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At least 217 records · Page 12

22 K superconductivity in Ba Fe 2 As 2 exposed to F 2

Several previous reports on undoped AEFe 2 As 2 (AE = alkaline earth metal) point to drops in resistivity indicative of possible superconductivity and some degree of Meissner effect in the magnetic susceptibility. Also, based on both resistivity and magnetic susceptibility measurements, controlled exposure to water vapor has been shown to induce superconductivity in AEFe 2 As 2 . In our study, BaFe 2 As 2 single crystals grown using the self-flux method showed a full resistive drop around 22 K and magnetic shielding, when exposed to fluorine gas postgrowth. Our measurements indicate electron (donor) doping via atomic substitution of F for As is concurrent with the observed superconductivity, which sheds light on the likely effect of exposure to water vapor in previous work. Like doping experiments (such as substitution of Co for Fe, P for As, or K for Ba) in AEFe 2 As 2 to date, the present work is consistent with suppression of the spin density wave transition coincident with the appearance of T c . In addition to answering the puzzle of superconductivity in undoped or water vapor exposed AEF 2 As 2 , our results also represent a fast (20 min exposure to 5% F in He) and reliable method suitable for inducing superconductivity in thin films of AEFe 2 As 2 . As a result, some supportive work on BaFe 2 As 2 exposed to Cl 2 is also presented.

36 MATERIALS SCIENCE↗

Perturbative study of the one-dimensional quantum clock model

In this report we calculate the ground-state energy density ε(g) for the one-dimensional N-state quantum clock model up to order 18, where g is the coupling and N = 3,4,5,...,10, 20. Using methods based on the Padé approximation, we extract the singular structure of ε"(g) or ε(g). They correspond to the specific heat and free energy of the classical two-dimensional (2D) clock model. We find that, for N = 3, 4, there is a single critical point at g c = 1. The heat capacity exponent of the corresponding 2D classical model is α = 0.34 ± 0.01 for N = 3, and α = - 0.01 ± 0.01 for N = 4. For N > 4, there are two exponential singularities related by g c1 = 1/g c2 , and ε(g) behaves as Ae - $\frac{c}{|g_c -g|^a}$ + analytic terms near g c . The exponent σ gradually grows from 0.2 to 0.5 as N increases from 5 to 9, and it stabilizes at 0.5 when N > 9. The phase transitions exhibited in these models should be generalizations of the Kosterlitz-Thouless transition, which has σ = 0.5 .

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Security Enhancement of Network Constraint Grid-Edge Energy Management System

Network constrained grid edge energy management system (EMS) provides economic solution for active and reactive power dispatch of distributed energy resources (DERs) at the grid edge level. Grid edge EMS ensures secure interconnection of a circuit segment to the distribution system by maintaining grid code requirements (e.g. IEEE 1547–2018). Grid edge EMS is dependent on communication to receive load measurement, which brings a risk of unobservable false data injection attacks (FDIAs). To mitigate the risk, this paper proposes a framework to enhance resilient operation of grid edge EMS by detecting the unobservable FDIAs on loads and replacing them with forecasted values. In this work, a two-step detection algorithm is proposed. In first step, conventional residual based algorithm is deployed. Autoencoder (AE) based data driven mechanism is included in second step to detect the presence of unobservable FDIAs. After ensuring the presence of FDIA, its specific location is detected by checking the maximum residue values till the predefined threshold value is reached. Detected false data injected loads are then replaced with forecasted load values following long-short term memory (LSTM) based forecast to ensure resilient performance of grid edge EMS in the presence of attacks. This proposed security enhancement framework for grid edge EMS is evaluated in IEEE 13 bus system with three integrated DERs. Numerical simulation shows the validation of the proposed framework by reducing voltage violation in real operation of grid edge EMS.

cyber attack detection↗

Securing 3D NAND Without Density Loss via In-Situ Encryption Using a Single Transistor XOR Cell

