Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “active data”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

CASTELO: clustered atom subtypes aided lead optimization—a combined machine learning and molecular modeling method

Background: Drug discovery is a multi-stage process that comprises two costly major steps: pre-clinical research and clinical trials. Among its stages, lead optimization easily consumes more than half of the pre-clinical budget. We propose a combined machine learning and molecular modeling approach that partially automates lead optimization workflow in silico, providing suggestions for modification hot spots. Results: The initial data collection is achieved with physics-based molecular dynamics simulation. Contact matrices are calculated as the preliminary features extracted from the simulations. To take advantage of the temporal information from the simulations, we enhanced contact matrices data with temporal dynamism representation, which are then modeled with unsupervised convolutional variational autoencoder (CVAE). Finally, conventional and CVAE-based clustering methods are compared with metrics to rank the submolecular structures and propose potential candidates for lead optimization. Conclusion: With no need for extensive structure-activity data, our method provides new hints for drug modification hotspots which can be used to improve drug potency and reduce the lead optimization time. It can potentially become a valuable tool for medicinal chemists.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

CSEWG 2016 Minutes

The Cross Section Evaluation Working Group met November 14 - 16, 2016. Brief status reports are given on nuclear data activities at various DOE laboratories and universities.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Residential Demand Flexibility: Modeling Occupant Behavior using Sociodemographic Predictors

Demand flexibility (DF) has the potential to increase the saturation of renewables in the grid and reduce operating costs for both utilities and customers. However, less than 8% of U.S. residential electric customers are enrolled in DF programs. A major research gap on this topic is an uneven understanding of behavioral drivers of electricity use and DF program participation at the household level. In this study, we employ machine learning models to predict residential occupant behavior in activities relevant to DF. We model occupants' extensive decisions (i.e., choice of action) and intensive behaviors (i.e., amount of time spent) during peak and off-peak time periods using the publicly available American Time Use Survey, which includes activities data for approximately 200,000 respondents. In our machine learning models, predictions for both extensive and intensive behavior fell within a +/-20% error margin at the aggregate level. We identify 13 key sociodemographic predictors of DF-related intensive behavior using LASSO inference and beta coefficient ranking. However, these top predictors differ by activity, suggesting potential scope for differential user targeting for DF events and technologies during program design. This work also contributes to understanding when and who might adopt these DF technologies based on their daily routine activities.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Developing and Evaluating a Smart Curtailment Strategy Integrated with a Wind Turbine Manufacturer Platform

The Renewable Energy Wildlife Institute lead a team of scientists, wind developers, and turbine manufacturers in a study to develop and test a “smart curtailment” system intended to help reduce bat collisions with wind turbines. The Vestas Bat Protection System (VBPS) is a newly developed software module within the Supervisory Control and Data Acquisition (SCADA) system of Vestas turbines. The VBPS combines data from commercially available environmental sensors and the turbine’s built-in sensors with the Vestas SCADA system. VBPS is designed to receive environmental data from sensors on the turbine such as temperature, wind speed, wind direction, time of day, and time of year, relays that information to the SCADA system to determine whether to execute turbine curtailments at any given time. The goals of this study were to 1) develop a bat fatality risk model based on bat activity data and environmental data collected in year 1, and to 2) evaluate the VBPS, using the bat fatality risk model to implement curtailment, in comparison to “blanket curtailment” (turbines curtailed when wind speed is below 5.0 meters per second (m/s)) and “control” (normally operating, feathered below 3.0 m/s) turbines in year 2. The field study took place at a wind energy facility in Iowa during the fall bat migration seasons (July – October) in 2021 and 2022. For VBPS to succeed as a viable strategy for the minimization of bat fatalities, it should meet or exceed the performance of blanket curtailment. Specifically, the VBPS should meet the following performance targets to demonstrate whether it an effective, practical risk reduction measure: (1) Turbines operating VBPS should have equal or fewer bat fatalities compared to turbines operating with blanket curtailment, and significantly fewer bat fatalities compared to control turbines; and (2) Turbines operating VBPS should have greater power production compared to turbines operating with blanket curtailment. The study was completed in accordance with the Statement of Project Objectives and within the terms of the Budget Justification. This Final Report describes the progress, challenges, and outcomes of the study.

