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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Batch Extraction Studies to Evaluate Trace Element Behavior in PUREX Conditions

The multilab Intentional Forensics Venture is working to identify which stable elements (i.e., taggants) at trace concentrations relative to U would persist throughout the nuclear fuel cycle in a voluntary fuel tagging scheme. A taggant would provide the nuclear forensics community with a “barcode” to help identify nuclear materials found outside of regulatory control. A portion of this project was focused on reprocessing effects and determining which, if any, elements would coextract with U(VI) in standard Pu–U reduction extraction (PUREX) conditions. Elements with a propensity to coextract could, in theory, be used as taggants from a PUREX perspective. Although retention is not a performance requirement, the taggant signature would need to partition predictably from the U stream after the PUREX process to maintain forensic utility. This report documents results from several batch extraction studies with numerous trace elements from HNO 3 (1.5–5 M), with and without U(VI), into 30% tri-n-butyl phosphate (TBP) in kerosene. Extraction and back-extraction tests were used to evaluate nearly 60 elements in surrogate conditions for PUREX, and distribution coefficients (i.e., D-values) for most species were <0.1, indicating few species are likely to co-extract with U through PUREX. Additional studies are needed to optimize sample volumes and dilutions to dial in these low D-values. The D-values (D) were determined for several of the more promising elements, including Re and Se. Ultimately, we conclude that only a limited number of the ~ 60 elements investigated are extractable in the U stream of PUREX, based on measured D values, meaning most candidate elemental taggants would likely be lost at this stage of the nuclear fuel cycle, even when considering a range of acid concentrations.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2021

Diffusional and Partitionless Ferrite‐to‐Austenite Phase Transformations during Intercritical Annealing of Medium‐Mn Steels

Experimental research on intercritical annealing of a cold‐rolled Fe–7Mn steel with ultralow carbon concentration is presented, providing insight into the efficacy of generating Mn‐enriched austenite during relatively short (≈1000 s) heat treatments compared with batch annealing, as well as the phase transformation mechanisms that can occur during intercritical annealing. It is shown through both bulk characterization and electron microscopy in conjunction with energy‐dispersive X‐ray spectroscopy that Mn partitioning to austenite occurs via diffusional, partitioning growth of austenite during these shorter treatments and that the intercritical temperature influences the level of Mn enrichment in austenite. Evidence of massive (partitionless) and diffusional (partitioning) transformations of ferrite to austenite occurring simultaneously in a single sample are also shown along with a thermodynamic rationale for this occurrence, which is suggested to be related to residual Mn‐banding that develops during solidification.

Mueller, Josh J.↗
DOE OSTI2022

Silver-Loaded Xerogel Nanostructures for Iodine Capture: A Comparison of Thiolated versus Unthiolated Sorbents

Here this paper describes the development and provides comparisons of thiolated (-SH) and unthiolated Ag-Al-Si-O xerogels for iodine gas capture. These xerogels were produced from alkoxides and then heat-treated at 350 °C to provide mechanical strength for subsequent processing steps. Then, a portion of the xerogels was thiolated using (3-mercaptopropyl)trimethoxysilane. Next, thiolated and unthiolated batches were ion-exchanged in AgNO 3 solutions where Ag + replaced Na + in the gel network on a near 1:1 molar basis. Subsamples of the Ag-exchanged xerogels were subjected to a reduction step in H 2 /Ar to convert Ag + to Ag 0 where the rest of the Ag-exchanged (Ag + ) were not reduced. X-ray diffraction, X-ray photoelectron spectroscopy, and transmission electron microscopy revealed nanoscale Ag 0 in the Ag + samples despite no active reduction where actively reduced samples had bimodal Ag 0 distribution of ~2-3 nm hexagonal and ~6-7 nm cubic crystallites. Synchrotron X-ray absorption spectroscopy was used to assess the oxidization states of Ag, S, and I within the different xerogel samples. The specific surface areas of the base xerogels decreased as subsequent treatments were performed on the as-made samples, albeit the decreases were smaller than aerogel equivalents of these samples from a previous study. All iodine-loaded Ag-based samples showed a mixture of β-AgI and γ-AgI. Comparisons of iodine-loading results with other Ag-based iodine sorbents show that the thiolated Ag 0 -xerogels in this work have one of the highest iodine-loading capacities (q e ) reported to date in saturated conditions with the thiolated Ag 0 -xerogel showing 522 mg iodine per g of the sorbent.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Single-cell RNA sequencing of batch Chlamydomonas cultures reveals heterogeneity in their diurnal cycle phase

