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At least 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Recycling Wind Energy Systems in the United States Part 1: Providing a Baseline for America's Wind Energy Recycling Infrastructure for Wind Turbines and Systems

The U.S. investments in building this new wind energy capacity will not only mobilize millions of tons of raw and processed materials in existing supply chains, some of which are critical materials, but also create new types and large volumes of end-of-life (EOL) waste streams. Building efficient, cost-effective, and environmentally responsible EOL management infrastructure of wind energy system components is pivotal in diverting upcoming volumes of waste stream from landfills, recovery of critical materials and reducing life cycle emissions from production of primary commodity materials . The primary goal of this report is to organize and communicate findings from this assessment on how alternate materials, designs and manufacturing processes could enable more efficient, cost-effective, and environmentally responsible disassembly and resource recovery from wind energy technologies. The findings of this assessment could inform prioritization of RD&D investment spending to meet Energy Act of 2020 directions. This assessment focused on key RD&D recommendations for three main temporal phases: Short-term (2023-2026), medium-term (2026 through 2035) and long-term (beyond 2035).

17 WIND ENERGY↗
DOE OSTI2025

ALICE-USA Barrel Tracking Upgrade (Project Final Report)

The ALICE-USA Barrel Tracking Upgrade (BTU) project began in 2015 to participate in a major upgrade of the Time Projection Chamber (TPC) and the Inner Tracking System (ITS) of the ALICE Experiment at CERN in Geneva, Switzerland. This upgrade increased the maximum readout rate of the ALICE detector to accommodate the increased heavy ion interaction rates following Long Shutdown 2 of the Large Hadron Collider, and greatly improved the vertexing performance of the detector. The original scope was completed and reviewed in November 2019. The BTU project document BTU.19.v1 "ALICE Barrel Tracking Upgrade Project Closeout / Transition to Operations (2019)" from November 2019 describes the status in detail and is attached as Appendix 1 below. At that point, all delivery milestones had been met on time, all Key Performance Parameters (KPPs) of the project had been satisfied, and the project was under budget. Several subsequent No Cost Extensions (NCEs) supported integration and pre-commissioning of the BTU project deliverables at CERN, as well as study and assessment of performance with Pb-Pb collisions at 50 kHz. The BTU project was successfully completed on 30 September 2024.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Report on the "Symposium on Advancements in Simulating Neutron Scattering Instruments and Experiments"

An international group of researchers gathered for the “Symposium on Advancements in Simulating Neutron Scattering Instruments and Experiments” at Oak Ridge National Laboratory (ORNL) on October 29- 30, 2024. The symposium highlighted state-of-the-art advancements in neutron scattering instrument simulations and the development of digital twins for scattering instruments. This document summarizes the recurring themes from the 19 talks and discussions. A key focus was on the role of neutronics simulations in the design, analysis, and performance optimization of neutron instruments. Presentations featured the most widely used software packages, such as McStas, McVine, Vitess, and MCNP. Another major theme addressed the analysis and interpretation of experimental neutron data, where materials models and simulations play a critical role. Talks on relevant software tools, including NCrystal, OCLimax, and Paradyse, were delivered by their respective developers. During the symposium, both talks and breakout sessions explored strategies to enhance the interplay between neutronics simulations and materials models. A key question emerged: How can we develop a RealTime Explainable Digital Twin of a neutron scattering experiment? Discussions include the idea that the Digital Twin concept has implications for instrument control and testing. Through this symposium, we gained valuable insights into the challenges and requirements for developing a Real-Time Explainable Digital Twin of a neutron scattering experiment. The discussions and presentations paved the way for future innovations in this rapidly advancing field.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Testing a Hazmatpac Can with Locking Ring as a Secondary Shipping Container for Radium-224/Lead-212 Generators

