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At least 289 records · Page 16

The Role of Low-Carbon Fuels and Carbon Capture in Decarbonizing the U.S. Clinker Manufacturing for Cement Production: CO2 Emissions Reduction Potentials

Low-carbon fuels, feedstocks, and energy sources can play a vital role in the decarbonization of clinker production in cement manufacturing. Fuel switching with renewable natural gas, green hydrogen, and biomass can provide a low-carbon energy source for the high-temperature process heat during the pyroprocessing steps of clinker production. However, up to 60% of CO2 emissions from clinker production are attributable to process-related CO2 emissions, which will need the simultaneous implementation of other decarbonization technologies, such as carbon capture. To evaluate the potential of fuel switching and carbon capture technologies in decarbonizing the cement industry, a study of the facility-level CO2 emissions is necessary. This study evaluates the potential for using a single low-carbon fuel as an energy source in clinker production for cement manufacturing compared to conventional clinker production (which uses a range of fuel mixes). In addition, conventional carbon capture (operated with natural gas-based steam for solvent regeneration) and electrified carbon capture configurations were designed and assessed for net-zero emission targets. Carbon emissions reductions with and without biogenic emissions credits were analyzed to ascertain their impact on the overall carbon accounting. Results show that carbon emissions intensity of cement can vary from 571 to 784 kgCO2eq/metric ton of cement without carbon capture and from 166.33 to 438.66 kgCO2eq/metric ton of cement with carbon capture. We find that when biogenic carbon credits are considered, cement production with a sustainably grown biomass as fuel source coupled with conventional carbon capture can lead to a net-negative emission cement (−271 kgCO2eq/metric ton of cement), outperforming an electrified capture design (35 kgCO2eq/metric ton of cement). The carbon accounting for the Scope 1, 2, and biogenic emissions conducted in this study is aimed at helping researchers and industry partners in the cement and concrete sector make an informed decision on the choice of fuel and decarbonization strategy to adopt.

42 ENGINEERING↗

Microchannel-based Membrane-less Extraction of Li from Unconventional Lithium Sources & the Separation of REE

