assignments and Defect Signals

In this study, Zeolitic Imidazolate Framework-8 (ZIF-8) is a promising material for gas separation applications. It also serves as a prototype for numerous ZIFs, including amorphous ones, with a broader range of possible applications, including sensors, catalysis, and lithography. It consists of zinc coordinated with 2-methylimidazolate (2mIm) and has been synthesized with methods ranging from liquid-phase to solvent-free synthesis, which aim to control its crystal size and shape, film thickness and microstructure, and incorporation into nanocomposites. Depending on the synthesis method and post-synthesis treatments, ZIF-8 materials may deviate from the nominal defect-free ZIF-8 crystal structure due to defects like missing 2mIm, missing zinc, and physically adsorbed 2mIm trapped in the ZIF-8 pores, which may alter its performance and stability. Infra-red (IR) spectroscopy has been used to assess the presence of defects in ZIF-8 and related materials. However, conflicting interpretations by various authors persist in the literature. Here, we systematically investigate ZIF-8 vibrational spectra by combining experimental IR spectroscopy and first-principles molecular dynamics simulations, focusing on assigning peaks and elucidating the spectroscopic signals of putative defects present in ZIF-8 material. We attempt to resolve conflicting assignments from the literature and to provide a comprehensive understanding of the vibrational spectra of ZIF-8 and its defect-induced variations, aiming towards more precise quality control and design of ZIF-8-based materials for emerging applications.

36 MATERIALS SCIENCE↗
NASA NTRS2002

Defect Localization Capabilities of a Global Detection Scheme: Spatial Pattern Recognition Using Full-field Vibration Test Data in Plates

Recently, a conceptually simple approach, based on the notion of defect energy in material space has been developed and extensively studied (from the theoretical and computational standpoints). The present study focuses on its evaluation from the viewpoint of damage localization capabilities in case of two-dimensional plates; i.e., spatial pattern recognition on surfaces. To this end, two different experimental modal test results are utilized; i.e., (1) conventional modal testing using (white noise) excitation and accelerometer-type sensors and (2) pattern recognition using Electronic speckle pattern interferometry (ESPI), a full field method capable of analyzing the mechanical vibration of complex structures. Unlike the conventional modal testing technique (using contacting accelerometers), these emerging ESPI technologies operate in a non-contacting mode, can be used even under hazardous conditions with minimal or no presence of noise and can simultaneously provide measurements for both translations and rotations. Results obtained have clearly demonstrated the robustness and versatility of the global NDE scheme developed. The vectorial character of the indices used, which enabled the extraction of distinct patterns for localizing damages proved very useful. In the context of the targeted pattern recognition paradigm, two algorithms were developed for the interrogation of test measurements; i.e., intensity contour maps for the damaged index, and the associated defect energy vector field plots.

Saleeb, A. F.↗
DOE OSTI2018

3D Imaging and Manipulation of Subsurface Selenium Vacancies in PdSe 2

Two-dimensional materials such as layered transition-metal dichalcogenides (TMDs) are ideal platforms for studying defect behaviors, an essential step towards defect engineering for novel material functions. Here, we image the 3D lattice locations of selenium-vacancy V Se defects and manipulate them using a scanning tunneling microscope (STM) near the surface of PdSe 2 , a recently discovered pentagonal layered TMD. The V Se show a characterisitc charging ring in a spatially resolved conductance map, based on which we can determine its subsurface lattice location precisely. Using the STM tip, not only can we reversibly switch the defect states between charge neutral and charge negative, but also trigger migrations of V Se defects. This allows a demonstration of direct “writing” and “erasing” of atomic defects and tracing the diffusion pathways. First-principles calculations reveal a small diffusion barrier of V Se in PdSe 2 , which is much lower than S vacancy in MoS 2 or an O vacancy in TiO 2 . As a result, this finding opens an opportunity of defect engineering in PdSe 2 for such as controlled phase transformations and resistive-switching memory device application.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2025

