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DOE OSTI2021

Reactor scale simulations of ALD and ALE: Ideal and non-ideal self-limited processes in a cylindrical and a 300 mm wafer cross-flow reactor

Here, we have developed a simulation tool to model self-limited processes such as atomic layer deposition (ALD) and atomic layer etching inside reactors of arbitrary geometry as well the output of in situ quartz crystal microbalance and mass spectrometry. We have applied this model to two standard types of cross-flow reactors: a cylindrical tube reactor and a model 300 mm wafer reactor, and explored both ideal and nonideal self-limited kinetics. The model results are in agreement with experimental results and analytic expressions obtained using a simple plug-flow model for the cylindrical tube reactor. We also extended the simulations to consider two nonideal self-limited processes: soft-saturating processes characterized by a slow reaction pathway and processes where surface by-products can compete with the precursor for the same pool of adsorption sites. Our results show that it is possible to have a self-limited process with saturated yet inhomogeneous growth profiles due to the competition of reactor by-products. This is in agreement with experimental observations for titanium dioxide ALD from titanium tetraisopropoxide and titanium tetrachloride precursors.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2023

Search for doubly charged Higgs boson production in multi-lepton final states using 139 fb$^{-1}$ of proton–proton collisions at $\sqrt{s}$ = 13 TeV with the ATLAS detector

A search for pair production of doubly charged Higgs bosons ($H$ ±± ), each decaying into a pair of prompt, isolated, and highly energetic leptons with the same electric charge, is presented. The search uses a proton–proton collision data sample at a centre-of-mass energy of 13 TeV corresponding to an integrated luminosity of 139 fb -1 recorded by the ATLAS detector during Run 2 of the Large Hadron Collider (LHC). This analysis focuses on same-charge leptonic decays, $H$ ±± → $\ell$ ± $\ell$ '± where $\ell$,$\ell$ ' = $e, μ, τ$, in two-, three-, and four-lepton channels, but only considers final states which include electrons or muons. No evidence of a signal is observed. Corresponding upper limits on the production cross-section of a doubly charged Higgs boson are derived, as a function of its mass $m$($H$ ±± ), at 95% confidence level. Assuming that the branching ratios to each of the possible leptonic final states are equal, $\mathcal{B}$($H$ ±± → $e$ ± $e$ ± ) = $\mathcal{B}$($H$ ±± → $e$ ± $μ$ ± ) = $\mathcal{B}$($H$ ±± → $μ$ ± $μ$ ± ) = $\mathcal{B}$($H$ ±± → $e$ ± $τ$ ± ) = $\mathcal{B}$($H$ ±± → $μ$ ± $τ$ ± ) = $\mathcal{B}$($H$ ±± → $τ$ ± $τ$ ± ) = 1/6, the observed (expected) lower limit on the mass of a doubly charged Higgs boson is 1080 GeV (1065 GeV) within the left right symmetric type-II seesaw model, which is the strongest limit to date produced by the ATLAS Collaboration. Additionally, this paper provides the first direct test of the Zee– Babu neutrino mass model at the LHC, yielding an observed (expected) lower limit of $m$($H$ ±± ) = 900 GeV (880 GeV).

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2022

BayFlux v1.0

This is an open source software library for performing Bayesian genome scale 13C Metabolic Flux Analysis (Bayesian 13C MFA). This is a new type of metabolic modeling that quantifies flux in a probabilistic manner at the genome scale.

Garcia Martin, Hector↗

DOE OSTI2025

In vitro toxicity assessment of uranium particulates on different human lung epithelial cell models

