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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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Alpha-decay induced shortening of fission tracks simulated by in situ ion irradiation

The diffusion of defects (e.g., vacancies and interstitials) and elements used for dating (e.g., He and Pb) in a mineral structure is a thermal process: This is the primary assumption used to determine the age and thermal history of minerals. For instance, thermal history reconstruction, through the number and length distribution of tracks produced by spontaneous fission of 238 U, is obtained by assuming a thermal event to be the only energy source for shortening of fission tracks. Here, we report a new, non-thermal energy source that induces additional shortening of fission tracks by the irradiation of alpha-recoils from the alpha-decay of 238 U and 232 Th. We simulate alpha-decay induced track-shortening by combining ion accelerator irradiations with transmission electron microscopy. This allows for the first observation of track-shrinkage during in situ ion irradiation. We show that rather than alpha-particles, alpha-recoils induce a significant shortening of fission tracks by nuclear-collisions. The shortening of track-length can be quantified as a function of alpha-decay event dose. However, apatite is less sensitive than zircon to this non-thermal process. Furthermore, the findings exemplify the interactions among different types of self-irradiation from alpha-particles, alpha-recoils and fission-fragment nuclei in single mineral grains and have important implications for the use of zircon and apatite for radiometric dating and thermochronology.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

Superconductivity Reinforces Charge-Density-Wave Phase Coherence across Cuprates

For decades, superconductivity in high-𝑇 c cuprates has been viewed as a competitor that suppresses charge-density-wave (CDW) order by reducing its amplitude and spatial extent. Here, in this study, we show that this picture is incomplete, as superconductivity is accompanied by a systematic enhancement of CDW phase coherence across multiple cuprate families. Using resonant soft x-ray scattering combined with a coherence-sensitive momentum-profile analysis, we uncover a BCS-like growth of phase coherence below 𝑇 c , which phenomenologically manifests as the absence of CDW peak broadening and near-perfect wave-vector locking. This enhancement remains visible even in a disorder-dominated regime created by long-term crystal aging and follows a common trend when compared with published data on Bi-, Hg-, Y-, and Nd-based cuprates. These results indicate that superconductivity reshapes CDW order in two distinct ways, suppressing its amplitude while strengthening its phase coherence, and reveal an additional phase-level interplay with lattice coupling in high-𝑇 c cuprates.

Lee, H. [SLAC National Accelerator Laboratory (SLA↗
DOE OSTI2020

Open Chemistry, JupyterLab, REST, and quantum chemistry

Quantum chemistry must evolve if it wants to fully leverage the benefits of the internet age, where the worldwide web offers a vast tapestry of tools that enable users to communicate and interact with complex data at the speed and convenience of a button press. The Open Chemistry project has developed an open-source framework that offers an end-to-end solution for producing, sharing, and visualizing quantum chemical data interactively on the web using an array of modern tools and approaches. These tools build on some of the best open-source community projects such as Jupyter for interactive online notebooks, coupled with 3D accelerated visualization, state-of-the-art computational chemistry codes including NWChem and Psi4, and emerging machine learning and data mining tools such as ChemML and ANI. They offer flexible formats to import and export data, along with approaches to compare computational and experimental data.

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

Creep ductility limiting mechanisms in an additively manufactured Al-Ce-Ni-Mn-Zr alloy

Tensile creep response and cavitation damage evolution in an additively manufactured Al-7.5Ce-4.5Ni-0.4Mn-0.7Zr (wt%) alloy with peak-aging and overaging treatments were investigated in the 300–400 ºC range. Microstructural heterogeneity and its response to heat treatment and subsequent creep deformation were studied to understand the interplay between cavity formation, creep lifetime and ductility. Increasing the applied stress activated the nucleation of more cavities, an experimental observation that is well described using the vacancy accumulation model. Cavities nucleated prematurely due to localized plasticity in the denuded zones that formed at/near melt-pool or grain boundaries. Microstructure/deformation heterogeneity with consequent evolution of stress triaxiality, especially at lower stresses, causes accelerated cavitation, thus producing low creep ductility (∼ 0.2–2.4 %), compared to (∼12–21 %) ductility of the alloy measured by regular tensile tests at equivalent temperatures. A constrained diffusional cavity growth mechanism with continuous cavity nucleation during creep is established as the dominant mechanism, implying that cavitation involves vacancy diffusion, yet its growth rate is dictated by the minimum creep rate. In conclusion, the ductility-limiting creep and cavitation mechanisms discussed here provide new insight into the creep behavior of 3D-printed metallic alloys.

