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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Diagnostic-free onboard battery health assessment

Diverse usage patterns induce complex and variable aging behaviors in lithiumion batteries, complicating accurate health diagnosis and prognosis. Separate diagnostic cycles are often used to untangle the battery’s current state of health from prior complex aging patterns. However, these same diagnostic cycles alter the battery’s degradation trajectory, are time-intensive, and cannot be practically performed in onboard applications. Here, in this work, we leverage portions of operational measurements in combination with an interpretable machine learning model to enable rapid, onboard battery health diagnostics and prognostics without offline diagnostic testing and the requirement of historical data. We integrate mechanistic constraints within an encoder-decoder architecture to extract electrode states in a physically interpretable latent space and enable improved reconstruction of the degradation path. The health diagnosis model framework can be flexibly applied across diverse application interests with slight fine-tuning.

battery aging reconstruction↗
DOE OSTI2021

Cancer/testis antigen LDHC promotes proliferation and metastasis by activating the PI3K/Akt/GSK-3β-signaling pathway and the in lung adenocarcinoma

The cancer/testis antigen lactate dehydrogenase-C4 (LDHC) is a specific isoenzyme of the LDH family that regulates invasion and metastasis in some malignancies; however, little is known regarding its role in progression of lung adenocarcinoma (LUAD). Thus, we investigated LDHC expression by immunohistochemistry, and analyzed its clinical significance in 88 LUAD specimens. The role and molecular mechanisms subserving LDHC in cellular proliferation, migration, and invasion were explored both in vitro and in vivo. As a result, we found that high LDHC expression was significantly correlated with clinicopathological features of aggressive LUAD and a poor prognosis. Overexpression of LDHC induced LUAD cells to produce lactate and ATP, increased their metastatic and invasive potential—, and accelerated xenograft tumor growth. We further demonstrated that overexpression of LDHC affected the expression of cell proliferation-related proteins (cyclin D1 and c-Myc) and epithelial-mesenchymal transition (EMT)-related proteins (MMP-2, MMP-9, E-cadherin, Vimentin, Twist, Slug, and Snail) both in vitro and in vivo. Finally, excessive activation of LDHC enhanced the phosphorylation levels of AKT and GSK-3β, revealing activation of the PI3K/Akt/GSK-3β oncogenic-signaling pathways. Treatment with a PI3K inhibitor reversed the effects of LDHC overexpression by inhibiting cellular proliferation, migration, and invasion, with diminished levels of p-Akt and p-GSK3β. PI3K inhibition also reversed cell proliferation-related and EMT-related proteins in LDHC-overexpressing A549 cells. In conclusion, LDHC promotes proliferation, migration, invasion, and EMT in LUAD cells via activation of the PI3K/Akt/GSK-3β pathway.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Shotgun Immunoproteomic Approach for the Discovery of Linear B-Cell Epitopes in Biothreat Agents Francisella tularensis and Burkholderia pseudomallei

Peptide-based subunit vaccines are coming to the forefront of current vaccine approaches, with safety and cost-effective production among their top advantages. Peptide vaccine formulations consist of multiple synthetic linear epitopes that together trigger desired immune responses that can result in robust immune memory. The advantages of linear compared to conformational epitopes are their simple structure, ease of synthesis, and ability to stimulate immune responses by means that do not require complex 3D conformation. Prediction of linear epitopes through use of computational tools is fast and cost-effective, but typically of low accuracy, necessitating extensive experimentation to verify results. On the other hand, identification of linear epitopes through experimental screening has been an inefficient process that requires thorough characterization of previously identified full-length protein antigens, or laborious techniques involving genetic manipulation of organisms. In this study, we apply a newly developed generalizable screening method that enables efficient identification of B-cell epitopes in the proteomes of pathogenic bacteria. As a test case, we used this method to identify epitopes in the proteome of Francisella tularensis (Ft), a Select Agent with a well-characterized immunoproteome. Our screen identified many peptides that map to known antigens, including verified and predicted outer membrane proteins and extracellular proteins, validating the utility of this approach. We then used the method to identify seroreactive peptides in the less characterized immunoproteome of Select Agent Burkholderia pseudomallei (Bp). This screen revealed known Bp antigens as well as proteins that have not been previously identified as antigens. Although B-cell epitope prediction tools Bepipred 2.0 and iBCE-EL classified many of our seroreactive peptides as epitopes, they did not score them significantly higher than the non-reactive tryptic peptides in our study, nor did they assign higher scores to seroreactive peptides from known Ft or Bp antigens, highlighting the need for experimental data instead of relying on computational epitope predictions alone. The present workflow is easily adaptable to detecting peptide targets relevant to the immune systems of other mammalian species, including humans (depending upon the availability of convalescent sera from patients), and could aid in accelerating the discovery of B-cell epitopes and development of vaccines to counter emerging biological threats.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Dispenser Reliability: Materials R&D. A Hydrogen Fueling Infrastructure Research and Station Technology (H2FIRST) Report

