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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 1,441 records · Page 80
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Application of 3D Printing for Smart Objects with Embedded Electronic Sensors and Systems

Applications of a 3D printing process are presented. This process integrates liquid-state printed components and interconnects with IC chips in all three dimensions, various orientations, and multiple printing layers to deliver personalized system-level functionalities. Here, as an example application, a form-fitting glove is demonstrated with embedded programmable heater, temperature sensor, and the associated control electronics for thermotherapeutic treatment.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Graphene K‐Tape Meshes for Densely Distributed Human Motion Monitoring

Abstract Wearable sensors that measure parameters associated with physical activity and bodily motions have been regarded as an indispensable tool for assessing personal wellness. Recent advances in nanocomposite strain sensors have been successfully used for monitoring skin strains and other strain‐derived physiological parameters. This study complements the existing body of work and presents a flexible, self‐adhering, fabric‐based wearable sensor for measuring skin strains and human motions. Graphene nanosheet thin films are directly spray‐coated onto kinesiology tape (K‐Tape) to obtain a self‐adhering strain sensor of high sensitivity and linearity. Their stable sensing performance and high repeatability are verified, while human subject tests confirm that they adequately capture muscle engagement during functional movements. In addition, densely distributed strain monitoring can be achieved using an electrical impedance tomography measurement approach and algorithm. Spatial strain sensing is successfully demonstrated using a single strip of piezoresistive K‐Tape, as well as when a K‐Tape network or mesh pattern is formed. The results show promise for using graphene K‐Tape meshes to measure how specific major muscle groups engage during different physical activities.

Lin, Yun‐An↗
DOE OSTI2020

Exploiting the Spinel Structure for Li-ion Battery Applications: A Tribute to John B. Goodenough

This review provides a personal account of career-long efforts, interwoven with the contributions of others, to exploit the [B 2 ]O 4 framework of an A[B 2 ]O 4 spinel structure for lithium-ion battery applications, where A = Li, and B is one or more metal cations. The narrative begins at the Council for Scientific and Industrial Research (CSIR) in South Africa in the mid-1970s when, in response to the Middle East oil crisis, worldwide efforts were turned to develop high-temperature sodium and lithium batteries to power electric vehicles. In 1981, results in CSIR's program on a high-temperature lithium battery led to a collaborative project on room-temperature lithium cells with Prof. John B. Goodenough at Oxford University, where studies of Fe 3 O 4 , Mn 3 O 4 , and LiMn 2 O 4 cathodes led to the recognition of the broad utility of the [B2]O4 spinel framework as an anode, cathode, or solid electrolyte for rechargeable lithium cells. This finding has had a profound and lasting impact, influencing further ideas and discoveries at the CSIR, Argonne National Laboratory, and elsewhere. The narrative emphasizes the compositional versatility of the spinel structure and the opportunities to tailor the electrochemical potential and stability of a Li-ion cell.

25 ENERGY STORAGE↗
DOE OSTI2025

Battery‐Grade Lithium Materials: Virgin Production and Recycling, a Techno‐Economic Comparison

Lithium has been identified as an essential mineral to the economic and national security of the United States. It is vital for rechargeable batteries that surround us daily from the personal electronics to large-scale energy storage. With a comprehensive techno-economic analysis, the cost of battery-grade lithium compounds production, i.e., lithium carbonate (LC) is evaluated and lithium hydroxide monohydrate (LHM), from both virgin (spodumene ore and brine) and recycled feedstocks (spent lithium-ion batteries). The goal of this study is to inform about the economics of lithium compounds production with comprehensive insights into differences in manufacturing routes and pave a pathway to explore more innovative, domestic manufacturing processes in future for their cost competitiveness and environmental impact. The study includes details on mining and extraction operations as well as unit level operation in the refining process. Moreover, process level information has been collected for pyrometallurgical and hydrometallurgical battery recycling routes. This analysis shows that brine and direct lithium extraction are the cheapest pathways to produce LC or LHM (between $\$3.39$ and 6.20 kg −1 ). The cost of production in the ore and recycling routes can range between $\$4.17$ and $\$53.41$ kg −1 and is highly depending on capital equipment investment, plant location, and the price of spodumene concentrate SC6.0.