Inhalation of uranium aerosols produced via human activities such as mining can pose a threat to human respiratory systems. Uranium oxide particulates emit short-range alpha particles that elicit DNA and direct damage, beyond associated physiochemical heavy-metal toxicity, to internal epithelial tissues. The availability of reliable in vitro models to study radiation exposure can greatly enhance our ability to understand and combat the biological impacts of exposure. However, the toxicological effects of alpha emissions and/or the oxidation states of uranium particulates vary across different human lung epithelial cell models and have not been systematically compared. We have endeavored to address this limitation by comparing impacts in three different human lung cell models: primary human bronchial and tracheal epithelial cells, primary human small airway epithelial cells, and human adenocarcinoma alveolar basal epithelial cells. Other studies have mainly investigated the toxicity of depleted uranium. Here, we compared the exposure of uranium oxide particulates (U 3 O 8 and UO 3 ) of different enrichment states on the chosen cell systems. Each cell model was exposed to 0.1, 1, 10, 50, 100, and 500 µg/mL of depleted U 3 O 8 , highly-enriched U 3 O 8 , and natural UO 3 particulates for 24 hours in submerged monolayer cultures. We compared viability and superoxide dismutase activity results across cell lines and uranium enrichment/ oxidative states. The results showed that 1) the oxide state of the particulates affected cell viability, implying that uranium’s different oxidation states contribute to different toxicological responses, and 2) each cell model reacts differently when exposed to uranium oxides, which may provide insights into the mechanistic processes associated with the exposure of radiological particulates on different biological systems. For instance, increased uranium enrichment corresponds to increased toxicity for the primary cells, but not for the immortalized cells. Our study shows that a holistic approach that incorporates similarities between model systems and types of radionuclides is required to truly develop empirical solutions for radiation exposure.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Review of Landscaping Equipment Vibration Risk Exposure, LLNL Site 200 (Various Locations), Whole Body Vibration Seated and Standing Mowers

WBV (Whole-Body Vibration) for operators of seated and standing lawn mowers was conducted during landscape activities from April 2019 through August 2019 at various locations around LLNL Site 200. Mowing is generally performed by each landscaper for 2-3 days every other week with a maximum duration of 3-5 hours each day. On mowing days, other tasks are performed for the remainder of the day that do not expose the worker to WBV such as irrigation, blowing, or sweeping. The mowing terrain at LLNL is variable with typical reported conditions such as gopher holes, exposed tree roots, quick turns, normal and high growth, weeds, and mushy/wet ground that can result in jolts to the mower operator. The Larson Davis HVM200 seat pad with tri-axial accelerometer was used for monitoring workers. For the seated mowers, the HVM200 seat pad with tri-axial accelerometer was placed on the seat between the user and seat pan of the mower. For standing mowers, the seat pad with tri-axial accelerometer was wrapped with Dycem (for seat pad protection) and placed directly on top of the mower deck and underneath the end-user’s right foot. Monitoring for WBV was conducted while operators used different types, makes, and models of mowers. A total of sixteen samples were collected from the operators of seated mower and 6 samples were collected from operators of standing mower. This initial data sampling was part of a discovery phase to identify if WBV exposure met the 2016 ACGIH TLVs (Threshold Limit Values). This initial data identified that workers operating the mowers do not exceed either the TLV or Action Level (AL) for Weighted Acceleration Levels (A(8)) but typically exceed the Vibration Dose Value (VDV) lower boundary for the standing mowers.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Parameterized Neural Ordinary Differential Equations: Applications to Computational Physics Problems

This work proposes an extension of neural ordinary differential equations (NODEs) by introducing an additional set of ODE input parameters to NODEs. This extension allows NODEs to learn multiple dynamics specified by the input parameter instances. Our extension is inspired by the concept of parameterized ordinary differential equations, which are widely investigated in computational science and engineering contexts, where characteristics of the governing equations vary over the input parameters. We apply the proposed parameterized NODEs (PNODEs) for learning latent dynamics of complex dynamical processes that arise in computational physics, which is an essential component for enabling rapid numerical simulations for time-critical physics applications. For this, we propose an encoder-decoder-type framework, which models latent dynamics as PNODEs. We demonstrate the effectiveness of PNODEs with important benchmark problems from computational physics.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2021

Assessment of ORIGEN Reactor Library Development for Pebble-Bed Reactors Based on the PBMR-400 Benchmark