Dispensers are the top cause of maintenance events and down-time at hydrogen fueling stations. In an effort to help characterize and enable improvements in dispenser reliability, an extensive accelerated lifetime testing set-up was designed and built at NREL involving components typically part of dispensing operations at fueling stations. Device Under Test (DUTs) included different components such as normally open valves, normally closed valves, fueling nozzles, breakaways devices and filters. Conditions of testing included pressures, and flow rates similar to light duty fuel cell electric vehicles fueling at -40°C, and -20°C for thousands of cycles in hydrogen. Tested components (failed and non-failed) were disassembled at SNL and polymeric O-rings were carefully retrieved and cataloged for chemical and physical characterization. Data collected was compared to similar O-rings from unexposed or non-tested components for hydrogen effects, and failure modes. Degradation analyses, based on select polymer chemistries common across all component types, their location within components, visual assessment of damage coupled with strong hydrogen effects from chemical characterization, was completed and presented to NREL and DOE. Overall, the failure rate amongst the components was not as high as expected for the test conditions. Among the component types tested, breakaways were the most susceptible to damage under these test conditions, with fueling nozzles a close second. The proper combination of selection of the right polymer and optimum component design was found to make a strong difference in component reliability under severe dispenser operating conditions. Physical degradation of polymers, rather than chemical changes due to low temperature hydrogen exposure, is more prevalent as failure mode for these test conditions. The nature and the extent of the degradation was much less at -20°C as compared to -40°C. The damage and failure rates were higher at lower temperatures than at higher test temperatures. As expected, increasing the number of cycles at the lowest test temperature (-40°C) increased damage. This indicates that cycling at the low temperature of -40°C required by SAE J2601 can reduce component life in fuel dispensing operations

08 HYDROGEN↗
DOE OSTI2021

Estrogen depletion alters osteogenic differentiation and matrix production by osteoblasts in vitro

Highlights: • Estrogen depletion accelerates osteoblast differentiation in static culture. • Mechanical stimulation exacerbated the effects of estrogen depletion on osteoblast differentiation. • Estrogen depletion alters osteoblasts capacity to produce a good quality matrix. Recent studies have revealed that the effects of estrogen deficiency are not restricted to osteoclasts and bone resorption, but that bone matrix composition is altered and osteoblasts exhibit an impaired response to mechanical stimulation. In this study, we test the hypothesis that estrogen depletion alters osteogenic differentiation and matrix production by mechanically stimulated osteoblasts in vitro. MC3T3-E1 cells were pre-treated with estrogen for 14 days, after which estrogen was withdrawn or inhibited with Fulvestrant up to 14 days. Fluid shear stress (FSS) was applied using an orbital shaker. Under estrogen depletion in static culture, osteogenic marker (ALP) and gene expression (Runx2) were decreased at 2 and after 7 days of estrogen depletion, respectively. In addition, up to 7 day the inhibition of the estrogen receptor significantly decreased fibronectin expression (FN1) under static conditions. Under estrogen depletion and daily mechanical stimulation, changes in expression of Runx2 occurred earlier (4 days) and by 14 days, changes in matrix production (Col1a1) were reported. We propose that changes in osteoblast differentiation and impaired matrix production during estrogen depletion may contribute to the altered quality of the bone and act as a contributing factor to increased bone fragility in postmenopausal osteoporosis.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Application of Peracetic Acid in Poultry Processing: Effects of Treatment Dynamics and Emerging Risk of Resistance Development in Salmonella spp.

Nontyphoidal Salmonella is a leading cause of foodborne illness, with poultry representing a major source. Peracetic acid (PAA), a widely adopted antimicrobial in poultry processing, offers advantages over traditional disinfectants but has sparked interest in its combined use with other antimicrobials and potential resistance. This review evaluates the efficacy of PAA in mitigating Salmonella in combination with other food-grade antimicrobials, explores possible synergism, efficacy under varying treatment parameters, resistance development against PAA, and its role in resistance evolution. While PAA demonstrates broad-spectrum efficacy, its performance varies with environmental parameters; higher temperatures generally enhance antimicrobial action but also accelerate PAA degradation. Organic matter diminishes PAA efficacy by reactive quenching. Variability in concentration and contact time further influences outcomes. Despite its oxidative mode of action and presumed low risk for resistance, emerging studies indicate that Salmonella can develop adaptive tolerance and potential cross/coresistance following repeated or sublethal exposure to PAA. These adaptations may involve genetic upregulation of oxidative stress response pathways, efflux systems, and modifications in cell membrane integrity, raising concerns about the long-term sustainability of PAA use. Additionally, combinatorial treatments (e.g., PAA with UV-C, enzymes, or organic acids) show promise in enhancing efficacy while mitigating resistance risks. Despite recognition of PAA's safety and effectiveness, knowledge gaps remain regarding standardized resistance definitions, serotype-specific tolerance, and optimal intervention strategies in commercial settings. Therefore, there is a need for standardized testing protocols, robust studies on potential resistance, and further exploration of synergistic PAA applications to ensure sustained poultry product safety and public health protection.