In this article, we push lightweight XOR-based in-situ encryption to extreme density by proposing a singletransistor XOR memory cell and applying it to 3D NAND, enabling secure data storage without density loss. Using a ferroelectric field-effect transistor (FeFET) as an example technology, we demonstrate that: i) a single-transistor memory can realize the XOR function by exploiting the ability to charge the source and drain separately and control current flow direction, eliminating the need for conventional encrypted cells that rely on complementary devices; ii) with a XOR-based cipher, encryption and decryption can be mapped to in-situ array operations, where ciphertext is stored as the threshold voltage (VTH) states of FeFETs in a NAND string, and decryption is achieved through read operations using key-dependent complementary source/drain bias; iii) the proposed technique is scalable to multi-level cell (MLC) storage by encrypting and decrypting data bit by bit; iv) using an integrated NAND FeFET array, we experimentally demonstrate encryption and decryption operations for both single-level cell (SLC) and MLC storage; v) systemlevel benchmarking shows that the proposed technique achieves 48× and 278× improvements in encryption and decryption throughput, respectively, compared to AES.

36 MATERIALS SCIENCE↗

Single-component-at-a-time variation study for glass-ceramic waste forms

Here, a 51-sample composition variation study was performed on glass-ceramic waste forms for a raffinate waste stream from aqueous reprocessing of used nuclear fuel containing high fractions of Mo, alkalis, alkaline earths (AEs), and rare earths (REs). The study was designed with a single-component-at-a-time variation approach off a centroid composition. The components that were varied included Al, B, Ca, Li, Mo, Na, REs, Si, Zr, and Others (containing minor components). Data analysis included crystallization curves, microstructure, and phase compositions. A number of components (i.e., Li 2 O, B 2 O 3 , REO x , MoO 3 , Na 2 O, and ZrO 2 ) significantly impacted the concentration and chemistry of phases, especially the primary phases of oxyapatite [i.e., Ca 2 RE 8 (SiO 4 ) 6 O 2 ] and powellite (i.e., AEMoO 4 ), precipitated in the slow-cool heat-treated waste forms; minor phases included cerianite [i.e., Ce x Zr (1-x) O 2 ], Ba-molybdate [i.e., Ba(Gd 0.67 Mo 0.33 O 3 ], noble metals, pollucite (i.e., CsAlSiO 4 ), and RE-borosilicate (i.e., RE 3 BSi 2 O 10 ).

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Auger spectroscopy beyond the ultra-short core-hole relaxation time approximation

Abstract We present a time-dependent computational approach to study Auger electron spectroscopy (AES) beyond the ultra-short core-hole relaxation time approximation and, as a test case, we apply it to the paradigmatic example of a one-dimensional Mott insulator represented by a half-filled Hubbard chain. The Auger spectrum is usually calculated by assuming that, after the creation of a core-hole, the system thermalizes almost instantaneously. This leads to a relatively simple analytical expression that uses the ground-state with a core-hole as a reference state and ignores all the transient dynamics related to the screening of the core-hole. In this picture, the response of the system can be associated to the pair spectral function. On the other hand, in our numerical calculations, the core hole is created by a light pulse, allowing one to study the transient dynamics of the system in terms of the pulse duration and in the non-perturbative regime. Time-dependent density matrix renormalization group calculations reveal that the relaxation process involves the creation of a polarization cloud of doublon excitations that have an effect similar to photo-doping. As a consequence, there is a leak of spectral weight to higher energies into what otherwise would be the Mott gap. For longer pulses, these excited states, mostly comprised of doublons, can dominate the spectrum. By changing the duration of the light-pulse, the entire screening process can be resolved in time.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Evaluating the Effect of Electrolyte Additive Functionalities on NMC622/Si Cell Performance

Unstable electrode/electrolyte interface is the major cause of degradation for silicon (Si)-based anodes for lithium (Li)-ion batteries. Development of functional electrolyte additives can provide a viable path toward stabilizing the dynamic Si/electrolyte interface, which will benefit the development of high energy density Li-ion batteries. Here, we evaluate polymerizable electrolyte additives with varying functional groups (fluorocarbon, thiophosphate, and fluorophosphazene). The additives are examined using LiNi 0.6 Mn 0.2 Co 0.2 O 2 /Si full cells where the cycle performance and impedance are measured. Electrochemical tests show that the fluorine-containing additives provide better passivation at the Si electrode, leading to enhanced full cell performance. Here, among the three additives examined, best electrochemical performance is observed from the fluorocarbon-containing compound, followed by fluorophosphazene- and thiophosphate-containing compounds. Characterization of the solid electrolyte interphase (SEI) on cycled electrodes using Auger electron spectroscopy (AES), X-ray photoelectron spectroscopy (XPS), and attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR) reveal that higher concentration of fluorine and lithium oxide, and lower concentration of carbonate and organic species correlate with enhanced electrochemical performance.

