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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 OSTI2024

Viability of Additively Manufactured Electrodes for Lithium-Ion Batteries

As the global economy becomes increasingly electrified, the demand for batteries and energy storage is expected to rise significantly, particularly in the transportation and electricity sectors. Lithium-ion batteries (LIBs) are currently the most advanced and widely used technology in this field. Traditionally, LIBs are manufactured using simple 2D planar geometries to maximize production efficiency and minimize costs. However, this approach limits energy density due to the restricted design flexibility of the electrodes. Additive manufacturing (AM) offers a promising solution to enhance the energy density and efficiency of LIBs by enabling the design of architectures that reduce diffusive losses and allow for a greater amount of active material to be incorporated within the same device footprint, thereby minimizing the use of inactive materials. Different AM techniques come with their own set of limitations, including printing speed, material compatibility, and scale, which must be considered when designing electrodes. Scalable and cost-effective methods are particularly important for electric vehicle batteries, while achieving higher energy densities in microbatteries is crucial for the miniaturization of wearable electronics and medical devices. Here, in this study, we simulate various 3D porous electrode designs for LIBs using graphite and nickel manganese cobalt oxide (NMC) electrodes. These designs are selected to represent structures that could be produced using different AM techniques, such as direct ink writing, fused deposition modeling, and stereolithography. Our results indicate that at higher charging rates and increased areal mass loading, 3D structures can outperform traditional 2D electrodes, although the benefits may diminish with more complex designs that are harder to manufacture. The observed gains in energy density are attributed to improved electrode utilization and reduced diffusive energy losses. This comprehensive analysis of structure–performance relationships will provide valuable insights to guide future research on 3D designs, material selection, and AM techniques for additively manufactured battery electrodes.

25 ENERGY STORAGE↗
DOE OSTI2021

COVID-19 Evidence Accelerator: A parallel analysis to describe the use of Hydroxychloroquine with or without Azithromycin among hospitalized COVID-19 patients

Background: The COVID-19 pandemic remains a significant global threat. However, despite urgent need, there remains uncertainty surrounding best practices for pharmaceutical interventions to treat COVID-19. In particular, conflicting evidence has emerged surrounding the use of hydroxychloroquine and azithromycin, alone or in combination, for COVID-19. The COVID-19 Evidence Accelerator convened by the Reagan-Udall Foundation for the FDA, in collaboration with Friends of Cancer Research, assembled experts from the health systems research, regulatory science, data science, and epidemiology to participate in a large parallel analysis of different data sets to further explore the effectiveness of these treatments. Methods: Electronic health record (EHR) and claims data were extracted from seven separate databases. Parallel analyses were undertaken on data extracted from each source. Each analysis examined time to mortality in hospitalized patients treated with hydroxychloroquine, azithromycin, and the two in combination as compared to patients not treated with either drug. Cox proportional hazards models were used, and propensity score methods were undertaken to adjust for confounding. Frequencies of adverse events in each treatment group were also examined. Results: Neither hydroxychloroquine nor azithromycin, alone or in combination, were significantly associated with time to mortality among hospitalized COVID-19 patients. No treatment groups appeared to have an elevated risk of adverse events. Conclusion: Administration of hydroxychloroquine, azithromycin, and their combination appeared to have no effect on time to mortality in hospitalized COVID-19 patients. Continued research is needed to clarify best practices surrounding treatment of COVID-19.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Unstructured clinical notes within the 24 hours since admission predict short, mid & long-term mortality in adult ICU patients