37 - INORGANIC, ORGANIC, PHYSICAL AND ANALYTICAL C↗
DOE OSTI2022

Application of FARM to an IES scenario within the FORCE ecosystem

The FARM (Feasible Actuator Range Modifier) software module is a component of the RAVEN-based FORCE framework for analysis of Integrated Energy Systems (IES). FARM supports the HERON software module in the evaluation of the optimal dispatch by evaluating feasible set-points for the different IES unit components. Set-points are required to satisfy limits on both production variables (i.e., the variables to be optimized such as the electrical power, the hydrogen production rate, etc.) and process variables tied to the service life of equipment (e.g., steam flowrate, vessel pressure, turbine firing temperature, etc.). This problem is addressed by adopting a two-stage approach. First, the HERON power dispatcher determines set-points that meet the constraints on the former variables (e.g., power levels and power ramp rate limits). These constraints are called explicit constraints. Then, FARM adjusts these set-points to ensure the respect of the limits on the latter variables given the knowledge of the system physics acquired through machine learning algorithms. These constraints are called implicit constraints. From this standpoint, FARM constitutes a bridge between the HERON power dispatcher that adopts a simplified description of the IES unit (low-resolution physics) and the HYBRID high-fidelity models (high-resolution physics). The original version of the FARM software module (FARM-Alpha) was released by Argonne National Laboratory in January 2021. In the latest version of the code released in July 2022 (FARM-Delta), the Reference Governor (RG) algorithm was upgraded to a Multi-Input Multi-Output version from its original Single-Input Single-Output form. The RG algorithm acts to enforce constraints. With this improvement an IES unit is now treated as a single dynamic system from the standpoint of control. The crosstalk among components in an IES unit is now fully considered thereby ensuring a true optimization is obtained for those units that have multiple set-points. In this report, the capabilities of FARM-Delta operating within the FORCE ecosystem are demonstrated for an IES test case. The specific configuration of IES unit for this case was selected by the IES team with consultation from the Advanced Reactor IES Expert Group. A full TEA analysis that invoked HERON, HYBRID, FARM, and RAVEN was performed and serves to demonstrate how the latest modification to FARM algorithms (i.e., state variable selection, state-space matrices derivation, set-point verification) can shape setpoints that might otherwise compromise the health of equipment through accelerated wear and tear. In this specific test case, it was demonstrated that these algorithms ensure a more efficient utilization of steam resources to be shared by two different subsystems, namely Balance of Plant (BOP) and High-Temperature Steam Electrolysis (HTSE). Finally, some code improvements that can further enhance the user-friendliness are suggested.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Engineering PHL7 for Improved Poly(Ethylene Terephthalate) Depolymerization via Rational Design and Directed Evolution

Enzymatic depolymerization of poly(ethylene terephthalate) (PET) has emerged as a promising approach for polyester recycling, and, to date, many natural and engineered PET hydrolase enzymes have been reported. For industrial use, PET hydrolases must achieve high depolymerization extent and exhibit excellent thermostability. Here, we engineered a natural PET hydrolase, Polyester Hydrolase Leipzig #7 (PHL7), through rational design and directed evolution using a high-throughput screening platform. Four new enzymes were engineered with enhanced properties compared with the parent enzyme, wild-type PHL7 (PHL7-WT), and other benchmark PET hydrolases, under the tested conditions. In bioreactors, the exemplary engineered enzyme, PHL7-Jemez, exhibited improved ability to depolymerize amorphous PET film compared with PHL7-WT at 2.9% and 20% substrate loadings, with 37% and 270% higher hydrolysis, respectively, after 48 h. This study develops several state-of-the-art PET hydrolases and demonstrates a directed evolution platform to engineer high-performance enzymes, which can accelerate enzyme discovery toward improved biocatalytic recycling.

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

What regulates decomposition in agroecosystems? Insights from reading the tea leaves

Litter decomposition is a critical Earth process, recycling nutrients and setting a portion of plant tissue on a path toward soil organic matter. Despite this importance, we still lack a good understanding of local factors that regulate decomposition, especially in agroecosystems where management plays an outsized role. Using a narrow range of climate and soils, we buried 1,308 pre-manufactured “litter bags” of differing residue quality (i.e., green and rooibos tea leaves) in 109 plots across several management practices to (1) explore the local controls on decomposition in agroecosystems and (2) test the robustness of the Tea Bag Index (TBI). We found that management practices intended to increase soil ecosystem services, that is, soil health, altered the decomposition of both teas. For example, adding nitrogen fertilizer and implementing perennial cropping decreased the extent of green tea decomposition (carbon-to-nitrogen ratio, or C:N = 12.8). No-tillage increased, but perennial cropping decreased, the rate of rooibos tea decomposition (C:N = 50.1). Cropped prairie accelerated green tea decomposition and increased the extent of red tea decomposition. A random forest regression model showed that soil temperature was the strongest predictor of green tea decomposition, but a soil health score also played a significant role in predicting the mass remaining. Soil texture and nutrient availability best predicted rooibos tea decomposition. Finer textured soils seemed to decelerate rooibos decomposition but increased the extent of decomposition. Furthermore, we demonstrated that the TBI metrics correlated somewhat well with empirically derived decomposition constants and were similarly sensitive to the effects of management. Still, the green tea stabilization factor had a substantial prediction bias. Our study increased our basic understanding of what regulates decomposition in agroecosystems. It also showed that the TBI can be a scientifically rigorous citizen science approach to monitoring changes in soil health.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

