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At least 199 records · Page 11

Frequency‐Locked Wireless Multifunctional Surface Acoustic Wave Sensors

Abstract Surface acoustic waves (SAWs) have shown great potential for developing sensors for structural health monitoring (SHM) and lab‐on‐a‐chip (LOC) applications. Existing SAW sensors mainly rely on measuring the frequency shifts of high‐frequency (e.g., >0.1 GHz) resonance peaks. This study presents frequency‐locked wireless multifunctional SAW sensors that enable multiple wireless sensing functions, including strain sensing, temperature measurement, water presence detection, and vibration sensing. These sensors leverage SAW resonators on piezoelectric chips, inductive coupling‐based wireless power transmission, and, particularly, a frequency‐locked wireless sensing mechanism that works at low frequencies (e.g., <0.1 GHz). This mechanism locks the input frequency on the slope of a sensor's reflection spectrum and monitors the reflection signal's amplitude change induced by the changes of sensing parameters. The proof‐of‐concept experiments show that these wireless sensors can operate in a low‐power active mode for on‐demand wireless strain measurement, temperature sensing, and water presence detection. Moreover, these sensors can operate in a power‐free passive mode for vibration sensing, with results that agree well with laser vibrometer measurements. It is anticipated that the designs and mechanisms of the frequency‐locked wireless SAW sensors will inspire researchers to develop future wireless multifunctional sensors for SHM and LOC applications.

Bo, Luyu↗

Single Primary Heat Extraction and Removal Emulator (SPHERE) Long Duration Testing

For the development of heat-pipe cooled microreactors, it is crucial to thoroughly understand the characteristics and functioning of heat pipes across a wide spectrum of operating conditions. Passive heat removal and its long-term performance stability are critical factors in this context. Enhanced experimental data is vital for evaluating the operational lifespan of alkali metal heat pipes. Idaho National Laboratory (INL) has successfully conducted an extended duration test on a high-performance sodium-filled heat pipe, closely monitoring the axial temperature profile, power supplied by the heaters, and heat removed by a gas-gap calorimeter. The results from this testing provide valuable data that are instrumental in supporting heat pipe validation efforts. Specifically, this data aids in the development and validation of Sockeye, the Multiphysics Object-Oriented Simulation Environment (MOOSE) tool under the US-DOE NEAMS program designed for heat pipe modeling. By comparing experimental results with Sockeye’s predictions, the tool's accuracy and reliability can be assessed and improved, thereby enhancing its capability to simulate heat pipe operations under various conditions.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

Effect of fluctuating redox conditions on trace metal release from wetland soils from South Carolina and stream sediments from Tennessee

Natural aquatic systems undergo fluctuating redox conditions due to microbial activity, varying water saturation levels, and nutrients dynamics. With fluctuating oxic and anoxic conditions, trace metals can be mobilized or sequestered in response to changes in iron and sulfur speciation and the concentrations and lability of organic carbon. We conducted a systematic laboratory-based microcosm study to examine the effect of redox fluctuations on trace metal mobility in samples collected from two different natural aquatic systems: riparian wetlands and a stream. We incubated water-saturated soils under three cycles of anoxic-oxic conditions (τanoxic:τoxic = 3) spanning 24 days and monitored the change in dissolved and bioavailable metal (copper (Cu), nickel (Ni), zinc (Zn), cobalt (Co), iron (Fe), and manganese (Mn)) concentrations. The dataset includes the results of the variation in metal concentrations due to redox fluctuations in wetland soils and stream sediments. Additionally, the variation in the bioavailable concentration of metals obtained using passive samplers based on diffuse gradient in thin-films technique is included in the dataset. We have also reported the change in the pH values and dissolved oxygen concentrations in the microcosms during the entire study of 24 days. The dataset also contains the dissolved organic carbon and sulfate concentrations, and the data on fractions of metals bound to reducible and oxidizable phases. For materials from both the wetlands and the stream, anoxic conditions favored Co and Zn release, which corresponded with the reductive dissolution of iron oxides. In contrast, dissolved Cu concentrations increased under oxic conditions for both sites and correlated positively with the release of sulfate. In wetland soils, dissolution of Fe (hydr)oxides increased Ni solubility; however, in stream sediments, Ni release occurred when sulfides or organic matter were oxidized. For stream sediments, each subsequent redox cycle increased the bioavailability of trace metals. Upon redox fluctuations in wetland soils, the bioavailability of Zn and Cu increased, whereas bioavailable Ni and Co decreased. This study illustrates that different trace metals display distinct bioavailability patterns during oxic-anoxic fluctuations in natural environments. The biogeochemical cycling of carbon and nitrogen in systems with redox fluctuations may be influenced by these patterns in trace metal availability in addition to the availability of electron donors and acceptors.

