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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 1,549 records · Page 86
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Modeling Evolvable Water Recovery Systems for Short and Long-Duration Missions in Partial Gravity

Water recovery technologies on the International Space Station (ISS) are designed and optimized for microgravity environments, thus creating a need for innovative systems optimized for mission operations in the presence of gravity. Alternative water recovery technologies under research by the Life Support Systems division were compiled into a series of Partial Gravity Water Recovery System (PGWRS) architectures. Individual unit processes were modeled via fundamental physical-chemical process equations to simulate their method of treatment, including chemical or biological oxidation, flash evaporation, filtration, or a combination of adsorption and ion exchange processes. Dimension and sizing data were then utilized to scale each architecture. Modeling was completed on an assortment of architectures assuming three scenarios in which treatment methods could take advantage of partial gravity: a short-duration mission with a temporary surface habitat, a longer duration mission with a more permanent habitat, and a long duration mission without resupply. Total system mass was estimated to quantitatively compare architectures within scenarios, but qualitative observations were also made regarding system robustness, flexibility, and capacity to meet more stringent demands. Technologies that traded most favorably between the scenarios were those that included a pre-oxidation stage to minimize mass loading to downstream absorption and ion exchange beds, exploited gravity in liquid-vapor separation processes, and reconstituted wastewater components into recyclable material streams.

Avery L. Carlson↗
DOE OSTI2016

Uncovering biologically significant lipid isomers with liquid chromatography, ion mobility spectrometry and mass spectrometry

Understanding how biological molecules are generated, metabolized and eliminated in living systems is important for interpreting processes such as immune response and disease pathology. While genomic and proteomic studies have provided vast amounts of information over the last several decades, interest in lipidomics has also grown due to improved analytical technologies revealing altered lipid metabolism in type 2 diabetes, cancer, and lipid storage disease. Liquid chromatography and mass spectrometry (LC-MS) measurements are currently the dominant approach for characterizing the lipidome by providing detailed information on the spatial and temporal composition of lipids. However, interpreting lipids’ biological roles is challenging due to the existence of numerous structural and stereoisomers (i.e. distinct acyl chain and double-bond positions), which are unresolvable using present LC-MS approaches. Here we show that combining structurally-based ion mobility spectrometry (IMS) with LC-MS measurements distinguishes lipid isomers and allows insight into biological and disease processes.

Environmental Molecular Sciences Laboratory↗
DOE OSTI2020

Synergistic Self-Assembly of Oxoanions and d-Block Metal Ions with Heteroditopic Receptors into Triple-Stranded Helicates

Cooperativity effects among the interconnected anion and cation binding sites can profoundly alter the performance of heteroditopic receptors in selective ion pair recognition, processes that are oftentimes pertinent to biological systems and chemical separations. In this paper, we report the effect of the linker that connects both binding sites on self-assembly of heteroditopic receptors in the presence of divalent first-row transition metal salts in solution and solid phase. Introduction of backbone flexibility in the receptor results in the formation of triple-stranded ion-pair helicates with an extraordinary selectivity towards CuSO 4 through an anion-induced fit.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Root identification in minirhizotron imagery with multiple instance learning

In this study, multiple instance learning (MIL) algorithms to automatically perform root detection and segmentation in minirhizotron imagery using only image-level labels are proposed. Root and soil characteristics vary from location to location, and thus, supervised machine learning approaches that are trained with local data provide the best ability to identify and segment roots in minirhizotron imagery. However, labeling roots for training data (or otherwise) is an extremely tedious and time-consuming task. This paper aims to address this problem by labeling data at the image level (rather than the individual root or root pixel level) and train algorithms to perform individual root pixel level segmentation using MIL strategies. Three MIL methods (multiple instance adaptive cosine coherence estimator, multiple instance support vector machine, multiple instance learning with randomized trees) were applied to root detection and compared to non-MIL approaches. The results show that MIL methods improve root segmentation in challenging minirhizotron imagery and reduce the labeling burden. In our results, multiple instance support vector machine outperformed other methods. The multiple instance adaptive cosine coherence estimator algorithm was a close second with an added advantage that it learned an interpretable root signature which identified the traits used to distinguish roots from soil and did not require parameter selection.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Unleashing the capacity of Rhodococcus for converting lignin into lipids