A Hazmatpac can, paint can style shipping container with locking ring, was tested for use as an alternative shipping configuration for shipment of radium- 224 /lead- 212 generators. 224 Ra ( t 1/2 = 3.63 d) decays by alpha emission to radon-220 ( t 1/2 = 55.6 s). The potential for the radioactive radon gas to escape the generator column and the shipping container is of particular concern for the safe delivery of 224 Ra/ 212 Pb generators to customers. The purpose of this study was to evaluate whether the Hazmatpac can is a suitable shipping configuration, capable of containing the radon gas that may escape the generator column during transit. A 17.3 mCi 224 Ra/ 212 Pb generator was built and packaged into a Hazmatpac can. The can was smeared by a Radiological Control Technician (RCT) every day for seven days to analyze for radioactive contamination on the outside of the can. Over the course of the study, no radioactive contamination was found on the outside of the can. Therefore, the Hazmatpac can was approved as an alternative shipping configuration for shipment of 224 Ra/ 212 Pb generators.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

MPEX AI Digital Twins

All magnetically confined plasma fusion power plant concepts (Tokamak, Spherical Tokamak, Stellarator, Mirror, ...) must exhaust the heat and plasma from the core confinement region to the material walls. The primary channel for this exhaust is through a plasma divertor which directs plasma along open magnetic field lines to a material target. The Material Plasma Exposure eXperiment (MPEX) illustrated in Figure 1, is a high-power, steady-state linear plasma device designed to produce the plasma material interaction (PMI) conditions of the divertor of future magnetic confinement fusion power plants: energy flux 20MW/m 2 , ion fluence 1031/m 2 , pulse duration 106 sec. These goals of plasma exposure in MPEX are well beyond those achieved in magnetic fusion experimental devices. Successfully achieving these high power steady state conditions for long pulses requires operational control of the heating and particle sources and the plasma flux to the walls and target. The MPEX AI Hot Spot Controller, proposed in this project, will help achieve the operational milestones of MPEX. The MPEX device will begin commissioning at the end of FY26. A smaller proto-MPEX was operated for 14,666 plasma discharges and will resume operation in September of 2025 as proto-MPEX-lite, with reduced capability, to test a new window for the Helicon plasma source. The proto-MPEX data has undergone surrogate modeling with machine learning methods (R. Archibald, 2022 IEEE International Conference on Big Data). This proto-MPEX data will be used to begin development of the AI digital twins described in this white paper. The scientific mission of MPEX is to qualify materials of different composition for use in the high energy and plasma flux conditions of a fusion power plant. The materials exposed in MPEX will in some cases be exposed to high neutron fluxes at other ORNL facilities to measure the changes to their PMI properties. The targets exposed in MPEX will be transported under vacuum to a Surface Analysis Station (SAS). The SAS will be equipped with the following diagnostics: Focused Ion Beam (FIB) for trench milling, 100-400 angstrom resolution scanning electron microscope (SEM), surface mapping x-ray spectrometer, high resolution camera, and a future upgrade to a laser induced breakdown spectroscopy quadruple mass spectrometer (LIBS-QMS). The MPEX experiments will generate diverse pre- and post-exposure measurement data of detailed material properties down to the crystal grain level in 3D for post-exposure assessment of PMI damage (e.g. cracking, melting, erosion and redeposition of the material). Physics models for the PMI, and how the material composition and manufacturing impact its performance under high energy plasma exposure, need to be validated with MPEX data to guide the selection of new candidate materials. Our vision for the MPEX AI Digital Twins project is to supply experimental and physics model simulation data to train Artificial Intelligence (AI) models for data processing, analysis, operational control, PMI and materials simulation to maximize the scientific output of the MPEX device. Ultimately, an AI digital twin of MPEX material assessment metrics for tested and synthetic material types with simulated PMI will be trained by the AI Modeling Teams on the experimental and physics simulation data submitted to the American Science Cloud by this project. A purely empirical search for the best material is inefficient given the finite number of samples that can be tested on MPEX. In order to expand the material properties database for training the MPEX Material Assessment AI Digital Twin, and to gain physics understanding of the PMI processes, physics models of the material properties and PMI processes are required. The physics simulations provide detailed simulation data, like impact angles for plasma ions, sputtering yields, transport of the ionized sputtered target material in the plasma, and redeposition locations. This simulation data expands the measurement data for deeper physics understanding. The experimental data is essential to validate the PMI and material structure simulation models. The validated models can then be used to generate new simulation data of MPEX material assessments for synthetic material compositions that have not been exposed in MPEX. These predictive simulations, plus the whole experimental dataset, will be used to train the MPEX Material Assessment AI Digital Twin allowing a rapid generative AI search for new materials with reduced PMI damage by interpolating the domain of the training set. These new optimum materials can be simulated with the physics codes and/or tested in MPEX. The ability of AI neural networks to interpolate multi-dimensional parameter spaces and generate virtual data is exploited for a more efficient search for optimum materials. The advent of the Transformational AI Models Consortium (TAIMC) is an opportunity to engage with state of the art private and public AI developers to achieve the goals of the AI digital twins and AI accelerated physics models proposed in this project. Our partners at ORNL from the Advance Scientific Computing Research (ASCR) organization will collaborate in accelerating the integrated plasma material interaction simulation framework. This simulation framework will provide a platform for generating simulation data across a range of physical fidelities, including hybrid methods that produce multi-fidelity results. This data will be leveraged for AI model development, both for generation of surrogates and the automation of simulation campaigns. A part of the research below will include collaborative efforts with the TAIMC to (i) adapt data storage approaches to ensure AI-readiness, (ii) provide a protypical exemplar to inform and exercise constructed workflows, and (iii) generate and share data, using the TAIMC unified AI data standard, for foundational models that will be trained from multiple sources across the DOE complex. We will also collaborate with the TAIMC, as well as the planned AI modeling teams, to develop approaches for reducing the cost of data generation. These include tailored multi-fidelity approaches as well as fine-tuning strategies to augment general, large-scale foundational models.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Y-12 National Security Complex Biological Monitoring and Abatement Program—2024 Calendar Year Report