This final report provides an overview of the Project's entire duration, covering July 1, 2021 to December 31, 2023. It primarily focuses on the achievements, technological developments, and unique challenges the team faced while working on separating and extracting Lithium from produced waters. The project's primary aim was to create an integrated, high-throughput, membrane-less, and modular microfluidic platform that could extract Lithium from unconventional sources. We have successfully met all goals and milestones envisioned in the SOPO document. The most critical primary milestones, including the Go-No-Go milestone (refer to the Gantt chart in the Appendices), were successfully accomplished. We demonstrated phase separation (>90%) and extraction (>85%) performance in the MPSE using synthetic, and representative produced water composition feed at 50 ml/min total flow through MPSE 36. We have also performed a parametric study of the MPSE operations, beyond the scope of SOPO, exploring operating conditions of current and broader interest. The extended investigation of operational parameters is concurrent with our efforts to seek further development of the MPSE technology beyond the scope of the Project. Along these lines of development, we have made efforts to be responsive to DOE calls for technological developments of other types of resources (beyond PW) for the recovery of Critical Materials and higher TRL development (beyond TRL 4). During the work on this Project, we developed and implemented three innovative technical approaches that emerged from our efforts to successfully meet the Project milestones. The innovative & original technical approaches developed and implemented in this Project are now the contributions to process engineering that could be clearly credited to the Project. First, Convergent Design Approach is a comprehensive feedforward & feedback loop of four design phases: i) design for functionality, ii) design for manufacturing, iii) design for sustainability, and iv) design for market. Next was Process Intensification. A major aim of this Project was to create an innovative phase separation & extraction microscale-based technology for Li separation – thus the words microchannel-based in the Project title. A microscale-based technology is intrinsically in the center of the Process Intensification domain as defined by its unique principles. Therefore, Process Intensification was implicitly envisioned in the Project’s SOPO. Lastly, Time Scale Analysis is a novel tool for discovering the needs and directions of Process Intensification implementations in any process technology. This Project is fully credited for developing and implementing the three novel technical approaches mentioned above. These are general contributions to process engineering that emerged from this Project. Beyond the original SOPO scope, the OSU-U.Pitt research group utilized a Convergent Design methodology, integrating first-principles mathematical modeling with experimental validation on the Minimum Development Vehicle. By creating these Digital Twins, the team rapidly assessed manufacturing iterations to support TEA analysis. This framework further enabled the development of advanced Surface Modification Techniques, where hydrophobic and oleophobic coating strategies were optimized via Digital Twin tools and validated through rigorous 100-hour longevity testing. TEA Analysis: The closing efforts of this Project were focused on the TEA analysis. TEA analysis had two primary functions: i) enabling critical assessments of design variations withing 10 the Concurrent Design Approach, thus enabling evolution of the MPSE design to reach faster- better-cheaper alternatives; and ii) to create a bridge between the accomplishments of this Project and future projects of higher TRL, beyond TRL 6 level. It is important to note that the TEA model created in the Project stirred the technological solutions for the recovery of critical materials toward a vision of a very profitable modular plant that has unique zero-waste water discharge signature. More importantly, thanks to our experimental performance data and conservative assumptions, the TEA model predicts minimal technological and investment risks. Low cost of a modular unit of a nominal capacity of [1000 tons of Li 2 CO 3 /year] positions the MPSE based technology within the reach of community investors, thus offering a paradigm shift in the development of critical technologies. The project successfully navigated two primary challenges: solvent selection and manufacturing adaptation. Restricted by the SOPO to existing literature for lithium recovery, the team identified a critical need for a "material excellence program" to develop next-generation solvents, eventually concluding with a preliminary investigation into promising Ionic Liquids (ILs). Simultaneously, COVID-19 supply chain disruptions forced a pivot from traditional manufacturing to advanced additive methods at ATAMI-OSU. By transitioning from stainless steel to 3D-printed polymer substrates, the team achieved a transformative three-order-of- magnitude reduction in manufacturing costs and compressed prototyping timelines from several months to just two days. The MPSE technology offers significant energy, environmental, and economic advantages by overcoming the traditional bottlenecks of phase-separation hardware and contactor size. Unlike conventional mixer-settlers or membrane-based systems, MPSE operates without moving parts or fouling-prone membranes, achieving robust performance even with challenging, viscous, or particulate-heavy feeds. Key performance metrics include an energy intensity reduction of 5–50x (3–40 kJ/m 3 ) compared to incumbent technologies and a dramatic reduction of processing time to under 60 seconds, which drastically reduces the physical plant footprint. These technical efficiencies translate into superior economic outcomes; for a 100 t/year Li 2 CO 3 facility, implementing MPSE is projected to nearly halve contactor CAPEX (from $\$$6.08M to $\$$3.01M) and significantly increase the project's Net Present Value (NPV), derisking new investment and enabling distributed critical-mineral processing configurations. The commercialization of MPSE technology is being spearheaded by Vigsur Dynamics Inc., which has adopted a structured, parallel approach to technical and business development since its formation in January 2026. Following extensive customer discovery and engagement with the Oregon State University accelerator, Vigsur Dynamics is working to establish a business model that transitions from pilot demonstrations to modular hardware sales, ultimately aiming for a "build-own-operate" service strategy. Current technical milestones—including 100 hours of continuous operation, superior energy efficiency, and successful 6-unit modular scale-up— provide a foundation for this transition. Backed by ongoing IP licensing and a growing network of industrial and venture advisors, the company is actively de-risking the platform to replace conventional mixer-settler systems in the critical minerals market.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Bias Corrected NOAA HRRR Wind Resource Data for Grid Integration Applications

