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DOE OSTI2026

Hierarchical low Pt-loading “core-shell” electrocatalysts for the oxygen reduction reaction in fuel cells

The sluggish kinetics of the oxygen reduction reaction (ORR) hinder cost-effective polymer electrolyte fuel cells (PEFCs), which rely on scarce, expensive platinum-based electrocatalysts (ECs). Here, we present a novel synthesis method for ORR ECs achieving exceptional platinum utilization. The design features a hierarchical “multi-carbon” support comprising carbon nanoparticles interacting with graphene nanoplatelets as the “core”, encapsulated by a porous carbon nitride (CN) “shell”. This configuration promotes strong core/shell interactions and a bimodal active site distribution, consisting of chemically dispersed Pt and Ni single-atom complexes and PtNix alloy nanoclusters embedded in the CN shell. These advantages enable high activity and durability, achieving an ORR activity of 1.6 A mgPt−1 at 0.9 V vs. RHE-an order of magnitude higher than Pt/C (0.17 A mgPt−1). A proof-of-concept PEFC demonstrates a specific power of 12.0 kW gPt−1 at 0.60 V. This approach offers a significant step toward more efficient and sustainable PEFC technologies.

Pagot, Gioele [University of Padova, Italy]↗

DOE OSTI2020

Chemical Vapor Deposition for Atomically Dispersed and Nitrogen Coordinated Single Metal Site Catalysts

Abstract Atomically dispersed and nitrogen coordinated single metal sites (M‐N‐C, M=Fe, Co, Ni, Mn) are the popular platinum group‐metal (PGM)‐free catalysts for many electrochemical reactions. Traditional wet‐chemistry catalyst synthesis often requires complex procedures with unsatisfied reproducibility and scalability. Here, we report a facile chemical vapor deposition (CVD) strategy to synthesize the promising M‐N‐C catalysts. The deposition of gaseous 2‐methylimidazole onto M‐doped ZnO substrates, followed by an in situ thermal activation, effectively generated single metal sites well dispersed into porous carbon. In particular, an optimal CVD‐derived Fe‐N‐C catalyst exclusively contains atomically dispersed FeN 4 sites with increased Fe loading relative to other catalysts from wet‐chemistry synthesis. The catalyst exhibited outstanding oxygen‐reduction activity in acidic electrolytes, which was further studied in proton‐exchange membrane fuel cells with encouraging performance.

Liu, Shengwen↗

DOE OSTI2020

On the mechanical behavior of a Nb 3 Sn superconducting coil during a quench: Two-dimensional finite element analysis of a quench heater protected magnet

New high-field accelerator magnets based on $Nb_3Sn$ superconductors are pushing the boundaries of magnet design and quench protection towards new limits. While their large stored energies and current densities result in a very challenging scenario for magnet protection, their great electromagnetic forces create also new requirements in terms of magnet design and stress management techniques. Furthermore, the strain sensitivity of $Nb_3Sn$ cables turns the electro-mechanical limits of the conductor into a parameter of the highest importance, where conductor degradation becomes a critical aspect in magnet operation. The coupling of all the above-mentioned considerations during quench is a case of special interest that adds further complexity to the design of $Nb_3Sn$ magnets. The objective of this paper is to provide a complete two-dimensional investigation of the coil and magnet structure mechanics during a quench event. Here, the analysis is performed using a combination of finite element codes that provide the necessary input for the mechanical study. The core of the modelling strategy relies on a thermal-electric model, whose results are directly used as loads in the mechanical simulation. In doing so, the stress evolution during and after a quench is obtained. We focus for this time in the analysis of a quench heater protected magnet, where dynamic effects are of less importance in contrast to other protection systems like CLIQ.

