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DOE OSTI2025

Implementation of a turbine farm model into the Energy Exascale Earth System Model for investigation and quantification of global climate impacts

Although there has been widespread deployment of wind farms in the United States, and plans to continue deployment into the future, the complete effects of wind farms on Earth systems are not well understood. The work performed here has incorporated wind farm models into the Energy Exascale Earth System Model (E3SM) capable of simulating the effects of extracting momentum from the atmospheric flow field using power generating wind farms. This new capability will allow scientists to quantify the impacts of wind farm induced changes on Earth systems by exploiting E3SM’s ability to couple atmospheric, oceanic, and biogeochemical (BGC) models on a global scale and monitor precipitation levels, extreme weather events, soil moisture content and jet stream location over decades-long time periods. This tool will be used to inform decision making on wind farm citing and will contribute to the Lab’s ability to assess energy technology impacts on the environment and evaluate the trade-offs between energy infrastructure investments and their impacts on natural systems.

17 WIND ENERGY↗

DOE OSTI2024

Dodecane Radiolysis Yields by Time-Resolved and Steady-State Methods

Liquid organic molecules are present as solvents, complexing ligands, and additives in both used nuclear fuel reprocessing solvent systems and in their subsequent nuclear waste streams. Under these extreme environments, these organic molecules are constantly exposed to ionizing radiation which promotes their radiolysis, forming a variety of short-lived, highly energetic, excited state and radical species.1-4 Here, we demonstrate new experimental results for the steady-state and time-resolved irradiations of dodecane (C12H26), a long chain, liquid, aliphatic hydrocarbon that is the prototypical solvent used for benchtop studies of aqueous-organic solvent extraction systems. When ionizing radiation interacts with neat dodecane, the energy transfer can result in molecular ionization, to give the dodecane radical cation (C12H26+•) and the solvated electron (eS–), and molecular electronic excitation (C12H26*), which rapidly produces transient carbon-centered radical fragments (CxHy•) and hydrogen atoms (H•).1-4 Studies on the initial yields of the ionization and excitation products were performed using time-resolved picosecond electron pulse radiolysis with the use of molecular probes. Using steady-state cobalt-60 gamma irradiations, the suite of products formed by dodecane radiolysis in aerated and deaerated solutions was determined. Then, using iodine as an alkyl radical scavenger, the loss of molecular iodine with dose was quantified, and by correlating with the molecular hydrogen yields of the system, the initial yields of the various carbon-centered radicals were also determined. Finally, the rates of reactions of the C12H26+• and eS– with ligands proposed for use in spent nuclear fuel reprocessing were studied as a function of temperature from 10 – 40 °C.

38 - RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCL↗

DOE OSTI2024

DEVELOPMENT AND DEMONSTRATION TESTBED FOR THE REMOTE OPERATIONS AND MONITORING OF MICROREACTORS

The nuclear industry is rapidly developing many advanced-reactor concepts for near-term deployment in both traditional and non-traditional nuclear-powered applications. One such category of advanced reactor is the microreactor, a class of reactor with less than 20MWth power output, intended for applications where the economics or logistics of traditional power sources are difficult. This includes applications such as remote communities, mining sites, defense installations, or humanitarian and disaster-relief missions. One key enabling feature for the successful deployment of microreactors is a remote operations capability. Remote operations provide monitoring and control capabilities which can significantly reduce staffing costs by eliminating the need for licensed operators at each reactor facility and improve the economic viability for microreactor deployment. A remote concept of operations is not currently an established capability in the nuclear industry. In addition, no demonstration microreactor is expected to complete construction or go critical until at least 2026. This leaves two major capability gaps: the successful demonstration of a remote concept of operations for microreactors and a test bed suitable for said demonstration. Both gaps must be addressed in order to advance the remote concepts of nuclear operation and, more broadly, microreactors themselves from paper to reality. This paper aims to fill these gaps and describes a test bed that would support development and deployment of a remote concept of nuclear operations, initial experimental results from that test bed, and the application of the test bed and experimental results for a digital-twin-based remote concept of operations underdevelopment at Idaho National Laboratory (INL). The platform chosen as a remote concept of nuclear operations test bed is the Single Primary Heat Extraction and Removal Emulator, known as SPHERE, located at INL. SPHERE is a small-scale non-nuclear test bed that emulates thermal behavior of a microreactor. The small-scale and non-nuclear nature of SHPERE limit safety concerns associated with remote operations while still providing the physical response representative of a microreactor. A network connection was added to SPHERE that enables remote-monitoring capability. This allows for real-time data streaming to networked workstations, data historians, and human-machine interfaces (HMIs). These are all critical components in a remote concept of operations, thus providing a robust development and demonstration platform. An initial experiment was performed using the SPHERE remote operations testbed. This included running a comprehensively instrumented SPHERE through a series of steady-state and transient operating scenarios in both normal and abnormal operating conditions, all while streaming live test data to a remote HMI and data warehouse. This initial experiment served three purposes: (1) characterizing the response of SPHERE, (2) demonstrating the remote connection to SPHERE, and (3) providing a baseline data set for development of a digital-twin-based remote concept of operations that is under development at INL.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2024

