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DOE OSTI2023

Key Takeaways: First Cohort of Action Plans for Rapid Power Sector Decarbonization

The purpose of this synthesis report is to extract key takeaways from the first cohort of CEM Action Plans for rapid power sector decarbonization, developed by Australia, Chile, the European Union, India, and the United Kingdom. These Action Plans differ in their approach to power sector decarbonization based on the domestic resources available, governance structure, and regional context, among other factors. However, they also share common themes that were emphasized in the collaborative report released at CEM13. This report is not intended to be inclusive of all components in each Action Plan. Rather, this report highlights how select best practices for planning, building, and operating power systems are being implemented differently in these Action Plans, with equal focus given to each jurisdiction. Ministers and stakeholders from other governments with similar decarbonization goals can consider these examples within their own unique context.

Australia↗

NASA NTRS2022

Natural Language Processing Techniques for Intelligent Knowledge Management of Safety Reports

Safety, failure, and incident reports are common artifacts across various domains, including aviation and wildfire response. These reports are often mandatory to submit, resulting in the culmination of large repositories of text-based documents. Simultaneously, these reports and corresponding repositories are often only manually analyzed and queried by users via out-of-date search engines. As a consequence, we have been developing the Manager for Intelligent Knowledge Access (MIKA) toolkit, which uses natural language processing to improve information access and reuse. In this presentation, we discuss natural language processing techniques for knowledge discovery and apply these methods to a repository of aerial wildfire mishap reports. Two methods are used for knowledge discovery: topic modeling and named-entity recognition. We use topic modeling to identify hazards and perform a trend analysis to produce a data-driven risk matrix. A custom named-entity recognition model, build from fine tuning a pre-trained language model, is used to identify failure modes, failure causes, failure effects, control processes, and recommendations to aid in failure modes and effects analysis (FMEA). Throughout the presentation, we discuss and apply natural language processing techniques to better leverage the vast amount of information contained in report repositories.

Machine learning↗

DOE OSTI2025

Long Baseline Neutrino Facility (LBNF) Corrector Magnets

The Long Baseline Neutrino Facility (LBNF) includes at the Fermi National Accelerator Laboratory (Fermilab) site a Beamline which will aim neutrinos towards massive detectors at the Sanford Underground Research Facility (SURF) at South Dakota. The neutrinos will be created by a beam of 60-120 GeV protons extracted from Fermilab’s Main Injector interacting with a target located in the end of the LBNF proton beamline. The design of the proton beamline involves 79 conventional magnets; 23 are corrector magnets. These correctors are of a new design which evolved from those built for the Fermilab Main Injector. Following the production of a prototype corrector magnet by the Institute of High Energy Physics (IHEP) and its testing by both IHEP and Fermilab, IHEP will procure the materials for the 24 (including one spare) corrector magnets needed by the LBNF proton beamline; then, will build, test and certify them

43 PARTICLE ACCELERATORS↗

NASA NTRS2015

Space Resource Utilization: Near-Term Missions and Long-Term Plans for Human Exploration

NASA's Human Exploration Plans: A primary goal of all major space faring nations is to explore space: from the Earth with telescopes, with robotic probes and space telescopes, and with humans. For the US National Aeronautics and Space Administration (NASA), this pursuit is captured in three important strategic goals: 1. Ascertain the content, origin, and evolution of the solar system and the potential for life elsewhere, 2. Extend and sustain human activities across the solar system (especially the surface of Mars), and 3. Create innovative new space technologies for exploration, science, and economic future. While specific missions and destinations are still being discussed as to what comes first, it is imperative for NASA that it foster the development and implementation of new technologies and approaches that make space exploration affordable and sustainable. Critical to achieving affordable and sustainable human exploration beyond low Earth orbit (LEO) is the development of technologies and systems to identify, extract, and use resources in space instead of bringing everything from Earth. To reduce the development and implementation costs for space resource utilization, often called In Situ Resource Utilization (ISRU), it is imperative to work with terrestrial mining companies to spin-in/spin-off technologies and capabilities, and space mining companies to expand our economy beyond Earth orbit. In the last two years, NASA has focused on developing and implementing a sustainable human space exploration program with the ultimate goal of exploring the surface of Mars with humans. The plan involves developing technology and capability building blocks critical for sustained exploration starting with the Space Launch System (SLS) and Orion crew spacecraft and utilizing the International Space Station as a springboard into the solar system. The evolvable plan develops and expands human exploration in phases starting with missions that are reliant on Earth, to performing ever more challenging and longer duration missions in cis-lunar space and beyond, to eventually being independent from Earth. The goal is no longer just to reach a destination, but to enable people to work, learn, operate, and live safely beyond the Earth for extended periods of time, ultimately in ways that are more sustainable and even indefinite.