Review of radiation-induced defects in GaAs

Radiation-resilient optoelectronic materials are highly desired in space and nuclear applications, and understanding the relevant defects and electronic processes in those materials is crucial for both current and next-generation applications. GaAs is a prototypical semiconductor that serves as a foundational system for describing and understanding optoelectronic devices. In this review, both experimental studies and molecular dynamics (MD) simulations of irradiated GaAs are reviewed, with particular emphasis on the deep-level transient spectroscopy, irradiation-induced amorphization zones, and MD predictions of damage structures. The MD results are also compared to predictions of the non-ionized energy-loss model. Recent theoretical studies, in particular, density functional theory based calculations on the simple intrinsic defects and defect clusters in GaAs, are also reviewed. These defects have an important role in dictating the evolution of GaAs in radiation damage environments, as they impact the coupled dynamics of charge carriers. Finally, possible gaps and challenges toward the general understanding of defect evolution in GaAs are discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2022

An objective inter-comparison of trash mark constellations generated by manual and automated detection methods

Trash marks are unintentional markings observed on printed, scanned, or photocopied documents that result from permanent defects or transient material in office machines and can be used for source attribution of questioned documents. Trash mark examinations have been in use in forensic laboratories for decades, yet the method remains relatively untested and relies on training, experience, and anecdotal information to support its validity. Herein this study generated and harnessed objective data to empirically test one of the foundational theories for assessing the origin of photocopied documents: provided trash marks are present in sufficient quantity and/or quality, no two machines will exhibit a constellation of trash marks that is indistinguishable from another. In this project, objective trash mark location and size data was generated for 50 known photocopiers using both a traditional and a novel, automated method. Inter-machine comparisons were conducted using a novel variant of the Hausdorff distance algorithm to generate a quantitative assessment of how similar or different the 2450 pairs of trash mark constellations were from one another. This study found that each of the machines bearing one or more trash marks exhibited objective differences in their trash mark constellations, ultimately providing support for the tested hypothesis

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

Enhanced temperature sensing based on sub-threshold nonlinear spectra of one-dimensional photonic crystal with a Kerr defect layer

A new method to achieve highly sensitive temperature sensing is proposed based on the nonlinear spectral properties of a one-dimensional photonic crystal (1DPC) composed of temperature-sensitive materials with a Kerr defect layer. The sensitivity can be two orders of magnitude higher than that of the corresponding linear 1DPC structure. The sensitivity and measuring range can be precisely tuned. These properties favor the fabrication of a versatile temperature sensor with switchable fine and coarse tuning functions. This principle of nonlinear temperature sensing can also be extended to other kinds of spectrum-based sensors to obtain higher performance.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2011

Battle against Phonons (A "Life at the Frontiers of Energy Research" contest entry from the 2011 Energy Frontier Research Centers (EFRCs) Summit and Forum

"Battle against Phonons" was submitted by the Solid State Solar Thermal Energy Conversion (S3TEC) EFRC to the "Life at the Frontiers of Energy Research" video contest at the 2011 Science for Our Nation's Energy Future: Energy Frontier Research Centers (EFRCs) Summit and Forum. Twenty-six EFRCs created short videos to highlight their mission and their work. This video was selected as one of five winners by a distinguished panel of judges for the special award, "Best with Popcorn". S3TEC, an EFRC directed by Gang Chen at the Massachusetts Institute of Technology is a partnership of scientists from four research institutions: MIT (lead), Oak Ridge National Laboratory, Boston College, and Rensselaer Polytechnic Institute. The Office of Basic Energy Sciences in the U.S. Department of Energy's Office of Science established the 46 Energy Frontier Research Centers (EFRCs) in 2009. These collaboratively-organized centers conduct fundamental research focused on 'grand challenges' and use-inspired 'basic research needs' recently identified in major strategic planning efforts by the scientific community. The overall purpose is to accelerate scientific progress toward meeting the nation's critical energy challenges. The mission of the Solid-State Solar Thermal Energy Conversion Center is 'to create novel, solid-state materials for the conversion of sunlight into electricity using thermal and photovoltaic processes.' Research topics are: solar photovoltaic, photonic, metamaterial, optics, solar thermal, thermoelectric, phonons, thermal conductivity, defects, ultrafast physics, interfacial characterization, matter by design, novel materials synthesis, charge transport, defect tolerant materials, and scalable processing.

