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At least 19 records

Membrane-based solvent extraction for the recovery of rare earths from phosphate mining process streams

This study reports on the capture of rare earth elements (REEs) from phosphate industry process streams, including phosphoric acid (PA) sludge and phosphogypsum (PG), using a membrane solvent extraction (MSX) process. While MSX has been proven effective for a relatively concentrated feed, its effectiveness for dilute REEs solutions remains unexplored. Investigated PA-sludge and PG particles contain total REEs concentrations of ∼1100 and ∼320 ppm, respectively. Acid leaching, implemented to dissolve the REEs, significantly dilutes the REEs concentration to ∼210 ppm for PA-sludge leachate and ∼60 ppm for PG leachate. These low concentrations, compounded by the higher levels of non-REE ions and radioactive species, uranium (U) and thorium (Th), poses challenges to the MSX process. Here, we demonstrated that N,N,N′,N′-tetraoctyl-diglycolamide (TODGA) selectively binds REEs from a >3 M nitric-acid leachate while effectively rejecting U and Th. Concentrations of light REEs in strip solution were doubled compared to the feed, while heavy REEs were preferentially extracted. Furthermore, >99% purity gypsum, free of U and Th, was precipitated during the acid leaching process, aiding separation by removing significant amounts of non-REEs species (e.g., calcium) prior to the MSX process. Molecular simulations support the experimental data, suggesting preferential separation of heavy over light REEs. Based on these results, a cost-effective integrated process including pretreatment, acid leaching, MSX, and wastewater treatment is proposed for the co-recovery of REEs, phosphoric acid, gypsum, and U. This study shows MSX as a technically and economically feasible process for the recovery of REEs from low-concentration process streams, offering advantages over conventional solvent extraction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Rapid Sensing to Facilitate Purification of Rare Earth Element-Containing Process Streams Produced Through Membrane-Assisted Solvent Extraction

The development of an economically competitive domestic supply of rare earth elements and yttrium (REY) is necessary for our nation’s economic growth and national security. The achievement of a secure domestic supply of REY requires not only the development of effective processes for recovery of REY from naturally occurring materials and/or recycled products, but also the development of downstream processes for the ultimate production of high-REY content solids. An impediment to the development of such processes is the scarcity of analytical methods that provide rapid determination of the process stream compositions. In this work, a membrane-based extraction process was used to selectively recover REYs from a dilute solution in the presence of much higher concentrations of Ca and Al. In tandem, the use of a portable spectrometer equipped with an immobilized zinc adeninate benzene tricarboxylate metal-organic framework sensing material makes possible the rapid detection of the presence of ppm concentrations of Tb and Eu in both weakly acidic and strongly acidic process streams within minutes. A solvent extraction processing time of 15-60 min maximized REY selectivity over gangue ions while achieving up to 80% REY and minimal gangue ion recovery. Taken together, these experiments highlight not only an innovative method for REY purification but also the importance of inexpensive, portable characterization methods for near real-time analysis of REY content.

Membrane-assisted solvent extraction

Arroyo Stream Processing Toolset (arroyopy) v0.1.0

Processing event or streaming data presents several technological challenges. A variety of technologies are often used by scientific user facilities. ZMQ is used to stream data and messages in a peer-to-peer fashion. Message brokers like Kafka, Redis Pubsub, EPICS PVA and RabbitMQ are often employed to route and pass messages from instruments to processing workflows. Arroyopy provides an API and structure to flexibly integrate with these tools and incorporate arbitrarily complex processing workflows, letting the hooks to the workflow code be independent of the connection code and hence reusable at a variety of instruments.

Chavez Esparza, Tanny Andrea [Lawrence Berkeley Na

Analysis of NuCycle® Process Waste Streams and Identification of Candidate Waste Forms (CRADA 719) Abstract

The objective of this project is to support collaboration between PNNL and Curio to address technical gaps in the immobilization of waste streams generated by the NuCycle® process, thereby improving the overall viability of the technology. This work will be carried out in two phases, described below. Phase 1 – Waste Management Study The first phase consists of a comprehensive waste management study focused on the waste streams produced during the NuCycle® process, including those containing long lived fission products (LLFPs, e.g., I 129) and transuranic elements (TRUs). This phase involves compiling waste compositions and characteristics based on recently completed NuCycle® testing and modeling efforts. Established waste forms and processing methods will be identified for streams where they are applicable.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W

