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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 883 records · Page 49
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Process Intensification for the Biological Production of the Fuel Precursor Butyric Acid from Biomass

The production of fuels from lignocellulosic biomass is key to reduce our reliance on petroleum and to promote a sustainable bioeconomy. Butyric acid (BA) is a promising chemical precursor for the production of renewable diesel and jet fuels. BA can be biologically produced from lignocellulosic sugars. However, challenges associated with product selectivity and recovery must be overcome to achieve industrially relevant metrics. Here, we evaluate various fermentation configurations and demonstrate near-homo-butyrate production by using the biocatalyst Clostridium tyrobutyricum. We also develop an advanced in situ product recovery process based on hybrid extraction-distillation (HED-ISPR) and conduct techno-economic analyses and life cycle assessments. We demonstrate that the HED-ISPR process lowers the overall capital and operating expenses and environmental impact compared to other traditional fermentation processes. Overall, BA minimum product selling price from biomass is 55% of the current BA selling price from petroleum, a significant decrease toward viable renewable fuel production.

09 BIOMASS FUELS↗
DOE OSTI2017

Review on landfill leachate treatment by electrochemical oxidation: Drawbacks, challenges and future scope

Highlights: • Comparison is made between conventional and bioreactor landfill leachate. • Organics and ammonium nitrogen removal mechanism have been described. • Various influencing factors of EO process have been discussed. • Application of EO combined with biological/physicochemical process is reviewed. • Incorporation of LCA in LL treatment technology selection is proposed. - Abstract: Various studies on landfill leachate treatment by electrochemical oxidation have indicated that this process can effectively reduce two major pollutants present in landfill leachate; organic matter and ammonium nitrogen. In addition, the process is able to enhance the biodegradability index (BOD/COD) of landfill leachate, which make mature or stabilized landfill leachate suitable for biological treatment. The elevated concentration of ammonium nitrogen especially observed in bioreactor landfill leachate can also be reduced by electrochemical oxidation. The pollutant removal efficiency of the system depends upon the mechanism of oxidation (direct or indirect oxidation) which depends upon the property of anode material. Applied current density, pH, type and concentration of electrolyte, inter-electrode gap, mass transfer mode, total anode area to volume of effluent to be treated ratio, temperature, flow rate or flow velocity, reactor geometry, cathode material and lamp power during photoelectrochemical oxidation may also influence the system performance. In this review paper, past and present scenarios of landfill leachate treatment efficiencies and costs of various lab scale, pilot scale electrochemical oxidation studies as a standalone system or integrated with biological and physicochemical processes have been reviewed with the conclusion that electrochemical oxidation can be employed as a complementary treatment system with biological process for conventional landfill leachate treatment as well as a standalone system for ammonium nitrogen removal from bioreactor landfill leachate. Furthermore, present drawbacks of electrochemical oxidation process as a landfill leachate treatment system and relevance of incorporating life cycle assessment into the decision-making process besides process efficiency and cost, have been discussed.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Determination of Total, Organic, and Inorganic Carbon in Biological Cultures and Liquid Fraction Process Samples

This procedure describes a method for analyzing dissolved and suspended total carbon, in organic and inorganic form in biological cultures, in the presence or absence of cells, and liquid fraction conversion process samples. This method calculates total organic carbon by subtraction of inorganic carbon, derived from sample acidification, from total dissolved carbon by combustion at 680°C with detection of derived gaseous CO 2 by a non-dispersive infrared (NDIR) sensor. The inclusion of details on a process step of heat treating biologically active samples before analysis can potentially halt biological activity, preserving carbon stores and allowing for accurate quantification of the carbon content at the time of sample collection.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Crowdsourcing and curation: perspectives from biology and natural language processing

Crowdsourcing is increasingly utilized for performing tasks in both natural language processing and biocuration. Although there have been many applications of crowdsourcing in these fields, there have been fewer high-level discussions of the methodology and its applicability to biocuration. This paper explores crowdsourcing for biocuration through several case studies that highlight different ways of leveraging ‘the crowd’; these raise issues about the kind(s) of expertise needed, the motivations of participants, and questions related to feasibility, cost and quality. The paper is an outgrowth of a panel session held at BioCreative V (Seville, September 9–11, 2015). The session consisted of four short talks, followed by a discussion. In their talks, the panelists explored the role of expertise and the potential to improve crowd performance by training; the challenge of decomposing tasks to make them amenable to crowdsourcing; and the capture of biological data and metadata through community editing.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2017