AI-Accelerated Design of Targeted Covalent Inhibitors for SARS-CoV-2

Direct-acting antivirals for the treatment of the COVID-19 pandemic caused by the SARS-CoV-2 virus are needed to complement vaccination efforts. Given the ongoing emergence of new variants, automated experimentation, and active learning based fast workflows for antiviral lead discovery remain critical to our ability to address the pandemic’s evolution in a timely manner. While several such pipelines have been introduced to discover candidates with noncovalent interactions with the main protease (M pro ), here we developed a closed-loop artificial intelligence pipeline to design electrophilic warhead-based covalent candidates. Here, this work introduces a deep learning-assisted automated computational workflow to introduce linkers and an electrophilic “warhead” to design covalent candidates and incorporates cutting-edge experimental techniques for validation. Using this process, promising candidates in the library were screened, and several potential hits were identified and tested experimentally using native mass spectrometry and fluorescence resonance energy transfer (FRET)-based screening assays. We identified four chloroacetamide-based covalent inhibitors of M pro with micromolar affinities (K I of 5.27 μM) using our pipeline. Experimentally resolved binding modes for each compound were determined using room-temperature X-ray crystallography, which is consistent with the predicted poses. The induced conformational changes based on molecular dynamics simulations further suggest that the dynamics may be an important factor to further improve selectivity, thereby effectively lowering KI and reducing toxicity. These results demonstrate the utility of our modular and data-driven approach for potent and selective covalent inhibitor discovery and provide a platform to apply it to other emerging targets.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

FY2025 Status Report: Model 9975 O Ring Fixture Long-Term Leak Performance

Leak testing experiments to monitor the aging performance of Viton® GLT and GLT-S O-rings used in the model 9975 shipping package have been ongoing since 2004 at Savannah River National Laboratory. Seventy tests using mock-up 9975 primary containment vessels (PCVs) with GLT O-rings were assembled and heated to temperatures ranging from 200 to 450 °F. Due to material substitution, fourteen tests with GLT-S O-rings were initiated in 2008 and heated to temperatures ranging from 200 to 400 °F. The conditioning temperatures are elevated compared to the calculated maximum O-ring temperature in a 9975 package in storage, 158 °F, to accelerate aging and enable observations of O-ring failures in a reasonable time frame. The mock-up PCV fixtures are leak tested periodically, and all GLT O-ring fixtures aged at 350 °F or above have failed to maintain a leak-tight seal. Eight GLT O-ring fixtures aged at 300 °F have failed after 2.8 to 5.7 years at temperature while the remaining fixtures at 300 °F were retired from testing following more than five years of aging without failure. Two of these retired fixtures were returned to testing and heated to 350 °F to evaluate the impact of additional heating at higher temperature for aged O-rings. Fixture #20 failed after 3 months while fixture #18 failed after 9 months at 350 °F. These O-rings demonstrated that aged and in-service O-rings can continue to be used, even at higher temperatures, after being in storage, and their leak performance are consistent with other samples at 350 °F. There has been one GLT O-ring fixture which failed after 13.4 years of aging at 200 °F. However, 20 other GLT O-rings aging at 200 °F have remained leak-tight for over 16.9 years and remain in test. There are two GLT O-ring fixtures at 270 °F; one fixture has failed after 12.9 years while the other fixture remains in test after 12.5 years. All GLT-S O-ring fixtures aged at 300 °F or above have failed their leak test. No failures have yet been observed in GLT-S O-ring fixtures aging at 250 °F for 14.9 years, while one GLT-S O-ring fixture failed after 12.4 years at 200 °F. The leak testing data to date suggest the GLT and GLT-S O-rings aging in the K-Area Complex (KAC) storage at temperatures of 158 °F might maintain a leak-tight seal for up to 59 years. Data from the O-ring fixtures are generally consistent with results from compression stress-relaxation testing and provide confidence in the predictive models based on those results. However, uncertainty exists in extrapolating these elevated temperature results to the lower temperatures of interest for normal storage in KAC. The collective data from these test efforts suggest the minimum O-ring service life at KAC normal storage conditions should be at least 34 years for GLT and GLT-S O-rings. Measurement of compression set in O-rings removed from failed fixtures, compared to that from KAC surveillance O-rings, indicate significant margin remains for O-rings still in service in 9975 packages in KAC. Aging and periodic leak testing will continue for the remaining 24 mock-up PCV fixtures.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Advanced Algal Biofoundries for the Production of Polyurethane Precursors