This report provides the results of the CY 2024 sampling of East Fork Poplar Creek (EFPC) as part of the Y-12 National Security Complex (Y-12) Biological Monitoring and Abatement Program (BMAP). The results are presented in the context of historical trends. The Y-12 BMAP was developed in 1985 to demonstrate that the effluent limits established for Y-12 protected the classified uses of the receiving stream, particularly the growth and propagation of aquatic life (Loar et al. 1989). Over the years, the BMAP has become an important and valuable long-term measure of stream conditions resulting from actions and activities at the Y-12 Complex. The BMAP currently consists of three tasks: (1) bioaccumulation monitoring, (2) benthic macroinvertebrate community monitoring, and (3) fish community monitoring. The benthic macroinvertebrate community monitoring task includes studies to evaluate the receiving stream’s biological integrity annually in comparison with Tennessee Water Quality Criteria following Tennessee Department of Environment and Conservation (TDEC) protocols. In addition to presenting the EFPC biological monitoring results, this report includes results from Comprehensive Environmental Response, Compensation, and Liability Act–funded BMAP programs in Bear Creek and McCoy Branch (presented in Appendixes A and B, respectively), as required in the Y-12 National Pollutant Discharge Elimination System (NPDES) permit. Additional biological testing at the Y-12 Complex includes toxicity testing of select storm drains as required in the NPDES permit. Although toxicity testing is not formally part of the BMAP, toxicity testing results from 2024 are provided in Appendix C.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Building a High-Throughput MiniFuel PIE Pipeline for HFIR-Based Advanced Fuel Evaluation