54 ENVIRONMENTAL SCIENCES↗

Coupled Bunch Instabilities Growth in the Fermilab Booster during Acceleration Cycle

Currently, Fermilab Booster accelerates ~4.5E12 protons per pulse (ppp) in 81 bunches from 400 MeV to 8 GeV at 15 Hz to provide beam to multiple HEP experiments and is being upgraded to handle higher beam intensity >6.7E12 ppp at a repetition rate of 20 Hz. In the current mode of operation, we control longitudinal coupled bunch instabilities (LCBI) using combination of passive and active dampers. The issues with LCBI are expected to worsen at higher beam intensities. Here, we would like to investigate at what time in the beam cycle a particular mode is going to originate and how much it contributes at a different time of the acceleration cycle using the collected wall current monitor data from injection to extraction. Also, measure growth rates as a function of beam intensity for some dominant modes. Finally, this paper presents results from the observed LCBI analysis for the highest available beam intensities, unexpected findings, and future plans to mitigate the LCBI at higher beam intensities

43 PARTICLE ACCELERATORS↗

Towards Commercialization of Hydrophone Flow Shields to Improve Passive Acoustic Data Quality (CRADA 678) (Final Report)

This project performed testing, market research, and manufacturing refinement to ready patent-pending hydrophone flow shields developed at PNNL for commercialization. The flow shields reduce the impact of flow noise on underwater sound recordings in areas of strong flow, like tidal channels or rivers. Flow noise is a challenge in many applications where it is necessary to measure underwater sound, including measuring the sound produced by marine energy converters and monitoring marine mammals. This project addressed several key questions about flow shield performance that are high-priority for potential customers and refined existing manufacturing processes to be scalable for market-level production. Specifically, this project conducted both laboratory and field evaluations of the flow shields to comprehensively evaluate their performance. Overall, the results indicate that the flow shields reduce flow noise by over 20 dB at frequencies below 50 Hz at flow speeds greater than 0.5 m/s and are proven to survive deployments more than 6 months long.

42 ENGINEERING↗

Initial development of a method for correlating indentation test results to damage accumulation in high temperature structural materials

This report describes an experimental approach based on microindentation creep or relaxation tests for assessing the remaining creep life of a sample material. The objective for this experimental program is to complement the development of passively loaded in situ surveillance specimens. These surveillance specimens could be placed in future advanced reactors to assess the degradation of structural properties, primary creep and creep-fatigue life, when the material is exposed to actual reactor operating conditions. The specimens and the corresponding indentation test protocol could form the basis of a structural health monitoring program designed to ensure the safe continued operation of the component given the relatively unknown effect of the reactor coolant chemistry, radiation exposure, and other environmental effects on the material properties of the constituent structural materials.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Advanced Laboratory and Field Arrays: Evaluating Sampling Techniques for MHK Biological Monitoring (Task 6)

The overall goal of the task was to identify cost effective biological sampling techniques for MHK environmental monitoring. Protected, demersal, and pelagic fish and selected nektonic invertebrates were surveyed using capture and remote sensing techniques at the PacWave sites. The performance of capture and remote sensing monitoring techniques were evaluated and generic nekton monitoring indices were developed for MHK technologies and sites. In parallel to data collections at the PacWave site, the ability of regression models to characterize, detect, and predict change in acoustic data was evaluated using acoustic data collected in Admiralty Inlet, WA, during a biological monitoring study of the proposed SnoPud tidal turbine project site. Expected outcomes of these efforts included an evaluation of instrumentation and techniques used to monitor biological variability; identification of data streams that can be used to detect and quantify change; and sampling requirements to ensure detection of change in monitored variables.

