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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 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

High-throughput screening of environmental polysaccharide-degrading bacteria using biomass containment and complex insoluble substrates

Abstract Carbohydrate degradation by microbes plays an important role in global nutrient cycling, human nutrition, and biotechnological applications. Studies that focus on the degradation of complex recalcitrant polysaccharides are challenging because of the insolubility of these substrates as found in their natural contexts. Specifically, current methods to examine carbohydrate-based biomass degradation using bacterial strains or purified enzymes are not compatible with high-throughput screening using complex insoluble materials. In this report, we developed a small 3D printed filter device that fits inside a microplate well that allows for the free movement of bacterial cells, media, and enzymes while containing insoluble biomass. These devices do not interfere with standard microplate readers and can be used for both short- (24–48 h) and long-duration (> 100 h) experiments using complex insoluble substrates. These devices were used to quantitatively screen in a high-throughput manner environmental isolates for their ability to grow using lignocellulose or rice grains as a sole nutrient source. Additionally, we determined that the microplate-based containment devices are compatible with existing enzymatic assays to measure activity against insoluble biomass. Overall, these microplate containment devices provide a platform to study the degradation of complex insoluble materials in a high-throughput manner and have the potential to help uncover ecologically important aspects of bacterial metabolism as well as to accelerate biotechnological innovation.

3D printing↗
DOE OSTI2025

Sample screening of uranium ore concentrates using portable spectrophotometers: investigating the correlation between visible colors and chemical signatures

A research collaboration between the Japan Atomic Energy Agency and the Department of Energy’s National Nuclear Security Administration examined nuclear forensic signatures and analytical methods for tracing the origins of uranium ore concentrates (UOCs). Here, this study focuses on utilizing portable spectrophotometers capable of reflectance measurements in the visible light spectrum as a potential rapid screening tool for nuclear forensics analysis. Unlike laboratory-based near-infrared spectroscopy or digital image analysis, this research investigated the potential to correlate visible color measurements with key nuclear forensics signatures using seven types of UOC samples with known origins and three UOC certified reference materials. Results demonstrated that distinct color groups, quantified using CIELAB values, correlated with major uranium compounds. Furthermore, the findings indicated that trace elements can influence the UOC colors, providing additional insights into material characteristics. Although this approach requires further validation across a broader range of UOC species, this study demonstrated that simple colorimetric analysis using visible spectrophotometry, which does not require complex sample preparation or data processing, can serve as a practical and novel rapid tool for preliminary screening and attribution in nuclear forensics investigations.

and nuclear chemistry↗
DOE OSTI2011

A whole mitochondrial genome screening in a MELAS patient: A novel mitochondrial tRNA{sup Val} mutation

Highlights: {yields} We report a young Tunisian patient with clinical features of MELAS syndrome. {yields} Reported mitochondrial mutations were absent after a mutational screening of the whole mtDNA. {yields} We described a novel m.1640A>G mutation in the tRNA{sup Val} gene which was absent in 150 controls. {yields} Mitochondrial deletions and POLG1 gene mutations were absent. {yields} The m.1640A>G mutation could be associated to MELAS syndrome. -- Abstract: Mitochondrial encephalopathy, lactic acidosis and strokelike episodes (MELAS) syndrome is a mitochondrial disorder characterized by a wide variety of clinical presentations and a multisystemic organ involvement. In this study, we report a Tunisian girl with clinical features of MELAS syndrome who was negative for the common m.3243A>G mutation, but also for the reported mitochondrial DNA (mtDNA) mutations and deletions. Screening of the entire mtDNA genome showed several known mitochondrial variants besides to a novel transition m.1640A>G affecting a wobble adenine in the anticodon stem region of the tRNA{sup Val}. This nucleotide was conserved and it was absent in 150 controls suggesting its pathogenicity. In addition, no mutations were found in the nuclear polymerase gamma-1 gene (POLG1). These results suggest further investigation nuclear genes encoding proteins responsible for stability and structural components of the mtDNA or to the oxidative phosphorylation machinery to explain the phenotypic variability in the studied family.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Novel stable HBV producing cell line systems for expression and screening antiviral inhibitor of hepatitis B virus in human hepatoma cell line

