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This is a short re-work of the previously accomplished simulations, using PARMELA code package. This exercise was done primarily for increase of fidelity and re-formulating the given task for a different beam dynamics (BD) code. The performed simulations showed very good agreement with the abovementioned simulations and confirm the previously produced results with the BEAMPATH code.
Transient kinetic data contain a wealth of information about intrinsic features of a catalyst as well as the reaction mechanism. Currently, high volume transient data is underutilized, and data science methods could both increase the value of information that can be extracted from this data, integrate experimental with theoretical data sources, and accelerate the pace of catalyst technology advancement. Transient kinetic characterizations with simple probe molecules exhibiting reversible adsorption, irreversible adsorption and bulk-surface diffusion are presented as training components for similar experiments with more complex surface reactions. In conclusion, by increasing the availability and accessibility of transient kinetic data through details of its structure and acquisition, we aim to decrease the barrier for data scientists to apply machine learning methods to this valuable data source.
Polymer-based electrochromic devices (ECDs) are a promising technology for enabling low-voltage, disposable displays, yet are currently limited by photo-oxidative bleaching of the active materials. Here, renewable barrier films composed of cellulose and chitin are presented as an alternative to poly(ethylene terephthalate) (PET) for encapsulating ECDs. To assess barrier film effectiveness, lateral ECDs composed of poly(3,4-propylenedioxythiophene-(CH 2 OEtHx) 2 ) (P(ProDOT)) active layers were constructed and encapsulated with a multilayer barrier consisting of chitin nanofibers and cellulose nanocrystals spray cast onto a cellulose acetate substrate (oxygen transmission rate (OTR) = 29 cm 3 m –2 day –1 ), a commercially available PET film (OTR = 8.5 cm 3 m –2 day –1 ), and a high-performance PET-Al 2 O 3 multilayer barrier film (OTR < 1 cm 3 m –2 day –1 ). The photodegradation of the P(ProDOT) active layer was determined by measuring the evolution of the colorimetric contrast (ΔE*) and switching speeds as a function of light exposure (100 mW cm –2 , AM 1.5 G light). Photodegradation was found to proceed at a similar rate for all encapsulated devices (roughly 10 times more slowly than unencapsulated devices), highlighting the opportunity for replacing petroleum packaging with bioderived barrier films. Analysis of the switching kinetics, the shifts in optical absorbance, and evidence of chemical degradation indicate that both photochemical breakdown of the electrolyte and cross-linking of the P(ProDOT) active material are key drivers for loss of device performance when oxygen flux to the active material is limited. Furthermore, pathways toward better understanding photodegradation are then proposed with sustainability in mind for future ECD design.
The Disposal Research and Development (R&D) Program of the US Department of Energy (DOE) office of Nuclear Energy (NE-8) Spent Fuel and Waste Science and Technology (SFWST) Campaign is to conduct R&D on disposal of spent nuclear fuel (SNF) and high-level waste (HLW). The goal of the Geologic Disposal Safety Assessment (GDSA) within this project is to develop a disposal system modeling and analysis capability that supports the integrated modeling of coupled processes controlling disposal system performance of deep geologic repositories, including uncertainty. This report describes specific activities in the Fiscal Year (FY) 2024 associated with the GDSA Repository Systems Analysis (RSA) work package. The overall objective of the GDSA RSA work package is to develop generic deep geologic repository concepts and repository system performance models in crystalline, argillite, salt, and unsaturated alluvium potential host-rock environments, and to simulate and analyze these generic repository concepts and models using GDSA Framework toolkit, and other tools as needed.