43 PARTICLE ACCELERATORS↗

DOE OSTI2023

Off-policy deep reinforcement learning with automatic entropy adjustment for adaptive online grid emergency control

Electric overloading conditions and contingencies put modern power systems at risk of voltage collapse and blackouts. Load shedding is crucial to maintain voltage stability for grid emergency control. However, the rule- or model-based schemes rely on accurate dynamic system models and face considerable challenges in adapting to various operating conditions and uncertain event occurrences. Here, to address these issues, this paper proposes a novel deep reinforcement learning (DRL)-based voltage stability control algorithm with automatic entropy adjustment (AEA) for grid emergency control. Various dynamic network components for complex system operations are modeled to construct the DRL environment. An off-policy soft actor-critic architecture is developed to maximize the expected reward and policy entropy simultaneously. The AEA mechanism is proposed to facilitate the policy maximum entropy procedure, and the proposed method can automatically provide effective discrete and continuous actions against various fault scenarios. Our approach accomplishes high sampling efficiency, scalability, and auto-adaptivity of the control policies under high uncertainties. Comparative studies with the existing DRL-based control methods in IEEE benchmarks indicate salient performance improvement of the proposed method for dynamic system emergency control.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2018

Microfluidics Synthesis of Gene Silencing Cubosomes

The success of gene technologies hinges on our ability to engineer superior encapsulation and delivery vectors. Cubosomes are lipid-based nanoparticles where membranes, instead of enveloping into classic liposomes, intertwine into complex arrays of pores well-ordered in a cubic lattice. These complex nanoparticles encapsulate large contents of siRNA compared to a liposomal analogue. Importantly, the membranes that form cubosomes have intrinsic fusogenic properties that promote fast endosomal escape. Despite the great potential, traditional routes of forming cubosomes lead to particle sizes too large to fulfill the state-of-the art requirements of delivery vectors. To overcome this challenge, in this work we utilize a microfluidic nanomanufacturing device to synthesize cubosomes and siRNA-loaded cubosomes, termed cuboplexes. Utilizing cryogenic TEM and small angle X-ray scattering we elucidate the time-resolved mechanisms in which microfluidic devices allow the production of small cubosomes and cuboplexes (75 nm) that outperform commercially available delivery vectors, as well as liposome-based systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

RingX: Scalable Parallel Attention for Long-Context Learning on HPC

The attention mechanism has become foundational for remarkable AI breakthroughs since the introduction of the Transformer, driving the demand for increasingly longer context to power frontier models such as large-scale reasoning language models and high-resolution image/video generators. However, its quadratic computational and memory complexities present substantial challenges. Current state-of-the-art parallel attention methods, such as ring attention, are widely adopted for long-context training but utilize a point-to-point communication strategy that fails to fully exploit the capabilities of modern HPC network architectures. In this work, we propose ringX, a scalable family of parallel attention methods optimized explicitly for HPC systems. By enhancing workload partitioning, refining communication patterns, and improving load balancing, ringX achieves up to 3.4 × speedup compared to conventional ring attention on the Frontier supercomputer. Optimized for both bi-directional and causal attention mechanisms, ringX demonstrates its effectiveness through training benchmarks of a Vision Transformer (ViT) on a climate dataset and a Generative Pre-Trained Transformer (GPT) model, Llama3 8B. Our method attains an end-to-end training speedup of approximately 1.5 × in both scenarios. To our knowledge, the achieved 38% model FLOPs utilization (MFU) for training Llama3 8B with a 1M-token sequence length on 4,096 GPUs represents one of the highest training efficiencies reported for long-context learning on HPC systems. Our code implementation is available at https://github.com/jqyin/ringX-attention.

