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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

New York-Presbyterian and Columbia University Irving Medical Center Requirements (Analysis Report)

EPOC uses the Deep Dive process to discuss and analyze current and planned science, research, or education activities and the anticipated data output of a particular use case, site, or project to help inform the strategic planning of a campus or regional networking environment. This includes understanding future needs related to network operations, network capacity upgrades, and other technological service investments. A Deep Dive comprehensively surveys major research stakeholders’ plans and processes in order to investigate data management requirements over the next 5–10 years. Between February and June 2024, staff members from the Engagement and Performance Operations Center (EPOC) met with researchers and staff from New York-Presbyterian (NYP), Columbia University Irving Medical Center (CUIMC), and NYSERNet for the purpose of a Deep Dive into scientific and research drivers. The goal of this activity was to help characterize the requirements for a number of campus use cases, and to enable cyberinfrastructure support staff to better understand the needs of the researchers within the community. Material for this event included the written documentation from each of the profiled research areas, documentation about the current state of technology support, and a write-up of the discussion that took place via e-mail and video conferencing. The case studies highlighted the ongoing challenges and opportunities that NYP and CUIMC have in supporting a cross-section of established and emerging research use cases. Each case study mentioned unique challenges which were summarized into common needs.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Machine learning based reconstruction of intracardiac electrical behavior based on electrocardiograms

A computer-based system and process are disclosed for reconstructing the internal electrical behavior of a patient's heart based partly or wholly on the patient's electrocardiogram (ECG). The output of the process may include, for example, a cardiac activation map, and/or a representation of transmembrane potentials over time. The process advantageously does not require any medical imaging of the patient, and does not require any special medical equipment. For example, the patient's activation map and transmembrane potentials may be reconstructed based solely on a preexisting or newly-obtained 12-lead cardiac ECG of the patient. The process makes use of a machine learning model, such as a neural network based model, trained with actual and/or simulated ECGs and intracardiac electrical data (typically transmembrane potentials) of many thousands of patients. Because an insufficient quantity of such data exists for actual patients, model training may be performed using ECGs and intracardiac electrical data obtained through computer simulations.

Blake, Robert↗
DOE OSTI2020

Uncertainty Analysis Framework for the Hospital Resource Supply Model for Covid-19

In March and April of 2020 there was widespread concern about availability of medical resources required to treat Covid-19 patients who become seriously ill. A simulation model of supply management was developed to aid understanding of how to best manage available supplies and channel new production. Forecasted demands for critical therapeutic resources have tremendous uncertainty, largely due to uncertainties about the number and timing of patient arrivals. It is therefore essential to evaluate any process for managing supplies in view of this uncertainty. To support such evaluations, we developed a modeling framework that would allow an integrated assessment in the context of uncertainty quantification. At the time of writing there has been no need to execute this framework because adaptations of the medical system have been able to respond effectively to the outbreak. This report documents the framework and its implemented components should need later arise for its application.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Actinium purification from elemental components of stainless steel and aluminum

Radioisotopes of actinium are valuable because of their potential use in the medical industry. Actinium-225 shows promise for treating disease—like cancer—via targeted alpha therapy (TAT), and the longer-lived actinium-227 is the parent of two radionuclides with potential application in TAT radiopharmaceuticals, thorium-227 and radium-223. Continuing progress in the development of these medical applications requires robust and diverse methods for extracting and purifying actinium from a wide range of matrices. Further, to define the strengths and limitations of separation methods commonly employed in actinium processing, we characterized the performance of ion exchange and extraction chromatographic steps for removing contaminants found in stainless steel (chromium, iron, nickel, and silicon) and aluminum from actinium-227. While AG-MP1 anion exchange resin with HCl (aq) successfully removed iron, cation exchanger AG 50W-X8 removed most other contaminants. The most persistent contaminant was aluminum, which was removed using a DGA Normal extraction resin. These results are presented within the context of applying that methodology toward actinium purification strategies.

36 MATERIALS SCIENCE↗
DOE OSTI2024

New Ultrafast Scintillators with Core Valence Luminescence: Cs 2 MgCl 4 and Cs 3 MgCl 5