Mortality prediction for intensive care unit (ICU) patients is crucial for improving outcomes and efficient utilization of resources. Accessibility of electronic health records (EHR) has enabled data-driven predictive modeling using machine learning. However, very few studies rely solely on unstructured clinical notes from the EHR for mortality prediction. In this work, we propose a framework to predict short, mid, and long-term mortality in adult ICU patients using unstructured clinical notes from the MIMIC III database, natural language processing (NLP), and machine learning (ML) models. Depending on the statistical description of the patients’ length of stay, we define the short-term as 48-hour and 4-day period, the mid-term as 7-day and 10-day period, and the long-term as 15-day and 30-day period after admission. We found that by only using clinical notes within the 24 hours of admission, our framework can achieve a high area under the receiver operating characteristics (AU-ROC) score for short, mid and long-term mortality prediction tasks. The test AU-ROC scores are 0.87, 0.83, 0.83, 0.82, 0.82, and 0.82 for 48-hour, 4-day, 7-day, 10-day, 15-day, and 30-day period mortality prediction, respectively. We also provide a comparative study among three types of feature extraction techniques from NLP: frequency-based technique, fixed embedding-based technique, and dynamic embedding-based technique. Lastly, we provide an interpretation of the NLP-based predictive models using feature-importance scores.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Experimental High Energy Physics at the University of Illinois

This research effort funded by the Office of High Energy Physics in the U.S. Department of Energy is aimed at exploring our universe at its most basic level. The goal of our effort is to learn more about how and why nature behaves the way it does. Within this effort, we are studying the smallest particles and the largest distances we can possibly observe. Our work in particular focuses on the search for new interactions that will help us understand how the universe came into being. Through this work, we collaborate with other scientists and engineers to develop new technologies that can be utilized throughout society. Benefits from our research include advances in medical technology, electronics, transportation, sustainability, information and computing as well as the advanced training of undergraduate and graduate students in science and engineering.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

2020 Medical Device Sterilization Workshop: Continuing the Conversation, Summary Report

Technical advancements are making accelerator-based sources of radiation viable candidates for sterilization of medical devices. Electron beams and x-rays are becoming more cost-competitive and new facilities are being built to provide needed capacity and redundancy. As the industry becomes more receptive to these modalities, there is a need for information and data to enable prospective users to evaluate these options for their products. The workshops offered in 20191 and now in 2020 strive to foster conversation between device manufacturers, equipment and service providers on needs, capabilities, and knowledge.

43 PARTICLE ACCELERATORS↗
DOE OSTI2026

Cost-Benefit Assessment of Additive Manufacturing for Injection Molds

This report presents an additive-manufacturing (AM) technology, where AM Cyclic Olefin Resin (COR) molds would be used for injection molding. The National Laboratory of the Rockies (NLR) team has focused on the costs and economics of this developing technology. This report presents a cost-benefit analysis of using the polySpectra AM COR molds made of COR, at the start of the project (Present') and the potential lifetime, cost-effectiveness, and performance by the end of the project period (Period 3'). The analysis of the AM COR molds is compared to traditional Computer Numerical Control (CNC) machined aluminum molds across the time periods. A cost-benefit model framework has been developed to evaluate AM COR molds. This model accounts for mold delivery to customers, current and future levels of technology readiness, the type of material injected, and various business cases. AM COR molds offer a major advantage in lead time, reducing production setup from weeks or months (with CNC machining) to as little as two to five days. This enables faster prototyping, quicker design cycles, and accelerated time-to-market, critical in industries like electronics, aerospace, medical devices, and automotive. Even modest improvements in the durability of polySpectra AM COR molds show the potential for these molds to complement traditional tooling. With further development, AM COR mold technology could provide significant time and cost savings while supporting increased domestic manufacturing capacity.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Deformable phrase level attention: A flexible approach for improving AI based medical coding

Objective: Improving the AI-driven automated medical encoding of clinical text plays a vital role in gathering information on the occurrence of diseases to improve population-level health. This work presents a novel attention mechanism designed to enhance text classification models and ensure appropriate classification of medical concepts in unstructured electronic health records. Materials and Methods: We developed a deformable, phrase-level attention mechanism to identify important lexical word-level and contextual phrase-level information from clinical text documents. We evaluated conventional and transformer-based deep learning models that we extended with our attention mechanism on the extraction of critical cancer information (e.g., site, subsite, laterality, histology, behavior) from 629,908 electronic pathology reports and on the automated medical encoding of 52,722 hospital discharge summaries. Results: Transformer-based models with the deformable, phrase-level attention mechanism achieved the best performance on the extraction of critical cancer information from pathology reports. Conventional- and transformer-based models show similar or better performance than their baseline counterparts on the automated medical encoding of clinical documents. Discussion: The addition of phrase-level information allowed models extended with our proposed method to outperform standard word-level attention. Our method showed favorable properties for the real-world application in terms of model robustness and phenotyping. These results indicate that our method is promising for automated data harmonization for common data models. Conclusion: This work proposes a novel deformable, phrase-level attention mechanism that enhances text classification models in the extraction of medical concepts from clinical text documents. We demonstrate strong performances on two clinical text datasets and showcase real-world deployability of our method.