13 HYDRO ENERGY↗

Online Monitoring of Medium Voltage Cable Systems with Spread Spectrum Time Domain and Frequency Domain Reflectometry

In-service failures of wave energy convertor (WEC) cable systems can have a significant cost and power availability impact. Close parallel research 2019 data showed > 1B£ and 9 Terra-Watt-Hours associated with global off-shore wind (OSW) cable failures (Strang-Moran 2020). OSW is a closely related technology but currently is significantly cheaper than WEC technology. For wave energy to compete, the problem of reliable cable transmission must be mitigated. This project develops isolation technology to allow online high frequency reflectometry testing of medium voltage cables (1 to 10 kV and higher) without arcing or damage to the test instrument. Online spread spectrum time domain reflectometry (SSTDR) testing has been established for low voltage cable systems in the aircraft and rail industry and the ability to detect and locate cable flaws of interest is well understood. Extending reflectometry testing to medium voltage systems could enable detection of cable damage before failures occur thereby allowing repair and replacement of damaged cable segments to be scheduled and managed. The seedling project succeeded to pass and receive high frequency SSTDR signals onto a cable up to 1 kV using a parallel trace isolation circuit board that can be connected onto the test cable. The approach used a novel circuit design for which an invention disclosure has been filed. A proposed sapling project would extend the technology toward the higher operating voltages used by WEC systems, thereby enabling online SSTDR cable monitoring. The goal of the seedling project was to extend the capability of the ARENA cable/motor test bed to address medium voltages and to develop a high pass filter isolation architecture to protect the reflectometry instrument from the low frequency (DC – 60 Hz) line voltage while allowing the high frequency diagnostic signal to pass to and from the test instrument to the live line. Initial efforts focused on passive LCR filter circuits to reduce 60 Hz levels below 10 volts from a 10 kV line while allowing the MHz high frequency chirps to pass onto the cables and for mV signals to be detected. We discovered that the parasitic loss behavior of real high voltage components precluded this approach from working. An alternate approach was adapted for the electric field to couple between two parallel traces on a printed circuit board much like a radio-frequency coupler. The challenge here was and is to have the parallel traces close enough to each other to effectively pass the high frequency chirp onto the live line and receive any reflected signal from any encountered impedance change along the cable. This reflected signal will be in the mV range. The traces however must be far enough apart to not allow arcing on the board. A design with 3 mm spacing was determined to allow the high frequency signal to pass onto the live line and receive the mV signal back into the instrument while reducing the 60 Hz voltage amplitude by >80 dB (more than a factor of 10,000) without allowing arcing from across the parallel traces. This was confirmed by simulation and test.

16 TIDAL AND WAVE POWER↗

Irreversible Catalyst Deactivation Mechanisms of PdO/γ-Al 2 O 3 Catalysts for Lean Methane Oxidation

PdO/γ-Al 2 O 3 catalysts suffer from gradual and irreversible catalyst deactivation under lean CH 4 oxidation conditions, especially in a wet feed. Here, time-resolved CO chemisorption DRIFTS measurements are conducted systematically on a series of PdO/γ-Al 2 O 3 catalysts to probe the surface reactivity of PdO nanoparticles after various in situ pretreatments. At 80 °C, CO barely adsorbs on fully oxidized PdO surfaces but interacts with coordinatively unsaturated Pd sites, causing gradual reduction of the PdO surfaces. This results in the formation of characteristic IR bands on various metallic Pd 0 sites. By monitoring and comparing the formation kinetics of these IR bands on samples before and after CH 4 oxidation, we theorize that the irreversible catalyst deactivation during CH 4 oxidation is caused by PdO surface reconstruction, in which coordinatively unsaturated Pd sites gradually become fully coordinated by oxygen. Effectively, the surface reconstruction leads to the formation of a passivation layer on the PdO nanoparticles, which hinders their ability in activating CH 4 , and hence the subsequent oxidation reaction. Temperature-programmed reduction with CO as the reductant (CO-TPR) reveals that the passivation layer formed during CH 4 oxidation is significant enough to increase the reduction temperature of PdO nanoparticles of the 3.0% PdO/γ-Al 2 O 3 samples, although such an effect is less obvious for the 0.4% PdO/γ-Al 2 O 3 samples. On the other hand, it is also discovered that the passivation layer is not completely inert. Under certain reaction conditions, with some being relatively mild, such as low-temperature CO oxidation in a net lean atmosphere and in the presence of H 2 O, the passivation layer can undergo structure change which results in regeneration or even activation of CH 4 oxidation activity of an already deactivated catalyst. Additionally, it is discovered that the fully coordinated Pd–O surface is a metastable phase under CH 4 oxidation conditions. In the presence of H 2 O and at ambient temperatures, surfaces with coordinatively unsaturated Pd sites are thermodynamically more favorable.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A Coincident CdTe Detector Array for Enhanced Nuclear Process Monitoring