MiniFuel irradiation experiments have become a key capability for accelerated evaluation of advanced and high-burnup nuclear fuels in the High Flux Isotope Reactor. As the number of irradiated MiniFuel targets entering postirradiation examination (PIE) has increased, improvements to the PIE workflow were needed to support more repeatable target disassembly, subcapsule processing, specimen recovery, and downstream measurements. This report summarizes FY 2026 improvements developed and implemented at the Irradiated Fuels Examination Laboratory to improve the MiniFuel target-to-specimen (T2S) workflow and related PIE activities.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Slicing Solutions for Wire Arc Additive Manufacturing

Both commercial and research applications of wire arc additive manufacturing (WAAM) have seen considerable growth in the additive manufacturing of metallic components. However, there remains a clear lack of a unified paradigm for toolpath generation when slicing parts for WAAM deposition. Existing toolpath generation options typically lack the appropriate features to account for all complexities of the WAAM process. This manuscript explores the key slicing challenges specific to toolpaths for WAAM geometry and pairs each consideration with multiple solutions to mitigate most negative effects on completed components. These challenges must be addressed to minimize voids, prevent bead collapse, and ensure deposited components accurately approximate the desired geometry. Slicing considerations are grouped into four general categories: geometric, process, thermal, and productivity. Geometric considerations are addressed with overhang compensation, corner-sharpening, and toolpath-smoothing features. Process considerations are addressed with start point configuration and controls for the bead lengths and end points. Thermal and productivity considerations are addressed with island optimization, multi-material printing, and connected insets. Finally, tools for the post-processing of generated G-code are explored. Overall, these solutions represent a critical set of slicing features used to improve generated toolpaths and the quality of the components deposited with those toolpaths.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Recycling Disassembled Automotive Plastic Components for New Vehicle Components: Enabling the Automotive Circular Economy

As the automotive industry increasingly relies on plastic components to meet fuel efficiency and emissions targets, the challenge of managing end-of-life vehicle (ELV) plastics continues to grow. Currently, more than 80% of ELV plastics in the U.S. are landfilled due to limited economic incentives and technical barriers to recycling. This study examines a mechanical recycling pathway for thermoplastic components disassembled from ELVs and assesses their usability for reintegration into new vehicle parts. Four representative materials were chosen based on material labels embedded in recovered parts and aligned with their virgin industrial equivalents: polypropylene (PP), 10% talc-filled PP (PP-T10), 20% talc-filled PP (PP-T20), and a 20% glass-/mineral-filled polyamide (PA6 + GF7 + MF13). The materials underwent shredding, drying, and injection molding before being characterized by particle size analysis, density measurement, thermal analysis (TGA, DSC), mechanical testing, and heat deflection temperature (HDT) evaluation. The results in this work indicated that minor differences in crystallinity were observed and small differences between model materials and ELV materials could have contributed to these changes. Mechanical testing revealed that neat polypropylene suffered a 15–20% reduction in stiffness and tensile strength, but talc-filled polypropylene and glass/mineral-filled nylon retained >90% of their modulus, strength, and heat deflection temperature values relative to virgin controls. Differences between virgin and ELV materials could have been attributed to use life degradation, contamination during use life, or even chemical/processing differences in model materials and ELV materials. However, these findings suggest that mechanically recycled, disassembled ELV plastics can retain sufficient structural performance to support circularity efforts in the automotive sector.

automotive recycling↗
DOE OSTI2025

Unveiling Atomistic Mechanisms Governing Additive Manufacturing Processability and Mechanical Behavior of a Refractory Complex Concentrated Alloy