The photosynthetic unicellular alga Chlamydomonas (Chlamydomonas reinhardtii) is a versatile reference for algal biology because of its ease of culture in the laboratory. Genomic and systems biology approaches have previously described transcriptome responses to environmental changes using bulk data, thus representing the average behavior from pools of cells. Here, we apply single-cell RNA sequencing (scRNA-seq) to probe the heterogeneity of Chlamydomonas cell populations under three environments and in two genotypes differing by the presence of a cell wall. First, we determined that RNA can be extracted from single algal cells with or without a cell wall, offering the possibility to sample natural algal communities. Second, scRNA-seq successfully separated single cells into nonoverlapping cell clusters according to their growth conditions. Cells exposed to iron or nitrogen deficiency were easily distinguished despite a shared tendency to arrest photosynthesis and cell division to economize resources. Notably, these groups of cells not only recapitulated known patterns observed with bulk RNA-seq but also revealed their inherent heterogeneity. A substantial source of variation between cells originated from their endogenous diurnal phase, although cultures were grown in constant light. We exploited this result to show that circadian iron responses may be conserved from algae to land plants. We document experimentally that bulk RNA-seq data represent an average of typically hidden heterogeneity in the population.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Benchmark of the Chlorine Worth Study Experiments in Support of Chlorine Nuclear Data Validation for Nuclear Criticality Safety

The Chlorine Worth Study (CWS) was a critical experiment to address an urgent need for thermal chlorine nuclear data validation in plutonium systems. This urgent need is tied directly to plutonium recycle and recovery operations in the plutonium facility at Los Alamos National Laboratory, where exceptionally conservative criticality safety limits are used because no credit is taken for the neutron capture by chlorine. The experiment used weapons-grade plutonium metal plates clad in stainless steel, known as the PANN (plutonium aluminum no nickel) ZPPR (zero power physics reactor) plates. The plutonium was reflected and moderated by high-density polyethylene and included combinations of polyvinyl chloride (PVC) and chlorinated polyvinyl chloride (CPVC) as absorbers. The experiment and benchmark included three configurations mimicking 30 g 239 Pu/L plutonium, 300 g 239 Pu/L plutonium, and 600 g 239 Pu/L plutonium in an aqueous chloride solution. Uncertainties in the benchmark included five broad categories: (1) criticality measurement, (2) mass and density, (3) dimensions, (4) material compositions, and (5) positioning. The largest contribution to the overall uncertainties for all three cases came from the material compositions, in particular the PVC and CPVC absorber compositions. A detailed model was created to be a near match (that is within expectations of transport code users) and a simplified model was created to minimize offset dimensions and expedite modeling for code validation. Sample calculations were completed in MCNP6.3 with ENDF/B-VIII.0 and ENDF/B-VII.1 nuclear data. For the detailed and simplified models, the average difference between the computed and experimental k eff was 951 pcm. CWS will serve as the key validation experiment for nuclear criticality safety in support of aqueous chloride operations. The sensitivity to the chlorine capture cross section is orders of magnitude greater than other existing benchmarks. The current limits, as defined by nuclear criticality safety, are 520 g Pu per batch, i.e. the minimum critical mass of the Pu solution infinitely reflected by water [Criticality Handbook: Volume II, (1969)]. This extremely conservative critical mass limit does not credit any neutron capture by chlorine (in particular neutron capture by 35 Cl) and greatly impedes the throughput required for current and future operations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Investigation of the structure, filler interaction and degradation of disulfide elastomers made by Reversible Radical Recombination Polymerization (R3P)