17 WIND ENERGY↗
DOE OSTI2015

Underwater characterization of control rods for waste disposal using SMOPY

Storage of spent fuel assemblies in cooling ponds requires careful control of the geometry and proximity of adjacent assemblies. Measurement of the fuel burnup makes it possible to optimise the storage arrangement of assemblies taking into account the effect of the burnup on the criticality safety margins ('burnup credit'). Canberra has developed a measurement system for underwater measurement of spent fuel assemblies. This system, known as 'SMOPY', performs burnup measurements based on gamma spectroscopy (collimated CZT detector) and neutron counting (fission chamber). The SMOPY system offers a robust and waterproof detection system as well as the needed capability of performing radiometric measurements in the harsh high dose - rate environments of the cooling ponds. The gamma spectroscopy functionality allows powerful characterization measurements to be performed, in addition to burnup measurement. Canberra has recently performed waste characterisation measurements at a Nuclear Power Plant. Waste activity assessment is important to control costs and risks of shipment and storage, to ensure that the activity level remains in the range allowed by the facility, and to declare activity data to authorities. This paper describes the methodology used for the SMOPY measurements and some preliminary results of a radiological characterisation of AIC control rods. After describing the features and normal operation of the SMOPY system, we describe the approach used for establishing an optimum control rod geometric scanning approach (optimum count time and speed) and the method of the gamma spectrometry measurements as well as neutron check measurements used to verify the absence of neutron sources in the waste. We discuss the results obtained including {sup 60}Co, {sup 110m}Ag and {sup 108m}Ag activity profiles (along the length of the control rods) and neutron results including Total Measurement Uncertainty evaluations. Full self-consistency checks were performed and these demonstrate the validity of the techniques. The results are described and analysed in the context of the measurement performance of the equipment. Different casks were fully characterized using a 60 mm{sup 3} CZT detector, to determine the total activities and spatial profiles. A total activity range measurement of 1x10{sup 8} - 1x10{sup 13} Bq/cm was found to be achievable. Finally, comments are made, based on our measurements, on the ability of this equipment for performing in-situ characterisation of wastes in the harsh environments typical of fuel assembly and waste storage ponds and silos. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2018

Enhancement of STAYSL_PNNL with IRDFF/V1.05 to 60 MeV

The STAYSL PNNL program performs a least-squares adjustment of the neutron spectrum based on the IRDFF cross section library and user-defined activation data and a starting neutron spectrum. All known covariances are included. Required corrections are included for the irradiation history, gamma absorption, neutron burn-up, and neutron self-shielding using separate utility programs prior to the execution of STAYSL PNNL. Several new neutron cross section libraries based on IRDFF V1.05 to 60 MeV are provided with the program including energy group structures of 69 (WIMS), 129 (14 MeV), 140 (prior 100 groups extended to 60 MeV), 175 (Vitamin J), 640 (old SANDII to 20 MeV), and 725 (old Sand II extended to 60 MeV) energy groups. Twelve new reactions were included in IRDFF V1.05. At higher neutron energies, calculations demonstrate the need for activation cross sections from natural targets such as Ti(n,x)46Sc rather than only isotopic targets such as 46Ti(n,p)46Sc and 47Ti(n,x)46Sc. The effects of such reactions increase dramatically with increasing neutron energies and cannot be neglected. Some critical reactions such as 56Fe(n,x)54Mn are not currently included in IRDFF and prevent the use of the 54Fe(n,p)54Mn reaction at higher neutron energies. It is recommended that natural element cross sections be included in future releases of IRDFF for a list of reactions that suffer from reactions on multiple isotopes that lead to the same activation product. Spectral adjustments are illustrated in Be(d,n) thick target neutron fields at deuteron energies of 30 and 40 MeV.

reactor dosimetry, neutron spectral adjustment↗
DOE OSTI2016

Association Between Anticholinergic Medication Use and Cognition, Brain Metabolism, and Brain Atrophy in Cognitively Normal Older Adults