battery recycling↗
DOE OSTI2018

Targeted brain proteomics uncover multiple pathways to Alzheimer's dementia

Objective Previous gene expression analysis identified a network of coexpressed genes that is associated with β‐amyloid neuropathology and cognitive decline in older adults. The current work targeted influential genes in this network with quantitative proteomics to identify potential novel therapeutic targets. Methods Data came from 834 community‐based older persons who were followed annually, died, and underwent brain autopsy. Uniform structured postmortem evaluations assessed the burden of β‐amyloid and other common age‐related neuropathologies. Selected reaction monitoring quantified cortical protein abundance of 12 genes prioritized from a molecular network of aging human brain that is implicated in Alzheimer's dementia. Regression and linear mixed models examined the protein associations with β‐amyloid load and other neuropathological indices as well as cognitive decline over multiple years preceding death. Results Average age at death was 88.6 years. Overall, 349 participants (41.9%) had Alzheimer's dementia at death. A higher level of PLXNB1 abundance was associated with more β‐amyloid load ( p = 1.0 × 10 −7 ) and higher PHFtau tangle density ( p = 2.3 × 10 −7 ), and the association of PLXNB1 with cognitive decline is mediated by these known Alzheimer's disease pathologies. On the other hand, higher IGFBP5, HSPB2, and AK4 and lower ITPK1 levels were associated with faster cognitive decline, and, unlike PLXNB1, these associations were not fully explained by common neuropathological indices, suggesting novel mechanisms leading to cognitive decline. Interpretation Using targeted proteomics, this work identified cortical proteins involved in Alzheimer's dementia and begins to dissect two different molecular pathways: one affecting β‐amyloid deposition and another affecting resilience without a known pathological footprint. Ann Neurol 2018;83:78–88

Yu, Lei↗
DOE OSTI2018

Soft Robotics

This description of “soft robotics” is not intended to be a conventional review, in the sense of a comprehensive technical summary of a developing field. Rather, its objective is to describe soft robotics as a new field—one that offers opportunities to chemists and materials scientists who like to make “things” and to work with macroscopic objects that move and exert force. It will give one (personal) view of what soft actuators and robots are, and how this class of soft devices fits into the more highly developed field of conventional “hard” robotics. It will also suggest how and why soft robotics is more than simply a minor technical “tweak” on hard robotics and propose a unique role for chemistry, and materials science, in this field. Finally, soft robotics is, at its core, intellectually and technologically different from hard robotics, both because it has different objectives and uses and because it relies on the properties of materials to assume many of the roles played by sensors, actuators, and controllers in hard robotics.

47 OTHER INSTRUMENTATION↗
DOE OSTI2016

Challenging/interesting lignin times

Anyone who is working in the fuels industry knows that we are living in challenging times. On a personal note, I recall that ~5 years ago, some of my children's friends headed out into the petroleum industry to start their careers and several have now returned because of the retrenching work force. Despite these challenging times, the cellulosic ethanol industry continues to develop commercial operations, but with today's cost structure, biofuels production facilities have certainly slowed their pace of development and roll-out. Furthermore, the biological technology platform for biorefining plant polysaccharides to biofuels has been reported to have an intrinsic advantage, if it can convert its waste lignin stream to value-added components.[1]

09 BIOMASS FUELS↗
DOE OSTI2017

Measured extent of agricultural expansion depends on analysis technique

Concern is rising that ecologically important, carbon-rich natural lands in the United States are losing ground to agriculture. We investigate how quantitative assessments of historical land use change to address this concern differ in their conclusions depending on the data set used. We examined land use change between 2006 and 2014 in 20 counties in the Prairie Pothole Region using the Cropland Data Layer, a modified Cropland Data Layer, data from the National Agricultural Imagery Program, and in-person ground-truthing. The Cropland Data Layer analyses overwhelmingly returned the largest amount of land use change with associated error that limits drawing conclusions from it. Analysis with visual imagery estimated a fraction of this land use change. Clearly, analysis technique drives understanding of the measured extent of land use change; different techniques produce vastly different results that would inform land management policy in strikingly different ways. As a result, best practice guidelines are needed.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Generalized Brønsted‐Evans‐Polanyi Relationships for Reactions on Metal Surfaces from Machine Learning