The primary goal of the BEEPs project was to develop a process that could accelerate the development of algae as bioproduction platforms, from initial chemical product concept to an economically viable market supply. Under this program we elected to develop strains of algae that could generate polyurethane precursors, while simultaneously developing basic genetic tools to enable improved algal production systems. This program was specifically designed to incorporate National Laboratories as a means to utilize the expertise and facilities for new bio-production platforms. To that end, we designed a program to collaborate with the Agile BioFoundry at Lawrence Berkeley National Laboratory (LBNL) and computational platforms at Pacific Northwest National Laboratory (PNNL). In addition to these National Laboratory partners, we also had academic partners from UC Davis and Georgia Tech, as well as commercial partners Algenesis Materials and BASF. To achieve these goals, we initially focused on developing the genetic tools and high throughput screening technologies necessary to generate and assess production of polymer precursors (succinic acid) in algae and cyanobacteria, including advanced promoters and biosensors. In parallel, we computationally identified potential production bottlenecks and then used the developed genetic tools to increase production rates and yields. Constant feedback of data was used in conjunction with machine learning, high-throughput cell sorting, and synthetic biology, for additional targeted metabolic engineering. Multiple rounds of tool design, building, testing, and learning were supplied to partners at PNNL and LBNL to develop new models and tools that could expedite bioproduction platform development and increase yield performance. We targeted, and achieved, the FOA requirement yield metric of 20 g/L, as a milestone and deliverable from at least one of our engineered strains for the production of succinic acid.

09 BIOMASS FUELS↗
DOE OSTI2021

Concentrating Rare Earth Elements in Coal mine drainage Using Coal Combustion Products through Abandoned Mine Land Reclamation

Rare earth elements (REEs) (including scandium, yttrium and a group of 15 lanthanides) are often considered to be critical components in the productions of renewable energy hardware, electric vehicles, health care and military equipment, and consumer electronic products. The demand of REEs has been projected to be growing at an annual rate of 5-9% in the next 25 years. In 2011, the global demand of total rare earth oxides (REOs) was estimated to be approximately 105,000 tons, which is expected to grow to 210,000 tons by 2025. China overwhelmingly dominates the current worldwide rare earth productions but has strategically restricted its exports, causing significant instability for the global market. In response to the increasing demand for REEs and the supply dominance of China, identifying alternative sources of REEs has become a critical issue for the United States and other countries. Coal, coal ash, and coal mine drainage (CMD) are considered to be the alternative sources of REEs. In the U.S., high REE concentrations have been reported to be closely associated with coal deposits, including the Appalachian Basins. When surface and/or groundwater come in contact with geologic strata containing sulfide minerals exposed by coal mining, the accelerated oxidation of sulfide minerals in the presence of ferric iron and/or oxygen can produce sulfuric acid. The process promotes the weathering of REE-bearing rocks and minerals in the host geologic strata. Compared to average river water and seawater, the concentrations of REEs can be orders of magnitude higher in CMD. In this study, we demonstrated a trap-extract-precipitate (TEP) process that can effectively recover REEs from CMD. The three-stage TEP process uses alkaline industrial by-products to capture REEs from CMD and then applies an extraction/precipitation procedure to produce a feedstock that can be economically processed to produce marketable rare earth oxides. The alkaline industrial by-products tested in this study include the residual from a water softening process (DRWP sludge) and two types of stabilized flue gas desulfurization materials (sFGDs). sFGD material is a mixture of lime (CaO) and two coal combustion by-products, calcium sulfite FGD by-product and fly ash. The objectives of this study are to (1) validate the effectiveness and feasibility; (2) determine mechanisms controlling the rare earth recovery, (3) quantify the associated economic and environmental benefits, and (4) evaluate the full-scale application. To achieve these objectives, tasks to be carried out in this proposed project are organized into three phases. In the first phase, the research team collaborated with Ohio Department of Natural Resources, American Electric Power, The Wilds (a nonprofit wildlife conservation organization), and a private landowner to carry out field investigations aimed to screen and evaluate the seasonal changes of rare earths in the CMD discharges that have high recovery potentials. Next, the recovery of REEs from CMD was tested using a series of lab-scale column and batch tests under, respectively, percolation and completely mixed conditions. Results obtained from these lab-scale studies show that all three tested solids are very effective in retaining REEs. Over 98% of the CMD REEs that contacted the solids were captured before the solids exhausted their neutralization capacities. We also determined an extraction process using a non-acid, organic ligand extraction solution that can effectively remobilize the retained REEs from the spent solids (over 90%). The REE concentrate (>7.5 wt. % of total REEs) is then formed in an aeration process. The TEP process uses environmentally benign industrial by-products and a naturally-occurring organic ligand to mitigate CMD and recover REEs. Techno-economic analysis (TEA) and life-cycle assessment (LCA) was carried out in the third phase. The engineering-economic costs and net energy, net CO2 emissions, and water and other requirements were investigated to understand the economic and environmental implications of this process. This work uses mass and energy balances from laboratory-scale experiments to estimate the economic costs and environmental impacts. The results suggest that passive treatment systems that use DRWP sludge are preferred over those that use sFGD material, because of lower economic costs ($89,300/yr with a unit cost of $86/gT-REE vs. $89,800/yr, or $278/gT-REE) and improved environmental performance across all indicators from two different impact assessment methods. These differences are largely attributable to the larger capacity of DRWP sludge in the passive treatment application. We envision this TEP process can be integrated with abandoned mine land (AML) reclamation to create an approach that can add economic incentives for AML reclamation, remediate CMD discharge, and eliminate public safety hazards and threats to local environment and ecological systems posed by AMLs. It can restore lands and communities that are adversely impacted by legacy mining.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2020