Importance of this Paper: The use of anticholinergic (AC) medication is linked to cognitive impairment and an increased risk of dementia. To our knowledge, this is the first study to investigate the association between AC medication use and neuroimaging biomarkers of brain metabolism and atrophy as a proxy for understanding the underlying biology of the clinical effects of AC medications. Objective: To assess the association between AC medication use and cognition, glucose metabolism, and brain atrophy in cognitively normal older adults from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) and the Indiana Memory and Aging Study (IMAS). Design, Setting, and Participants: The ADNI and IMAS are longitudinal studies with cognitive, neuroimaging, and other data collected at regular intervals in clinical and academic research settings. For the participants in the ADNI, visits are repeated 3, 6, and 12 months after the baseline visit and then annually. For the participants in the IMAS, visits are repeated every 18 months after the baseline visit (402 cognitively normal older adults in the ADNI and 49 cognitively normal older adults in the IMAS were included in the present analysis). Participants were either taking (hereafter referred to as the AC + participants [52 from the ADNI and 8 from the IMAS]) or not taking (hereafter referred to as the AC - participants [350 from the ADNI and 41 from the IMAS]) at least 1 medication with medium or high AC activity. Data analysis for this study was performed in November 2015. Main Outcomes and Measures: Cognitive scores, mean fludeoxyglucose F 18 standardized uptake value ratio (participants from the ADNI only), and brain atrophy measures from structural magnetic resonance imaging were compared between AC + participants and AC - participants after adjusting for potential confounders. The total AC burden score was calculated and was related to target measures. The association of AC use and longitudinal clinical decline (mean [SD] follow-up period, 32.1 [24.7] months [range, 6-108 months]) was examined using Cox regression. Results: The 52 AC + participants (mean [SD] age, 73.3 [6.6] years) from the ADNI showed lower mean scores on Weschler Memory Scale–Revised Logical Memory Immediate Recall (raw mean scores: 13.27 for AC + participants and 14.16 for AC - participants; P = .04) and the Trail Making Test Part B (raw mean scores: 97.85 seconds for AC + participants and 82.61 seconds for AC - participants; P = .04) and a lower executive function composite score (raw mean scores: 0.58 for AC + participants and 0.78 for AC - participants; P = .04) than the 350 AC - participants (mean [SD] age, 73.3 [5.8] years) from the ADNI. Reduced total cortical volume and temporal lobe cortical thickness and greater lateral ventricle and inferior lateral ventricle volumes were seen in the AC + participants relative to the AC - participants. Conclusions and Relevance of this Paper: The use of AC medication was associated with increased brain atrophy and dysfunction and clinical decline. Thus and finally, use of AC medication among older adults should likely be discouraged if alternative therapies are available.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Computational approaches to detect allosteric pathways in transmembrane molecular machines

Many of the functions of transmembrane proteins involved in signal processing and transduction across the cell membrane are determined by allosteric couplings that propagate the functional effects well beyond the original site of activation. Data gathered from breakthroughs in biochemistry, crystallography, and single molecule fluorescence have established a rich basis of information for the study of molecular mechanisms in the allosteric couplings of such transmembrane proteins. The mechanistic details of these couplings, many of which have therapeutic implications, however, have only become accessible in synergy with molecular modeling and simulations. Here, we review some recent computational approaches that analyze allosteric coupling networks (ACNs) in transmembrane proteins, and in particular the recently developed Protein Interaction Analyzer (PIA) designed to study ACNs in the structural ensembles sampled by molecular dynamics simulations. The power of these computational approaches in interrogating the functional mechanisms of transmembrane proteins is illustrated with selected examples of recent experimental and computational studies pursued synergistically in the investigation of secondary active transporters and GPCRs. This article is part of a Special Issue entitled: Membrane Proteins edited by J.C. Gumbart and Sergei Noskov.