Additive manufacturing↗
DOE OSTI2021

Battery Performance, Thermal, and Life Modeling for Southern California Edison (Cooperative Research and Development Final Report)

The objective of this project is to develop battery performance models, thermal models and life models for SCE to use in simulation and analysis of grid services involving energy storage. NREL will fit the models to three separate chemistries using test data provided by SCE. The dataset for each chemistry will include electrical, thermal and aging response to different temperatures and cycling conditions, measured under a variety of cell-level and module-level experiments described in SCE test protocol documents. Once tuned to a test dataset, the battery system model software will provide predictions of battery energy and power loss, and thus cycle and calendar life, for any energy storage grid service power profile of interest to SCE. The automated battery life modeling and simulation tool can also be applied to any other grid battery systems as long as necessary input data is available to accelerate battery model development and battery lifetime analysis.

25 ENERGY STORAGE↗
DOE OSTI2023

PV encapsulant formulations and stress test conditions influence dominant degradation mechanisms

Polyethylene-based poly(ethylene-co-vinyl acetate) (EVA), polyolefin elastomer (POE), and thermoplastic polyolefin (TPO) are common polymer candidates for photovoltaic (PV) module encapsulants. The choice of encapsulant must be carefully considered in novel module designs, such as bifacial glass/glass laminates, to limit performance degradation through loss of optical transmittance, mechanical integrity, and corrosion - as well as potential-induced degradation. Encapsulant quality and resilience against environmental stressors are readily influenced by the additives in the encapsulant formulation. Here, we show that, the changes in optical transmittance after UV aging result from the discoloration caused by interactions between additives, and optical scattering from changes in the polymer crystal structure. We observed competing cross-linking and chain scission mechanisms, with their kinetics influenced by the presence of oxygen and elevated temperatures. Increasing chamber temperatures from 55 °C to 85 °C during the UV stress test amplified encapsulant discoloration and promoted polymer cross-linking, causing severe, irreversible damage that remains to be proven field relevant. Damp heat aging was found to be insufficient to produce significant encapsulant degradation; however, combining stress tests sequentially allowed detection of further degradation beyond the limitations of the damp heat test alone. Appropriate degradation screening methods are necessary to uncover potential encapsulant weaknesses.

14 SOLAR ENERGY↗
DOE OSTI2025

A formal Fe III/V redox couple in an intercalation electrode

Iron redox cycling between low-valent oxidation states of Fe II and Fe III drives crucial processes in nature. The Fe II/III redox couple charge compensates the cycling of lithium iron phosphate, a positive electrode (cathode) for lithium-ion batteries. High-valent iron redox couples, involving formal oxidation higher than Fe III , could deliver higher electrochemical potentials and energy densities. However, because of the instability of high-valent Fe electrodes, they have proven difficult to probe and exploit in intercalation systems. Here, in this study, we report and characterize a formal Fe III/V redox couple by revisiting the charge compensation mechanism of (de)lithiation in Li 4 FeSbO 6 . Valence-sensitive experimental and computational core-level spectroscopy reveal a direct transition from Fe III (3d 5 ) to a negative-charge-transfer FeV (3d 5 L 2 ) ground state on delithiation, without forming Fe IV , or oxygen dimers. We identify that the cation ordering in Li 4 FeSbO 6 drives a templated phase transition to stabilize the unique Fe V species and demonstrate that disrupting cation ordering suppresses the Fe III/V redox couple. Exhibiting resistance to calendar aging, high operating potential and low voltage hysteresis, the Fe III/V redox couple in Li 4 FeSbO 6 provides a framework for developing sustainable, Fe-based intercalation cathodes for high-voltage applications.