Highlights: • Novel HBV clones with high replication activities were identified from the sera of patients with chronic HBV. • Novel stable cell lines showed HBV replication activities and were susceptible to several antiviral inhibitors. • Novel stable cell lines are valuable tools for analyzing viral phenotypes in vitro and for screening antiviral agents. Chronic hepatitis B virus (HBV) infection is currently a major public health burden. Therefore, there is an urgent need for the development of novel antiviral inhibitors. The stable HBV-producing cell lines of genotype D are widely used to investigate the HBV life cycle and to evaluate antiviral agents. However, stable HBV-producing cell lines of different genotypes do not exist. To construct more convenient and efficient novel cell systems, stable cell lines of genotypes A, B, and C were established using a full-length HBV genome sequence isolated from chronic HBV patients in human hepatoma HepG2 cells. Novel HBV clones were identified and stable HBV-producing cell lines derived from these clones were constructed. HBV replication activities demonstrated time-dependent expression, and the novel cell lines were susceptible to several antiviral inhibitors with no cytotoxicity. Furthermore, infectious viruses were produced from these cell lines. In conclusion, we have established novel stable HBV-producing cell line systems of genotypes A, B, and C. These systems can provide valuable tools for screening antiviral agents and analyzing viral phenotypes in vitro.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Reprint of: A chemical screen identifies trifluoperazine as an inhibitor of glioblastoma growth

Highlights: • Screening of GBM cells uncovers 45 active dopaminergic ligands and 8 were validated. • Ligand selectivity suggests dopamine-mediated cell viability regulation in GBM. • The DRD2 antagonist trifluoperazine inhibits cell viability and growth of GBM cells. • DR expression profile of GBM cells alter the susceptibility to trifluoperazine. Glioblastoma (GBM) is regarded as the most common malignant brain tumor but treatment options are limited. Thus, there is an unmet clinical need for compounds and corresponding targets that could inhibit GBM growth. We screened a library of 80 dopaminergic ligands with the aim of identifying compounds capable of inhibiting GBM cell line proliferation and survival. Out of 45 active compounds, 8 were further validated. We found that the dopamine receptor D2 antagonist trifluoperazine 2HCl inhibits growth and proliferation of GBM cells in a dose dependent manner. Trifluoperazine’s inhibition of GBM cells is cell line dependent and correlates with variations in dopamine receptor expression profile. We conclude that components of the dopamine receptor signaling pathways are potential targets for pharmacological interventions of GBM growth.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

A natural compound, aristoyagonine, is identified as a potent bromodomain inhibitor by mid-throughput screening

Bromodomain-containing protein 4 (Brd4) is known to play a key role in tumorigenesis. It binds acetylated histones to regulate the expression of numerous genes. Because of the importance of brd4 in tumorigenesis, much research has been undertaken to develop brd4 inhibitors with therapeutic potential. As a result, various scaffolds for bromodomain inhibitors have been identified. To discover new scaffolds, we performed mid-throughput screening using two different enzyme assays, alpha-screen and ELISA. We found a novel bromodomain inhibitor with a unique scaffold, aristoyagonine. This natural compound showed inhibitory activity in vitro and tumor growth inhibition in a Ty82-xenograft mouse model. In addition, we tested Brd4 inhibitors in gastric cancer cell lines, and found that aristoyagonine exerted cytotoxicity not only in I-BET-762-sensitive cancer cells, but also in I-BET-762-resistant cancer cells. This is the first paper to describe a natural compound as a Brd4 bromodomain inhibitor.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Computational catalyst screening: Scaling, bond-order and catalysis