To address the need for regularly updated wind resource data, NREL has processed the High-Resolution Rapid Refresh (HRRR) outputs for use in grid integration modeling. The HRRR is an hourly-updated operational forecast product produced by the National Oceanic and Atmospheric Administration (NOAA) (Dowell et al., 2022). Several barriers have prevented the HRRR's widespread proliferation in the wind energy industry: missing timesteps (prior to 2019), challenging file format for wind energy analysis, limited vertical height resolution, and negative bias versus legacy WIND Toolkit data (2007-2013). NREL has applied re-gridding, interpolation, and bias-correction to the native HRRR data to overcome these limitations. This results in the now-publicly-available bias corrected and interpolated HRRR (BC-HRRR) dataset for weather years 2015 to 2023. Bias correction is necessary for wind resource consistency across weather years to be used simultaneously in planning-focused grid integration studies alongside the original WIND Toolkit data. We show that quantile mapping with the WIND Toolkit as a historical baseline is an effective method for bias correcting the interpolated HRRR data: the BC-HRRR has reduced mean bias versus comparable gridded wind resource datasets (+0.12 m/s versus Vortex) and has very low mean bias versus ground measurement stations (+0.01 m/s) (Buster et al., 2024). BC-HRRR's consistency with the legacy WIND Toolkit allows NREL to extend grid integration analysis to 15+ weather years of wind data with low-overhead extensibility to future years as they are made available by NOAA. As with historical datasets like the WIND Toolkit, BC-HRRR is intended for use in grid integration modeling (e.g., capacity expansion, production cost, and resource adequacy modeling) both independently and alongside the legacy WIND Toolkit.

Array↗

EvoDiffMol: evolutionary diffusion framework for 3D molecular design with optimized properties

Designing molecules with specific target properties remains a fundamental challenge in computational chemistry. While existing approaches show promise, most rely on simplified representations like SMILES strings or 2D graphs that lack essential three-dimensional geometric information. We present EvoDiffMol, a computational framework that integrates evolutionary algorithms with three-dimensional diffusion models for property-driven molecular generation. The method operates through adaptive evolutionary optimization, where population-based selection guides the generation process toward desired property landscapes. EvoDiffMol supports both unconstrained molecular design and scaffold-constrained generation that preserves fixed substructures while optimizing complementary regions. Comprehensive evaluation demonstrates exceptional performance, achieving the highest drug-likeness score (0.94) among all compared state-of-the-art methods while maintaining excellent validity, uniqueness, and novelty. Beyond single property optimization, the framework demonstrates flexible multi-property optimization capabilities, simultaneously controlling multiple molecular descriptors including synthetic accessibility, lipophilicity, topological polar surface area, and clinically relevant ADMET properties such as cardiotoxicity (hERG) and intestinal permeability (Caco-2). This adaptability spans from simple descriptors to practical pharmaceutical endpoints without requiring complete model retraining. The framework achieves precise control over target property values, generating molecules with properties closely matching specified targets for both single and multiple descriptors. Scaffold-constrained experiments preserve fixed molecular cores while maintaining effective property optimization. The three-dimensional representation offers advantages in maintaining structural validity during iterative optimization, with potential for geometry-aware applications in materials science and drug discovery.

3D molecular generation↗

Extraction of Vibration Data with Imaging

To date, the primary sensing technology used to measure the vibration response has been accelerometers and strain gages mounted directly to the structure and using either wired or, more recently, wireless telemetry. Cost issues with these sensors and the associated data acquisition systems typically limit the numbers that are deployed on in situ structures. Although there are a few structures with larger sensing counts that in some cases exceed over 1000 sensors, more typical numbers range from ten to one hundred sensors resulting in low spatial resolution when they are applied to physically large systems. When one considers that nuclear power plant structures usually have complex geometries, material properties, connectivity and boundary conditions, it is clear these current approaches to vibration measurements can only provide limited information about a system’s dynamics response characteristics. As an alternative, many non-contact measurement technologies have emerged, including point wise measurement methods such as Global Positioning System (GPS), microwave interferometry, and laser Doppler vibrometry (LDV), as well as simultaneous full-field measurement methods such as electronic speckle pattern interferometry, holography interferometry, and muon tomography, some of which can provide high spatial resolution measurements. Among these methods, digital video imaging techniques have emerged as a feasible solution for full-field vibration measurements that provide significantly more detailed dynamic response information because every pixel becomes a measurement point. Furthermore, recent advances in image processing and computer vision algorithms have been successfully used to process video data for experimental and operational modal analysis. Such full-field measurements have the potential to significantly improve many current structural assessment procedures including system identification (modal parameter estimation), structural health monitoring, load reconstruction, model validation, and model updating. Furthermore, more recent full-field imaging techniques can be accomplished with relatively low-cost, commercially-available off-the-shelf cameras. However, these measurement procedures have other limitations that must be considered such as the ability to only measure visibly accessible points on a structure and a more limited dynamic range and bandwidth than can be achieved with accelerometers or strain gages.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Primer to SWIFt 2.0 Technical Information Sheets