Sanders, Gerald B.↗

NASA NTRS2015

Space Resource Utilization: Near-Term Missions and Long-Term Plans for Human Exploration

A primary goal of all major space faring nations is to explore space: from the Earth with telescopes, with robotic probes and space telescopes, and with humans. For the US National Aeronautics and Space Administration (NASA), this pursuit is captured in three important strategic goals: 1. Ascertain the content, origin, and evolution of the solar system and the potential for life elsewhere, 2. Extend and sustain human activities across the solar system (especially the surface of Mars), and 3. Create innovative new space technologies for exploration, science, and economic future. While specific missions and destinations are still being discussed as to what comes first, it is imperative for NASA that it foster the development and implementation of new technologies and approaches that make space exploration affordable and sustainable. Critical to achieving affordable and sustainable human exploration beyond low Earth orbit (LEO) is the development of technologies and systems to identify, extract, and use resources in space instead of bringing everything from Earth. To reduce the development and implementation costs for space resource utilization, often called In Situ Resource Utilization (ISRU), it is imperative to work with terrestrial mining companies to spin-in/spin-off technologies and capabilities, and space mining companies to expand our economy beyond Earth orbit. In the last two years, NASA has focused on developing and implementing a sustainable human space exploration program with the ultimate goal of exploring the surface of Mars with humans. The plan involves developing technology and capability building blocks critical for sustained exploration starting with the Space Launch System (SLS) and Orion crew spacecraft and utilizing the International Space Station as a springboard into the solar system. The evolvable plan develops and expands human exploration in phases starting with missions that are reliant on Earth, to performing ever more challenging and longer duration missions in cis-lunar space and beyond, to eventually being independent from Earth. The goal is no longer just to reach a destination, but to enable people to work, learn, operate, and live safely beyond the Earth for extended periods of time, ultimately in ways that are more sustainable and even indefinite.

Sanders, Gerald B.↗

DOE OSTI2024

Building on success in systems design of high yielding low‐input energycanes for marginal lands

Energycane and Miscanthus are highly sustainable and productive perennial grasses that produce a large annual crop of shoot biomass. Theoretical analysis of metabolism has suggested that these crops could be engineered to accumulate 20% of their harvestable biomass as oil. Given their much higher biomass yields than soybean and canola, this would yield several times more oil per acre. This could be converted to biodiesel or sustainable aviation fuel (SAF) by well‐established technologies. Energycane is well suited to the southeast quarter of the contiguous 48 states and Miscanthus to the northeast quarter. The objective of this award was to provide the foundation for converting these crops to oilcanes from DNA constructs and transformation to field trials and pilot plant development of oil extraction. Genetic engineering focused on development and implementation of improved constructs to increase oil levels, and increased photosynthesis to support the additional energy needed for oil production. The specific progress in each of our subtasks follows together with the products arising.

09 BIOMASS FUELS↗

NASA NTRS2005

Separating the Chemical and Dynamical Contributions to the Ozone Change

Statistical analysis is used to extract the sensitivity of ozone to changes in stratospheric chlorine due to emissions of chlorofluorcarbons from the observed ozone record. The statistical analysis relies on a model that accounts for natural variations in ozone including the seasonal cycle, the solar cycle, variations in aerosols due to volcanic eruption, and the quasi- biennial oscillation, A noise term includes contributions to ozone variability due to inter-annual variability in the stratospheric circulation not due to the quasi-biennial oscillation, The residual circulation varies due to variability in planetary wave forcing, and studies using meteorological analyses show that the build-up of ozone over the winter is correlated with the planetary wave Eliassen-Palm flux. This variability in the residual circulation is not included in the statistical model, and contributes to the apparent ozone sensitivity to chlorine derived from observations for 1979 - 2000. We have investigated these relationships using multi-decadal simulations of our off-line chemistry and transport model (CTM). Our simulations use meteorological fields output from a 50 year simulation of a general circulation model (GCM). A 50 climatology specifies the sea surface temperatures to produce the GCM simulation. The CTM was used with these winds to produce two simulations, one in which the boundary conditions for chlorofluorcarbons and other source gases vary as specified for 1973-2022 by the Scenario A2 of the World Meteorological Organization ozone assessment, and the second with source gases fixed to their 1979 values. The same statistical analysis used to derive trends from observations is applied to the CTM output. When applied to the difference between the two simulations the statistical analysis provides a more precise measure of the ozone sensitivity to chlorine change. We are testing ways of including the interannual variability in the residual circulation in the statistical model so that we can derive the same result from the Scenario A2 simulation as is obtained when the statistical analysis is applied to the difference between the two simulations. This should provide direction as to how to account for the changes in ozone due to interannual variability in the residual circulation in the statistical model that is applied to the observed data record.