Nuclear fuel cycle aqueous separation processes desire improved real-time material characterization and process monitoring techniques; gamma coincidence spectroscopy has the potential to meet this need in these high throughput and high radiation environments based on its ability to reduce background noise, thereby enhancing detection limits and improving isotopic identification accuracy. A detector array composed of three CdTe detectors was designed to surround a chemical processing pipe in a reprocessing facility and evaluate the feasibility of passively assaying the nuclear materials flowing though this measurement point. This array uses commercial off the shelf components that are radiation hard and highly efficiency at low energies relevant to actinide photon signatures. Detector efficiency characterizations, coincidence detection, and potential configuration improvements are presented here.

Good, Erin C.↗

Development of Bismuth and Platinum Bi-Metallic Nanoparticles to Enhance Melt Wire Temperature Resolution

Advanced manufacturing (AM) based on direct-write (DW) technologies has emerged as the predominant enabler for the fabrication of active and passive sensors to be deployed in harsh operating environments seen in a nuclear reactor. Recently, Idaho National Laboratory and Boise State University have recently established capabilities to incorporate advanced manufacturing (AM) methods to accelerate, modernize and enhance functionality of nuclear sensors and instrumentation to achieve the goal of enhancing the safety and efficiency of nuclear reactors. A significant thrust of this work includes the development of nuclear relevant feedstock materials compatible with a variety of direct-write processes for the development, fabrication and testing of AM sensors for peak temperature detection and neutron flux monitoring. For this report, bismuth and bismuth/platinum (BiPt) bi-metallic nanoparticles were synthesized using wet chemical approaches to develop bi-metallic feedstock materials to enhance the sensitivity of melt wires for peak temperature detection. Nanoparticle characterization was performed with Transmission Electron Microscopy (TEM) for nanoparticle composition and size, Transmission X-Ray Diffraction Fluorescence (TXRF) for nanoparticle composition, and Differential Scanning Calorimetry to elucidate the melting point of BiPt bi-metallic nanoparticles. Preliminary results indicate bi-metallic BiPt nanoparticles as a viable pathway for fabricating high resolution AM melt wires.

36 MATERIALS SCIENCE↗

Bioremediation Retrospective: DOE Experiences and Lessons Learned – 26131

The U.S. Department of Energy (DOE) has implemented bioremediation strategies for chlorinated volatile organic compounds (cVOCs) for more than three decades across multiple contaminated groundwater sites. A retrospective analysis conducted by the Savannah River National Laboratory (SRNL) and collaborating field sites evaluated the design, performance, and outcomes of bioremediation projects at DOE’s Savannah River, Hanford, Idaho, Mound, and Pinellas sites. This retrospective was based on a series of case studies, leveraging historical documentation and site interviews. Technical approaches employed at the various sites were explored, including active bioremediation, enhanced attenuation (EA), and monitored natural attenuation, with specific sub-sections discussing anaerobic, aerobic, and combined anaerobic-aerobic strategies. Each case study includes detailed descriptions of the site-specific conditions, deployment strategies, regulatory considerations, metrics, and performance. Key findings include general cost savings compared to traditional remedies such as pump and treat (P&T), significant success in applying enhanced attenuation to transition remedies toward a passive site management strategy, and documentation of robust subsurface microbial communities at most sites limiting the need for bioaugmentation. Challenges highlighted in the study include underperformance due to poor amendment delivery in low-permeability zones and unfavorable biogeochemical conditions, emphasizing the importance of site-specific designs. Cost analysis across DOE sites suggests bioremediation may offer long-term economic benefits. The retrospective study underscores valuable lessons that can help inform current and future bioremediation efforts.