Yin, Junqi [ORNL] (ORCID:0000000338435520)↗

DOE OSTI2019

Development of a Planar Focusing Collector for CSP

In the field of the concentrating solar power (CSP) technology, the parabolic trough is a common choice for a solar collector. Parabolic troughs are highly reflective curved mirrors that take incident sunlight and focus it onto a line-shaped receiver that runs down the center of troughs. The receivers are generally heat-absorbing pipes containing a heat transfer fluid that delivers the collected thermal energy to steam turbines or engines for generating electricity. However, parabolic troughs are constrained by wind loads and cost of materials and support structure. The goal of this project was to develop a planar focusing collector (PFC) that would serve as an alternative to the parabolic trough. An ideal PFC is ultrathin (less than a few microns) and lightweight, and could be manufactured in a manner that is scalable and low cost. Furthermore, these features would be attractive to CSP technology because of the potential to reduce cost and complexity of installation and maintenance. The work pursued in this project attempted to actualize the PFC concept by utilizing advances in the emerging area of metasurfaces, which rely on the nanopatterning of surfaces to control the amplitude and phase of light at length scales smaller than an optical wavelength. Academic pursuits of metasurface technology predominately employ electron-beam lithography (EBL) for fabrication because the technique offers highly reliable nanopatterning of surfaces with a spatial resolution of ~10 nm. However, due to the techno-economic constraints of the DOE’s SunShot program, particularly cost-effective scalability, the use of EBL was avoided in this project. Rather, fabrication approaches that lend themselves to scalable manufacturing by way of stamping or imprinting were favored. Ultimately, the tradeoffs with using such methods was the larger feature size—on the order of ~150 um critical dimension—resulting in poorer control of light compared to structures fabricated by EBL. A summary of our 2-year investigation on this topic is presented herein. We begin by presenting highlights of our 1 st -year efforts using plasmonics, i.e., metallic nanostructures, as the building block for our PFC. The limitations in this approach are subsequently summarized. We then review the strategy we employed during the final year of our project, in particular utilizing insulating or dielectric materials as the light controlling medium. We round out the report discussing the results of our findings from using this approach. The report is relatively self-contained in that and no prior knowledge of optics or nanotechnology is assumed and technical jargon is kept at a minimum.

14 SOLAR ENERGY↗

DOE OSTI2021

Integration of the Back End of the Nuclear Fuel Cycle

Management of spent nuclear fuel and high-level radioactive waste consists of three main phases – storage, transportation, and disposal – commonly referred to as the back end of the nuclear fuel cycle. Current practice for commercial spent nuclear fuel management in the United States (US) includes temporary storage of spent fuel in both pools and dry storage systems at operating or shutdown nuclear power plants. Storage pools are filling to their operational capacity, and management of the approximately 2,200 metric tons of spent fuel newly discharged each year requires transferring older and cooler spent fuel from pools into dry storage. Unless a repository becomes available that can accept spent fuel for permanent disposal, projections indicate that the US will have approximately 136,000 metric tons of spent fuel in dry storage systems by mid-century, when the last plants in the current reactor fleet are decommissioned. Current designs for dry storage systems rely on large multi-assembly canisters, the most common of which are so-called “dual-purpose canisters” (DPCs). DPCs are certified for both storage and transportation, but are not designed or licensed for permanent disposal. The large capacity (greater number of spent fuel assemblies) of these canisters can lead to higher canister temperatures, which can delay transportation and/or complicate disposal. This current management practice, in which the utilities continue loading an ever-increasing inventory of larger DPCs, does not emphasize integration among storage, transportation, and disposal. This lack of integration does not cause safety issues, but it does lead to a suboptimal system that increases costs, complicates storage and transportation operations, and limits options for permanent disposal. This paper describes strategies for improving integration of management practices in the US across the entire back end of the nuclear fuel cycle. The complex interactions between storage, transportation, and disposal make a single optimal solution unlikely. However, efforts to integrate various phases of nuclear waste management can have the greatest impact if they begin promptly and continue to evolve throughout the remaining life of the current fuel cycle. A key factor that influences the path forward for integration of nuclear waste management practices is the identification of the timing and location for a repository. The most cost-effective path forward would be to open a repository by mid-century with the capability to directly dispose of DPCs without repackaging the spent fuel into disposalready canisters. Options that involve repackaging of spent fuel from DPCs into disposalready canisters or that delay the repository opening significantly beyond mid-century could add 10s of billions of dollars to the total system life cycle cost.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2015

SU-E-T-157: CARMEN: A MatLab-Based Research Platform for Monte Carlo Treatment Planning (MCTP) and Customized System for Planning Evaluation