Bioconversion of bioresources/wastes (e.g., lignin, chemical pulping byproducts) represents a promising approach for developing a bioeconomy to help address growing energy and materials demands. Rhodococcus, a promising microbial strain, utilizes numerous carbon sources to produce lipids, which are precursors for synthesizing biodiesel and aviation fuels. However, compared to chemical conversion, bioconversion involves living cells, which is a more complex system that needs further understanding and upgrading. Various wastes amenable to bioconversion are reviewed herein to highlight the potential of Rhodococci for producing lipid-derived bioproducts. In light of the abundant availability of these substrates, Rhodococcus’ metabolic pathways converting them to lipids are analyzed from a “beginning-to-end” view. Based on an in-depth understanding of microbial metabolic routes, genetic modifications of Rhodococcus by employing emerging tools (e.g., multiplex genome editing, biosensors, and genome-scale metabolic models) are presented for promoting the bioconversion. Co-solvent enhanced lignocellulose fractionation (CELF) strategy facilitates the generation of a lignin-derived aromatic stream suitable for the Rhodococcus’ utilization. Novel alkali sterilization (AS) and elimination of thermal sterilization (ETS) approaches can significantly enhance the bioaccessibility of lignin and its derived aromatics in aqueous fermentation media, which promotes lipid titer significantly. In order to achieve value-added utilization of lignin, biodiesel and aviation fuel synthesis from lignin and lipids are further discussed. In conclusion, the possible directions for unleashing the capacity of Rhodococcus through synergistically modifying microbial strains, substrates, and fermentation processes are proposed toward a sustainable biological lignin valorization.

09 BIOMASS FUELS↗
DOE OSTI2019

Identifying and creating pathways to improve biological lignin valorization

Biological lignin valorization to fuels and value-added chemicals enables sustainable and economic biorefineries. Even though significant progress has been made, several major challenges arose due to high recalcitrance and heterogeneity of lignin, which needs to be addressed to improve lignin processing. This work demonstrates an overview of biological lignin conversion and its regulation from a metabolic engineering and systems biology viewpoint. Biological lignin valorization includes three stages: lignin depolymerization, aromatics degradation, and target product biosynthesis. Ligninolytic microorganisms have an extensive enzymatic toolbox to break down the lignin and convert heterogeneous lignin derivatives to central intermediates, such as protocatechuate or catechol, through a peripheral pathway. These intermediates undergo ring cleavage via the β-ketoadipate pathway and are ultimately transformed into metabolites by yielding acetyl-CoA for internal product biosynthesis, such as triacylglycerols, polyhydroxyalkanoates, etc. Bioprospecting will expand the knowledge base of ligninolytic microbial communities, strains, and enzymes to facilitate the understanding of aromatics metabolism. Systems biology analyses achieve an understanding of molecular and systems-level degradation mechanisms and metabolic pathways of lignin and aromatics. By identifying these mechanisms, synthetic biology provides promising approaches to create the lignin conversion pathways and engineer ligninolytic strains suitable as potential hosts for lignin conversion. Techno-economic analysis of biological lignin upgrading to coproducts in biorefineries will guide the implementation of lignin valorization by mitigating technical risk for scale-up and improving the profitability of biorefinery. Through improving the understanding of biological lignin valorization, it should be possible to create biological lignin valorization route to effectively produce value-added products from lignin.