Automated medical encoding↗
DOE OSTI2024

Connecting radiation-driven changes in structural, thermal, and mechanical properties in several medical device polymers

Stemming from security threats and shortages in supply, a recent push has emerged to develop alternatives to radioisotope Cobalt-60 gamma radiation for sterilization of polymeric medical products, including electron beam (e-beam) and X-ray machine-based sources. However, before large-scale implementation, the effects of these non-isotope-based methods must be thoroughly investigated from several perspectives, involving their potential detrimental effects on the structural, thermal, and mechanical properties of polymers in medical devices. This paper investigates such effects in commonly used medical device polymers, including polypropylene homopolymer (PPH), polyolefin elastomer (POE), low-density polyethylene (LDPE), acrylonitrile butadiene styrene (ABS), and chlorobutyl rubber (CIIR). To connect radiation-driven changes in polymer structural and thermal properties and corresponding changes in mechanical properties, several characterization techniques were utilized, including gel permeation chromatography (GPC), Fourier transform infrared spectroscopy (FTIR), dynamic mechanical analysis (DMA) and differential scanning calorimetry (DSC). We found that the tensile strength of X-ray irradiated PPH, as well as X-ray, e-beam, and gamma irradiated CIIR decreases due to chain scission, which is corroborated by GPC and DMA. The GPC results of LDPE suggest chain scission, but interestingly without a corresponding decline in tensile strength. By comparison, POE and ABS appear to undergo further crosslinking with increasing irradiation dose, which generally strengthens them. Importantly, in the vast majority of the cases, there were small to no changes in properties upon changing radiation technologies (at a given dose), i.e., no radiation source dependence. However, in a few specific cases, radiation method dependencies did arise, for instance, in terms of the molecular weight of PPH being significantly increased upon X-ray irradiation, while the melting temperature, glass transition temperature, and elongation at break reduced compared to gamma. Overall, this study provides valuable insight into radiation-driven chemical and structural changes in polymers that produce changes in physical and functional properties.

36 MATERIALS SCIENCE↗
DOE OSTI2022

A Phenome-Wide Association Study of genes associated with COVID-19 severity reveals shared genetics with complex diseases in the Million Veteran Program