Ramachandran, Hari [Stanford Univ., CA (United Sta↗
DOE OSTI2022

Interplay of Electrode Heterogeneity and Lithium Plating

Lateral microstructure heterogeneity in anodes is known to induce nonuniform current density, state of charge, and lithium plating. This means that such electrode heterogeneity can limit the fast charging of lithium-ion batteries. In this work, a combination of experiments and simulation is employed to understand the effect of mm scale lateral heterogeneity on cell aging. A previously developed model was extended to efficiently simulate SEI formation and Li plating for independent regions of an electrode. The model consists of three parallel regions each described under a P2D framework and with a distinct ionic resistance and possibly active material loading. The results suggest that during fast charge when the active material is uniformly distributed across the three regions, the region with the highest resistance reaches the end of life sooner than the other regions. There is also positive feedback from Li metal filling the pores near the separator interface that further accelerates lithium plating. Lastly, when there is a non-uniform active material distribution associated with the ionic resistance heterogeneity, tight competition between regions can occur, leading to less overall lithium plating and plating that is more uniform between regions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Nitrogen‐Nitrogen Bond Breaking in Irradiation Products of Hexanitrohexaazaisowurtzitane (CL‐20)

While the primary result of an interaction of ionizing radiation with an organic material is the ejection of electrons from molecular orbitals producing cations, the free electrons can further interact, yielding excited states; and, potentially, anions. In this work, we computed reaction barriers and energies for N−N bond breaking in the CL-20 cation, anion, and excited state to investigate if CL-20 degradation is accelerated after radiation exposure. We focused on N−N bond dissociation because it is the rate-determining step in the thermal degradation of CL-20. We found that N−N cleavage rapidly takes place in the CL-20 cation and anion with greatly reduced reaction energies as compared to CL-20. We also outlined a potential path for photodissociation of the N−N bond. While CL-20 is kinetically stable, initial degradation occurs readily in its irradiation products. In conclusion, this is of importance for the performance of the explosive after high-dose exposure and influences aging if CL-20 is irradiated at a low dose over extended periods of time.

CL-20 anion↗
DOE OSTI2021

Learning to Rank in the Age of Muppets: Effectiveness–Efficiency Tradeoffs in Multi-Stage Ranking

It is well known that rerankers built on pretrained transformer models such as BERT have dramatically improved retrieval effectiveness in many tasks. However, these gains have come at substantial costs in terms of efficiency, as noted by many researchers. In this work, we show that it is possible to retain the benefits of transformer-based rerankers in a multi-stage reranking pipeline by first using feature-based learning-to-rank techniques to reduce the number of candidate documents under consideration without adversely affecting their quality in terms of recall. Applied to the MS MARCO passage and document ranking tasks, we are able to achieve the same level of effectiveness, but with up to 18 increase in efficiency. Furthermore, our techniques are orthogonal to other methods focused on accelerating transformer inference, and thus can be combined for even greater efficiency gains. A higher-level message from our work is that, even though pretrained transformers dominate the modern IR landscape, there are still important roles for “traditional” LTR techniques, and that we should not forget history.