In this paper we report the synthesis and analysis of cyclic polydisulfides, their redox depolymerization as well as their interaction with carbon black. Cyclic poly(3,6-dioxa-1,8-octanedithiol)s (pDODT) were synthesized by Reversible Radical Recombination Polymerization (R3P). R3P is a scalable “green” polymerization process using triethylamine (TEA), H 2 O 2 and air for the polymerization of dithiol monomers. pDODTs were synthesized in 5 and 20 g batches. The effect of peroxide concentration (3, 5, 10, 20, 30%) was investigated. It was found that the molecular weights increased exponentially with increasing peroxide concentrations. At 30% peroxide concentration pDODTs with M n up to 400,000 g/mol and polydispersity of 2 were obtained. 700 and 800 MHz NMR were used for investigating the chemical structure of the polymers. The absence of thiol end group signals in polymers made with > 10wt % H 2 O 2 and M n < 100,000 g/mol, including a sample of a fractionated polymer with starting Mn = 600,000 g/mol, verified cyclic structures. Dithiothreitol reduced the polymers to monomer and a small percentage of oligomers. Carbon black was shown to increase the moduli of high molecular weight pDODTs. Swelling tests in chloroform showed that polymers made with 20 and 30w% peroxide swelled 14 and 10 times of their starting weight without dissolving, indicating chemical interaction between the polymers and carbon black. In conclusion, further analysis of these interesting elastomers, available at the 20 g scale, is in progress.

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

Navigating the Noise: Bringing Clarity to ML Parameterization Design With O $\boldsymbol{\mathcal{O}}$(100) Ensembles

Abstract Machine‐learning (ML) parameterizations of subgrid processes (here of turbulence, convection, and radiation) may one day replace conventional parameterizations by emulating high‐resolution physics without the cost of explicit simulation. However, uncertainty about the relationship between offline and online performance (i.e., when integrated with a large‐scale general circulation model) hinders their development. Much of this uncertainty stems from limited sampling of the noisy, emergent effects of upstream ML design decisions on downstream online hybrid simulation. Our work rectifies the sampling issue via the construction of a semi‐automated, end‐to‐end pipeline for size ensembles of hybrid simulations, revealing important nuances in how systematic reductions in offline error manifest in changes to online error and online stability. For example, removing dropout and switching from a Mean Squared Error to a Mean Absolute Error loss both reduce offline error, but they have opposite effects on online error and online stability. Other design decisions, like incorporating memory, converting moisture input from specific humidity to relative humidity, using batch normalization, and training on multiple climates do not come with any such compromises. Finally, we show that ensemble sizes of may be necessary to reliably detect causally relevant differences online. By enabling rapid online experimentation at scale, we can empirically settle debates regarding subgrid ML parameterization design that would have otherwise remained unresolved in the noise.

Lin, Jerry [Department of Earth System Sciences Un↗
DOE OSTI2021

MicroResonators for Compacts Optical Sensors (μRCOS)

As the demand for continuous, in-situ surveillance of health of systems and environments rapidly increases, miniaturized sensors with fast responses are sought. Optical dielectric resonators supporting Whispering Gallery Modes (WGMs) have exceptional properties, like very high-power density, very narrow spectral linewidth, and extremely small mode volume. As the footprint of these sensors is drastically reduced, measurements of microvolumes samples with dramatic reduction in analysis time are possible, enabling large numbers of parallel analyses using microarrays. The high sensitivity and speed of WGM resonators combined with the ability to detect molecules in their native state have great future potential for basic and applied research such as reliable single molecule, trace-gas detection, environmental monitoring, chemical threat sensing, and biodefense Such appealing peculiarities motivated us developing WMG resonators (WGMRs) for Cavity Enhanced Absorption Spectroscopy (CEAS) for chem-bio detection. Specifically, we designed and batch-fabricated microspheres and fiber tapers for resonances excitation. We successfully detected gases (N 2 and CO 2 ) in customized environmental chambers, and bio-organisms (Inf. A and E. Coli) with integrated microfluidic systems. Background calibration and environmental isolation were always accounted for in proving the performances.