Existing quantum network testbeds and prototypes are typically implemented in laboratory experiments with limited functionality and operate in a tightly coupled manner. These characteristics make it difficult to evaluate the behavior of emerging quantum platforms and protocols beyond local resource limitations. The QNPack software enables full-stack modeling of quantum repeater networks that allows researchers to simulate new approaches, and understand emergent behaviors, from local to national scales. Novel capabilities include: (1) performant and accurate quantum models that can be executed as independent simulations, which will allow users to characterize specific analog quantum processes, quantum devices, and protocols, (2) a modular and extensible approach to the simulation architecture to accommodate new quantum technologies, protocols, and topologies as they are developed across the quantum repeater generations under evaluation, and (3) a focus on managing the interactions between the simulation framework sub-components so that they may be re-used and composed in flexible ways.
The purpose of the Total ELectricity Load (tell) model is to generate 21st century profiles of hourly electricity load (demand) across the Conterminous United States (CONUS). tell loads reflect the impact of climate and socioeconomic change at a spatial and temporal resolution adequate for input to an electricity grid operations model. tell uses machine learning to develop profiles that are driven by projections of climate/meteorology and population. tell also harmonizes its results with United States (U.S.) state-level, annual projections from a national- to global-scale energy-economy model. This model accounts for a wide range of other factors affecting electricity demand, including technology change in the building sector, energy prices, and demand elasticities, which stems from model coupling with the U.S. version of the Global Change Analysis Model (GCAM-USA). tell was developed as part of the Integrated Multisector Multiscale Modeling (IM3) project. IM3 explores the vulnerability and resilience of interacting energy, water, land, and urban systems in response to compound stressors, such as climate trends, extreme events, population, urbanization, energy system transitions, and technology change
The Disposal Research and Development (R&D) Program of the US Department of Energy (DOE) office of Nuclear Energy (NE-8) Spent Fuel and Waste Science and Technology (SFWST) Campaign is to conduct R&D on disposal of spent nuclear fuel (SNF) and high-level waste (HLW). The goal of the Geologic Disposal Safety Assessment (GDSA) within this project is to develop a disposal system modeling and analysis capability that supports the integrated modeling of coupled processes controlling disposal system performance of deep geologic repositories, including uncertainty. This report describes a specific activity in the Fiscal Year 2024 (FY24) associated with the GDSA Repository Systems Analysis (RSA) work package in collaboration with the GDSA Geologic Modeling work package at Los Alamos National Laboratory (LANL). The overall objective of the GDSA RSA work package is to develop generic deep geologic repository concepts and repository system performance models in crystalline, argillite, salt, and unsaturated alluvium potential host-rock environments, and to simulate and analyze these generic repository concepts and models using GDSA Framework toolkit, and other tools as needed.
Quantum computing has been identified as a “wild card” by the International Energy Agency in predicting future global data center energy usage. This is primarily because both uncertainty in the extent to which quantum computing will be adopted, and uncertainty in the power consumption of individual quantum data centers. Unlike the classical counterparts, quantum computers need to be maintained at near absolute zero, requiring energy-intensive cryogenic cooling systems. Therefore, as quantum computers scale up from existing 50 qubit technology demonstrations to the 10,000 to 100,000 qubit systems that will be able to solve complex problems, the energy consumption of both the electronics and the required cooling systems will also increase. To predict this scaling, this work analyzes the energy requirements for both computation and cooling of quantum hardware. We show that the energy requirements for cooling of quantum computers is determined by several computing system parameters, including the number and type of physical qubits, the operating temperature, the packaging efficiency of the system, and the split between circuits operating at cryogenic temperatures and those operating at room temperature. The energy requirements can then be found based on thermal system parameters such as cooling efficiency and cryostat heat transfer. Analysis of these parameters shows that the energy required for cooling is significantly larger than that required for computation, a reversal from energy usage patterns seen in conventional computing. The results and discussions provide a road-map for creating energy efficient quantum computers through the selection of computer architectures and cryogenic system configurations that minimize cooling requirements.