Hyporheic-zone Processes and Stream Oxygen Dynamics: Insights from a Multiscale Reactive Transport Model: Modeling Archive

This archive contains the data and Python scripts required to reproduce the analyses and figures in the study: Gomez-Velez, J. D., Rathore, S. S., Cohen, M. J., & Painter, S. L. (2025). Hyporheic-zone Processes and Stream Oxygen Dynamics: Insights from a Multiscale Reactive Transport Model. Submitted to Water Resources Research. The analysis utilizes the subgrid model Advection Dispersion Equation with Lagrangian Subgrids (ADELS) implemented in the Advanced Terrestrial Simulator (ATS; https://amanzi.github.io/ats/stable/). In this case, the ATS and Amanzi versions are (1) ATS version 1.5.1_f5ba18f8 and (2) Amanzi version 1.6-dev_53444cca4. The repository includes a Jupyter Notebook and the necessary data (Pandas DataFrames stored as pickle files) to generate the figures for the manuscript. Additionally, it contains Python scripts to create ATS input files, run the ATS simulations, and post-process the results. Finally, it provides routines for parameter estimation using the Single-Station Metabolism (SSM) model with the Differential Evolution Adaptive Metropolis (DREAM) Markov Chain Monte Carlo (MCMC) algorithm with ZS enhancements (DREAM-ZS).

54 ENVIRONMENTAL SCIENCES

Preliminary Testing of a Continuous Cryopump for Primary Fusion Device Pumping and Direct Internal Recycling

Here, the concept of directly recirculating fusion machine exhaust gas, bypassing the tritium plant, to make fuel pellets was proposed in the 1990s and later termed direct internal recycling (DIR). In the DIR concept, the residual fusion fuel in the machine exhaust stream is separated from impurities locally and diverted directly to the fueling systems, bypassing isotopic separation and other processing equipment, and therefore significantly reducing the required size of the fuel processing plant, reducing plant inventory, and thus increasing the economic viability of fusion as an energy source. One concept for DIR consists of a series of cryogenic pumps to separate the impurities from the machine exhaust gas using different triple point temperatures and saturation curves of exhaust constituents. In this concept, the plasma exhaust is initially passed through an impurity trap operating at ~25–30 K to desublimate impurities such as hydrocarbons, argon, oxygen, and nitrogen. The resulting process stream will consist of DT fuel and helium. The process stream is then pumped by a continuous cryopump known as a “snail pump.” This pump is a steady-state continuous cryopump that desublimates all remaining exhaust gas constituents while allowing helium, a byproduct of the fusion reaction, to pass through. The helium is pumped to the tritium plant for processing while the desublimated material is continuously scraped off, heated up, and transported to the fueling system. This article will present the cryogenic DIR concept and outline the design and operation of the snail pump, along with results from preliminary testing. Tests to assess pumping and separation efficiency found that at D2 flows below 50.7 Pa ⋅ m3/s with 1% helium, the pump is capable of pumping and separating the gas with a resulting DIR fraction of >99%, with no helium entrained in the primary fuel exhaust stream. The main limitation is due to the thermal performance of the cryogenic circuits of the pump, which will be addressed in future testing.

Gebhart III, Trey E. [Oak Ridge National Laborator

Rapid measurement of soluble xylo-oligomers using near-infrared spectroscopy (NIRS) and multivariate statistics: calibration model development and practical approaches to model optimization