Purpose: Although there exist several radiotherapy research platforms, such as: CERR, the most widely used and referenced; SlicerRT, which allows treatment plan comparison from various sources; and MMCTP, a full MCTP system; it is still needed a full MCTP toolset that provides users complete control of calculation grids, interpolation methods and filters in order to “fairly” compare results from different TPSs, supporting verification with experimental measurements. Methods: This work presents CARMEN, a MatLab-based platform including multicore and GPGPU accelerated functions for loading RT data; designing treatment plans; and evaluating dose matrices and experimental data.CARMEN supports anatomic and functional imaging in DICOM format, as well as RTSTRUCT, RTPLAN and RTDOSE. Besides, it contains numerous tools to accomplish the MCTP process, managing egs4phant and phase space files.CARMEN planning mode assist in designing IMRT, VMAT and MERT treatments via both inverse and direct optimization. The evaluation mode contains a comprehensive toolset (e.g. 2D/3D gamma evaluation, difference matrices, profiles, DVH, etc.) to compare datasets from commercial TPS, MC simulations (i.e. 3ddose) and radiochromic film in a user-controlled manner. Results: CARMEN has been validated against commercial RTPs and well-established evaluation tools, showing coherent behavior of its multiple algorithms. Furthermore, CARMEN platform has been used to generate competitive complex treatment that has been published in comparative studies. Conclusion: A new research oriented MCTP platform with a customized validation toolset has been presented. Despite of being coded with a high-level programming language, CARMEN is agile due to the use of parallel algorithms. The wide-spread use of MatLab provides straightforward access to CARMEN’s algorithms to most researchers. Similarly, our platform can benefit from the MatLab community scientific developments as filters, registration algorithms etc. Finally, CARMEN arises the importance of grid and filtering control in treatment plan comparison.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2024

Towards intelligent emergency control for large-scale power systems: Convergence of learning, physics, computing and control

Here, this paper has delved into the pressing need for intelligent emergency control in large-scale power systems, which are experiencing significant transformations and are operating closer to their limits with more uncertainties. Learning-based control methods are promising and have shown effectiveness for intelligent power system control. However, when they are applied to large-scale power systems, there are multifaceted challenges such as scalability, adaptiveness, and security posed by the complex power system landscape, which demand comprehensive solutions. The paper first proposes and instantiates a convergence framework for integrating power systems physics, machine learning, advanced computing, and grid control to realize intelligent grid control at a large scale. Our developed methods and platform based on the convergence framework have been applied to a large (more than 3000 buses) Texas power system, and tested with 56 000 scenarios. Our work achieved a 26% reduction in load shedding on average and outperformed existing rule-based control in 99.7% of the test scenarios. The results demonstrated the potential of the proposed convergence framework and DRL-based intelligent control for the future grid.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2020

Role of the Terrestrial Biosphere in Atmospheric Chemistry and Climate

The terrestrial biosphere–atmosphere interface provides a key chemical, biological, and physical lower boundary for the atmosphere. The presence of vegetation itself modifies the physical boundary, or the biogeophysical aspects of the system, by controlling important climate drivers such as soil moisture, light environment, and temperature. The leaf surface area of the terrestrial biosphere provides additional surface area for emissions, and it can be up to 55% of the total Earth’s surface area during the boreal summer. Vegetation also influences the biogeochemical aspects of the system by emitting a broad suite of reactive trace gases such as biogenic volatile organic compound (BVOC) emissions and climate-relevant primary biological aerosol particles (PBAP). Many of these emissions are a function of meteorological and climatological conditions at the surface, including temperature, light environment, soil moisture, and winds. Once emitted, they can be processed in the troposphere through a suite of chemical reactions. BVOC can contribute to the formation of ozone and secondary organic aerosols (SOA), and PBAP can rupture to form smaller particles with climatic relevance. These emissions and subsequent aerosol products can influence atmospheric processes that affect the surface climate, such as the attenuation of radiation, the formation of greenhouse gases such as ozone that can feedback to surface air temperature, and the alteration of clouds and subsequent precipitation. These atmospheric changes can then feedback to the land surface and emissions themselves, creating positive or negative feedback loops that can dampen or amplify the emission response. For the dominant BVOC isoprene, the feedback response to temperature can be positive or negative depending on ambient temperatures that drive isoprene emissions. The feedback response to soil moisture and precipitation can be positive, negative, or uncoupled depending on the moisture content of the soil and the total atmospheric aerosol loading. For light, the isoprene response can be positive or negative depending on the role of diffuse light. Overall, these feedbacks highlight the dynamical response of the biosphere to changing atmospheric conditions across a range of time scales, from minutes for trace gases and aerosols, to months for phenological changes, to years for land cover and land use change. Here, the dynamic aspect of this system requires us to understand, simulate, and predict the complex feedbacks between the biosphere and atmosphere and understand their role in the simulation and understanding of climate and global change. From the observational perspective, these feedbacks are challenging to identify in observations, and predictive modeling tools provide a crucial link for understanding how these feedbacks will change under warming climate scenarios.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2016