Douglass, Anne R.↗

NASA NTRS2004

Building Hybrid Rover Models for NASA: Lessons Learned

Particle filters have recently become popular for diagnosis and monitoring of hybrid systems. In this paper we describe our experiences using particle filters on a real diagnosis problem, the NASA Ames Research Center's K-9 rover. As well as the challenge of modelling the dynamics of the system, there are two major issues in applying a particle filter to such a model. The first is the asynchronous nature of the system-observations from different subsystems arrive at different rates, and occasionally out of order, leading to large amounts of uncertainty in the state of the system. The second issue is data interpretation. The particle filter produces a probability distribution over the state of the system, from which summary statistics that can be used for control or higher-level diagnosis must be extracted. We describe our approaches to both these problems, as well as other modelling issues that arose in this domain.

Willeke, Thomas↗

DOE OSTI2021

Aqueous harvesting of 88 Zr at a radioactive-ion-beam facility for cross-section measurements

Isotope harvesting is a method of collecting the long-lived radioisotopes that build up during the operation of ion-beam facilities in a way that is useful for subsequent research. As a demonstration of this method for the collection of a group IV metal at a fragmentation facility, the high-energy Zr 88 secondary beam produced from a 140-MeV/u Mo 92 primary beam at the National Superconducting Cyclotron Laboratory (NSCL) was stopped in a water target. The setup aimed to mimic the aqueous beam dump that will be implemented at the Facility for Rare Isotope Beams (FRIB). The collected Zr 88 and accompanying Y 88 decay daughter were radiochemically extracted from the solution and made into target samples suitable for neutron-capture cross-section measurements. These samples were then irradiated at two reactor facilities, and the Zr 88 average thermal-neutron-capture cross section ( σ T ) and resonance integral ( I ) were determined to be σ T = ( 8.04 ± 0.63 ) × 10 5 b and I = ( 2.53 ± 0.28 ) × 10 6 b. The σ T value agrees well with previous results and I , determined for the first time here, was found to be the largest measured resonance integral by two orders of magnitude. The Y 88 thermal-neutron-capture cross section was determined to be less than 1.8 × 10 4 b. This work demonstrates the steps needed to make cross-section measurements with samples produced via aqueous isotope harvesting.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

DOE OSTI2023

Understanding structure-processing relationships in metal additive manufacturing via featurization of microstructural images

Understanding and predicting accurate property-structure-processing relationships for additively manufactured components is important for both forward and inverse design of robust, reliable parts and assemblies. While direct mapping of process parameters to properties is sometimes plausible, it is often rendered difficult due to poor microstructural control. Exploring the direct relationship between processing conditions and microstructural features can thus provide significant physical insights and aid the overall design process. Here, in this study, we develop an automated high-throughput framework to simulate an uncertainty-aware additive manufacturing (AM) process, characterize microstructural images, and extract meaningful features/descriptors. A kinetic Monte Carlo (KMC) based model of the AM process is used to simulate microstructural evolution for a diverse set of experimentally relevant processing conditions. We perform a parametric study to explore the relationship between microstructural features and processing conditions. Our results indicate that a many-to-one mapping can exist between processing conditions and typical descriptors; therefore, multiple descriptors are thus necessary to unambiguously represent microstructural images. Our work provides crucial quantitative and qualitative in-formation that would aid in the selection of features for microstructural images. Featurized microstructures could then be utilized to build data-driven models for predictive control of microstructures and thereby properties of additively manufactured components.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Investigating the p--π ± and p--p--π ± dynamics with femtoscopy in pp collisions at $\sqrt{s}$ = 13 TeV

