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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Sonochemical synthesis of carbon dots, mechanism, effect of parameters, and catalytic, energy, biomedical and tissue engineering applications

Carbon-based nanomaterials are gaining more and more interest because of their wide range of applications. In this study, carbon dots (CDs) have shown exclusive interest due to unique and novel physicochemical, optical, electrical, and biological properties. Since their discovery, CDs became a promising material for wide range of research applications from energy to biomedical and tissue engineering applications. At same time several new methods have been developed for the synthesis of CDs. Compared to many of these methods, the sonochemical preparation is a green method with advantages such as facile, mild experimental conditions, green energy sources, and feasibility to formulate CDs and doped CDs with controlled physicochemical properties and lower toxicity. In the last five years, the sonochemically synthesized CDs were extensively studied in a wide range of applications. In this review, we discussed the sonochemical assisted synthesis of CDs, doped CDs and their nanocomposites. In addition to the synthetic route, we will discuss the effect of various experimental parameters on the physicochemical properties of CDs; and their applications in different research areas such as bioimaging, drug delivery, catalysis, antibacterial, polymerization, neural tissue engineering, dye absorption, ointments, electronic devices, lithium ion batteries, and supercapacitors. This review concludes with further research directions to be explored for the applications of sonochemical synthesized CDs.

36 MATERIALS SCIENCE↗
DOE OSTI2024

In-situ heating-and-electron tomography for materials research: from 3D ( In-situ 2D) to 4D ( In-situ 3D)

In-situ observation has expanded the application of transmission electron microscopy (TEM) and has made a significant contribution to materials research and development for energy, biomedical, quantum, etc. Recent technological developments related to in-situ TEM have empowered the incorporation of three-dimensional observation, which was previously considered incompatible. In this review article, we take up heating as the most commonly used external stimulus for in-situ TEM observation and overview recent in-situ TEM studies. Then, we focus on the electron tomography (ET) and in-situ heating combined observation by introducing the authors’ recent research as an example. Assuming that in-situ heating observation is expanded from two dimensions to three dimensions using a conventional TEM apparatus and a commercially available in-situ heating specimen holder, the following in-situ heating-and-ET observation procedure is proposed: (i) use a rapid heating-and-cooling function of a micro-electro-mechanical system holder; (ii) heat and cool the specimen intermittently and (iii) acquire a tilt-series dataset when the specimen heating is stopped. This procedure is not too technically challenging and can have a wide range of applications. Essential technical points for a successful 4D (space and time) observation will be discussed through reviewing the authors’ example application.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Electrospun PVA Fibers for Drug Delivery: A Review

Innovation in biomedical science is always a field of interest for researchers. Drug delivery, being one of the key areas of biomedical science, has gained considerable significance. The utilization of simple yet effective techniques such as electrospinning has undergone significant development in the field of drug delivery. Various polymers such as PEG (polyethylene glycol), PLGA (Poly(lactic-co-glycolic acid)), PLA(Polylactic acid), and PCA (poly(methacrylate citric acid)) have been utilized to prepare electrospinning-based drug delivery systems (DDSs). Polyvinyl alcohol (PVA) has recently gained attention because of its biocompatibility, biodegradability, non-toxicity, and ideal mechanical properties as these are the key factors in developing DDSs. Moreover, it has shown promising results in developing DDSs individually and when combined with natural and synthetic polymers such as chitosan and polycaprolactone (PCL). Considering the outstanding properties of PVA, the aim of this review paper was therefore to summarize these recent advances by highlighting the potential of electrospun PVA for drug delivery systems.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Understanding interactions between biomolecules and two-dimensional nanomaterials using in silico microscopes

We report two-dimensional (2D) nanomaterials such as graphene are increasingly used in research and industry for various biomedical applications. Extensive experimental and theoretical studies have revealed that 2D nanomaterials are promising drug delivery vehicles, yet certain materials exhibit toxicity under biological conditions. So far, it is known that 2D nanomaterials possess strong adsorption propensities for biomolecules. To mitigate potential toxicity and retain favorable physical and chemical properties of 2D nanomaterials, it is necessary to explore the underlying mechanisms of interactions between biomolecules and nanomaterials for the subsequent design of biocompatible 2D nanomaterials for nanomedicine. The purpose of this review is to integrate experimental findings with theoretical observations and facilitate the study of 2D nanomaterial interaction with biomolecules at the molecular level. We discuss the current understanding and progress of 2D nanomaterial interaction with proteins, lipid membranes, and DNA based on molecular dynamics (MD) simulation. In this review, we focus on the 2D graphene nanosheet and briefly discuss other 2D nanomaterials. With the ever-growing computing power, we can image nanoscale processes using MD simulation that are otherwise not observable in experiment. We expect that molecular characterization of the complex behavior between 2D nanomaterials and biomolecules will help fulfill the goal of designing effective 2D nanomaterials as drug delivery platforms.