Newby, Deborah T. [Savannah River National Laborat↗

Operando Acoustic Monitoring of SEI Formation and Long-Term Cycling in NMC/SiGr Composite Pouch Cells

Stable long-term cycling and solid-electrolyte-interphase (SEI) formation are key challenges in the design of Si/graphite composites as Li-ion battery (LIB) anode materials. Typically, these long-term cycling properties are examined in flooded half-cell settings making use of a Li-metal counter electrode and a Si/graphite working electrode. This form factor has the advantage of offering an unlimited supply of Li-ions and electrolyte, thus isolating performance degradation to the passivation of the working electrode. However, half-cell studies are ineffective in revealing performance and degradation mechanisms of the Si/graphite composite in a more commercially realistic full cell setting. This paper outlines an operando acoustic technique that can offer insights on SEI formation and capacity degradation of Si/graphite composites in a full cell setting. Through a combination of electrochemical and chemical analyses, we show that increasing passivation of the silicon particles in the Si/graphite composite anode is correlated with an increase in the acoustic time-of-flight shift. We further show that temporary loss of the acoustic signal during the first cycle is associated with significant gassing of the cell. The operando acoustic technique outlined here is low-cost, simple to setup and has the potential for localized resolution, indicating usefulness in commercial-scale Si/graphite cell quality control and diagnosis.

42 ENGINEERING↗

Deep learning with mixup augmentation for improved pore detection during additive manufacturing

In additive manufacturing (AM), process defects such as keyhole pores are difficult to anticipate, affecting the quality and integrity of the AM-produced materials. Hence, considerable efforts have aimed to predict these process defects by training machine learning (ML) models using passive measurements such as acoustic emissions. This work considered a dataset in which keyhole pores of a laser powder bed fusion (LPBF) experiment were identified using X-ray radiography and then registered both in space and time to acoustic measurements recorded during the LPBF experiment. Due to AM’s intrinsic process controls, where a pore-forming event is relatively rare, the acoustic datasets collected during monitoring include more non-pores than pores. In other words, the dataset for ML model development is imbalanced. Moreover, this imbalanced and sparse data phenomenon remains ubiquitous across many AM monitoring schemes since training data is nontrivial to collect. Hence, we propose a machine learning approach to improve this dataset imbalance and enhance the prediction accuracy of pore-labeled data. Specifically, we investigate how data augmentation helps predict pores and non-pores better. This imbalance is improved using recent advances in data augmentation called Mixup, a weak-supervised learning method. Convolutional neural networks (CNNs) are trained on original and augmented datasets, and an appreciable increase in performance is reported when testing on five different experimental trials. When ML models are trained on original and augmented datasets, they achieve an accuracy of 95% and 99% on test datasets, respectively. We also provide information on how dataset size affects model performance. Lastly, we investigate the optimal Mixup parameters for augmentation in the context of CNN performance.

36 MATERIALS SCIENCE↗

Deep learning with mixup augmentation for improved pore detection during additive manufacturing

In additive manufacturing (AM), process defects such as keyhole pores are difficult to anticipate, affecting the quality and integrity of the AM-produced materials. Hence, considerable efforts have aimed to predict these process defects by training machine learning (ML) models using passive measurements such as acoustic emissions. This work considered a dataset in which keyhole pores of a laser powder bed fusion (LPBF) experiment were identified using X-ray radiography and then registered both in space and time to acoustic measurements recorded during the LPBF experiment. Due to AM’s intrinsic process controls, where a pore-forming event is relatively rare, the acoustic datasets collected during monitoring include more non-pores than pores. In other words, the dataset for ML model development is imbalanced. Moreover, this imbalanced and sparse data phenomenon remains ubiquitous across many AM monitoring schemes since training data is nontrivial to collect. Hence, we propose a machine learning approach to improve this dataset imbalance and enhance the prediction accuracy of pore-labeled data. Specifically, we investigate how data augmentation helps predict pores and non-pores better. This imbalance is improved using recent advances in data augmentation called Mixup, a weak-supervised learning method. Convolutional neural networks (CNNs) are trained on original and augmented datasets, and an appreciable increase in performance is reported when testing on five different experimental trials. When ML models are trained on original and augmented datasets, they achieve an accuracy of 95% and 99% on test datasets, respectively. We also provide information on how dataset size affects model performance. Lastly, we investigate the optimal Mixup parameters for augmentation in the context of CNN performance.