The study aims to determine the shared genetic architecture between COVID-19 severity with existing medical conditions using electronic health record (EHR) data. We conducted a Phenome-Wide Association Study (PheWAS) of genetic variants associated with critical illness (n = 35) or hospitalization (n = 42) due to severe COVID-19 using genome-wide association summary data from the Host Genetics Initiative. PheWAS analysis was performed using genotype-phenotype data from the Veterans Affairs Million Veteran Program (MVP). Phenotypes were defined by International Classification of Diseases (ICD) codes mapped to clinically relevant groups using published PheWAS methods. Among 658,582 Veterans, variants associated with severe COVID-19 were tested for association across 1,559 phenotypes. Variants at the ABO locus (rs495828, rs505922) associated with the largest number of phenotypes (n rs495828 = 53 and n rs505922 = 59); strongest association with venous embolism, odds ratio (OR rs495828 1.33 (p = 1.32 x 10 –199 ), and thrombosis OR rs505922 1.33, p = 2.2 x10 -265 . Among 67 respiratory conditions tested, 11 had significant associations including MUC5B locus (rs35705950) with increased risk of idiopathic fibrosing alveolitis OR 2.83, p = 4.12 × 10 –191 ; CRHR1 (rs61667602) associated with reduced risk of pulmonary fibrosis, OR 0.84, p = 2.26× 10 –12 . The TYK2 locus (rs11085727) associated with reduced risk for autoimmune conditions, e.g., psoriasis OR 0.88, p = 6.48 x10 -23 , lupus OR 0.84, p = 3.97 x 10 –06 . PheWAS stratified by ancestry demonstrated differences in genotype-phenotype associations. LMNA (rs581342) associated with neutropenia OR 1.29 p = 4.1 x 10 –13 among Veterans of African and Hispanic ancestry but not European. Overall, we observed a shared genetic architecture between COVID-19 severity and conditions related to underlying risk factors for severe and poor COVID-19 outcomes. Differing associations between genotype-phenotype across ancestries may inform heterogenous outcomes observed with COVID-19. Divergent associations between risk for severe COVID-19 with autoimmune inflammatory conditions both respiratory and non-respiratory highlights the shared pathways and fine balance of immune host response and autoimmunity and caution required when considering treatment targets.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Lightweight, Flexible Electromagnetic Shielding Composite Films Reinforced with Recycled Carbon Fibers and Carbon Nanofillers

Lightweight, flexible polymer composites are widely adopted in modern electronic devices and systems for high-efficiency electromagnetic interference (EMI) shielding. Reinforcing polymer composites with conductive fillers offers a promising alternative to conventional metal-based shielding material thanks to their low density, tunable properties, and flexibility. Herein, lightweight, flexible ultra-high molecular weight polyethylene composite films reinforced with recycled carbon fibers (rCFs) and carbon-based nanofillers, including graphene nanoplatelets (GNPs) and carbon nanotubes, are reported for EMI shielding applications. The incorporation of these nanofillers significantly reduces the required content of rCFs and improves processability while maintaining comparable shielding effectiveness. The addition of these nanofillers with rCFs enhances the EMI shielding effectiveness by up to 15 dB. Incorporating 1 wt% GNPs can replace 5 wt% rCFs and achieve comparable EMI shielding performance, while 5 wt% of either nanofillers can substitute for 10 wt% rCFs. Numerical modeling of electromagnetic wave transmission reveals that increasing nanofiller concentrations enhances both reflection and absorption losses, with absorption consistently dominating across all levels. Furthermore, this study not only provides insight into the synergistic contributions of rCFs and carbon nanofillers to shielding effectiveness but also paves the way for the design of sustainable, lightweight EMI shielding composite films for applications in electric vehicles, medical equipment, and portable electronics.

carbon nanofiller↗
DOE OSTI2020

A Multimodal Approach to Materials Design for Next Generation Energy Storage Systems

While batteries of various chemistries have been responsible for powering everything from small electronics to cars to medical devices, the need for energy storage continues to increase. This increase is in both volume and in scale, as energy storage systems are increasingly being evaluated for inclusion into both larger and broader applications. An important factor to consider with batteries is the end application, as each chemistry and battery system has specific benefits as well as limitations. This necessitates development of a wide range of battery chemistries as well as substantive improvements to these chemistries and their integration on the material, electrode, and systems level. Herein, this work will present on a multi-scale level, different energy storage studies can that are geared to address the demands and needs of varying applications. To highlight the diversity and uniqueness of the required breadth of approaches, several systems are presented in combination with different characterization techniques and analysis relevant to the system. Highlights include proof of concept and development of a self - forming, rechargeable solid state battery, materials development for Lithium Sulfur (Li-S) batteries, electrochemical and characterization techniques to elucidate materials properties, and utilizing theoretical calculations to compliment experimental observations.