Optimization of Poly(DL-Lactic Acid) Degradation and Evaluation of Biological Re-polymerization

Poly(DL-lactic acid) or PLA is a biodegradable polymer. It has received much attention since it plays an important role in resolving the global warming problem. The protease produced by Actinomadura keratinilytica strain T16-1 was previously reported as having PLA depolymerase potential and being applicable to PLA biodegradation, which was used in this work. Therefore, this research demonstrates the important basic knowledge on the biological degradation process by the crude PLA-degrading enzyme from strain T16-1. Its re-polymerization was evaluated. The optimization of PLA degradation by statistical methods based on central composite design was determined. Approximately 6700 mg/l PLA powder was degraded by the crude enzyme under optimized conditions: an initial enzyme activity of 200 U/ml, incubated at 60 °C for 24 h released 6843 mg/l lactic acid with 82% conversion, which was similar to the commercial enzyme proteinase K (81%). The degradable products were re-polymerized repeatedly by using commercial lipase as a catalyst under a nitrogen atmosphere for 6 h. A PLA oligomer was achieved with a molecular weight of 378 Da (n = 5). This is the first report to demonstrate the high efficiency of the enzyme to degrade 100% of PLA powder and to show the biological recycling process of PLA, which is promising for the treatment and utilization of biodegradable plastic wastes in the future.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Contrasting effects of glutamate and branched-chain amino acid metabolism on acid tolerance in a Castellaniella isolate from acidic groundwater

Groundwater acidification co-occurring with nitrate pollution is a common, global environmental health hazard. Denitrifying bacteria have been leveraged for the in situ removal of nitrate in groundwater. However, co-existing stressors—such as low pH—reduce the efficacy of biological removal processes. Castellaniella sp. str. MT123 is a complete denitrifier that was isolated from acidic, nitrate-contaminated groundwater. The strain grows robustly by nitrate respiration at pH < 6.0, completely reducing nitrate to dinitrogen gas. Genomic analyses of MT123 revealed few previously characterized acid tolerance genes. Thus, we utilized a combination of proteomics, metabolomics, and competitive mutant fitness to characterize the genetic mechanisms of MT123 acclimation to growth under mildly acidic conditions. We found that glutamate accumulation is critical in the acid acclimation of MT123, possibly through consumption of intracellular protons via glutamate decarboxylation to GABA. This is despite the fact that MT123 lacks the canonical glutamate decarboxylase-glutamate/GABA antiporter system implicated in acid tolerance in other bacteria. In contrast, branched-chain amino acid (BCAA) accumulation was detrimental to cell growth at lower pHs, possibly through indirect mechanisms impacting the cellular glutamate pool. Genetic analysis previously linked MT123 to a population of Castellaniella that bloomed—concurrent to nitrate removal—during a biostimulation effort to reduce groundwater nitrate concentrations at MT123’s location of origin. Thus, our analyses provide novel insight into mechanisms of acclimation to acidic conditions in a strain with significant potential for nitrate bioremediation.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1984

Global Biology Research Program: Biogeochemical Processes in Wetlands

The results of a workshop examining potential NASA contributions to research on wetland processes as they relate to global biogeochemical cycles are summarized. A wetlands data base utilizing remotely sensed inventories, studies of wetland/atmosphere exchange processes, and the extrapolation of local measurements to global biogeochemical cycling processes were identified as possible areas for NASA support.

Bartlett, D. S.↗
NASA NTRS2016

Thirsty Walls: A New Paradigm for Air Revitalization in Life Support

This Phase I project Summary will be formatted as a series of summary statements, with additional comments. The summary statements are intended to focus on the most significant findings and discoveries – things that the project team knows now, but we didn’t know at the beginning of the project: 1) Direct Contact Between Gases is an ECLS (Environmental Control and Life Support) System enabling capability; 2) CO2 capture using liquid sorbents in microgravity is feasible; 3) There are other ways to contact gases and liquids – but thin film capillary techniques are new, exciting, and have amazing potential; 4) ECLS system reliability is the key to exploration missions – the key to reliability is having system attributes that favor reliability; 5) The processes with favorable reliability attributes tend to be biological; 6) The single greatest impact on launch mass of an ECLS system is water. The best way to enable biological water processing is to develop a capillary based method of urine capture that doesn’t use pretreat chemicals; 7) There is good, promising, forward design and development work – but no fundamental “show stoppers” – to develop a thin film liquid sorbent CO2 capture system; 8) The most capable Ionic Liquids are not presently feasible, but other chemically active liquids can be used to make an effective thin film CO2 capture device; 9) The C9 reduced gravity flight showed feasibility – and taught us about flow instability issues; 10) Capillary fluid management has ECLS system wide implications.