Abstract Brønsted‐Evans‐Polanyi (BEP) relationships, i. e., a linear scaling between reaction and activation energies, lie at the core of computational design of heterogeneous catalysts. However, BEPs are not general and often require reparameterization for each class of reactions. Here we construct generalized BEPs (gBEPs), which can predict activation energies for a diverse dataset of reactions of C, O, N and H containing molecules on metal surfaces. In a first step we develop a set of descriptors based on scaling relationships that can capture the change in chemical identity of reactants during the reaction. Subsequently, we use the reaction energy, these descriptors and a single descriptor for the surface structure to parameterize machine learning based regression approaches for the prediction of activation energies. The best approach we developed shows a Mean Absolute Error (MAE) of 0.11 eV for the training set (80 % of the data set) and 0.23 eV for the test set (20 % of the data set). The methodology presented here allows to calculate activation energies within fractions of seconds on a typical personal computer and due to its generality, accuracy and simplicity in application it might prove to be useful in transition metal catalyst design.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Risk and incidence of head and neck cancers in veterans living with HIV and matched HIV‐negative veterans

Background Persons living with HIV/AIDS have a higher incidence of virus‐related and tobacco/alcohol‐related cancers. This study is the first to estimate the effect of HIV versus HIV‐negative veterans on the risk of head and neck squamous cell carcinoma incidence in a large retrospective cohort study. Methods The authors constructed a retrospective cohort study using patient data from 1999 to 2016 from the National Veterans Administration Corporate Data Warehouse and the VA Central Cancer Registry. This cohort study included 45,052 veterans living with HIV/AIDS and 162,486 HIV‐negative patients matched by age, sex, and index visit (i.e., HIV diagnosis date or clinic visit date). The age‐standardized incidence rates and estimated adjusted hazard ratios were calculated with a Cox proportional hazards regression for oropharyngeal and nonoropharyngeal head and neck cancer squamous cell carcinoma (HNSCC). The authors also abstracted human papillomavirus (HPV) status from oropharyngeal HNSCC diagnosed after 2010. Results Veterans living with HIV/AIDS (VLWH) have 1.71 (95% confidence interval [CI], 1.36, 2.14) times the risk of oropharyngeal cancer and 2.06 (95% CI, 1.76, 2.42) times the hazard of nonoropharyngeal cancer compared with HIV‐negative veterans. VLWH with oropharyngeal squamous cell carcinoma (OPSCC) were more likely to be HPV‐positive ( N = 30 [81.1%]) than the HIV‐negative veterans with OPSCC ( N = 50 [67.6%]), although this difference was not significant ( p = .135). For nonoropharyngeal cancer, the increased risk of oral cavity cancer among VLWH drove the increased risk. Conclusions The study results suggest that HIV may play a role in virally mediated and nonvirally mediated HNSCC. As the HIV prevalence rises in the United States due to better survival and the incidence of HPV‐positive oropharyngeal HNSCC increases, the interaction between HPV and HIV becomes increasingly relevant.