Abraham, Alyson↗
DOE OSTI2023

X-ray induced electron and ion fragmentation dynamics in IBr

Characterization of the inner-shell decay processes in molecules containing heavy elements is key to understanding x-ray damage of molecules and materials and for medical applications with Auger-electron-emitting radionuclides. The 1s hole states of heavy atoms can be produced by absorption of tunable x rays and the resulting vacancy decays characterized by recording emitted photons, electrons, and ions. The 1s hole states in heavy elements have large x-ray fluorescence yields that transfer the hole to intermediate electron shells that then decay by sequential Auger-electron transitions that increase the ion’s charge state until the final state is reached. In molecules, the charge is spread across the atomic sites, resulting in dissociation to energetic atomic ions. We have used x-ray/ion coincidence spectroscopy to measure charge states and energies of Iq+ and Brq′+ atomic ions following 1s ionization at the I and Br K-edges of IBr. We present the charge states and kinetic energies of the two correlated fragment ions associated with core-excited states produced during the various steps of the cascades. Here, to understand the dynamics leading to the ion data, we develop a computational model that combines Monte-Carlo/Molecular-Dynamics (MC/MD) simulations with a classical over-the-barrier model to track inner-shell cascades and redistribution of electrons in valence orbitals and nuclear motion of fragments.

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

Effects of gamma, electron beam, and X-ray irradiation on the plastic components of a universal bone cement mixer medical device

Due to market and regulatory pressures, many healthcare manufacturers are considering alternatives to cobalt-60 gamma radiation, including accelerator-based electron beam (E-beam) and X-ray radiation for product sterilization. In this work, the effects of irradiation on a representative medical product, comprised of eight distinct polymer materials, were directly compared for three radiation technologies – cobalt-60 gamma, E-beam, and X-ray – at four dose levels (15, 25, 50, and 70 kGy). The objective was to determine how radiation effects (deleterious or beneficial) are influenced by source and dose level, with the specific goal of determining whether E-beam radiation and/or X-ray radiation could be viable alternatives to gamma radiation for device sterilization. Here, the specific product considered is a single-use medical device for orthopedic surgery, the Stryker Instruments MixeVac III bone cement mixer, which is currently sterilized using gamma radiation from cobalt-60 sources. Following ASTM International standards and input from the manufacturer, we characterized the effects of the three radiation sources on product functionality as well as on the mechanical and optical properties of the constituent polymers. Results indicate that although measurable differences in properties between the standard gamma irradiated materials and the alternative E-beam and X-ray irradiated materials were observed, those differences were small. Statistically significant differences were noted in the case of yellowness index for polyvinyl chloride, high-density polyethylene, and polycarbonate, and in the case of tensile elongation at break for high impact polystyrene and polyvinyl chloride. In general, the results of this study support the viability of E-beam and X-ray radiation as alternative options to cobalt-60 gamma radiation for sterilization of Stryker single-use universal bone cement mixer medical devices.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Optically Excited Lasing in a Cavity‐Based, High‐Current‐Density Quantum Dot Electroluminescent Device

Abstract Laser diodes based on solution‐processable materials can benefit numerous technologies including integrated electronics and photonics, telecommunications, and medical diagnostics. An attractive system for implementing these devices is colloidal semiconductor quantum dots (QDs). The progress towards a QD laser diode has been hampered by rapid nonradiative Auger decay of optical‐gain‐active multicarrier states, fast device degradation at high current densities required for laser action, and unfavorable competition between optical gain and optical losses in a multicomponent device stack. Here we resolve some of these challenges and demonstrate optically excited lasing from fully functional high‐current density electroluminescent (EL) devices with an integrated optical resonator. This advance has become possible due to excellent optical gain properties of continuously graded QDs and a refined device architecture, which allows for highly efficient light amplification in a thin, EL‐active QD layer.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Quantum Molecular Charge-Transfer Model for Multistep Auger–Meitner Decay Cascade Dynamics