Mechanoadaptive strain and functional osseointegration of dental implants in rats

Spatiotemporal implant-bone biomechanics and mechanoadaptive strains in peri-implant tissue are poorly understood. Physical and chemical characteristics of an implant-bone complex (IBC) were correlated in three-dimensional space (along the length and around a dental implant) to gather insights into time related integration of the implant with the cortical portion of a jaw bone in a rat. Rats (N = 9) were divided into three experimental groups with three rats per time point; 3-, 11-, and 24-day. All rats were fed crumbled hard pellets mixed with water (soft-food diet) for the first 3 days followed by a hard-food diet with intact hard-food pellets (groups of 11- and 24-day only). Biomechanics of the IBCs harvested from rats at each time point was evaluated by performing mechanical testing in situ in tandem with X-ray imaging. The effect of physical association (contact area) of a loaded implant with adapting peri-implant tissue, and resulting strain within was mapped by using digital volume correlation (DVC) technique. The IBC stiffness at respective time points was correlated with mechanical strain in peri-implant tissue. Results illustrated that IBC stiffness at 11-day was lower than that observed at 3-day. However, at 24-day, IBC stiffness recovered to that which was observed at 3-day. Furthermore, correlative microscopy and spectroscopy illustrated that the lower IBC stiffness was constituted by softer and less mineralized peri-implant tissue that contained varying expressions of osteoconductive elements. Lower IBC stiffness observed at 11-day was constituted by less mineralized peri-implant tissue with osteoconductive elements that included phosphorus (P) which was co-localized with higher expression of zinc (Zn), and lower expression of calcium (Ca). Higher IBC stiffness at 24-day was constituted by mineralized peri-implant tissue with higher expressions of osteoconductive elements including Ca and P, and lower expressions of Zn. These spatiotemporal correlative maps of peri-implant tissue architecture, heterogeneous distribution of mineral density, and elemental colocalization underscore mechanoadaptive physicochemical properties of peri-implant tissue that facilitate functional osseointegration of an implant. These results provided insights into 1) plausible "prescription" of mechanical loads as an osteoinductive "therapeutic dose" to encourage osteoconductive elements in the peri-implant tissue that would facilitate functional osseointegration of the implant; 2) a "critical temporal window" between 3 and 11 days, and perhaps it is this acute phase during which key candidate regenerative molecules can be harnessed to accelerate osseointegration of an implant under load.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Evaluating algorithmic bias on biomarker classification of breast cancer pathology reports

Objectives: This work evaluated algorithmic bias in biomarkers classification using electronic pathology reports from female breast cancer cases. Bias was assessed across 5 subgroups: cancer registry, race, Hispanic ethnicity, age at diagnosis, and socioeconomic status. Materials and Methods: We utilized 594 875 electronic pathology reports from 178 121 tumors diagnosed in Kentucky, Louisiana, New Jersey, New Mexico, Seattle, and Utah to train 2 deep-learning algorithms to classify breast cancer patients using their biomarkers test results. We used balanced error rate (BER), demographic parity (DP), equalized odds (EOD), and equal opportunity (EOP) to assess bias. Results: We found differences in predictive accuracy between registries, with the highest accuracy in the registry that contributed the most data (Seattle Registry, BER ratios for all registries >1.25). BER showed no significant algorithmic bias in extracting biomarkers (estrogen receptor, progesterone receptor, human epidermal growth factor receptor 2) for race, Hispanic ethnicity, age at diagnosis, or socioeconomic subgroups (BER ratio <1.25). DP, EOD, and EOP all showed insignificant results. Discussion: We observed significant differences in BER by registry, but no significant bias using the DP, EOD, and EOP metrics for socio-demographic or racial categories. This highlights the importance of employing a diverse set of metrics for a comprehensive evaluation of model fairness. Conclusion: A thorough evaluation of algorithmic biases that may affect equality in clinical care is a critical step before deploying algorithms in the real world. We found little evidence of algorithmic bias in our biomarker classification tool. Artificial intelligence tools to expedite information extraction from clinical records could accelerate clinical trial matching and improve care.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Impact of Testing Method on Safety Assessment of Aged Li-Ion Cells: Part II – Aged Cells Without Li Plating