Rapid monitoring of biomass conversion processes using techniques such as near-infrared (NIR) spectroscopy can be substantially quicker and less labor-, resource-, and energy-intensive than conventional measurement techniques such as gas or liquid chromatography (GC or LC) due to the lack of solvents and preparation methods, as well as removing the need to transfer samples to an external lab for analytical evaluation. The purpose of this study was to determine the feasibility of rapid monitoring of a biomass conversion process using NIR spectroscopy combined with multivariate statistical modeling, and to examine the impact of (1) subsetting the samples in the original dataset by process location and (2) reducing the spectral range used in the calibration model on model performance. We develop multivariate calibration models for the concentrations of soluble xylo-oligosaccharides (XOS), monomeric xylose, and total solids at multiple points in a biomass conversion process which produces and then purifies XOS compounds from sugar cane bagasse. A single model using samples from multiple locations in the process stream showed acceptable performance as measured by standard statistical measures. However, compared to the single model, we show that separate models built by segregating the calibration samples according to process location show improved performance. We also show that combining an understanding of the sample spectra with simple multivariate analysis tools can result in a calibration model with a substantially smaller spectral range that provides essentially equal performance to the full-range model. We demonstrate that real-time monitoring of soluble xylo-oligosaccharides (XOS), monomeric xylose, and total solids concentration at multiple points in a process stream using NIR spectroscopy coupled with multivariate statistics is feasible. Segregation of sample populations by process location improves model performance. Models using a reduced spectral range containing the most relevant spectral signatures show very similar performance to the full-range model, reinforcing the importance of performing robust exploratory data analysis before beginning multivariate modeling.

09 BIOMASS FUELS

Hyporheic‐Zone Processes and Stream Oxygen Dynamics: Insights From a Multiscale Reactive Transport Model

Aquatic ecosystem metabolism encapsulates the daily fixation (gross primary production, GPP d ) and mineralization (ecosystem respiration, ER d ) of organic carbon. In fluvial systems, these are commonly estimated by inverse solutions to field observations using a model that describes oxygen concentrations varying in the water column in response to metabolic fluxes and air‐water gas exchange controlled by a rate coefficient (K 600 ). The most common conceptual model is the single‐station metabolism (SSM) model. The simplicity and flexibility of this conceptualization make it attractive; however, it implicitly assumes that all the processes that consume oxygen in fluvial systems can be lumped into a bulk estimate of respiration with poorly understood consequences for estimates of GPP d , ER d , and K 600 . Here, we focus on the implications of using SSM conceptualization when estimating metabolic fluxes from oxygen dynamics in channels where hyporheic exchange occurs. We use a new multiscale numerical model for reactive transport in streams that represents hyporheic exchange and streambed heterotrophic respiration. Nondimensionalization of this model reveals dimensionless groups that collectively control oxygen dynamics. Numerical experiments offer a mechanistic understanding of the impacts of hyporheic exchange on diel oxygen dynamics revealing that potential biases arise from neglecting mass transfer limitations. Specifically, we found that hyporheic exchange significantly affects diel oxygen dynamics, even for nonreactive streambed sediments. Moreover, while the SSM performs well in many situations, we find conditions where significant bias is produced by hyporheic exchange, even when oxygen data are well‐fitted. These situations pose a major challenge in the interpretation of metabolism assessment estimates.

Gomez‐Velez, Jesus D. [Oak Ridge National Laborato

EJFAT Scientific Perspective

Presented new computing model to the test by deploying the EJFAT system alongside a data-stream processing framework running the production-level CLAS12 event reconstruction application. In this experiment, a continuous stream of CLAS12 Level-1 identified events was processed in real-time using the EJFAT load balancer, distributing the workload across 90 computing nodes located across the U.S. This marks the first-ever large-scale, real-time distributed data stream processing experiment, demonstrating that scientific data-streaming pipelines can efficiently scale across four dimensions, thanks to EJFAT’s advanced hardware and software capabilities.

Gyurjyan, Vardan [Thomas Jefferson National Accele

Rapid Characterization Tools for Process Optimization: Cooperative Research and Development (Final Report)

In this project Prenexus Health, Inc. (Prenexus) and NLR will develop rapid characterization tools to improve the Prenexus production process. First, we will develop a tool to predict the overall performance of the Prenexus manufacturing process converting high-fiber sugarcane to xylo-oligosaccharides (XOS) (both the overall process yield and the composition of the XOS product) using rapid characterization of the incoming feedstock and knowledge of key process parameters. This tool will dramatically increase Prenexus’ understanding of the overall process. Second, we will develop a tool to predict the concentration of soluble oligomeric and monomeric xylose and organic acids in multiple process streams at-line in the Prenexus process, enabling real-time process control of the conversion process.