Here, the design of new and better heterogeneous catalysts needed to accommodate the growing demand for energy from renewable sources is an important challenge for coming generations. Most surface catalyzed processes involve a large number of complex reaction networks and the energetics ultimately defines the turn-over-frequency and the selectivity of the process. In order not to get lost in the large quantities of data, simplification schemes that still contain the key elements of the reaction are required. Adsorption and transition state scaling relations constitutes such a scheme that not only maps the reaction relevant information in terms of few parameters but also provides an efficient way of screening for new materials in a continuous multi-dimensional energy space. As with all relations they impose certain restrictions on what can be achieved and in this paper, I show why these limitations exist and how we can change the behavior through an energy-resolved approach that still maintains the screening capabilities needed in computational catalysis.

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

Discovery of multi-functional polyimides through high-throughput screening using explainable machine learning

Polyimides have been widely used in modern industries because of their excellent mechanical and thermal properties, e.g., high-temperature fuel cells, displays, and aerospace composites. However, it usually takes decades of experimental efforts to develop a successful product. Aiming to expedite the discovery of high-performance polyimides, we utilize computational methods of machine learning (ML) and molecular dynamics (MD) simulations. Our study provides compelling evidence for the effectiveness of a data-driven approach in discovering novel polyimides. We first build a comprehensive library of more than 8 million hypothetical polyimides based on the polycondensation of existing dianhydride and diamine/diisocyanate molecules. Then we establish multiple ML models for the thermal and mechanical properties of polyimides based on their experimentally reported values, including glass transition temperature, Young’s modulus, and tensile yield strength. The obtained ML models demonstrate excellent predictive performance in identifying the key chemical substructures influencing the thermal and mechanical properties of polyimides. The use of explainable machine learning describes the effect of chemical substructures on individual properties, from which human experts can understand the cause of the ML model decision. Applying the well-trained ML models, we obtain property predictions of the 8 million hypothetical polyimides. Then, we screen the whole hypothetical dataset and identify three (3) best-performing novel polyimides that have better-combined properties than existing ones through Pareto frontier analysis. For an easy query of the discovered high-performing polyimides, we also create an online platform https://polyimide-explorer.herokuapp.com/ that embeds the developed ML model with interactive visualization. Furthermore, we validate the ML predictions through all-atom MD simulations and examine their synthesizability. The MD simulations are in good agreement with the ML predictions and the three novel polyimides are predicted to be easy to synthesize via Schuffenhauer’s synthetic accessibility score. Following the proposed ML guidance, we successfully synthesized a novel polyimide and the experimentally obtained high glass transition/thermal decomposition temperature demonstrated its excellent thermal stability. Here our study demonstrates an efficient way to expedite the discovery of novel polymers using ML prediction and MD validation. The high-throughput screening of a large computational dataset can serve as a general approach for new material discovery in other polymeric material exploration problems, such as organic photovoltaics, polymer membranes, and dielectrics.

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

The use of gas chromatography – high resolution mass spectrometry for suspect screening and non-targeted analysis of per- and polyfluoroalkyl substances

This study is a workflow development for the analysis, identification, and categorization of per- and polyfluoroalkyl substances (PFAS) using gas chromatography-high resolution mass spectrometry (GC-HRMS) with non-targeted analysis (NTA) and suspect screening techniques. The behavior of various PFAS in a GC-HRMS was studied with regards to retention indices, ionization susceptibility, fragmentation patterns, etc. A custom PFAS database was constructed from 141 diverse PFAS. The database contains mass spectra from electron ionization (EI) mode, as well as MS and MS/MS spectra from positive and negative chemical ionization (PCI and NCI, respectively) modes. Common fragments of PFAS were identified across a diverse set of 141 PFAS analyzed. A workflow for suspect screening of PFAS and partially fluorinated products of incomplete combustion/destruction (PICs/PIDs) was developed which utilized both the custom PFAS database and external databases. PFAS and other fluorinated compounds were identified in both a challenge sample (designed to test the identification workflow) and incineration samples suspected to contain PFAS and fluorinated PICs/PIDs. The challenge sample resulted in a 100% true positive rate (TPR) for PFAS which were present in the custom PFAS database. In conclusion, several fluorinated species were tentatively identified in the incineration samples using the developed workflow.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Biomarkers of Tuberculosis Severity and Treatment Effect: A Directed Screen of 70 Host Markers in a Randomized Clinical Trial