09 BIOMASS FUELS↗
DOE OSTI2017

STK40 Is a Pseudokinase that Binds the E3 Ubiquitin Ligase COP1

Serine/threonine kinase 40 (STK40) was originally identified as a distant homolog of Tribbles-family proteins. Despite accumulating data attesting to the importance of STK40 in a variety of different physiologic processes, little is known about its biological activity or mechanism of action.In this work, we show that STK40 interacts with Constitutive Photomorphogenic Protein 1 (COP1), relying primarily on a C-terminal sequence analogous to the motif found in Tribbles proteins. In order to further elucidate structure-function relationships in STK40, we determined the crystal structure of the STK40 kinase homology domain at 2.5 Å resolution. The structure, together with ATP-binding assay results, show that STK40 is a pseudokinase, in which substitutions of conserved residues within the kinase domain prevent ATP binding. Although the structure of the kinase homology domain diverges from the analogous region of Trib1, the results reported here suggest functional parallels between STK40 and Tribbles-family proteins as COP1 adaptors.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

A fluorescence high throughput screening method for the detection of reactive electrophiles as potential skin sensitizers

Skin sensitization is an important toxicological end-point in the risk assessment of chemical allergens. Because of the complexity of the biological mechanisms associated with skin sensitization, integrated approaches combining different chemical, biological and in silico methods are recommended to replace conventional animal tests. Chemical methods are intended to characterize the potential of a sensitizer to induce earlier molecular initiating events. The presence of an electrophilic mechanistic domain is considered one of the essential chemical features to covalently bind to the biological target and induce further haptenation processes. Current in chemico assays rely on the quantification of unreacted model nucleophiles after incubation with the candidate sensitizer. In the current study, a new fluorescence-based method, ‘HTS-DCYA assay’, is proposed. The assay aims at the identification of reactive electrophiles based on their chemical reactivity toward a model fluorescent thiol. The reaction workflow enabled the development of a High Throughput Screening (HTS) method to directly quantify the reaction adducts. The reaction conditions have been optimized to minimize solubility issues, oxidative side reactions and increase the throughput of the assay while minimizing the reaction time, which are common issues with existing methods. Thirty-six chemicals previously classified with LLNA, DPRA or KeratinoSens™ were tested as a proof of concept. Preliminary results gave an estimated 82% accuracy, 78% sensitivity, 90% specificity, comparable to other in chemico methods such as Cys-DPRA. In addition to validated chemicals, six natural products were analyzed and a prediction of their sensitization potential is presented for the first time. - Highlights: • A novel fluorescence-based method to detect electrophilic sensitizers is proposed. • A model fluorescent thiol was used to directly quantify the reaction products. • A discussion of the reaction workflow and critical parameters is presented. • The method could provide a useful tool to complement existing chemical assays.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Resistive Switching of Spinel Li 4 Ti 5 O 12 Lithium-Ion Battery Material for Neuromorphic Computing

The rapid rise of AI has exposed significant limitations in conventional Von Neumann computing architecture, particularly in regard to speed and energy efficiency. To address these challenges, researchers are exploring a brain-inspired neuromorphic architecture that mimics biological neural networks, enabling massive parallel processing with reduced power consumption for complex AI computational demands. Recent interest has focused on utilizing battery electrodes and solid electrolyte materials for their resistive switching properties in developing a neuromorphic architecture. These properties are precisely tuned through local- and bulk-level chemical composition modifications via voltage bias stimuli. In this study, we demonstrate fabricating a three-terminal lithium-ion electrochemical transistor based on lithium titanium oxide (Li 4 Ti 5 O 12 ), a popular lithium-ion battery anode material. We deposited and characterized LTO thin films using RF sputtering, demonstrating a 6 orders of magnitude increase in electronic conductivity upon lithiation, with conductivity plateauing after 20% lithiation. Density functional theory calculations revealed transformation from the insulating to conducting state, supported by experimental characterization through X-Ray Photoelectron Spectroscopy (XPS) and Direct Current (DC) polarization analyses. The fabricated transistor consisted of LTO as the channel layer, gold as source/drain terminals, lithium phosphorus oxynitride (LiPON) as the lithium-ion conductor, and copper as the gate terminal. The device exhibited clear hysteresis in transfer characteristics due to lithium insertion/extraction processes. Long-term potentiation (LTP) and long-term depression (LTD) measurements showed an asymmetric ratio of 1.425 and maximum/minimum conductance ratio of 7.83. When implemented in a deep neural network (DNN) for MNIST handwritten digit recognition, the device achieved 92.03% accuracy over 20 training epochs. Detailed transport mechanism analysis revealed the crucial role of oxygen vacancies and interface effects in device operation. Our preliminary findings establish LTO-based lithium-ion electrochemical transistors as promising candidates for energy-efficient neuromorphic computing applications, offering potential solutions to traditional Von Neumann architecture limitations.