25 ENERGY STORAGE↗

Study on Intelligent Compaction-Equipment Logistics Scheduling and Propagation Characteristics of Vibration Wave in Nonlinear Systems with Multistability Based on Field Test

The equipment scheduling and propagation characteristics of vibration wave from vibratory roller ⟶ filling material nonlinear systems with multistability are the core problems of subgrade intelligent construction technology, and the logistics scheduling of the equipment is directly related to the construction efficiency. Aiming at the shortages, one typical subgrade located at the Gu’an station of Beijing-Xiong’an city railway is selected to research and finish the field tests; some findings are shown as follows: first, some valuable suggestions about the logistics scheduling of intelligent equipment are proposed, which can break the barriers between the organizations and improve construction efficiency; second, when the vibration wave propagates from the vibratory roller ⟶ surface of filling material ⟶ different buried depths of filling material, the peak acceleration of vibration wave gradually decreases and is hyperbolic distribution approximately. At the same time, the sensitive of attenuation is shown as follows: Z R 2 >0.9), and the concrete functional relationship among different amplitudes of harmonics can be summarized as y = Ae −BX ; fourth, the vibration energy is mainly concentrated near 10–30 Hz in the vibratory roller, but when the vibration wave propagates from vibratory roller⟶filling material, the vibration energy gradually decreases with the increase in depth, and the marginal spectrum gradually changes from one peak to two peaks, that is, 30–50 Hz and 50–100 Hz; fifth, the vibration energy in the vibrational wheel is distributed averagely in the compaction process, and the effective compaction time is two seconds, which will be helpful for revealing the propagation characteristics of vibration wave, optimizing the compaction quality control models and providing some support for the development of intelligent compaction theory of railway subgrade.

Han, Yixuan↗

ModuleOT

ModuleOT is an open hardware security platform which provides all features necessary for securing remote energy resources. The platform consists of a physical bump in-the wire device which runs a custom-built application built with Go and Python and leverages AES-NI Instruction set available on modern hardware for cryptographic acceleration. By combining these features, ModuleOT acts as an all-in-one low-cost solution to enable cryptographically secured communications to any critical remote servers or devices. Because the software application has been built using Golang, this source can be easily compiled for different hardware platforms. The module is designed to provide the following core features: (1) encrypted communications across an untrusted network, (2) certificate-based authentication with secure storage, (3) hardware cryptographic acceleration, (4) IP-based whitelisting, (5) local firewall management, and (6) legacy (RS485) device support.

Hasandka, Adarsh↗

labquake_future_prediction

The labquake_future_prediction code is a collection of python modules and scripts that serves as supporting information for the article “Predicting future laboratory fault friction through deep learning” for publication in the journal of “Geophysical Research Letters”. It is designed to predict laboratory fault slips in the immediate future by scanning continuous acoustic emission (AE) waveforms recorded in laboratory biaxial shear experiments. The predictions are made with a deep learning model based on convolutional encoder-decoder (CED) models and the Transformer model primarily developed for Natural Language Processing (NLP). The deep learning model is trained with the tensorflow package using publicly available laboratory data sets in standard binary file format in numpy. The utility functions for reading data files, configuring model hyperparameters, constructing the CED and Transformer models, training and testing of the models are defined in python module files. The workflow of training the models for labquake future predictions and the multiple GPU’s rapid model hyperparameter optimization as described in the journal article, are demonstrated in accompanying python script files and Jupyter notebooks.