More efficacious treatment regimens are needed for tuberculosis, however, drug development is impeded by a lack of reliable biomarkers of disease severity and of treatment effect. In this study, we conducted a directed screen of host biomarkers in participants enrolled in a tuberculosis clinical trial to address this need. Serum samples from 319 protocol-correct, culture-confirmed pulmonary tuberculosis patients treated under direct observation as part of an international, phase 2 trial were screened for 70 markers of infection, inflammation, and metabolism. Biomarker assays were specifically developed for this study and quantified using a novel, multiplexed electrochemiluminescence assay. We evaluated the association of biomarkers with baseline characteristics, as well as with detailed microbiologic data, using Bonferroni-adjusted, linear regression models. Across numerous analyses, seven proteins, SAA1, PCT, IL-1, IL-6, CRP, PTX-3 and MMP-8, showed recurring strong associations with markers of baseline disease severity, smear grade and cavitation; were strongly modulated by tuberculosis treatment; and had responses that were greater for patients who culture-converted at 8 weeks. With treatment, all proteins decreased, except for osteocalcin, MCP-1 and MCP-4, which significantly increased. Several previously reported putative tuberculosis-associated biomarkers (HOMX1, neopterin, and cathelicidin) were not significantly associated with treatment response. In conclusion, across a geographically diverse and large population of tuberculosis patients enrolled in a clinical trial, several previously reported putative biomarkers were not significantly associated with treatment response, however, seven proteins had recurring strong associations with baseline radiographic and microbiologic measures of disease severity, as well as with early treatment response, deserving additional study.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2011

Heat Flux Calculation and Problem of Flaking of Boron Carbide Coatings on the Faraday Screen of the ICRH Antennas During Tore Supra High Power, Long Pulse Operation

Reliable and repetitive high power and long pulse tokamak operation is strongly dependant of the ability to secure the Plasma Facing Components (PFCs). In Tore Supra, a network of 7 infrared (IR) video cameras is routinely used to prevent PFCs overheating and damage in selected regions. Real time feedback control and offline analysis are essential for basic protection and understanding of abnormal thermal events. One important limitation detected by the IR real time feed-back loop during high power RF operation (injected power of 9.5 MW over 26 s and 12 MW over 10 s have been achieved respectively in 2006 and 2008) is due to the interaction between fast ions which increase the power flux density and flaking of the boron carbide coatings on the Faraday screen box of the ICRH antennas. An IR-based experimental procedure is proposed in order to detect new flakes during plasma operation. The thermal response of the B4C coating is studied with and without flaking during plasma operation. The experimental heat flux deposited by fast ion losses on the Faraday screen is calculated for high (3.8 T) and low magnetic field (2 T) during high RF power operation (with fundamental hydrogen minority and second harmonic ICRH heating schemes respectively). The paper addresses both thermal science issues applied to machine protection and limitation due to fast ions issues during high RF power, long pulse operation. Safety margin to critical heat flux and number of fatigue cycles under heat load are presented in the paper.