Understanding the safety profile of aged Li-ion batteries is essential for developing effective battery management and hazard mitigation strategies. However, most safety assessments have focused on fresh batteries, with just a few calorimetry studies on aged batteries with metal oxide positive electrodes. This study provides a broad assessment of commercial 18650-type Li-ion batteries with NCA, NMC, and LFP positive electrodes, both uncycled and aged under conditions that promoted solid electrolyte interphase (SEI) growth as the dominant degradation mechanism. The cells underwent mechanical (nail penetration, crush), electrical (overcharge, overdischarge), and thermal (accelerating rate calorimetry) abuse tests. Safety was rated on general characteristics such as mass loss, maximum temperature, and EUCAR (European Council for Automotive R&D) hazard level, as well as characteristics specific to individual abuse tests. Generally, aged cells with SEI growth exhibited similar or improved safety compared to uncycled cells, contrasting with our previous findings on NCA cells with Li plating as the dominant aging mechanism (Part I of this series). Yet, some tests and characteristics indicated reduced aged cell safety, such as earlier triggering of mechanical failure. These results emphasize the need to examine aged battery safety across diverse empirical techniques, degradation modes, and chemistries.

Lithium-ion cells↗
DOE OSTI2020

Design and feasibility of a novel program of cervical screening in Nigeria: self-sampled HPV testing paired with visual triage

Background: Accelerated global control of cervical cancer would require primary prevention with human papillomavirus (HPV) vaccination in addition to novel screening program strategies that are simple, inexpensive, and effective. We present the feasibility and outcome of a community-based HPV self-sampled screening program. Methods: In Ile Ife, Nigeria, 9406 women aged 30–49 years collected vaginal self-samples, which were tested for HPV in the local study laboratory using Hybrid Capture-2 (HC2) (Qiagen). HPV-positive women were referred to the colposcopy clinic. Gynecologist colposcopic impression dictated immediate management; biopsies were taken when definite acetowhitening was present to produce a histopathologic reference standard of precancer (and to determine final clinical management). Retrospective linkage to the medical records identified 442 of 9406 women living with HIV (WLWH). Results: With self-sampling, it was possible to screen more than 100 women per day per clinic. Following an audio-visual presentation and in-person instructions, overall acceptability of self-sampling was very high (81.2% women preferring self-sampling over clinician collection). HPV positivity was found in 17.3% of women. Intensive follow-up contributed to 85.9% attendance at the colposcopy clinic. Of those referred, 8.2% were initially treated with thermal ablation and 5.6% with large loop excision of transformation zone (LLETZ). Full visibility of the squamocolumnar junction, necessary for optimal visual triage and ablation, declined from 68.5% at age 30 to 35.4% at age 49. CIN2+ and CIN3+ (CIN- Cervical intraepithelial neoplasia), including five cancers, were identified by histology in 5.9 and 3.2% of the HPV-positive women, respectively (0.9 and 0.5% of the total screening population), leading to additional treatment as indicated. The prevalences of HPV infection and CIN2+ were substantially higher (40.5 and 2.5%, respectively) among WLWH. Colposcopic impression led to over- and under-treatment compared to the histopathology reference standard. Conclusion: A cervical cancer screening program using self-sampled HPV testing, with colposcopic immediate management of women positive for HPV, proved feasible in Nigeria. Based on the collected specimens and images, we are now evaluating the use of a combination of partial HPV typing and automated visual evaluation (AVE) of cervical images to improve the accuracy of the screening program.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Findings on Subtask 3.1 - Bakken Rich Gas Enhanced Oil Recovery Project

