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Yang, Kun

Publications and source records attributed to Yang, Kun.

At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Oxidation kinetics of SPS-densified U 3 Si 2 fuels—Microstructure impact

Here, U 3 Si 2 is a potential candidate for accident tolerant fuels because of its high uranium density and excellent thermal conductivity in comparison to UO 2 . However, U 3 Si 2 suffers from oxidation, steam corrosion, and subsequent disintegration/pulverization. The detailed investigation of kinetics that incorporates fundamental treatment of oxidation of U 3 Si 2 is scarcely reported, and the oxidation mechanisms have not been fully elucidated. In this paper, the oxidation behavior of microcrystalline (mc - ) and nanocrystalline (nc - ) U 3 Si 2 have been systematically investigated using a thermogravimetric analysis (TGA) apparatus through a series of isothermal and non-isothermal kinetic studies. The isothermal kinetic study with a model-fitting approach indicates oxidation activation energy of 85 kJ/mol for dense mc - U 3 Si 2 and 96.4 kJ/mol for nc - U 3 Si 2 pellets, while the isoconversional approach leads to an activation energy in the range of 70–85 kJ/mol for mc - U 3 Si 2 and 75–86 kJ/mol for nc - U 3 Si 2 with three most common model-free methods, including Kissinger–Akahira–Sunose, Flynn–Wall–Ozawa, and Friedman methods. The derivation of oxidation activation energies using both isothermal and isoconversional methods highlights the approach to evaluate the oxidation resistance of nuclear materials using TGA quantitatively and makes it possible to compare among various nuclear fuels.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Cs 3 Bi 2 I 9 -hydroxyapatite composite waste forms for cesium and iodine immobilization

Perovskite-based ceramic composites were developed as potential waste form materials for immobilizing cesium (Cs) and iodine (I) with high waste loadings and chemical durability. The perovskite Cs 3 Bi 2 I 9 has high Cs (22 wt%) and I (58 wt%) content, and thus can be used as a potential host phase to immobilize these critical radionuclides. In this work, the perovskite Cs 3 Bi 2 I 9 phase was synthesized by a cost effective solution-based approach, and was embedded into a highly durable hydroxyapatite matrix by spark plasma sintering to form dense ceramic composite waste forms. The chemical durabilities of the monolithic Cs 3 Bi 2 I 9 and Cs 3 Bi 2 I 9 -hydroxyapatite composite pellets were investigated by static and semi-dynamic leaching tests, respectively. Cs and I are incongruently released from the matrix for both pure Cs 3 Bi 2 I 9 and composite structures. The normalized Cs release rate is faster than that of I, which can be explained by the difference in the strengths between Cs-I and Bi-I bonds as well as the formation of insoluble micrometer-sized BiOI precipitates. The activation energies of elemental releases based on dissolution and diffusion-controlled mechanisms are determined with significantly higher energy barriers for dissolution from the composite versus that of the monolithic Cs 3 Bi 2 I 9 . The ceramic-based composite waste forms exhibit excellent chemical durabilities and waste loadings, commensurate with the state-of-the-art glass-bonded perovskite composites for I and Cs immobilization.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

New data-driven approach to bridging power system protection gaps with deep learning

Protection is a critical function in power systems to avoid equipment damage, maintain personnel safety, and support system reliability. However, current protective relay technology cannot adequately protect equipment and personnel from effects of some events; these deficiencies are termed protection gaps. In this paper, a data-driven approach is proposed to complement traditional protection technology and distinguish fault conditions from transients caused by normal operations. A combined convolutional neural network and long short-term memory (CNN-LSTM) network is implemented to achieve data translation invariance and capture the temporal correlation of the time-series input data. As a result, the data-driven method can accurately detect system faults despite variation and noise in the input data. In addition, using the CNN-LSTM--based method avoids the complicated, manual feature extraction procedure required by many traditional data-driven methods. The effectiveness of the proposed approach is tested on two kinds of protection gaps: high-impedance faults and transformer inter-turn faults. Lastly, a transfer learning method is also proposed to address the common issue of data-driven methods for which real-world training data are scarce. Extensive study results demonstrate that the proposed approach can accurately bridge power system protection gaps.