CO2↗
DOE OSTI2019

Acceleration and Stabilization of Electron Transfer Products with Improved Quantum Yields upon Cation Binding to a Fused Bis-Zinc Porphyrin-Quinone Donor–Acceptor Conjugate

The role of metal ions in promoting electron transfer processes in biological coenzymes is of great significance not only to understand their mechanistic details but also due to their direct utilization in a number of chemical and biochemical processes. Here, we demonstrate an increased rate of forward electron transfer with improved reaction quantum yield, and an enhanced lifetime of electron transfer products upon cation binding to the acceptor entity in a donor-acceptor conjugate. Selective binding of cations such as Mg 2+ or Sc 3+ to the electron acceptor, quinone, in a fused, bis-zinc porphyrin-quinone donor-acceptor conjugate leads to facile reduction of the quinone making the electron transfer process thermodynamically highly feasible. Furthermore, the binding of metal ions to the electron transfer product, quinone anion, decelerates the reverse electron transfer process due to ion-pairing interactions, resulting in improving both the lifetime and quantum yields of the electron transfer products. Furthermore, systematic studies including spectral, electrochemical, computational, spectroelectrochemical, and transient absorption techniques, coupled with data analysis by Global Target Analysis (GloTarAn), are performed to demonstrate these novel findings that are relevant to further our understanding of electron transfer processes occurring in biological coenzymes and pertinent energy harvesting schemes.

Charge transfer↗
NASA NTRS1984

Inland Aquatic Resources and Biogeochemical Cycles

The biosphere is the entire planetary system that includes, sustains and is influenced by life. The central issue of the science of the biosphere is the extent to which the Earth's surface, atmosphere and hydrosphere is the result of biological rather than abiotic processes. Space science and technology accelerates the understanding of global biological processes by providing repetive synoptic observations on large spatial scales once the relationships between the processes and the remotely sensed quantities are established. Especially promising applications of space technology are the measurement of biological productivity and portions of geochemical cycles in aquatic ecosystems and the evaluation and management of the quality of freshwater resources.

Melack, J. M.↗
NASA NTRS2008

Growth Control and Disease Mechanisms in Computational Embryogeny

This paper presents novel approach to applying growth control and diseases mechanisms in computational embryogeny. Our method, which mimics fundamental processes from biology, enables individuals to reach maturity in a controlled process through a stochastic environment. Three different mechanisms were implemented; disease mechanisms, gene suppression, and thermodynamic balancing. This approach was integrated as part of a structural evolutionary model. The model evolved continuum 3-D structures which support an external load. By using these mechanisms we were able to evolve individuals that reached a fixed size limit through the growth process. The growth process was an integral part of the complete development process. The size of the individuals was determined purely by the evolutionary process where different individuals matured to different sizes. Individuals which evolved with these characteristics have been found to be very robust for supporting a wide range of external loads.

Genetic algorithm↗
DOE OSTI2026

Divergent carbon use efficiency-growth rate tradeoff in popular biological growth models

Carbon use efficiency (CUE) is an important trait emerging from processes regulating biological growth. CUE can be computed either based on the growth of structural biomass or total biomass divided by substrate uptake rate. Nonequilibrium thermodynamics and observations suggest that, for an exponentially growing population of cells, structural biomass CUE should first increase, then peak, and finally decrease with specific growth rate; meanwhile, total biomass CUE increases asymptotically with specific growth rate. We compared predictions from six popular models that are often used for plant and microbial growth in existing ecosystem models. We found that, for an exponentially growing population of biological cells, (1) the source-driven Pirt and Compromise models predict that structural biomass CUE increase asymptotically with growth rate; (2) the apparent sink-driven modified Droop model predicts that structural biomass CUE decreases with growth rate; and (3) the sink-driven variable internal storage model and two dynamic energy budget models predict that structural biomass CUE first increases, then peaks, and finally decreases with growth rate. Moreover, the modified Droop model predicts that total biomass CUE is constant with growth rate, while all other five models predict that total biomass CUE increases with growth rate asymptotically. For non-exponential biological growth, we show that there is no static relationship between total biomass CUE or structural biomass CUE with respect to either growth rate or temperature. Therefore, we contend that biological growth models should explicitly represent interactions between substrate acquisition, substate transformation, and maintenance respiration to better capture observed CUE dynamics, and the sink-driven model should be preferred for general ecosystem biogeochemistry modeling.