Photomultiplier tubes (PMTs) have been used for decades as the default light detection technology for scintillator-based radiation monitors. PMTs come with a handful of disadvantages, however, including large volume usage, fragility, high-voltage requirements, and susceptibility to magnetic fields. Arrays of silicon photomultipliers (SiPMs) are a possible alternative to PMTs providing similar performance while offering improvements in the areas listed. We focus on straightforward “drop-in replacement” evaluations by imposing a single channel output of the SiPM signal and a backend electronics data acquisition and analysis routine identical to that used for PMTs. In the realm of nuclear safeguards, the primary performance metric for gamma spectroscopy is detector resolution, and for neutron detection it is pulse shape discrimination (PSD) to separate neutron and gamma signals. In this work we present the results of replacing a PMT with a 2” x 2” SiPM array mounted, in turn, to the same 2” x 2” cylindrical sodium iodide (NaI) crystal. The ultimate comparison for this gamma spectrometry is confirmation of uranium enrichment standards, ranging from depleted uranium to 93% highly enriched uranium (HEU), by analyzing the resulting spectra with both a simple integral scaling in key energy regions of the spectrum, as well as with the NaIGEM software package. In addition to the gamma spectroscopy work, we will present the latest results on comparing the PSD capabilities of a 4” x 4” SiPM array to a 5” PMT. As with the gamma spectroscopy evaluations, the light detectors are mounted in turn to the same liter-scale organic scintillators. This neutron-focused work includes evaluation of prototype SiPM readout boards with a single output signal summed over 256 individual SiPM pixels, and evident tradeoffs between PSD capability and fast response.
Many actions are underway at global, national, and local levels to address the plastic waste problem and transition toward a circular economy of plastics. Studies evaluating environmental and socioeconomic impacts of such a transition are lacking. Here, the purpose of this study is to conduct a national systems analysis of polyethylene terephthalate (PET) packaging supply chains in the United States. Material flow data was combined with environmental and socioeconomic indicators to evaluate and compare the sustainability of the linear PET packaging supply chain, current (2019) supply chain, and possible future circular supply chain options in the United States. Environmentally optimal circular US PET packaging material flows showed 31% and 38% savings of GHG emissions and energy demand, respectively, with a circularity of 77% when compared with a linear supply chain. Additionally, the environmentally optimal system showed higher employment (29%) and wages (31%) than a linear system, but with a 5% decrease in revenue generation. A socioeconomically optimal circular PET supply chain showed increased employment (by 52%), wages (by 67%), and revenues (by 1%), with a circularity of 59% when compared with the linear system. However, it showed 14% higher GHG emissions than a linear system, indicating a trade-off between environmentally and socioeconomically optimal circular PET packaging systems. Overall, linear-to-circular material flow transition may not necessarily lead to increased revenues and decreased environmental impacts of the entire system, but it does benefit society due to increased employment and wages. Future systems analysis work should focus on improving data quality for environmental and socioeconomic dimensions.
A well-posed physics-based compact model for a three-terminal silicon–oxide–nitride–oxide–silicon (SONOS) synaptic circuit element is presented for use by neuromorphic circuit/system engineers. Based on technology computer aided design (TCAD) simulations of a SONOS device, the model contains a nonvolatile memristor with the state variable QM representing the memristor charge under the gate of the three-terminal element. By incorporating the exponential dependence of the memristance on QM and the applied bias V for the gate, the compact model agrees quantitatively with the results from TCAD simulations as well as experimental measurements for the drain current. The compact model is implemented through VerilogA in the circuit simulation package Cadence Spectre and reproduces the experimental training behavior for the source–drain conductance of a SONOS device after applying writing pulses ranging from –12 V to +11 V, with an accuracy higher than 90%.