Extending the concept of complex concentrated alloys (CCAs) to the refractory alloys (solidus temperature over 2000 °C) space potentially facilitates the design of lightweight structural alloys with service temperatures that exceed those of Ni and Co‐based alloys. However, the room and elevated temperature tensile properties of the current refractory‐CCAs (R‐CCAs) are inferior to those of the Ni/Co‐based alloys. Furthermore, the manufacturing scalability of R‐CCAs remains challenging, in that cracks are prevalent in all R‐CCAs when processed using near‐net shape manufacturing processes, such as fusion‐based additive manufacturing (F‐BAM). Still, mechanisms governing the poor F‐BAM processability of R‐CCAs remain unexplored. Here, to this end, this work unveils the atomistic mechanisms underlying F‐BAM process‐induced cracking in a NbTiTaMoHfZrC R‐CCA. The implications of light elements’ presence for intrinsic ductility and grain boundary cohesion, and subsequently for F‐BAM processability and mechanical behavior, are revealed. Leveraging the insights, we accomplish what is, to the best of the knowledge, the first instance of crack‐free F‐BAM processing of any R‐CCA. Additionally, the R‐CCA exhibits over 20% tensile ductility and ≈160 MPa tensile yield strength at 1200 °C. In addition to facilitating the design of lightweight R‐CCAs, findings enable scalable manufacturing of these ultra‐high temperature alloys for structural applications.

Refractory alloys↗
DOE OSTI2025

Binder Effects on Processing, Mechanical Properties, and Performance of Thin Sulfide Solid‐State Electrolytes

All‐solid‐state batteries (ASSBs) offer enhanced safety and energy density compared to conventional lithium‐ion batteries by replacing flammable liquid electrolytes with solid‐state electrolytes (SSEs). Among SSEs, sulfide‐based electrolytes exhibit high ionic conductivity and mechanical deformability, making them promising candidates for next‐generation energy storage. However, their practical implementation is hindered by interfacial instability, mechanical brittleness, and challenges in fabricating ultrathin electrolyte membranes (<30 μm) with robust mechanical integrity. Here, this study systematically examines the influence of polymeric binders—polyisobutylene, hydrogenated nitrile butadiene rubber, and styrene–ethylene–butylene–styrene (SEBS)—on the structural, mechanical, and electrochemical performance of thin sulfide SSE membranes. Key findings reveal that SEBS enables the fabrication of ultrathin, uniform membranes, while binder elasticity significantly affects structural stability during cycling. Operando stack pressure measurements indicate that binder properties directly influence adhesion force for LPSCl particles, influencing their stabilizing cycling period. These results underscore the critical role of polymer binders beyond mechanical reinforcement, positioning them as essential design variables in sulfide SSE engineering. By linking binder chemistry to processability and electrochemical performance, this study provides insights into optimizing sulfide SSEs, advancing their commercial viability in ASSBs.

argyrodite sulfide electrolyte↗
DOE OSTI2026

Reaction Optimization for Enzymatic Deconstruction of Industrially Relevant Nylon Composites

Plastics such as polyamides (PAs) possess unique physicochemical properties that make them indispensable in modern society. However, their energy‐intensive production and challenging end‐of‐life management highlight the urgent need for efficient recycling or remanufacturing solutions. Enzymatic depolymerization offers a promising route toward circular recycling, yet remains constrained by limited enzyme characterization, lack of validation under industrially relevant conditions and substrates, and overall performance. Here, we optimized the reaction conditions for three recently discovered nylon‐degrading enzymes. One of them, Nyl12, achieved product titers with PA6 and PA66 that exceed previously reported values, without enzyme engineering or substrate pretreatment. We further demonstrated the scalability of the process and its application to complex PA‐based materials used in microelectronic components. Analysis of substrate features, including surface area and particle size, revealed key parameters governing enzymatic activity and provided a framework for future pretreatment and process optimization efforts. In combination, these efforts provide a new benchmark for enzymatic nylon recycling.

nylon↗
DOE OSTI2025

Reciprocal Ternary Molten Salts Enable the Direct Upcycling of Spent Lithium‐Nickel‐Manganese‐Cobalt Oxide (NMC) Mixtures to Make NMC 622