The interaction between pions and nucleons plays a crucial role in hadron physics. It represents a fundamental building block of the low-energy QCD dynamics and is subject to several resonance excitations. This work studies the p--π ± dynamics using femtoscopic correlations in high-multiplicity pp collisions at $\sqrt{s}$ = 13 TeV measured by ALICE at the LHC. As the final-state interaction between protons and pions is well constrained by scattering experiments and the study of pionic hydrogen, the results give access to information on the particle-emitting source in pp collisions using the femtoscopy methods. The scaling of the source size of primordial protons and pions against their pair transverse mass is extracted. The results are compared with the source sizes studied with p–p, p--K + , and π ± –π ± pairs by ALICE in the same collision system and are found to be in agreement for the different particle pairs. This reinforces recent findings by ALICE of a common emission source for all hadron-pairs in pp collisions at LHC energies. Furthermore, the p--p--π ± systems are studied using three-particle femtoscopy in pp collisions at TeV. The presence of three-body effects is analyzed utilizing the cumulant expansion method. In this formalism, the known two-body interactions are subtracted in order to isolate the three-body effects. For both, p--p--π + and p--p--π – , a non-zero cumulant is found, indicating effects beyond pairwise interactions. These results give information on the coupling of the pion to multiple nucleons.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

NASA NTRS1994

Spectral filtering for plant production

Both plants and animals have one general commonality in their perception of light. They both are sensitive primarily to the 400 to 700 nm wavelength portion of the electromagnetic spectrum. This is referred to as the visible spectrum for animals and as the photosynthetically active radiation (PAR) spectrum for plants. Within this portion of the spectrum, animals perceive colors. Relatively recently it has been learned that within this same spectral range plants also demonstrate varying responses at different wavelengths, somewhat analogous to the definition of various colors at specific wavelengths. Although invisible to the human eye, portions of the electromagnetic spectrum on either side of the visible range are relatively inactive photosynthetically but have been found to influence important biological functions. These portions include the ultraviolet (UV approximately equal to 280-400 nm) and the far-red (FR approximately equal to 700-800 nm). The basic photoreceptor of plants for photosynthesis is chlorophyll. It serves to capture radiant energy which combined with carbon dioxide and water produces oxygen and assimulated carbon, used for the synthesis of cell wall polysaccarides, proteins, membrane lipids and other cellular constituents. The energy and carbon building blocks of photosynthesis sustain growth of plants. On the other hand, however, there are other photoreceptors, or pigments, that function as signal transducers to provide information that controls many physiological and morphological responses of how a plant grows. Known photomorphogenic receptors include phytochrome (the red/far-red sensor in the narrow bands of 655-665 nm and 725-735 nm ranges, respectively) and 'cryptochrome' (the hypothetical UV-B sensor in the 280-320 nm range). Since the USDA team of W. L. Butler, S. B. Hendricks, H. A. Borthwick, H. A. Siegleman and K. Norris in Beltsville, MD detected by spectroscopy, extracted and identified phytochrome as a protein in the 1950's, many other investigators have found evidence of its control functions in plants. Considerably less, however, is known about the yet non-isolated cryptochrome. The information-transferring roles of photoreceptors in plants at specific spectral ranges quite naturally stimulated plant scientists and engineers to consider physically manipulating light to achieve desired physiological and morphological characteristics. One way to manipulate light is to filter it through materials that selectively transmit portions of the sun's spectrum in and near the PAR range.

Young, Roy E.↗

DOE OSTI2024

ADRIANO2 Calorimeter performance from 2022 Prototypes

A novel high-granularity dual-readout calorimetric technique was developed as part of the T1604 collaboration research program. The building block of ADRIANO2 Calorimeter consists of a pair of optically isolated, small sized tiles made of scintillating plastic and lead glass. The two components of the dual-readout energy compensation technique. Furthermore,Cˇerenkovlightfromtheleadglassareexploitedtoforhighresolutiontimingmeasurements,whilehigh granularity from scintillating plastic can be used to probe the spatial component of the particle shower. This setup works for excellent energy resolution and particle identification for REDTOP as it is crucial for a calorimeter to detect and identify the decay products of eta/eta-prime mesons. Measurements were collected on several ADRIANO2 prototypes between February to December 2022 to evaluate the detector performance. The key metrics extracted from the analyses are presented in this paper are the efficiencies and light-yi eld for various tile configurations. The measured values will be used as input parameters for improved REDTOP Montecarlo simulation.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2022