36 MATERIALS SCIENCE↗
DOE OSTI2021

MicroResonators for Compacts Optical Sensors (μRCOS)

As the demand for continuous, in-situ surveillance of health of systems and environments rapidly increases, miniaturized sensors with fast responses are sought. Optical dielectric resonators supporting Whispering Gallery Modes (WGMs) have exceptional properties, like very high-power density, very narrow spectral linewidth, and extremely small mode volume. As the footprint of these sensors is drastically reduced, measurements of microvolumes samples with dramatic reduction in analysis time are possible, enabling large numbers of parallel analyses using microarrays. The high sensitivity and speed of WGM resonators combined with the ability to detect molecules in their native state have great future potential for basic and applied research such as reliable single molecule, trace-gas detection, environmental monitoring, chemical threat sensing, and biodefense Such appealing peculiarities motivated us developing WMG resonators (WGMRs) for Cavity Enhanced Absorption Spectroscopy (CEAS) for chem-bio detection. Specifically, we designed and batch-fabricated microspheres and fiber tapers for resonances excitation. We successfully detected gases (N 2 and CO 2 ) in customized environmental chambers, and bio-organisms (Inf. A and E. Coli) with integrated microfluidic systems. Background calibration and environmental isolation were always accounted for in proving the performances.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Improved Performance of Cu(InGa)(SeS) 2 PV Modules Using the Reaction of Metal Precursors. Final Report

This project “Improved Performance of Cu(InGa)(SeS) 2 PV Modules using the Reaction of Metal Precursors” was a partnership led by the Institute of Energy Conversion (IEC) at the University of Delaware with Columbia University and the Molecular Foundry at the Lawrence Berkeley National Laboratory. The aim was to develop pathways to improve Cu(InGa)(SeS) 2 (CIGSS) thin film photovoltaic modules using processes compatible with low manufacturing cost. The CIGSS approach investigated was a two-step process including deposition of metal precursor films following by reaction in hydride gases utilizing IEC’s novel reactor. The process was similar to that under commercial development by the project’s industry partner Stion. When Stion went out of business mid-project the focus changed to a rapid thermal process considered more commercially viable. Approaches to improve the performance of solar cells using the reacted films focused on two material innovations. First, the overall Ga content was increased to increase the operating voltage, which is desirable for scale-up to commercial modules. Second, the processing and performance advantages arising from Ag alloying were investigated. Advanced characterization guided process and material development including control of relative composition gradients. Research on the formation of Cu-Ga-In metal precursors utilized sputtering deposition which is normally used in commercial applications. The work resulted in processes for deposition of precursor stacks with increased relative Ga content and effects of deposition parameters on morphology and phase composition were established. It was shown that the metal precursor films have comparable phase composition and morphology so subsequent reaction follows from the same starting point. The addition of Ag to the metal precursors gave more uniform morphology and improved adhesion of reacted films which enable higher reaction temperature for faster processing. A novel outcome was the discovery of a previously undocumented material phase in sputter-deposited and evaporated Ag-Cu-In-Ga thin films. Hydride gas reaction processes including time-temperature-concentration profiles were developed for different precursor compositions. This enables control of composition profiles to engineer through-film gradients for solar cell optimization with characterization and simulations used to correlate measured film composition profiles to measurements of devices. In particular, the gradient of sulfur at the front of the CIGSS film was found to be critical. The simulations guided process development leading to improved reproducibility of devices improved performance with higher Ga content and higher voltage. With Ag-alloyed precursors, the reaction pathways leading were determined. A significant finding was that Ag-alloying increases the reaction rate to completely convert precursor films to the final chalcopyrite which could enable reduced reaction time to benefit manufacturability. To maintain potential commercial viability, the process under investigation was refocused to a rapid thermal process that could potentially be incorporated into an in-line process for manufacturing. Precursors with different composition were capped with an extra selenium layer and reacted in hydrogen sulfide 5-15 minutes, compared to typically 2 hours in the previous multi-step batch process. Critical RTP parameters were identified to control the reaction. Further optimization would be needed for high efficiency solar cells but pathways to high quality devices with further optimization and improved heating uniformity were developed. The project also developed new optoelectronic characterization approaches with a focus on development and application of spatial- and time-resolved photoluminescence and a custom mapping photoluminescence microscope built. It was shown how critical electronic transport properties strongly depend on the chemical composition of the material and that a wide range of samples show inhomogeneity on a length scale larger than the grains in the films. Additionally, two-photon excitation capability was developed to distinguish bulk vs surface losses. The project advances the state-of-the -art for precursor reaction processes in several ways that could impact manufacturing. This includes validation of approaches to increase voltage and establishment of model-guided control to form optimal composition profiles. The application of process control approaches with knowledge of phase formation and reaction pathways can be critically valuable in designing a large-scale process.