Wang, Kun↗

Sustainable production of radionuclidically pure antimony-119

Background Radiopharmaceutical therapy (RPT) uses radionuclides that decay via one of three therapeutically relevant decay modes (alpha, beta, and internal conversion (IC) / Auger electron (AE) emission) to deliver short range, highly damaging radiation inside of diseased cells, maintaining localized dose distribution and sparing healthy cells. Antimony-119 ( 119 Sb, t 1/2 = 38.19 h, EC = 100%) is one such IC/AE emitting radionuclide, previously limited to in silico computational investigation due to barriers in production, chemical separation, and chelation. A theranostic (therapeutic/diagnostic) pair can be formed with 119 Sb’s radioisotopic imaging analogue 117 Sb (t 1/2 = 2.80 h, E γ = 158.6 keV, I γ = 85.9%, β + = 262.4 keV, I β+ = 1.81%). Results Within, we report techniques for sustainable and cost-effective production of pre-clinical quality and quantity, radionuclidically pure 119 Sb and 117 Sb, novel low energy photon measurement techniques for 119 Sb activity determination, and physical yields for various tin target isotopic enrichments and thicknesses using (p, n) and (d, n) nuclear reactions. Additionally, we present a two-column separation providing a radioantimony yield of 73.1% ± 6.9% (N = 3) and tin separation factor of (6.8 ± 5.5) x 10 5 (N = 3). Apparent molar activity measurements for deuteron produced 117 Sb using the chelator TREN-CAM were measured at 42.4 ± 25 MBq 117 Sb/µmol (1.14 ± 0.68 mCi/µmol), and we recovered enriched 119 Sn target material at a recycling efficiency of 80.2% ± 5.5% (N = 6) with losses of 11.6 mg ± 0.8 mg (N = 6) per production. Conclusion We report significant steps in overcoming barriers in 119 Sb production, chemical isolation and purification, enriched target material recycling, and chelation, helping promote accessibility and application of this promising therapeutic radionuclide. We describe a method for 119 Sb activity measurement using its low energy gamma (23.87 keV), negating the need for attenuation correction. Finally, we report the largest yet-measured 119 Sb production yields using proton and deuteron irradiation of natural and enriched targets and radioisotopic purity > 99.8% at end of purification.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Processed Lab Data for Neural Network-Based Shear Stress Level Prediction

Machine learning can be used to predict fault properties such as shear stress, friction, and time to failure using continuous records of fault zone acoustic emissions. The files are extracted features and labels from lab data (experiment p4679). The features are extracted with a non-overlapping window from the original acoustic data. The first column is the time of the window. The second and third columns are the mean and the variance of the acoustic data in this window, respectively. The 4th-11th column is the the power spectrum density ranging from low to high frequency. And the last column is the corresponding label (shear stress level). The name of the file means which driving velocity the sequence is generated from. Data were generated from laboratory friction experiments conducted with a biaxial shear apparatus. Experiments were conducted in the double direct shear configuration in which two fault zones are sheared between three rigid forcing blocks. Our samples consisted of two 5-mm-thick layers of simulated fault gouge with a nominal contact area of 10 by 10 cm^2. Gouge material consisted of soda-lime glass beads with initial particle size between 105 and 149 micrometers. Prior to shearing, we impose a constant fault normal stress of 2 MPa using a servo-controlled load-feedback mechanism and allow the sample to compact. Once the sample has reached a constant layer thickness, the central block is driven down at constant rate of 10 micrometers per second. In tandem, we collect an AE signal continuously at 4 MHz from a piezoceramic sensor embedded in a steel forcing block about 22 mm from the gouge layer The data from this experiment can be used with the deep learning algorithm to train it for future fault property prediction.

15 GEOTHERMAL ENERGY↗

The importance of accounting for landscape position when investigating grasslands: A multidisciplinary characterisation of a Californian coastal grassland