More than 16,000 publicly owned municipal wastewater treatment plants (WWTPs) in the U.S. treat a wide range of wastewater (WW) flows ranging from <0.5 to >200 MGD. Municipal WWTPs act as the last barrier before exposure to water-borne diseases and contaminants, thus serving as a critical infrastructure protecting human health and the environment. A recent survey by the American Society of Civil Engineers assigned the U.S.’s WW infrastructure a grade of D+ because of the number of improvements needed for end-of-life infrastructure with operating conditions being over or under design capacities. With increasing population growth and urbanization, the municipal WW sector needs to grow resiliently and sustainably to accommodate increasing sewer flows in the wake of new infrastructure needs and global priorities. In addition, this growth will be affected by rising concerns over constrained resources (e.g., electricity, energy, and water) and regulations. This necessitates molding the WW sector toward sustainability- and resiliency-related planning and innovations to address current and future needs while simultaneously producing profitable by-products.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

In Situ High-Temperature Ultrafast Electron Diffraction through Integrated Furnace and MEMS Platforms

Temperature fundamentally governs phase stability, defect evolution, and transport behavior in materials. Despite its central role, direct measurements of structural evolution at elevated temperatures on ultrafast timescales have remained limited. Here, we report the design, integration, and validation of 2 complementary in situ heating platforms that substantially extend the thermal operating range of ultrafast electron diffraction (UED). A compact furnace-type heating stage enables stable diffraction measurements from room temperature to 800 K with ±0.1 K stability under ultrahigh vacuum, achieved through multi-sensor feedback control, dual air-cooling channels, and a thermally isolated motion stage. In parallel, a microelectromechanical system (MEMS)-based heating platform provides rapid thermal response and access to extreme temperatures ≥1,373 K with ±0.1 K stability over hundreds-micrometer regions while supporting simultaneous electrical biasing for electrothermal coupling studies. Absolute temperature calibration is established using diffraction-based thermometry via aluminum lattice expansion and independently validated through in situ melting of bismuth thin films. UED measurements further reveal pronounced temperature-dependent nonequilibrium lattice dynamics in bismuth, including modifications to electron–phonon coupling and Debye–Waller behavior, as well as enhanced ultrafast diffuse scattering in aluminum at elevated temperatures. Together, these developments establish a practical framework for quantitative, time-resolved studies of temperature-driven kinetics and nonequilibrium structural dynamics under extreme thermal environments.

Bai, Qianqian [Chinese Academy of Sciences (CAS), ↗

Foam-insulated cryo-compressed hydrogen storage vessels for buses

Here, large reductions (40 % vs. compressed gaseous hydrogen vessels and 17 % vs. vacuum insulated cryo-compressed vessels) in hydrogen storage system cost are possible by operating buses with foam-insulated cryo-compressed hydrogen (CcH 2 ) vessels. Detailed thermodynamic analysis reveals that large size and rapid H 2 consumption in buses compensate for the poor performance of foam insulation (∼100 times more conductive than vacuum multilayer insulation), resulting in compact and inexpensive H 2 storage systems with sufficient H 2 capacity for the longest routes (500 km) while maintaining previously identified advantages of CcH 2 systems: increased autonomy, rapid high density refueling, and improved safety, while simultaneously avoiding vacuum insulation stability problems resulting from composite resin outgassing.

Cryo-compressed↗

Skewness-dependent moments of the pion GPD from nonlocal quark-bilinear correlators

We present lattice QCD calculations of the odd Mellin moments of pion valence-quark generalized parton distribution up to fifth order ⟨𝑥 4 ⟩ and for the skewness range [−0.33, 0] using operator product expansion of bilocal quark-bilinear operators. The calculations are performed on an ensemble with lattice spacing 𝑎 = 0.04 fm and valence pion mass 300 MeV, employing boosted pion states with momenta up to 2.428 GeV and momentum transfers reaching 2.748 GeV 2 . We employ ratio-scheme renormalization and next-to-leading logarithmic resummed perturbative matching. At zero skewness, our results are consistent with previous lattice studies. By combining matrix elements at multiple values of skewness and momentum transfer, skewness-dependent moments are obtained through simultaneous polynomiality-constrained fits.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Measurement of t -channel production of single top quarks and antiquarks in pp collisions at 13 TeV using the full ATLAS Run 2 data sample