DEVELOPMENT AND DEMONSTRATION TESTBED FOR THE REMOTE OPERATIONS AND MONITORING OF MICROREACTORS

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2025

Scalable and Regenerable Fibrous Amine-functionalized Matrix (FAM) sorbent for Efficient Enrichment of Critical Minerals from Coal Wastewaters

The poster presents the latest progress on utilizing a commercially scalable flat sheet sorbent for the effective enrichment of critical minerals from coal wastewater. It highlights the performance, scalability, and potential for industrial applications, addressing key challenges in critical recovery from complex wastewater streams.

critical metals↗

DOE OSTI2024

Oxidative Catalytic Fractionation of Lignocellulosic Biomass Using a Co-N-P-C Catalyst and One-Step Isolation of Aromatic Monomers via Centrifugal Partition Chromatography

Methods for catalytic fractionation of biomass provide a means to convert lignin directly into monomers while generating a high-quality cellulosic stream, contrasting conventional biomass pretreatment strategies that prioritize the cellulosic fraction. Here, a nonprecious-metal Co-N-P-C catalyst is identified for aerobic oxidative catalytic fractionation (OCF) of poplar feedstock in dimethyl carbonate that achieves significantly higher yields of aromatic monomers (24 wt %) relative to those obtained with a recently reported Co-N-C catalyst in acetone solvent (15 wt %). Mechanistic studies indicate that the acidic properties of the catalyst contribute to its improved performance by promoting extraction of lignin from insoluble polysaccharides. This OCF process is complemented by the development of a new centrifugal partition chromatography (CPC) method that supports isolation of all five major aromatic monomers (syringic acid, syringaldehyde, vanillic acid, vanillin, and para-hydroxybenzoic acid) in a single liquid–liquid extraction purification step. Furthermore, this OCF/CPC sequence has important implications for future lignin valorization efforts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Full Modeling and parameter compression methods in configuration space for DESI 2024 and beyond

In the contemporary era of high-precision spectroscopic surveys, led by projects like DESI, there is an increasing demand for optimizing the extraction of cosmological information from clustering data. This work conducts a thorough comparison of various methodologies for modeling the full shape of the two-point statistics in configuration space. We investigate the performance of both direct fits (Full Modeling) and the parameter compression approaches (ShapeFit and Standard). We utilize the ABACUS-SUMMIT simulations, tailored to exceed DESI's precision requirements. Particularly, we fit the two-point statistics of three distinct tracers (LRG, ELG, and QSO), by employing a Gaussian Streaming Model in tandem with Convolution Lagrangian Perturbation Theory and Effective Field Theory. We explore methodological setup variations, including the range of scales, the set of galaxy bias parameters, the inclusion of the hexadecapole, as well as model extensions encompassing varying ns and allowing for w 0 w a CDM dark energy model. Throughout these varied explorations, while precision levels fluctuate and certain configurations exhibit tighter parameter constraints, our pipeline consistently recovers the parameter values of the mocks within 1σ in all cases for a 1-year DESI volume. Additionally, we compare the performance of configuration space analysis with its Fourier space counterpart using three models: PyBird, FOLPS and velocileptors, presented in companion papers. We find good agreement with the results from all these models.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

Deuterium Extraction from Helium with a Vanadium Vacuum Permeator: Commissioning of the Tritium Extraction eXperiment (TEX)