2D nanomaterials↗
DOE OSTI2020

Coordination Chemistry in the Structural and Functional Exploration of Actinide-Based Metal-Organic Frameworks

The coordination chemistry between inorganic and organic species can be optimally exemplified by metal–organic frameworks (MOFs), whose structures and functionalities can be rationally designed from these highly tunable building blocks. The high porosity, stability, and versatile functionalities of MOFs have attracted wide-spread attention from energy-related research and pollution remediation to biomedical applications. A unique and underexplored subset of these materials are MOFs based on actinide nodes; these MOFs have distinguished themselves as a unique platform for investigating the versatile oxidation states, reactivity, and coordination chemistry of actinides. Herein, we will focus on the rational design and synthesis of actinide-based MOFs under the general guidelines of coordination chemistry for their structural and functional explorations. The dimensionality, topology, and structures of actinide-based MOFs can be controlled by selecting pre-designed building blocks of actinide-based nodes and organic linkers with certain desired coordination geometries and functionalities. Furthermore, these unique actinide-based MOFs have shown promise for applications in nuclear waste mitigation, pollution control, and catalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Accelerating scientific discoveries through data-driven innovations

Developing artificial intelligence (AI) and machine learning (ML) methods that can accelerate scientific discoveries and advance science has become one of the important research directions for the AI/ML research community. It has been gaining increasing attention from researchers in diverse scientific areas, including biomedical science, materials science, climate science, physics, chemistry, and many others. Data-driven AI/ML innovations to enable reliable predictions and optimal decision making for scientific discoveries face several critical challenges, among which are high system complexity, large search space, incomplete knowledge, and small data, all of which demand novel strategies to effectively address them. Meeting these challenges and thereby accelerating scientific discoveries and industrial innovations, calls for research that can take full advantage of the latest advances in AI/ML to integrate data-driven techniques with scientific knowledge and is able to execute them in modern high-performance computing (HPC) environments at scale. This Patterns special collection "Accelerating scientific discoveries through data-driven innovations" features articles that showcase the promising roles of AI/ML and data-driven modeling in accelerating scientific discoveries and may inspire the next wave of data-driven innovations in various scientific domains.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Reuniting philosophy and science to advance cancer research

Cancers rely on multiple, heterogeneous processes at different scales, pertaining to many biomedical fields. Therefore, understanding cancer is necessarily an interdisciplinary task that requires placing specialised experimental and clinical research into a broader conceptual, theoretical, and methodological framework. Without such a framework, oncology will collect piecemeal results, with scant dialogue between the different scientific communities studying cancer. We argue that one important way forward in service of a more successful dialogue is through greater integration of applied sciences (experimental and clinical) with conceptual and theoretical approaches, informed by philosophical methods. By way of illustration, we explore six central themes: (i) the role of mutations in cancer; (ii) the clonal evolution of cancer cells; (iii) the relationship between cancer and multicellularity; (iv) the tumour microenvironment; (v) the immune system; and (vi) stem cells. In each case, we examine open questions in the scientific literature through a philosophical methodology and show the benefit of such a synergy for the scientific and medical understanding of cancer.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

An image classification deep-learning algorithm for shrapnel detection from ultrasound images