Stable Aqueous Dispersions of Hydrophobically Modified Titanium Dioxide Pigments through Polyanion Adsorption: Synthesis, Characterization, and Application in Coatings

Polyanion dispersants stabilize aqueous dispersions of hydrophilic (native) inorganic oxide particles, including pigments currently used in paints, which are used at an annual scale of 3 million metric tons. While obtaining stable aqueous dispersions of hydrophobically modified particles has been desired for the promise of improved film performance and water barrier properties, it has until now required either prohibitively complex polyanions, which represent a departure from conventional dispersants, or multistep syntheses based on hybrid-material constructs. Here, we demonstrate the aqueous dispersion of alkylsilane-capped inorganic oxide pigments with conventional polycarboxylate dispersants, such as carboxymethylcellulose (CMC) and polyacrylate, as well as a commercial anionic copolymer. Contact-angle measurements demonstrate that the hydrophobically modified pigments retain significant hydrophobic character even after adsorbing polyanion dispersants. CMC adsorption isotherms demonstrate 92% greater polyanion loading on trimethylsilyl modified hydrophobic particles relative to native oxide at pH 8. However, consistent with prior literature, hydrophobically modified silica particles adsorb polyanions very weakly under these conditions. These data suggest that Lewis acidic heteroatoms such as Al 3+ sites on the pigment surface are necessary for polyanion adsorption. The adsorbed polyanions increase the dispersion stability and zeta potential of the particles. Based on particle sedimentation under centrifugal force, the hydrophobically modified pigments possess greater dispersion stability with polyanions than the corresponding native hydroxylated particles. The polyanions also assist in the aqueous wetting of the hydrophobic particles, facilitating the transition from a dry powder into an aqueous dispersion of primary particles using less agitation than the native hydroxylated pigment. The application of aqueous dispersions of hydrophobically modified oxide particles to waterborne coatings leads to films that display lower water uptake at high relative humidities and greater hydrophilic stain resistances. Finally, this improved film performance with hydrophobically modified pigments is the result of better association between latex polymer and pigment in the dry film.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Synchrophasor Measurements-based Events Detection Using Deep Learning

Deep learning algorithms have been developed for phasor measurement units (PMUs) analysis aiming at providing grid operators to observe and react to significant real-time changes in the grid associated with multiple factors (e.g., power generation and load variations, different type of faults, and equipment mailfunction), or for offline post-event system diagnostics. In this study, a Long Short-Term Memory (LSTM)-based deep neural network (DNN) is adopted and evaluated to identify the most appropriate model configurations for event detection and longer-term anomalous pattern extraction. The proposed DNN model shows the potential on long-term predictions with the ability to capture nonlinear and nonstationary mixture complex patterns in PMU datasets. Real-world PMU in the WECC system were used for model development and validation.

deep learning↗

DOE OSTI2014

New Carbon-Based Porous Materials with Increased Heats of Adsorption for Hydrogen Storage