14 SOLAR ENERGY↗
DOE OSTI2021

Reviewing computational studies of defect formation and behaviors in carbon fiber structural units

Solid-state carbon materials, such as graphite and graphene, are at the forefront of materials research because of their unique electronic, vibrational, and mechanical properties, leading to a broad range of potential and realized applications. One key application is their role as basic structural units of carbon fiber (CF), a lightweight alternative to steel. In CF, a delicate relationship exists between ultimate material strength and the atomic-scale density of defects contained at the inter- and intra-subunit levels. Computational studies provide insight into the stability of various types of defects that can form in these systems and connect with experimental observables such as bandgap and spectroscopic measurements. Therefore, the literature contains many computational studies that focus on changes induced by defects, including vacancies and Dienes transformations (Stone-Wales and Thrower defects). However, wide-ranging methods and cell sizes have been used, and property-specific information is often lacking. Furthermore, this review summarizes key literature findings, paying particular attention to changes in the electronic, vibrational, and mechanical properties induced by defects in graphitic materials relevant to CF.

36 MATERIALS SCIENCE↗
DOE OSTI2016

2D materials advances: from large scale synthesis and controlled heterostructures to improved characterization techniques, defects and applications

The rise of two-dimensional (2D) materials research took place following the isolation of graphene in 2004. These new 2D materials include transition metal dichalcogenides, mono-elemental 2D sheets, and several carbide- and nitride-based materials. The number of publications related to these emerging materials has been drastically increasing over the last five years. Thus, through this comprehensive review, we aim to discuss the most recent groundbreaking discoveries as well as emerging opportunities and remaining challenges. This review starts out by delving into the improved methods of producing these new 2D materials via controlled exfoliation, metal organic chemical vapor deposition, and wet chemical means. Here we look into recent studies of doping as well as the optical properties of 2D materials and their heterostructures. Recent advances towards applications of these materials in 2D electronics are also reviewed, and include the tunnel MOSFET and ways to reduce the contact resistance for fabricating high-quality devices. Finally, several unique and innovative applications recently explored are discussed as well as perspectives of this exciting and fast moving field.

36 MATERIALS SCIENCE↗
NASA NTRSDate not supplied

Towards Integrated Computational Materials Engineering for Quantifying Performance Impacts of Microstructure and Defect Interactions in Powder Bed Fusion Parts

Powder bed fusion (PBF) additive manufacturing (AM) enables the creation of parts with complexity and functionality levels that were previously impossible with traditional manufacturing methods. By modifying the laser power, hatch spacing, or the numerous other processing parameters, the PBF process supports the production of a wide set of materials and geometries. However, that same process parameter design flexibility causes the process-design space of PBF to be massive and expensive to explore experimentally. Another challenge is quality variation across a build. As a part is being built, geometric variance between locations, such as at a thin-wall section vs. the bulk material, may cause the specified processing parameters to no longer be acceptable for producing defect-free printing. Furthermore, if the processing parameters deviate during the print process, it is difficult to assess if the part will still perform satisfactorily. Integrated Computational Materials Engineering (ICME) provides a way to understand and address these various challenges. This talk will present advancements in process-structure simulations of PBF at NASA Langley Research Center. The ability to simulate grain-scale PBF microstructures using the Physically Based Monte Carlo method will be demonstrated and compared to experimental measurements. Techniques for simulating three-dimensional lack-of-fusion and keyhole porosity defects based on the specific processing conditions and approaches for integrating the two porosity prediction techniques alongside the computational microstructure evolution models will be shown. Finally, the integration of simulated PBF microstructures, embedded process defects, and crystal plasticity finite element models to elucidate the interaction of porosity and microstructure on micromechanical fields will be demonstrated. These integrated techniques demonstrate an example of using ICME to relate processing to performance for PBF AM materials. With continued maturity, it is hoped that such ICME approaches will lead to next-generation computational-materials supported qualification and certification of AM parts.

Additive manufacturing↗
DOE OSTI2023

Application of a deep learning semantic segmentation model to helium bubbles and voids in nuclear materials