25 ENERGY STORAGE↗
DOE OSTI2020

Urban Scaling as Validation for Predictions of Imperviousness From Population

Abstract Strategies for creating quantitative projections for human systems, especially impervious surfaces, are necessary to consider the human drivers of climate and ecosystem change. There are models that generate predictions of how impervious surfaces may change in response to different potential futures, but few tools exist for validating those predictions. We seek to fill that gap. We demonstrate a statistically robust sublinear scaling relationship between population and urban imperviousness across a 15 year history. We show that Integrated Climate and Land‐Use Scenarios (ICLUS) urbanization projections are also consistent with theory. These results demonstrate a theory that can be used to validate other models' predictions of urban growth and land cover change, analogous to the ways in which allometric scaling laws in biology have been used to validate process‐based models of ecosystem composition under different climate scenarios.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Multi-scale organization in communicating active matter

The emergence of collective motion among interacting, self-propelled agents is a central paradigm in non-equilibrium physics. Examples of such active matter range from swimming bacteria and cytoskeletal motility assays to synthetic self-propelled colloids and swarming microrobots. Remarkably, the aggregation capabilities of many of these systems rely on a theme as fundamental as it is ubiquitous in nature: communication. Despite its eminent importance, the role of communication in the collective organization of active systems is not yet fully understood. Here we report on the multi-scale self-organization of interacting self-propelled agents that locally process information transmitted by chemical signals. We show that this communication capacity dramatically expands their ability to form complex structures, allowing them to self-organize through a series of collective dynamical states at multiple hierarchical levels. Our findings provide insights into the role of self-sustained signal processing for self-organization in biological systems and open routes to applications using chemically driven colloids or microrobots.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

ContScout: sensitive detection and removal of contamination from annotated genomes

Contamination of genomes is an increasingly recognized problem affecting several downstream applications, from comparative evolutionary genomics to metagenomics. Here we introduce ContScout, a precise tool for eliminating foreign sequences from annotated genomes. It achieves high specificity and sensitivity on synthetic benchmark data even when the contaminant is a closely related species, outperforms competing tools, and can distinguish horizontal gene transfer from contamination. A screen of 844 eukaryotic genomes for contamination identified bacteria as the most common source, followed by fungi and plants. Furthermore, we show that contaminants in ancestral genome reconstructions lead to erroneous early origins of genes and inflate gene loss rates, leading to a false notion of complex ancestral genomes. Taken together, we offer here a tool for sensitive removal of foreign proteins, identify and remove contaminants from diverse eukaryotic genomes and evaluate their impact on phylogenomic analyses.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Random heteropolymers as enzyme mimics

Despite successes in replicating the primary–secondary–tertiary structure hierarchy of protein, it remains elusive to synthetically materialize protein functions that are deeply rooted in their chemical, structural and dynamic heterogeneities. We propose that for polymers with backbone chemistries different from that of proteins, programming spatial and temporal projections of sidechains at the segmental level can be effective in replicating protein behaviours; and leveraging the rotational freedom of polymer can mitigate deficiencies in monomeric sequence specificity and achieve behaviour uniformity at the ensemble level. Here, guided by the active site analysis of about 1,300 metalloproteins, we design random heteropolymers (RHPs) as enzyme mimics based on one-pot synthesis. We introduce key monomers as the equivalents of the functional residues of protein and statistically modulate the chemical characteristics of key monomer-containing segments, such as segmental hydrophobicity. The resultant RHPs form pseudo-active sites that provide key monomers with protein-like microenvironments, co-localize substrates with catalytic or cofactor-binding sidechains and catalyse reactions such as oxidation and cyclization of citronellal with isopulegol/menthoglycol selectivity. This RHP design led to enzyme-like materials that can retain catalytic activity under non-biological conditions, are compatible with scalable processing and have expanded substrate scope, including environmentally long-lasting antibiotic tetracycline.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Coassembly and binning of a twenty-year metagenomic time-series from Lake Mendota