09 BIOMASS FUELS

Deacetylation and Mechanical Refining Pathway for the Bioconversion of Sugarcane Bagasse

Advancing lignocellulose biorefining is imperative for the deployment of cellulosic (2G) biofuels. This work investigates the tailoring of the alkaline deacetylation and mechanical refining (DMR) pathway for the bioconversion of sugarcane bagasse. Experiments are conducted at laboratory and pilot scales, varying the pretreatment conditions (70–92 °C; 48–100 g NaOH /kg) and the mechanical refining technologies (PFI and disk refining). The pretreatments selectively solubilize acetyl groups (> 86%) and lignin (10–63%) while mostly preserving structural carbohydrates in the solid phase. Enzymatic hydrolysis generates hydrolysates of clean sugars (glucose and xylose), with sugar yields increasing up to 81% for glucose and 89% for xylose in response to delignification and mechanical refining. Biochemical methane potential assays reveal specific methane productions of up to 568 NmL CH₄ gVS⁻¹ for alkaline liquor monodigestion and 344 NmL CH₄ gVS⁻¹ for co-digestion with sugarcane vinasse from the conventional (1G) sugarcane ethanol, indicating a strong potential for bioenergy recovery from this process stream. Synergies are identified in integrating 1G ethanol, 2G DMR processing of bagasse, and anaerobic co-digestion of 1G vinasse and 2G DMR alkaline liquor. This technology enables sugarcane biorefineries to enhance the co-production of ethanol, methane, and concentrated streams of CO 2 .

09 BIOMASS FUELS

Overview of design developments for Condensable Vapor Devices for ITER

The Condensable Vapor Devices (CVDs), which are part of the ITER Roughing Pump System (RPS), are designed to separate tritiated water content to protect downstream pumps and transfer the water to Tokamak Exhaust Processing (TEP) systems for further separation. CVDs operate on the principle that a cooling fluid, such as liquid nitrogen, cools the exhaust gas stream (process gas) from the Tokamak, allowing the water present in the process gas to condense and freeze, thereby trapping it in the CVDs. The CVDs once saturated with the ice are then regenerated to release the trapped water molecules, which are sent to the TEP. The present article will describe the technical requirements, challenges, and design progress made so far in the development of the CVDs.

Choukekar, Ketan [ORNL] (ORCID:0009000288016383)

Computationally Guided and Experimentally Validated Design of Custom Chelators for Critical Mineral Recovery

Selective, high throughput separation of target critical metals from complex environments such as fly ash leachates and mining process streams presents a significant challenge for economical production. Custom chelators and sorbents are an attractive technology for selective metal extraction, however it can be difficult to predict their performance, and significant experimental efforts are often required to develop chelating technologies. Here, we present a computational strategy focused on modelling chelator-metal binding interactions and benchmark these results versus experimental data. A computational pipeline combining forcefield, semiempirical, and meta-GGA methods with a thermodynamic framework optimized for error cancellation has been developed to predict binding energies of chelator complexes towards critical mineral recovery applications. This approach, originally validated on [2.2.2] cryptates binding mono- and divalent cations, demonstrated robust predictive capabilities with an R2 of 0.850 against experimental aqueous binding energies. The workflow includes metadynamics for exploring high-dimensional potential energy surfaces and a cluster-continuum model for accurate yet computationally efficient solvation modeling. Error cancellation between solvation energies of free and chelator-coordinated ions enables faster convergence, even with finite cluster sizes. Initial studies on the cryptates revealed consistent metal-ligand coordination patterns, with systematic variations influenced by ion size and charge, highlighting key structural features linked to binding selectivity. Further studies of a proprietary chelator have resulted in identification of previously unreported selectivity towards economically significant metals, which in-house experiments have confirmed, demonstrating the feasibility of this approach. By applying this methodology to new chelators targeting critical minerals such as lithium, cobalt, nickel and other strategic metals, we aim to accelerate the discovery of next-generation chelators for efficient recovery, recycling, and separation processes. This computational framework serves as the backbone of a high-throughput design pipeline tailored for sustainable resource utilization and may be applied to a wide range of systems to meet experimental needs.

computational materials

Insights into Tetravalent Np Speciation in HNO 3 through Spectroelectrochemistry and Multivariate Analysis