Data from the characterisation of the Point Reyes Field Site, published in AGU Earth's Future under the title: The importance of accounting for landscape position when investigating grasslands: A multidisciplinary characterisation of a Californian coastal grassland. This paper explored the effect of landscape position on the response of a Californian grassland to seasonal changes. All files are csv files. The EMI data contains 8 csv files with a metadata csv explaining the columns. The dataset also includes soil variables including total concentrations calculated from fused samples, then dissolved and measured on ICP-AES for whole-rock elements and ICP-MS for trace elements. Mineral composition was attained using X-ray diffraction at BL 11-3 at SSRL . Data was then run through the High Score database to characterise different mineral phases. total It also includes a table with bulk soil characteristics such as soil pH, cation exchange capacity, and soil textural data. Data from Teros 12 Meter soil moisture, electrical conductivity and temperature sensors are presented in SMS Csv file. While the WL bottom and top files contain data from Piezometers measuring the ground water table. We have included a csv file that contains soil CO2 efflux data from Feb 2021-Oct 2021 in the Point Reyes Grassland Experiment We have included the spatially orientated (easting northing) remotely sensed datasets that were used in the K-means clustering analysis conducted on our site with electrical conductivity, normalised difference vegetation index, elevation, slope, solar radiation, topographic position and wetness index, and a clustering score. Finally there is a list of all the identified grassland species at the site.For more information on flux data, please contact the corresponding author.

54 ENVIRONMENTAL SCIENCES↗

Project Plan: Salt in Situ Heater Test

This project plan gives a high-level description of the US Department of Energy Office of Nuclear Energy (DOE-NE) Spent Fuel and Waste Disposition (SFWD) campaign in situ borehole heater test project planned for the Waste Isolation Pilot Plant (WIPP) site, titled the Brine Availability Test in Salt (BATS). BATS is the first stage in a planned sequence of tests to bolster the technical basis for disposal of heat generating waste in salt. This plan provides an overview of the schedule and responsibilities of the parties involved. This project is a collaborative effort by Sandia, Los Alamos, and Lawrence Berkeley National Laboratories to execute a series of small-diameter borehole heater tests in salt for the DOE-NE SFWD campaign. Design of a heater test in salt at WIPP has evolved over several years. The experiment has begun in January 2020 and the first phase will continue for several months with the possibility for follow on testing. BATS comprises a suite of modular tests, which consist of a group of adjacent horizontal boreholes in the wall of drifts at WIPP. Each test is centered around a packer-isolated heated borehole (12.2 cm [4.81 diameter) containing equipment for water-vapor collection and borehole closure monitoring, surrounded by smaller-diameter (up to 5.3 cm [2.11 diameter) satellite observation boreholes. Observation boreholes contain grouted-in temperature sensors, electrical resistivity tomography (ERT) sensors, and fiber optics; packer-isolated tracer release and sampling intervals; and acoustic emission (AE) piezoelectric sensors. A larger-diameter (12.2 cm [4.81) satellite borehole includes sorel and salt cement plugs, as part of an engineered barrier sealing test. The first two tests, to be implemented in parallel, are heated (target borehole wall temperature of 120 °C) and unheated, with similar arrays of observation borehole monitoring changes. Follow-on tests will be designed using information gathered from the first two tests, and may be conducted at other borehole wall temperatures, use multiple observation boreholes, and may include different measurement types and test designs. This 2020 update of the original 2018 project plan satisfies DOE-NE Spent Fuel and Waste Science and Technology (SFWST) milestone M3SF-205N010303034, as part of the SNL "Salt Disposal R&D" work package.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Tests and Field Mapping of RODM01 Septum Magnet

RODM01 is a septum magnet located in the extraction region of LANSCE Proton Storage Ring. Tests and field mapping of RODM01 Set #2 were performed on 02/04/2020 by members of AOT-MDE, AOT-RFE and AOT-AE Groups. Setups of test and mapping are presented. Magnetic field measurements was performed using Hall probe. Results of measurements are almost identical to that of RODM01 Set #1 performed in July 2018. Trim coil current of magnet selected to be as - 9.28 A.

43 PARTICLE ACCELERATORS↗

Reification of latent microstructures: On supervised unsupervised and semi-supervised deep learning applications for microstructures in materials informatics

Machine learning (ML), including deep learning (DL), has become increasingly popular in the last few years due to its continually outstanding performance. In this context, we apply machine learning techniques to "learn" the microstructure using both supervised and unsupervised DL techniques. In particular, we focus (1) on the localization problem bridging (micro)structure (localized) property using supervised DL and (2) on the microstructure reconstruction problem in latent space using unsupervised DL. The goal of supervised and semi-supervised DL is to replace crystal plasticity finite element model (CPFEM) that maps from (micro)structure (localized) property, and implicitly the (micro)structure (homogenized) property relationships, while the goal of unsupervised DL is (1) to represent high-dimensional microstructure images in a non-linear low-dimensional manifold, and (2) to discover a way to interpolate microstructures via latent space associating with latent microstructure variables. At the heart of this report is the applications of several common DL architectures, including convolutional neural networks (CNN), autoencoder (AE), and generative adversarial network (GAN), to multiple microstructure datasets, and the quest of neural architecture search for optimal DL architectures.