This report provides an evaluation of present SCALE capabilities for modeling depletion of pebble-bed reactor systems, using the PBMR-400 benchmark as a test case. A specific aim of this work is to understand the system characteristics required to generate production-quality reactor data libraries for rapid depletion calculations with ORIGEN. This report includes a discussion of present SCALE capabilities for modeling doubly heterogeneous fuels, prior SCALE work modeling pebble bed–type reactors, and a detailed neutronic analysis of the PBMR-400 core for both fresh and equilibrium-composition core conditions.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2021

Indoor Occupant Counting by RF Backscattering

Building HVAC (heating, ventilation and air conditioning) consumes approximately 13% of all energy consumption in USA. Motion detectors, cameras and user programmable thermostats have been shown to be ineffective for HVAC controls to save energy, mostly due to the user concerns of comfort, reliability and privacy. A new HVAC control system based on real-time occupant counting that is fully automated, highly accurate, economically sensible and preserving privacy and aesthetics can thus bring forth a disruptive impact to this large energy sector. Our indoor occupant monitoring technology is based on the radio-frequency identification system (RFID), deployed in the room, not on the occupants. One reader with four antennas can be deployed on the ceiling or behind the ceiling panels for every thousand square feet in home, office and assisted living, with or without room partitions. The sticker-like passive tag, 10 cents each and maintenance-free, are profusely hidden on the wall or inside the furniture at arbitrary position, preserving privacy and aesthetics. The large number of tags can realize diverse observation points to accommodate arbitrary room layouts, which is impractical by other active units of camera, infrared, radar or lidar. With 20 tags, the system can reliably detect the number of occupants. For 100 tags, occupant posture and location can be known. The technology has been verified in the research labs and test buildings with very high accuracy. When the real-time occupant number can be accurately known without assuming devices on occupants or occupant motion, the building HVAC system can be automated to achieve building energy saving without sacrificing occupant comfort. According to our limited testing in a few types of building models and the simplified cost calculation, the RFID system has low overall cost in production, deployment, operation and maintenance. The signal processing algorithm based on machine learning requires very small number of training cases as most learning is transferrable for various layouts, and very low computational needs during operation, according to our testing in four different room sizes and layouts. In our preliminary estimate from HVAC saving alone, the RFID system can potentially pay for itself within 1.5 years, in addition to the other enhancement in building automation systems (BAS). Our commercialization strategy and business pitch deck focus on venturing this Cornell occupant monitoring technology into BAS and energy management markets. We have identified three broad BAS market segments of senior living, residential buildings, and office buildings. We have put together the minimum viable product characteristics for these identified segments, including analyses on total cost and competing technologies, as well as the fit and technical gaps for these market segments. We intend to bring the technology to market by licensing or partnering with existing BAS vendors. A list of potential collaborators and licensing partner candidates was assembled for different aspects of integrating our technology into a potential product that can be used with BAS.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2024

Real-Time Testbed for Transmission Line Protection

Hardware in the loop (HIL) testing is crucial for designing and managing electric power grids. These grids are becoming larger and more complex. The importance for students to have safe and intuitive ways to interact with the devices associated with the power grids has never been more crucial. Since most of these tests involve high voltages, this can be a deterrent for instructors and students in undergraduate programs. HIL testing is a solution to these common issues. This method has become one of the most popular methods for testing these power systems. With the use of Western Michigan University’s (WMU) Real-Time Digital Simulator (RTDS) and SEL-421-7 protection relay, a HIL testbed has been created. These devices were interconnected using the communication protocol known as Generic Object-Oriented Substation Event (GOOSE). A simulated transmission line system was modeled in an RTDS software RSCAD as the basis for this testbed. This model simulated different types of faults that could occur in a transmission line while in operation. The SEL-421-7 relay is connected to the RSCAD simulation via GOOSE to protect our simulated transmission line. This testbed was set up to give students a clear understanding of how distance protection works as well as how the SEL-421-7 will react to various kinds of faults, in addition to how useful the RTDS can be when testing different power systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2026