The production of single top quarks and top antiquarks via the t-channel exchange of a virtual W boson is measured in proton-proton collisions at a centre-of-mass energy of 13 TeV at the LHC using 140 fb -1 of ATLAS data. The total cross-sections are determined to be σ(tq) = 137$^{+8}_{-8}$ pb and σ($\bar{t}q$) = 84$^{+6}_{-5}$ pb for top-quark and top-antiquark production, respectively. The combined cross-section is found to be σ(tq + $\bar{t}q$) = 221$^{+13}_{-13}$ pb and the cross-section ratio is R t = σ(tq) / σ($\bar{t}q$) = 1.636$^{+0.036}_{-0.034}$. The predictions at next-to-next-to-leading-order in quantum chromodynamics are in good agreement with these measurements. The predicted value of R t using different sets of parton distribution functions is compared with the measured value, demonstrating the potential to further constrain the functions when using this result in global fits. The measured cross-sections are interpreted in an effective field theory approach, setting limits at the 95% confidence level on the strength of a four-quark operator and an operator coupling the third quark generation to the Higgs boson doublet: -0.37 < C$^{3,1}_{Qq}$ /Λ 2 < 0.06 and -0.87 < C$^{3}_{ΦQ}$ / Λ 2 < 1.42. The constraint |V tb | > 0.95 at the 95% confdence level is derived from the measured value of σ(tq + $\bar{t}q$), assuming that the Wtb interaction is a left-handed weak coupling and that |V tb | $\gg$ |V td |, |V ts |. In a more general approach, pairs of CKM matrix elements involving top quarks are simultaneously constrained, leading to confdence contours in the corresponding two-dimensional parameter spaces.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

A holistic platform for accelerating sorbent-based carbon capture

Abstract Reducing carbon dioxide (CO 2 ) emissions urgently requires the large-scale deployment of carbon-capture technologies. These technologies must separate CO 2 from various sources and deliver it to different sinks 1,2 . The quest for optimal solutions for specific source–sink pairs is a complex, multi-objective challenge involving multiple stakeholders and depends on social, economic and regional contexts. Currently, research follows a sequential approach: chemists focus on materials design 3 and engineers on optimizing processes 4,5 , which are then operated at a scale that impacts the economy and the environment. Assessing these impacts, such as the greenhouse gas emissions over the plant’s lifetime, is typically one of the final steps 6 . Here we introduce the PrISMa (Process-Informed design of tailor-made Sorbent Materials) platform, which integrates materials, process design, techno-economics and life-cycle assessment. We compare more than 60 case studies capturing CO 2 from various sources in 5 global regions using different technologies. The platform simultaneously informs various stakeholders about the cost-effectiveness of technologies, process configurations and locations, reveals the molecular characteristics of the top-performing sorbents, and provides insights on environmental impacts, co-benefits and trade-offs. By uniting stakeholders at an early research stage, PrISMa accelerates carbon-capture technology development during this critical period as we aim for a net-zero world.

Science & Technology - Other Topics↗

In-situ sensor monitoring of multi-class gas porosity formation in laser powder bed fusion using convolutional neural network