Fundamental research and development of ultra-wide bandgap (UWBG) semiconductor devices are under way to realize next-generation power conversion and wireless communication systems. Devices based on aluminum gallium nitride (AlxGa1-xN, x is the Al composition), ..beta..-phase gallium oxide (..beta..-Ga2O3), and diamond give promise to the development of power switching devices and radio frequency power amplifiers with higher performance and efficiency than commercial wide bandgap semiconductor devices based on gallium nitride (GaN) and silicon carbide (SiC). However, one of the most critical challenges for the successful deployment of UWBG device technologies is to overcome adverse thermal effects that impact the device performance and reliability. Overheating of UWBG devices originates from the projected high power density operation and poor intrinsic thermal properties of AlxGa1-xN and ..beta..-Ga2O3. This Perspective delineates the need and process for the "electro-thermal co-design" of laterally configured UWBG electronic devices and provides a comprehensive review of current state-of-the-art thermal characterization methods, device thermal modeling practices, and both device- and package-level thermal management solutions.
Photomultiplier tubes (PMTs) have been used for decades as the default light detection technology for scintillator-based radiation monitors. PMTs come with a handful of disadvantages, however, including large volume usage, fragility, high-voltage requirements, and susceptibility to magnetic fields. Arrays of silicon photomultipliers (SiPMs) are a possible alternative to PMTs providing similar performance while offering improvements in the areas listed. We focus on straightforward “drop-in replacement” evaluations by imposing a single channel output of the SiPM signal and a backend electronics data acquisition and analysis routine identical to that used for PMTs. In the realm of nuclear safeguards, the primary performance metric for gamma spectroscopy is detector resolution, and for neutron detection it is pulse shape discrimination (PSD) to separate neutron and gamma signals. In this work we present the results of replacing a PMT with a 2” x 2” SiPM array mounted, in turn, to the same 2” x 2” cylindrical sodium iodide (NaI) crystal. The ultimate comparison for this gamma spectrometry is confirmation of uranium enrichment standards, ranging from depleted uranium to 93% highly enriched uranium (HEU), by analyzing the resulting spectra with both a simple integral scaling in key energy regions of the spectrum, as well as with the NaIGEM software package. In addition to the gamma spectroscopy work, we will present the latest results on comparing the PSD capabilities of a 4” x 4” SiPM array to a 5” PMT. As with the gamma spectroscopy evaluations, the light detectors are mounted in turn to the same liter-scale organic scintillators. This neutron-focused work includes evaluation of prototype SiPM readout boards with a single output signal summed over 256 individual SiPM pixels, and evident tradeoffs between PSD capability and fast response.
This final technical report summarizes the work of the Michigan State University (MSU) team supported by grant # DE-SC0021423 awarded by the Office of Nuclear Physics, Department of Energy. Objectives: The successful fulfillment of the FRIB science mission hinges on ensuring the availability of fast, stopped, and reaccelerated beams consisting of rare isotopes. This project's research and development focus was dedicated to supporting the advancement and creation of a cutting-edge linear gas stopper. The primary aim is to efficiently convert the high-intensity fast beams of rare isotopes provided by FRIB into high-quality, low-energy beams. These beams are essential for conducting stopped beam experiments or for subsequent reacceleration. The overarching goal is to advance technology, aiming to increase the beam rate capability of the linear gas stopper for medium-to-heavy-mass rare isotopes by more than tenfold compared to the currently most effective gas stopper in operation, and to improve the purity of the delivered beams. Project Description: The existing technology employed in gas stopping devices designed for low-energy, rare-isotope beams presents limitations in both the purity of extracted beams and the intensities of injected beams. These limitations are incompatible with the requirements of the recently commissioned rare isotope beam facility, FRIB. Our research and development efforts, aligned with the previously outlined objectives, focused on addressing the most critical aspects for enhancing beam-rate capability and purity. Specifically, advanced particle-in-cell simulations were developed and integrated into a simulation pipeline to explore the efficacy of multi-layer RF carpets on increasing ion transport efficiency with high incoming beam rates that generate space charge fields which can limit it. We also explored the