Mazul, Angela L.↗
DOE OSTI2021

A NIR fluorescent smart probe for imaging tumor hypoxia

Abstract Background Tumor hypoxia is a characteristic of paramount importance due to low oxygenation levels in tissue negatively correlating with resistance to traditional therapies. The ability to noninvasively identify such could provide for personalized treatment(s) and enhance survival rates. Accordingly, we recently developed an NIR fluorescent hypoxia‐sensitive smart probe ( NO 2 ‐Rosol ) for identifying hypoxia via selectively imaging nitroreductase (NTR) activity, which could correlate to oxygen deprivation levels in cells, thereby serving as a proxy. We demonstrated proof of concept by subjecting a glioblastoma (GBM) cell line to extreme stress by evaluating such under radiobiological hypoxic ( p O 2 ≤ ~0.5%) conditions, which is a far cry from representative levels for hypoxia for brain glioma ( p O 2 = ~1.7%) which fluctuate little from physiological hypoxic ( p O 2 = 1.0‐3.0%) conditions. Aim We aimed to evaluate the robustness, suitability, and feasibility of NO 2 ‐Rosol for imaging hypoxia in vitro and in vivo via assessing NTR activity in diverse GBM models under relevant oxygenation levels ( p O 2 = 2.0%) within physiological hypoxic conditions that mimic oxygenation levels in GBM tumor tissue in the brain. Methods We evaluated multiple GBM cell lines to determine their relative sensitivity to oxygenation levels via measuring carbonic anhydrase IX (CAIX) levels, which is a surrogate marker for indirectly identifying hypoxia by reporting on oxygen deprivation levels and upregulated NTR activity. We evaluated for hypoxia via measuring NTR activity when employing NO 2 ‐Rosol in in vitro and tumor hypoxia imaging studies in vivo. Results The GBM39 cell line demonstrated the highest CAIX expression under hypoxic conditions representing that of GBM in the brain. NO 2 ‐Rosol displayed an 8‐fold fluorescence enhancement when evaluated in GBM39 cells ( p O 2 = 2.0%), thereby establishing its robustness and suitability for imaging hypoxia under relevant physiological conditions. We demonstrated the feasibility of NO 2 ‐Rosol to afford tumor hypoxia imaging in vivo via it demonstrating a tumor‐to‐background of 5 upon (i) diffusion throughout, (ii) bioreductive activation by NTR activity in, and (iii) retention within, GBM39 tumor tissue. Conclusion We established the robustness, suitability, and feasibility of NO 2 ‐Rosol for imaging hypoxia under relevant oxygenation levels in vitro and in vivo via assessing NTR activity in GBM39 models.

Hettie, Kenneth S.↗
DOE OSTI2020

Mechanistic modelling of SARS-CoV-2 and other infectious diseases and the effects of therapeutics

Modern viral kinetic modeling and its application to therapeutics is a field that attracted the attention of the medical, pharmaceutical and modeling communities during the early days of the AIDS epidemic. Its successes lead to applications of modeling methods not only to HIV but a plethora of other viruses, such as hepatitis C virus (HCV), hepatitis B virus (HBV) and cytomegalovirus (CMV), which along with HIV cause chronic diseases, and viruses such as influenza, respiratory syncytial virus (RSV), West Nile virus (WNV), Zika virus, and SAR-CoV-2, which generally cause acute infections. Here we first review the historical development of mathematical models to understand HIV and HCV infections and the effects of treatment by fitting the models to clinical data. Furthermore, we then focus on recent efforts and contributions of applying these models towards understanding SARS-CoV-2 infection and highlight outstanding questions where modeling can provide crucial insights and help to optimize non-pharmaceutical and pharmaceutical interventions of the COVID-19 pandemic. The review is written from our personal perspective emphasizing the power of simple target cell limited models that provided important insights and then their evolution into more complex models that captured more of the virology and immunology. To quote Albert Einstein “Everything should be made as simple as possible, but not simpler”, and this idea underlies the modeling we describe below.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Recommendations for developing, documenting, and distributing data products derived from NEON data

The National Ecological Observatory Network (NEON) provides over 180 distinct data products from 81 sites (47 terrestrial and 34 freshwater aquatic sites) within the United States and Puerto Rico. These data products include both field and remote sensing data collected using standardized protocols and sampling schema, with centralized quality assurance and quality control (QA/QC) provided by NEON staff. Such breadth of data creates opportunities for the research community to extend basic and applied research while also extending the impact and reach of NEON data through the creation of derived data products—higher level data products derived by the user community from NEON data. Derived data products are curated, documented, reproducibly-generated datasets created by applying various processing steps to one or more lower level data products—including interpolation, extrapolation, integration, statistical analysis, modeling, or transformations. Derived data products directly benefit the research community and increase the impact of NEON data by broadening the size and diversity of the user base, decreasing the time and effort needed for working with NEON data, providing primary research foci through the development via the derivation process, and helping users address multidisciplinary questions. Creating derived data products also promotes personal career advancement to those involved through publications, citations, and future grant proposals. However, the creation of derived data products is a nontrivial task. Here we provide an overview of the process of creating derived data products while outlining the advantages, challenges, and major considerations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2011