Hydrogen fuel cell vehicles are a promising alternative to internal combustion engines that burn gasoline. A significant challenge in developing fuel cell vehicles is to store enough hydrogen on-board to allow the same driving range as current vehicles. One option for storing hydrogen on vehicles is to use tanks filled with porous materials that act as “sponges” to take up large quantities of hydrogen without the need for extremely high pressures. The materials must meet many requirements to make this possible. This project aimed to develop two related classes of porous materials to meet these requirements. All materials were synthesized from molecular constituents in a building-block approach, which allows for the creation of an incredibly wide variety of materials in a tailorable fashion. The materials have extremely high surface areas, to provide many locations for hydrogen to adsorb. In addition, they were designed to contain cations that create large electric fields to bind hydrogen strongly but not too strongly. Molecular modeling played a key role as a guide to experiment throughout the project. A major accomplishment of the project was the development of a material with record hydrogen uptake at cryogenic temperatures. Although the ultimate goal was materials that adsorb large quantities of hydrogen at room temperature, this achievement at cryogenic temperatures is an important step in the right direction. In addition, there is significant interest in applications at these temperatures. The hydrogen uptake, measured independently at NREL was 8.0 wt %. This is, to the best of our knowledge, the highest validated excess hydrogen uptake reported to date at 77 K. This material was originally sketched on paper based on a hypothesis that extended framework struts would yield materials with excellent hydrogen storage properties. However, before starting the synthesis, we used molecular modeling to assess the performance of the material for hydrogen uptake. Only after modeling suggested record-breaking hydrogen uptake at 77 K did we proceed to synthesize, characterize, and test the material, ultimately yielding experimental results that agreed closely with predictions that were made before the material was synthesized. We also synthesized, characterized, and computationally simulated the behavior of two new materials displaying the highest experimental Brunauer$-$Emmett$-$Teller (BET) surface areas of any porous materials reported to date (~7000 m 2 /g). Key to evacuating the initially solvent-filled materials without pore collapse, and thereby accessing the ultrahigh areas, was the use of a supercritical CO 2 activation technique developed by our team. In our efforts to increase the hydrogen binding energy, we developed the first examples of “zwitterionic” metal-organic frameworks (MOFs). The two structures feature zwitterionic characteristics arising from N-heterocyclic azolium groups in the linkers and negatively charged Zn 2 (CO 2 ) 5 nodes. These groups interact strongly with the H 2 quadrupole. High initial isosteric heats of adsorption for hydrogen were measured at low H 2 loading. Simulations were used to determine the H 2 binding sites, and results were compared with inelastic neutron scattering. In addition to MOFs, the project produced a variety of related materials known as porous organic frameworks (POFs), including robust catechol-functionalized POFs with tunable porosities and degrees of functionalization. Post-synthesis metalation was readily carried out with a wide range of metal precursors (Cu II , Mg II , and Mn II salts and complexes), resulting in metalated POFs with enhanced heats of hydrogen adsorption compared to the starting nonmetalated materials. Isosteric heats of adsorption as high as 9.6 kJ/mol were observed, compared to typical values around 5 kJ/mol in unfunctionalized MOFs and POFs. Modeling played an important role throughout the project. For example, we used molecular simulations to determine that the optimal isosteric heat of adsorption (Q st ) for maximum hydrogen delivery using MOFs is approximately 20 kJ/mol. If the heat of adsorption is too low, little hydrogen is adsorbed. If the heat of adsorption is too high, it is difficult to recover the hydrogen at the desorption pressure. The results supported the major premise of this project that increasing Q st for MOFs with large surface areas is required to attain current hydrogen storage targets in terms of deliverable capacity.

08 HYDROGEN↗

DOE OSTI2017

9975 Shipping package component long-term degradation rates

Special nuclear materials are being stored in the K-Area Complex using 3013 containers that are held within Model 9975 shipping packages. The service life for these packages in storage was recently increased from 15 to 20 years, since some of these packages have been stored for nearly 15 years. A strategy is also being developed whereby such storage might be extended beyond 20 years. This strategy is based on recent calculations that support acceptable 9975 package performance for 20 years with internal heat loads up to 19 watts, and identifies a lower heat load limit for which the package components should degrade at half the bounding rate or less, thus doubling the effective storage life for these lower wattage packages. The components of the 9975 package that are sensitive to aging under storage conditions are the fiberboard overpack and the O-ring seals, although some degradation of the lead shield and outer drum are also possible. This report summarizes degradation rates applicable to lower heat load storage conditions. In particular, the O-ring seals should provide leak-tight performance for more than 40 years in packages for which their maximum temperature is ≤135 °F. Similarly, the fiberboard should remain acceptable in performance of its required safety functions for up to 40 years in packages with a maximum fiberboard temperature ≤125 °F.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2024

Ion Exchange Processing of AN-107 Hanford Tank Waste through Crystalline Silicotitanate in a Staged 2- then 3-Column System