Future experiments in high energy physics and medical imaging require radiation detectors having properties which are not presently available. The main limitations arise from lack of suitable scintillation crystals. This dilemma prompts the need for research leading to the discovery of new fast and bright scintillator materials that combine unique properties to fulfil modern experiment requirements without compromises. In this work, single crystals of Cs 2 MgCl 4 and Cs 3 MgCl 5 up to 12 mm in diameter are grown via the vertical Bridgman method. Scintillation properties are reported for the first time, and core valence luminescence is observed for both compounds. X-ray excited radioluminescence emission of Cs 2 MgCl 4 is centered at 295 nm, with a scintillation decay time of 2.25 ± 0.05 ns and relatively high core-valence light yield of 2,200 ± 110 ph/MeV. Cs 3 MgCl 5 has two main emission peaks centered at 242 nm and 302 nm, decay time of 1.46 ± 0.05 ns, and light yield of 1,340 ± 70 ph/MeV. The better coincidence time resolution (CTR) is obtained with Cs 2 MgCl 4 , which is measured to be 129 ± 4 ps FWHM. Density functional theory (DFT) calculations are also performed and provide supporting evidence that the observed scintillation originates from core valence luminescence. Furthermore, the combination of speed and brightness of these new scintillators could be useful for fast timing applications in which moderately dense materials are required.

36 MATERIALS SCIENCE↗
DOE OSTI2020

The antibiotic sorangicin A inhibits promoter DNA unwinding in a Mycobacterium tuberculosis rifampicin-resistant RNA polymerase

Rifampicin (Rif) is a first-line therapeutic used to treat the infectious disease tuberculosis (TB), which is caused by the pathogen Mycobacterium tuberculosis (Mtb). The emergence of Rif-resistant (Rif R ) Mtb presents a need for new antibiotics. Rif targets the enzyme RNA polymerase (RNAP). Sorangicin A (Sor) is an unrelated inhibitor that binds in the Rif-binding pocket of RNAP. Sor inhibits a subset of Rif R RNAPs, including the most prevalent clinical Rif R RNAP substitution found in Mtb infected patients (S456>L of the β subunit). In this paper, we present structural and biochemical data demonstrating that Sor inhibits the wild-type Mtb RNAP by a similar mechanism as Rif: by preventing the translocation of very short RNAs. By contrast, Sor inhibits the RifR S456L enzyme at an earlier step, preventing the transition of a partially unwound promoter DNA intermediate to the fully opened DNA and blocking the template-strand DNA from reaching the active site in the RNAP catalytic center. By defining template-strand blocking as a mechanism for inhibition, we provide a mechanistic drug target in RNAP. Our finding that Sor inhibits the wild-type and mutant RNAPs through different mechanisms prompts future considerations for designing antibiotics against resistant targets. Also, we show that Sor has a better pharmacokinetic profile than Rif, making it a suitable starting molecule to design drugs to be used for the treatment of TB patients with comorbidities who require multiple medications.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Evaluation of Tungsten—Steel Solid-State Bonding: Options and the Role of CALPHAD to Screen Diffusion Bonding Interlayers

Critical aspects of innovative design in engineering disciplines like infrastructure, transportation, and medical applications require the joining of dissimilar materials. This study investigates the literature on solid-state bonding techniques, with a particular focus on diffusion bonding, as an effective method for establishing engineering bonds. Welding and brazing, while widely used, may pose challenges when joining materials with large differences in melting temperature and can lead to mechanical property degradation. In contrast, diffusion bonding offers a lower temperature process that relies on solid-state interactions to develop bond strength. The joining of tungsten and steel, especially for fusion reactors, presents a unique challenge due to the significant disparity in melting temperatures and the propensity to form brittle intermetallics. Here, diffusion characteristics of tungsten–steel interfaces are examined and the influence of bonding parameters on mechanical properties are investigated. Additionally, CALPHAD modeling is employed to explore joining parameters, thermal stability, and diffusion kinetics. The insights from this research can be extended to join numerous dissimilar materials for specific applications such as aerospace, automobile industry, power plants, etc., enabling advanced and robust design with high efficiency.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Multi-Objective Optimization of Uranium Target Assembly–3: A Comparison of Genetic and Traditional Methods

Commonly produced as a byproduct of uranium fission, 99 Mo is a key medical isotope that is in high demand in the United States. An international goal is to switch from medical isotope production technologies that require highly enriched uranium to medical isotope production technologies that require only low-enriched uranium. Niowave Inc. is contributing to this goal by developing an accelerator-driven subcritical assembly called the Uranium Target Assembly (UTA). This work compares the performance of Dakota’s Multi-Objective Genetic Algorithm (MOGA) against traditional sensitivity analysis in the neutronic optimization of the UTA-3 system. The design objectives are k-eigenvalue (k eff ) and natural uranium fission power, which are directly correlated with the amount of 99 Mo produced. Dakota:MOGA did not perform as well as human engineering ingenuity in optimization studies with high numbers of input parameters, such as fuel rod type selection and fuel rod placement. However, Dakota:MOGA did outperform traditional sensitivity analysis in optimization studies with fewer than 20 parameters and revealed the degree to which each parameter influences the optimal design space for k eff and natural uranium fission power (to a lesser extent). As the design model became more complex in the final stage of design, the computational resources required to calculate the design objective values in the Monte Carlo N-Particle transport code from selected input parameter combinations limited Dakota:MOGA’s performance, and, unfortunately, human intervention was required to discern the optimal design space. In conclusion, future work will attempt to reduce computational resource constraints by incorporating areduced-order neutronics model into the optimization cycle.