Biochemistry & Molecular Biology↗
DOE OSTI2020

A global anthropogenic emission inventory of atmospheric pollutants from sector- and fuel-specific sources (1970–2017): an application of the Community Emissions Data System (CEDS)

Global anthropogenic emission inventories remain vital for understanding the sources of atmospheric pollution and the associated impacts on the environment, human health, and society. Rapid changes in today's society require that these inventories provide contemporary estimates of multiple atmospheric pollutants with both source sector and fuel type information to understand and effectively mitigate future impacts. To fill this need, we have updated the open-source Community Emissions Data System (CEDS) (Hoesly et al., 2019) to develop a new global emission inventory, CEDSGBD-MAPS. This inventory includes emissions of seven key atmospheric pollutants (NOx; CO; SO2; NH3; non-methane volatile organic compounds, NMVOCs; black carbon, BC; organic carbon, OC) over the time period from 1970–2017 and reports annual country-total emissions as a function of 11 anthropogenic sectors (agriculture; energy generation; industrial processes; on-road and non-road transportation; separate residential, commercial, and other sectors (RCO); waste; solvent use; and international shipping) and four fuel categories (total coal, solid biofuel, the sum of liquid-fuel and natural-gas combustion, and remaining process-level emissions). The CEDSGBD-MAPS inventory additionally includes monthly global gridded (0.5°?×?0.5°) emission fluxes for each compound, sector, and fuel type to facilitate their use in earth system models. CEDSGBD-MAPS utilizes updated activity data, updates to the core CEDS default scaling procedure, and modifications to the final procedures for emissions gridding and aggregation. Relative to the previous CEDS inventory (Hoesly et al., 2018), these updates extend the emission estimates from 2014 to 2017 and improve the overall agreement between CEDS and two widely used global bottom-up emission inventories. The CEDSGBD-MAPS inventory provides the most contemporary global emission estimates to date for these key atmospheric pollutants and is the first to provide global estimates for these species as a function of multiple fuel types and source sectors. Dominant sources of global NOx and SO2 emissions in 2017 include the combustion of oil, gas, and coal in the energy and industry sectors as well as on-road transportation and international shipping for NOx. Dominant sources of global CO emissions in 2017 include on-road transportation and residential biofuel combustion. Dominant global sources of carbonaceous aerosol in 2017 include residential biofuel combustion, on-road transportation (BC only), and emissions from the waste sector. Global emissions of NOx, SO2, CO, BC, and OC all peak in 2012 or earlier, with more recent emission reductions driven by large changes in emissions from China, North America, and Europe. In contrast, global emissions of NH3 and NMVOCs continuously increase between 1970 and 2017, with agriculture as a major source of global NH3 emissions and solvent use, energy, residential, and the on-road transport sectors as major sources of global NMVOCs. Due to similar development methods and underlying datasets, the CEDSGBD-MAPS emissions are expected to have consistent sources of uncertainty as other bottom-up inventories. The CEDSGBD-MAPS source code is publicly available online through GitHub: https://github.com/emcduffie/CEDS/tree/CEDS_GBD-MAPS (last access: 1 December 2020). The CEDSGBD-MAPS emission inventory dataset (both annual country-total and monthly global gridded files) is publicly available under https://doi.org/10.5281/zenodo.3754964 (McDuffie et al., 2020c).

Mcduffie, Erin↗
DOE OSTI2021

A measure of active interfaces in supported catalysts for high-temperature reactions

Formulating knowledge of structure-function relationships in heterogeneous catalysis is central to the design of efficient catalysts; yet, the elucidation of dominant reaction sites has remained as a challenge. Here, in this paper, we present a methodology that can be used to visualize metal-gas and metal-oxide-gas interfaces in three dimensions and to quantify their catalytic activity levels. As a case study, CH 4 oxidation occurring in a Pt/CeO 2 system is chosen. By employing thermally robust Pt@CeO 2 model catalysts with size-tunable and monodisperse cores, and gas-permeable shells, we reconstruct a series of structures in 3D via electron tomography and match the information to activity data and theoretical calculations. This strategy reveals that two different interfaces catalyze the CH 4 oxidation and that their contribution to the overall rate changes with the Pt size, temperature, and gas atmosphere. Our results provide an analytic platform on which to explore reaction pathways and mechanisms applicable to multiple reactions and materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Russian anthropogenic black carbon: Emission reconstruction and Arctic black carbon simulation

