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Results for “bio engineered”

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 OSTI2019

Perovskite nickelates as bio-electronic interfaces

Functional interfaces between electronics and biological matter are essential to diverse fields including health sciences and bio-engineering. In this work, we report the discovery of spontaneous (no external energy input) hydrogen transfer from biological glucose reactions into SmNiO 3 , an archetypal perovskite quantum material. The enzymatic oxidation of glucose is monitored down to ~5 × 10 ⁻16 M concentration via hydrogen transfer to the nickelate lattice. The hydrogen atoms donate electrons to the Ni d orbital and induce electron localization through strong electron correlations. By enzyme specific modification, spontaneous transfer of hydrogen from the neurotransmitter dopamine can be monitored in physiological media. We then directly interface an acute mouse brain slice onto the nickelate devices and demonstrate measurement of neurotransmitter release upon electrical stimulation of the striatum region. These results open up avenues for use of emergent physics present in quantum materials in trace detection and conveyance of bio-matter, bio-chemical sciences, and brain-machine interfaces.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Mechanical analysis of heterogeneous materials with higher-order parameters

Abstract Even though heterogeneous porous materials are widely used in a variety of engineering and scientific fields, such as aerospace, energy-storage technology, and bio-engineering, the relationship between effective material properties of porous materials and their underlying morphology is still not fully understood. To contribute to this knowledge gap, this paper adopts a higher-order asymptotic homogenization method to numerically investigate the effect of complex micropore morphology on the effective mechanical properties of a porous system. Specifically, we use the second-order scheme that is an extension of the first-order computational homogenization framework, where a generalized continuum enables us to introduce length scale into the material constitutive law and capture both pore size and pore distribution. Through several numerical case studies with different combinations of porosity, pore shapes, and distributions, we systematically studied the relationship between the underlying morphology and effective mechanical properties. The results highlight the necessity of higher-order homogenization in understanding the mechanical properties and reveal that higher-order parameters are required to capture the role of realistic pore morphologies on effective mechanical properties. Furthermore, for specific pore shapes, higher-order parameters exhibit dominant influence over the first-order continuum.

42 ENGINEERING↗
DOE OSTI2020

Structure of disordered TiO 2 phases from ab initio based deep neural network simulations

Amorphous TiO 2 (a-TiO 2 ) is widely used in many fields, ranging from photo-electrochemistry to bio-engineering, hence detailed knowledge of its atomic structure is of scientific and technological interest. Here we use an ab initio-based deep neural network potential (DP) to simulate large scale atomic models of crystalline and disordered TiO 2 with molecular dynamics. Our DP reproduces the structural properties of all (11) TiO 2 crystalline phases, predicts the densities and structure factors of molten and amorphous TiO 2 with only a few percent deviation from experiments, and describes the pressure dependence of the amorphous structure in agreement with recent observations. Furthermore, it can be extended to model additional structures and compositions and can be thus of great value in the study of TiO 2 -based (nano-)materials.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Corrosion Potential of Selected Bio-blendstock Fuel Candidates for Boosted Spark Ignited Engines

Eight bio-blendstock fuel candidates for boosted spark ignited engines were evaluated for their susceptibility to corrode infrastructure metals. These candidates included five alcohols (methanol, ethanol, isobutanol, n-propanol, and isopropanol), diisobutylene, mixed furans, and aromatics. Methanol was also added to the list for comparison. These molecules are not corrosive to metals since they cannot dissociate into ions and anions. However, the addition of contaminants and a separate water phase may facilitate corrosion due to phenomena associated with the formation of ions and anions (from key contaminants), differential aeration cell (due to dissolved oxygen), and microbial-induced corrosion. A literature review was conducted to determine the influence of these phenomena on corrosion for the nine fuel candidates. In addition, the oxygen solubility of each fuel type was determined to ascertain their relative influence on forming and enhancing a differential aeration cell. Of the fuel candidates, only the alcohols are water soluble, and therefore have an opportunity to cause corrosion. However, differential aeration cells, by themselves have not been shown to contribute to corrosion. Other factors, such as galvanic coupling and/or crevice regions are necessary to promote corrosion in laboratory conditions. However, differential aeration as a corrosion mechanism has not been established in the field. Likewise, microbial-induced corrosion is another known corrosion pathway that has yet to be positively identified for blends of the fuel candidates with gasoline. In summary, corrosion is not anticipated with any of the bio-blendstock candidates with infrastructure metals.

09 BIOMASS FUELS↗
DOE OSTI2021

Genome-Scale Metabolic Model of Caldicellulosiruptor bescii Reveals Optimal Metabolic Engineering Strategies for Bio-based Chemical Production

The extremely thermophilic cellulolytic bacterium, Caldicellulosiruptor bescii , degrades plant biomass at high temperatures without any pretreatments and can serve as a strategic platform for industrial applications. The metabolic engineering of C. bescii , however, faces potential bottlenecks in bio-based chemical productions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Artificial Intelligence