Ultrasound imaging is essential for non-invasively diagnosing injuries where advanced diagnostics may not be possible. However, image interpretation remains a challenge as proper expertise may not be available. In response, artificial intelligence algorithms are being investigated to automate image analysis and diagnosis. Here, we highlight an image classification convolutional neural network for detecting shrapnel in ultrasound images. As an initial application, different shrapnel types and sizes were embedded first in a tissue mimicking phantom and then in swine thigh tissue. The algorithm architecture was optimized stepwise by minimizing validation loss and maximizing F1 score. The final algorithm design trained on tissue phantom image sets had an F1 score of 0.95 and an area under the ROC curve of 0.95. It maintained higher than a 90% accuracy for each of 8 shrapnel types. When trained only on swine image sets, the optimized algorithm format had even higher metrics: F1 and area under the ROC curve of 0.99. Overall, the algorithm developed resulted in strong classification accuracy for both the tissue phantom and animal tissue. This framework can be applied to other trauma relevant imaging applications such as internal bleeding to further simplify trauma medicine when resources and image interpretation are scarce.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

A review of laser materials processing paradigms

Laser-based processing of materials has progressed from traditional applications such as macroscale cutting and welding, to sophisticated techniques, including ultrafast micromachining, additive manufacturing, and surface engineering at micro- and nano-metric scales. Innovations in laser source technology, particularly the advent of high-power and ultrashort-pulse lasers, have expanded the range of processable materials, enabled a plethora of manufacturing applications, and propelled groundbreaking research in optics, photonics, electronics, and biomedical domains. In this article, we provide a concise, yet broad review of the congruent evolution of lasers and materials processing, and highlight seminal developments in the field over the years, combined with a critical assessment of the state of the art. Finally, we also provide an outlook on emerging needs, as well as a roadmap of anticipated developments in laser technologies and materials platforms over the next 50 years.

Lasers↗
DOE OSTI2021

BRAVE_EBC-TMT.1.0

Exhaled breath condensate (EBC) represents a low-cost and non-invasive means of examining respiratory health. EBC has been used to discover and validate exhaled volatile and non-volatile biomarkers of disease related to the respiratory system distress such as asthma, COPD, lung cancer, and secondary infections. One newly emerging utilization of EBC, is proteomics analysis, which can provide an unbiased snapshot into ongoing biological processes in the airway. Fully characterizing the biological landscape of EBC collections is challenging though, due to sample variability, and low detection sensitivity. EBC is primarily composed of condensed water, causing technical challenges with detecting key macromolecules from the dilute sample matrix; therefore, high sensitivity techniques are required to unlock the full capability of EBC as a method for non-invasive biomarker detection. To overcome some of these technical challenges for proteomic analyses, we applied our recently developed microscale proteomic techniques and developed a novel TMT based approach which enabled reliable, relative quantification with significantly improved detection of low abundance peptides/proteins across multiple healthy volunteer EBC samples. Our EBC collection design includes longitudinal EBC collections from five individual healthy volunteers on three separate days of the week with triplicate, back-to-back donations each day. Here, we report a total of 235 quantifiable proteins corresponding to 1,877 non-redundant peptides for evaluating sample collection reproducibility and establishing a healthy (human host) baseline EBC biomarker proteome studies. This work will pave the way for further investigations of EBC protein expression profiles and showcase the value of using non-invasive collection method techniques for clinically relevant biomarker discovery. This research was supported by the LDRD Biomedical Resilience And Readiness in AdVerse Operating Environments (BRAVE) Project (73748), and was conducted at Pacific Northwest National Laboratory (PNNL) in Richland, WA. PNNL is a multiprogram national laboratory operated by Battelle for the Department of Energy (DOE) under Contract DE-AC05-76RLO 1830.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Data for The utility of transfer learning to improve the performance of deep learning in axon segmentation

The utility of transfer learning to improve the performance of deep learning in axon segmentation Data Data: All the input and labeled volumes tf-logs: Tensorflow logs, view with command "tensorboard --logdir [name of folder]" Model Weights: model_weights: the argument list under variable combo indicate 1) no oversampling, 2) no rotation, 3) no learn scheduler, and 4) flipping on all three dimensions, and the additional values indicate 5) elastic deformation percentage, 6) rotate deformation percentage, 7) layer setting , 8) learning rate, and 9) training/validation/test data division suffix (leave '' if not using suffix). Results: Output from inference segment_total_results_validation_final: All validation results and calculations segment_total_results: All test results and calculations Authors The modified code was created for a paper by: Marjolein Oostrom, Michael A. Muniak, Rogene Eichler West, Sarah Akers, Paritosh Pande, Moses Obiri, Wei Wang, Kasey Bowyer, Zhuhao Wu, Lisa Bramer, Tianyi Mao, Bobbie Jo Webb-Robertson The work is adapted from Github TrailMap, which was created by Albert Pun and Drew Friedmann Acknowledgments MO, RMEW, SA, MO, LB, BJWR were supported by the Laboratory Directed Research and Development at Pacific Northwest National Laboratory (PNNL), a Department of Energy facility operated by Battelle under contract DE-AC05-76RLO01830. WW, KB, and ZW were supported in part by a NIH/BRAIN Initiative Grant RF1MH128969. MAM and TM were supported by two NIH/BRAIN Initiative Grants R01NS104944, RF1MH120119 and NIH R01NS081071. This research is affiliated with the Pacific northwest bioMedical Innovation Co-laboratory (PMedIC) collaboration between OHSU and PNNL.