Development of reliable source emission inventories is needed to advance the understanding of the origin of Arctic haze using chemical transport modeling. This paper develops a regional anthropogenic black carbon (BC) emission inventory for the Russian Federation, the largest country by land area in the Arctic Council. Activity data from combination of local Russia information and international resources, emission factors based on either Russian documents or adjusted values for local conditions, and other emission source data are used to approximate the BC emissions. Emissions are gridded at a resolution of 0.1° × 0.1° and developed into a monthly temporal profile. Total anthropogenic BC emission of Russia in 2010 is estimated to be around 224 Gg. Gas flaring, a commonly ignored black carbon source, contributes a significant fraction of 36.2% to Russia's total anthropogenic BC emissions. Other sectors, i.e., residential, transportation, industry, and power plants, contribute 25.0%, 20.3%, 13.1%, and 5.4%, respectively. Three major BC hot spot regions are identified: the European part of Russia, the southern central part of Russia where human population densities are relatively high, and the Urals Federal District where Russia's major oil and gas fields are located but with sparse human population. BC simulations are conducted using the hemispheric version of Community Multi-scale Air Quality Model with emission inputs from a global emission database EDGAR (Emissions Database for Global Atmospheric Research)-HTAPv2 (Hemispheric Transport of Air Pollution) and EDGAR-HTAPv2 with its Russian part replaced by the newly developed Russian BC emissions, respectively. The simulation using the new Russian BC emission inventory could improve 30–65% of absorption aerosol optical depth measured at the AERONET sites in Russia throughout the whole year as compared to that using the default HTAPv2 emissions. At the four ground monitoring sites (Zeppelin, Barrow, Alert, and Tiksi) in the Arctic Circle, surface BC simulations are improved the most during the Arctic haze periods (October–March). The poor performance of Arctic BC simulations in previous studies may be partly ascribed to the Russian BC emissions built on out-of-date and/or missing information, which could result in biases to both emission rates and the spatial distribution of emissions. Finally, this study highlights that the impact of Russian emissions on the Arctic haze has likely been underestimated, and its role in the Arctic climate system needs to be reassessed. The Russian black carbon emission source data generated in this study can be obtained via http://abci.ornl.gov/download.shtml or http://acs.engr.utk.edu/Data.php.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

ADP‐Induced Ca 2+ Signaling and Proliferation of Rat Ventricular Myofibroblasts Depend on Phospholipase C‐Linked TRP Channels Activation Within Lipid Rafts

Nucleotides released during heart injury affect myocardium electrophysiology and remodeling through P2 purinoceptors activation in cardiac myofibroblasts. ATP and UTP endorse [Ca 2+ ] i accumulation and growth of DDR‐2/α‐SMA‐expressing myofibroblasts from adult rat ventricles via P2Y 4 and P2Y 2 receptors activation, respectively. Ventricular myofibroblasts also express ADP‐sensitive P2Y 1 , P2Y 12 , and P2Y 13 receptors as demonstrated by immunofluorescence confocal microscopy and western blot analysis, but little information exists on ADP effects in these cells. ADP (0.003–3 mM) and its stable analogue, ADPßS (100 μM), caused fast [Ca 2+ ] i transients originated from thapsigargin‐sensitive internal stores, which partially declined to a plateau sustained by capacitative Ca 2+ entry through transient receptor potential (TRP) channels inhibited by 2‐APB (50 μM) and flufenamic acid (100 μM). Hydrophobic interactions between G q/11 ‐coupled P2Y purinoceptors and TRP channels were suggested by prevention of the ADP‐induced [Ca 2+ ] i plateau following PIP 2 depletion with LiCl (10 mM) and cholesterol removal from lipid rafts with methyl‐ß‐cyclodextrin (2 mM). ADP [Ca 2+ ] i transients were insensitive to P2Y 1 , P2Y 12 , and P2Y 13 receptor antagonists, MRS2179 (10μM), AR‐C66096 (0.1 μM), and MRS2211 (10μM), respectively, but were attenuated by suramin and reactive blue‐2 (100 μM) which also blocked P2Y 4 receptors activation by UTP. Cardiac myofibroblasts growth and type I collagen production were favored upon activation of MRS2179‐sensitive P2Y 1 receptors with ADP or ADPßS (30 μM). In conclusion, ADP exerts a dual role on ventricular myofibroblasts: [Ca 2+ ] i transients are mediated by fast‐desensitizing P2Y 4 receptors, whereas the pro‐fibrotic effect of ADP involves the P2Y 1 receptor activation. Data also show that ADP‐induced capacitative Ca 2+ influx depends on phospholipase C‐linked TRP channels opening in lipid raft microdomains. J. Cell. Physiol. 232: 1511–1526, 2017. © 2016 Wiley Periodicals, Inc.