In-situ monitoring of defect formation remains a significant challenge in the laser powder bed fusion (LPBF) process. Recent advances have enabled real-time defect detection with machine learning and in-situ sensing technologies; however, most studies focus on binary classification of keyhole pores, limiting nuanced multi-class pore differentiation and formation mechanisms. This work introduces a multi-class pore detection framework (no pore, small pores < 15 µm, and large pores > 15 µm) by leveraging photodiode sensor data alongside high-fidelity synchrotron X-ray imaging. The 15 µm threshold is selected to distinguish between two fundamentally different defect mechanisms, following the physical size-mechanism boundary established by prior high-resolution synchrotron X-ray characterization of Al6061 LPBF. Distinguishing these classes is critical because large keyhole pores are structurally detrimental, whereas small gas pores are often benign, requiring different process control strategies. Thermal emission monitoring data collected simultaneously with high-speed X-ray imaging at the Stanford Synchrotron Radiation Lightsource (SSRL), are correlated with subsurface melt pool dynamics to establish ground truth. Continuous Wavelet Transform (CWT) with optimized parameters converts the photodiode time-series signals into time–frequency images, facilitating feature extraction. Convolutional Neural Networks (CNN) are then applied for real-time multi-class pore classification in an average inference time of 1 ms per signal window. It achieves 79% accuracy and an Area Under the Receiver Operating Characteristic curve (AUC ROC) score of 0.89 with five-fold cross-validation. The results demonstrate that coupling CWT-based feature engineering with CNN architecture enables reliable multi-class pore detection in Al6061 builds using affordable in-situ sensors. This approach advances scalable and affordable quality assurance in additive manufacturing by moving beyond binary defect detection toward more nuanced classification of porosity mechanisms with in-situ sensors and machine learning.

Laser powder bed fusion, Multi-class pores, In-sit↗

The Urban Deployment Model: A Toolset for the Simulation and Performance Characterization of Radiation Detector Deployments in Urban Environments

Static and mobile radiation detectors can be deployed in urban environments for a range of nuclear security applications, including radiological source search-and-tracking scenarios. Modeling detector performance for such applications is challenging, as it does not depend solely on the detector capabilities themselves. Many factors must be taken into consideration, including specific source and background signatures, the topology and constraints of the deployment environment, the presence of nuisance sources, and whether detectors are mobile or static. When considering the simultaneous deployment of multiple, heterogeneous detectors, assessment of the system-wide performance requires the simulation of the individual detectors, and a system-level analysis of the detection performance. In radiological source search-and-tracking scenarios, performance is mostly dominated by the probability of encounter, which depends on the specifics of a given deployment, e.g., static vs. mobile detectors or a combination of both modalities, the number of detectors deployed, the dynamic vs. static setting of false alarm rates, and individual vs. networked operation. The Urban Deployment Model (UDM) toolset was specifically developed to cover the gap in the available generic frameworks for the simulation of radiation detector deployments at city scales. UDM provides a unified and modular framework to support the simulation and performance characterization of heterogeneous detector deployments in urban environments. This paper presents the key components along the UDM workflow.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

Variational Optical Phase Learning on a Continuous-Variable Quantum Compiler

Quantum process learning is a fundamental primitive that draws inspiration from machine learning with the goal of better studying the dynamics of quantum systems. One approach to quantum process learning is quantum compilation, whereby an analog quantum operation is digitized by compiling it into a series of basic gates. While there has been significant focus on quantum compiling for discrete-variable systems, the continuous-variable (CV) framework has received comparatively less attention. We present an experimental implementation of a CV quantum compiler that uses two-mode squeezed light to learn a Gaussian unitary operation. We demonstrate the compiler by learning a parameterized linear phase unitary through the use of target and control phase unitaries to demonstrate a factor of 5.4 increase in the precision of the phase estimation and a 3.6-fold acceleration in the time-to-solution metric when leveraging quantum resources. We further show how our approach can be extended to higher-dimensional compilation tasks. Our results are enabled by the tunable control of our cost landscape via variable squeezing, thus providing a critical framework to simultaneously increase precision and reduce time-to-solution.

97 MATHEMATICS AND COMPUTING↗

Intermediate Scale Test Platform Conceptual Design and Hybrid Resin Performance Evaluation Recommendations

Recent laboratory evaluations demonstrated that further testing of alternative hybrid resins is warranted for their potential use as part of the 200 West Area (200W) pump-and-treat (P&T) remedy. 200W P&T has been treating technetium (Tc) since 2012 and uranium (U) since 2015 via two separate ion exchange (IX) treatment units: a single treatment train (i.e., a three-vessel system) for the removal of uranium utilizing a gel strong base anion (SBA) exchange resin, Dowex 21K; and two parallel treatment trains for the removal technetium using a gel SBA resin, Purolite® A532E. While these resins have been removing these contaminants effectively, new hybrid resins can provide additional benefits of further optimizing the IX treatment unit capacities and addressing additional treatment needs (e.g., Cr(VI)) by removing multiple contaminants simultaneously and/or through specific design configurations. Some of these resins also demonstrated some level of removal for I-129 which would be significant for expansion of the P&T into the 200 East Area. This document provides design recommendations for an intermediate scale test platform (ISTP) to evaluate alternative hybrid IX resin performance under conditions approaching field scale and using 200W P&T process groundwater. Results from the ISTP will provide the technical basis required to inform alternative IX resin selection in future 200W P&T facility operations where the treatment of multiple contaminants of concern may be required.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