Accelerator-driven systems↗
DOE OSTI2023

A new center for heavy ion research

Progress in cancer therapy with ions heavier than protons, i.e., helium, carbon, oxygen and neon, requires research and development capability. Ion research activity, however, is limited from the absence of U.S. accelerator facilities offering ion beams for therapy – placing the U.S. significantly behind Europe and Asia. With dramatic advances in beam delivery and compact accelerators, the potential exists to create a facility that can play a leadership role in particle therapy and ion-based research. This paper announces summary details of a new center for ion therapy research under construction in Waco, TX, in collaboration with recognized accelerator entities both academic and industrial. The advanced accelerator technologies will produce beams for both clinical and research applications, offering a complete range of ions, intensities and energies required by the medical community, including the capability to perform ultra-high dose irradiation (FLASH) research. FLASH, a recent research initiative, which has the potential of reducing cancer treatment toxicities, is an important if not critical capability for a competitive research center – requiring beam intensities well beyond those provided by current medical accelerators. Building a state-of-the-art cancer research center within a comprehensive facility will provide the resources to promote ion therapy in the U.S, including, preclinical/clinical trials and protocols between modalities, and also support broad ion R&D.

43 PARTICLE ACCELERATORS↗
DOE OSTI2021

Request for Medical Exemption from Covid-19 Vaccination

If you have a specific medical condition that precludes the COVID-19 vaccination requirement and you seek a medical exemption from Los Alamos National Laboratory’s COVID-19 vaccination requirement, please consult with your physician and provide the following information.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2020

Opinion to address the personal protective equipment shortage in the global community during the COVID-19 outbreak

The current COVID-19 pandemic is stretching both the global supply for face masks and personal protective equipment (PPE). Production capacity is severely limited in many countries. This is a call for the R&D community, particularly to those in the polymer degradation and stability field. We have not only an opportunity but an obligation to engage and collaborate with virology and bio-medical experts. We require comparative R&D for extended, reuse and recyclability options. Additionally, there is urgent need for large scale institutional approaches and methods that can be quickly applied locally by non-experts with limited resources.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Exploring the Impact of Copper Oxide Substitution on Structure, Morphology, Bioactivity, and Electrical Properties of 45S5 Bioglass®

In recent decades, the requirements for implantable medical devices have increased, but the risks of implant rejection still exist. These issues are primarily associated with poor osseointegration, leading to biofilm formation on the implant surface. This study focuses on addressing these issues by developing a biomaterial for implant coatings. 45S5 bioglass® has been widely used in tissue engineering due to its ability to form a hydroxyapatite layer, ensuring a strong bond between the hard tissue and the bioglass. In this context, 45S5 bioglasses®, modified by the incorporation of different amounts of copper oxide, from 0 to 8 mol%, were synthesized by the melt–quenching technique. The incorporation of Cu ions did not show a significant change in the glass structure. Since the bioglass exhibited the capacity for being polarized, thereby promoting the osseointegration effectiveness, the electrical properties of the prepared samples were studied using the impedance spectroscopy method, in the frequency range of 102–106 Hz and temperature range of 200–400 K. The effects of CuO on charge transport mobility were investigated. Additionally, the bioactivity of the modified bioglasses was evaluated through immersion tests in simulated body fluid. The results revealed the initiation of a Ca–P-rich layer formation on the surface within 24 h, indicating the potential of the bioglasses to enhance the bone regeneration process.

Hammami, Imen (ORCID:0000000290072221)↗
DOE OSTI2021

Gene expression for biodosimetry and effect prediction purposes: promises, pitfalls and future directions – key session ConRad 2021

In a nuclear or radiological event, an early diagnostic or prognostic tool is needed to distinguish unexposed from low- and highly exposed individuals with the latter requiring early and intensive medical care. Radiation-induced gene expression (GE) changes observed within hours and days after irradiation have shown potential to serve as biomarkers for either dose reconstruction (retrospective dosimetry) or the prediction of consecutively occurring acute or chronic health effects. The advantage of GE markers lies in their capability for early (1–3 days after irradiation), high-throughput, and point-of-care (POC) diagnosis required for the prediction of the acute radiation syndrome (ARS).