catalysis↗
DOE OSTI2022

Image transformers for classifying acute lymphoblastic leukemia

Cancer is the leading cause of death by disease in American children. Each year, nearly 16,000 children in the United States and over 300,000 children globally are diagnosed with cancer. Leukemia is a form of blood cancer that originates in the bone marrow and accounts for one-third of pediatric cancers. This disease occurs when the bone marrow contains 20% or more immature white blood cell blasts. Acute lymphoblastic leukemia is the most prevalent leukemia type found in children, with half of all annual cases in the U.S. diagnosed for subjects under 20 years of age. To diagnose acute lymphoblastic leukemia, pathologists often conduct a morphological bone marrow assessment. This assessment determines whether the immature white blood cell blasts in bone marrow display the correct morphological characteristics, such as size and appearance of nuclei. Pathologists also use immunophenotyping via multi-channel flow cytometry to test whether certain antigens are present on the surface of blast cells; the antigens are used to identify the cell lineage of acute lymphoblastic leukemia. These manual processes require well-trained personnel and medical professionals, thus being costly in time and expenses. Computerized decision support via machine learning can accelerate the diagnosis process and reduce the cost. Training a reliable classification model to distinguish between mature and immature white blood cells is essential to the decision support system. Here, we adopted the Vision Transformer model to classify white blood cells. The Vision Transformer achieved superb classification performance compared to state-of-the-art convolutional neural networks while requiring less computational resources for training. Additionally, the latent self-attention architecture provided attention maps for a given image, providing clues as to which portion(s) of the image were significant in decision-making. We applied the Vision Transformer model and a convolutional neural network model to an acute lymphoblastic leukemia classification dataset of 12,528 samples and achieved accuracies of 88.4% and 86.2%.

Cho, Priscilla↗
DOE OSTI2023

Rapid and robust squashed spore/colony PCR of industrially important fungi

Fungi have been utilized for centuries in medical, agricultural, and industrial applications. Development of systems biology techniques has enabled the design and metabolic engineering of these fungi to produce novel fuels, chemicals, and enzymes from renewable feedstocks. Many genetic tools have been developed for manipulating the genome and creating mutants rapidly. However, screening and confirmation of transformants remain an inefficient step within the design, build, test, and learn cycle in many industrial fungi because extracting fungal genomic DNA is laborious, time-consuming, and involves toxic chemicals. In this study we developed a rapid and robust technique called “Squash-PCR” to break open the spores and release fungal genomic DNA as a template for PCR. The efficacy of Squash-PCR was investigated in eleven different filamentous fungal strains. Clean PCR products with high yields were achieved in all tested fungi. Spore age and type of DNA polymerase did not affect the efficiency of Squash-PCR. However, spore concentration was found to be the crucial factor for Squash-PCR in Aspergillus niger, with the dilution of starting material often resulting in higher PCR product yield. We then further evaluated the applicability of the squashing procedure for nine different yeast strains. We found that Squash-PCR can be used to improve the quality and yield of colony PCR in comparison to direct colony PCR in the tested yeast strains. The developed technique will enhance the efficiency of screening transformants and accelerate genetic engineering in filamentous fungi and yeast.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Cosmogenic surface exposure ( 10 Be) dating of raised beaches in Marguerite bay, Antarctic Peninsula: Implications for relative sea-level history

Understanding the dynamics of ice mass loss in polar regions is crucial for deciphering climate change and Glacio Isostatic Adjustment patterns. This study focuses on Marguerite Bay, located in the south-central Antarctic Peninsula. We dated raised beaches to investigate relative sea-level changes using the cosmogenic surface exposure ( 10 Be) method. Previous studies have provided valuable insights into the region's glacial history, but limitations in dating techniques and age estimates necessitate further investigation. By analysing raised shingle beaches in Gaul Cove of Horseshoe Island and the southern coast of Calmette Bay, this research aims to contribute relative sea-level change history for these areas. In Horseshoe Island's Gaul Cove, raised beaches clustered on prominent steps reveal a 15 m relative sea-level change over the last 3.31 ka. Differently, Calmette Bay exhibits a 36 m relative sea-level fall over the last 7.29 ka. Finally, these findings indicate significant and differential glacial-isostatic adjustments in both regions during the middle and late Holocene. Additionally, our data reveal accelerated sea-level fall periods corresponding to Holocene deglaciation and glacial advance events, indicating the shorelines' relative sea-level change sensitivity to climate change.