Cathode active material is the most valuable component of spent lithium‐ion batteries, accounting for ≈30% of their overall value. Direct recycling of cathode materials involves recovering, regenerating, and reusing them without breaking down their chemical structure. This approach maximizes the added value of the cathode compound and reduces manufacturing costs by avoiding the need for virgin material production. However, one key challenge in scaling direct recycling from lab to industry is the requirement for highly purified cathode materials, contrasting with the low purity of black mass generated from battery shredding. No efficient separation process currently exists to isolate different lithium‐nickel‐manganese‐cobalt oxides (NMCs) from each other. Thus, direct recycling technologies that can operate with mixtures of multiple NMC stoichiometries will be best‐suited for industrial adoption. This study explores the direct recycling of NMC mixtures into NMC 622 using a “reciprocal ternary molten salts (RTMS)” system. Ionothermal relithiation and upcycling within the RTMS system successfully restore the layered structure, lithium content, and electrochemical performance of degraded NMCs, yielding results comparable to pristine NMC 622 (P‐NMC 622).

25 ENERGY STORAGE↗
DOE OSTI2025

Closed‐Loop Recyclable Vitrimer Plastics from PET Waste: A Design for Circularity

Plastics are essential to modern society, but their low recycling rates and inefficient end-of-life management pose a significant environmental challenge. Herein, the efficient strategy for upcycling postconsumer poly(ethylene terephthalate) (PET) waste into robust, closed-loop recyclable vitrimer plastics and composites is presented to address this issue. The catalyst-free aminolysis utilizes readily available amines to deconstruct diverse PET wastes into macromonomers, which are upcycled into vitrimers, exhibiting superior mechanical properties and exceeding the ultimate tensile stress and Young's Modulus of virgin PET by 80% and 150% respectively. These vitrimers exhibit excellent healability, shape memory, thermal reprocessability, and closed-loop chemical recyclability, enabling quantitative macromonomer recovery even from mixed plastic waste streams and glass/carbon fiber reinforced vitrimer (G/CFRV) composites. Furthermore, the vitrimer resin yields robust GFRV and CFRV composites with tensile strengths exceeding those of traditional epoxy composites by 100% and 80%, respectively, while maintaining complete chemical recyclability of both constituent materials. A preliminary technoeconomic analysis confirms the costeffectiveness and competitiveness of the facile PET deconstruction approach, which is potentially adaptable to other condensation polymers. Further, this study presents a facile approach to upcycling plastic waste into circular plastics and composites, offering a sustainable solution to global plastic waste management and fostering a circular economy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Hierarchically Structured Vitrimer Biocomposites for Sustainable Manufacturing

Polymers containing dynamic covalent bonds (DCBs) exhibit thermoplastic-like flow above their topology freezing temperature (T v ) while maintaining thermoset-like properties below it, making them promising for sustainable manufacturing. However, their large-scale adoption remains limited due to challenges in accurately determining T v and achieving efficient fiber-matrix bonding in composite applications. Here, hierarchically structured epoxy-anhydride-based polyester vitrimer composites reinforced with cellulosic filaments is demonstrated, where hydroxyl groups on fiber surfaces participate directly in transesterification with the matrix. Further, this dynamic interfacial bonding delivers exceptional mechanical properties, including ≈70 MPa shear strength and >10% strain-to-failure, while enabling thermal malleability. Using a combination of nuclear magnetic resonance and nano-infrared spectroscopies, direct evidence is provided that chemical bond exchange begins well below the conventionally measured T v , supporting the hypothesis that rheologically determined T v reflects a combination of chemical exchange and frictional dynamics rather than a discrete transition. The composites demonstrate excellent processability through vacuum-assisted resin transfer molding and maintain >90% of their mechanical properties after multiple thermal reforming cycles. These findings advance both the fundamental understanding of vitrimeric transitions and the practical development of sustainable, high-performance composite materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Adiabatic quantum support vector machines

Adiabatic quantum computers can solve difficult optimization problems (e.g., the quadratic unconstrained binary optimization problem), and they seem well suited to train machine learning models. In this paper, we describe an adiabatic quantum approach for training support vector machines. We show that the time complexity of our quantum approach is an order of magnitude better than the classical approach. Next, we compare the test accuracy of our quantum approach against a classical approach that uses the Scikit-learn library in Python across five benchmark datasets (Iris, Wisconsin Breast Cancer (WBC), Wine, Digits, and Lambeq). We show that our quantum approach obtains accuracies on par with the classical approach. Finally, we perform a scalability study in which we compute the total training times of the quantum approach and the classical approach with an increasing number of features and an increasing number of data points in the training dataset. In conclusion, our scalability results show that the quantum approach obtains a 3.5–4.5x speedup over the classical approach on datasets with many (millions of) features.