Total in-place oil for the Bakken petroleum system (BPS) (which includes the Bakken and Three Forks Formations) has been estimated to be 600 billion barrels (bbl). However, BPS wells have decline rates as high as 85% over the first 3 years of their lives, and primary recovery factors typically range from 3% to 10% of original oil in place. Given the low initial recovery rates, even small incremental productivity improvements could dramatically increase technically recoverable oil in the BPS. One potential solution is enhanced oil recovery (EOR) using gas injection, such as carbon dioxide (CO2) or hydrocarbon (HC) gases. While commonly used in conventional reservoirs, CO2 EOR in unconventional tight oil reservoirs has been limited to pilot tests. EOR using rich gas (mixture of methane, ethane, and propane) has also been employed in numerous pilots in several unconventional plays and has recently been successfully applied in the Eagle Ford play. If successful, large-scale gas-based EOR in the BPS could dramatically increase oil productivity and recovery factors and extend the life of the play for decades. While CO2 may be a technically suitable working fluid for EOR in the BPS, supplies are limited and costs for using CO2 in EOR pilots are prohibitively high. Meanwhile, produced gas flaring has presented challenges for BPS operators in North Dakota. Analysis conducted by the North Dakota Pipeline Authority indicates that the current gas-gathering infrastructure in North Dakota is insufficient to accommodate all of the associated gas that is produced from the BPS. The geographically isolated location of North Dakota relative to large natural gas markets, combined with suppressed natural gas prices, has made it economically challenging for industry to invest capital in expanding gas-gathering infrastructure in the state. These circumstances led to a research program conducted by the Energy & Environmental Research Center (EERC) in partnership with Liberty Resources Management Company LLC (LR) to examine the potential to use rich gas injection for EOR and mitigate flaring. A rich gas EOR pilot test was designed and executed by LR at its Stomping Horse development area in Williams County, North Dakota. From July 2018 through May 2019, a total of 160 million standard cubic feet (MMscf) of rich produced gas was injected into the BPS using five different wells in a sequential injection strategy. LR’s Leon–Gohrick drill spacing unit (DSU) was used as the test site. Regulatory oversight was provided by the North Dakota Industrial Commission (NDIC). Technical support was provided by the EERC through a series of laboratory, modeling, and field-based activities, and additional post-pilot research activities incorporated learnings from the test, developed new laboratory data, improved fracture modeling methods, and developed machine learning and big data analytics. The results from the Stomping Horse rich gas EOR pilot activities indicate that developing an effective, economical EOR approach for the BPS will require more field tests. Another key lesson learned from the Stomping Horse tests is that detailed pre- and posttest data on reservoir conditions and fluids production are essential. Robust reservoir characterization provides information that is crucial to creating realistic geomodels and conducting valid dynamic simulations of potential EOR scenarios. A detailed understanding of the completions and production history of offset wells is also necessary for valid test result interpretations. This knowledge is essential to designing the operational parameters of injectivity tests and interpreting the results. A conformance control strategy is also essential to success. Laboratory-based examinations of rich gas interactions with reservoir fluids and rocks were conducted, with an emphasis on determining the ability to mobilize oil in the tight reservoir rocks and shales of the BPS. Injection fluid composition was shown to have a positive impact on reducing reservoir oil minimum miscibility pressure (MMP), reducing interfacial tension (IFT), and altering wettability. IFT and contact angle measurements demonstrated that wettability can be altered in the presence of rich gas, suggesting the potential to improve oil recovery. Iterative modeling of surface infrastructure and reservoir performance using data generated by the various project activities was conducted. A geologic model of the Stomping Horse area was built; history-matched oil, gas, and water production was used in simulations of various EOR scenarios. Early programmatic modeling results were used to support LR’s design and operation of the EOR pilot and to provide insight regarding optimization of future commercial-scale BPS EOR design and operations. Post-pilot modeling focused on alternative methods of understanding complex fracture networks and accelerating simulation time. These led to improved simulation run times and provide excellent history-matching results. Several of these iterative models were used as the bases for developing algorithms into machine learning and big data analytics. History matching in reservoir simulation is time-consuming and computer processing-intensive. Machine learning algorithms were created, and an automated history-matching tool was developed. A large set of synthetic reservoir simulations were created to generate well responses (oil, gas, and water production, well bottomhole pressure [BHP], and tracer or propane breakthrough) for a set of EOR operating parameters that included offset well status (open or closed), injectate (rich gas or propane), injection rate, and injection well BHP. A user interface was developed to provide real-time visualization. Machine learning-based models were developed to provide rapid forecasting of well performance given a set of user-defined EOR operating parameters. These predictive models allow the user to modify the offset well status, injection rate, and injection well BHP and rapidly forecast future production performance. The combination of real-time visualization tools with real-time forecasting tools provides a framework for real-time control—operational changes that the EOR site operator can enact (e.g., changing gas injection rates) to affect the observed performance and potentially improve the EOR outcome. There is great reason to be optimistic about the future of EOR in the Bakken. The results of the laboratory studies suggest significant potential for high rates of oil mobilization using produced field gas injection under the right conditions. The results of the lab studies, combined with rigorous statistical analysis of well production data and associated modeling efforts, confirm the notion that fluid mobility within the reservoir is controlled by fractures. As more knowledge is gained about the nature and distribution of fracture networks in the Bakken, the industry will be in a better position to predict and, ultimately, influence fluid mobility. New field tests are necessary to develop a more complete understanding of those conditions. Thoughtful and creatively engineered field tests within a well-characterized geologic setting will yield the fundamental knowledge needed to take Bakken oil production to the next level. This subtask was cofunded through the EERC–U.S. Department of Energy Joint Program on Research and Development for Fossil Energy-Related Resources Cooperative Agreement No. DE-FE0024233. Nonfederal funding was provided by the North Dakota Industrial Commission’s Oil and Gas Research Program and Computer Modelling Group.

04 OIL SHALES AND TAR SANDS↗