Multimodal sensor fusion framework for residential building occupancy detection

For several years now, smart building energy systems have been a research area of intensive activity. In light of the increasing need for sustainable buildings and energy systems, this trend motivates an increasing need for a solution to reduce carbon dioxide emissions and improve energy efficiency. This work proposes a high-performing and transferable occupancy detection framework that combines sensor data from different data modalities, including time series environmental data (temperature, humidity, and illuminance), image data, and acoustic energy data using ensemble method. To draw out the best prediction performance in each modality, the proposed framework was developed, including various models that were designed to learn the occupancy patterns reflected in the physical data streams. To tackle the time series environmental data, we designed two variants of an occupancy detection spatiotemporal pattern network (Occ-STPN) that performs both feature level and decision level fusion, respectively. We also propose a new metric; the fading memory mean square error (FMMSE), that provides a fair evaluation and penalization of delayed occupancy predictions. Multiple open-sourced datasets, including the Electricity Consumption and Occupancy and the University of California, Irvine's (UCI) building occupancy detection dataset, along with our own real data collected from six different houses, were used to validate the algorithms' performance. The experimental results presented herein break down the performance for each sensing modality, and a detailed analysis of the performance is also discussed.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2023

Front-End Engineering and Design: Project Tundra Carbon Capture System (Final Report)

As the next phase of Project Tundra, Minnkota Power Cooperative (MPC) completed a front-end engineering and design (FEED) study to install a post-combustion CO 2 capture system (CCS) at the MPC operated (Square Butte Electric Cooperative-owned) Milton R. Young Station (MRYS) Unit 2 (MRY2), a 477-MW power plant fueled by North Dakota lignite. The project team completed the FEED with Fluor’s Econamine FG Plus℠ (EFG+) technology and is taking the next steps leading up to start of construction. Team members included FEED technical lead Fluor Enterprises (Fluor); owner’s engineer and balance of plant (BOP) engineer Burns & McDonnell (BMcD); leading carbon capture consultants (David Greeson Consulting, Hunt International Energy Services); environmental consultants (AECOM, Agora Environmental), other BOP engineering consultants (Golder Associates, Nels); cost-share funding agency, the North Dakota Industrial Commission (NDIC); and the Energy & Environmental Research Center (EERC). Project Tundra’s goal is to implement carbon capture, utilization, and storage (CCUS) in North Dakota, while preserving the use of lignite. Future options could lead to revitalizing legacy oil fields and creating a new CO 2 enhanced oil recovery (EOR) industry. The topic of this report is the FEED study for the carbon dioxide capture portion of Project Tundra. Building on the findings of a pre-FEED study for MRY2, the key deliverables contained in this FEED study are: a) design, costing, and performance data needed to commence project financing activities; b) engineering and material balances required to file for all project permits; and c) a final project schedule. Based on the results of the previous pre-FEED study, MPC and its team evaluated two options to provide the large amount of steam needed to operate the CCS: 1) installation of new natural gas package boilers and a new pipeline to supply natural gas to the facility and 2) extraction of steam from the existing MRYS steam turbine generator. The FEED study was performed using the package boilers option, as it was deemed to have the lowest technical risk, overall cost, and cost uncertainty. A key feature of the design, however, was the mixing the natural gas boilers’ flue gas with the MRY2 flue gas. This increased the size of the CCS system. This design also enabled the tie-in of Unit 1 flue gas for times when Unit 2 is offline. The CCS was designed to capture a combined 12,978 short tons per day (STPD) of CO 2 from the flue gases produced by the existing MRY Unit 2 along with flue gas produced by the new boiler package within the CCS. The 12,978 STPD CO 2 capture is achieved by normally processing 100% of the total available MRY Unit 2 flue gas (considering full load operation) and 100% of the boiler package flue gas, then removing 90% of the CO 2 available from the processed flue gas streams.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2020

On the Formalization of Development and Assessment Process for Digital Twins in the Nearly Autonomous Management and Control System