Here, the Tritium Extraction eXperiment (TEX) is a forced-convection lead-lithium (PbLi) loop in the Safety and Tritium Applied Research (STAR) facility at Idaho National Laboratory (INL) with the purpose of providing validation data for the vacuum permeator tritium extraction concept. A vanadium tube of 1000 mm length, 12.7 mm outside diameter, and 0.50 mm wall thickness is installed in the test section of TEX. The installed vanadium tube is characterized to quantify impurity concentrations, surface chemistry, and microstructure to elucidate permeation phenomena observed in experimentation. Herein, the permeation properties of the vanadium tube are characterized by measuring deuterium permeation at 300 °C, 325 °C, and 350 °C at 100 kPa, 125 kPa, and 150 kPa total pressures with 5000 ppm deuterium in helium gas mixture in a once-through flow configuration. The hydrogen isotope permeation through the vanadium tube in the test section is measured with quadrupole mass spectrometers and the hydrogen isotope concentration in the feed and retentate gas stream is measured with gas chromatography. The transient permeation results are modeled with MELCOR-TMAP, a thermal-hydraulic tritium transport code, and compared well with literature data.

70 - PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

Developing Digital Twin Visualizations: A Methodology and Case Study on Chemical Separation Processing

As advances in digital engineering continue to push the technological boundaries, digital twin (DT) visualizations for diagnostics and safeguards advancement become much more feasible and practical. DTs generate large and complex data streams that require effective user interfaces to provide monitoring and diagnostic capabilities. Unfortunately, while these frameworks exist, there is not much research on the systematic documentation of human–computer interaction (HCI) for DT visualization. This work presents a dual-mode visualization methodology (two dimensional [2D] graphical user interface dashboard and 3D mixed reality) designed to support diagnostic tasks in DT systems and building on a validated framework and applying established HCI principles. The methodology is demonstrated through a case study of aqueous processing at Idaho National Laboratory, using experimental data from the chemical solvent extraction runs. Our interfaces display real-time alerts and monitoring to inform users of safeguards anomalies. The interfaces use immersive 3D mixed-reality visualization for further system and experiment investigation. This work demonstrates how the systematic application of HCI principles can inform DT visualization design for diagnostic and safeguards applications. While formal user evaluation studies remain as future work, this paper documents the systematic design methodology and demonstrates a proof-of-concept implementation.

3D visualization↗

DOE OSTI2026

Feature-Based PMU Event Classification under Variable PMU Participation and Overlapping Events

Danovo Energy Solution's presented its paper named: Feature-Based PMU Event Classification under Variable PMU Participation and Overlapping Events at the 2026 Georgia Tech Fault & Disturbance Analysis Conference. The full paper can be found at OSTI ID# 3169150 Paper Abstract—Phasor Measurement Units (PMUs) stream time synchronized, high-resolution measurements from the grid, enabling data-driven techniques for event detection and classification. Accurate event classification improves grid reliability and stability. Events can be detected by varying numbers of PMUs and exhibit different durations depending on the event type. This variability challenges standard classifiers that require uniform input sizes. Moreover, multiple events may coincide, which increases classification complexity. Standard classifiers assign each instance to the class with the highest predicted probability, whereas overlapping events may exhibit comparable probabilities across multiple classes. In this study, to handle data size variability, we extract a wide range of time–frequency domain features from all available PMUs for each event into a fixed-length vector, facilitating the application of standard machine learning classifiers, including Random Forest, XGBoost, LightGBM, Support Vector Machine, and Multilayer Perceptron. To account for overlapping events, a probabilistic post-processing step is applied. For a given data instance, if multiple predicted class probabilities exceed 30% and the differences between them are less than 10%, the event is assigned to multiple classes. Experiments using real-world PMU data demonstrate that the Random Forest and XGBoost models achieve the highest accuracy, while the proposed post-processing method yields perfect classification performance on external unseen test sets.

Nematirad, Reza [Danova Energy Solutions]↗

DOE OSTI2026

Feature-Based PMU Event Classification under Variable PMU Participation and Overlapping Events

This paper is the basis for a presentation help at the 2026 Georgia Tech Fault & Disturbance Analysis Conference, which can be found at OSTI # 3168287 Paper Abstract—Phasor Measurement Units (PMUs) stream time synchronized, high-resolution measurements from the grid, enabling data-driven techniques for event detection and classification. Accurate event classification improves grid reliability and stability. Events can be detected by varying numbers of PMUs and exhibit different durations depending on the event type. This variability challenges standard classifiers that require uniform input sizes. Moreover, multiple events may coincide, which increases classification complexity. Standard classifiers assign each instance to the class with the highest predicted probability, whereas overlapping events may exhibit comparable probabilities across multiple classes. In this study, to handle data size variability, we extract a wide range of time–frequency domain features from all available PMUs for each event into a fixed-length vector, facilitating the application of standard machine learning classifiers, including Random Forest, XGBoost, LightGBM, Support Vector Machine, and Multilayer Perceptron. To account for overlapping events, a probabilistic post-processing step is applied. For a given data instance, if multiple predicted class probabilities exceed 30% and the differences between them are less than 10%, the event is assigned to multiple classes. Experiments using real-world PMU data demonstrate that the Random Forest and XGBoost models achieve the highest accuracy, while the proposed post-processing method yields perfect classification performance on external unseen test sets.