Field Emission Analysis in SRF Cavities for PIP-II Using GEANT4

Field emission (FE) remains a key limitation to achieving optimal performance and reliability in superconducting radiofrequency (SRF) cavities used in accelerator cryomodules. Addressing this challenge requires a detailed understanding of the generation and transport of FE-induced radiation; however, the absence of standardized measurement protocols complicates comparisons across different testing stages and facilities. This work presents initial steps toward a quantitative, systematic framework for analyzing FE-induced radiation using Geant4 simulations. We model four cavity types to be deployed in Fermilab’s Proton Improvement Plan-II (PIP-II) linac - HB650, LB650, SSR2, and SSR1 - to investigate radiation signatures and their dependence on emission conditions. By integrating simulation results with radiation diagnostics, our goal is to identify probable emission sites, enhance diagnostic accuracy, and optimize detector placement. Ultimately, this approach seeks to inform cavity preparation, assembly, and testing procedures, enabling the delivery of FE-free SRF cryomodules for PIP-II.

Wijethunga, Sajini [Fermilab] (ORCID:0000000287659↗

DOE OSTI2026

Field Emission Analysis in SRF Cavities for PIP-II Using GEANT4

Wijethunga, Sajini [Fermilab] (ORCID:0000000287659↗

DOE OSTI2024

Supercharged cellulases show superior thermal stability and enhanced activity towards pretreated biomass and cellulose

Non-productive binding of cellulolytic enzymes to various plant cell wall components, such as lignin and cellulose, necessitates high enzyme loadings to achieve efficient conversion of pretreated lignocellulosic biomass to fermentable sugars. Protein supercharging was previously employed as one of the strategies to reduce non-productive binding to biomass. However, various questions remain unanswered regarding the hydrolysis kinetics of supercharged enzymes towards pretreated biomass substrates and the role played by enzyme interactions with individual cell wall polymers such as cellulose and xylan. In this study, CBM2a (from Thermobifida fusca ) fused with endocellulase Cel5A (from T. fusca ) was used as the model wild-type enzyme and CBM2a was supercharged using Rosetta, to obtain eight variants with net charges spanning -14 to +6. These enzymes were recombinantly expressed in E. coli , purified from cell lysates, and their hydrolytic activities were tested against pretreated biomass substrates (AFEX and EA treated corn stover). Although the wild-type enzyme showed greater activity compared to both negatively and positively supercharged enzymes towards pretreated biomass, thermal denaturation assays identified two negatively supercharged constructs that perform better than the wild-type enzyme (~3 to 4-fold difference in activity) upon thermal deactivation at higher temperatures. To better understand the causal factor of reduced supercharged enzyme activity towards AFEX corn stover, we performed hydrolysis assays on cellulose-I/xylan/pNPC, lignin inhibition assays, and thermal stability assays. Altogether, these assays showed that the negatively supercharged mutants were highly impacted by reduced activity towards xylan whereas the positively supercharged mutants showed dramatically reduced activity towards cellulose and xylan. It was identified that a combination of impaired cellulose binding and lower thermal stability was the cause of reduced hydrolytic activity of positively supercharged enzyme sub-group. Overall, this study demonstrated a systematic approach to investigate the behavior of supercharged enzymes and identified supercharged enzyme constructs that show superior activity at elevated temperatures. Future work will address the impact of parameters such as pH, salt concentration, and assay temperature on the hydrolytic activity and thermal stability of supercharged enzymes.

09 BIOMASS FUELS↗

DOE OSTI2020

A Review of the Serrated-Flow Phenomenon and Its Role in the Deformation Behavior of High-Entropy Alloys

High-entropy alloys (HEAs) are a novel class of alloys that have many desirable properties. The serrated flow that occurs in high-entropy alloys during mechanical deformation is an important phenomenon since it can lead to significant changes in the microstructure of the alloy. In this article, we review the recent findings on the serration behavior in a variety of high-entropy alloys. Relationships among the serrated flow behavior, composition, microstructure, and testing condition are explored. Importantly, the mechanical-testing type (compression/tension), testing temperature, applied strain rate, and serration type for certain high-entropy alloys are summarized. The literature reveals that the serrated flow can be affected by experimental conditions such as the strain rate and test temperature. Furthermore, this type of phenomenon has been successfully modeled and analyzed, using several different types of analytical methods, including the mean-field theory formalism and the complexity-analysis technique. Importantly, the results of the analyses show that the serrated flow in HEAs consists of complex dynamical behavior. It is anticipated that this review will provide some useful and clarifying information regarding the serrated-flow mechanisms in this material system. Finally, suggestions for future research directions in this field are proposed, such as the effects of irradiation, additives (such as C and Al), the presence of nanoparticles, and twinning on the serrated flow behavior in HEAs.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Bead–Spring Simulation of Ionomer Melts—Studying the Effects of Chain-Length and Associating Group Fraction on Equilibrium Structure and Extensional Flow Behavior