In recent years, the autonomous control system has been encouraged in advanced reactors for restoring economic viability, simplifying the operation and maintenance, and enabling remote-site power generations [1]. Since the reactor is expected to be operated for a long period of time with a limited number of individuals onsite, it is recommended that the autonomous control system should have access to very realistic models of the state of processes in the whole lifecycle, together with these process behaviors in interaction with their environment in the real world. As a result, digital twin (DT) technology is suggested in autonomous control systems. DT is defined as a digital representation of a physical object or system, which contains a record for the histories of loads, operation and maintenance status, predictions for the near-term transient of important state variables, and decision-making process [2]. Since machine learning (ML) can recognize patterns within a complex system in real-time applications, it has been used to build DTs in the autonomous control systems for advanced reactors. Meanwhile, due to the rareness of operation data in accident scenarios, the development and assessment of DTs is expected to be mainly driven by simulations. Although the capability and feasibility of ML-based DTs are recognized in improving the safety and efficiency of reactor control, a major concern from the regulatory commission and the nuclear industry is whether the information from a DT is developed and assessed in accordance with expectation and requirements by the target decision. Such concerns not only affect the acceptance criteria for DTs, but also values that can be extracted from DTs and autonomous control system during operations. Inspired by the success of formal methods in improving the reliability and robustness of computer programming and software development, it is suggested that the development and assessment process (DAP) for both separate DTs and integral control system should be formalized in a transparent, consistent, and improvable manner. In this study, a digital-twin development and assessment process (DT-DAP) is proposed by adapting the evaluation model development and assessment process (EMDAP) [3] to requirements by the autonomous control system, ML algorithms, and DT technology. To demonstrate the framework, a baseline nearly autonomous management and control (NAMAC) system with ML-based DTs for diagnosis and prognosis is developed and assessed based on the framework. It is found that with selected testing methods and techniques, the DT-DAP can help identify errors in DTs and NAMAC which would otherwise be left unverified. Meanwhile, it is found that the DT-DAP can improve the DTs and NAMAC by continuously learning and iterating through different elements.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2021

Adoption of image-driven machine learning for microstructure characterization and materials design: A Perspective

Microstructure characterization enables the development of structure-processing-property relationships critical to several research areas within the broad field of materials science, from alloy design to the assessment of corrosion resistance, and failure analysis. Conventional approaches to material characterization have relied on either qualitative inference by the human ex-pert or software applications that can extract high-level features from images, such as boundary segmentation, average grain diameter, etc. Such approaches rely heavily on subject matter expert user intervention and knowledge of what phases or more generally, what microstructural features, are of interest. The recent surge in the adoption of machine learning techniques to address problems in materials engineering has brought with it an increased interest and application of Image Driven Machine Learning (IDML) approaches. In this work, we review the applications of IDML to the field of materials characterization. A canonical hierarchy of stages is defined, which when put sequentially together completes an IDML study: problem definition, dataset building, model selection and training, model evaluation, and integration with existing instrumentation or simulation workflow. The studies reviewed in this work are analyzed from the perspective of each of these stages. Such a review permits agranular assessment of the field, for example the impact of IDML on materials characterization at the nanoscale, the size of a typical dataset required to train a semantic segmentation model on electron microscopy images, ubiquitousness of transfer learning in the domain, etc. Finally, we discuss the importance of interpretability and explainability in the field of IDML for materials characterization, and provide an overview of two emerging techniques in the field: semantic segmentation and generative adversarial networks.

Baskaran, Arun↗

DOE OSTI2023

Measurement of isotopic separation of argon with the prototype of the cryogenic distillation plant Aria for dark matter searches

The Aria cryogenic distillation plant, located in Sardinia, Italy, is a key component of the DarkSide-20k experimental program for WIMP dark matter searches at the INFN Laboratori Nazionali del Gran Sasso, Italy. Aria is designed to purify the argon, extracted from underground wells in Colorado, USA, and used as the DarkSide-20k target material, to detector-grade quality. In this paper, we report the first measurement of argon isotopic separation by distillation with the 26 m tall Aria prototype. We discuss the measurement of the operating parameters of the column and the observation of the simultaneous separation of the three stable argon isotopes: ${}^{36}\hbox {Ar}$, ${}^{38}\textrm{Ar}$, and ${}^{40}\textrm{Ar}$. We also provide a detailed comparison of the experimental results with commercial process simulation software. This measurement of isotopic separation of argon is a significant achievement for the project, building on the success of the initial demonstration of isotopic separation of nitrogen using the same equipment in 2019.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