Tang, Jinyun [Lawrence Berkeley National Laborator↗
DOE OSTI2016

WE-DE-202-00: Connecting Radiation Physics with Computational Biology

Radiation therapy for the treatment of cancer has been established as a highly precise and effective way to eradicate a localized region of diseased tissue. To achieve further significant gains in the therapeutic ratio, we need to move towards biologically optimized treatment planning. To achieve this goal, we need to understand how the radiation-type dependent patterns of induced energy depositions within the cell (physics) connect via molecular, cellular and tissue reactions to treatment outcome such as tumor control and undesirable effects on normal tissue. Several computational biology approaches have been developed connecting physics to biology. Monte Carlo simulations are the most accurate method to calculate physical dose distributions at the nanometer scale, however simulations at the DNA scale are slow and repair processes are generally not simulated. Alternative models that rely on the random formation of individual DNA lesions within one or two turns of the DNA have been shown to reproduce the clusters of DNA lesions, including single strand breaks (SSBs), double strand breaks (DSBs) without the need for detailed track structure simulations. Efficient computational simulations of initial DNA damage induction facilitate computational modeling of DNA repair and other molecular and cellular processes. Mechanistic, multiscale models provide a useful conceptual framework to test biological hypotheses and help connect fundamental information about track structure and dosimetry at the sub-cellular level to dose-response effects on larger scales. In this symposium we will learn about the current state of the art of computational approaches estimating radiation damage at the cellular and sub-cellular scale. How can understanding the physics interactions at the DNA level be used to predict biological outcome? We will discuss if and how such calculations are relevant to advance our understanding of radiation damage and its repair, or, if the underlying biological processes are too complex for a mechanistic approach. Can computer simulations be used to guide future biological research? We will debate the feasibility of explaining biology from a physicists’ perspective. Learning Objectives: Understand the potential applications and limitations of computational methods for dose-response modeling at the molecular, cellular and tissue levels Learn about mechanism of action underlying the induction, repair and biological processing of damage to DNA and other constituents Understand how effects and processes at one biological scale impact on biological processes and outcomes on other scales J. Schuemann, NCI/NIH grantsS. McMahon, Funding: European Commission FP7 (grant EC FP7 MC-IOF-623630)

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

WE-DE-202-01: Connecting Nanoscale Physics to Initial DNA Damage Through Track Structure Simulations

Radiation therapy for the treatment of cancer has been established as a highly precise and effective way to eradicate a localized region of diseased tissue. To achieve further significant gains in the therapeutic ratio, we need to move towards biologically optimized treatment planning. To achieve this goal, we need to understand how the radiation-type dependent patterns of induced energy depositions within the cell (physics) connect via molecular, cellular and tissue reactions to treatment outcome such as tumor control and undesirable effects on normal tissue. Several computational biology approaches have been developed connecting physics to biology. Monte Carlo simulations are the most accurate method to calculate physical dose distributions at the nanometer scale, however simulations at the DNA scale are slow and repair processes are generally not simulated. Alternative models that rely on the random formation of individual DNA lesions within one or two turns of the DNA have been shown to reproduce the clusters of DNA lesions, including single strand breaks (SSBs), double strand breaks (DSBs) without the need for detailed track structure simulations. Efficient computational simulations of initial DNA damage induction facilitate computational modeling of DNA repair and other molecular and cellular processes. Mechanistic, multiscale models provide a useful conceptual framework to test biological hypotheses and help connect fundamental information about track structure and dosimetry at the sub-cellular level to dose-response effects on larger scales. In this symposium we will learn about the current state of the art of computational approaches estimating radiation damage at the cellular and sub-cellular scale. How can understanding the physics interactions at the DNA level be used to predict biological outcome? We will discuss if and how such calculations are relevant to advance our understanding of radiation damage and its repair, or, if the underlying biological processes are too complex for a mechanistic approach. Can computer simulations be used to guide future biological research? We will debate the feasibility of explaining biology from a physicists’ perspective. Learning Objectives: Understand the potential applications and limitations of computational methods for dose-response modeling at the molecular, cellular and tissue levels Learn about mechanism of action underlying the induction, repair and biological processing of damage to DNA and other constituents Understand how effects and processes at one biological scale impact on biological processes and outcomes on other scales J. Schuemann, NCI/NIH grantsS. McMahon, Funding: European Commission FP7 (grant EC FP7 MC-IOF-623630)

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

WE-DE-202-02: Are Track Structure Simulations Truly Needed for Radiobiology at the Cellular and Tissue Levels?