Health, safety, and environmental risks from energy production: A year-long reality check

Large-scale carbon dioxide capture and storage (CCS) offers the benefit of reducing CO{sub 2} emissions and thereby mitigating climate change risk, but it will also bring its own health, safety, and environmental risks. Curtis M. Oldenburg, Editor-in-Chief, considers these risks in the context of the broader picture of energy production. Over the last year, there have been major acute health, safety, and environmental (HSE) consequences related to accidents involving energy production from every major primary energy source. These are, in chronological order: (i) the Upper Big Branch (coal) Mine disaster, (ii) the Gulf of Mexico Macondo (oil) well blowout, (iii) the San Bruno (natural gas) pipeline leak and explosion, and (iv) the Fukushima (nuclear) reactor radioactivity releases. Briefly, the Upper Big Branch Mine disaster occurred in West Virginia on April 5, 2010, when natural methane in the mine ignited, causing the deaths of 29 miners, the worst coal mine disaster in the USA since 1970. Fifteen days later, the Macondo oil well in the Gulf of Mexico suffered a blowout, with a gas explosion and fire on the floating drilling platform that killed 11 people. The oil and gas continued to flow out of the well at the seafloor until July 15, 2010, spilling a total of approximately 5 million barrels of oil into the sea. On September 9, 2010, a 30-inch (76-cm) buried, steel, natural gas pipeline in San Bruno, California, leaked gas and exploded in a residential neighborhood, killing 8 people in their homes and burning a total of 38 homes. Flames were up to 1000 ft (300 m) high, and the initial explosion itself reportedly measured 1.1 on the Richter scale. Finally, on March 11, 2011, a magnitude 9.0 earthquake off the coast of Japan's main island, Honshu, caused a tsunami that crippled the backup power and associated cooling systems for six reactor cores and their spent fuel storage tanks at the Fukushima nuclear power plant. At time of writing, workers trying to bring the crisis under control have been exposed to dangerous levels of radiation, and radioactive water and particulates have been released to the sea and atmosphere. These four disasters, all of which occurred within the past 12 months, were not unprecedented; similar events differing only in detail have happened around the world before, and such events will occur again. Today, developed nations primarily use fossil fuels to create affordable energy for comforts such as lighting, heating and air-conditioning, refrigeration, transportation, education, and entertainment, as well as for powering manufacturing, which creates jobs and a wealth of material goods. In addition to the risks of the existing energy infrastructure that have become obvious through these recent disasters, there is also the ongoing risk of climate change that comes from the vast emissions of greenhouse gases, primarily CO{sub 2}, from the burning of fossil fuels. The implementation of CO{sub 2} capture and storage (CCS) will help mitigate CO{sub 2} emissions from fossil fuel energy, but it also carries with it HSE risks. In my personal interactions with the public and with students, the main concern voiced is whether CO{sub 2} could leak out of the deep reservoirs into which it is injected and rise up out of the ground, smothering people and animals at the ground surface. Another concern expressed is that CO{sub 2} pipelines could fail and cause similar gaseous plumes of CO{sub 2}. The widespread concerns about CO{sub 2} leaking out over the ground surface may be inspired by events that have happened within natural systems in equatorial Africa, in Indonesia, and in Italy. Researchers have been investigating a wide variety of HSE risks of geologic CO{sub 2} storage for some time and have determined that wells are the main potential pathways for significant leakage from the deep subsurface. I discuss the acute HSE risks of CO{sub 2} leakage through wells and from pipelines, and compare the behavior of failures in CO{sub 2} wells and pipelines with oil and gas analogues from which most of our experience derives.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Connectivity‐based parcellation of normal and anatomically distorted human cerebral cortex