High‐Energy LiNiO 2 Li Metal Batteries Enabled by Hybrid Electrolyte Consisting of Ionic Liquid and Weakly Solvating Fluorinated Ether

Abstract In pursuit of the highest possible energy density, researchers shift their focus to the ultimate anode material, lithium metal (Li 0 ), and high‐capacity cathode materials with high nickel content (Ni > 80%). The combination of these aggressive electrodes presents unprecedented challenges to the electrolyte. Here, we report a hybrid electrolyte consisting of a highly fluorinated ionic liquid and a weakly solvating fluorinated ether, whose hybridization structure enables the reversible operation of a battery chemistry based on Li 0 and LiNiO 2 (Ni = 100%), delivering nearly theoretical capacity of the latter (up to 249 mAh g −1 ) for >300 cycles with retention of 78.6% and in absence of unwanted morphological changes in both electrodes. Extensive characterization assisted by molecular dynamic simulation and density functional theory calculations reveals the function of the fluorinated ether to be far more profound than simple dilution and viscosity reduction. Instead, it induces drastic changes in Li + ‐solvation environment, the consequence of which engenders simultaneous stabilization of electrode/electrolyte and interfacing via formation of respective interfacial chemistries. This study further unlocks fundamental knowledge underneath the prevailing “diluent strategy” that is extensively applied by the electrolyte researchers and opens more design space for the next‐generation electrolytes and interphases for these coveted battery chemistries.

25 ENERGY STORAGE↗

Productivity and cost of energy chipping with non-integrated harvesting systems in the Coastal Plain of the US south

Research from the 1980s–2010s suggested that integrated harvesting systems that harvest conventional products (e.g., sawtimber, pulpwood) and energy chips simultaneously were the most effective solution to produce energy chips in the US South. Alternatives, such as biomass-only systems, have important advantages in forest stands with low volumes of merchantable timber. The goal of this study was to estimate the productivity and cost of producing energy chips using non-integrated systems. Innovative chipping contractors using non-integrated systems were identified through contacts with procurement foresters responsible for purchasing energy chips. Elemental time-and-motion studies were conducted to estimate harvesting productivity on five operations, including one clearcut harvest and four first thinnings in overstocked stands. The hourly cost of equipment was estimated using the machine rate method. Cost per tonne was estimated by combining hourly productivity and hourly costs in a modified version of the Auburn Harvesting Analyzer. System productivity averaged 37 tonnes per scheduled machine hour (smh) and cut-and-haul costs averaged $33.86 t −1 (USD), which was comparable to previous estimates from integrated systems. In conclusion, this study suggests there are viable alternatives to integrated harvesting systems to produce energy chips, especially in stands with low volumes of merchantable timber.

09 BIOMASS FUELS↗

First operation of superconducting quantum bits as particle detectors

Transmon qubits are among the leading technologies for the development of future quantum computers. However these superconducting devices are sensitive to ionizing radiation, which reduces their coherence time and leads to correlated errors. This study represents the first quantitative estimation of cosmic rays and ambient radiation impact on transmon qubits. In the shielded underground facility at the Laboratori Nazionali del Gran Sasso (LNGS), errors induced by the interaction of a radioactive source were reconstructed with an efficiency of about 10%. In contrast, in the unshielded above-ground facility at the Fermi National Accelerator Laboratory (FNAL), cosmic and ambient radiation impacts were detected with an efficiency ranging from 10% to 20% by modifying the acquisition protocol. Lastly, the simultaneous readout of three transmons in coincidence was demonstrated, achieving an event reconstruction efficiency of 90% when the devices were illuminated with an LED.

Bonomo, Camilla [Rome U.; INFN, Rome]↗