14 SOLAR ENERGY↗
DOE OSTI2026

Analytical workflow dependence of experimental observables for uranium chemistries

In this work, we investigated how the sequencing of laboratory analytical methods used for chemical and morphological characterization influences analytical findings for particulate materials relevant to the nuclear fuel cycle, including UO2, U3O8, studtite (UO2O2·4H2O), and β-UO3, in the context of nuclear forensic analysis. Particles of each chemistry obtained from consistent production batches were exposed to Raman spectroscopy and scanning electron microscopy in varying orders to elucidate how the order in which the techniques are applied influences morphological and chemical observations as a function of particle size. The results indicate that particles from all four chemistries exposed to high-resolution electron imaging before Raman spectral analysis demonstrate optical vibrational spectral changes that reduce accurate interpretation of the underlying chemistry via Raman spectral analysis. We hypothesize that these changes are due to the thermal load of the electron beam imparted to the sample being unable to be dissipated by materials with poor thermal conduction properties. Results from this study will aid in determining best practices for forensic analysis procedures to reduce uncertainty in chemical determination of unknown particulate samples.

Manns, Rebecca [University of Nevada, Las Vegas]↗
DOE OSTI2021

Melting rate correlation with batch properties and melter operating conditions during conversion of nuclear waste melter feeds to glasses

The rate of conversion of nuclear waste melter feed to glass is affected by the selection of melter feed materials and by melter design and operation. The melting rate correlation (MRC) is an equation that relates the glass production rate with two types of variables: (1) feed and melt properties: conversion heat, cold-cap bottom temperature, and glass melt viscosity; and (2) melter design and operation parameters: melter geometry, melter operating temperature, and gas bubbling rate. The MRC shows good agreement for an extended melting-rate data set of high-level waste (HLW) melter feeds and a data set generated for low-activity waste (LAW) melter feeds. Laboratory observation of heated melter feed samples is often used to assess the cold-cap bottom temperature of HLW melter feeds (moderately foaming feeds), but this technique appears inadequate for LAW melter feeds (vigorously foaming feeds). For LAW feeds, an adequate assessment of the cold-cap bottom temperature was achieved using evolved gas analysis, which allows identification of the collapse of primary foam for oxidized feeds. This assessment shows that the cold-cap bottom temperature for vigorously foaming LAW feeds is higher than that for moderately foaming HLW feeds. When the results of MRC are compared, LAW feeds are generally less sensitive to the bubbling rate and melt viscosity, and more sensitive to the cold-cap bottom temperature than HLW feeds. The MRC qualifies as a promising tool to support the selection of melter feed materials and melter operating conditions, which is determined from expensive independent scaled melter experiments, and sophisticated mathematical models.

Lee, Seung Min↗
DOE OSTI2025

Pyrogenic Organic Matter Laboratory Experiment: Aerobic Respiration and Geochemistry from Variably Inundated Stream Sediments (v3)

This dataset supports a broader study examining the effects of variable inundation and pyrogenic organic matter on ecosystem respiration. The dataset provides data generated from a laboratory batch experiment investigating the interaction between variable inundation conditions (wet and dry sediment) and pyrogenic organic matter (burned and unburned treatments). The contents include time series dissolved oxygen, sediment geochemistry data, and field metadata (including qualitative information on instream and river corridor characteristics). This data package was originally published in November 2025. It was updated in April 2026 (v2; new and modified files) and May 2026 (v3; modified files). See the change history section in the readme for more details For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. In addition to a readme, this data package also includes a file-level metadata (FLMD) file that describes each file and a data dictionary (DD) that describes all column/row headers and variable definitions. This dataset is comprised of (1) file-level metadata; (2) data dictionary; (3) field metadata; (4) international generic sample number (IGSN) mapping file; (5) readme; (6) field protocol; (7) sample name metadata; (8) an environmental context picture for the dry and inundated sampling locations; and (9) a subfolder with sample data from the sediment incubation experiment. The sample data subfolder contains (1) dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC); (2) total nitrogen (TN); (3) gravimetric moisture; (4) partial pressure and production rates of carbon dioxide, methane, and nitrous oxide; (5) field wet sediment mass, dry sediment mass, water mass, and field wet sediment volume in incubation and sediment NPOC/TN vials; (6) methods codes; (7) respiration rates, pH, and temperature from after the incubation, raw time series dissolved oxygen and temperature, and a subfolder containing associated plots and scripts; (8) ions; (9) FTICR-MS methods; and (10) a subfolder of 12 Tesla (12T) FTICR-MS data. This folder contains the CoreMS processed data and three subfolders, one containing the .xml files, one containing the CoreMS output files, and the other containing instructions and scripts for processing the files in CoreMS (https://github.com/EMSL-Computing/CoreMS). All files are .csv, .pdf, .R, .xml, .html, .Rmd, .py, .cal, .json, or .jpg.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Characterization and QC practice of 16-channel ADC ASIC at cryogenic temperature for Liquid Argon TPC front-end readout electronics system in DUNE experiment