In situ optical spectroscopy, spectropotentiometry, and multivariate analysis were applied to the Np(IV) nitrate system to better understand speciation and quantify HNO 3 concentration. Thin-layer spectropotentiometry, or spectroelectrochemistry, was leveraged to isolate and stabilize Np(IV) without compromising the solution conditions and generate representative Vis-NIR absorption spectra from 0.5 to 10 M HNO 3 and benchmark the corresponding Np(IV) molar absorptivity coefficients. Spectra were described with principal component analysis (PCA) to identify the purest Np(IV) absorbance spectra among other oxidation states [e.g., Np(V/VI)] at each acid concentration and then to identify the primary sources of variance within each Np(IV) spectrum with respect to Np(IV) nitrate complexes. Then, partial least-squares regression (PLSR) and support vector regression (SVR) models were built to predict HNO 3 concentration from the Np(IV) spectral data. The nonlinear SVR model outperformed the linear PLSR model for the HNO 3 concentration predictions. Finally, the inclusion of spectra collected in edge and center point HNO 3 concentrations in the calibration set was determined to be crucial for producing models with strong predictive capabilities. The multivariate approach used in this study makes it possible to quantify HNO 3 concentration solely based on Np(IV) absorption spectra, which is essential to quantifying processing streams in various online monitoring applications.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA

Effects of Recovery Conditions and Aggregation Mechanisms on the Chemical and Physical Properties of Hybrid Poplar and Corn Stover Lignins

Heterogeneity in the physical properties and processing behavior of lignins recovered from biorefining process streams can hinder their effective utilization and industrial valorization. This work investigates lignin recovery by acidification from alkaline pretreatment liquors of varying sources (corn stover and hybrid poplar), compositions, solid contents, and incubation temperatures prior to filtration. Recovered lignins were characterized for filtration performance, mass yield, chemical composition, particle size and morphology, and color. A transition temperature was identified corresponding to marked shifts in lignin physical properties and was a function of the solid content and liquor source. Filtration below this temperature yielded slow-filtering, dark, brittle lignins with smoother particle surfaces, whereas precipitation above this threshold yielded fast-filtering, lighter, powdery lignins with rougher particle surfaces. The impact of temperature and concentration on universal cluster aggregation mechanisms was proposed to explain the differences between lignin particle properties and filtration behavior.

Aggregation

Portable fiber optic sensor for rare earth elements and other critical metals using photoluminescence methods

Rare earth elements and other metals are vital to a range of technologies that are used in the energy and defense sectors. However, monopolistic market conditions have caused significant concern over the stability of the critical metal supply chain, and this has spurred extensive efforts in many nations to produce these metals domestically, both from conventional sources such as mining and well as from unconventional sources such as coal and its utilization byproducts. Slow and expensive characterization methods pose a significant barrier for both metals prospecting and process monitoring. A promising solution to this challenge is the development of highly sensitive luminescent sensors for metals, which can offer low costs, portability, and sensitivity. Anionic zinc adeninate metal-organic frameworks (BioMOFs) are known to distinguishing and detect part-per-billion levels of terbium, europium, samarium, and dysprosium in water by sensitizing the narrow, element-specific emission bands from these lanthanides. Here, a BioMOF material is immobilized onto a large diameter, solarization-resistant fiber optic tip integrated with a portable, low-cost spectrometer for rare earth element sensing. Immobilizing the sensing material on fiber instead of dispersing the sensing material in solution offers several advantages: it facilitates solvent removal, which enhances luminescent signal from the sensitized lanthanides, and it also allows the BioMOF to be recycled for multiple uses. The sensing system was deployed on a simulated process stream and exhibited qualitative agreement with inductively-coupled plasma mass spectrometry for terbium and europium detection, highlighting the potential for the sensing system to be deployed for real-world applications. By using different sensing materials, the same portable sensor may be deployed to detect other energy relevant metals such as cobalt, providing a cost-effective and sensitive platform for critical metal characterization.

Crawford, Scott

Net-Zero Lime Kiln and Carbon Removal Facility

The final scientific/technical report for DE-FE0032248. The Project Objective for DE-FE0032248, Net-Zero Lime Kiln and Carbon Removal Facility, was to execute and complete the initial design of a commercial-scale, advanced carbon capture system that separates CO2 with at least 95% capture efficiency from process streams at the Carmeuse Kentucky (KY) lime plant that will be retrofitted to utilize sustainably sourced biomass (SSB) alone or in combination with natural gas, and/or coal, with at least a 20-year available feedstock supply and remaining asset life.

29 ENERGY PLANNING, POLICY, AND ECONOMY