Ionomers are associative polymers with diverse applications ranging from selective membranes and high-performance adhesives to abrasion- and chemical-resistant coatings, insulation layers, vacuum packaging, and foamed sheets. Within equilibrium melt, the ionic or associating groups are known to form thermally reversible, associative clusters whose presence can significantly affect the system’s mechanical, viscoelastic, and transport properties. It is, thus, of great interest to understand how to control such clusters’ size distribution, shape, and stability through the designed choice of polymer architecture and the ionic groups’ fraction, arrangement, and interaction strength. In this work, we represent linear associating polymers using a Kremer–Grest type bead–spring model and perform large-scale MD simulations to explore the effect of polymer chain-length (l) and fraction (f s ) of randomly placed associating groups on the size distribution and stability of formed clusters. We consider different chain-lengths (below and above entanglement), varying fractions of associating groups (represented by ‘sticky’ beads) between 5 and 20%, and a fixed sticky–sticky nonbond interaction strength of four times that between regular non-associating beads. For all melts containing associating groups the equilibrium structure factor S(q) displays a signature ionomer peak at low wave vector q whose intensity increases with increasing f s and l. The average cluster size Nc increases with f s . However, the effect of chain-length on Nc appears to be pronounced only at higher values of f s . Under extensional flows, the computed stress (and viscosity) is higher at higher f s and l regardless of strain rate. Beyond a critical strain rate, we observe fragmentation of the associative clusters, which has interesting effects on the stress/viscous response.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Smartphone-Based Device for Colorimetric Detection of MicroRNA Biomarkers Using Nanoparticle-Based Assay

The detection of microRNAs (miRNAs) is emerging as a clinically important tool for the non-invasive detection of a wide variety of diseases ranging from cancers and cardiovascular illnesses to infectious diseases. Over the years, miRNA detection schemes have become accessible to clinicians, but they still require sophisticated and bulky laboratory equipment and trained personnel to operate. The exceptional computing ability and ease of use of modern smartphones coupled with fieldable optical detection technologies can provide a useful and portable alternative to these laboratory systems. Herein, we present the development of a smartphone-based device called Krometriks, which is capable of simple and rapid colorimetric detection of microRNA (miRNAs) using a nanoparticle-based assay. The device consists of a smartphone, a 3D printed accessory, and a custom-built dedicated mobile app. We illustrate the utility of Krometriks for the detection of an important miRNA disease biomarker, miR-21, using a nanoplasmonics-based assay developed by our group. We show that Krometriks can detect miRNA down to nanomolar concentrations with detection results comparable to a laboratory-based benchtop spectrophotometer. With slight changes to the accessory design, Krometriks can be made compatible with different types of smartphone models and specifications. Thus, the Krometriks device offers a practical colorimetric platform that has the potential to provide accessible and affordable miRNA diagnostics for point-of-care and field applications in low-resource settings.

Krishnan, Tushar (ORCID:0000000342610336)↗

DOE OSTI2023

Vehicle Localization in 3D World Coordinates Using Single Camera at Traffic Intersection