42 ENGINEERING↗
DOE OSTI2022

A simple framework to characterize land aridity based on surface energy partitioning regimes

Land aridity is often characterized by the aridity index (AI), which does not account for land surface water-energy interactions that are crucially important in determining regional climate. Such interactions can be captured by the evaporative fraction (EF, ratio of evapotranspiration to available energy) regimes. As EF is subject to energy and water limitations in humid and dry areas, respectively, EF regimes may be used to characterize land aridity to account for the influence of complex land characteristics and their impact on water availability. Here, we propose a simple framework to characterize land aridity by statistically ranking the coupling strength between EF and surface energy and water terms. The framework is demonstrated using gridded data and compared with AI over the U.S. and China. Results show that regionalization of aridity zones based on EF regimes and a two-tiered classification scheme may provide information such as surface energy and water variability complementary to the background aridity depicted by AI, with implications for extreme events.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

The International Soil Moisture Network: serving Earth system science for over a decade

In 2009, the International Soil Moisture Network (ISMN) was initiated as a community effort, funded by the European Space Agency, to serve as a centralised data hosting facility for globally available in situ soil moisture measurements (Dorigo et al., 2011b, a). The ISMN brings together in situ soil moisture measurements collected and freely shared by a multitude of organisations, harmonises them in terms of units and sampling rates, applies advanced quality control, and stores them in a database. Users can freely retrieve the data from this database through an online web portal (https://ismn.earth/en/, last access: 28 October 2021). Meanwhile, the ISMN has evolved into the primary in situ soil moisture reference database worldwide, as evidenced by more than 3000 active users and over 1000 scientific publications referencing the data sets provided by the network. As of July 2021, the ISMN now contains the data of 71 networks and 2842 stations located all over the globe, with a time period spanning from 1952 to the present. The number of networks and stations covered by the ISMN is still growing, and approximately 70% of the data sets contained in the database continue to be updated on a regular or irregular basis. The main scope of this paper is to inform readers about the evolution of the ISMN over the past decade, including a description of network and data set updates and quality control procedures. A comprehensive review of the existing literature making use of ISMN data is also provided in order to identify current limitations in functionality and data usage and to shape priorities for the next decade of operations of this unique community-based data repository.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Graviton chirality and topological order in the half-filled Landau level

The fractional quantum Hall state at the Landau level filling factor 5/2 is extremely interesting because it is likely the first non-Abelian state, but its precise nature remains unclear after decades of study. Here we demonstrate this can be resolved by studying the chirality of its graviton excitations, using circularly polarized Raman scattering. We discuss the advantage of this bulk probe over the existing edge probes.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Dynamics of quantum Hall interfaces

A quantum Hall (QH) interface is different from an ordinary QH edge, as the latter has its location determined by the confining potential, while the former can be unpinned and behave like a free string. In this paper, we demonstrate this difference by studying three different interfaces formed by (i) the Laughlin state and the vacuum, (ii) the Pfaffian state and the vacuum, and (iii) the Pfaffian and the anti-Pfaffian states. We find that stringlike interfaces propagating freely in the QH system lead to very different dynamical properties from edges. This qualitative difference gives rise to fascinating physics and suggests a different direction for future research on QH physics. We also discuss briefly possible analogies between QH interfaces and concepts in string theory.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Machine learning-enabled prediction of chemical durability of A 2 B 2 O 7 pyrochlore and fluorite

Pyrochlore-structure type and its derivative in a general formula A 2 B 2 O 7 (A = rare earth elements and actinides; B = Ti, Sn, Zr, Hf, Pb, Si, etc.) display excellent structural flexibility and rich crystal chemistry as promising nuclear waste form materials capable of immobilizing actinides and fission products. It is essential to understand these materials’ chemical durability and element release of radionuclides in order to evaluate their performance in near-field environment. However, it is a formidable grand technological challenge to experimentally perform durability testing across hundreds of thousands of possibilities resulting from their extreme compositional complexities due to cation substitutions at both A and B-sites. In this work, we demonstrate a machine learning approach to determine the key materials parameters and structural characteristics governing the leaching behaviors from a small set of selected compositions as model systems, enabling a science-based prediction of their chemical durability that can be extended to a wide range of chemical compositions. The combination of four key structural characteristics and materials parameters, including ionic radius size difference , ionic potential difference , electronegativity difference , and lattice parameter , creates features an optimized prediction of the chemical durability. Two machine learning models, linear regression and Kernel ridge regression models, are trained on the randomly-split training dataset derived from the experimentally-determined elemental release rates, and subsequently tested on the testing dataset. The predicted leaching rates from both machine learning models show an excellent agreement with the experimental data, demonstrating the feasibility of rapidly evaluating the material properties of new compositions. These results highlight the immense potential of synergizing informatics through machine learning-based models and well-controlled experiments of selected model systems to accelerate materials design and discovery with optimized compositions and performance of promising materials for effective nuclear waste management.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Uranium nitride (UN) pellets with controllable microstructure and phase – fabrication by spark plasma sintering and their thermal-mechanical and oxidation properties