Artificial intelligence is the study of intelligence agents as demonstrated by machines. It is an interdisciplinary field involving computer science as well as, various kinds of engineering and science, for example, robotics, bio-medical engineering, that accentuates automation of human acts and intelligence through machines. AI represents state-of-the-art use of machines to bring about algorithmic computation and understanding of tasks that include learning, problem solving, mapping, perception, and reasoning. Given the data and a description of its properties and relations between objects of interest, AI methods can perform the aforementioned tasks. Widely applied AI capabilities, e.g. learning, are now achievable at large scale through machine learning (ML), large volumes of data and specialized computational machines. ML encompasses learning without any kind of supervision (unsupervised learning) and learning with full supervision (supervised learning). Widely applied supervised learning techniques include deep learning and other machine learning methods that require less data than deep learning e.g. support vector machines, random forests. Unsupervised learning examples include dictionary learning, independent component analysis, and autoencoders. For application tasks with less labeled data, both supervised and unsupervised techniques can be adapted in a semi-supervised manner to produce accurate models and to increase the size of the labeled training data.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Sooting tendencies of 20 bio-derived fuels for advanced spark-ignition engines

The sooting tendencies of 20 bio-derived fuels indicated as potential blendstocks for spark-ignition engines by the Co-Optimization of Fuels & Engines (Co-Optima) Initiative are studied. The Yield Sooting Index (YSI) is used to quantify the sooting tendencies. The Co-Optima Chemical Model is used to predict the numerical YSIs for all test fuels, and these results are compared with measurements. Experimental YSIs are newly measured for 2 furans and are taken from our previous work for the other compounds. Overall, the predicted YSIs agree well with measurements, within the experimental uncertainties, except for 2,5-dimethylfuran (2,5-DMF). It is found that Polycyclic Aromatic Hydrocarbons (PAH) growth reactions have little influence on the relative soot production from each fuel and therefore on YSI predictions. A modified sensitivity coefficient formulation is proposed to evaluate reaction sensitivities specifically for YSI. This formulation is applied to the 2,5-DMF-doped flame, and six 2,5-DMF initial decomposition reactions, which lead to different major soot precursors, are identified as the most sensitive reactions. The impact of the chemical kinetic uncertainties embedded in these reactions is quantified by randomly perturbing their reaction rates within a factor of two. The resulting prediction uncertainty in the 2,5-DMF-doped flame is found to be ± 8 YSI units (±11%), which demonstrates that the test-fuel-specific decomposition reactions indeed have considerable influence on its YSI prediction. Our research suggests that more accurate kinetic parameters for fuel initial decomposition reactions can potentially improve YSI predictions effectively, without altering the YSI predictions of other fuels with significantly different molecular structures.

09 BIOMASS FUELS↗
DOE OSTI2018

Toward engineering E. coli with an autoregulatory system for lignin valorization

Significance Lignin valorization is critical for economic viability of future biorefineries but is hindered due to the challenges of engineered bio-chassis such as the slow kinetics of substrate uptake, aromatics toxicity, and cost. Here, an autoregulatory system involving a vanillin autoinducible promoter is demonstrated with an aromatics transporter in Escherichia coli that is induced by lignin-derived aromatics and simultaneously converted to value-added platform chemical with diverse applications. In addition to alleviating toxicity, the engineered E. coli strain eliminates the need for an external inducer such as isopropyl β- d -1-thiogalactopyranoside during fermentation, thereby significantly reducing the process cost. This study demonstrates an autoregulatory system for aromatics bioconversion and serves as a platform for future strain development for lignin valorization.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Deciphering Time-Dependent DNA Damage Complexity, Repair, and Oxygen Tension: A Mechanistic Model for FLASH-Dose-Rate Radiation Therapy

Irradiation with ultrahigh dose rates (FLASH) has reemerged as a promising radiation therapy approach to effectively lower potential damage burden on normal tissue without sacrificing tumor control. However, the large number of recent FLASH studies have been conducted under vastly different experimental conditions and circumstances (ie, investigated biological endpoint, radiation quality, and environmental oxygen level), with unverified biological mechanisms of action and unexplored interplay effect of the main dependencies. To facilitate radiobiological investigation of FLASH phenomena and assessment of clinical applicability, we present an extension of the mechanistic radiobiological model “UNified and VERSatile bio response Engine” (UNIVERSE).

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2017

Biotemplated synthesis of inorganic materials: An emerging paradigm for nanomaterial synthesis inspired by nature

Biomineralization, the process by which biological systems direct the synthesis of inorganic structures from organic templates, is an exquisite example of nanomaterial self-assembly in nature. Its products include the shells of mollusks and the bones and teeth of vertebrates. By comparison, conventional inorganic synthesis techniques provide limited control over inorganic nanomaterial architecture. Inspired by biomineralization in nature, over the last two decades, the field of biotemplating has emerged as a new paradigm for inorganic nanomaterial assembly, wherein researchers seek to design novel nano-structures in which inorganic nanomaterial synthesis is directed from an underlying biomolecular template. Here, we review the motivation, mechanistic understanding, progress, and challenges for the field of biotemplating. We highlight the interdisciplinary nature of this field, and survey a broad range of examples of bio-templated engineering: ranging from strategies that exploit the inherent capabilities of proteins in nature, to genetically-engineered systems that unlock new capabilities for self-assembly with biomolecules. Here, we illustrate that the use of biological materials as templates for inorganic self-assembly holds tremendous potential for nanomaterial engineering, with applications that range from electronics and energy to medicine.

36 MATERIALS SCIENCE↗