Imaging nanoscale radiation-induced defects using the transmission electron microscope (TEM) is a key factor in the successful implementation of materials for nuclear energy structural applications. Analyzing each defect in a TEM micrograph is currently a manual task. To identify the defects in a single image can take anywhere from 15 min to an hour and a project can require the analysis of anywhere from tens to ≥ 100 images. Here, we use artificial intelligence (AI) models to automate this task. For simplification, we evaluated images with only a single type of defect; helium bubbles. Additionally, we performed semantic segmentation of these helium bubble defects in electron microscopy images of irradiated FeCrAl alloys using a deep learning DefectSegNet model. This model, which was previously used to classify crystal defects, is inspired by the classic DenseNet and U-Net image segmentation models. It claims high spatial resolution, but has poor performance at object boundaries. Our paper improves the DefectSegNet model’s application by adding two new features. First, the DefectSegNet model is applied not only to perform calculation pixel-wise but also object (or feature) wise. Because object-wise metrics are directly relevant to our final goal of detecting bubbles, whereas pixel-wise classification is only an intermediate step, it is an important part of our study. Second, a distance map loss (DML) function has been added to increase its performance at object boundaries. It is crucial to accurately represent defects boundaries, especially bubbles, in order to track the bubble-induced swelling caused by irradiation. The boundary-focused DML function is also compared to other loss functions like Cross-entropy, Weighted Binary Cross Entropy (WBCE), Dice and Intersection over Union (IOU). Finally, by incorporating new features, we found a marked improvement on segmentation quality and better shape preservation at the boundaries and areas of the bubbles.

42 ENGINEERING↗
DOE OSTI2016

The Effect of Thermal Annealing on Charge Transport in Organolead Halide Perovskite Microplate Field-Effect Transistors

Transformation of unipolar n-type semiconductor behavior to ambipolar and finally to unipolar p-type behavior in CH 3 NH 3 PbI 3 microplate field-effect transistors by thermal annealing is reported. The photoluminescence spectra essentially maintain the same features before and after the thermal annealing process, demonstrating that the charge transport measurement provides a sensitive way to probe low-concentration defects in perovskite materials.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Tailoring the Properties of Calcium Aluminate Macro-Defect-Free Cements: From Brittle to Ductile Behavior

Cementitious macro-defect-free (MDF) materials can be obtained processing a mixture of a water-soluble polymer, namely polyvinyl alcohol (PVA) and the calcium aluminate cement. Based on process techniques typical of plastics, the MDF products can be obtained in complex forms and, thanks to the reduced water to cement ratio, w/c, their strength is very high compared to standard cements. However, these materials show both the sensitivity typical of water-soluble polymers, presenting a low glass transition temperature (T{sub g}), and the brittle behavior typical of ceramic materials and therefore low toughness. The aim of this work is to modify the mechanical properties of MDF cements by tuning their unacceptable brittle behavior. Water solution of carboxylate styrene butadiene rubber is used as reactive additives, and different mixture formulations are tested changing the rubber-like content both with respect to the fixed water content and PVA amounts. It is shown that the modifications of the organic phase imply small or negligible effects on paste formation of different recipes as detected by the torque–time responses. From flexural and fracture toughness tests, a wide range of responses was observed, and depending on the particular recipe, the mechanical behavior can be tuned from a brittle to a ductile behavior.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Phase Identification in Synchrotron X-ray Diffraction Patterns of Ti–6Al–4V Using Computer Vision and Deep Learning

X-ray diffraction patterns contain information about the atomistic structure and microstructure (defect population) of materials, extracting detailed information from diffraction patterns is complex, demanding and relies on prior knowledge. Here, we hypothesize that deep-learning techniques can help to perform an effective and accurate analysis with high throughput rates. To demonstrate this concept, we applied a novel deep learning framework to determine the evolution of the β-phase volume fraction in a Ti–6Al–4V alloy during heat-treatment from video sequences of 2D diffraction patterns recorded in transmission and with highly monochromatic radiation in a synchrotron beamline. In particular, we studied the impact of network design on prediction reliability and computational performance. Networks of different architectures were trained using 3008 experimental 2D patterns. A well-tuned model was found to reproduce the phase fractions of another experimental data set, consisting of 1100 diffraction patterns, with a mean-square error as small as 2.6 x 10 -4 . The average prediction error of β-phase volume fraction was within 1.6 x 10 -2 (in each diffraction pattern) of the values obtained by conventional methods. Our work demonstrates that convolutional neural networks can evaluate high energy X-ray diffraction patterns with a remarkable level of reliability. Furthermore, it demonstrates the significance of network design on the reliability of predictions and computational performance. The most complex models do not necessarily result in highest accuracy and may even fail to learn from the data.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Formation of pyrophosphates across grain boundaries induces the formation of mismatched but oriented interfaces in silver phosphate polypods