ColdADC is a low-noise 16-channel analog-to-digital converter ASIC designed for cold readout electronics of Liquid Argon Time Projection Chambers (LArTPCs) in the Deep Underground Neutrino Experiment (DUNE). ColdADC was specifically designed for operation at cryogenic temperatures (77 K–89 K). Cold electronics is considered to be an enabling technology for liquid argon detectors in neutrino experiments. The main function of the chip is to digitize signals from the 16-channel charge-sensitive amplifier designed at BNL (LArASIC) and send digitized signals to the data aggregator and serializer chip (COLDATA). ColdADC operates with a resolution of 12 bits and a sampling rate of 2 MS/s per channel. A complete characterization of prototype chips was conducted at cryogenic temperature, involving power consumption, noise and linearity performance. In the first DUNE Far-Detector module, 384000 data channels will be read out, corresponding to 24000 ColdADC chips. Therefore, systematic testing of ColdADC chips at cryogenic temperature is vital for the quality and reliability of DUNE Single-Phase modules. We have developed a Quality Control (QC) test stand that includes ColdADC evaluation and characterization at cryogenic temperature. The QC procedure was applied to a first batch of 33 chips, corresponding to 528 data channels. The obtained results meet all the required DUNE specifications for ColdADC. Moreover, the testing outcome allowed us to identify possibilities of performance optimization that are currently being addressed in the design of the next version of the chip. The Quality Control procedure is proved to be successful and will be a reference design for future large-batch production testing of final ColdADC ASICs.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Coupling flux balance analysis with reactive transport modeling through machine learning for rapid and stable simulation of microbial metabolic switching

Integrating genome-scale metabolic networks with reactive transport models (RTMs) provides a detailed description of the dynamic changes in microbial growth and metabolism. Despite promising demonstrations in the past, computational inefficiency has been pointed out as a critical issue to overcome because it requires repeated application of linear programming (LP) to obtain flux balance analysis (FBA) solutions in every time step and spatial grid. To address this challenge, we propose a new simulation method where we train and validate artificial neural networks (ANNs) using randomly sampled FBA solutions and incorporate the resulting surrogate FBA model (represented as algebraic equations) into RTMs as source/sink terms. We demonstrate the efficiency of our method via a case study of Shewanella oneidensis MR-1. During aerobic growth on lactate, S. oneidensis produces metabolic byproducts (such as pyruvate and acetate), which are subsequently consumed as alternative carbon sources when the preferred nutrients are depleted. To effectively simulate these complex dynamics, we used a cybernetic approach that models metabolic switches as the outcome of dynamic competition among multiple growth options. In both zero-dimensional batch and one-dimensional column configurations, the ANN-based surrogate models achieved substantial reduction of computational time by several orders of magnitude compared to the original LP-based FBA models. Moreover, the ANN models produced robust solutions without any special measures to prevent numerical instability. These developments significantly promote our ability to utilize genome-scale networks in complex, multi-physics, and multi-dimensional ecosystem modeling.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Recursive Gaussian Process over graphs for Integrating Multi-timescale Measurements in Low-Observable Distribution Systems