The Hanford Site stores an estimated 56 million gallons of mixed radioactive and chemically hazardous waste in large underground tanks. In support of the Direct Feed Low-Activity Waste (DFLAW) Program for expediting Hanford tank waste supernate treatment, laboratory-scale ion exchange processing using prototypic unit operations was conducted on AN-107 tank waste at the Pacific Northwest National Laboratory Radiochemical Processing Laboratory. This report describes the small-scale ion exchange testing with 13.7 L of diluted and filtered supernate from Tank 241-AN-107 (hereafter referred to as AN-107) at 16 °C (62 °F). One of the waste acceptance criteria (WAC) for the Waste Treatment Plant (WTP) Low-Activity Waste Facility is that the waste must contain less than 3.18×10 -5 Ci 137 Cs per mole of Na. For the AN-107 tank waste to meet this criterion, only 0.147% of the influent 137 Cs concentration may be delivered to the WTP; this requires a Cs decontamination factor of 678. Testing with AN-107 matched current Tank Side Cesium Removal (TSCR) facility prototypic operations where a lead-lag configuration was used until the lag column reached the WAC limit, then a polish column was brought online for continued processing in a lead-lag-polish column configuration. Feed was processed at 1.9 bed volumes (BVs) per hour; the flowrate, in terms of contact time with the crystalline silicotitanate (CST) bed, matched the expected flowrate at TSCR. The Cs-decontaminated product was retained for vitrification testing (to be reported separately). The lead column reached 40% Cs breakthrough after processing ~1700 BVs of feed; the 50% Cs breakthrough was extrapolated from the breakthrough data to occur at 1873 BVs. Testing compared to previous AP-101 and AP-107 testing at 16 °C showed ~300 BV increases in volume processed to reach the WAC limit for both lead and lag columns. The increase in capacity was determined to be due to the significantly lower K concentration in the AN-107 compared to the other tank waste matrices. A comparison in breakthrough curves for the three tests indicated slightly slower kinetic behavior in the AN-107, with variations in feed matrices (high organic complexants) likely responsible for the deviation. The Cs effluent from the lag column reached the WAC limit after processing 1097 BVs. Anticipating this breakthrough point, the polish column was preemptively installed around 900 BVs. Cs breakthrough from the lag column began at 500 BVs, reaching 3.06×10 0 µCi/mL, or 2.6 % Cs breakthrough, after processing all 1700 BVs of feed. Table S.1 and Figure S.1 summarize the observed column performance and relevant Cs loading characteristics.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2020

Bistable dynamics and Hopf bifurcation in a refined model of early stage HIV infection

Recent clinical studies have shown that HIV disease pathogenesis can depend strongly on many factors at the time of transmission, including the strength of the initial viral load and the local availability of CD4+ T-cells. In this article, a new within-host model of HIV infection that incorporates the homeostatic proliferation of T-cells is formulated and analyzed. Due to the effects of this biological process, the influence of initial conditions on the proliferation of HIV infection is further elucidated. The identifiability of parameters within the model is investigated and a local stability analysis, which displays additional complexity in comparison to previous models, is conducted. The current study extends previous theoretical and computational work on the early stages of the disease and leads to interesting nonlinear dynamics, including a parameter region featuring bistability of infectious and viral clearance equilibria and the appearance of a Hopf bifurcation within biologically relevant parameter regimes.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Enhanced Dynamic Equivalent Identification Method of Large-Scale Power Systems Using Multiple Event

The increasing complexity of the interconnected power system makes high-fidelity dynamic simulation models computationally more intensive. To improve computation efficiency, model reduction techniques have been investigated to only preserve the dynamics in a limited area of interest (study area), while deriving equivalent representation for the external area. For this purpose, a measurement-based reduction approach using system identification techniques has been previously proposed. In that case, external areas are represented by dynamic equivalent loads using transfer function estimation. In this paper, in order to enhance the accuracy of the reduced model in preserving dynamics of the study area, multiple “grid” events of different types and at different locations are considered for identifying the parameters of the equivalent loads. Case studies are carried out in the NPCC 140-bus system. Comparison are made between multiple events training and single event training, highlighting the advantages of the proposed method in providing a better representation of the grid dynamics under different operating conditions.

Xue, Yaosuo↗