Certal, Mariana↗
DOE OSTI2020

Machine learning-based prediction of enzyme substrate scope: Application to bacterial nitrilases

Predicting the range of substrates accepted by an enzyme from its amino acid sequence is challenging. Although sequenc- and structure-based annotation approaches are often accurate for predicting broad categories of substrate specificity, they generally cannot predict which specific molecules will be accepted as substrates for a given enzyme, particularly within a class of closely related molecules. Combining targeted experimental activity data with structural modeling, ligand docking, and physicochemical properties of proteins and ligands with various machine learning models provides complementary information that can lead to accurate predictions of substrate scope for related enzymes. Here we describe such an approach that can predict the substrate scope of bacterial nitrilases, which catalyze the hydrolysis of nitrile compounds to the corresponding carboxylic acids and ammonia. Each of the four machine learning models (logistic regression, random forest, gradient-boosted decision trees, and support vector machines) performed similarly (average ROC = 0.9, average accuracy = ~82%) for predicting substrate scope for this dataset, although random forest offers some advantages. Finally, this approach is intended to be highly modular with respect to physicochemical property calculations and software used for structural modeling and docking.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Assessment of Myocarditis: Cardiac MR, PET/CT, or PET/MR?

Purpose of Review: Diagnosis of myocarditis is challenging given its variable clinical manifestations and non-specific laboratory findings. Cardiac magnetic resonance (MR) is currently the preferred imaging modality for the diagnosis of myocarditis. {sup 18}F-fluoro-deoxy-glucose (FDG) positron emission tomography/computed tomography (PET/CT), as a functional imaging tool, has a potential role in the assessment of myocarditis by detecting the underlying myocardial inflammatory activity. Data are accumulating that simultaneous cardiac PET/MR may have complementary and incremental values for the evaluation of myocarditis compared to PET/CT or cardiac MR alone. The article aims to summarize the findings in the literature and discuss future directions of cardiac PET/MR for myocarditis. Recent Findings: The Lake Louis Criteria (CLL) of cardiac MR is widely used for the diagnosis of myocarditis. It has an overall acceptable sensitivity of 67% and specificity of 91% for acute myocarditis but does not have the same accuracy for chronic myocarditis. FDG PET/CT is capable of assessing myocarditis by providing metabolic information of inflammation as increased myocardial FDG uptake. In addition to reduced radiation exposure, FDG PET performed on a hybrid PET/MR may detect more myocarditis than FDG PET/CT, because of the delayed PET acquisition time on PET/MR. Case-based observations and small clinical studies of FDG PET/MR have shown that FDG PET findings as abnormally increased myocardial uptake correlate well with the cardiac MR biomarkers. FDG PET findings may add complementary and incremental values to cardiac MR by improving the sensitivity of cardiac MR for mild or borderline myocarditis, and increasing specificity for chronic myocarditis. Summary: Preliminary data from retrospective and case-based observational studies have suggested the complementary and incremental values of simultaneous cardiac FDG PET/MR for evaluation of myocarditis, compared to PET/CT or MR alone. Well-designed studies are needed to confirm the findings and to assess the value of cardiac PET/MR for clinical management and more importantly patient’s outcome in both acute and chronic myocarditis.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2020