Optimizing traffic control systems at traffic intersections can reduce the network-wide fuel consumption, as well as emissions of conventional fuel-powered vehicles. While traffic signals have been controlled based on predetermined schedules, various adaptive signal control systems have recently been developed using advanced sensors such as cameras, radars, and LiDARs. Among these sensors, cameras can provide a cost-effective way to determine the number, location, type, and speed of the vehicles for better-informed decision-making at traffic intersections. In this research, a new approach for accurately determining vehicle locations near traffic intersections using a single camera is presented. For that purpose, a well-known object detection algorithm called YOLO is used to determine vehicle locations in video images captured by a traffic camera. YOLO draws a bounding box around each detected vehicle, and the vehicle location in the image coordinates is converted to the world coordinates using camera calibration data. During this process, a significant error between the center of a vehicle’s bounding box and the real center of the vehicle in the world coordinates is generated due to the angled view of the vehicles by a camera installed on a traffic light pole. As a means of mitigating this vehicle localization error, two different types of regression models are trained and applied to the centers of the bounding boxes of the camera-detected vehicles. The accuracy of the proposed approach is validated using both static camera images and live-streamed traffic video. Based on the improved vehicle localization, it is expected that more accurate traffic signal control can be made to improve the overall network-wide energy efficiency and traffic flow at traffic intersections.

47 OTHER INSTRUMENTATION↗

DOE OSTI2023

Understanding AMOC stability: the North Atlantic Hosing Model Intercomparison Project

Abstract. The Atlantic meridional overturning circulation (AMOC) is an important part of our climate system. The AMOC is predicted to weaken under climate change; however, theories suggest that it may have a tipping point beyond which recovery is difficult, hence showing quasi-irreversibility (hysteresis). Although hysteresis has been seen in simple models, it has been difficult to demonstrate in comprehensive global climate models. Here, we outline a set of experiments designed to explore AMOC hysteresis and sensitivity to additional freshwater input as part of the North Atlantic Hosing Model Intercomparison Project (NAHosMIP). These experiments include adding additional freshwater (hosing) for a fixed length of time to examine the rate and mechanisms of AMOC weakening and whether the AMOC subsequently recovers once hosing stops. Initial results are shown from eight climate models participating in the Sixth Coupled Model Intercomparison Project (CMIP6). The AMOC weakens in all models as a result of the freshening, but once the freshening ceases, the AMOC recovers in half of the models, and in the other half it stays in a weakened state. The difference in model behaviour cannot be explained by the ocean model resolution or type nor by details of subgrid-scale parameterisations. Likewise, it cannot be explained by previously proposed properties of the mean climate state such as the strength of the salinity advection feedback. Instead, the AMOC recovery is determined by the climate state reached when hosing stops, with those experiments where the AMOC is weakest not experiencing a recovery.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Multi-Level Impacts of Extreme Climate-Related Events on Food Supply Chain: Idaho Potato's Case Study

Background: The world is experiencing frequent extreme weather events like droughts, floods, snowstorms, and shifting of seasons due to climate change. Increasing frequencies and severity of these extreme weather events threaten food security because agriculture is extremely vulnerable to climate change. Higher temperature reduces overall yields of the desirable crops but proliferates weeds and harmful pests. Current data shows that every year U.S. farmers spend more than 11 billion USD to fight weeds and this number is expected to rise in the coming years due to climate change. Due to droughts, the water required for irrigation is becoming scarcer. Since many areas are becoming climatically unusable for crop production, the amount of farmland area is shrinking rapidly. In addition, changes in precipitation patterns are causing crop failures and negatively impacting expected yields. In this study, we investigated how different extreme climate events impact different stages of a food supply chain. Approach: As a case study, we chose Idaho’s potato supply chain (SC). Idaho is the top potato producing state in the U.S. and contributes around 30% of the nation’s potato production. Using the agent-based modeling (ABM) approach, we developed a multi-echelon potato supply chain computer simulation model with six types of agents – seed producers, farmers, shippers, processors, retailers, and logistics companies. In addition to the baseline scenario, we developed two additional climate-related disruption events – drought and snowstorm. We investigated how each of these disruption events impacts different stakeholders across the supply chain in terms of revenue and some other key performance metrics such as lead time, food waste, number of delayed orders, and order fulfillment rate. Results: Extreme climate events not only impact the growers but there is also cascading ripple effects downstream of the supply chain. The methodology developed in this study could be applied to other food and agricultural SC to understand the vulnerabilities of the different links. The findings would potentially help to adopt new policies for the well-being of the overall SC.

54 ENVIRONMENTAL SCIENCES↗