possibility of using a collision-induced-dissociation (CID) gas cell to break up molecular contaminant ions that are generated during the stopping process. A prototype CID gas cell was constructed and tested with beams from an offline ion source, validating the concept with the successful demonstration of breaking of molecular ions. The outcome of this research enabled the formulation a conceptual design for a next-generation linear gas stopping device specifically tailored for FRIB. This device is envisioned to deliver rare-isotope-ion beams at a rate of 10 8 particles per second or higher, accompanied by advancements in purity. Methods employed: This project leverages advancements in technologies initially designed for the Advanced Cryogenic Gas Stopper (ACGS), the current state-of-the-art linear gas stopper, through the use of new simulations and beam purification via collision-induced-dissociation. The methods include: 1. Development of a prototype low-energy, low-pressure CID gas stopper. This prototype features a thin, approximately 20 nm, Si 3 N 4 entrance window designed for dissociating stable and rare-isotope molecular ions. The goal is to enhance beam purification and overall efficiency. 2. Creation of Particle-in-cell (PIC) simulations to assess the advantages of multi-layer RF carpets and multi-point extraction for ion transport efficiency. These simulations rely on the 3DCylPIC package, specifically designed for studying devices of this nature. The goal is to quantify and mitigate ion transport losses due to space charge generated in the stopping process of large numbers of ions. 3. Perform ion transport simulations across an RF carpet using an 8-phase travelling wave and evaluate its performance. Compared to the 4-phase RF carpets used in ACGS, the 8-phase carpets will double the wavelength of the generated traveling wave allowing for larger maximum RF amplitudes that could result in improved ion transport efficiency for high-intensity incoming beams when large space charge fields are present. Impact: Tackling the primary challenges associated with transforming high-energy projectile fragment beams into low-energy beams—specifically, addressing efficiency and purity—holds significant promise for advancing FRIB science. This advancement will particularly impact precision mass measurements, laser spectroscopy of short-lived nuclei, and studies in astrophysics and nuclear reactions using reaccelerated beams. These domains play a crucial role in addressing key questions outlined in the 2023 NSAC long-range plan, spanning nuclear structure, nuclear astrophysics, and fundamental symmetries. Additionally, they contribute to addressing 10 out of the 17 benchmarks identified by the NRC RISAC. The development of a next-generation gas stopping device capable of delivering low-energy, rare-isotope beams at a rate of 10 8 particles per second, or more, with high purity holds the potential to unlock experiments that would otherwise be unfeasible. Furthermore, it is expected to reduce the time required for experiments at FRIB, thereby maximizing scientific output. The research and development activities performed as part of this project bolstered essential competencies at FRIB in beam physics and ion source technologies, provided valuable training opportunities for junior scientists.
Cooperative Research and Development Agreement (CRADA) NFE-19-07859 between Oak Ridge National Laboratory (ORNL) and Purist Inc. (Purist) focused on developing a technology for production of high purity radioisotopes using small-scale underutilized research nuclear reactors. Purist is developing a novel production mechanism that will produce, and efficiently isolate radioisotopes with high specific activity at small-scale research reactors. The goal of this technology is to enable underutilized smaller scale reactors, typically not capable of producing medical grade radioisotopes, to be utilized as a production supply source. Such radioisotope production facilities will complement production efforts of the few larger production facilities to reduce and prevent risk in the medical isotope supply chain. The work done under this CRADA explored target development, to maximize isotope production and separation using Purist’s technology to ultimately obtain a radioisotope product with high specific activity for use in medical applications. Furthermore, under this CRADA post production, capture, concentration and encapsulation of the radioisotope product was studied by developing post irradiation midi to microscale processes to capture, store and release the separated radioisotopes from large volumes of the capture matrix after production, via automated High-Pressure Ion Chromatography (HPIC) and microfluidic purification/separation systems. This will enable concentration of the radioisotope product obtained into small volumes, which will aid in packaging and transporting the final radioisotope product to users.