Nematirad, Reza [Danovo Energy Solutions]↗

DOE OSTI2025

Conceptual Model Testing Related to SDU 6 Drainwell Observations

From its inception in the early 1950s through the end of the Cold War in the early 1990s, the Savannah River Site (SRS) produced nuclear materials for national defense in five reactors. Additionally, irradiated reactor fuel and target tubes were dissolved in nitric acid to recover plutonium and uranium using the PUREX (Plutonium Uranium Reduction EXtraction) process. Liquid waste from these chemical separations processes was then stored onsite in 51 underground tanks. Eight waste storage tanks have been operationally closed (i.e. cleaned and grouted) and the remaining tanks hold a mixture of liquids, insoluble solids, and precipitated salts (SRMC-LWP-2022-00001), the latter generated by evaporating water from the liquid waste. Waste is currently being retrieved from tanks and separated into 1) high-radioactivity, low-volume, and 2) low-radioactivity, high-volume components, principally through the Salt Waste Processing Facility (SWPF) (SRMC-LWP-2023-00001). The former waste stream is vitrified in the Defense Waste Processing Facility (DWPF), stored onsite, and destined for offsite disposal in a deep geologic repository. The latter stream is mixed with dry cementitious materials in the Saltstone Production Facility (SPF) and the wet slurry placed in onsite Saltstone Disposal Units (SDUs) within the Saltstone Disposal Facility (SDF), where it hardens into a cement waste form termed saltstone. A low-infiltration surface cover system will be placed over the SDF at closure, where SDUs will then be in the subsurface post-closure (SRR-CWDA-2019-00001).

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2024

ICED: An Integrated CGRA Framework Enabling DFVS-Aware Acceleration

oarse-grained reconfigurable arrays (CGRAs) are a promising solution to enable energy-efficient acceleration of applications from different domains. By leveraging reconfiguration at the functional level, they can adapt to significantly different computational patterns. Existing CGRA mapping approaches extract instruction-level parallelism, exploit loop-pipelining opportunities, guarantee the data dependency, and target high throughput of a given loop. However, the recurrence data-dependency in the DFG and the mismatch between required and available computing/communication resources complicate the mapping, and might lead to significant unbalances in the utilization of the CGRA's tiles. This results in wasted power for tiles with low utilization. Applying dynamic voltage and frequency scaling (DVFS) can potentially solve this challenge and improve energy efficiency by adjusting voltage and frequency of different tiles independently. CGRAs have also been successful in accelerating data-dependent streaming applications. However, in these applications, the execution time of each kernel in the pipeline might dynamically vary depending on the characteristics of the input. This also leads to under-utilization of resources for the dynamically changing kernels that do not limit the application throughput. DVFS can also improve energy efficiency for these applications by dynamically changing the voltage and frequency levels of tiles that host non performance-constraining kernels. This paper proposes ICEDTEA -- an integrated DVFS-aware framework to map applications on CGRAs that support power islands. ICEDTEA proposes a CGRA architecture supporting DVFS islands at varying granularity (from a single tile to a group of tiles) and the related DVFS-aware compilation and mapping toolchain. ICEDTEA is the first work that introduces DVFS support for spatio-temporal CGRAs at power-island levels. The experimental evaluation shows that ICEDTEA improves average utilization by 2.3$\times$ and energy-efficiency by 1.32$\times$ over a conventional CGRA. With streaming applications, ICEDTEA improves energy efficiency by 1.12$\times$ over a state-of-the-art CGRA that introduces partial dynamic reconfiguration to adapt to variations in kernels' throughput.