Corre, Y.↗
DOE OSTI2012

Dynamic Contrast-Enhanced MRI of Cervical Cancers: Temporal Percentile Screening of Contrast Enhancement Identifies Parameters for Prediction of Chemoradioresistance

Purpose: To systematically screen the tumor contrast enhancement of locally advanced cervical cancers to assess the prognostic value of two descriptive parameters derived from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). Methods and Materials: This study included a prospectively collected cohort of 81 patients who underwent DCE-MRI with gadopentetate dimeglumine before chemoradiotherapy. The following descriptive DCE-MRI parameters were extracted voxel by voxel and presented as histograms for each time point in the dynamic series: normalized relative signal increase (nRSI) and normalized area under the curve (nAUC). The first to 100th percentiles of the histograms were included in a log-rank survival test, resulting in p value and relative risk maps of all percentile-time intervals for each DCE-MRI parameter. The maps were used to evaluate the robustness of the individual percentile-time pairs and to construct prognostic parameters. Clinical endpoints were locoregional control and progression-free survival. The study was approved by the institutional ethics committee. Results: The p value maps of nRSI and nAUC showed a large continuous region of percentile-time pairs that were significantly associated with locoregional control (p < 0.05). These parameters had prognostic impact independent of tumor stage, volume, and lymph node status on multivariate analysis. Only a small percentile-time interval of nRSI was associated with progression-free survival. Conclusions: The percentile-time screening identified DCE-MRI parameters that predict long-term locoregional control after chemoradiotherapy of cervical cancer.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2019

High-Throughput Screening of Solid-State Li-Ion Conductors Using Lattice-Dynamics Descriptors

Low lithium-ion migration barriers have recently been associated with low average vibrational frequencies or phonon band centers, further helping identify descriptors for superionic conduction. To further explore this correlation, here we present the computational screening of ~14,000 Li-containing compounds in the Materials Project database using a descriptor based on lattice dynamics reported recently to identify new promising Li-ion conductors. An efficient computational approach was optimized to compute the average vibrational frequency or phonon band center of ~1,200 compounds obtained after pre-screening based on structural stability, band gap, and their composition. Combining a low computed Li phonon band center with large computed electrochemical stability window and structural stability, 18 compounds were predicted to be promising Li-ion conductors, one of which, Li 3 ErCl 6 , has been synthesized and exhibits a reasonably high room-temperature conductivity of 0.05–0.3 mS/cm, which shows the promise of Li-ion conductor discovery based on lattice dynamics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

A Quick Screening Approach for Design of Multi-Principle Element Alloy with Solid Solution Phase

Multi-principle element alloys (MPEAs) provide an innovative way to design materials with potential applications in extreme conditions, such as high-dose irradiation in nuclear reactors, high temperatures in aeronautic and aerospace engineering, etc. However, the composition design and optimization of MPEAs are challenging due to the vast options and complexity which make traditional theory and methods insufficient or even invalid. To effectively design MPEAs, a two-parameter approach is developed based on newly proposed enthalpy and entropy-enthalpy competition parameters. This approach can not only be used to classify conventional steels, high-entropy steels (HESs), high-entropy alloys (HEAs) and amorphous alloys, but also to predict the optimal composition of MPEAs with stable solid solution (SS) phases. The optimal compositions of three sets of Fe-Mn-Cr-Co-Ni alloys are quickly screened from millions of options to form HESs or HEAs with stable SS phases. This quick screening approach can also be applied to design other alloys and facilitate the research and development of MPEAs possessing the targeted properties and economic acceptability.

Zheng, Mingjie↗
DOE OSTI2025

CoRE MOF DB: A curated experimental metal-organic framework database with machine-learned properties for integrated material-process screening

Here, we present an updated version of the Computation-Ready, Experimental (CoRE) Metal-Organic Framework (MOF) database, which includes a curated set of computation-ready MOF crystal structures designed for high-throughput computational materials discovery. Data collection and curation procedures were improved from the previous version to enable more frequent updates in the future. Machine-learning-predicted properties, such as stability metrics and heat capacities, are included in the dataset to streamline screening activities. An updated version of MOFid was developed to provide detailed information on metal nodes, organic linkers, and topologies of an MOF structure. DDEC6 partial atomic charges of MOFs were assigned based on a machine-learning model. Gibbs ensemble Monte Carlo simulations were used to classify the hydrophobicity of MOFs. The finalized dataset was subsequently used to perform integrated material-process screening for various carbon-capture conditions using high-fidelity temperature-swing adsorption (TSA) simulations. Our workflow identified multiple MOF candidates that are predicted to outperform CALF-20 for these applications.