Oostrom, Marjolein T↗
DOE OSTI2024

Human Subjects in Energy Technology and Policy Research (Symposium Report)

The U.S. Department of Energy (DOE) has a unique and wide-ranging research portfolio. One focus of the department’s research mission is to develop and promote the adoption of technologies that reduce greenhouse gas emissions and result in renewable and clean energy for the country. This research encompasses a surprisingly diverse array of studies, many of which involve the inclusion of human participants that go beyond traditional biomedical investigations. For example, individuals play an important role in DOE research on clean energy sources, development and testing of new energy-efficient technologies, and partnerships with local communities for equitable climate solutions.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Lignin - A green material for antibacterial application — A review

Lignin's antibacterial properties have become increasingly relevant due to the rise of microbial infectious diseases and antibiotic resistance. Lignin is capable of interacting electrostatically with bacteria and contains polyphenols that cause damage to their cell walls. These features make lignin a desirable material to exhibit antibacterial behavior. Therefore, lignin in antibacterial applications offers a novel approach to address the growing need for sustainable and effective antibacterial materials. Recent research has explored the incorporation of lignin in various biomedical applications, such as wound dressings, implants, and drug delivery systems, highlighting their potential as a sustainable alternative to synthetic antibacterial agents. Furthermore, the development of lignin-based nanomaterials with enhanced antimicrobial activity is an active area of research that holds great promise for the future. Here, in this review, we have provided a summary of how lignin can be incorporated into different forms, such as composite and non-composite synthesis of antibacterial agents and their performances. The challenges and future considerations are also discussed in this review article.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Design, characterization and shape recovery behavior of 3D/4D printed shape memory polymers (SMPs)

Shape memory polymers (SMPs) represent a paradigm shift in material science, uniquely capable of undergoing reversible shape transformations triggered by external stimuli, positioning them as pivotal in developing next-generation biomedical devices, aerospace components, and adaptive structures. Extensive research has been done on SMPs with a major focus on high-temperature programming methods, which can limit energy efficiency and applicability with temperature-sensitive materials. Additionally, while various SMP blends have demonstrated great potential, limited work has been done on the suitability for 3D printing these materials, particularly under high-strain and ambient temperature programming conditions. In this study, a three-component optimized SMP composition was evaluated by 3D printing via the Material Extrusion (MEX) technique and investigating its ambient temperature-programming behavior at high strains. The SMP formulation studied was a tailored blend of thermoplastic polyurethane (TPU), polycaprolactone (PCL), and an octadecane diol-based copolymer (OBC) that exhibits robust shape memory behavior, high strain tolerance, and efficient force generation. Rigorous thermal, mechanical, and shape recovery analyses, along with optimized printing parameters and consistent shape recovery rates of up to 90%, were achieved under dynamic mechanical analysis (DMA), even under ambient programming conditions. This work demonstrates the SMP composition’s potential for adaptive, self-deployable systems with 4D printing characteristics ideal for bio-inspired structures and artificial muscle fibers.

Sudan, Kavish [University of Louisville, KY]↗
DOE OSTI2020

Smoky Mountain Data Challenge 2020: An Open Call to Solve Data Problems in the Areas of Neutron Science, Material Science, Urban Modeling and Dynamics, Geophysics, and Biomedical Informatics

The 2020 Smoky Mountains Computational Sciences and Engineering Conference enlists research scientists from across Oak Ridge National Laboratory (ORNL) to be data sponsors and help create data analytics challenges for eminent data sets at the laboratory. This work describes the significance of each of the seven data sets and their as- sociated challenge questions. The challenge questions for each data set were required to cover multiple difficulty levels. An international call for participation was sent to students, and researchers asking them to form teams of up to four people to apply novel data analytics techniques to these data sets.