36 MATERIALS SCIENCE↗

5.5 Hybrid Additively Manufactured Tooling for Large Composite Structures

This program sought to lower tooling costs for tightly toleranced, large composite aerostructures by using large format additive manufacturing (LFAM). LFAM tooling has the potential to lower tooling costs, but the large and unpredictable thermal expansion of polymer-based tooling did not previously allow for the production of large structures made with high performance resins requiring 350 deg F cures. Geometric tolerance issues and demolding concerns continued to arise. The proposed approach for this work was to print a thin shell via additive manufacturing that would be used as a scaffold for a conventional tooling prepreg. The prepreg would be laminated and cured onto both sides of the shell, creating a tool with a sandwich construction. The cured prepreg would then be machined and serve as the tooling surface. In addition to providing a clean, pit-free surface, the prepreg stiffness and low thermal expansion would physically restrain the AM shell and prevent it from expanding during thermal cycling, thus preventing any geometric mismatch between the nominal and actual part dimensions. A stair-step approach was taken to prove out this approach. Coupon level testing was done to ensure a good bond was possible between the AM shell and the tooling prepreg. These samples were also used to determine the amount of prepreg needed to achieve the desired coefficient of thermal expansion (CTE). The project team than progressed to a subscale tool measuring two feet in length. The geometry used was a C-section spar from Airbus’ Wing of Tomorrow program. A hybrid tool, using the AM shell and tooling prepreg, was made, and a composite part was fabricated with the tool. Dimensional scans of the tool and part indicated that the desired CTE was achieved with the tool. A second tooling approach was taken to reduce risk. In this approach, a subscale tool of the same geometry as previously mentioned was created, but the tool was entirely constructed of the tooling prepreg. AM was used to print a “master” that was then used to fabricate the tool by creating a splash off of the master using tooling prepreg. The innovation was that the master was not machined, but rather, was used right off the printer after a small amount of surface preparation. Removing this machining step was thought to make this approach economically viable when compared to conventional master fabrication. As before, the tool was used to fabricate a part and tested for dimensional accuracy. For the conclusion of the program, a ten-foot tool was created using the hybrid tool approach. The geometry also came from the Airbus C-section spar previously mentioned. Some difficulty arose in accurately predicting the geometry of the tool after laminating the tooling prepreg, resulting in multiple material additions and a tool geometry change. A part was fabricated in an autoclave using the tool. A cost savings of almost 50% was achieved on the subscale tool in both the hybrid and master-style tool, but the savings dropped considerably as the tool length increased in the full-scale tool. Given the less than expected cost savings and added complexity of the tool construction, it is suggested that the master-style tool is best for immediate commercialization for larger tools (although it may be appropriate for smaller, table-top size tools). Since its construction is very similar to conventionally made composite tooling, there already exists a broad supply chain for building the tool, and project partner Additive Engineering Solutions (AES) is well acquainted with the design and build of the AM master needed.

36 MATERIALS SCIENCE↗

Investigating Wireless Quantum Key Distribution for Advanced Reactor Communications

Remote operation of small modular reactor (SMR) facilities is an appealing prospect for streamlined operation costs, safety concerns, and user convenience. The ability to guarantee security of communication channels between offsite users and nuclear reactor facilities is critical to enabling remote operations, given the sensitive nature of reactor state data. This report proposes a configuration implementing quantum key distribution (QKD) and advanced encryption standard (AES) protocols to establish secure reactor data feeds. The model outlined, which utilizes the Argonne-developed SeQUeNCe software package and custom MATLAB code, determines free-space channel losses for microwave-band communications in a variety of weather conditions and simulates QKD via ground-satellite links. This report demonstrates the feasibility of repeatable, real-time key generation and distribution for this configuration towards enabling secure wireless reactor communications.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