The fragmentation of molecular cations following inner-shell decay processes in molecules containing heavy elements underpins the X-ray damage effects observed in X-ray scattering measurements of biological and chemical materials, as well as in medical applications involving Auger electron-emitting radionuclides. Traditionally, these processes are modeled using simulations that describe the electronic structure at an atomic level, thereby omitting molecular bonding effects. This work addresses the gap by introducing a novel approach that couples Auger–Meitner decay to nuclear dynamics across multiple decay steps, by developing a decay spawning dynamics algorithm and applying it to potential energy surfaces characterized with ab initio molecular dynamics simulations. We showcase the approach on a model decay cascade following K-shell ionization of IBr and subsequent Kβ fluorescence decay. We examine two competing channels that undergo two decay steps, resulting in ion pairs with a total 3+ charge state. This approach provides a continuous description of the electron transfer dynamics occurring during the multistep decay cascade and molecular fragmentation, revealing the combined inner-shell decay and charge transfer time scale to be approximately 75 fs. In conclusion, our computed kinetic energies of ion fragments show good agreement with experimental data.

Ab initio molecular dynamics↗
DOE OSTI2020

Characterizing Sub-Cohorts via Data Normalization and Representation Learning

The process of identifying a cohort of interest is a very challenging task. It requires manually inspecting many patient records of complex structure that might include medical coding errors and missing data. This paper presents a computational pipeline for refining the process of cohort selection based on medical concepts recorded in the electronic health records (EHRs). The pipeline extracts EHR data for a given cohort and normalizes this data using standard vocabularies. Then a stacked denoising autoencoder is used to embed the normalized patient vectors in a low dimensional space, where the patients are subsequently clustered into sub-cohorts. The goal is to represent the cohort in a standard format and abstract variants of sub-populations. As a use-case, we applied the pipeline to 1.8 million Veterans diagnosed with major depressive disorder (MDD), and identified four meaningful sub-cohorts using the features learned by the autoencoder. Then, each sub-cohort was explored using a set of keywords for interpretation.

Rush III, Everett↗
DOE OSTI2020

Octave-spanning mid-infrared femtosecond OPA in a ZnGeP 2 pumped by a 2.4 μm Cr:ZnSe chirped-pulse amplifier

We report on the highly efficient, octave-spanning mid-infrared (mid-IR) optical parametric amplification (OPA) in a ZnGeP 2 (ZGP) crystal, pumped by a 1 kHz, 2.4 μm, 250 fs Cr:ZnSe chirped-pulse amplifier. The full spectral coverage of 3−10 μm with the amplified signal and idler beams is demonstrated. The signal beam in the range of ∼3 − 5 μm is produced by either white light generation (WLG) in YAG or optical parametric generation (OPG) in ZGP using the common 2.4 μm pump laser. We demonstrate the pump to signal and idler combined conversion efficiency of 23% and the pulse energy of up to 130 μJ with ∼2 μJ OPG seeding, while we obtain the efficiency of 10% and the pulse energy of 55 μJ with ∼0.2 μJ WLG seeding. The OPA output energy is limited by the available pump pulse energy (0.55 mJ at ZGP crystal) and therefore further energy scaling is feasible with multi-stage OPA and higher pump pulse energy. The autocorrelation measurements based on random quasi-phase matching show that the signal pulse durations are ∼318 fs and ∼330 fs with WLG and OPG seeding, respectively. In addition, we show the spectrally filtered 30 μJ OPA output at 4.15 μm suitable for seeding a Fe:ZnSe amplifier. Our ultrabroadband femtosecond mid-IR source is attractive for various applications, such as strong-field interactions, dielectric laser electron acceleration, molecular spectroscopy, and medical surgery.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Microtron Data Log

The Microtron at Los Alamos National Laboratory (LANL) is a versatile electron accelerator originally designed for medical therapy. Since 2001, it has been used for non-destructive radiographic imaging and research and development applications. Operating at four different energy levels—6, 10, 15, and 20 MeV—the Microtron produces dose rates of approximately 780, 1800, 2700, and 2800 R/min at a distance of one meter from the source, respectively. This high-energy X-ray source enables detailed internal examination of dense and thick objects without causing damage, making it invaluable for various scientific and industrial applications. For instance, LANL’s Microtron has been utilized to study the performance of large-panel cerium-doped lutetium yttrium silicon oxide (LYSO) scintillators, which are essential components in advanced imaging systems.

62 RADIOLOGY AND NUCLEAR MEDICINE↗