Computational Complexity↗
DOE OSTI2025

Material extrusion with integrated compression molding of NdFeB/SmFeN nylon bonded magnets using small- and large-scale pellet-based 3D-printers

High-density bonded rare-earth magnets are manufactured using pellet-fed additive manufacturing (AM)/material extrusion and an integrated additive manufacturing-compression molding (AM-CM) process. Neodymium iron boron – samarium iron nitride in polyamide 12 (NdFeB-SmFeN/PA12) of 93 % weight fraction (65 % volume fraction) are used for the study. The mechanical properties (tensile strength and modulus), magnetic properties (maximum energy density, coercivity, remanence) are reported. Manufacturing parameters such as layer height, barrel temperatures, screw speed and gantry feed rate are optimized to obtain the highest possible density of the magnets using a small-scale desktop material extrusion printer. Large scale integrated additive manufacturing-compression molding (AM-CM) is then utilized to increase the density of the magnets by reducing porosity defects common in the material extrusion process. The density of as-printed magnets was 5.2 g/cm 3 with a BH max value of 124.14 kJ/m 3 , tensile strength of 20 MPa and a modulus of 2 GPa. AM-CM increased the density of the compound by 5.5 % (5.49 g/cm 3 ). The reduction in porosity was confirmed using X-ray tomography (XCT). Improvement in mechanical strength of the material was also observed, with an increase in tensile strength of 25 % (25.09 MPa) and increase in tensile modulus of 275 % (5.49 GPa). Scanning electron microscopy showed increased particle-matrix adhesion with the integrated AM-CM process.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Influence of extreme temperature conditions on CO 2 direct air capture using amino-acid solutions

Geological features play a pivotal role in determining the feasibility of deploying CO₂ direct air capture (DAC) technologies, primarily because they influence the availability of cost-effective energy sources, such as natural gas and geothermal energy, and also due to the potential for CO₂ sequestration. Many regions face challenges due to variable weather conditions including seasonal temperature fluctuations, high or low humidity, and sub-ambient temperatures. These extremes can reduce DAC performance or even lead to catastrophic events. Aqueous solvents considered for DAC systems are particularly vulnerable to seasonal variations in colder climates, where the solvent may underperform or freeze. It is therefore essential to investigate the CO₂ capture efficiency of aqueous solvents across a broad range of environmental temperatures, spanning sub-zero to hot conditions (>30 °C). In this study, DAC operation is examined using a high-flux solvent–air crossflow contactor under two major weather scenarios: (i) cold conditions below 0 °C and (ii) hot conditions above 30 °C. A parametric study is conducted to investigate the contactor performance regarding CO₂ removal efficiency, uptake capacity, and reaction kinetics versus temperature when the air velocity through the contactor exceeds 1 m/s. The efficacy of the contactor is systematically investigated using various anti-freeze amino-acid solvent formulations. A mass-transfer mechanistic model is developed to assess the process performance over a wide temperature range and propose scalable design guidelines. Machine learning is also employed to identify key parameters affecting the CO₂ capture efficiency. It is shown that air velocity and temperature are the primary factors influencing CO₂ uptake. Based on performance data obtained under subfreezing temperatures, a technoeconomic analysis is conducted to evaluate the feasibility of using aqueous solvents in seasonal cold regions. In conclusion, the findings of this study provide valuable insights into siting considerations for deploying solvent-based DAC, thereby contributing to the advancement of sustainable carbon removal solutions.

Air–liquid contactor↗