Abstract The North Temperate Lakes Long-Term Ecological Research (NTL-LTER) program has been extensively used to improve understanding of how aquatic ecosystems respond to environmental stressors, climate fluctuations, and human activities. Here, we report on the metagenomes of samples collected between 2000 and 2019 from Lake Mendota, a freshwater eutrophic lake within the NTL-LTER site. We utilized the distributed metagenome assembler MetaHipMer to coassemble over 10 terabases (Tbp) of data from 471 individual Illumina-sequenced metagenomes. A total of 95,523,664 contigs were assembled and binned to generate 1,894 non-redundant metagenome-assembled genomes (MAGs) with ≥50% completeness and ≤10% contamination. Phylogenomic analysis revealed that the MAGs were nearly exclusively bacterial, dominated by Pseudomonadota (Proteobacteria, N = 623) and Bacteroidota (N = 321). Nine eukaryotic MAGs were identified by eukCC with six assigned to the phylum Chlorophyta. Additionally, 6,350 high-quality viral sequences were identified by geNomad with the majority classified in the phylum Uroviricota. This expansive coassembled metagenomic dataset provides an unprecedented foundation to advance understanding of microbial communities in freshwater ecosystems and explore temporal ecosystem dynamics.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Standardized phylogenetic and molecular evolutionary analysis applied to species across the microbial tree of life

There is growing interest in reconstructing phylogenies from the copious amounts of genome sequencing projects that target related viral, bacterial or eukaryotic organisms. To facilitate the construction of standardized and robust phylogenies for disparate types of projects, we have developed a complete bioinformatic workflow, with a web-based component to perform phylogenetic and molecular evolutionary (PhaME) analysis from sequencing reads, draft assemblies or completed genomes of closely related organisms. Furthermore, the ability to incorporate raw data, including some metagenomic samples containing a target organism (e.g. from clinical samples with suspected infectious agents), shows promise for the rapid phylogenetic characterization of organisms within complex samples without the need for prior assembly.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Outlier analyses of the Protein Data Bank archive using a probability-density-ranking approach

Outlier analyses are central to scientific data assessments. Conventional outlier identification methods do not work effectively for Protein Data Bank (PDB) data, which are characterized by heavy skewness and the presence of bounds and/or long tails. We have developed a data-driven nonparametric method to identify outliers in PDB data based on kernel probability density estimation. Unlike conventional outlier analyses based on location and scale, Probability Density Ranking can be used for robust assessments of distance from other observations. Analyzing PDB data from the vantage points of probability and frequency enables proper outlier identification, which is important for quality control during deposition-validation-biocuration of new three-dimensional structure data. Ranking of Probability Density also permits use of Most Probable Range as a robust measure of data dispersion that is more compact than Interquartile Range. The Probability-Density-Ranking approach can be employed to analyze outliers and data-spread on any large data set with continuous distribution.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Proton transfer in acetaldehyde–water clusters mediated by a single water molecule

Proton transfer in aqueous media is a ubiquitous process, occurring in acid–base chemistry, biology, and in atmospheric photochemistry. Photoionization mass spectrometry coupled with theoretical calculations demonstrate that a relay-type proton transfer mechanism is operational for single-water-molecule-assisted proton transfer between two acetaldehyde molecules in the gas phase. Threshold photoionization of acetaldehyde–water clusters leads to proton transfer between the formyl groups (–CH=O) of one acetaldehyde molecule to another, and the subsequent formation of cationic moieties. Density functional theory computations reveal several plausible pathways of proton transfer in mixed cluster cations. Among these pathways, water-mediated proton transfer is energetically favored. Finally, mass spectra and photoionization efficiency curves confirm these theoretical findings and also demonstrate the increased stability of cluster cations where acetaldehyde molecules are symmetrically bonded to the hydronium ion.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