Effect of sodium loading on Pt/ZrO 2 during ethanol steam reforming

Ethanol steam reforming (ESR) was investigated on unpromoted and several sodium promoted Pt/ZrO 2 catalysts. From DRIFTS experiments, the following steps during ESR were inferred: dissociation of ethanol to produce ethoxy species; oxidative dehydrogenation of ethoxy species to acetate; and acetate decomposition. Acetate decomposition depends on the catalyst formulation. Decarboxylation is the most favored route at high sodium loading (2.5 and 5 wt.%); acetate decomposes in the forward direction to CH 4 and a carbonate, which further decomposes to CO 2 . In contrast, decarbonylation is prevalent for the unpromoted catalyst or catalysts having low sodium loading. Furthermore, acetate likely decomposes to CH 3 OH and CO. Adsorbed methanol may undergo further steam reforming by oxidative dehydrogenation to formate species, which decarbonylates via reverse decomposition to CO and H 2 O. Temperature programmed desorption/reaction and activity data confirmed that alkali promotion, especially at 1.8 %Na and higher loading, facilitates the forward acetate decomposition step, favoring decarboxylation over decarbonylation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Discovery and crystallography of bicyclic arylaminoazines as potent inhibitors of HIV-1 reverse transcriptase

Non-nucleoside inhibitors of HIV-1 reverse transcriptase (HIV-RT) are reported that incorporate a 7-indolizinylamino or 2-naphthylamino substituent on a pyrimidine or 1,3,5-triazine core. The most potent compounds show below 10 nanomolar activity towards wild-type HIV-1 and variants bearing Tyr181Cys and Lys103Asn/Tyr181Cys resistance mutations. As a result, the compounds also feature good aqueous solubility. Crystal structures for two complexes enhance the analysis of the structure–activity data.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Facile synthesis of efficient visible active C-doped TiO{sub 2} nanomaterials with high surface area for the simultaneous removal of phenol and Cr(VI)

Highlights: • Facile synthesis of C-doped TiO{sub 2} nanomaterials with high surface area. • Utilization of citric acid and ascorbic acid as fuels based on evolution of gases. • Enhanced visible activity for the oxidation of phenol and reduction of Cr(VI). • Study of simultaneous oxidation of phenol and reduction of Cr(VI) for the first time. • Proposed plausible mechanism for the simultaneous removal of phenol and Cr(VI). - Abstract: A single step synthesis of carbon doped TiO{sub 2} (anatase) nanomaterials have been reported by using combustion synthesis using ascorbic acid and citric acid fuels. X-ray diffraction studies indicated the formation of nanosized anatase titania, whereas, transmission electron microscopy confirmed the formation of nanosized TiO{sub 2} anatase. The carbon doping into TiO{sub 2} matrix was identified by X-ray photoelectron spectroscopy, whereas, thermogravimetric study quantified the carbon doping. Diffuse reflectance UV–vis spectra indicated the band gap of less than 3 eV, a prerequisite for the photocatalytic activity under visible light irradiation. The N{sub 2} adsorption studies revealed the high surface area (upto 290 m{sup 2}/g) of the synthesized photocatalysts. Typical photocatalytic activity data indicated that the simultaneous removal of Cr(VI) and phenol is advantageous than degradation of the individual pollutants.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Exploring Subsite Selectivity within Plasmodium vivax N -Myristoyltransferase Using Pyrazole-Derived Inhibitors

N-myristoyltransferase (NMT) is a promising antimalarial drug target. Despite biochemical similarities between Plasmodium vivax and human NMTs, our recent research demonstrated that high selectivity is achievable. Herein, we report PvNMT-inhibiting compounds aimed at identifying novel mechanisms of selectivity. Various functional groups are appended to a pyrazole moiety in the inhibitor to target a pocket formed beneath the peptide binding cleft. The inhibitor core group polarity, lipophilicity, and size are also varied to probe the water structure near a channel. Selectivity index values range from 0.8 to 125.3. Cocrystal structures of two selective compounds, determined at 1.97 and 2.43 Å, show that extensions bind the targeted pocket but with different stabilities. A bulky naphthalene moiety introduced into the core binds next to instead of displacing protein-bound waters, causing a shift in the inhibitor position and expanding the binding site. Our structure-activity data provide a conceptual foundation for guiding future inhibitor optimizations.

60 APPLIED LIFE SCIENCES↗