Radiation therapy for the treatment of cancer has been established as a highly precise and effective way to eradicate a localized region of diseased tissue. To achieve further significant gains in the therapeutic ratio, we need to move towards biologically optimized treatment planning. To achieve this goal, we need to understand how the radiation-type dependent patterns of induced energy depositions within the cell (physics) connect via molecular, cellular and tissue reactions to treatment outcome such as tumor control and undesirable effects on normal tissue. Several computational biology approaches have been developed connecting physics to biology. Monte Carlo simulations are the most accurate method to calculate physical dose distributions at the nanometer scale, however simulations at the DNA scale are slow and repair processes are generally not simulated. Alternative models that rely on the random formation of individual DNA lesions within one or two turns of the DNA have been shown to reproduce the clusters of DNA lesions, including single strand breaks (SSBs), double strand breaks (DSBs) without the need for detailed track structure simulations. Efficient computational simulations of initial DNA damage induction facilitate computational modeling of DNA repair and other molecular and cellular processes. Mechanistic, multiscale models provide a useful conceptual framework to test biological hypotheses and help connect fundamental information about track structure and dosimetry at the sub-cellular level to dose-response effects on larger scales. In this symposium we will learn about the current state of the art of computational approaches estimating radiation damage at the cellular and sub-cellular scale. How can understanding the physics interactions at the DNA level be used to predict biological outcome? We will discuss if and how such calculations are relevant to advance our understanding of radiation damage and its repair, or, if the underlying biological processes are too complex for a mechanistic approach. Can computer simulations be used to guide future biological research? We will debate the feasibility of explaining biology from a physicists’ perspective. Learning Objectives: Understand the potential applications and limitations of computational methods for dose-response modeling at the molecular, cellular and tissue levels Learn about mechanism of action underlying the induction, repair and biological processing of damage to DNA and other constituents Understand how effects and processes at one biological scale impact on biological processes and outcomes on other scales J. Schuemann, NCI/NIH grantsS. McMahon, Funding: European Commission FP7 (grant EC FP7 MC-IOF-623630)

60 APPLIED LIFE SCIENCES↗
NASA NTRS2019

Uncertainties in the Geostationary Ocean Color Imager (GOCI) Remote Sensing Reflectance for Assessing Diurnal Variability of Biogeochemical Processes

Short-term (sub-diurnal) biological and biogeochemical processes cannot be fully captured by the current suite of polar-orbiting satellite ocean color sensors, as their temporal resolution is limited to potentially one clear image per day. Geostationary sensors, such as the Geostationary Ocean Color Imager (GOCI) from the Republic of Korea, allow the study of these short-term processes because their orbit permit the collection of multiple images throughout each day for any area within the sensor’s field of regard. Assessing the capability to detect sub-diurnal changes in in-water properties caused by physical and biogeochemical processes characteristic of open ocean and coastal ocean ecosystems, however, requires an understanding of the uncertainties introduced by the instrument and/or geophysical retrieval algorithms. This work presents a study of the uncertainties during the daytime period for an ocean region with characteristically low-productivity with the assumption that only small and undetectable changes occur in the in-water properties due to biogeochemical processes during the daytime period. The complete GOCI mission data were processed using NASA’s SeaDAS/l2gen package. The assumption of homogeneity of the study region was tested using three-day sequences and diurnal statistics. This assumption was found to hold based on the minimal diurnal and day-to-day variability in GOCI data products. Relative differences with respect to the midday value were calculated for each hourly observation of the day in order to investigate what time of the day the variability is greater. Also, the influence of the solar zenith angle in the retrieval of remote sensing reflectances and derived products was examined. Finally, we determined that the uncertainties in water-leaving “remote-sensing” reflectance (Rrs) for the 412, 443, 490, 555, 660 and 680 nm bands on GOCI are 8.05 × 10−4, 5.49 × 10−4, 4.48 × 10−4, 2.51 × 10−4, 8.83 × 10−5, and 1.36 × 10−4 sr−1, respectively, and 1.09 × 10−2 mg m−3 for the chlorophyll-a concentration (Chl-a), 2.09 × 10−3 m−1 for the absorption coefficient of chromophoric dissolved organic matter at 412 nm (ag (412)), and 3.7 mg m−3 for particulate organic carbon (POC). These Rrs values can be considered the threshold values for detectable changes of the in-water properties due to biological, physical or biogeochemical processes from GOCI.

Geostationary Ocean Color Imager (GOCI)↗