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2021

The novel Mechanical Ventilator Milano for the COVID-19 pandemic

This paper presents the Mechanical Ventilator Milano (MVM), a novel intensive therapy mechanical ventilator designed for rapid, large-scale, low-cost production for the COVID-19 pandemic. Free of moving mechanical parts and requiring only a source of compressed oxygen and medical air to operate, the MVM is designed to support the long-term invasive ventilation often required for COVID-19 patients and operates in pressure-regulated ventilation modes, which minimize the risk of furthering lung trauma. The MVM was extensively tested against ISO standards in the laboratory using a breathing simulator, with good agreement between input and measured breathing parameters and performing correctly in response to fault conditions and stability tests. The MVM has obtained Emergency Use Authorization by U.S. Food and Drug Administration (FDA) for use in healthcare settings during the COVID-19 pandemic and Health Canada Medical Device Authorization for Importation or Sale, under Interim Order for Use in Relation to COVID-19. Furthermore, following these certifications, mass production is ongoing and distribution is under way in several countries. The MVM was designed, tested, prepared for certification, and mass produced in the space of a few months by a unique collaboration of respiratory healthcare professionals and experimental physicists, working with industrial partners, and is an excellent ventilator candidate for this pandemic anywhere in the world

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Reducing the Energy Consumption of Magnetic Resonance Imaging and Computed Tomography Scanners: Integrating Ecodesign and Sustainable Operations

This review aims to provide valuable insights into how energy consumption in magnetic resonance imaging (MRI) and computed tomography (CT) scanners can be effectively monitored, managed, and reduced, thereby contributing to more sustainable medical imaging practices. Demand for advanced imaging technologies such as MRI and CT scanners continues to increase, and understanding the resultant impact on greenhouse gas emissions requires a thorough evaluation of their energy consumption. Here, this review examines the energy monitoring and consumption characteristics of MRI and CT scanners, highlighting potential approaches for energy savings. An overview of MRI and CT principles, hardware components, and their associated energy consumption is provided. After addressing the technical aspects, the hardware and software requirements essential for accurate energy metering are detailed. Baseline measurements of energy consumption data are then provided as a foundation to understand current usage patterns and identify areas for improvement. Ongoing efforts to reduce energy consumption are categorized into 3 main strategies: operations, scanner design enhancements, and active scanning techniques, including accelerated MRI protocols. Ultimately, we emphasize that achieving sustainability in medical imaging requires collaboration across disciplines. By incorporating eco-friendly design in new imaging equipment, we can reduce the environmental impact, promote sustainability, and set a health care industry standard for a healthier planet.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
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 OSTI2020

Design of a multichannel photonic crystal dielectric laser accelerator

To be useful for most scientific and medical applications, compact particle accelerators will require much higher average current than enabled by current architectures. For this purpose, we propose a photonic crystal architecture for a dielectric laser accelerator, referred to as a multi-input multi-output silicon accelerator (MIMOSA), that enables simultaneous acceleration of multiple electron beams, increasing the total electron throughput by at least 1 order of magnitude. To achieve this, we show that the photonic crystal must support a mode at the Γ point in reciprocal space, with a normalized frequency equal to the normalized speed of the phase-matched electron. We show that the figure of merit of the MIMOSA can be inferred from the eigenmodes of the corresponding infinitely periodic structure, which provides a powerful approach to design such devices. Additionally, we extend the MIMOSA architecture to electron deflectors and other electron manipulation functionalities. These additional functionalities, combined with the increased electron throughput of these devices, permit all-optical on-chip manipulation of electron beams in a fully integrated architecture compatible with current fabrication technologies, which opens the way to unconventional electron beam shaping, imaging, and radiation generation.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

Federated benchmarking of medical artificial intelligence with MedPerf

Medical artificial intelligence (AI) has tremendous potential to advance healthcare by supporting and contributing to the evidence-based practice of medicine, personalizing patient treatment, reducing costs, and improving both healthcare provider and patient experience. Unlocking this potential requires systematic, quantitative evaluation of the performance of medical AI models on large-scale, heterogeneous data capturing diverse patient populations. Here, to meet this need, we introduce MedPerf, an open platform for benchmarking AI models in the medical domain. MedPerf focuses on enabling federated evaluation of AI models, by securely distributing them to different facilities, such as healthcare organizations. This process of bringing the model to the data empowers each facility to assess and verify the performance of AI models in an efficient and human-supervised process, while prioritizing privacy. We describe the current challenges healthcare and AI communities face, the need for an open platform, the design philosophy of MedPerf, its current implementation status and real-world deployment, our roadmap and, importantly, the use of MedPerf with multiple international institutions within cloud-based technology and on-premises scenarios. Finally, we welcome new contributions by researchers and organizations to further strengthen MedPerf as an open benchmarking platform.

60 APPLIED LIFE SCIENCES↗