58 GEOSCIENCES↗
DOE OSTI2021

Cyberbiosecurity and Public Health in the Age of COVID-19

Cyberbiosecurity, the aspect of biosecurity involving the digital representation of biological data, had already been emerging as a matter of public concern even prior to the onset of the COVID-19 pandemic. Key issues of concern include, among others, the privacy of patient data, the security of public health databases, the integrity of diagnostic test data, the integrity of public biological databases, the security implications of automated laboratory systems and the security of proprietary biological engineering advances. With the onset of the COVID-19 pandemic, and the importance of digital resources in combatting it, concern about the potential for cyber attacks by state-based or non-state actors has been elevated. To illuminate the challenges, we focus on the cyber vulnerabilities that need to be addressed in public health activities such as disease surveillance and outbreak management. In particular, we examine cyber issues raised by the accelerated pace of development for COVID mitigations, treatments, and vaccines.

cybersecurity, biosecurity↗
DOE OSTI2025

X-rays from inelastic dark matter freeze-in

We study inelastic dark matter produced via freeze-in through a light mediator with a mass splitting below the electron-positron threshold. In this regime, the heavier dark matter state is naturally long-lived compared to the age of the Universe and decays to the lighter state in association with photons. Given a light mediator, the dark matter abundance is directly related to the decay rate of the heavier dark matter. We show that observations of photons from the Galactic Center can effectively probe inelastic dark matter freeze-in with mediators at the 100 MeV scale and dark matter at the GeV scale.

Krnjaic, Gordan [Fermi National Accelerator Labora↗
DOE OSTI2023

2022 Prentice Award Lecture: Advancing Retinal Imaging and Visual Function in Patient Management and Disease Mechanisms

Patient-based research plays a key role in probing basic visual mechanisms. Less-well recognized is the role of patient-based retinal imaging and visual function studies in elucidating disease mechanisms, which are accelerated by advances in imaging and function techniques and are most powerful when combined with the results from histology and animal models. A patient's visual complaints can be one key to patient management, but human data are also key to understanding disease mechanisms. Unfortunately, pathological changes can be difficult to detect. Before advanced retinal imaging, the measurement of visual function indicated the presence of pathological changes that were undetectable with existing clinical examination. Over the past few decades, advances in retinal imaging have increasingly revealed the unseen. This has led to great strides in the management of many diseases, particularly diabetic retinopathy and macular edema, and age-related macular degeneration. It is likely widely accepted that patient-based research, as in clinical trials, led to such positive outcomes. Both visual function measures and advanced retinal imaging have clearly demonstrated differences among retinal diseases. Contrary to initial thinking, sight-threatening damage in diabetes occurs to the outer retina and not only to the inner retina. This has been clearly indicated in patient results but has only gradually entered the clinical classifications and understanding of disease etiology. There is strikingly different pathophysiology for age-related macular degeneration compared with photoreceptor and retinal pigment epithelial genetic defects, yet research models and even some treatments confuse these. It is important to recognize the role that patient-based research plays in probing basic visual mechanisms and elucidating disease mechanisms, combining these findings with the concepts from histology and animal models. Thus, this article combines sample instrumentation from my laboratory and progress in the fields of retinal imaging and visual function.

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 OSTI2021

Identification of Life Models for Li-Ion Batteries Using Penalized Regression and Bilevel Optimization

Reduced-order physics-based life models are extremely useful for rapidly predicting battery state-of-health and for simulating battery lifetime in arbitrary aging conditions. However, identification of well-parameterized models is difficult. This is because, for maximum usefulness in predicting lifetime under a variety of conditions, aging test data exhibits many degradation mechanisms, which all need to be accurately modeled. However, because aging tests are time-consuming and expensive, especially for large-format batteries, a minimum of tests are conducted while probing many stress factors. Building a well-parameterized model is then very challenging: an under-parameterized model will neglect critical degradation modes, and an over-parameterized model will extrapolate poorly to new testing conditions. To complicate this matter, the functional form of the model for any individual degradation rate can be very difficult to identify. In this work, the statistical tools of penalized regression and bilevel optimization are used to help identify both the functional forms of and optimize the parameters of reduced-order life models, accelerating identification of robust models. Model robustness is demonstrated through traditional statistics methods of cross-validation and sensitivity analysis, uncertainty quantification through bootstrap resampling and Monte-Carlo simulation, and simulation of real-world use cases.

47 OTHER INSTRUMENTATION↗