The interfaces and their misfit defects determine the materials properties for a wide range of applications, such as electronic devices, photocatalysis, and mechanical engineering, etc. However, current understanding of atomic interfacial structures is limited. Here we discover a special interfacial structure, mismatched but oriented interface via two distinct facets. Transmission and scanning electron microscopy results suggest that, in Ag 3 PO 4 polypods structures, interfaces of {1 0 0} and {1 1 0}, ({1 0 0}/(1 1 0}), {1 0 0}/{1 1 1}, {1 1 0}/{1 1 1}, and {1 0 0}/{1 0 0}, etc., have a certain orientation relationship, corresponding to the energy minima and coincident site lattice of interfacial atoms as demonstrated by molecular dynamics simulations. Density functional theory demonstrates that the formation of pyrophosphate and/or phosphates rotation to bond across the interface compensate the lattice mismatch at the interfaces, as well as deformations of Ag-O bonds. Furthermore, our work opens up a new avenue for a much wider range of interfacial structures, allow for a higher diversity of structures, and shine light on tailoring crystal structures, morphologies, and the resulting properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2013

Radiation damage in cubic-stabilized zirconia

Cubic yttria-stabilized zirconia (YSZ) can be used for nuclear applications as an inert matrix for actinide immobilization or transmutation. Indeed, the large amount of native oxygen vacancies leads to a high radiation tolerance of this material owing to defect recombination occurring in the atomic displacements cascades induced by fast neutron irradiation or ion implantations, as showed by Molecular dynamics (MD) simulations. Amorphization cannot be obtained in YSZ either by nuclear-collision or electronic-excitation damage, just like in urania. A kind of polygonization structure with slightly disoriented crystalline domains is obtained in both cases. In the first steps of damage, specific isolated point defects (like F+-type color centers) and point-defect clusters are produced by nuclear collisions with charged particles or neutrons. Further increase of damage leads to dislocation-loop formation, then to collapse of the dislocation network into a polygonization structure. For swift heavy ion irradiations, a similar polygonization structure is obtained above a threshold stopping power value of about 20-30 keV nm-1.

color centers↗
DOE OSTI2023

Uncovering metallic glasses hidden vacancy-like motifs using machine learning

Vacancies are a ubiquitous type of defect in crystalline materials that can affect their properties and behavior, including atomic diffusivity, deformation processes, thermal conductivity, and electrical conductivity. While well-defined in crystals, it is challenging to identify such topological footprints in the amorphous structure of metallic glasses (MGs). Here, we uncover an unforeseen vacancy-like structural motif named Q7, which refers to an atomic Voronoi polyhedron with seven quadrangular faces, by investigating MG local atomic configurations with the help of machine learning. The Q7 motif exhibits characteristics similar to crystalline vacancies and plays a significant role in short-range structural disorder in MGs. The atoms at the center of the Q7 motif display larger local entropy, atomic volume, and local tension. Additionally, its concentration follows an Arrhenius-like relationship with temperature, accurately indicating the glass transition temperature, and is strongly correlated with the yield and failure of MGs during mechanical deformation. The discovery of the Q7 motif provides new insights into understanding the intricate relationship between local disorder and structural relaxation in MGs, offering a remarkable ability to predict their thermal and mechanical behavior. This potentially paves the way for enhancements in the design and manufacturing processes of MGs and other amorphous materials.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Evidence of hexagonal germanium grains on annealed monolayer MoS 2

Growing three-dimensional (3D) materials on two-dimensional (2D) van der Waals surface has shown its effectiveness in overcoming materials incompatibility for stacking transferrable membranes toward advanced device manufacturing. Herein, we demonstrate that the nucleation of hexagonal germanium (Ge) grains within a continuous crystalline film, which has been unfeasible through traditional epitaxy techniques, is realized by chemical vapor deposition on top of n-type monolayer molybdenum disulfide (MoS 2 ) substrates. Suggested by quantum molecular dynamics calculation, the hexagonal Ge nucleation is thermodynamically preferable to cubic Ge when growing on monolayer MoS 2 with sulfur vacancies. The strained hexagonal Ge grains have been confirmed by transmission electron microscopy analyses from both real space and reciprocal space. Scanning probe microscopy shows that the hexagonal Ge film possesses higher reflectivity in infrared spectral range, implying a higher carrier concentration resulted from the narrower band gap, as compared to cubic Ge.

36 MATERIALS SCIENCE↗