Abstract For over a century, neuroscientists have been working toward parcellating the human cortex into distinct neurobiological regions. Modern technologies offer many parcellation methods for healthy cortices acquired through magnetic resonance imaging. However, these methods are suboptimal for personalized neurosurgical application given that pathology and resection distort the cerebrum. We sought to overcome this problem by developing a novel connectivity‐based parcellation approach that can be applied at the single‐subject level. Utilizing normative diffusion data, we first developed a machine‐learning (ML) classifier to learn the typical structural connectivity patterns of healthy subjects. Specifically, the Glasser HCP atlas was utilized as a prior to calculate the streamline connectivity between each voxel and each parcel of the atlas. Using the resultant feature vector, we determined the parcel identity of each voxel in neurosurgical patients ( n = 40) and thereby iteratively adjusted the prior. This approach enabled us to create patient‐specific maps independent of brain shape and pathological distortion. The supervised ML classifier re‐parcellated an average of 2.65% of cortical voxels across a healthy dataset ( n = 178) and an average of 5.5% in neurosurgical patients. Our patient dataset consisted of subjects with supratentorial infiltrating gliomas operated on by the senior author who then assessed the validity and practical utility of the re‐parcellated diffusion data. We demonstrate a rapid and effective ML parcellation approach to parcellation of the human cortex during anatomical distortion. Our approach overcomes limitations of indiscriminately applying atlas‐based registration from healthy subjects by employing a voxel‐wise connectivity approach based on individual data.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Alcohol consumption and breast cancer risk in Japan: A pooled analysis of eight population‐based cohort studies

Abstract Although alcohol consumption is reported to increase the incidence of breast cancer in European studies, evidence for an association between alcohol and breast cancer in Asian populations is insufficient. We conducted a pooled analysis of eight large‐scale population‐based prospective cohort studies in Japan to evaluate the association between alcohol (both frequency and amount) and breast cancer risk with categorization by menopausal status at baseline and at diagnosis. Estimated hazard ratios (HR) and 95% confidence intervals were calculated in the individual cohorts and combined using random‐effects models. Among 158 164 subjects with 2 369 252 person‐years of follow‐up, 2208 breast cancer cases were newly diagnosed. Alcohol consumption had a significant association with a higher risk of breast cancer in both women who were premenopausal at baseline (regular drinker compared to nondrinker: HR 1.37, 1.04‐1.81, ≥23 g/d compared to 0 g/d: HR 1.74, 1.25‐2.43, P for trend per frequency category: P = .017) and those who were premenopausal at diagnosis (≥23 g/d compared to 0 g/d: HR 1.89, 1.04‐3.43, P for trend per frequency category: P = .032). In contrast, no significant association was seen in women who were postmenopausal at baseline or at diagnosis, despite a substantial number of subjects and long follow‐up period. Our results revealed that frequent and high alcohol consumption are both risk factors for Asian premenopausal breast cancer, similarly to previous studies in Western countries. The lack of a clear association in postmenopausal women in our study warrants larger investigation in Asia.

Iwase, Madoka↗
DOE OSTI2021

What's Left for a Computational Chemist To Do in the Age of Machine Learning?

Machine learning (ML) has become a central focus of the computational chemistry community. In this paper, I will first discuss my personal history in the field. Then I will provide a broader view of how this resurgence in ML interest echoes and advances upon earlier efforts. Although numerous changes have brought about this latest wave, one of the most significant is the increased accuracy and efficiency of low-cost methods (e.g., density functional theory or DFT) that have made it possible to generate large data sets for ML models. ML has also been used to bypass, guide, or improve DFT. The field of computational chemistry thus finds itself at a crossroads as ML both augments and supersedes traditional efforts. I will present what I believe the role of the computational chemist will be in this evolving landscape, with specific focus on my experience in the development of autonomous workflows in computational materials discovery for open-shell transition-metal chemistry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