Tan, Cheng↗

DOE OSTI2026

Equivalent equilibrium ion distributions in ion sources and beams

Ion sources and ion beams often contain ions of more than one charge-to-mass ratio, due to the presence of multiple ionization states and/or multiple atomic and molecular ion species in the source. We show that, under certain conditions, analysis of these systems can be simplified using the notion of “equivalent equilibrium ion distributions” (EEIDs). These distributions have identical ion trajectories, space-charge distributions, and electric-field distributions, but can be composed of ion species with arbitrary charge-to-mass ratios. We use this result to obtain multi-species generalizations for the perveance of an ion diode, which relates the diode voltage to the extracted beam current, and for the perveance of a drifting ion beam, which determines the axial length-scale for beam expansion due to the self-electric field. Applied to a quasi-neutral plasma ion source containing cold ions and hot electrons, we find that the location of the beam-plasma interface (meniscus), where ions are extracted from the plasma, depends on the electron density and ion energy per unit charge at the interface, independent of the ion composition. For certain types of numerical simulations, EEIDs allow one to calculate the beam optics of an intense multi-species ion source by doing a simulation for a single ion species with an artificial charge-to-mass ratio chosen to minimize computation time. We illustrate these results using the 3D particle-in-cell, finite-element code Aleph. The simulations show how ions in a plasma source self-consistently accelerate to the supersonic speed needed for steady, radially expanding flow. Multi-species equilibria are subject to streaming instabilities because, while the different species have the same kinetic energy per unit charge, their velocities scale with the square root of the charge-to-mass ratio. The simulations show that a strong ion streaming instability can occur in a multi-species plasma ion source.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2026

Online Alpha Monitoring of High Cs-137 Hanford and SRS High Level Waste with Tensioned Metastable Fluid Detectors

The Department of Energy’s Hanford and Savannah River Sites maintain millions of gallons of caustic supernate and salt high activity waste in their high-level waste (HLW) tank farm inventories. The Savannah River Site is currently treating this waste with a calixarene-based solvent extraction of Cs-137 to reduce these inventories. Hanford is employing an at-tank crystalline silico titanate (CST) based solid phase extraction methodology to reduce their liquid HLW inventories. Due to the high solubility of Cs-137 and the relative insolubility of the actinides in these caustic waste forms, the beta to alpha radioactivity ratio can often exceed six orders of magnitude in the feed solutions to these treatment processes. This unique characteristic leads to significant technical challenges in making rapid gross alpha measurements in the presence of the overwhelming beta, gamma, as well as dissolved sodium salt in these HLW matrices. Conventional radioanalytical techniques, such as liquid scintillation analysis or gas flow proportional counting require significant radiochemistry preparation prior to the radiometric measurements for gross alpha activity. These required pretreatments render these technologies untenable for rapid quantification of gross alpha activity that could be required to support on or at-line measurements ensuring a waste stream will meet regulatory requirements. The radiation measurement properties of Tensioned Metastable Fluid Detectors (TMFDs) have been studied by Purdue University’s Taleyarkhan research group for well over a decade. Fluids tensioned to the appropriate degree will rupture when struck by radiation, resulting in a measurable cavitation event. The negative pressure generating this tension can be adjusted by centrifugal rotation or by acoustic means in such a way that these cavitation events can be generated from alpha radiation but will not be generated by beta or gamma radiation. Purdue University and the Savannah River National Laboratory are currently collaborating to develop a gamma/beta blind, spectroscopic alpha measurement system based on the Tensioned Metastable Fluid Detector technology to provide a potential solution for performing rapid gross alpha measurements on these high gamma/beta sample matrices. Measurements using the Indirect Drive Acoustically Tensioned Metastable Fluid Detectors developed as part of this collaboration were performed with an alpha emitting radionuclide. Successful determination of gross alpha activity was observed, indicating a potential pathway for rapid gross alpha measurements in remote-handled shielded cells or in process situations requiring online alpha monitoring. Measurements using this system have been conducted on high beta activity solutions, demonstrating the beta blind capability of this system. Measurements are currently underway to test the system’s capability to measure gross alpha activity on Savannah River Site high level waste high Cs-137 samples that have been measured by the SRNL radiochemistry team. This work was supported by the DOE EM Technology Development program.