Parete-Koon, Suzanne↗
DOE OSTI2022

Exaflops Biomedical Knowledge Graph Analytics

We are motivated by newly proposed methods for mining large-scale corpora of scholarly publications (e.g., full biomedical literature), which consists of tens of millions of papers spanning decades of research. In this setting, analysts seek to discover relationships among concepts. They construct graph representations from annotated text databases and then formulate the relationship-mining problem as an all-pairs shortest paths (APSP) and validate connective paths against curated biomedical knowledge graphs (e.g., Spoke). In this context, we present Coast (Exascale Communication-Optimized All-Pairs Shortest Path) and demonstrate 1.004 EF/s on 9,200 Frontier nodes (73,600 GCDs). We develop hyperbolic performance models (HYPERMOD), which guide optimizations and parametric tuning. The proposed Coast algorithm achieved the memory constant parallel efficiency of 99% in the single-precision tropical semiring. Looking forward, Coast will enable the integration of scholarly corpora like PubMed into the Spoke biomedical knowledge graph.

Kannan, Ramakrishnan {ramki}↗
DOE OSTI2025

Announcing the Biomedical Data Translator: Initial Public Release

ABSTRACT The growing availability of biomedical data offers vast potential to improve human health, but the complexity and lack of integration of these datasets often limit their utility. To address this, the Biomedical Data Translator Consortium has developed an open‐source knowledge graph–based system—Translator—designed to integrate, harmonize, and make inferences over diverse biomedical data sources. We announce here Translator's initial public release and provide an overview of its architecture, standards, user interface, and core features. Translator employs a scalable, federated, knowledge graph framework for the integration of clinical, genomic, pharmacological, and other biomedical knowledge sources, enabling query retrieval, inference, and hypothesis generation. Translator's user interface is designed to support the exploration of knowledge relationships and the generation of insights, without requiring deep technical expertise and gradually revealing more detailed evidence, provenance, and confidence information, as needed by a given user. To demonstrate Translator's application and impact, we highlight features of the user interface in the context of three real‐world use cases: suggesting potential therapeutics for patients with rare disease; explaining the mechanism of action of a pipeline drug; and screening and validating drug candidates in a model organism. We discuss strengths and limitations of reasoning within a largely federated system and the need for rich concept modeling and deep provenance tracking. Finally, we outline future directions for enhancing Translator's functionality and expanding its data sources. Translator represents a significant step forward in making complex biomedical knowledge more accessible and actionable, aiming to accelerate translational research and improve patient care.

Research & Experimental Medicine↗
DOE OSTI2023

Bioimaging Science Program Principal Investigator Meetings Proceedings (2021)

As part of the 2021 Biological Systems Science Division (BSSD) Principal Investigator (PI) Meeting, the Bioimaging Science program (BSP), within BSSD's Biomolecular Characterization and Imaging Science portfolio, held its annual PI meeting virtually February 22–23. BSP's mission is to understand the translation of genomic information into the mechanisms that power living cells, communities of cells, and whole organisms. The goal of BSP is to develop new imaging and measurement technologies to visualize the spatial and temporal relationships of key metabolic processes governing phenotypic expression in plants and microbes. BSP convenes annual PI meetings to bring together its contributing investigators to review progress and current state-of-the-art bioimaging research. Holding the BSP meeting as part of the broader BSSD PI meeting allowed researchers to interact with the extended Genomic Science program community. This convergence provided a platform for networking and exchange of ideas, helping to forge new multidisciplinary collaborations among investigators from the two sister programs. An important highlight of the BSP meeting was the keynote presentation “Enhancing Fluorescence Microscopy with Computation” by Dr. Hari Shroff of the NIH National Institute of Biomedical Imaging and Bioengineering. All the BSP PIs made presentations describing their research focus and progress, and these were followed by roundtable discussions of each project. The meeting’s proceedings provide an outline of the program’s current state and potential future directions and opportunities.

59 BASIC BIOLOGICAL SCIENCES↗