Based on deep learning, a Dust Ablation Trail Analysis (DATA) code package is developed to detect dust ablation trails in tokamaks, which is intended to analyze a large amount data of tokamak dusts. To validate and benchmark the DATA code package, 2440 plasma jet images are exploited for the training and test of the deep learning DATA code package, since plasma jets resemble the shape and size of dust ablation clouds in tokamaks. After being trained by 1920 plasma jet images, the DATA code package is able to locate 100% plasma jets, classify plasma jets with the accuracy of >99.9%, and output image skeleton information for classified plasma jets. The DATA code package trained by the plasma jet images is also used to analyze the dust ablation trails captured in the Experimental Advanced Superconducting (EAST) tokamak with the satisfactory performance, further verifying its applicability in the fusion dust ablation investigation. Based on its excellent performance presented here, it is demonstrated that our DATA code package is able to automatically identify and analyze dust ablation trails in tokamaks, which can be used for further detailed investigations, such as the three-dimensional reconstruction of dusts and their ablation trails.
Recent advances in nuclear power generation technologies show great promise for efficient, safe generation of carbon-free power in the near future. Consequently, many new generation reactor designs are being pursued by government and industry groups, including both fission- and fusion-based technologies. Radiation- and temperature-tolerant sensor technology continues to advance, yet development of the electronics/instrumentation technologies suitable for these environments have fallen behind. Industry has adequately addressed harsh environment electronics needs for low earth orbit satellites, but the much more extreme conditions associated with electronics placed near or in a reactor core remain unaddressed. This project investigates the use of gallium nitride (GaN) circuit technology to address the unique needs for sensor interface electronics and communications in reactor environments. This report provides a summary of the first year’s project activities related to developing and optimizing devices and circuits for this GaN high electronic mobility transistor (HEMT) process. Activities reported include multiple analog and digital circuit designs simulated using custom Verilog-A models generated from measured GaN devices fabricated in the target process. Digital circuit designs included fundamental logic circuits such as an inverter, NAND, NOR, AND and OR gates, as well as a 5-stage ring oscillator. Each design was simulated using an open-source SPICE simulator, and an integrated circuit layout was produced of each design for use in future fabrication. Analog circuit designs focused on the fundamental building blocks to be used to construct sensor interface and communications circuits. These included current mirrors, matched differential pairs, and a Gilbert cell mixer design, each with an associated integrated circuit layout. Layout tools used for these designs included two open-source packages—KLayout and Magic—which were customized for specific use with the OSU GaN process layers. Design rules and preliminary device extraction capabilities were built for the Magic tool to enable device extraction and subsequent netlist generation for SPICE simulation. Finally, future research directions for year two are summarized. When the year-two directions are implemented, the project will be in position to advance the state of the art in electronics for near- or in-reactor sensor interfacing and communications.
Abstract Plant neutral lipids, also known as “vegetable oils”, are synthesized within the endoplasmic reticulum (ER) membrane and packaged into subcellular compartments called lipid droplets (LDs) for stable storage in the cytoplasm. The biogenesis, modulation, and degradation of cytoplasmic LDs in plant cells are orchestrated by a variety of proteins localized to the ER, LDs, and peroxisomes. Recent studies of these LD-related proteins have greatly advanced our understanding of LDs not only as steady oil depots in seeds but also as dynamic cell organelles involved in numerous physiological processes in different tissues and developmental stages of plants. In the past 2 decades, technology advances in proteomics, transcriptomics, genome sequencing, cellular imaging and protein structural modeling have markedly expanded the inventory of LD-related proteins, provided unprecedented structural and functional insights into the protein machinery modulating LDs in plant cells, and shed new light on the functions of LDs in nonseed plant tissues as well as in unicellular algae. Here, we review critical advances in revealing new LD proteins in various plant tissues, point out structural and mechanistic insights into key proteins in LD biogenesis and dynamic modulation, and discuss future perspectives on bridging our knowledge gaps in plant LD biology.