DiPrete, David [Savannah River National Laboratory↗

DOE OSTI2026

Postanaerobic Digestion Manure Fibers as a Renewable Source of Lignin-Derived Aromatic Compounds for Microbial Upgrading

Abstract Postanaerobic digestion manure fibers are an abundant solid residue that remains underutilized. The substantial lignocellulosic content of digested manure opens the possibility of using it as a renewable resource for producing valuable products. In this study, we performed compositional and nuclear magnetic resonance analyses to determine lignin content and aromatic composition of these fibers. Additionally, alkaline-based treatment and reductive catalytic fractionation were evaluated as two different processes to produce aromatic-rich streams. The liquor from the alkaline treatment was subsequently utilized for microbial upgrading to produce 2-pyrone-4,6-dicarboxylic acid (PDC). The results showed that lignin in manure fibers represents 30% of the biomass (dry weight basis), with a ∼26% abundance of β-ether-linked aromatics and ∼13% p-coumarate moieties, indicating that the amount of lignin in the postanaerobic biomass is comparable to a moderately pretreated plant biomass. The alkaline treatment released 5.6 g aromatics/kg fibers, while reductive catalytic fractionation produced 14.0 g aromatics/kg fibers. A bioreactor operated in fed-batch mode produced a yield of ∼1 mol of PDC/mol measured aromatics at a rate of 0.2 g PDC/L·h and a titer of 2.6 g PDC/L. This study demonstrates how postanaerobic digestion manure fibers could be used in a circular bioeconomy by harnessing their lignocellulosic content to extract aromatic compounds and use them for obtaining valuable chemicals via microbial upgrading.

Riascos, Brayan D. [University of Wisconsin-Madiso↗

DOE OSTI2025

Simulation Results of a Thermal Power Dispatch System from a Generic Pressurized Water Reactor in Normal and Abnormal Operating Conditions

Amid economic pressures in the U.S. electricity market, nuclear utilities are exploring new revenue streams, including hydrogen production. A generic pressurized water reactor simulator was modified to incorporate a novel design for a TPD system coupled to a hydrogen production plant. Standard malfunctions were included in the simulation design, including steam line breaks at various system locations and flow interruptions in the hydrogen plant due to multiple faults, reflecting anticipated operational challenges. It is imperative that the TPD system operation has a minimal effect on the reactor power, primary coolant system, and turbine system operation and performance. Due to the specific design and application of this TPD system, with the proposed turbine control system changes, the overall impact on the existing plant systems is low. Normal TPD operating scenarios resulted in minor effects on the existing plant systems: reactor power changes by at most 0.2%, and gross generator output changes by 20.5 MWe from 100 MWt of TPD. The most severe malfunction analyzed in this work is a full TPD steam line break downstream of the extraction location, which results in an increase in reactor power of about 0.5%. The gross generator output decreases by 36 MWe, a total decrease of 60 MWe from the full power steady state (FPSS) condition. These results indicate that an industrial hydrogen production plant could be coupled thermally to a nuclear power plant with limited effects on the existing system operation and safety.

08 HYDROGEN↗

DOE OSTI2025

Contaminant Investigation and Pre‐Processing Opportunities for Textile‐To‐Textile Recycling

Millions of metric tons of textiles are landfilled or incinerated each year in the United States, with less than 1% of textiles recycled into new clothing or fabrics. To counter this trend, a growing number of companies and researchers are exploring how a circular economy can be applied to support textile‐to‐textile recycling. A significant barrier they face comes down to quickly and efficiently extracting pure feedstock material from post‐consumer garments that feature a mix of natural and synthetic fibers. Textile recyclers prefer pure feedstocks, as working with mixed sources typically means lower throughput, higher risk of equipment failure, and diminished business margins. To facilitate a circular economy for textiles, methods, and technologies are needed that can efficiently separate out materials and contaminants from end‐of‐life textiles to increase the flow of pure feedstocks to recyclers. This paper summarizes findings from interviews with a cross section of textile recyclers and from a review of literature to define basic feedstock requirements. In addition to our qualitative research, we deconstruct a bale of post‐consumer textiles and analyze them using computer‐vision imaging, Fourier transform infrared spectroscopy (FTIR), and machine learning. The resulting data are used to set system‐level design inputs for an automated contaminant removal system to process post‐consumer clothing into appropriate feedstocks for recycling. To set the system's levels for automated real‐time near‐infrared analysis, we identify the minimum percentage of primary material that any single garment in a load of used clothing must contain for the average of the full output stream to meet the target purity levels of recyclers. Here, the envisioned automated system can also address undesirable trace materials that might contaminate the processed stream by using imaging cameras coupled with artificial intelligence to identify sections of clothing for de‐trimming. Proof‐of‐concept machine learning algorithms are evaluated to locate and identify trims or garment areas with hidden contaminant materials. Integrating these methods into automated textile cutting systems can provide a cost‐effective means for increasing feedstock purity from used clothing, which can advance circularity for textiles by helping recyclers to reach production volumes and quality targets that were not possible solely with manual dismantling operations.

Parsons, Ryan [Rochester Institute of Technology, ↗