Dense uranium mononitride (UN) pellets with controlled microstructures and tailored grain size from large-grained to a few microns are synthesized by spark plasma sintering (SPS) combined with high energy ball milling. The impacts of the sintering conditions on fuel microstructure, grain size, physical density, and phase behavior are systematically investigated, and the thermal-mechanical properties and oxidation behavior of the SPS densified UN pellets are characterized. Higher sintering temperatures and longer ball milling durations and thus finer starting UN powders promote sintering and densification, and dense UN pellets above 95% theoretical density can be achieved by SPS at 1873 K for 10 min. UN phase purity is maintained in the SPS-densified pellets sintered at a lower temperature and short duration. A phase heterogeneity with secondary UO 2 or uranium sesquinitride (U 2 N 3 ) occurs for the UN pellets sintered at higher temperatures using finer UN powders. The hardness and fracture toughness of the SPS-densified UN pellets increase with smaller grain sizes and higher densities to 7.9 GPa and 3.5 MPa m 1/2 , respectively. Furthermore, both small (1–2 μm) and large grain-sized (30–50 µm) UN pellets exhibit good thermal conductivity. Dynamic oxidation testing by a thermogravimetric analyzer in air shows that the onset temperature for oxidation varies with microstructure and phase heterogeneity of the SPS densified UN pellets. Particularly, the smaller-grained (micron-sized) UN pellets containing uranium oxides and U 2 N 3 display lower weight gain and significantly-reduced oxidation kinetics, and full oxidation completes at a temperature above 1173 K when tested with a ramp rate of 10 K/min.

36 MATERIALS SCIENCE↗
DOE OSTI2021

An Improved Algorithm for Estimating Surface Shortwave Radiation: Preliminary Evaluation With MODIS Products

Cloud parameters, as key inputs in radiative transfer algorithms, have a critical impact on surface shortwave radiation (SSR) computation. By introducing a parameterization of cloud transmittance and reflectance, based on radiative transfer simulations, this study improves the accuracy of an existing physically based model which severely underestimates SSR under thick cloud conditions. The cloud parameterization adopts the single-layer cloud model and simulates cloud transmittances and reflectances by varying cloud optical thickness, cloud particle size, and solar zenith angle. The revised model is applied to estimate instantaneous SSR using Moderate-resolution Imaging Spectroradiometer (MODIS) atmospheric and land products. The retrieved SSR is evaluated against observation data from 41 Baseline Surface Radiation Network (BSRN) stations and is also compared with the MODIS official SSR product. The root mean square error (RMSE) of the estimated instantaneous radiation is approximately 52 and 98 W m -2 under clear-sky and all-sky conditions, respectively. The accuracy of the improved parameterization is higher than that of the original model, and there is no obvious underestimation of SSR in the case of high cloud optical thickness. Therefore, the new algorithm improves the accuracy of SSR estimates in the presence of thick clouds. Retrievals with the improved model also achieve higher accuracy than the MODIS official SSR product (MCD18A1). To conclude, the reliable performance of the scheme at most BSRN stations illustrates that the improved model can be used to map SSR on a global scale.

42 ENGINEERING↗
DOE OSTI2021

Spin-valley locking and bulk quantum Hall effect in a noncentrosymmetric Dirac semimetal BaMnSb 2

Spin-valley locking in monolayer transition metal dichalcogenides has attracted enormous interest, since it offers potential for valleytronic and optoelectronic applications. Such an exotic electronic state has sparsely been seen in bulk materials. Here, we report spin-valley locking in a Dirac semimetal BaMnSb 2 . This is revealed by comprehensive studies using first principles calculations, tight-binding and effective model analyses, angle-resolved photoemission spectroscopy measurements. Moreover, this material also exhibits a stacked quantum Hall effect (QHE). The spin-valley degeneracy extracted from the QHE is close to 2. This result, together with the Landau level spin splitting, further confirms the spin-valley locking picture. In the extreme quantum limit, we also observed a plateau in the z-axis resistance, suggestive of a two-dimensional chiral surface state present in the quantum Hall state. These findings establish BaMnSb 2 as a rare platform for exploring coupled spin and valley physics in bulk single crystals and accessing 3D interacting topological states.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Synthetic High Impedance Fault Data through Deep Convolutional Generated Adversarial Network

High impedance faults (HIFs) have always been significant challenge in the power grids. Researchers have developed some advanced protective methods to detect the HIFs. To test and validate these methods, large amounts of HIF data are required. This paper presents a synthetic HIF data generating method using the deep convolutional generated adversarial network (DCGAN). The DCGAN includes a generator module to create synthetic HIF waveform from random noises; and a discriminator module to identify the flaws of those synthetic data, which ultimately help improve the quality of the synthetic data created by the generator. To test the fidelity of the generated synthetic HIF data, two different HIF-detection methods have been applied. Extensive simulation results have validated the effectiveness of using the DCGAN to create synthetic HIF data.