42 ENGINEERING↗

Surveillance Test Articles Development

Material degradation in Advance Test Reactors (ATR) is governed by irradiation, corrosion, elevated temperature exposure and cyclic mechanical creep-fatigue loads. This degradation information during reactor operation condition is limited. Hence, material damage monitoring is a key aspect of the design, analysis and licensing of ATR components. The idea is to monitor material component operation conditions of component by using a surveillance test article. This test article is fabricated with bi-metal configuration with two different thermal expansion coefficients, and design is motivated by Simplified Model Test (SMT) specimen which can capture structure-like mechanical response. Upon raising temperature of the bi-metal test article configuration, expansion mismatch results tensile load on specimen. Thus, temperature dependent passively actuated loading is achieved. The idea is to place this surveillance test article in reactor at location ‘x’ to surveil the mechanical response at critical location ‘y’. By calibrating the test article design, material degradation at critical location can be surveilled through assessing the degradation in surveillance test article. This study presents test article development with different material combinations and follow-up experimental testing work through passively loading test article with temperature history. The test article geometry and observed test results are presented in presentation slides.

36 MATERIALS SCIENCE↗

Low-loss superconducting titanium nitride grown using plasma-assisted molecular beam epitaxy

Titanium nitride (TiN) is a known superconducting material that is attractive for use as passive components in superconducting circuits for both conventional and quantum information devices. In contrast to conventional synthesis techniques, here, plasma-assisted molecular beam epitaxy is reported to produce high-quality TiN on bare silicon wafers. Using a rf-plasma source to crack the nitrogen molecules and a conventional high-temperature effusion cell for titanium, TiN growth is completed under nitrogen-rich conditions. The growth and nucleation is monitored in situ, while the structure and composition are characterized using x-ray diffraction, atomic force microscopy, x-ray photoelectron spectroscopy, secondary ion mass spectroscopy, and scanning transmission electron microscopy. The stoichiometric TiN (111) films sit on an amorphous nitride layer with low impurity concentrations. The films superconduct with Tc=5.4 K, and coplanar waveguide resonators are fabricated with a small center width of 6 μm that demonstrate single-photon quality factors approaching 1M and high-power quality factors over 5M without observing saturation.

Richardson, C. J. K. (ORCID:0000000188175347)↗

Meteorological Conditions and Atmospheric Components Concentration in Urban Sites in Knoxville, USA. 2024

This dataset, which contains five csv files, reports several meteorological conditions such as temperature, wind speed, solar radiation, and net radiation measured in Cumberland Estates Park (CEP) and Socially Equal Energy Efficient Development (SEEED) sites in Knoxville, Tennessee, USA. Also, hourly concentration of particulate matter (PM) with different aerodynamic diameter and inorganic gases such as ozone and nitrogen dioxide measured in the two are included in this dataset. The concentrations of PM and inorganic gases were monitored using the MODULAIR, a low-cost sensor equipped with a solar power module. The measurement of the concentration of biogenic and anthropogenic volatile organic compounds (VOCs) of the two sites was determined using a High-Resolution Proton Transfer Reaction Time of Flight Mass Spectrometer (PTR-ToF-MS). The VOCs were collected using miniature canister (400 mL) equipped with female RAVEqc valve to 1/4” male compression fitting and an integrated passive air sampling kit. This work is a part of a larger study which investigates the impact of soil moisture and plant evapotranspiration on ambient temperature and relative humidity in several city parks in Knoxville, Tennessee.

54 ENVIRONMENTAL SCIENCES↗