CoRE MOF database↗
DOE OSTI2023

Extraction of valuable chemicals from food waste via computational solvent screening and experiments

About 1.3 billion tons of global food production end up in landfills and composting, leading to significant anthropogenic greenhouse gas (GHG) emissions. Extracting antioxidant and antimicrobial chemicals (flavonoids, phenolic acids, etc.) from food waste is an economically lucrative valorization strategy but is hindered by efficient solvent selection. Here we perform in silico high throughput screening to identify high solubility solvents for key phenolics and reveal more than 100+ higher-performing solvents than the traditional ethanol and methanol. Solubilities of nine shortlisted solvents are measured and found in reasonable agreement with model predictions. Analysis of the Conductor like Screening Model for Real Solvents (COSMO-RS) σ-profiles and Hansen Solubility Parameters reveals that polarity and hydrogen bonding make dimethylformamide (DMF) an excellent single solvent. We showcase the replacement of high-solubility toxic solvents with green mixtures and demonstrate the approach to potato peel waste. As a result, our work provides a blueprint for solvent selection and generates new insights into extraction from food waste.

09 BIOMASS FUELS↗
DOE OSTI2017

A topological screening heuristic for low-energy, high-index surfaces

Robust ab initio investigations of nanoparticle surface properties require a method to identify candidate low-energy surface facets a priori . By assuming that low-energy surfaces are planes with high atomic density, we devise an efficient algorithm to screen for low-energy surface orientations, even if they have high ( hkl ) miller indices. We successfully predict the observed low-energy, high-index {$10\overline{12} $} and {$10\bar{1}4 $} surfaces of hematite α-Fe 2 O 3 , the {311} surfaces of cuprite Cu 2 O, and the {112} surfaces of anatase TiO 2 . We further tabulate candidate low-energy surface orientations for nine of the most common binary oxide structures. Screened surfaces are found to be generally applicable across isostructural compounds with varying chemistries, although relative surface energies between facets may vary based on the preferred coordination of the surface atoms.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Longitudinal analysis of risk factors for dementia based on Mild Cognitive Impairment Screen results and questionnaire responses from healthy Japanese individuals registered in an online database

Abstract Introduction Despite an urgent need for developing remedial measures against dementia, no disease‐modifying drugs have been developed. Efficient protocols for participant recruitment need to be established for conducting clinical trials. To meet this need, a large‐scale online registry system, the Integrated Registry of Orange Plan (IROOP ® ), was created for healthy individuals. Although the risk factors for dementia have been discussed in our previous studies for a short interval of 6 months, some factors remain controversial. The present study aimed to explore factors affecting longitudinal changes in cognitive function for a longer interval of 18 months using the IROOP ® data. Methods This study assessed the longitudinal changes in the collated data for predicting the risk of dementia and included 473 individuals (175 men and 298 women; mean age 59.6 ± 10.1 years) registered in the IROOP ® between July 5, 2016 and January 15, 2018 who completed the initial questionnaire and brief assessment of cognitive function (Mild Cognitive Impairment Screen) at baseline and the regular questionnaire and the Mild Cognitive Impairment Screen at least once after baseline. Statistical analyses were performed using IBM SPSS, version 23.0, for Windows for demographic data and the MIXED procedure in SAS, version 9.4, for the linear mixed‐effect model. In each analysis, the statistical significance level was set at P < .05. Results Mood, sleep, quality of life, and medical histories including cognition were found to influence longitudinal changes in cognitive function. Discussion Given the multifactorial etiology of dementia, preventive measures targeting multiple domains are required for maintaining cognitive function, instead of focusing on one lifestyle factor.

Ogawa, Masayo↗