Yang, Kun↗
DOE OSTI2021

Characterizing uncertainties in ground “truth” of precipitation over complex terrain through high-resolution numerical modeling

Ground observation of precipitation over complex terrain is subject to large uncertainties due to inadequate sampling. This study explores a method that combines limited gauge data and a high-resolution numerical simulation to quantify the precipitation uncertainties in central Himalaya. Specifically, the Coefficient of spatial Variability (CV) of precipitation and the minimum Number of Required Stations (NRS) to obtain areal-mean precipitation ground truth values within a 0.25-degree area are investigated using fine-scale meteorological simulation at 1.5 km grid spacing. Evaluation over a densely-gauged area demonstrates comparable CV and NRS values between station observations and simulations. The simulated CV and NRS values in a larger area show a strong and positive dependence on each other and an expected positive (negative) correlation with topographic complexity (temporal scale). The proposed method sheds lights on evaluating precipitation products and holds promise for informing the layout of rain gauge networks in complex terrain.

Ouyang, Lin↗
DOE OSTI2021

Chemical durability and surface alteration of lanthanide zirconates (A 2 Zr 2 O 7 : A = La-Yb)

Chemical durability of lanthanide zirconates (A 2 Zr 2 O 7 ) (A = La-Yb) under near-field environments is important for evaluating their application as potential nuclear waste forms. In this work, A 2 Zr 2 O 7 (A = La-Yb) are synthesized by spark plasma sintering with controlled microstructure and their chemical durability are evaluated in a nitric acid solution (pH = 1). Scanning transmission electron microscopy analysis reveals an amorphous passivation film either enriched with Zr or lanthanide. The complex chemistry of the passivation films can be correlated with a transition in corrosion mechanisms from a preferential release of lanthanide in La 2 Zr 2 O 7 to a preferential release of Zr in Er 2 Zr 2 O 7 and Yb 2 Zr 2 O 7 . These results suggest a dominant mechanism of incongruent dissolution and surface reorganization for the formation of passivation films. Strong correlations are identified between the leaching rates and cation ionic size, ionic potential, electronegativity differences between A-site cation and Zr, and bonding valence sum of oxygen, suggesting important impacts of structural and bonding characteristics in controlling chemical durability of lanthanide zirconates.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Perovskite-Derived Cs 2 SnCl 6 –Silica Composites as Advanced Waste Forms for Chloride Salt Wastes

Advanced materials and processes are required to separate halides and fission products from complex salt waste streams associated with the chemical reprocessing of used nuclear fuels and molten salt reactor technologies for immobilization into chemically durable waste forms. Here, in this work, we explore an innovative concept using metal-halide perovskites as advanced host phases to incorporate Cs and Cl with very high waste loadings. Wet chemistry-synthesized Cs 2 SnCl 6 powders from CsCl salt solutions are successfully encapsulated into a silica matrix to form a composite using low-temperature spark plasma sintering with tunable Cs and Cl loadings up to 31 wt.% and 26 wt.%, respectively. Chemical durability testing of the composite waste forms by semi-dynamic leaching experiments demonstrates that incongruent leaching mechanism dominated. The metal-halide perovskite-silica composite waste forms display exceptional chemical durability with the long-term release rates of Cs and Cl comparable to or outperforming the state-of-the-art waste form materials but with significantly higher waste loadings. The scalable synthesis of the metal-halide perovskite from wet-chemistry processes opens up new opportunities in designing perovskite-glass composite waste forms for salt wastes with very high waste loadings and exceptional chemical durability for the sustainable development of advanced fuel cycles and next-generation reactor technologies.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Multicomponent pyrochlore solid solutions with uranium incorporation – A new perspective of materials design for nuclear applications

Multicomponent pyrochlore solid solutions with and without uranium incorporation were fabricated and their thermal-mechanical properties were characterized. Multicomponent pyrochlore solid solutions without uranium exhibit comparable thermal conductivity and higher mechanical strength compared to baseline single component rare-earth titanate pyrochlore (A 2 Ti 2 O 7 ). Uranium incorporation reduces hardness as compared with single component compositions. High entropy pyrochlore with uranium displays the highest thermal conductivity within multicomponent pyrochlore solid solutions with significantly better mechanical properties than UO 2 . The measured thermal conductivity correlates well with A-site cation mixing entropy and a modified size disorder parameter, and thus the size disorder and mixing entropy could be good indicators for predicting thermal conductivity of multicomponent pyrochlore solid solutions. This work opens up the possibility of designing multicomponent oxide solid solutions by controlling their chemical disorder/mixing entropy to achieve acceptable thermal-mechanical properties, desired radiation and corrosion performance for potential nuclear waste form and inert matrix fuel applications.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