The transition to a smarter grid is empowered by enhanced sensor deployments and smart metering infrastructure in the distribution system. Measurements from these sensors and meters can be used for many applications, including distribution system state estimation (DSSE). However, these measurements are typically sampled at different rates and could be intermittent due to losses during the aggregation process. These multi timescale measurements should be reconciled in real-time to perform accurate grid monitoring. This paper tackles this problem by formulating a recursive multi-task Gaussian process (RGP-G) approach that sequentially aggregates sensor measurements. Specifically, we formulate a recursive multi-task GP with and without network connectivity information to reconcile the multi time-scale measurements in distribution systems. Here, the proposed framework is capable of aggregating the multi-time scale measurements batch-wise or in real-time. Following the aggregation of the multi time-scale measurements, the spatial states of the consistent time-series are estimated using matrix completion based DSSE approach. Simulation results on IEEE 37 and IEEE 123 bus test systems illustrate the efficiency of the proposed methods from the standpoint of both multi time-scale data aggregation and DSSE.

42 ENGINEERING↗
DOE OSTI2026

Cost Competitive Process of Battery Grade Oxides Preparation from Aged LIBs

The increasing demand for lithium-ion batteries (LIBs) is driving development of advanced recycling and refining methods. In this project, new cathode active materials are prepared from recycled lithium battery materials and subsequently electrochemically evaluated in coin cells. In detail, scrap LIBs were mechanically processed into a metal rich black mass, then reductive acid leached into an aqueous metal solution, and finally high-purity metal hydroxide precursor materials were prepared by selective electrochemical flow precipitation. Closed-loop LIB recycling into active electrode materials will enable US manufacturers to break their reliance on foreign sources of critical materials. For example, electroextraction process used here has potential to significantly reduce chemical & water use as well as waste production as compared to traditional metallurgic techniques. To this end, electroextracted materials refined from used batteries were collected and processed to be tested as precursor cathode active material (pCAM). For this project, two samples of high purity recycled NMC hydroxide (~1 kg each) were received from N th Cycle’s Ohio demonstration facility. The NMC compositions of the two materials are similar, and the levels of impurities have been confirmed. Indeed, impurities like copper, boron and sodium are present in quantities that could negatively impact battery performance. However, some studies have demonstrated that the control of the quantity of elements like copper or boron may improve the electrochemistry properties of Lithium-NMC batteries. The principal objective is to determine the electrochemical performance of these 2 NMC hydroxide batches and clearly determine the effect of the impurities on the performance.

25 ENERGY STORAGE↗
DOE OSTI2025

Functionalized Porous Polymer Networks as High-Performance PFAS Adsorbents

Toxic per- and polyfluoroalkyl substances (PFAS) are now found in nearly every water source on the planet. Exposure to these molecules can have negative health consequences, but the low concentration of PFAS relative to other solutes in water makes their removal challenging. Adsorbents offer a promising treatment route, but often exhibit low selectivities and removal capacities, as well as slow kinetics. The performance in these metrics can be improved by chemically optimizing PFAS binding sites and maximizing PFAS-adsorbent interactions. To explore how to achieve this, a porous polymer network solid (PPN-6, also known as PAF-1) was postsynthetically modified with various chemical moieties capable of leveraging unique combinations of electrostatic, hydrogen-bonding, hydrophobic, and fluorophilic interactions with PFAS molecules. Batch adsorption experiments and computational studies revealed that electrostatic and hydrogen-bonding interactions drive short-chain PFAS adsorption, while hydrophobic and fluorophilic interactions improve long-chain PFAS adsorption. In complex water matrices, a combination of electrostatic and fluorophilic interactions led to the greatest total PFAS removal. The best-performing material, functionalized with a fluorinated alkylammonium (PPN-6-FNDMB), selectively adsorbs PFAS with high capacity (up to 4.0 mmol/g) and rapid kinetics (equilibrium reached in <30 s). Furthermore, PPN-6-FNDMB outperforms several commercial adsorbents, achieving near-complete removal of 21 different PFAS from a groundwater sample collected at a US Air Force base. The PFAS could subsequently be desorbed from PPN-6-FNDMB, concentrating them by a factor of over 50 times. The recycled PPN-6-FNDMB could then be reused with minimal losses in long-chain PFAS adsorption capacity over four cycles.

Pezoulas, Ethan R↗